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stringlengths 40
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jsayles/Porthole | porthole/management/commands/brocade.py | a4176aad632e319eba88dfbe40cb96a4c437725d | from django.core.management.base import BaseCommand, CommandError
from django.conf import settings
from porthole import models, brocade
class Command(BaseCommand):
help = "Command the Brocade switch stacks"
args = ""
requires_system_checks = False
def add_arguments(self, parser):
parser.add_argument(
'--print_stacks',
action='store_true',
dest='print_stacks',
help='Show the VLAN data from all switch stacks',
)
def handle(self, *args, **options):
if options['print_stacks']:
self.print_stacks()
def print_stacks(self):
for s in models.SwitchStack.objects.all():
stack = brocade.SwitchStack(s.name, s.ip_address, s.raw_username, s.raw_password, port=s.port)
stack.print_stack()
print()
| [((653, 685), 'porthole.models.SwitchStack.objects.all', 'models.SwitchStack.objects.all', ([], {}), '()\n', (683, 685), False, 'from porthole import models, brocade\n'), ((707, 797), 'porthole.brocade.SwitchStack', 'brocade.SwitchStack', (['s.name', 's.ip_address', 's.raw_username', 's.raw_password'], {'port': 's.port'}), '(s.name, s.ip_address, s.raw_username, s.raw_password,\n port=s.port)\n', (726, 797), False, 'from porthole import models, brocade\n')] |
willjschmitt/joulia-webserver | joulia/unit_conversions_test.py | 712decb749c2d1bda71af49ecab245378bf30078 | """Tests joulia.unit_conversions.
"""
from django.test import TestCase
from joulia import unit_conversions
class GramsToPoundsTest(TestCase):
def test_grams_to_pounds(self):
self.assertEquals(unit_conversions.grams_to_pounds(1000.0), 2.20462)
class GramsToOuncesTest(TestCase):
def test_grams_to_ounces(self):
self.assertEquals(unit_conversions.grams_to_ounces(1000.0), 35.27392)
| [((208, 248), 'joulia.unit_conversions.grams_to_pounds', 'unit_conversions.grams_to_pounds', (['(1000.0)'], {}), '(1000.0)\n', (240, 248), False, 'from joulia import unit_conversions\n'), ((358, 398), 'joulia.unit_conversions.grams_to_ounces', 'unit_conversions.grams_to_ounces', (['(1000.0)'], {}), '(1000.0)\n', (390, 398), False, 'from joulia import unit_conversions\n')] |
zarif007/Blog-site | Django/blog/tests.py | e20e3f73fedbd7acb2f3d22398c36f3dcd4f88b4 | from django.contrib.auth.models import User
from django.test import TestCase
from blog.models import Category, Post
class Test_Create_Post(TestCase):
@classmethod
def setUpTestData(cls):
test_category = Category.objects.create(name='django')
testuser1 = User.objects.create_user(
username='test-123', password='testpass'
)
test_post = Post.objects.create(category_id=1, title='Post', excerpt='Excerpt',
content='Content', slug='Slug', author_id=1, status='published')
def test_blog_contenet(self):
post = Post.postobjects.get(id=1)
cat = Category.objects.get(id=1)
author = f'{post.author}'
excerpt = f'{post.excerpt}'
title = f'{post.title}'
content = f'{post.content}'
status = f'{post.status}'
self.assertEqual(author, 'test-123')
self.assertEqual(title, 'Post')
self.assertEqual(content, 'Content')
self.assertEqual(status, 'published')
self.assertEqual(str(post), 'Post')
self.assertEqual(str(cat), 'django') | [((223, 261), 'blog.models.Category.objects.create', 'Category.objects.create', ([], {'name': '"""django"""'}), "(name='django')\n", (246, 261), False, 'from blog.models import Category, Post\n'), ((282, 348), 'django.contrib.auth.models.User.objects.create_user', 'User.objects.create_user', ([], {'username': '"""test-123"""', 'password': '"""testpass"""'}), "(username='test-123', password='testpass')\n", (306, 348), False, 'from django.contrib.auth.models import User\n'), ((391, 528), 'blog.models.Post.objects.create', 'Post.objects.create', ([], {'category_id': '(1)', 'title': '"""Post"""', 'excerpt': '"""Excerpt"""', 'content': '"""Content"""', 'slug': '"""Slug"""', 'author_id': '(1)', 'status': '"""published"""'}), "(category_id=1, title='Post', excerpt='Excerpt', content\n ='Content', slug='Slug', author_id=1, status='published')\n", (410, 528), False, 'from blog.models import Category, Post\n'), ((623, 649), 'blog.models.Post.postobjects.get', 'Post.postobjects.get', ([], {'id': '(1)'}), '(id=1)\n', (643, 649), False, 'from blog.models import Category, Post\n'), ((664, 690), 'blog.models.Category.objects.get', 'Category.objects.get', ([], {'id': '(1)'}), '(id=1)\n', (684, 690), False, 'from blog.models import Category, Post\n')] |
kreshuklab/hylfm-net | scripts/train_presets/beads.py | 9f1013640e40e998674b65176023367b1e978782 | from pathlib import Path
from hylfm.hylfm_types import (
CriterionChoice,
DatasetChoice,
LRSchedThresMode,
LRSchedulerChoice,
MetricChoice,
OptimizerChoice,
PeriodUnit,
)
from hylfm.model import HyLFM_Net
from hylfm.train import train
if __name__ == "__main__":
train(
dataset=DatasetChoice.beads_highc_b,
batch_multiplier=2,
batch_size=1,
crit_apply_weight_above_threshold=False,
crit_beta=1.0,
crit_decay_weight_by=0.8,
crit_decay_weight_every_unit=PeriodUnit.epoch,
crit_decay_weight_every_value=1,
crit_decay_weight_limit=1.0,
crit_ms_ssim_weight=0.01,
crit_threshold=0.5,
crit_weight=0.001,
criterion=CriterionChoice.WeightedSmoothL1,
data_range=1.0,
eval_batch_size=1,
interpolation_order=2,
lr_sched_factor=0.5,
lr_sched_patience=10,
lr_sched_thres=0.0001,
lr_sched_thres_mode=LRSchedThresMode.abs,
lr_scheduler=LRSchedulerChoice.ReduceLROnPlateau,
max_epochs=10,
model_weights=None, # Path()
opt_lr=3e-4,
opt_momentum=0.0,
opt_weight_decay=0.0,
optimizer=OptimizerChoice.Adam,
patience=5,
score_metric=MetricChoice.MS_SSIM,
seed=None,
validate_every_unit=PeriodUnit.epoch,
validate_every_value=1,
win_sigma=1.5,
win_size=11,
# model
nnum=19,
z_out=51,
kernel2d=3,
c00_2d=976,
c01_2d=976,
c02_2d=0,
c03_2d=0,
c04_2d=0,
up0_2d=488,
c10_2d=488,
c11_2d=0,
c12_2d=0,
c13_2d=0,
c14_2d=0,
up1_2d=244,
c20_2d=244,
c21_2d=0,
c22_2d=0,
c23_2d=0,
c24_2d=0,
up2_2d=0,
c30_2d=0,
c31_2d=0,
c32_2d=0,
c33_2d=0,
c34_2d=0,
last_kernel2d=1,
cin_3d=7,
kernel3d=3,
c00_3d=7,
c01_3d=0,
c02_3d=0,
c03_3d=0,
c04_3d=0,
up0_3d=7,
c10_3d=7,
c11_3d=7,
c12_3d=0,
c13_3d=0,
c14_3d=0,
up1_3d=0,
c20_3d=0,
c21_3d=0,
c22_3d=0,
c23_3d=0,
c24_3d=0,
up2_3d=0,
c30_3d=0,
c31_3d=0,
c32_3d=0,
c33_3d=0,
c34_3d=0,
init_fn=HyLFM_Net.InitName.xavier_uniform_,
final_activation=None,
)
| [((297, 1857), 'hylfm.train.train', 'train', ([], {'dataset': 'DatasetChoice.beads_highc_b', 'batch_multiplier': '(2)', 'batch_size': '(1)', 'crit_apply_weight_above_threshold': '(False)', 'crit_beta': '(1.0)', 'crit_decay_weight_by': '(0.8)', 'crit_decay_weight_every_unit': 'PeriodUnit.epoch', 'crit_decay_weight_every_value': '(1)', 'crit_decay_weight_limit': '(1.0)', 'crit_ms_ssim_weight': '(0.01)', 'crit_threshold': '(0.5)', 'crit_weight': '(0.001)', 'criterion': 'CriterionChoice.WeightedSmoothL1', 'data_range': '(1.0)', 'eval_batch_size': '(1)', 'interpolation_order': '(2)', 'lr_sched_factor': '(0.5)', 'lr_sched_patience': '(10)', 'lr_sched_thres': '(0.0001)', 'lr_sched_thres_mode': 'LRSchedThresMode.abs', 'lr_scheduler': 'LRSchedulerChoice.ReduceLROnPlateau', 'max_epochs': '(10)', 'model_weights': 'None', 'opt_lr': '(0.0003)', 'opt_momentum': '(0.0)', 'opt_weight_decay': '(0.0)', 'optimizer': 'OptimizerChoice.Adam', 'patience': '(5)', 'score_metric': 'MetricChoice.MS_SSIM', 'seed': 'None', 'validate_every_unit': 'PeriodUnit.epoch', 'validate_every_value': '(1)', 'win_sigma': '(1.5)', 'win_size': '(11)', 'nnum': '(19)', 'z_out': '(51)', 'kernel2d': '(3)', 'c00_2d': '(976)', 'c01_2d': '(976)', 'c02_2d': '(0)', 'c03_2d': '(0)', 'c04_2d': '(0)', 'up0_2d': '(488)', 'c10_2d': '(488)', 'c11_2d': '(0)', 'c12_2d': '(0)', 'c13_2d': '(0)', 'c14_2d': '(0)', 'up1_2d': '(244)', 'c20_2d': '(244)', 'c21_2d': '(0)', 'c22_2d': '(0)', 'c23_2d': '(0)', 'c24_2d': '(0)', 'up2_2d': '(0)', 'c30_2d': '(0)', 'c31_2d': '(0)', 'c32_2d': '(0)', 'c33_2d': '(0)', 'c34_2d': '(0)', 'last_kernel2d': '(1)', 'cin_3d': '(7)', 'kernel3d': '(3)', 'c00_3d': '(7)', 'c01_3d': '(0)', 'c02_3d': '(0)', 'c03_3d': '(0)', 'c04_3d': '(0)', 'up0_3d': '(7)', 'c10_3d': '(7)', 'c11_3d': '(7)', 'c12_3d': '(0)', 'c13_3d': '(0)', 'c14_3d': '(0)', 'up1_3d': '(0)', 'c20_3d': '(0)', 'c21_3d': '(0)', 'c22_3d': '(0)', 'c23_3d': '(0)', 'c24_3d': '(0)', 'up2_3d': '(0)', 'c30_3d': '(0)', 'c31_3d': '(0)', 'c32_3d': '(0)', 'c33_3d': '(0)', 'c34_3d': '(0)', 'init_fn': 'HyLFM_Net.InitName.xavier_uniform_', 'final_activation': 'None'}), '(dataset=DatasetChoice.beads_highc_b, batch_multiplier=2, batch_size=1,\n crit_apply_weight_above_threshold=False, crit_beta=1.0,\n crit_decay_weight_by=0.8, crit_decay_weight_every_unit=PeriodUnit.epoch,\n crit_decay_weight_every_value=1, crit_decay_weight_limit=1.0,\n crit_ms_ssim_weight=0.01, crit_threshold=0.5, crit_weight=0.001,\n criterion=CriterionChoice.WeightedSmoothL1, data_range=1.0,\n eval_batch_size=1, interpolation_order=2, lr_sched_factor=0.5,\n lr_sched_patience=10, lr_sched_thres=0.0001, lr_sched_thres_mode=\n LRSchedThresMode.abs, lr_scheduler=LRSchedulerChoice.ReduceLROnPlateau,\n max_epochs=10, model_weights=None, opt_lr=0.0003, opt_momentum=0.0,\n opt_weight_decay=0.0, optimizer=OptimizerChoice.Adam, patience=5,\n score_metric=MetricChoice.MS_SSIM, seed=None, validate_every_unit=\n PeriodUnit.epoch, validate_every_value=1, win_sigma=1.5, win_size=11,\n nnum=19, z_out=51, kernel2d=3, c00_2d=976, c01_2d=976, c02_2d=0, c03_2d\n =0, c04_2d=0, up0_2d=488, c10_2d=488, c11_2d=0, c12_2d=0, c13_2d=0,\n c14_2d=0, up1_2d=244, c20_2d=244, c21_2d=0, c22_2d=0, c23_2d=0, c24_2d=\n 0, up2_2d=0, c30_2d=0, c31_2d=0, c32_2d=0, c33_2d=0, c34_2d=0,\n last_kernel2d=1, cin_3d=7, kernel3d=3, c00_3d=7, c01_3d=0, c02_3d=0,\n c03_3d=0, c04_3d=0, up0_3d=7, c10_3d=7, c11_3d=7, c12_3d=0, c13_3d=0,\n c14_3d=0, up1_3d=0, c20_3d=0, c21_3d=0, c22_3d=0, c23_3d=0, c24_3d=0,\n up2_3d=0, c30_3d=0, c31_3d=0, c32_3d=0, c33_3d=0, c34_3d=0, init_fn=\n HyLFM_Net.InitName.xavier_uniform_, final_activation=None)\n', (302, 1857), False, 'from hylfm.train import train\n')] |
CsekM8/LVH-THESIS | TrainingPreprocess/filtered_to_dataset.py | b0dc60daaf0825ad43951e6895289da4e3ed911b | import os
import pickle
from PIL import Image
class PatientToImageFolder:
def __init__(self, sourceFolder):
self.sourceFolder = sourceFolder
# How many patient with contrast SA for each pathology (used for classification)
self.contrastSApathologyDict = {}
# How many patient with contrast LA for each pathology (used for classification)
self.contrastCH2pathologyDict = {}
self.contrastCH3pathologyDict = {}
self.contrastCH4pathologyDict = {}
# How many patient with SA image (used for autoencoder training)
self.totalSaImagePatientNum = 0
self.curSaImagePatientNum = 0
# How many patient with LA image (used for autoencoder training)
self.totalCH2ImagePatientNum = 0
self.curCH2ImagePatientNum = 0
self.totalCH3ImagePatientNum = 0
self.curCH3ImagePatientNum = 0
self.totalCH4ImagePatientNum = 0
self.curCH4ImagePatientNum = 0
self.curContrastSaImagePatientNum = {}
self.curContrastCH2ImagePatientNum = {}
self.curContrastCH3ImagePatientNum = {}
self.curContrastCH4ImagePatientNum = {}
self.collectInfo()
def collectInfo(self):
for file in os.listdir(self.sourceFolder):
if ".p" in file:
tmpPat = pickle.load(open(os.path.join(self.sourceFolder, file), 'rb'))
patho = tmpPat.pathology.strip()
if "U18" in patho or "sport" in patho or "Normal" in patho:
continue
# elif "sport" in patho:
# patho = "Sport"
# elif "Normal" not in patho and "HCM" not in patho:
# patho = "Other"
if tmpPat.normalSaImages is not None:
self.totalSaImagePatientNum += 1
if (tmpPat.contrastSaImages is not None and tmpPat.contrastLaImages.ch2Images is not None and
tmpPat.contrastLaImages.ch3Images is not None and tmpPat.contrastLaImages.ch4Images is not None):
if patho in self.contrastSApathologyDict:
self.contrastSApathologyDict[patho] += 1
else:
self.contrastSApathologyDict[patho] = 1
if patho in self.contrastCH2pathologyDict:
self.contrastCH2pathologyDict[patho] += 1
else:
self.contrastCH2pathologyDict[patho] = 1
if patho in self.contrastCH3pathologyDict:
self.contrastCH3pathologyDict[patho] += 1
else:
self.contrastCH3pathologyDict[patho] = 1
if patho in self.contrastCH4pathologyDict:
self.contrastCH4pathologyDict[patho] += 1
else:
self.contrastCH4pathologyDict[patho] = 1
if tmpPat.normalLaImages.ch2Images is not None:
self.totalCH2ImagePatientNum += 1
if tmpPat.normalLaImages.ch3Images is not None:
self.totalCH3ImagePatientNum += 1
if tmpPat.normalLaImages.ch4Images is not None:
self.totalCH4ImagePatientNum += 1
for key in self.contrastSApathologyDict:
self.curContrastSaImagePatientNum[key] = 0
for key in self.contrastCH2pathologyDict:
self.curContrastCH2ImagePatientNum[key] = 0
for key in self.contrastCH3pathologyDict:
self.curContrastCH3ImagePatientNum[key] = 0
for key in self.contrastCH4pathologyDict:
self.curContrastCH4ImagePatientNum[key] = 0
def convertImage(self, image_2d):
# if image_2d.min() > 254:
# return None
# Converting image from numpy array to PIL.
pil_img = Image.fromarray(image_2d)
if pil_img.getbbox() is None:
return None
return pil_img
def createAutoEncoderImageFolderStructure(self, folderName):
autoFolder = os.path.join(os.path.dirname(self.sourceFolder), folderName)
autoTrainingFolder = os.path.join(autoFolder, "training")
autoTestFolder = os.path.join(autoFolder, "test")
os.makedirs(autoTrainingFolder)
os.makedirs(autoTestFolder)
return autoFolder, autoTrainingFolder, autoTestFolder
def createClassificationImageFolderStructure(self, folderName):
classFolder = os.path.join(os.path.dirname(self.sourceFolder), folderName)
classTrainingFolder = os.path.join(classFolder, "training")
classValidationFolder = os.path.join(classFolder, "validation")
classTestFolder = os.path.join(classFolder, "test")
classAllFolder = os.path.join(classFolder, 'all')
os.makedirs(classTrainingFolder)
os.makedirs(classValidationFolder)
os.makedirs(classTestFolder)
os.makedirs(classAllFolder)
return classFolder, classTrainingFolder, classValidationFolder, classTestFolder, classAllFolder
def saveImageForClassification(self, image, patientId, patho, testFolder, validationFolder, trainingFolder,
axis, imPatho, curPatientNum, allFolder, pathologyDict):
pil_img = self.convertImage(image[:, :])
if pil_img is not None:
if (curPatientNum[patho] <= pathologyDict[patho] * 0.075 or
(pathologyDict[patho] * 0.85 <= curPatientNum[patho] <= pathologyDict[patho] * 0.925)):
imFolder = os.path.join(testFolder, imPatho)
os.makedirs(imFolder, exist_ok=True)
patientFolder = os.path.join(self.patientSeperatedTestFolder, imPatho + '_' + patientId)
os.makedirs(patientFolder, exist_ok=True)
elif ((pathologyDict[patho] * 0.075 <= curPatientNum[patho] <= pathologyDict[patho] * 0.15) or
curPatientNum[patho] >= int(pathologyDict[patho] * 0.925)):
imFolder = os.path.join(validationFolder, imPatho)
os.makedirs(imFolder, exist_ok=True)
patientFolder = os.path.join(self.patientSeperatedValidationFolder, imPatho + '_' + patientId)
os.makedirs(patientFolder, exist_ok=True)
else:
imFolder = os.path.join(trainingFolder, imPatho)
os.makedirs(imFolder, exist_ok=True)
patientFolder = os.path.join(self.patientSeperatedTrainingFolder, imPatho + '_' + patientId)
os.makedirs(patientFolder, exist_ok=True)
axisFolder = os.path.join(patientFolder, axis)
os.makedirs(axisFolder, exist_ok=True)
pil_img.save(os.path.join(imFolder, "{}.png".format(patientId)))
# pil_img.save(os.path.join(allFolder, "{}.png".format(patientId)))
pil_img.save(os.path.join(axisFolder, "{}.png".format(patientId)))
file = open(os.path.join(patientFolder, "pathology.txt"), "w")
file.write("{}\n".format(patho))
file.close()
def saveImageForAutoEncoder(self, images, patientId, testFolder, trainingFolder,
curPatientNum, totalPatientNum, sliceIdx, frameIdx):
if sliceIdx is not None:
pil_img = self.convertImage(images[sliceIdx, frameIdx, :, :])
else:
pil_img = self.convertImage(images[frameIdx, :, :])
if pil_img is not None:
if (curPatientNum <= totalPatientNum * 0.1
or curPatientNum >= int(totalPatientNum * 0.9)):
if sliceIdx is not None:
pil_img.save(os.path.join(testFolder, "{}_{}_{}.png".format(patientId, sliceIdx, frameIdx)))
else:
pil_img.save(os.path.join(testFolder, "{}_{}.png".format(patientId, frameIdx)))
else:
if sliceIdx is not None:
pil_img.save(os.path.join(trainingFolder, "{}_{}_{}.png".format(patientId, sliceIdx, frameIdx)))
else:
pil_img.save(os.path.join(trainingFolder, "{}_{}.png".format(patientId, frameIdx)))
def createImageFolderDatasets(self):
subfol = "only_abnormal"
# autoSaFolder, autoSaTrainingFolder, autoSaTestFolder = self.createAutoEncoderImageFolderStructure(
# "SaAutoEncoder")
(contrastSaFolder, contrastSaTrainingFolder,
contrastSaValidationFolder, contrastSaTestFolder,
contrastSaAllFolder) = self.createClassificationImageFolderStructure(
"{}/SaClassification".format(subfol))
# autoCH2Folder, autoCH2TrainingFolder, autoCH2TestFolder = self.createAutoEncoderImageFolderStructure(
# "CH2AutoEncoder")
(contrastCH2Folder, contrastCH2TrainingFolder,
contrastCH2ValidationFolder, contrastCH2TestFolder,
contrastCH2AllFolder) = self.createClassificationImageFolderStructure(
"{}/CH2Classification".format(subfol))
# autoCH3Folder, autoCH3TrainingFolder, autoCH3TestFolder = self.createAutoEncoderImageFolderStructure(
# "CH3AutoEncoder")
(contrastCH3Folder, contrastCH3TrainingFolder,
contrastCH3ValidationFolder, contrastCH3TestFolder,
contrastCH3AllFolder) = self.createClassificationImageFolderStructure(
"{}/CH3Classification".format(subfol))
# autoCH4Folder, autoCH4TrainingFolder, autoCH4TestFolder = self.createAutoEncoderImageFolderStructure(
# "CH4AutoEncoder")
(contrastCH4Folder, contrastCH4TrainingFolder,
contrastCH4ValidationFolder, contrastCH4TestFolder,
contrastCH4AllFolder) = self.createClassificationImageFolderStructure(
"{}/CH4Classification".format(subfol))
self.patientSeperatedFolder = os.path.join(os.path.dirname(self.sourceFolder), '{}/patients'.format(subfol))
os.makedirs(self.patientSeperatedFolder)
self.patientSeperatedTrainingFolder = os.path.join(self.patientSeperatedFolder, 'training')
self.patientSeperatedValidationFolder = os.path.join(self.patientSeperatedFolder, 'validation')
self.patientSeperatedTestFolder = os.path.join(self.patientSeperatedFolder, 'test')
os.makedirs(self.patientSeperatedTrainingFolder)
os.makedirs(self.patientSeperatedValidationFolder)
os.makedirs(self.patientSeperatedTestFolder)
for file in os.listdir(self.sourceFolder):
if ".p" in file:
tmpPat = pickle.load(open(os.path.join(self.sourceFolder, file), 'rb'))
patho = tmpPat.pathology.strip()
if "U18" in patho or "sport" in patho or "Normal" in patho:
continue
# elif "sport" in patho:
# patho = "Sport"
# elif "Normal" not in patho and "HCM" not in patho:
# patho = "Other"
imPatho = patho
# if "sport" in patho:
# imPatho = "Sport"
# if "Normal" not in patho:
# imPatho = "Hypertrophic"
classificationReady = False
if (tmpPat.contrastSaImages is not None and tmpPat.contrastLaImages.ch2Images is not None and
tmpPat.contrastLaImages.ch3Images is not None and tmpPat.contrastLaImages.ch4Images is not None):
classificationReady = True
# if tmpPat.normalSaImages is not None:
# for i in range(tmpPat.normalSaImages.shape[0]):
# for j in range(tmpPat.normalSaImages.shape[1]):
# self.saveImageForAutoEncoder(tmpPat.normalSaImages, tmpPat.patientID, autoSaTestFolder,
# autoSaTrainingFolder, self.curSaImagePatientNum,
# self.totalSaImagePatientNum, i, j)
# self.curSaImagePatientNum += 1
if classificationReady:
self.saveImageForClassification(tmpPat.contrastSaImages, tmpPat.patientID, patho,
contrastSaTestFolder, contrastSaValidationFolder,
contrastSaTrainingFolder, 'SA', imPatho,
self.curContrastSaImagePatientNum, contrastSaAllFolder,
self.contrastSApathologyDict)
self.curContrastSaImagePatientNum[patho] += 1
# if tmpPat.normalLaImages.ch2Images is not None:
# for i in range(tmpPat.normalLaImages.ch2Images.shape[0]):
# self.saveImageForAutoEncoder(tmpPat.normalLaImages.ch2Images, tmpPat.patientID,
# autoCH2TestFolder,
# autoCH2TrainingFolder, self.curCH2ImagePatientNum,
# self.totalCH2ImagePatientNum, None, i)
# self.curCH2ImagePatientNum += 1
if classificationReady:
self.saveImageForClassification(tmpPat.contrastLaImages.ch2Images, tmpPat.patientID, patho,
contrastCH2TestFolder, contrastCH2ValidationFolder,
contrastCH2TrainingFolder, 'CH2', imPatho,
self.curContrastCH2ImagePatientNum, contrastCH2AllFolder,
self.contrastCH2pathologyDict)
self.curContrastCH2ImagePatientNum[patho] += 1
# if tmpPat.normalLaImages.ch3Images is not None:
# for i in range(tmpPat.normalLaImages.ch3Images.shape[0]):
# self.saveImageForAutoEncoder(tmpPat.normalLaImages.ch3Images, tmpPat.patientID,
# autoCH3TestFolder,
# autoCH3TrainingFolder, self.curCH3ImagePatientNum,
# self.totalCH3ImagePatientNum, None, i)
# self.curCH3ImagePatientNum += 1
if classificationReady:
self.saveImageForClassification(tmpPat.contrastLaImages.ch3Images, tmpPat.patientID, patho,
contrastCH3TestFolder, contrastCH3ValidationFolder,
contrastCH3TrainingFolder, 'CH3', imPatho,
self.curContrastCH3ImagePatientNum, contrastCH3AllFolder,
self.contrastCH3pathologyDict)
self.curContrastCH3ImagePatientNum[patho] += 1
# if tmpPat.normalLaImages.ch4Images is not None:
# for i in range(tmpPat.normalLaImages.ch4Images.shape[0]):
# self.saveImageForAutoEncoder(tmpPat.normalLaImages.ch4Images, tmpPat.patientID,
# autoCH4TestFolder,
# autoCH4TrainingFolder, self.curCH4ImagePatientNum,
# self.totalCH4ImagePatientNum, None, i)
# self.curCH4ImagePatientNum += 1
if classificationReady:
self.saveImageForClassification(tmpPat.contrastLaImages.ch4Images, tmpPat.patientID, patho,
contrastCH4TestFolder, contrastCH4ValidationFolder,
contrastCH4TrainingFolder, 'CH4', imPatho,
self.curContrastCH4ImagePatientNum, contrastCH4AllFolder,
self.contrastCH4pathologyDict)
self.curContrastCH4ImagePatientNum[patho] += 1
self.createLabelFileFromPathoDict(contrastSaFolder, self.contrastSApathologyDict)
self.createLabelFileFromPathoDict(contrastCH2Folder, self.contrastCH2pathologyDict)
self.createLabelFileFromPathoDict(contrastCH3Folder, self.contrastCH3pathologyDict)
self.createLabelFileFromPathoDict(contrastCH4Folder, self.contrastCH4pathologyDict)
def createLabelFileFromPathoDict(self, destination, pathoDict):
file = open(os.path.join(destination, "pathologies.txt"), "w")
for key in pathoDict:
file.write("{}\n".format(key))
file.close()
if __name__ == "__main__":
sourceFolder = 'D:/BME/7felev/Szakdolgozat/whole_dataset/filtered_data'
imageFolderArranger = PatientToImageFolder(sourceFolder)
imageFolderArranger.createImageFolderDatasets()
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os\n'), ((4663, 4702), 'os.path.join', 'os.path.join', (['classFolder', '"""validation"""'], {}), "(classFolder, 'validation')\n", (4675, 4702), False, 'import os\n'), ((4729, 4762), 'os.path.join', 'os.path.join', (['classFolder', '"""test"""'], {}), "(classFolder, 'test')\n", (4741, 4762), False, 'import os\n'), ((4788, 4820), 'os.path.join', 'os.path.join', (['classFolder', '"""all"""'], {}), "(classFolder, 'all')\n", (4800, 4820), False, 'import os\n'), ((4830, 4862), 'os.makedirs', 'os.makedirs', (['classTrainingFolder'], {}), '(classTrainingFolder)\n', (4841, 4862), False, 'import os\n'), ((4871, 4905), 'os.makedirs', 'os.makedirs', (['classValidationFolder'], {}), '(classValidationFolder)\n', (4882, 4905), False, 'import os\n'), ((4914, 4942), 'os.makedirs', 'os.makedirs', (['classTestFolder'], {}), '(classTestFolder)\n', (4925, 4942), False, 'import os\n'), ((4951, 4978), 'os.makedirs', 'os.makedirs', (['classAllFolder'], {}), '(classAllFolder)\n', (4962, 4978), False, 'import os\n'), ((9947, 9987), 'os.makedirs', 'os.makedirs', (['self.patientSeperatedFolder'], {}), '(self.patientSeperatedFolder)\n', (9958, 9987), False, 'import os\n'), ((10034, 10087), 'os.path.join', 'os.path.join', (['self.patientSeperatedFolder', '"""training"""'], {}), "(self.patientSeperatedFolder, 'training')\n", (10046, 10087), False, 'import os\n'), ((10136, 10191), 'os.path.join', 'os.path.join', (['self.patientSeperatedFolder', '"""validation"""'], {}), "(self.patientSeperatedFolder, 'validation')\n", (10148, 10191), False, 'import os\n'), ((10234, 10283), 'os.path.join', 'os.path.join', (['self.patientSeperatedFolder', '"""test"""'], {}), "(self.patientSeperatedFolder, 'test')\n", (10246, 10283), False, 'import os\n'), ((10292, 10340), 'os.makedirs', 'os.makedirs', (['self.patientSeperatedTrainingFolder'], {}), '(self.patientSeperatedTrainingFolder)\n', (10303, 10340), False, 'import os\n'), ((10349, 10399), 'os.makedirs', 'os.makedirs', (['self.patientSeperatedValidationFolder'], {}), '(self.patientSeperatedValidationFolder)\n', (10360, 10399), False, 'import os\n'), ((10408, 10452), 'os.makedirs', 'os.makedirs', (['self.patientSeperatedTestFolder'], {}), '(self.patientSeperatedTestFolder)\n', (10419, 10452), False, 'import os\n'), ((10474, 10503), 'os.listdir', 'os.listdir', (['self.sourceFolder'], {}), '(self.sourceFolder)\n', (10484, 10503), False, 'import os\n'), ((4099, 4133), 'os.path.dirname', 'os.path.dirname', (['self.sourceFolder'], {}), '(self.sourceFolder)\n', (4114, 4133), False, 'import os\n'), ((4515, 4549), 'os.path.dirname', 'os.path.dirname', (['self.sourceFolder'], {}), '(self.sourceFolder)\n', (4530, 4549), False, 'import os\n'), ((6629, 6662), 'os.path.join', 'os.path.join', (['patientFolder', 'axis'], {}), '(patientFolder, axis)\n', (6641, 6662), False, 'import os\n'), ((6675, 6713), 'os.makedirs', 'os.makedirs', (['axisFolder'], {'exist_ok': '(True)'}), '(axisFolder, exist_ok=True)\n', (6686, 6713), False, 'import os\n'), ((9873, 9907), 'os.path.dirname', 'os.path.dirname', (['self.sourceFolder'], {}), '(self.sourceFolder)\n', (9888, 9907), False, 'import os\n'), ((16692, 16736), 'os.path.join', 'os.path.join', (['destination', '"""pathologies.txt"""'], {}), "(destination, 'pathologies.txt')\n", (16704, 16736), False, 'import os\n'), ((5577, 5610), 'os.path.join', 'os.path.join', (['testFolder', 'imPatho'], {}), '(testFolder, imPatho)\n', (5589, 5610), False, 'import os\n'), ((5627, 5663), 'os.makedirs', 'os.makedirs', (['imFolder'], {'exist_ok': '(True)'}), '(imFolder, exist_ok=True)\n', (5638, 5663), False, 'import os\n'), ((5696, 5768), 'os.path.join', 'os.path.join', (['self.patientSeperatedTestFolder', "(imPatho + '_' + patientId)"], {}), "(self.patientSeperatedTestFolder, imPatho + '_' + patientId)\n", (5708, 5768), False, 'import os\n'), ((5785, 5826), 'os.makedirs', 'os.makedirs', (['patientFolder'], {'exist_ok': '(True)'}), '(patientFolder, exist_ok=True)\n', (5796, 5826), False, 'import os\n'), ((6974, 7018), 'os.path.join', 'os.path.join', (['patientFolder', '"""pathology.txt"""'], {}), "(patientFolder, 'pathology.txt')\n", (6986, 7018), False, 'import os\n'), ((6039, 6078), 'os.path.join', 'os.path.join', (['validationFolder', 'imPatho'], {}), '(validationFolder, imPatho)\n', (6051, 6078), False, 'import os\n'), ((6095, 6131), 'os.makedirs', 'os.makedirs', (['imFolder'], {'exist_ok': '(True)'}), '(imFolder, exist_ok=True)\n', (6106, 6131), False, 'import os\n'), ((6164, 6242), 'os.path.join', 'os.path.join', (['self.patientSeperatedValidationFolder', "(imPatho + '_' + patientId)"], {}), "(self.patientSeperatedValidationFolder, imPatho + '_' + patientId)\n", (6176, 6242), False, 'import os\n'), ((6259, 6300), 'os.makedirs', 'os.makedirs', (['patientFolder'], {'exist_ok': '(True)'}), '(patientFolder, exist_ok=True)\n', (6270, 6300), False, 'import os\n'), ((6346, 6383), 'os.path.join', 'os.path.join', (['trainingFolder', 'imPatho'], {}), '(trainingFolder, imPatho)\n', (6358, 6383), False, 'import os\n'), ((6400, 6436), 'os.makedirs', 'os.makedirs', (['imFolder'], {'exist_ok': '(True)'}), '(imFolder, exist_ok=True)\n', (6411, 6436), False, 'import os\n'), ((6469, 6545), 'os.path.join', 'os.path.join', (['self.patientSeperatedTrainingFolder', "(imPatho + '_' + patientId)"], {}), "(self.patientSeperatedTrainingFolder, imPatho + '_' + patientId)\n", (6481, 6545), False, 'import os\n'), ((6562, 6603), 'os.makedirs', 'os.makedirs', (['patientFolder'], {'exist_ok': '(True)'}), '(patientFolder, exist_ok=True)\n', (6573, 6603), False, 'import os\n'), ((1339, 1376), 'os.path.join', 'os.path.join', (['self.sourceFolder', 'file'], {}), '(self.sourceFolder, file)\n', (1351, 1376), False, 'import os\n'), ((10576, 10613), 'os.path.join', 'os.path.join', (['self.sourceFolder', 'file'], {}), '(self.sourceFolder, file)\n', (10588, 10613), False, 'import os\n')] |
Iolaum/Phi1337 | scripts/pipeline/a06a_submission.py | c73b01cb85c0187ed5c23c672d4f3d05a6934a9f | import pandas as pd
import numpy as np
import pickle
from sklearn.cross_validation import train_test_split
from sklearn.linear_model import LinearRegression
from sklearn.metrics import mean_squared_error
from math import sqrt
from sklearn.svm import SVR
from sklearn.svm import LinearSVR
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import RandomForestRegressor
def prune(x):
if x < 1:
return 1
elif x > 3:
return 3
else:
return x
def regression(reg_type, standardize_df, debug=False):
# load model
filename = '../../dataset/model_' + reg_type + '.pickle'
lin_model = None
with open(filename, 'rb') as f:
lin_model = pickle.load(f)
score_df_tst = pd.read_pickle('../../dataset/score_df_final_tst.pickle')
# Fill NaN value
# score_df = score_df.fillna(0.0)
# The last column is the target
X = np.array(score_df_tst)
if standardize_df:
print("Standardizing...")
with open("../../dataset/scaler.pickle", 'rb') as handle:
scaler = pickle.load(handle)
X = scaler.transform(X)
# Debug
if debug:
print("Score DataFrame")
print(score_df)
print("")
print("Training Values")
print(X)
print("")
print("Output Values")
print(Y)
print("")
print("Shapes of X and Y")
print(X.shape)
print(Y.shape)
# Debug
if debug:
print("XTR - XTS")
print(xtr.shape)
print(xts.shape)
print("")
print("YTR - YTS")
print(ytr.shape)
print(yts.shape)
print("")
yts_pred = lin_model.predict(X)
#yts_error = sqrt(mean_squared_error(yts_pred, yts))
print("Prediction by (" + reg_type + ") on Test data have finished")
# create submission file
id_series = pd.read_csv('../../dataset/test.csv')['id']
submission_df = pd.DataFrame(id_series, columns=['id'])
submission_df['relevance'] = yts_pred
submission_df['relevance'] = submission_df['relevance'].map(lambda x: prune(x))
submission_df.to_csv('../../dataset/submission.csv', columns=['id', 'relevance'], index=False)
if __name__ == "__main__":
# Change between:
# svr
# linear
# rfr
regression_type = 'svr'
standardize_df = True
regression(regression_type, standardize_df, debug=False) | [((697, 754), 'pandas.read_pickle', 'pd.read_pickle', (['"""../../dataset/score_df_final_tst.pickle"""'], {}), "('../../dataset/score_df_final_tst.pickle')\n", (711, 754), True, 'import pandas as pd\n'), ((848, 870), 'numpy.array', 'np.array', (['score_df_tst'], {}), '(score_df_tst)\n', (856, 870), True, 'import numpy as np\n'), ((1706, 1745), 'pandas.DataFrame', 'pd.DataFrame', (['id_series'], {'columns': "['id']"}), "(id_series, columns=['id'])\n", (1718, 1745), True, 'import pandas as pd\n'), ((665, 679), 'pickle.load', 'pickle.load', (['f'], {}), '(f)\n', (676, 679), False, 'import pickle\n'), ((1645, 1682), 'pandas.read_csv', 'pd.read_csv', (['"""../../dataset/test.csv"""'], {}), "('../../dataset/test.csv')\n", (1656, 1682), True, 'import pandas as pd\n'), ((992, 1011), 'pickle.load', 'pickle.load', (['handle'], {}), '(handle)\n', (1003, 1011), False, 'import pickle\n')] |
Carter-eng/SeniorDesign | Data Gathering/PythonPlottingScript.py | 5305531d251ea749f909cc09eb1ccfe21714cebd | import numpy as np
import serial
import time
import matplotlib.pyplot as plt
def getData():
ser = serial.Serial('/dev/ttyACM7', 9600)
sensorReadings = []
start = time.time()
current = time.time()
while current - start < 10:
data =ser.readline()
sensorReadings.append(float(data))
current = time.time()
return sensorReadings
def plotter(sensorReadings):
plt.plot(sensorReadings)
plt.ylabel('EEG Sensor sensorReadings')
plt.show()
if __name__ == '__main__':
sensorReadings = getData()
plotter(sensorReadings)
| [((109, 144), 'serial.Serial', 'serial.Serial', (['"""/dev/ttyACM7"""', '(9600)'], {}), "('/dev/ttyACM7', 9600)\n", (122, 144), False, 'import serial\n'), ((183, 194), 'time.time', 'time.time', ([], {}), '()\n', (192, 194), False, 'import time\n'), ((210, 221), 'time.time', 'time.time', ([], {}), '()\n', (219, 221), False, 'import time\n'), ((424, 448), 'matplotlib.pyplot.plot', 'plt.plot', (['sensorReadings'], {}), '(sensorReadings)\n', (432, 448), True, 'import matplotlib.pyplot as plt\n'), ((454, 493), 'matplotlib.pyplot.ylabel', 'plt.ylabel', (['"""EEG Sensor sensorReadings"""'], {}), "('EEG Sensor sensorReadings')\n", (464, 493), True, 'import matplotlib.pyplot as plt\n'), ((499, 509), 'matplotlib.pyplot.show', 'plt.show', ([], {}), '()\n', (507, 509), True, 'import matplotlib.pyplot as plt\n'), ((348, 359), 'time.time', 'time.time', ([], {}), '()\n', (357, 359), False, 'import time\n')] |
robinvoogt/text-sdk-python | Examples/Rich_Message_Example.py | 1acd624991f396cc673dad22cfa3272b4b3fb53b | from CMText.TextClient import TextClient
# Message to be send
message = 'Examples message to be send'
# Media to be send
media = {
"mediaName": "conversational-commerce",
"mediaUri": "https://www.cm.com/cdn/cm/cm.png",
"mimeType": "image/png"
}
# AllowedChannels in this case Whatsapp
allowedChannels = ['Whatsapp']
# Recipients
to = ['003156789000', '002134567890']
# Instantiate client with your own api-key
client = TextClient(apikey=UNIQUE_API_KEY)
# Add a Rich message to the queue
client.AddRichMessage(message=message, from_='pythonSDK', to=to, allowedChannels=allowedChannels, media=media)
# Send the messages
response = client.send()
# Print response
print(response.text) | [((468, 501), 'CMText.TextClient.TextClient', 'TextClient', ([], {'apikey': 'UNIQUE_API_KEY'}), '(apikey=UNIQUE_API_KEY)\n', (478, 501), False, 'from CMText.TextClient import TextClient\n')] |
Dmitry450/asynciogame | client/audio.py | 47a2a118155805db37f2c3bd916bd6c68c504cff | import pygame
from pygame.math import Vector2
class Sound:
def __init__(self, manager, snd, volume=1.0):
self.manager = manager
self.snd = pygame.mixer.Sound(snd)
self.snd.set_volume(1.0)
self.ttl = snd.get_length()
self.playing = True
self.snd.play()
def update(self, dtime):
self.ttl -= dtime
if self.ttl <= 0:
self.playing = False
class AttachedSound(Sound):
def __init__(self, manager, snd, position, volume=1.0, fade_dist=1, min_volume=0.1):
super().__init__(manager, snd)
if not isinstance(position, Vector2):
position = Vector2(position)
self.position = position
self.volume = volume
self.fade_dist = fade_dist
self.min_volume = min_volume
def update(self, dtime):
super().update(dtime)
if self.playing and self.manager.track_object is not None:
dist = self.position.distance_to(self.manager.track_object.position)
volume = self.volume*self.fade_dist/dist
if volume > self.min_volume:
self.snd.set_volume(volume)
else:
self.snd.set_volume(0)
class AudioManager:
def __init__(self):
self.loaded = {}
self.sounds = []
self.track_object = None
def play_sound(self, d):
name = d["name"]
if self.loaded.get(name) is None:
self.loaded[name] = pygame.mixer.Sound(name)
if d["type"] == "normal":
self.sounds.append(Sound(self, self.loaded[name], volume=d.get("volume", 1.0)))
# Actually sound can be "attached_to_position" and "attached_to_entity".
# To avoid adding EntityManager reference into AudioManager, "position"
# will be replaced by entity.position in Connection when sound event handled.
# Anyway, d["type"] will be set to "attached"
elif d["type"] == "attached":
self.sounds.append(AttachedSound(self, self.loaded[name], d["position"],
volume=d.get("volume", 1.0),
fade_dist=d.get("fade_dist", 1),
min_volume=d.get("min_volume", 0.1)))
def update(self, dtime):
for sound in self.sounds:
sound.update(dtime)
if not sound.playing:
self.sounds.remove(sound)
| [((166, 189), 'pygame.mixer.Sound', 'pygame.mixer.Sound', (['snd'], {}), '(snd)\n', (184, 189), False, 'import pygame\n'), ((707, 724), 'pygame.math.Vector2', 'Vector2', (['position'], {}), '(position)\n', (714, 724), False, 'from pygame.math import Vector2\n'), ((1613, 1637), 'pygame.mixer.Sound', 'pygame.mixer.Sound', (['name'], {}), '(name)\n', (1631, 1637), False, 'import pygame\n')] |
MmeK/ganjoor-telegram-bot | bot/ganjoor/category_choose.py | 3992bdd860ea3626dccd79b0c1993a3662e92aa5 |
# Copyright 2021 Mohammad Kazemi <kazemi.me.222@gmail.com>.
# SPDX-License-Identifier: MIT
# Telegram API framework core imports
from collections import namedtuple
from functools import partial
from ganjoor.ganjoor import Ganjoor
from telegram.ext import Dispatcher, CallbackContext
from telegram import Update
# Helper methods import
from utils.logger import get_logger
from utils.telegram.keyboards import category_keyboard
# Telegram API framework handlers imports
from telegram.ext import CallbackQueryHandler
# Init logger
logger = get_logger(__name__)
CallbackData = namedtuple('CallbackData', "menu_name doto")
def init(dispatcher: Dispatcher, ganjoor: Ganjoor):
"""Provide handlers initialization."""
dispatcher.add_handler(CallbackQueryHandler(
partial(category_id, ganjoor=ganjoor), pattern=r'^category_*'))
def category_id(update: Update, context: CallbackContext, ganjoor: Ganjoor) -> int:
"""Process a /start command."""
query = update.callback_query
message_id = '_'.join(query.data.split('_')[2:])
cat_id = query.data.split('_')[1]
cat = ganjoor.find_category_by_id(cat_id, with_poems=True)
# query.answer()
query.answer()
context.bot.edit_message_reply_markup(
inline_message_id=message_id, reply_markup=category_keyboard(cat, message_id))
# query.edit_reply_markup()
| [((539, 559), 'utils.logger.get_logger', 'get_logger', (['__name__'], {}), '(__name__)\n', (549, 559), False, 'from utils.logger import get_logger\n'), ((575, 619), 'collections.namedtuple', 'namedtuple', (['"""CallbackData"""', '"""menu_name doto"""'], {}), "('CallbackData', 'menu_name doto')\n", (585, 619), False, 'from collections import namedtuple\n'), ((774, 811), 'functools.partial', 'partial', (['category_id'], {'ganjoor': 'ganjoor'}), '(category_id, ganjoor=ganjoor)\n', (781, 811), False, 'from functools import partial\n'), ((1285, 1319), 'utils.telegram.keyboards.category_keyboard', 'category_keyboard', (['cat', 'message_id'], {}), '(cat, message_id)\n', (1302, 1319), False, 'from utils.telegram.keyboards import category_keyboard\n')] |
walterfan/snippets | python/util/md_utils.py | 62f87720c411093fcff888f25b338afd1d99a6f9 | import os
import sys
import struct
import re
import logging
logging.basicConfig(stream=sys.stderr, level=logging.DEBUG)
logger = logging.getLogger(__name__)
def list_to_md(str_list):
output = ""
for str in str_list:
output = output + "* %s \n" % str
return output
def str_to_md_list(the_str, sep):
str_list = the_str.split(sep)
output = ""
for str in str_list:
output = output + "* %s \n" % str
return output
| [((61, 120), 'logging.basicConfig', 'logging.basicConfig', ([], {'stream': 'sys.stderr', 'level': 'logging.DEBUG'}), '(stream=sys.stderr, level=logging.DEBUG)\n', (80, 120), False, 'import logging\n'), ((130, 157), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (147, 157), False, 'import logging\n')] |
Josverl/micropython-stubber | board/main.py | 3dc57ea9e957bd9f36fce6abfe051a2fa7ace522 | import uos as os
import time
def countdown():
for i in range(5, 0, -1):
print("start stubbing in {}...".format(i))
time.sleep(1)
import createstubs
# import stub_lvgl
try:
# only run import if no stubs yet
os.listdir("stubs")
print("stub folder was found, stubbing is not automatically started")
except OSError:
countdown()
| [((247, 266), 'uos.listdir', 'os.listdir', (['"""stubs"""'], {}), "('stubs')\n", (257, 266), True, 'import uos as os\n'), ((137, 150), 'time.sleep', 'time.sleep', (['(1)'], {}), '(1)\n', (147, 150), False, 'import time\n')] |
zipated/src | third_party/blink/tools/blinkpy/web_tests/breakpad/dump_reader_multipart_unittest.py | 2b8388091c71e442910a21ada3d97ae8bc1845d3 | # Copyright (C) 2013 Google Inc. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above
# copyright notice, this list of conditions and the following disclaimer
# in the documentation and/or other materials provided with the
# distribution.
# * Neither the name of Google Inc. nor the names of its
# contributors may be used to endorse or promote products derived from
# this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
# "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
# LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
# A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
# OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
# SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
# LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
# DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
# THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
import unittest
from blinkpy.common.host import Host
from blinkpy.common.host_mock import MockHost
from blinkpy.web_tests.breakpad.dump_reader_multipart import DumpReaderMultipart
class TestDumpReaderMultipart(unittest.TestCase):
_MULTIPART_DUMP = [
'--boundary',
'Content-Disposition: form-data; name="prod"',
'',
'content_shell',
'--boundary',
'Content-Disposition: form-data; name="pid"',
'',
'4711',
'--boundary',
'Content-Disposition: form-data; name="upload_file_minidump"; filename="dump"',
'Content-Type: application/octet-stream',
'',
'MDMP',
'--boundary--',
]
def test_check_generate_breakpad_symbols_actually_exists(self):
host = Host()
dump_reader = DumpReaderMultipart(host, build_dir=None)
self.assertTrue(host.filesystem.exists(dump_reader._path_to_generate_breakpad_symbols()))
def test_check_is_functional_breakpad_tools_not_found(self):
host = MockHost()
build_dir = "/mock-checkout/out/Debug"
host.filesystem.maybe_make_directory(build_dir)
dump_reader = DumpReaderMultipart(host, build_dir)
dump_reader._file_extension = lambda: 'dmp'
dump_reader._binaries_to_symbolize = lambda: ['content_shell']
self.assertFalse(dump_reader.check_is_functional())
def test_get_pid_from_dump(self):
host = MockHost()
dump_file = '/crash-dumps/dump.dmp'
expected_pid = '4711'
host.filesystem.write_text_file(dump_file, "\r\n".join(TestDumpReaderMultipart._MULTIPART_DUMP))
build_dir = "/mock-checkout/out/Debug"
host.filesystem.maybe_make_directory(build_dir)
host.filesystem.exists = lambda x: True
# The mock file object returned by open_binary_file_for_reading doesn't
# have readline(), however, the real File object does.
host.filesystem.open_binary_file_for_reading = host.filesystem.open_text_file_for_reading
dump_reader = DumpReaderMultipart(host, build_dir)
dump_reader._file_extension = lambda: 'dmp'
dump_reader._binaries_to_symbolize = lambda: ['content_shell']
self.assertTrue(dump_reader.check_is_functional())
self.assertEqual(expected_pid, dump_reader._get_pid_from_dump(dump_file))
def test_get_stack_from_dump(self):
host = MockHost()
dump_file = '/crash-dumps/dump.dmp'
host.filesystem.write_text_file(dump_file, "\r\n".join(TestDumpReaderMultipart._MULTIPART_DUMP))
build_dir = "/mock-checkout/out/Debug"
host.filesystem.maybe_make_directory(build_dir)
host.filesystem.exists = lambda x: True
# The mock file object returned by open_binary_file_for_reading doesn't
# have readline(), however, the real File object does.
host.filesystem.open_binary_file_for_reading = host.filesystem.open_text_file_for_reading
dump_reader = DumpReaderMultipart(host, build_dir)
dump_reader._file_extension = lambda: 'dmp'
dump_reader._binaries_to_symbolize = lambda: ['content_shell']
self.assertTrue(dump_reader.check_is_functional())
self.assertEqual("MOCK output of child process", dump_reader._get_stack_from_dump(dump_file))
self.assertEqual(2, len(host.executive.calls))
cmd_line = " ".join(host.executive.calls[0])
self.assertIn('generate_breakpad_symbols.py', cmd_line)
cmd_line = " ".join(host.executive.calls[1])
self.assertIn('minidump_stackwalk', cmd_line)
| [((2307, 2313), 'blinkpy.common.host.Host', 'Host', ([], {}), '()\n', (2311, 2313), False, 'from blinkpy.common.host import Host\n'), ((2336, 2377), 'blinkpy.web_tests.breakpad.dump_reader_multipart.DumpReaderMultipart', 'DumpReaderMultipart', (['host'], {'build_dir': 'None'}), '(host, build_dir=None)\n', (2355, 2377), False, 'from blinkpy.web_tests.breakpad.dump_reader_multipart import DumpReaderMultipart\n'), ((2557, 2567), 'blinkpy.common.host_mock.MockHost', 'MockHost', ([], {}), '()\n', (2565, 2567), False, 'from blinkpy.common.host_mock import MockHost\n'), ((2694, 2730), 'blinkpy.web_tests.breakpad.dump_reader_multipart.DumpReaderMultipart', 'DumpReaderMultipart', (['host', 'build_dir'], {}), '(host, build_dir)\n', (2713, 2730), False, 'from blinkpy.web_tests.breakpad.dump_reader_multipart import DumpReaderMultipart\n'), ((2969, 2979), 'blinkpy.common.host_mock.MockHost', 'MockHost', ([], {}), '()\n', (2977, 2979), False, 'from blinkpy.common.host_mock import MockHost\n'), ((3575, 3611), 'blinkpy.web_tests.breakpad.dump_reader_multipart.DumpReaderMultipart', 'DumpReaderMultipart', (['host', 'build_dir'], {}), '(host, build_dir)\n', (3594, 3611), False, 'from blinkpy.web_tests.breakpad.dump_reader_multipart import DumpReaderMultipart\n'), ((3933, 3943), 'blinkpy.common.host_mock.MockHost', 'MockHost', ([], {}), '()\n', (3941, 3943), False, 'from blinkpy.common.host_mock import MockHost\n'), ((4509, 4545), 'blinkpy.web_tests.breakpad.dump_reader_multipart.DumpReaderMultipart', 'DumpReaderMultipart', (['host', 'build_dir'], {}), '(host, build_dir)\n', (4528, 4545), False, 'from blinkpy.web_tests.breakpad.dump_reader_multipart import DumpReaderMultipart\n')] |
SilverWingedSeraph/sws-dotfiles | scripts/emoji-to-scl.py | 6bee2b2ece03439101848673d6bcd9196359f7c4 | #!/usr/bin/python3
# -*- coding: utf-8 -*-
from subprocess import Popen, PIPE
emojis="""⛑🏻 Helmet With White Cross, Type-1-2
⛑🏼 Helmet With White Cross, Type-3
⛑🏽 Helmet With White Cross, Type-4
⛑🏾 Helmet With White Cross, Type-5
⛑🏿 Helmet With White Cross, Type-6
💏🏻 Kiss, Type-1-2
💏🏼 Kiss, Type-3
💏🏽 Kiss, Type-4
💏🏾 Kiss, Type-5
💏🏿 Kiss, Type-6
💑🏻 Couple With Heart, Type-1-2
💑🏼 Couple With Heart, Type-3
💑🏽 Couple With Heart, Type-4
💑🏾 Couple With Heart, Type-5
💑🏿 Couple With Heart, Type-6
⛷🏻 Skier, Type-1-2
⛷🏼 Skier, Type-3
⛷🏽 Skier, Type-4
⛷🏾 Skier, Type-5
⛷🏿 Skier, Type-6
😀 Grinning Face
😁 Grinning Face With Smiling Eyes
😂 Face With Tears of Joy
🤣 Rolling on the Floor Laughing
😃 Smiling Face With Open Mouth
😄 Smiling Face With Open Mouth & Smiling Eyes
😅 Smiling Face With Open Mouth & Cold Sweat
😆 Smiling Face With Open Mouth & Closed Eyes
😉 Winking Face
😊 Smiling Face With Smiling Eyes
😋 Face Savouring Delicious Food
😎 Smiling Face With Sunglasses
😍 Smiling Face With Heart-Eyes
😘 Face Blowing a Kiss
😗 Kissing Face
😙 Kissing Face With Smiling Eyes
😚 Kissing Face With Closed Eyes
☺ Smiling Face
🙂 Slightly Smiling Face
🤗 Hugging Face
🤩 Star-Struck
🤔 Thinking Face
🤨 Face With Raised Eyebrow
😐 Neutral Face
😑 Expressionless Face
😶 Face Without Mouth
🙄 Face With Rolling Eyes
😏 Smirking Face
😣 Persevering Face
😥 Disappointed but Relieved Face
😮 Face With Open Mouth
🤐 Zipper-Mouth Face
😯 Hushed Face
😪 Sleepy Face
😫 Tired Face
😴 Sleeping Face
😌 Relieved Face
😛 Face With Stuck-Out Tongue
😜 Face With Stuck-Out Tongue & Winking Eye
😝 Face With Stuck-Out Tongue & Closed Eyes
🤤 Drooling Face
😒 Unamused Face
😓 Face With Cold Sweat
😔 Pensive Face
😕 Confused Face
🙃 Upside-Down Face
🤑 Money-Mouth Face
😲 Astonished Face
☹ Frowning Face
🙁 Slightly Frowning Face
😖 Confounded Face
😞 Disappointed Face
😟 Worried Face
😤 Face With Steam From Nose
😢 Crying Face
😭 Loudly Crying Face
😦 Frowning Face With Open Mouth
😧 Anguished Face
😨 Fearful Face
😩 Weary Face
🤯 Exploding Head
😬 Grimacing Face
😰 Face With Open Mouth & Cold Sweat
😱 Face Screaming in Fear
😳 Flushed Face
🤪 Crazy Face
😵 Dizzy Face
😡 Pouting Face
😠 Angry Face
🤬 Face With Symbols Over Mouth
😷 Face With Medical Mask
🤒 Face With Thermometer
🤕 Face With Head-Bandage
🤢 Nauseated Face
🤮 Face Vomiting
🤧 Sneezing Face
😇 Smiling Face With Halo
🤠 Cowboy Hat Face
🤡 Clown Face
🤥 Lying Face
🤫 Shushing Face
🤭 Face With Hand Over Mouth
🧐 Face With Monocle
🤓 Nerd Face
😈 Smiling Face With Horns
👿 Angry Face With Horns
👹 Ogre
👺 Goblin
💀 Skull
☠ Skull and Crossbones
👻 Ghost
👽 Alien
👾 Alien Monster
🤖 Robot Face
💩 Pile of Poo
😺 Smiling Cat Face With Open Mouth
😸 Grinning Cat Face With Smiling Eyes
😹 Cat Face With Tears of Joy
😻 Smiling Cat Face With Heart-Eyes
😼 Cat Face With Wry Smile
😽 Kissing Cat Face With Closed Eyes
🙀 Weary Cat Face
😿 Crying Cat Face
😾 Pouting Cat Face
🙈 See-No-Evil Monkey
🙉 Hear-No-Evil Monkey
🙊 Speak-No-Evil Monkey
👶 Baby
👶🏻 Baby: Light Skin Tone
👶🏼 Baby: Medium-Light Skin Tone
👶🏽 Baby: Medium Skin Tone
👶🏾 Baby: Medium-Dark Skin Tone
👶🏿 Baby: Dark Skin Tone
🧒 Child
🧒🏻 Child: Light Skin Tone
🧒🏼 Child: Medium-Light Skin Tone
🧒🏽 Child: Medium Skin Tone
🧒🏾 Child: Medium-Dark Skin Tone
🧒🏿 Child: Dark Skin Tone
👦 Boy
👦🏻 Boy: Light Skin Tone
👦🏼 Boy: Medium-Light Skin Tone
👦🏽 Boy: Medium Skin Tone
👦🏾 Boy: Medium-Dark Skin Tone
👦🏿 Boy: Dark Skin Tone
👧 Girl
👧🏻 Girl: Light Skin Tone
👧🏼 Girl: Medium-Light Skin Tone
👧🏽 Girl: Medium Skin Tone
👧🏾 Girl: Medium-Dark Skin Tone
👧🏿 Girl: Dark Skin Tone
🧑 Adult
🧑🏻 Adult: Light Skin Tone
🧑🏼 Adult: Medium-Light Skin Tone
🧑🏽 Adult: Medium Skin Tone
🧑🏾 Adult: Medium-Dark Skin Tone
🧑🏿 Adult: Dark Skin Tone
👨 Man
👨🏻 Man: Light Skin Tone
👨🏼 Man: Medium-Light Skin Tone
👨🏽 Man: Medium Skin Tone
👨🏾 Man: Medium-Dark Skin Tone
👨🏿 Man: Dark Skin Tone
👩 Woman
👩🏻 Woman: Light Skin Tone
👩🏼 Woman: Medium-Light Skin Tone
👩🏽 Woman: Medium Skin Tone
👩🏾 Woman: Medium-Dark Skin Tone
👩🏿 Woman: Dark Skin Tone
🧓 Older Adult
🧓🏻 Older Adult: Light Skin Tone
🧓🏼 Older Adult: Medium-Light Skin Tone
🧓🏽 Older Adult: Medium Skin Tone
🧓🏾 Older Adult: Medium-Dark Skin Tone
🧓🏿 Older Adult: Dark Skin Tone
👴 Old Man
👴🏻 Old Man: Light Skin Tone
👴🏼 Old Man: Medium-Light Skin Tone
👴🏽 Old Man: Medium Skin Tone
👴🏾 Old Man: Medium-Dark Skin Tone
👴🏿 Old Man: Dark Skin Tone
👵 Old Woman
👵🏻 Old Woman: Light Skin Tone
👵🏼 Old Woman: Medium-Light Skin Tone
👵🏽 Old Woman: Medium Skin Tone
👵🏾 Old Woman: Medium-Dark Skin Tone
👵🏿 Old Woman: Dark Skin Tone
👨⚕️ Man Health Worker
👨🏻⚕️ Man Health Worker: Light Skin Tone
👨🏼⚕️ Man Health Worker: Medium-Light Skin Tone
👨🏽⚕️ Man Health Worker: Medium Skin Tone
👨🏾⚕️ Man Health Worker: Medium-Dark Skin Tone
👨🏿⚕️ Man Health Worker: Dark Skin Tone
👩⚕️ Woman Health Worker
👩🏻⚕️ Woman Health Worker: Light Skin Tone
👩🏼⚕️ Woman Health Worker: Medium-Light Skin Tone
👩🏽⚕️ Woman Health Worker: Medium Skin Tone
👩🏾⚕️ Woman Health Worker: Medium-Dark Skin Tone
👩🏿⚕️ Woman Health Worker: Dark Skin Tone
👨🎓 Man Student
👨🏻🎓 Man Student: Light Skin Tone
👨🏼🎓 Man Student: Medium-Light Skin Tone
👨🏽🎓 Man Student: Medium Skin Tone
👨🏾🎓 Man Student: Medium-Dark Skin Tone
👨🏿🎓 Man Student: Dark Skin Tone
👩🎓 Woman Student
👩🏻🎓 Woman Student: Light Skin Tone
👩🏼🎓 Woman Student: Medium-Light Skin Tone
👩🏽🎓 Woman Student: Medium Skin Tone
👩🏾🎓 Woman Student: Medium-Dark Skin Tone
👩🏿🎓 Woman Student: Dark Skin Tone
👨🏫 Man Teacher
👨🏻🏫 Man Teacher: Light Skin Tone
👨🏼🏫 Man Teacher: Medium-Light Skin Tone
👨🏽🏫 Man Teacher: Medium Skin Tone
👨🏾🏫 Man Teacher: Medium-Dark Skin Tone
👨🏿🏫 Man Teacher: Dark Skin Tone
👩🏫 Woman Teacher
👩🏻🏫 Woman Teacher: Light Skin Tone
👩🏼🏫 Woman Teacher: Medium-Light Skin Tone
👩🏽🏫 Woman Teacher: Medium Skin Tone
👩🏾🏫 Woman Teacher: Medium-Dark Skin Tone
👩🏿🏫 Woman Teacher: Dark Skin Tone
👨⚖️ Man Judge
👨🏻⚖️ Man Judge: Light Skin Tone
👨🏼⚖️ Man Judge: Medium-Light Skin Tone
👨🏽⚖️ Man Judge: Medium Skin Tone
👨🏾⚖️ Man Judge: Medium-Dark Skin Tone
👨🏿⚖️ Man Judge: Dark Skin Tone
👩⚖️ Woman Judge
👩🏻⚖️ Woman Judge: Light Skin Tone
👩🏼⚖️ Woman Judge: Medium-Light Skin Tone
👩🏽⚖️ Woman Judge: Medium Skin Tone
👩🏾⚖️ Woman Judge: Medium-Dark Skin Tone
👩🏿⚖️ Woman Judge: Dark Skin Tone
👨🌾 Man Farmer
👨🏻🌾 Man Farmer: Light Skin Tone
👨🏼🌾 Man Farmer: Medium-Light Skin Tone
👨🏽🌾 Man Farmer: Medium Skin Tone
👨🏾🌾 Man Farmer: Medium-Dark Skin Tone
👨🏿🌾 Man Farmer: Dark Skin Tone
👩🌾 Woman Farmer
👩🏻🌾 Woman Farmer: Light Skin Tone
👩🏼🌾 Woman Farmer: Medium-Light Skin Tone
👩🏽🌾 Woman Farmer: Medium Skin Tone
👩🏾🌾 Woman Farmer: Medium-Dark Skin Tone
👩🏿🌾 Woman Farmer: Dark Skin Tone
👨🍳 Man Cook
👨🏻🍳 Man Cook: Light Skin Tone
👨🏼🍳 Man Cook: Medium-Light Skin Tone
👨🏽🍳 Man Cook: Medium Skin Tone
👨🏾🍳 Man Cook: Medium-Dark Skin Tone
👨🏿🍳 Man Cook: Dark Skin Tone
👩🍳 Woman Cook
👩🏻🍳 Woman Cook: Light Skin Tone
👩🏼🍳 Woman Cook: Medium-Light Skin Tone
👩🏽🍳 Woman Cook: Medium Skin Tone
👩🏾🍳 Woman Cook: Medium-Dark Skin Tone
👩🏿🍳 Woman Cook: Dark Skin Tone
👨🔧 Man Mechanic
👨🏻🔧 Man Mechanic: Light Skin Tone
👨🏼🔧 Man Mechanic: Medium-Light Skin Tone
👨🏽🔧 Man Mechanic: Medium Skin Tone
👨🏾🔧 Man Mechanic: Medium-Dark Skin Tone
👨🏿🔧 Man Mechanic: Dark Skin Tone
👩🔧 Woman Mechanic
👩🏻🔧 Woman Mechanic: Light Skin Tone
👩🏼🔧 Woman Mechanic: Medium-Light Skin Tone
👩🏽🔧 Woman Mechanic: Medium Skin Tone
👩🏾🔧 Woman Mechanic: Medium-Dark Skin Tone
👩🏿🔧 Woman Mechanic: Dark Skin Tone
👨🏭 Man Factory Worker
👨🏻🏭 Man Factory Worker: Light Skin Tone
👨🏼🏭 Man Factory Worker: Medium-Light Skin Tone
👨🏽🏭 Man Factory Worker: Medium Skin Tone
👨🏾🏭 Man Factory Worker: Medium-Dark Skin Tone
👨🏿🏭 Man Factory Worker: Dark Skin Tone
👩🏭 Woman Factory Worker
👩🏻🏭 Woman Factory Worker: Light Skin Tone
👩🏼🏭 Woman Factory Worker: Medium-Light Skin Tone
👩🏽🏭 Woman Factory Worker: Medium Skin Tone
👩🏾🏭 Woman Factory Worker: Medium-Dark Skin Tone
👩🏿🏭 Woman Factory Worker: Dark Skin Tone
👨💼 Man Office Worker
👨🏻💼 Man Office Worker: Light Skin Tone
👨🏼💼 Man Office Worker: Medium-Light Skin Tone
👨🏽💼 Man Office Worker: Medium Skin Tone
👨🏾💼 Man Office Worker: Medium-Dark Skin Tone
👨🏿💼 Man Office Worker: Dark Skin Tone
👩💼 Woman Office Worker
👩🏻💼 Woman Office Worker: Light Skin Tone
👩🏼💼 Woman Office Worker: Medium-Light Skin Tone
👩🏽💼 Woman Office Worker: Medium Skin Tone
👩🏾💼 Woman Office Worker: Medium-Dark Skin Tone
👩🏿💼 Woman Office Worker: Dark Skin Tone
👨🔬 Man Scientist
👨🏻🔬 Man Scientist: Light Skin Tone
👨🏼🔬 Man Scientist: Medium-Light Skin Tone
👨🏽🔬 Man Scientist: Medium Skin Tone
👨🏾🔬 Man Scientist: Medium-Dark Skin Tone
👨🏿🔬 Man Scientist: Dark Skin Tone
👩🔬 Woman Scientist
👩🏻🔬 Woman Scientist: Light Skin Tone
👩🏼🔬 Woman Scientist: Medium-Light Skin Tone
👩🏽🔬 Woman Scientist: Medium Skin Tone
👩🏾🔬 Woman Scientist: Medium-Dark Skin Tone
👩🏿🔬 Woman Scientist: Dark Skin Tone
👨💻 Man Technologist
👨🏻💻 Man Technologist: Light Skin Tone
👨🏼💻 Man Technologist: Medium-Light Skin Tone
👨🏽💻 Man Technologist: Medium Skin Tone
👨🏾💻 Man Technologist: Medium-Dark Skin Tone
👨🏿💻 Man Technologist: Dark Skin Tone
👩💻 Woman Technologist
👩🏻💻 Woman Technologist: Light Skin Tone
👩🏼💻 Woman Technologist: Medium-Light Skin Tone
👩🏽💻 Woman Technologist: Medium Skin Tone
👩🏾💻 Woman Technologist: Medium-Dark Skin Tone
👩🏿💻 Woman Technologist: Dark Skin Tone
👨🎤 Man Singer
👨🏻🎤 Man Singer: Light Skin Tone
👨🏼🎤 Man Singer: Medium-Light Skin Tone
👨🏽🎤 Man Singer: Medium Skin Tone
👨🏾🎤 Man Singer: Medium-Dark Skin Tone
👨🏿🎤 Man Singer: Dark Skin Tone
👩🎤 Woman Singer
👩🏻🎤 Woman Singer: Light Skin Tone
👩🏼🎤 Woman Singer: Medium-Light Skin Tone
👩🏽🎤 Woman Singer: Medium Skin Tone
👩🏾🎤 Woman Singer: Medium-Dark Skin Tone
👩🏿🎤 Woman Singer: Dark Skin Tone
👨🎨 Man Artist
👨🏻🎨 Man Artist: Light Skin Tone
👨🏼🎨 Man Artist: Medium-Light Skin Tone
👨🏽🎨 Man Artist: Medium Skin Tone
👨🏾🎨 Man Artist: Medium-Dark Skin Tone
👨🏿🎨 Man Artist: Dark Skin Tone
👩🎨 Woman Artist
👩🏻🎨 Woman Artist: Light Skin Tone
👩🏼🎨 Woman Artist: Medium-Light Skin Tone
👩🏽🎨 Woman Artist: Medium Skin Tone
👩🏾🎨 Woman Artist: Medium-Dark Skin Tone
👩🏿🎨 Woman Artist: Dark Skin Tone
👨✈️ Man Pilot
👨🏻✈️ Man Pilot: Light Skin Tone
👨🏼✈️ Man Pilot: Medium-Light Skin Tone
👨🏽✈️ Man Pilot: Medium Skin Tone
👨🏾✈️ Man Pilot: Medium-Dark Skin Tone
👨🏿✈️ Man Pilot: Dark Skin Tone
👩✈️ Woman Pilot
👩🏻✈️ Woman Pilot: Light Skin Tone
👩🏼✈️ Woman Pilot: Medium-Light Skin Tone
👩🏽✈️ Woman Pilot: Medium Skin Tone
👩🏾✈️ Woman Pilot: Medium-Dark Skin Tone
👩🏿✈️ Woman Pilot: Dark Skin Tone
👨🚀 Man Astronaut
👨🏻🚀 Man Astronaut: Light Skin Tone
👨🏼🚀 Man Astronaut: Medium-Light Skin Tone
👨🏽🚀 Man Astronaut: Medium Skin Tone
👨🏾🚀 Man Astronaut: Medium-Dark Skin Tone
👨🏿🚀 Man Astronaut: Dark Skin Tone
👩🚀 Woman Astronaut
👩🏻🚀 Woman Astronaut: Light Skin Tone
👩🏼🚀 Woman Astronaut: Medium-Light Skin Tone
👩🏽🚀 Woman Astronaut: Medium Skin Tone
👩🏾🚀 Woman Astronaut: Medium-Dark Skin Tone
👩🏿🚀 Woman Astronaut: Dark Skin Tone
👨🚒 Man Firefighter
👨🏻🚒 Man Firefighter: Light Skin Tone
👨🏼🚒 Man Firefighter: Medium-Light Skin Tone
👨🏽🚒 Man Firefighter: Medium Skin Tone
👨🏾🚒 Man Firefighter: Medium-Dark Skin Tone
👨🏿🚒 Man Firefighter: Dark Skin Tone
👩🚒 Woman Firefighter
👩🏻🚒 Woman Firefighter: Light Skin Tone
👩🏼🚒 Woman Firefighter: Medium-Light Skin Tone
👩🏽🚒 Woman Firefighter: Medium Skin Tone
👩🏾🚒 Woman Firefighter: Medium-Dark Skin Tone
👩🏿🚒 Woman Firefighter: Dark Skin Tone
👮 Police Officer
👮🏻 Police Officer: Light Skin Tone
👮🏼 Police Officer: Medium-Light Skin Tone
👮🏽 Police Officer: Medium Skin Tone
👮🏾 Police Officer: Medium-Dark Skin Tone
👮🏿 Police Officer: Dark Skin Tone
👮♂️ Man Police Officer
👮🏻♂️ Man Police Officer: Light Skin Tone
👮🏼♂️ Man Police Officer: Medium-Light Skin Tone
👮🏽♂️ Man Police Officer: Medium Skin Tone
👮🏾♂️ Man Police Officer: Medium-Dark Skin Tone
👮🏿♂️ Man Police Officer: Dark Skin Tone
👮♀️ Woman Police Officer
👮🏻♀️ Woman Police Officer: Light Skin Tone
👮🏼♀️ Woman Police Officer: Medium-Light Skin Tone
👮🏽♀️ Woman Police Officer: Medium Skin Tone
👮🏾♀️ Woman Police Officer: Medium-Dark Skin Tone
👮🏿♀️ Woman Police Officer: Dark Skin Tone
🕵 Detective
🕵🏻 Detective: Light Skin Tone
🕵🏼 Detective: Medium-Light Skin Tone
🕵🏽 Detective: Medium Skin Tone
🕵🏾 Detective: Medium-Dark Skin Tone
🕵🏿 Detective: Dark Skin Tone
🕵️♂️ Man Detective
🕵🏻♂️ Man Detective: Light Skin Tone
🕵🏼♂️ Man Detective: Medium-Light Skin Tone
🕵🏽♂️ Man Detective: Medium Skin Tone
🕵🏾♂️ Man Detective: Medium-Dark Skin Tone
🕵🏿♂️ Man Detective: Dark Skin Tone
🕵️♀️ Woman Detective
🕵🏻♀️ Woman Detective: Light Skin Tone
🕵🏼♀️ Woman Detective: Medium-Light Skin Tone
🕵🏽♀️ Woman Detective: Medium Skin Tone
🕵🏾♀️ Woman Detective: Medium-Dark Skin Tone
🕵🏿♀️ Woman Detective: Dark Skin Tone
💂 Guard
💂🏻 Guard: Light Skin Tone
💂🏼 Guard: Medium-Light Skin Tone
💂🏽 Guard: Medium Skin Tone
💂🏾 Guard: Medium-Dark Skin Tone
💂🏿 Guard: Dark Skin Tone
💂♂️ Man Guard
💂🏻♂️ Man Guard: Light Skin Tone
💂🏼♂️ Man Guard: Medium-Light Skin Tone
💂🏽♂️ Man Guard: Medium Skin Tone
💂🏾♂️ Man Guard: Medium-Dark Skin Tone
💂🏿♂️ Man Guard: Dark Skin Tone
💂♀️ Woman Guard
💂🏻♀️ Woman Guard: Light Skin Tone
💂🏼♀️ Woman Guard: Medium-Light Skin Tone
💂🏽♀️ Woman Guard: Medium Skin Tone
💂🏾♀️ Woman Guard: Medium-Dark Skin Tone
💂🏿♀️ Woman Guard: Dark Skin Tone
👷 Construction Worker
👷🏻 Construction Worker: Light Skin Tone
👷🏼 Construction Worker: Medium-Light Skin Tone
👷🏽 Construction Worker: Medium Skin Tone
👷🏾 Construction Worker: Medium-Dark Skin Tone
👷🏿 Construction Worker: Dark Skin Tone
👷♂️ Man Construction Worker
👷🏻♂️ Man Construction Worker: Light Skin Tone
👷🏼♂️ Man Construction Worker: Medium-Light Skin Tone
👷🏽♂️ Man Construction Worker: Medium Skin Tone
👷🏾♂️ Man Construction Worker: Medium-Dark Skin Tone
👷🏿♂️ Man Construction Worker: Dark Skin Tone
👷♀️ Woman Construction Worker
👷🏻♀️ Woman Construction Worker: Light Skin Tone
👷🏼♀️ Woman Construction Worker: Medium-Light Skin Tone
👷🏽♀️ Woman Construction Worker: Medium Skin Tone
👷🏾♀️ Woman Construction Worker: Medium-Dark Skin Tone
👷🏿♀️ Woman Construction Worker: Dark Skin Tone
🤴 Prince
🤴🏻 Prince: Light Skin Tone
🤴🏼 Prince: Medium-Light Skin Tone
🤴🏽 Prince: Medium Skin Tone
🤴🏾 Prince: Medium-Dark Skin Tone
🤴🏿 Prince: Dark Skin Tone
👸 Princess
👸🏻 Princess: Light Skin Tone
👸🏼 Princess: Medium-Light Skin Tone
👸🏽 Princess: Medium Skin Tone
👸🏾 Princess: Medium-Dark Skin Tone
👸🏿 Princess: Dark Skin Tone
👳 Person Wearing Turban
👳🏻 Person Wearing Turban: Light Skin Tone
👳🏼 Person Wearing Turban: Medium-Light Skin Tone
👳🏽 Person Wearing Turban: Medium Skin Tone
👳🏾 Person Wearing Turban: Medium-Dark Skin Tone
👳🏿 Person Wearing Turban: Dark Skin Tone
👳♂️ Man Wearing Turban
👳🏻♂️ Man Wearing Turban: Light Skin Tone
👳🏼♂️ Man Wearing Turban: Medium-Light Skin Tone
👳🏽♂️ Man Wearing Turban: Medium Skin Tone
👳🏾♂️ Man Wearing Turban: Medium-Dark Skin Tone
👳🏿♂️ Man Wearing Turban: Dark Skin Tone
👳♀️ Woman Wearing Turban
👳🏻♀️ Woman Wearing Turban: Light Skin Tone
👳🏼♀️ Woman Wearing Turban: Medium-Light Skin Tone
👳🏽♀️ Woman Wearing Turban: Medium Skin Tone
👳🏾♀️ Woman Wearing Turban: Medium-Dark Skin Tone
👳🏿♀️ Woman Wearing Turban: Dark Skin Tone
👲 Man With Chinese Cap
👲🏻 Man With Chinese Cap: Light Skin Tone
👲🏼 Man With Chinese Cap: Medium-Light Skin Tone
👲🏽 Man With Chinese Cap: Medium Skin Tone
👲🏾 Man With Chinese Cap: Medium-Dark Skin Tone
👲🏿 Man With Chinese Cap: Dark Skin Tone
🧕 Woman With Headscarf
🧕🏻 Person With Headscarf: Light Skin Tone
🧕🏼 Person With Headscarf: Medium-Light Skin Tone
🧕🏽 Person With Headscarf: Medium Skin Tone
🧕🏾 Person With Headscarf: Medium-Dark Skin Tone
🧕🏿 Person With Headscarf: Dark Skin Tone
🧔 Bearded Person
🧔🏻 Bearded Person: Light Skin Tone
🧔🏼 Bearded Person: Medium-Light Skin Tone
🧔🏽 Bearded Person: Medium Skin Tone
🧔🏾 Bearded Person: Medium-Dark Skin Tone
🧔🏿 Bearded Person: Dark Skin Tone
👱 Blond-Haired Person
👱🏻 Blond-Haired Person: Light Skin Tone
👱🏼 Blond-Haired Person: Medium-Light Skin Tone
👱🏽 Blond-Haired Person: Medium Skin Tone
👱🏾 Blond-Haired Person: Medium-Dark Skin Tone
👱🏿 Blond-Haired Person: Dark Skin Tone
👱♂️ Blond-Haired Man
👱🏻♂️ Blond-Haired Man: Light Skin Tone
👱🏼♂️ Blond-Haired Man: Medium-Light Skin Tone
👱🏽♂️ Blond-Haired Man: Medium Skin Tone
👱🏾♂️ Blond-Haired Man: Medium-Dark Skin Tone
👱🏿♂️ Blond-Haired Man: Dark Skin Tone
👱♀️ Blond-Haired Woman
👱🏻♀️ Blond-Haired Woman: Light Skin Tone
👱🏼♀️ Blond-Haired Woman: Medium-Light Skin Tone
👱🏽♀️ Blond-Haired Woman: Medium Skin Tone
👱🏾♀️ Blond-Haired Woman: Medium-Dark Skin Tone
👱🏿♀️ Blond-Haired Woman: Dark Skin Tone
🤵 Man in Tuxedo
🤵🏻 Man in Tuxedo: Light Skin Tone
🤵🏼 Man in Tuxedo: Medium-Light Skin Tone
🤵🏽 Man in Tuxedo: Medium Skin Tone
🤵🏾 Man in Tuxedo: Medium-Dark Skin Tone
🤵🏿 Man in Tuxedo: Dark Skin Tone
👰 Bride With Veil
👰🏻 Bride With Veil: Light Skin Tone
👰🏼 Bride With Veil: Medium-Light Skin Tone
👰🏽 Bride With Veil: Medium Skin Tone
👰🏾 Bride With Veil: Medium-Dark Skin Tone
👰🏿 Bride With Veil: Dark Skin Tone
🤰 Pregnant Woman
🤰🏻 Pregnant Woman: Light Skin Tone
🤰🏼 Pregnant Woman: Medium-Light Skin Tone
🤰🏽 Pregnant Woman: Medium Skin Tone
🤰🏾 Pregnant Woman: Medium-Dark Skin Tone
🤰🏿 Pregnant Woman: Dark Skin Tone
🤱 Breast-Feeding
🤱🏻 Breast-Feeding: Light Skin Tone
🤱🏼 Breast-Feeding: Medium-Light Skin Tone
🤱🏽 Breast-Feeding: Medium Skin Tone
🤱🏾 Breast-Feeding: Medium-Dark Skin Tone
🤱🏿 Breast-Feeding: Dark Skin Tone
👼 Baby Angel
👼🏻 Baby Angel: Light Skin Tone
👼🏼 Baby Angel: Medium-Light Skin Tone
👼🏽 Baby Angel: Medium Skin Tone
👼🏾 Baby Angel: Medium-Dark Skin Tone
👼🏿 Baby Angel: Dark Skin Tone
🎅 Santa Claus
🎅🏻 Santa Claus: Light Skin Tone
🎅🏼 Santa Claus: Medium-Light Skin Tone
🎅🏽 Santa Claus: Medium Skin Tone
🎅🏾 Santa Claus: Medium-Dark Skin Tone
🎅🏿 Santa Claus: Dark Skin Tone
🤶 Mrs. Claus
🤶🏻 Mrs. Claus: Light Skin Tone
🤶🏼 Mrs. Claus: Medium-Light Skin Tone
🤶🏽 Mrs. Claus: Medium Skin Tone
🤶🏾 Mrs. Claus: Medium-Dark Skin Tone
🤶🏿 Mrs. Claus: Dark Skin Tone
🧙 Mage
🧙🏻 Mage: Light Skin Tone
🧙🏼 Mage: Medium-Light Skin Tone
🧙🏽 Mage: Medium Skin Tone
🧙🏾 Mage: Medium-Dark Skin Tone
🧙🏿 Mage: Dark Skin Tone
🧙♀️ Woman Mage
🧙🏻♀️ Woman Mage: Light Skin Tone
🧙🏼♀️ Woman Mage: Medium-Light Skin Tone
🧙🏽♀️ Woman Mage: Medium Skin Tone
🧙🏾♀️ Woman Mage: Medium-Dark Skin Tone
🧙🏿♀️ Woman Mage: Dark Skin Tone
🧙♂️ Man Mage
🧙🏻♂️ Man Mage: Light Skin Tone
🧙🏼♂️ Man Mage: Medium-Light Skin Tone
🧙🏽♂️ Man Mage: Medium Skin Tone
🧙🏾♂️ Man Mage: Medium-Dark Skin Tone
🧙🏿♂️ Man Mage: Dark Skin Tone
🧚 Fairy
🧚🏻 Fairy: Light Skin Tone
🧚🏼 Fairy: Medium-Light Skin Tone
🧚🏽 Fairy: Medium Skin Tone
🧚🏾 Fairy: Medium-Dark Skin Tone
🧚🏿 Fairy: Dark Skin Tone
🧚♀️ Woman Fairy
🧚🏻♀️ Woman Fairy: Light Skin Tone
🧚🏼♀️ Woman Fairy: Medium-Light Skin Tone
🧚🏽♀️ Woman Fairy: Medium Skin Tone
🧚🏾♀️ Woman Fairy: Medium-Dark Skin Tone
🧚🏿♀️ Woman Fairy: Dark Skin Tone
🧚♂️ Man Fairy
🧚🏻♂️ Man Fairy: Light Skin Tone
🧚🏼♂️ Man Fairy: Medium-Light Skin Tone
🧚🏽♂️ Man Fairy: Medium Skin Tone
🧚🏾♂️ Man Fairy: Medium-Dark Skin Tone
🧚🏿♂️ Man Fairy: Dark Skin Tone
🧛 Vampire
🧛🏻 Vampire: Light Skin Tone
🧛🏼 Vampire: Medium-Light Skin Tone
🧛🏽 Vampire: Medium Skin Tone
🧛🏾 Vampire: Medium-Dark Skin Tone
🧛🏿 Vampire: Dark Skin Tone
🧛♀️ Woman Vampire
🧛🏻♀️ Woman Vampire: Light Skin Tone
🧛🏼♀️ Woman Vampire: Medium-Light Skin Tone
🧛🏽♀️ Woman Vampire: Medium Skin Tone
🧛🏾♀️ Woman Vampire: Medium-Dark Skin Tone
🧛🏿♀️ Woman Vampire: Dark Skin Tone
🧛♂️ Man Vampire
🧛🏻♂️ Man Vampire: Light Skin Tone
🧛🏼♂️ Man Vampire: Medium-Light Skin Tone
🧛🏽♂️ Man Vampire: Medium Skin Tone
🧛🏾♂️ Man Vampire: Medium-Dark Skin Tone
👯🏻 Woman With Bunny Ears, Type-1-2
👯🏼 Woman With Bunny Ears, Type-3
🧛🏿♂️ Man Vampire: Dark Skin Tone
👯🏽 Woman With Bunny Ears, Type-4
👯🏾 Woman With Bunny Ears, Type-5
🧜 Merperson
👯🏿 Woman With Bunny Ears, Type-6
🧜🏻 Merperson: Light Skin Tone
👯🏻♂️ Men With Bunny Ears Partying, Type-1-2
🧜🏼 Merperson: Medium-Light Skin Tone
👯🏼♂️ Men With Bunny Ears Partying, Type-3
🧜🏽 Merperson: Medium Skin Tone
👯🏽♂️ Men With Bunny Ears Partying, Type-4
🧜🏾 Merperson: Medium-Dark Skin Tone
👯🏾♂️ Men With Bunny Ears Partying, Type-5
🧜🏿 Merperson: Dark Skin Tone
👯🏿♂️ Men With Bunny Ears Partying, Type-6
🧜♀️ Mermaid
👯🏻♀️ Women With Bunny Ears Partying, Type-1-2
🧜🏻♀️ Mermaid: Light Skin Tone
👯🏼♀️ Women With Bunny Ears Partying, Type-3
🧜🏼♀️ Mermaid: Medium-Light Skin Tone
👯🏽♀️ Women With Bunny Ears Partying, Type-4
👯🏾♀️ Women With Bunny Ears Partying, Type-5
🧜🏽♀️ Mermaid: Medium Skin Tone
👯🏿♀️ Women With Bunny Ears Partying, Type-6
🧜🏾♀️ Mermaid: Medium-Dark Skin Tone
🧜🏿♀️ Mermaid: Dark Skin Tone
🧜♂️ Merman
🧜🏻♂️ Merman: Light Skin Tone
🧜🏼♂️ Merman: Medium-Light Skin Tone
👫🏻 Man and Woman Holding Hands, Type-1-2
🧜🏽♂️ Merman: Medium Skin Tone
👫🏼 Man and Woman Holding Hands, Type-3
👫🏽 Man and Woman Holding Hands, Type-4
🧜🏾♂️ Merman: Medium-Dark Skin Tone
👫🏾 Man and Woman Holding Hands, Type-5
👫🏿 Man and Woman Holding Hands, Type-6
🧜🏿♂️ Merman: Dark Skin Tone
👬🏻 Two Men Holding Hands, Type-1-2
🧝 Elf
👬🏼 Two Men Holding Hands, Type-3
👬🏽 Two Men Holding Hands, Type-4
🧝🏻 Elf: Light Skin Tone
👬🏾 Two Men Holding Hands, Type-5
🧝🏼 Elf: Medium-Light Skin Tone
👬🏿 Two Men Holding Hands, Type-6
🧝🏽 Elf: Medium Skin Tone
🧝🏾 Elf: Medium-Dark Skin Tone
👭🏻 Two Women Holding Hands, Type-1-2
🧝🏿 Elf: Dark Skin Tone
🧝♀️ Woman Elf
👭🏼 Two Women Holding Hands, Type-3
👭🏽 Two Women Holding Hands, Type-4
🧝🏻♀️ Woman Elf: Light Skin Tone
👭🏾 Two Women Holding Hands, Type-5
👭🏿 Two Women Holding Hands, Type-6
🧝🏼♀️ Woman Elf: Medium-Light Skin Tone
🧝🏽♀️ Woman Elf: Medium Skin Tone
🧝🏾♀️ Woman Elf: Medium-Dark Skin Tone
🧝🏿♀️ Woman Elf: Dark Skin Tone
🧝♂️ Man Elf
👪🏻 Family, Type-1-2
🧝🏻♂️ Man Elf: Light Skin Tone
👪🏼 Family, Type-3
👪🏽 Family, Type-4
🧝🏼♂️ Man Elf: Medium-Light Skin Tone
👪🏾 Family, Type-5
👪🏿 Family, Type-6
🧝🏽♂️ Man Elf: Medium Skin Tone
🧝🏾♂️ Man Elf: Medium-Dark Skin Tone
🧝🏿♂️ Man Elf: Dark Skin Tone
🧞 Genie
🧞♀️ Woman Genie
🧞♂️ Man Genie
🧟 Zombie
🧟♀️ Woman Zombie
🧟♂️ Man Zombie
🙍 Person Frowning
🙍🏻 Person Frowning: Light Skin Tone
🙍🏼 Person Frowning: Medium-Light Skin Tone
🙍🏽 Person Frowning: Medium Skin Tone
🙍🏾 Person Frowning: Medium-Dark Skin Tone
🙍🏿 Person Frowning: Dark Skin Tone
🙍♂️ Man Frowning
🙍🏻♂️ Man Frowning: Light Skin Tone
🏻 Light Skin Tone
🏼 Medium-Light Skin Tone
🙍🏼♂️ Man Frowning: Medium-Light Skin Tone
🏽 Medium Skin Tone
🙍🏽♂️ Man Frowning: Medium Skin Tone
🏾 Medium-Dark Skin Tone
🏿 Dark Skin Tone
🙍🏾♂️ Man Frowning: Medium-Dark Skin Tone
🙍🏿♂️ Man Frowning: Dark Skin Tone
🙍♀️ Woman Frowning
🙍🏻♀️ Woman Frowning: Light Skin Tone
🙍🏼♀️ Woman Frowning: Medium-Light Skin Tone
🙍🏽♀️ Woman Frowning: Medium Skin Tone
🙍🏾♀️ Woman Frowning: Medium-Dark Skin Tone
🙍🏿♀️ Woman Frowning: Dark Skin Tone
🙎 Person Pouting
🙎🏻 Person Pouting: Light Skin Tone
🙎🏼 Person Pouting: Medium-Light Skin Tone
🙎🏽 Person Pouting: Medium Skin Tone
🙎🏾 Person Pouting: Medium-Dark Skin Tone
🙎🏿 Person Pouting: Dark Skin Tone
🙎♂️ Man Pouting
🙎🏻♂️ Man Pouting: Light Skin Tone
🙎🏼♂️ Man Pouting: Medium-Light Skin Tone
🙎🏽♂️ Man Pouting: Medium Skin Tone
🙎🏾♂️ Man Pouting: Medium-Dark Skin Tone
🙎🏿♂️ Man Pouting: Dark Skin Tone
🙎♀️ Woman Pouting
🙎🏻♀️ Woman Pouting: Light Skin Tone
🙎🏼♀️ Woman Pouting: Medium-Light Skin Tone
🙎🏽♀️ Woman Pouting: Medium Skin Tone
🙎🏾♀️ Woman Pouting: Medium-Dark Skin Tone
🙎🏿♀️ Woman Pouting: Dark Skin Tone
🙅 Person Gesturing No
🙅🏻 Person Gesturing No: Light Skin Tone
🙅🏼 Person Gesturing No: Medium-Light Skin Tone
🙅🏽 Person Gesturing No: Medium Skin Tone
🙅🏾 Person Gesturing No: Medium-Dark Skin Tone
🙅🏿 Person Gesturing No: Dark Skin Tone
🙅♂️ Man Gesturing No
🙅🏻♂️ Man Gesturing No: Light Skin Tone
🙅🏼♂️ Man Gesturing No: Medium-Light Skin Tone
🙅🏽♂️ Man Gesturing No: Medium Skin Tone
🙅🏾♂️ Man Gesturing No: Medium-Dark Skin Tone
🙅🏿♂️ Man Gesturing No: Dark Skin Tone
🙅♀️ Woman Gesturing No
🙅🏻♀️ Woman Gesturing No: Light Skin Tone
🙅🏼♀️ Woman Gesturing No: Medium-Light Skin Tone
🙅🏽♀️ Woman Gesturing No: Medium Skin Tone
🙅🏾♀️ Woman Gesturing No: Medium-Dark Skin Tone
🙅🏿♀️ Woman Gesturing No: Dark Skin Tone
🙆 Person Gesturing OK
🙆🏻 Person Gesturing OK: Light Skin Tone
🙆🏼 Person Gesturing OK: Medium-Light Skin Tone
🙆🏽 Person Gesturing OK: Medium Skin Tone
🙆🏾 Person Gesturing OK: Medium-Dark Skin Tone
🙆🏿 Person Gesturing OK: Dark Skin Tone
🙆♂️ Man Gesturing OK
🙆🏻♂️ Man Gesturing OK: Light Skin Tone
🙆🏼♂️ Man Gesturing OK: Medium-Light Skin Tone
🙆🏽♂️ Man Gesturing OK: Medium Skin Tone
🙆🏾♂️ Man Gesturing OK: Medium-Dark Skin Tone
🙆🏿♂️ Man Gesturing OK: Dark Skin Tone
🙆♀️ Woman Gesturing OK
🙆🏻♀️ Woman Gesturing OK: Light Skin Tone
🙆🏼♀️ Woman Gesturing OK: Medium-Light Skin Tone
🙆🏽♀️ Woman Gesturing OK: Medium Skin Tone
🙆🏾♀️ Woman Gesturing OK: Medium-Dark Skin Tone
🙆🏿♀️ Woman Gesturing OK: Dark Skin Tone
💁 Person Tipping Hand
💁🏻 Person Tipping Hand: Light Skin Tone
💁🏼 Person Tipping Hand: Medium-Light Skin Tone
💁🏽 Person Tipping Hand: Medium Skin Tone
💁🏾 Person Tipping Hand: Medium-Dark Skin Tone
💁🏿 Person Tipping Hand: Dark Skin Tone
💁♂️ Man Tipping Hand
💁🏻♂️ Man Tipping Hand: Light Skin Tone
💁🏼♂️ Man Tipping Hand: Medium-Light Skin Tone
💁🏽♂️ Man Tipping Hand: Medium Skin Tone
💁🏾♂️ Man Tipping Hand: Medium-Dark Skin Tone
💁🏿♂️ Man Tipping Hand: Dark Skin Tone
💁♀️ Woman Tipping Hand
💁🏻♀️ Woman Tipping Hand: Light Skin Tone
💁🏼♀️ Woman Tipping Hand: Medium-Light Skin Tone
💁🏽♀️ Woman Tipping Hand: Medium Skin Tone
💁🏾♀️ Woman Tipping Hand: Medium-Dark Skin Tone
💁🏿♀️ Woman Tipping Hand: Dark Skin Tone
🙋 Person Raising Hand
🙋🏻 Person Raising Hand: Light Skin Tone
🙋🏼 Person Raising Hand: Medium-Light Skin Tone
🙋🏽 Person Raising Hand: Medium Skin Tone
🙋🏾 Person Raising Hand: Medium-Dark Skin Tone
🙋🏿 Person Raising Hand: Dark Skin Tone
🙋♂️ Man Raising Hand
🙋🏻♂️ Man Raising Hand: Light Skin Tone
🙋🏼♂️ Man Raising Hand: Medium-Light Skin Tone
🙋🏽♂️ Man Raising Hand: Medium Skin Tone
🙋🏾♂️ Man Raising Hand: Medium-Dark Skin Tone
🙋🏿♂️ Man Raising Hand: Dark Skin Tone
🙋♀️ Woman Raising Hand
🙋🏻♀️ Woman Raising Hand: Light Skin Tone
🙋🏼♀️ Woman Raising Hand: Medium-Light Skin Tone
🙋🏽♀️ Woman Raising Hand: Medium Skin Tone
🙋🏾♀️ Woman Raising Hand: Medium-Dark Skin Tone
🙋🏿♀️ Woman Raising Hand: Dark Skin Tone
🙇 Person Bowing
🙇🏻 Person Bowing: Light Skin Tone
🙇🏼 Person Bowing: Medium-Light Skin Tone
🙇🏽 Person Bowing: Medium Skin Tone
🙇🏾 Person Bowing: Medium-Dark Skin Tone
🙇🏿 Person Bowing: Dark Skin Tone
🙇♂️ Man Bowing
🙇🏻♂️ Man Bowing: Light Skin Tone
🤝🏻 Handshake, Type-1-2
🙇🏼♂️ Man Bowing: Medium-Light Skin Tone
🤝🏼 Handshake, Type-3
🤝🏽 Handshake, Type-4
🙇🏽♂️ Man Bowing: Medium Skin Tone
🤝🏾 Handshake, Type-5
🤝🏿 Handshake, Type-6
🙇🏾♂️ Man Bowing: Medium-Dark Skin Tone
🙇🏿♂️ Man Bowing: Dark Skin Tone
🙇♀️ Woman Bowing
🙇🏻♀️ Woman Bowing: Light Skin Tone
🙇🏼♀️ Woman Bowing: Medium-Light Skin Tone
🙇🏽♀️ Woman Bowing: Medium Skin Tone
🙇🏾♀️ Woman Bowing: Medium-Dark Skin Tone
🙇🏿♀️ Woman Bowing: Dark Skin Tone
🤦 Person Facepalming
🤦🏻 Person Facepalming: Light Skin Tone
🤦🏼 Person Facepalming: Medium-Light Skin Tone
🤦🏽 Person Facepalming: Medium Skin Tone
🤦🏾 Person Facepalming: Medium-Dark Skin Tone
🤦🏿 Person Facepalming: Dark Skin Tone
🤦♂️ Man Facepalming
🤦🏻♂️ Man Facepalming: Light Skin Tone
🤦🏼♂️ Man Facepalming: Medium-Light Skin Tone
🤦🏽♂️ Man Facepalming: Medium Skin Tone
🤦🏾♂️ Man Facepalming: Medium-Dark Skin Tone
🤦🏿♂️ Man Facepalming: Dark Skin Tone
🤦♀️ Woman Facepalming
🤦🏻♀️ Woman Facepalming: Light Skin Tone
🤦🏼♀️ Woman Facepalming: Medium-Light Skin Tone
🤦🏽♀️ Woman Facepalming: Medium Skin Tone
🤦🏾♀️ Woman Facepalming: Medium-Dark Skin Tone
🤦🏿♀️ Woman Facepalming: Dark Skin Tone
🤷 Person Shrugging
🤷🏻 Person Shrugging: Light Skin Tone
🤷🏼 Person Shrugging: Medium-Light Skin Tone
🤷🏽 Person Shrugging: Medium Skin Tone
🤷🏾 Person Shrugging: Medium-Dark Skin Tone
🤷🏿 Person Shrugging: Dark Skin Tone
🤷♂️ Man Shrugging
🤷🏻♂️ Man Shrugging: Light Skin Tone
🤷🏼♂️ Man Shrugging: Medium-Light Skin Tone
🤷🏽♂️ Man Shrugging: Medium Skin Tone
🤷🏾♂️ Man Shrugging: Medium-Dark Skin Tone
🤷🏿♂️ Man Shrugging: Dark Skin Tone
🤷♀️ Woman Shrugging
🤷🏻♀️ Woman Shrugging: Light Skin Tone
🤷🏼♀️ Woman Shrugging: Medium-Light Skin Tone
🤷🏽♀️ Woman Shrugging: Medium Skin Tone
🤷🏾♀️ Woman Shrugging: Medium-Dark Skin Tone
🤷🏿♀️ Woman Shrugging: Dark Skin Tone
💆 Person Getting Massage
💆🏻 Person Getting Massage: Light Skin Tone
💆🏼 Person Getting Massage: Medium-Light Skin Tone
💆🏽 Person Getting Massage: Medium Skin Tone
💆🏾 Person Getting Massage: Medium-Dark Skin Tone
💆🏿 Person Getting Massage: Dark Skin Tone
💆♂️ Man Getting Massage
💆🏻♂️ Man Getting Massage: Light Skin Tone
💆🏼♂️ Man Getting Massage: Medium-Light Skin Tone
💆🏽♂️ Man Getting Massage: Medium Skin Tone
💆🏾♂️ Man Getting Massage: Medium-Dark Skin Tone
💆🏿♂️ Man Getting Massage: Dark Skin Tone
💆♀️ Woman Getting Massage
💆🏻♀️ Woman Getting Massage: Light Skin Tone
💆🏼♀️ Woman Getting Massage: Medium-Light Skin Tone
💆🏽♀️ Woman Getting Massage: Medium Skin Tone
💆🏾♀️ Woman Getting Massage: Medium-Dark Skin Tone
💆🏿♀️ Woman Getting Massage: Dark Skin Tone
💇 Person Getting Haircut
💇🏻 Person Getting Haircut: Light Skin Tone
💇🏼 Person Getting Haircut: Medium-Light Skin Tone
💇🏽 Person Getting Haircut: Medium Skin Tone
💇🏾 Person Getting Haircut: Medium-Dark Skin Tone
💇🏿 Person Getting Haircut: Dark Skin Tone
💇♂️ Man Getting Haircut
💇🏻♂️ Man Getting Haircut: Light Skin Tone
💇🏼♂️ Man Getting Haircut: Medium-Light Skin Tone
💇🏽♂️ Man Getting Haircut: Medium Skin Tone
💇🏾♂️ Man Getting Haircut: Medium-Dark Skin Tone
💇🏿♂️ Man Getting Haircut: Dark Skin Tone
💇♀️ Woman Getting Haircut
💇🏻♀️ Woman Getting Haircut: Light Skin Tone
💇🏼♀️ Woman Getting Haircut: Medium-Light Skin Tone
💇🏽♀️ Woman Getting Haircut: Medium Skin Tone
💇🏾♀️ Woman Getting Haircut: Medium-Dark Skin Tone
💇🏿♀️ Woman Getting Haircut: Dark Skin Tone
🚶 Person Walking
🚶🏻 Person Walking: Light Skin Tone
🚶🏼 Person Walking: Medium-Light Skin Tone
🚶🏽 Person Walking: Medium Skin Tone
🚶🏾 Person Walking: Medium-Dark Skin Tone
🚶🏿 Person Walking: Dark Skin Tone
🚶♂️ Man Walking
🚶🏻♂️ Man Walking: Light Skin Tone
🚶🏼♂️ Man Walking: Medium-Light Skin Tone
🚶🏽♂️ Man Walking: Medium Skin Tone
🚶🏾♂️ Man Walking: Medium-Dark Skin Tone
🚶🏿♂️ Man Walking: Dark Skin Tone
🚶♀️ Woman Walking
🚶🏻♀️ Woman Walking: Light Skin Tone
🚶🏼♀️ Woman Walking: Medium-Light Skin Tone
🚶🏽♀️ Woman Walking: Medium Skin Tone
🚶🏾♀️ Woman Walking: Medium-Dark Skin Tone
🚶🏿♀️ Woman Walking: Dark Skin Tone
🏃 Person Running
🏃🏻 Person Running: Light Skin Tone
🏃🏼 Person Running: Medium-Light Skin Tone
🏃🏽 Person Running: Medium Skin Tone
🏃🏾 Person Running: Medium-Dark Skin Tone
🏃🏿 Person Running: Dark Skin Tone
🏃♂️ Man Running
🏃🏻♂️ Man Running: Light Skin Tone
🏃🏼♂️ Man Running: Medium-Light Skin Tone
🏃🏽♂️ Man Running: Medium Skin Tone
🏃🏾♂️ Man Running: Medium-Dark Skin Tone
🏃🏿♂️ Man Running: Dark Skin Tone
🏃♀️ Woman Running
🏃🏻♀️ Woman Running: Light Skin Tone
🏃🏼♀️ Woman Running: Medium-Light Skin Tone
🏃🏽♀️ Woman Running: Medium Skin Tone
🏃🏾♀️ Woman Running: Medium-Dark Skin Tone
🏃🏿♀️ Woman Running: Dark Skin Tone
💃 Woman Dancing
💃🏻 Woman Dancing: Light Skin Tone
💃🏼 Woman Dancing: Medium-Light Skin Tone
💃🏽 Woman Dancing: Medium Skin Tone
💃🏾 Woman Dancing: Medium-Dark Skin Tone
💃🏿 Woman Dancing: Dark Skin Tone
🕺 Man Dancing
🕺🏻 Man Dancing: Light Skin Tone
🕺🏼 Man Dancing: Medium-Light Skin Tone
🕺🏽 Man Dancing: Medium Skin Tone
🕺🏾 Man Dancing: Medium-Dark Skin Tone
🕺🏿 Man Dancing: Dark Skin Tone
👯 People With Bunny Ears Partying
👯♂️ Men With Bunny Ears Partying
👯♀️ Women With Bunny Ears Partying
🧖 Person in Steamy Room
🧖🏻 Person in Steamy Room: Light Skin Tone
🧖🏼 Person in Steamy Room: Medium-Light Skin Tone
🧖🏽 Person in Steamy Room: Medium Skin Tone
🧖🏾 Person in Steamy Room: Medium-Dark Skin Tone
🧖🏿 Person in Steamy Room: Dark Skin Tone
🧖♀️ Woman in Steamy Room
🧖🏻♀️ Woman in Steamy Room: Light Skin Tone
🧖🏼♀️ Woman in Steamy Room: Medium-Light Skin Tone
🧖🏽♀️ Woman in Steamy Room: Medium Skin Tone
🧖🏾♀️ Woman in Steamy Room: Medium-Dark Skin Tone
🧖🏿♀️ Woman in Steamy Room: Dark Skin Tone
🧖♂️ Man in Steamy Room
🧖🏻♂️ Man in Steamy Room: Light Skin Tone
🧖🏼♂️ Man in Steamy Room: Medium-Light Skin Tone
🧖🏽♂️ Man in Steamy Room: Medium Skin Tone
🧖🏾♂️ Man in Steamy Room: Medium-Dark Skin Tone
🧖🏿♂️ Man in Steamy Room: Dark Skin Tone
🧗 Person Climbing
🧗🏻 Person Climbing: Light Skin Tone
🧗🏼 Person Climbing: Medium-Light Skin Tone
🧗🏽 Person Climbing: Medium Skin Tone
🧗🏾 Person Climbing: Medium-Dark Skin Tone
🧗🏿 Person Climbing: Dark Skin Tone
🧗♀️ Woman Climbing
🧗🏻♀️ Woman Climbing: Light Skin Tone
🧗🏼♀️ Woman Climbing: Medium-Light Skin Tone
🧗🏽♀️ Woman Climbing: Medium Skin Tone
🧗🏾♀️ Woman Climbing: Medium-Dark Skin Tone
🧗🏿♀️ Woman Climbing: Dark Skin Tone
🧗♂️ Man Climbing
🧗🏻♂️ Man Climbing: Light Skin Tone
🧗🏼♂️ Man Climbing: Medium-Light Skin Tone
🧗🏽♂️ Man Climbing: Medium Skin Tone
🧗🏾♂️ Man Climbing: Medium-Dark Skin Tone
🧗🏿♂️ Man Climbing: Dark Skin Tone
🧘 Person in Lotus Position
🧘🏻 Person in Lotus Position: Light Skin Tone
🧘🏼 Person in Lotus Position: Medium-Light Skin Tone
🧘🏽 Person in Lotus Position: Medium Skin Tone
🧘🏾 Person in Lotus Position: Medium-Dark Skin Tone
🧘🏿 Person in Lotus Position: Dark Skin Tone
🧘♀️ Woman in Lotus Position
🧘🏻♀️ Woman in Lotus Position: Light Skin Tone
🧘🏼♀️ Woman in Lotus Position: Medium-Light Skin Tone
🧘🏽♀️ Woman in Lotus Position: Medium Skin Tone
🧘🏾♀️ Woman in Lotus Position: Medium-Dark Skin Tone
🧘🏿♀️ Woman in Lotus Position: Dark Skin Tone
🧘♂️ Man in Lotus Position
🧘🏻♂️ Man in Lotus Position: Light Skin Tone
🧘🏼♂️ Man in Lotus Position: Medium-Light Skin Tone
🧘🏽♂️ Man in Lotus Position: Medium Skin Tone
🧘🏾♂️ Man in Lotus Position: Medium-Dark Skin Tone
🧘🏿♂️ Man in Lotus Position: Dark Skin Tone
🛀 Person Taking Bath
🛀🏻 Person Taking Bath: Light Skin Tone
🛀🏼 Person Taking Bath: Medium-Light Skin Tone
🛀🏽 Person Taking Bath: Medium Skin Tone
🛀🏾 Person Taking Bath: Medium-Dark Skin Tone
🛀🏿 Person Taking Bath: Dark Skin Tone
🛌 Person in Bed
🛌🏻 Person in Bed: Light Skin Tone
🛌🏼 Person in Bed: Medium-Light Skin Tone
🛌🏽 Person in Bed: Medium Skin Tone
🛌🏾 Person in Bed: Medium-Dark Skin Tone
🛌🏿 Person in Bed: Dark Skin Tone
🕴 Man in Business Suit Levitating
🕴🏻 Man in Business Suit Levitating: Light Skin Tone
🕴🏼 Man in Business Suit Levitating: Medium-Light Skin Tone
🕴🏽 Man in Business Suit Levitating: Medium Skin Tone
🕴🏾 Man in Business Suit Levitating: Medium-Dark Skin Tone
🕴🏿 Man in Business Suit Levitating: Dark Skin Tone
🗣 Speaking Head
👤 Bust in Silhouette
👥 Busts in Silhouette
🤺 Person Fencing
🏇 Horse Racing
🏇🏻 Horse Racing: Light Skin Tone
🏇🏼 Horse Racing: Medium-Light Skin Tone
🏇🏽 Horse Racing: Medium Skin Tone
🏇🏾 Horse Racing: Medium-Dark Skin Tone
🏇🏿 Horse Racing: Dark Skin Tone
⛷ Skier
🏂 Snowboarder
🏂🏻 Snowboarder: Light Skin Tone
🏂🏼 Snowboarder: Medium-Light Skin Tone
🏂🏽 Snowboarder: Medium Skin Tone
🏂🏾 Snowboarder: Medium-Dark Skin Tone
🏂🏿 Snowboarder: Dark Skin Tone
🏌 Person Golfing
🏌🏻 Person Golfing: Light Skin Tone
🏌🏼 Person Golfing: Medium-Light Skin Tone
🏌🏽 Person Golfing: Medium Skin Tone
🏌🏾 Person Golfing: Medium-Dark Skin Tone
🏌🏿 Person Golfing: Dark Skin Tone
🏌️♂️ Man Golfing
🏌🏻♂️ Man Golfing: Light Skin Tone
🏌🏼♂️ Man Golfing: Medium-Light Skin Tone
🏌🏽♂️ Man Golfing: Medium Skin Tone
🏌🏾♂️ Man Golfing: Medium-Dark Skin Tone
🏌🏿♂️ Man Golfing: Dark Skin Tone
🏌️♀️ Woman Golfing
🏌🏻♀️ Woman Golfing: Light Skin Tone
🏌🏼♀️ Woman Golfing: Medium-Light Skin Tone
🏌🏽♀️ Woman Golfing: Medium Skin Tone
🏌🏾♀️ Woman Golfing: Medium-Dark Skin Tone
🏌🏿♀️ Woman Golfing: Dark Skin Tone
🏄 Person Surfing
🏄🏻 Person Surfing: Light Skin Tone
🏄🏼 Person Surfing: Medium-Light Skin Tone
🏄🏽 Person Surfing: Medium Skin Tone
🏄🏾 Person Surfing: Medium-Dark Skin Tone
🏄🏿 Person Surfing: Dark Skin Tone
🏄♂️ Man Surfing
🏄🏻♂️ Man Surfing: Light Skin Tone
🏄🏼♂️ Man Surfing: Medium-Light Skin Tone
🏄🏽♂️ Man Surfing: Medium Skin Tone
🏄🏾♂️ Man Surfing: Medium-Dark Skin Tone
🏄🏿♂️ Man Surfing: Dark Skin Tone
🏄♀️ Woman Surfing
🏄🏻♀️ Woman Surfing: Light Skin Tone
🏄🏼♀️ Woman Surfing: Medium-Light Skin Tone
🏄🏽♀️ Woman Surfing: Medium Skin Tone
🏄🏾♀️ Woman Surfing: Medium-Dark Skin Tone
🏄🏿♀️ Woman Surfing: Dark Skin Tone
🚣 Person Rowing Boat
🚣🏻 Person Rowing Boat: Light Skin Tone
🚣🏼 Person Rowing Boat: Medium-Light Skin Tone
🚣🏽 Person Rowing Boat: Medium Skin Tone
🚣🏾 Person Rowing Boat: Medium-Dark Skin Tone
🚣🏿 Person Rowing Boat: Dark Skin Tone
🚣♂️ Man Rowing Boat
🚣🏻♂️ Man Rowing Boat: Light Skin Tone
🚣🏼♂️ Man Rowing Boat: Medium-Light Skin Tone
🚣🏽♂️ Man Rowing Boat: Medium Skin Tone
🚣🏾♂️ Man Rowing Boat: Medium-Dark Skin Tone
🚣🏿♂️ Man Rowing Boat: Dark Skin Tone
🚣♀️ Woman Rowing Boat
🚣🏻♀️ Woman Rowing Boat: Light Skin Tone
🚣🏼♀️ Woman Rowing Boat: Medium-Light Skin Tone
🚣🏽♀️ Woman Rowing Boat: Medium Skin Tone
🚣🏾♀️ Woman Rowing Boat: Medium-Dark Skin Tone
🚣🏿♀️ Woman Rowing Boat: Dark Skin Tone
🏊 Person Swimming
🏊🏻 Person Swimming: Light Skin Tone
🏊🏼 Person Swimming: Medium-Light Skin Tone
🏊🏽 Person Swimming: Medium Skin Tone
🏊🏾 Person Swimming: Medium-Dark Skin Tone
🏊🏿 Person Swimming: Dark Skin Tone
🏊♂️ Man Swimming
🏊🏻♂️ Man Swimming: Light Skin Tone
🏊🏼♂️ Man Swimming: Medium-Light Skin Tone
🏊🏽♂️ Man Swimming: Medium Skin Tone
🏊🏾♂️ Man Swimming: Medium-Dark Skin Tone
🏊🏿♂️ Man Swimming: Dark Skin Tone
🏊♀️ Woman Swimming
🏊🏻♀️ Woman Swimming: Light Skin Tone
🏊🏼♀️ Woman Swimming: Medium-Light Skin Tone
🏊🏽♀️ Woman Swimming: Medium Skin Tone
🏊🏾♀️ Woman Swimming: Medium-Dark Skin Tone
🏊🏿♀️ Woman Swimming: Dark Skin Tone
⛹ Person Bouncing Ball
⛹🏻 Person Bouncing Ball: Light Skin Tone
⛹🏼 Person Bouncing Ball: Medium-Light Skin Tone
⛹🏽 Person Bouncing Ball: Medium Skin Tone
⛹🏾 Person Bouncing Ball: Medium-Dark Skin Tone
⛹🏿 Person Bouncing Ball: Dark Skin Tone
⛹️♂️ Man Bouncing Ball
⛹🏻♂️ Man Bouncing Ball: Light Skin Tone
⛹🏼♂️ Man Bouncing Ball: Medium-Light Skin Tone
⛹🏽♂️ Man Bouncing Ball: Medium Skin Tone
⛹🏾♂️ Man Bouncing Ball: Medium-Dark Skin Tone
⛹🏿♂️ Man Bouncing Ball: Dark Skin Tone
⛹️♀️ Woman Bouncing Ball
⛹🏻♀️ Woman Bouncing Ball: Light Skin Tone
⛹🏼♀️ Woman Bouncing Ball: Medium-Light Skin Tone
⛹🏽♀️ Woman Bouncing Ball: Medium Skin Tone
⛹🏾♀️ Woman Bouncing Ball: Medium-Dark Skin Tone
⛹🏿♀️ Woman Bouncing Ball: Dark Skin Tone
🏋 Person Lifting Weights
🏋🏻 Person Lifting Weights: Light Skin Tone
🏋🏼 Person Lifting Weights: Medium-Light Skin Tone
🏋🏽 Person Lifting Weights: Medium Skin Tone
🏋🏾 Person Lifting Weights: Medium-Dark Skin Tone
🏋🏿 Person Lifting Weights: Dark Skin Tone
🏋️♂️ Man Lifting Weights
🏋🏻♂️ Man Lifting Weights: Light Skin Tone
🏋🏼♂️ Man Lifting Weights: Medium-Light Skin Tone
🏋🏽♂️ Man Lifting Weights: Medium Skin Tone
🏋🏾♂️ Man Lifting Weights: Medium-Dark Skin Tone
🏋🏿♂️ Man Lifting Weights: Dark Skin Tone
🏋️♀️ Woman Lifting Weights
🏋🏻♀️ Woman Lifting Weights: Light Skin Tone
🏋🏼♀️ Woman Lifting Weights: Medium-Light Skin Tone
🏋🏽♀️ Woman Lifting Weights: Medium Skin Tone
🏋🏾♀️ Woman Lifting Weights: Medium-Dark Skin Tone
🏋🏿♀️ Woman Lifting Weights: Dark Skin Tone
🚴 Person Biking
🚴🏻 Person Biking: Light Skin Tone
🚴🏼 Person Biking: Medium-Light Skin Tone
🚴🏽 Person Biking: Medium Skin Tone
🚴🏾 Person Biking: Medium-Dark Skin Tone
🚴🏿 Person Biking: Dark Skin Tone
🚴♂️ Man Biking
🚴🏻♂️ Man Biking: Light Skin Tone
🚴🏼♂️ Man Biking: Medium-Light Skin Tone
🚴🏽♂️ Man Biking: Medium Skin Tone
🚴🏾♂️ Man Biking: Medium-Dark Skin Tone
🚴🏿♂️ Man Biking: Dark Skin Tone
🚴♀️ Woman Biking
🚴🏻♀️ Woman Biking: Light Skin Tone
🚴🏼♀️ Woman Biking: Medium-Light Skin Tone
🚴🏽♀️ Woman Biking: Medium Skin Tone
🚴🏾♀️ Woman Biking: Medium-Dark Skin Tone
🚴🏿♀️ Woman Biking: Dark Skin Tone
🚵 Person Mountain Biking
🚵🏻 Person Mountain Biking: Light Skin Tone
🚵🏼 Person Mountain Biking: Medium-Light Skin Tone
🚵🏽 Person Mountain Biking: Medium Skin Tone
🚵🏾 Person Mountain Biking: Medium-Dark Skin Tone
🚵🏿 Person Mountain Biking: Dark Skin Tone
🚵♂️ Man Mountain Biking
🚵🏻♂️ Man Mountain Biking: Light Skin Tone
🚵🏼♂️ Man Mountain Biking: Medium-Light Skin Tone
🚵🏽♂️ Man Mountain Biking: Medium Skin Tone
🚵🏾♂️ Man Mountain Biking: Medium-Dark Skin Tone
🚵🏿♂️ Man Mountain Biking: Dark Skin Tone
🚵♀️ Woman Mountain Biking
🚵🏻♀️ Woman Mountain Biking: Light Skin Tone
🚵🏼♀️ Woman Mountain Biking: Medium-Light Skin Tone
🚵🏽♀️ Woman Mountain Biking: Medium Skin Tone
🚵🏾♀️ Woman Mountain Biking: Medium-Dark Skin Tone
🚵🏿♀️ Woman Mountain Biking: Dark Skin Tone
🏎 Racing Car
🏍 Motorcycle
🤸 Person Cartwheeling
🤸🏻 Person Cartwheeling: Light Skin Tone
🤸🏼 Person Cartwheeling: Medium-Light Skin Tone
🤸🏽 Person Cartwheeling: Medium Skin Tone
🤸🏾 Person Cartwheeling: Medium-Dark Skin Tone
🤸🏿 Person Cartwheeling: Dark Skin Tone
🤸♂️ Man Cartwheeling
🤸🏻♂️ Man Cartwheeling: Light Skin Tone
🤸🏼♂️ Man Cartwheeling: Medium-Light Skin Tone
🤸🏽♂️ Man Cartwheeling: Medium Skin Tone
🤸🏾♂️ Man Cartwheeling: Medium-Dark Skin Tone
🤸🏿♂️ Man Cartwheeling: Dark Skin Tone
🤸♀️ Woman Cartwheeling
🤸🏻♀️ Woman Cartwheeling: Light Skin Tone
🤸🏼♀️ Woman Cartwheeling: Medium-Light Skin Tone
🤸🏽♀️ Woman Cartwheeling: Medium Skin Tone
🤸🏾♀️ Woman Cartwheeling: Medium-Dark Skin Tone
🤸🏿♀️ Woman Cartwheeling: Dark Skin Tone
🤼 People Wrestling
🤼♂️ Men Wrestling
🤼♀️ Women Wrestling
🤽 Person Playing Water Polo
🤽🏻 Person Playing Water Polo: Light Skin Tone
🤽🏼 Person Playing Water Polo: Medium-Light Skin Tone
🤽🏽 Person Playing Water Polo: Medium Skin Tone
🤽🏾 Person Playing Water Polo: Medium-Dark Skin Tone
🤽🏿 Person Playing Water Polo: Dark Skin Tone
🤽♂️ Man Playing Water Polo
🤽🏻♂️ Man Playing Water Polo: Light Skin Tone
🤽🏼♂️ Man Playing Water Polo: Medium-Light Skin Tone
🤽🏽♂️ Man Playing Water Polo: Medium Skin Tone
🤽🏾♂️ Man Playing Water Polo: Medium-Dark Skin Tone
🤽🏿♂️ Man Playing Water Polo: Dark Skin Tone
🤽♀️ Woman Playing Water Polo
🤽🏻♀️ Woman Playing Water Polo: Light Skin Tone
🤽🏼♀️ Woman Playing Water Polo: Medium-Light Skin Tone
🤽🏽♀️ Woman Playing Water Polo: Medium Skin Tone
🤽🏾♀️ Woman Playing Water Polo: Medium-Dark Skin Tone
🤽🏿♀️ Woman Playing Water Polo: Dark Skin Tone
🤾 Person Playing Handball
🤾🏻 Person Playing Handball: Light Skin Tone
🤾🏼 Person Playing Handball: Medium-Light Skin Tone
🤾🏽 Person Playing Handball: Medium Skin Tone
🤾🏾 Person Playing Handball: Medium-Dark Skin Tone
🤾🏿 Person Playing Handball: Dark Skin Tone
🤾♂️ Man Playing Handball
🤾🏻♂️ Man Playing Handball: Light Skin Tone
🤾🏼♂️ Man Playing Handball: Medium-Light Skin Tone
🤾🏽♂️ Man Playing Handball: Medium Skin Tone
🤾🏾♂️ Man Playing Handball: Medium-Dark Skin Tone
🤾🏿♂️ Man Playing Handball: Dark Skin Tone
🤾♀️ Woman Playing Handball
🤾🏻♀️ Woman Playing Handball: Light Skin Tone
🤾🏼♀️ Woman Playing Handball: Medium-Light Skin Tone
🤾🏽♀️ Woman Playing Handball: Medium Skin Tone
🤾🏾♀️ Woman Playing Handball: Medium-Dark Skin Tone
🤾🏿♀️ Woman Playing Handball: Dark Skin Tone
🤹 Person Juggling
🤹🏻 Person Juggling: Light Skin Tone
🤹🏼 Person Juggling: Medium-Light Skin Tone
🤹🏽 Person Juggling: Medium Skin Tone
🤹🏾 Person Juggling: Medium-Dark Skin Tone
🤹🏿 Person Juggling: Dark Skin Tone
🤹♂️ Man Juggling
🤹🏻♂️ Man Juggling: Light Skin Tone
🤹🏼♂️ Man Juggling: Medium-Light Skin Tone
🤹🏽♂️ Man Juggling: Medium Skin Tone
🤹🏾♂️ Man Juggling: Medium-Dark Skin Tone
🤹🏿♂️ Man Juggling: Dark Skin Tone
🤹♀️ Woman Juggling
🤹🏻♀️ Woman Juggling: Light Skin Tone
🤹🏼♀️ Woman Juggling: Medium-Light Skin Tone
🤹🏽♀️ Woman Juggling: Medium Skin Tone
🤹🏾♀️ Woman Juggling: Medium-Dark Skin Tone
🤹🏿♀️ Woman Juggling: Dark Skin Tone
🤼🏻 Wrestlers, Type-1-2
🤼🏼 Wrestlers, Type-3
👫 Man and Woman Holding Hands
🤼🏽 Wrestlers, Type-4
👬 Two Men Holding Hands
🤼🏾 Wrestlers, Type-5
👭 Two Women Holding Hands
🤼🏿 Wrestlers, Type-6
💏 Kiss
👩❤️💋👨 Kiss: Woman, Man
🤼🏻♂️ Men Wrestling, Type-1-2
🤼🏼♂️ Men Wrestling, Type-3
🤼🏽♂️ Men Wrestling, Type-4
👨❤️💋👨 Kiss: Man, Man
🤼🏾♂️ Men Wrestling, Type-5
🤼🏿♂️ Men Wrestling, Type-6
👩❤️💋👩 Kiss: Woman, Woman
🤼🏻♀️ Women Wrestling, Type-1-2
💑 Couple With Heart
🤼🏼♀️ Women Wrestling, Type-3
👩❤️👨 Couple With Heart: Woman, Man
🤼🏽♀️ Women Wrestling, Type-4
🤼🏾♀️ Women Wrestling, Type-5
👨❤️👨 Couple With Heart: Man, Man
🤼🏿♀️ Women Wrestling, Type-6
👩❤️👩 Couple With Heart: Woman, Woman
👪 Family
👨👩👦 Family: Man, Woman, Boy
👨👩👧 Family: Man, Woman, Girl
👨👩👧👦 Family: Man, Woman, Girl, Boy
👨👩👦👦 Family: Man, Woman, Boy, Boy
👨👩👧👧 Family: Man, Woman, Girl, Girl
👨👨👦 Family: Man, Man, Boy
👨👨👧 Family: Man, Man, Girl
👨👨👧👦 Family: Man, Man, Girl, Boy
👨👨👦👦 Family: Man, Man, Boy, Boy
👨👨👧👧 Family: Man, Man, Girl, Girl
👩👩👦 Family: Woman, Woman, Boy
👩👩👧 Family: Woman, Woman, Girl
👩👩👧👦 Family: Woman, Woman, Girl, Boy
👩👩👦👦 Family: Woman, Woman, Boy, Boy
👩👩👧👧 Family: Woman, Woman, Girl, Girl
👨👦 Family: Man, Boy
👨👦👦 Family: Man, Boy, Boy
👨👧 Family: Man, Girl
👨👧👦 Family: Man, Girl, Boy
👨👧👧 Family: Man, Girl, Girl
👩👦 Family: Woman, Boy
👩👦👦 Family: Woman, Boy, Boy
👩👧 Family: Woman, Girl
👩👧👦 Family: Woman, Girl, Boy
👩👧👧 Family: Woman, Girl, Girl
🤳 Selfie
🤳🏻 Selfie: Light Skin Tone
🤳🏼 Selfie: Medium-Light Skin Tone
🤳🏽 Selfie: Medium Skin Tone
🤳🏾 Selfie: Medium-Dark Skin Tone
🤳🏿 Selfie: Dark Skin Tone
💪 Flexed Biceps
💪🏻 Flexed Biceps: Light Skin Tone
💪🏼 Flexed Biceps: Medium-Light Skin Tone
💪🏽 Flexed Biceps: Medium Skin Tone
💪🏾 Flexed Biceps: Medium-Dark Skin Tone
💪🏿 Flexed Biceps: Dark Skin Tone
👈 Backhand Index Pointing Left
👈🏻 Backhand Index Pointing Left: Light Skin Tone
👈🏼 Backhand Index Pointing Left: Medium-Light Skin Tone
👈🏽 Backhand Index Pointing Left: Medium Skin Tone
👈🏾 Backhand Index Pointing Left: Medium-Dark Skin Tone
👈🏿 Backhand Index Pointing Left: Dark Skin Tone
👉 Backhand Index Pointing Right
👉🏻 Backhand Index Pointing Right: Light Skin Tone
👉🏼 Backhand Index Pointing Right: Medium-Light Skin Tone
👉🏽 Backhand Index Pointing Right: Medium Skin Tone
👉🏾 Backhand Index Pointing Right: Medium-Dark Skin Tone
👉🏿 Backhand Index Pointing Right: Dark Skin Tone
☝ Index Pointing Up
☝🏻 Index Pointing Up: Light Skin Tone
☝🏼 Index Pointing Up: Medium-Light Skin Tone
☝🏽 Index Pointing Up: Medium Skin Tone
☝🏾 Index Pointing Up: Medium-Dark Skin Tone
☝🏿 Index Pointing Up: Dark Skin Tone
👆 Backhand Index Pointing Up
👆🏻 Backhand Index Pointing Up: Light Skin Tone
👆🏼 Backhand Index Pointing Up: Medium-Light Skin Tone
👆🏽 Backhand Index Pointing Up: Medium Skin Tone
👆🏾 Backhand Index Pointing Up: Medium-Dark Skin Tone
👆🏿 Backhand Index Pointing Up: Dark Skin Tone
🖕 Middle Finger
🖕🏻 Middle Finger: Light Skin Tone
🖕🏼 Middle Finger: Medium-Light Skin Tone
🖕🏽 Middle Finger: Medium Skin Tone
🖕🏾 Middle Finger: Medium-Dark Skin Tone
🖕🏿 Middle Finger: Dark Skin Tone
👇 Backhand Index Pointing Down
👇🏻 Backhand Index Pointing Down: Light Skin Tone
👇🏼 Backhand Index Pointing Down: Medium-Light Skin Tone
👇🏽 Backhand Index Pointing Down: Medium Skin Tone
👇🏾 Backhand Index Pointing Down: Medium-Dark Skin Tone
👇🏿 Backhand Index Pointing Down: Dark Skin Tone
✌ Victory Hand
✌🏻 Victory Hand: Light Skin Tone
✌🏼 Victory Hand: Medium-Light Skin Tone
✌🏽 Victory Hand: Medium Skin Tone
✌🏾 Victory Hand: Medium-Dark Skin Tone
✌🏿 Victory Hand: Dark Skin Tone
🤞 Crossed Fingers
🤞🏻 Crossed Fingers: Light Skin Tone
🤞🏼 Crossed Fingers: Medium-Light Skin Tone
🤞🏽 Crossed Fingers: Medium Skin Tone
🤞🏾 Crossed Fingers: Medium-Dark Skin Tone
🤞🏿 Crossed Fingers: Dark Skin Tone
🖖 Vulcan Salute
🖖🏻 Vulcan Salute: Light Skin Tone
🖖🏼 Vulcan Salute: Medium-Light Skin Tone
🖖🏽 Vulcan Salute: Medium Skin Tone
🖖🏾 Vulcan Salute: Medium-Dark Skin Tone
🖖🏿 Vulcan Salute: Dark Skin Tone
🤘 Sign of the Horns
🤘🏻 Sign of the Horns: Light Skin Tone
🤘🏼 Sign of the Horns: Medium-Light Skin Tone
🤘🏽 Sign of the Horns: Medium Skin Tone
🤘🏾 Sign of the Horns: Medium-Dark Skin Tone
🤘🏿 Sign of the Horns: Dark Skin Tone
🤙 Call Me Hand
🤙🏻 Call Me Hand: Light Skin Tone
🤙🏼 Call Me Hand: Medium-Light Skin Tone
🤙🏽 Call Me Hand: Medium Skin Tone
🤙🏾 Call Me Hand: Medium-Dark Skin Tone
🤙🏿 Call Me Hand: Dark Skin Tone
🖐 Raised Hand With Fingers Splayed
🖐🏻 Raised Hand With Fingers Splayed: Light Skin Tone
🖐🏼 Raised Hand With Fingers Splayed: Medium-Light Skin Tone
🖐🏽 Raised Hand With Fingers Splayed: Medium Skin Tone
🖐🏾 Raised Hand With Fingers Splayed: Medium-Dark Skin Tone
🖐🏿 Raised Hand With Fingers Splayed: Dark Skin Tone
✋ Raised Hand
✋🏻 Raised Hand: Light Skin Tone
✋🏼 Raised Hand: Medium-Light Skin Tone
✋🏽 Raised Hand: Medium Skin Tone
✋🏾 Raised Hand: Medium-Dark Skin Tone
✋🏿 Raised Hand: Dark Skin Tone
👌 OK Hand
👌🏻 OK Hand: Light Skin Tone
👌🏼 OK Hand: Medium-Light Skin Tone
👌🏽 OK Hand: Medium Skin Tone
👌🏾 OK Hand: Medium-Dark Skin Tone
👌🏿 OK Hand: Dark Skin Tone
👍 Thumbs Up
👍🏻 Thumbs Up: Light Skin Tone
👍🏼 Thumbs Up: Medium-Light Skin Tone
👍🏽 Thumbs Up: Medium Skin Tone
👍🏾 Thumbs Up: Medium-Dark Skin Tone
👍🏿 Thumbs Up: Dark Skin Tone
👎 Thumbs Down
👎🏻 Thumbs Down: Light Skin Tone
👎🏼 Thumbs Down: Medium-Light Skin Tone
👎🏽 Thumbs Down: Medium Skin Tone
👎🏾 Thumbs Down: Medium-Dark Skin Tone
👎🏿 Thumbs Down: Dark Skin Tone
✊ Raised Fist
✊🏻 Raised Fist: Light Skin Tone
✊🏼 Raised Fist: Medium-Light Skin Tone
✊🏽 Raised Fist: Medium Skin Tone
✊🏾 Raised Fist: Medium-Dark Skin Tone
✊🏿 Raised Fist: Dark Skin Tone
👊 Oncoming Fist
👊🏻 Oncoming Fist: Light Skin Tone
👊🏼 Oncoming Fist: Medium-Light Skin Tone
👊🏽 Oncoming Fist: Medium Skin Tone
👊🏾 Oncoming Fist: Medium-Dark Skin Tone
👊🏿 Oncoming Fist: Dark Skin Tone
🤛 Left-Facing Fist
🤛🏻 Left-Facing Fist: Light Skin Tone
🤛🏼 Left-Facing Fist: Medium-Light Skin Tone
🤛🏽 Left-Facing Fist: Medium Skin Tone
🤛🏾 Left-Facing Fist: Medium-Dark Skin Tone
🤛🏿 Left-Facing Fist: Dark Skin Tone
🤜 Right-Facing Fist
🤜🏻 Right-Facing Fist: Light Skin Tone
🤜🏼 Right-Facing Fist: Medium-Light Skin Tone
🤜🏽 Right-Facing Fist: Medium Skin Tone
🤜🏾 Right-Facing Fist: Medium-Dark Skin Tone
🤜🏿 Right-Facing Fist: Dark Skin Tone
🤚 Raised Back of Hand
🤚🏻 Raised Back of Hand: Light Skin Tone
🤚🏼 Raised Back of Hand: Medium-Light Skin Tone
🤚🏽 Raised Back of Hand: Medium Skin Tone
🤚🏾 Raised Back of Hand: Medium-Dark Skin Tone
🤚🏿 Raised Back of Hand: Dark Skin Tone
👋 Waving Hand
👋🏻 Waving Hand: Light Skin Tone
👋🏼 Waving Hand: Medium-Light Skin Tone
👋🏽 Waving Hand: Medium Skin Tone
👋🏾 Waving Hand: Medium-Dark Skin Tone
👋🏿 Waving Hand: Dark Skin Tone
🤟 Love-You Gesture
🤟🏻 Love-You Gesture: Light Skin Tone
🤟🏼 Love-You Gesture: Medium-Light Skin Tone
🤟🏽 Love-You Gesture: Medium Skin Tone
🤟🏾 Love-You Gesture: Medium-Dark Skin Tone
🤟🏿 Love-You Gesture: Dark Skin Tone
✍ Writing Hand
✍🏻 Writing Hand: Light Skin Tone
✍🏼 Writing Hand: Medium-Light Skin Tone
✍🏽 Writing Hand: Medium Skin Tone
✍🏾 Writing Hand: Medium-Dark Skin Tone
✍🏿 Writing Hand: Dark Skin Tone
👏 Clapping Hands
👏🏻 Clapping Hands: Light Skin Tone
👏🏼 Clapping Hands: Medium-Light Skin Tone
👏🏽 Clapping Hands: Medium Skin Tone
👏🏾 Clapping Hands: Medium-Dark Skin Tone
👏🏿 Clapping Hands: Dark Skin Tone
👐 Open Hands
👐🏻 Open Hands: Light Skin Tone
👐🏼 Open Hands: Medium-Light Skin Tone
👐🏽 Open Hands: Medium Skin Tone
👐🏾 Open Hands: Medium-Dark Skin Tone
👐🏿 Open Hands: Dark Skin Tone
🙌 Raising Hands
🙌🏻 Raising Hands: Light Skin Tone
🙌🏼 Raising Hands: Medium-Light Skin Tone
🙌🏽 Raising Hands: Medium Skin Tone
🙌🏾 Raising Hands: Medium-Dark Skin Tone
🙌🏿 Raising Hands: Dark Skin Tone
🤲 Palms Up Together
🤲🏻 Palms Up Together: Light Skin Tone
🤲🏼 Palms Up Together: Medium-Light Skin Tone
🤲🏽 Palms Up Together: Medium Skin Tone
🤲🏾 Palms Up Together: Medium-Dark Skin Tone
🤲🏿 Palms Up Together: Dark Skin Tone
🙏 Folded Hands
🙏🏻 Folded Hands: Light Skin Tone
🙏🏼 Folded Hands: Medium-Light Skin Tone
🙏🏽 Folded Hands: Medium Skin Tone
🙏🏾 Folded Hands: Medium-Dark Skin Tone
🙏🏿 Folded Hands: Dark Skin Tone
🤝 Handshake
💅 Nail Polish
💅🏻 Nail Polish: Light Skin Tone
💅🏼 Nail Polish: Medium-Light Skin Tone
💅🏽 Nail Polish: Medium Skin Tone
💅🏾 Nail Polish: Medium-Dark Skin Tone
💅🏿 Nail Polish: Dark Skin Tone
👂 Ear
👂🏻 Ear: Light Skin Tone
👂🏼 Ear: Medium-Light Skin Tone
👂🏽 Ear: Medium Skin Tone
👂🏾 Ear: Medium-Dark Skin Tone
👂🏿 Ear: Dark Skin Tone
👃 Nose
👃🏻 Nose: Light Skin Tone
👃🏼 Nose: Medium-Light Skin Tone
👃🏽 Nose: Medium Skin Tone
👃🏾 Nose: Medium-Dark Skin Tone
👃🏿 Nose: Dark Skin Tone
👣 Footprints
👀 Eyes
👁 Eye
👁️🗨️ Eye in Speech Bubble
🧠 Brain
👅 Tongue
👄 Mouth
💋 Kiss Mark
💘 Heart With Arrow
❤ Red Heart
💓 Beating Heart
💔 Broken Heart
💕 Two Hearts
💖 Sparkling Heart
💗 Growing Heart
💙 Blue Heart
💚 Green Heart
💛 Yellow Heart
🧡 Orange Heart
💜 Purple Heart
🖤 Black Heart
💝 Heart With Ribbon
💞 Revolving Hearts
💟 Heart Decoration
❣ Heavy Heart Exclamation
💌 Love Letter
💤 Zzz
💢 Anger Symbol
💣 Bomb
💥 Collision
💦 Sweat Droplets
💨 Dashing Away
💫 Dizzy
💬 Speech Balloon
🗨 Left Speech Bubble
🗯 Right Anger Bubble
💭 Thought Balloon
🕳 Hole
👓 Glasses
🕶 Sunglasses
👔 Necktie
👕 T-Shirt
👖 Jeans
🧣 Scarf
🧤 Gloves
🧥 Coat
🧦 Socks
👗 Dress
👘 Kimono
👙 Bikini
👚 Woman’s Clothes
👛 Purse
👜 Handbag
👝 Clutch Bag
🛍 Shopping Bags
🎒 School Backpack
👞 Man’s Shoe
👟 Running Shoe
👠 High-Heeled Shoe
👡 Woman’s Sandal
👢 Woman’s Boot
👑 Crown
👒 Woman’s Hat
🎩 Top Hat
🎓 Graduation Cap
🧢 Billed Cap
⛑ Rescue Worker’s Helmet
📿 Prayer Beads
💄 Lipstick
💍 Ring
💎 Gem Stone
🐵 Monkey Face
🐒 Monkey
🦍 Gorilla
🐶 Dog Face
🐕 Dog
🐩 Poodle
🐺 Wolf Face
🦊 Fox Face
🐱 Cat Face
🐈 Cat
🦁 Lion Face
🐯 Tiger Face
🐅 Tiger
🐆 Leopard
🐴 Horse Face
🐎 Horse
🦄 Unicorn Face
🦓 Zebra
🦌 Deer
🐮 Cow Face
🐂 Ox
🐃 Water Buffalo
🐄 Cow
🐷 Pig Face
🐖 Pig
🐗 Boar
🐽 Pig Nose
🐏 Ram
🐑 Ewe
🐐 Goat
🐪 Camel
🐫 Two-Hump Camel
🦒 Giraffe
🐘 Elephant
🦏 Rhinoceros
🐭 Mouse Face
🐁 Mouse
🐀 Rat
🐹 Hamster Face
🐰 Rabbit Face
🐇 Rabbit
🐿 Chipmunk
🦔 Hedgehog
🦇 Bat
🐻 Bear Face
🐨 Koala
🐼 Panda Face
🐾 Paw Prints
🦃 Turkey
🐔 Chicken
🐓 Rooster
🐣 Hatching Chick
🐤 Baby Chick
🐥 Front-Facing Baby Chick
🐦 Bird
🐧 Penguin
🕊 Dove
🦅 Eagle
🦆 Duck
🦉 Owl
🐸 Frog Face
🐊 Crocodile
🐢 Turtle
🦎 Lizard
🐍 Snake
🐲 Dragon Face
🐉 Dragon
🦕 Sauropod
🦖 T-Rex
🐳 Spouting Whale
🐋 Whale
🐬 Dolphin
🐟 Fish
🐠 Tropical Fish
🐡 Blowfish
🦈 Shark
🐙 Octopus
🐚 Spiral Shell
🦀 Crab
🦐 Shrimp
🦑 Squid
🐌 Snail
🦋 Butterfly
🐛 Bug
🐜 Ant
🐝 Honeybee
🐞 Lady Beetle
🦗 Cricket
🕷 Spider
🕸 Spider Web
🦂 Scorpion
💐 Bouquet
🌸 Cherry Blossom
💮 White Flower
🏵 Rosette
🌹 Rose
🥀 Wilted Flower
🌺 Hibiscus
🌻 Sunflower
🌼 Blossom
🌷 Tulip
🌱 Seedling
🌲 Evergreen Tree
🌳 Deciduous Tree
🌴 Palm Tree
🌵 Cactus
🌾 Sheaf of Rice
🌿 Herb
☘ Shamrock
🍀 Four Leaf Clover
🍁 Maple Leaf
🍂 Fallen Leaf
🍃 Leaf Fluttering in Wind
🍇 Grapes
🍈 Melon
🍉 Watermelon
🍊 Tangerine
🍋 Lemon
🍌 Banana
🍍 Pineapple
🍎 Red Apple
🍏 Green Apple
🍐 Pear
🍑 Peach
🍒 Cherries
🍓 Strawberry
🥝 Kiwi Fruit
🍅 Tomato
🥥 Coconut
🥑 Avocado
🍆 Eggplant
🥔 Potato
🥕 Carrot
🌽 Ear of Corn
🌶 Hot Pepper
🥒 Cucumber
🥦 Broccoli
🍄 Mushroom
🥜 Peanuts
🌰 Chestnut
🍞 Bread
🥐 Croissant
🥖 Baguette Bread
🥨 Pretzel
🥞 Pancakes
🧀 Cheese Wedge
🍖 Meat on Bone
🍗 Poultry Leg
🥩 Cut of Meat
🥓 Bacon
🍔 Hamburger
🍟 French Fries
🍕 Pizza
🌭 Hot Dog
🥪 Sandwich
🌮 Taco
🌯 Burrito
🥙 Stuffed Flatbread
🥚 Egg
🍳 Cooking
🥘 Shallow Pan of Food
🍲 Pot of Food
🥣 Bowl With Spoon
🥗 Green Salad
🍿 Popcorn
🥫 Canned Food
🍱 Bento Box
🍘 Rice Cracker
🍙 Rice Ball
🍚 Cooked Rice
🍛 Curry Rice
🍜 Steaming Bowl
🍝 Spaghetti
🍠 Roasted Sweet Potato
🍢 Oden
🍣 Sushi
🍤 Fried Shrimp
🍥 Fish Cake With Swirl
🍡 Dango
🥟 Dumpling
🥠 Fortune Cookie
🥡 Takeout Box
🍦 Soft Ice Cream
🍧 Shaved Ice
🍨 Ice Cream
🍩 Doughnut
🍪 Cookie
🎂 Birthday Cake
🍰 Shortcake
🥧 Pie
🍫 Chocolate Bar
🍬 Candy
🍭 Lollipop
🍮 Custard
🍯 Honey Pot
🍼 Baby Bottle
🥛 Glass of Milk
☕ Hot Beverage
🍵 Teacup Without Handle
🍶 Sake
🍾 Bottle With Popping Cork
🍷 Wine Glass
🍸 Cocktail Glass
🍹 Tropical Drink
🍺 Beer Mug
🍻 Clinking Beer Mugs
🥂 Clinking Glasses
🥃 Tumbler Glass
🥤 Cup With Straw
🥢 Chopsticks
🍽 Fork and Knife With Plate
🍴 Fork and Knife
🥄 Spoon
🔪 Kitchen Knife
🏺 Amphora
🌍 Globe Showing Europe-Africa
🌎 Globe Showing Americas
🌏 Globe Showing Asia-Australia
🌐 Globe With Meridians
🗺 World Map
🗾 Map of Japan
🏔 Snow-Capped Mountain
⛰ Mountain
🌋 Volcano
🗻 Mount Fuji
🏕 Camping
🏖 Beach With Umbrella
🏜 Desert
🏝 Desert Island
🏞 National Park
🏟 Stadium
🏛 Classical Building
🏗 Building Construction
🏘 House
🏙 Cityscape
🏚 Derelict House
🏠 House
🏡 House With Garden
🏢 Office Building
🏣 Japanese Post Office
🏤 Post Office
🏥 Hospital
🏦 Bank
🏨 Hotel
🏩 Love Hotel
🏪 Convenience Store
🏫 School
🏬 Department Store
🏭 Factory
🏯 Japanese Castle
🏰 Castle
💒 Wedding
🗼 Tokyo Tower
🗽 Statue of Liberty
⛪ Church
🕌 Mosque
🕍 Synagogue
⛩ Shinto Shrine
🕋 Kaaba
⛲ Fountain
⛺ Tent
🌁 Foggy
🌃 Night With Stars
🌄 Sunrise Over Mountains
🌅 Sunrise
🌆 Cityscape at Dusk
🌇 Sunset
🌉 Bridge at Night
♨ Hot Springs
🌌 Milky Way
🎠 Carousel Horse
🎡 Ferris Wheel
🎢 Roller Coaster
💈 Barber Pole
🎪 Circus Tent
🎭 Performing Arts
🖼 Framed Picture
🎨 Artist Palette
🎰 Slot Machine
🚂 Locomotive
🚃 Railway Car
🚄 High-Speed Train
🚅 High-Speed Train With Bullet Nose
🚆 Train
🚇 Metro
🚈 Light Rail
🚉 Station
🚊 Tram
🚝 Monorail
🚞 Mountain Railway
🚋 Tram Car
🚌 Bus
🚍 Oncoming Bus
🚎 Trolleybus
🚐 Minibus
🚑 Ambulance
🚒 Fire Engine
🚓 Police Car
🚔 Oncoming Police Car
🚕 Taxi
🚖 Oncoming Taxi
🚗 Automobile
🚘 Oncoming Automobile
🚙 Sport Utility Vehicle
🚚 Delivery Truck
🚛 Articulated Lorry
🚜 Tractor
🚲 Bicycle
🛴 Kick Scooter
🛵 Motor Scooter
🚏 Bus Stop
🛣 Motorway
🛤 Railway Track
⛽ Fuel Pump
🚨 Police Car Light
🚥 Horizontal Traffic Light
🚦 Vertical Traffic Light
🚧 Construction
🛑 Stop Sign
⚓ Anchor
⛵ Sailboat
🛶 Canoe
🚤 Speedboat
🛳 Passenger Ship
⛴ Ferry
🛥 Motor Boat
🚢 Ship
✈ Airplane
🛩 Small Airplane
🛫 Airplane Departure
🛬 Airplane Arrival
💺 Seat
🚁 Helicopter
🚟 Suspension Railway
🚠 Mountain Cableway
🚡 Aerial Tramway
🛰 Satellite
🚀 Rocket
🛸 Flying Saucer
🛎 Bellhop Bell
🚪 Door
🛏 Bed
🛋 Couch and Lamp
🚽 Toilet
🚿 Shower
🛁 Bathtub
⌛ Hourglass
⏳ Hourglass With Flowing Sand
⌚ Watch
⏰ Alarm Clock
⏱ Stopwatch
⏲ Timer Clock
🕰 Mantelpiece Clock
🕛 Twelve O’clock
🕧 Twelve-Thirty
🕐 One O’clock
🕜 One-Thirty
🕑 Two O’clock
🕝 Two-Thirty
🕒 Three O’clock
🕞 Three-Thirty
🕓 Four O’clock
🕟 Four-Thirty
🕔 Five O’clock
🕠 Five-Thirty
🕕 Six O’clock
🕡 Six-Thirty
🕖 Seven O’clock
🕢 Seven-Thirty
🕗 Eight O’clock
🕣 Eight-Thirty
🕘 Nine O’clock
🕤 Nine-Thirty
🕙 Ten O’clock
🕥 Ten-Thirty
🕚 Eleven O’clock
🕦 Eleven-Thirty
🌑 New Moon
🌒 Waxing Crescent Moon
🌓 First Quarter Moon
🌔 Waxing Gibbous Moon
🌕 Full Moon
🌖 Waning Gibbous Moon
🌗 Last Quarter Moon
🌘 Waning Crescent Moon
🌙 Crescent Moon
🌚 New Moon Face
🌛 First Quarter Moon With Face
🌜 Last Quarter Moon With Face
🌡 Thermometer
☀ Sun
🌝 Full Moon With Face
🌞 Sun With Face
⭐ White Medium Star
🌟 Glowing Star
🌠 Shooting Star
☁ Cloud
⛅ Sun Behind Cloud
⛈ Cloud With Lightning and Rain
🌤 Sun Behind Small Cloud
🌥 Sun Behind Large Cloud
🌦 Sun Behind Rain Cloud
🌧 Cloud With Rain
🌨 Cloud With Snow
🌩 Cloud With Lightning
🌪 Tornado
🌫 Fog
🌬 Wind Face
🌀 Cyclone
🌈 Rainbow
🌂 Closed Umbrella
☂ Umbrella
☔ Umbrella With Rain Drops
⛱ Umbrella on Ground
⚡ High Voltage
❄ Snowflake
☃ Snowman
⛄ Snowman Without Snow
☄ Comet
🔥 Fire
💧 Droplet
🌊 Water Wave
🎃 Jack-O-Lantern
🎄 Christmas Tree
🎆 Fireworks
🎇 Sparkler
✨ Sparkles
🎈 Balloon
🎉 Party Popper
🎊 Confetti Ball
🎋 Tanabata Tree
🎍 Pine Decoration
🎎 Japanese Dolls
🎏 Carp Streamer
🎐 Wind Chime
🎑 Moon Viewing Ceremony
🎀 Ribbon
🎁 Wrapped Gift
🎗 Reminder Ribbon
🎟 Admission Tickets
🎫 Ticket
🎖 Military Medal
🏆 Trophy
🏅 Sports Medal
🥇 1st Place Medal
🥈 2nd Place Medal
🥉 3rd Place Medal
⚽ Soccer Ball
⚾ Baseball
🏀 Basketball
🏐 Volleyball
🏈 American Football
🏉 Rugby Football
🎾 Tennis
🎱 Pool 8 Ball
🎳 Bowling
🏏 Cricket
🏑 Field Hockey
🏒 Ice Hockey
🏓 Ping Pong
🏸 Badminton
🥊 Boxing Glove
🥋 Martial Arts Uniform
🥅 Goal Net
🎯 Direct Hit
⛳ Flag in Hole
⛸ Ice Skate
🎣 Fishing Pole
🎽 Running Shirt
🎿 Skis
🛷 Sled
🥌 Curling Stone
🎮 Video Game
🕹 Joystick
🎲 Game Die
♠ Spade Suit
♥ Heart Suit
♦ Diamond Suit
♣ Club Suit
🃏 Joker
🀄 Mahjong Red Dragon
🎴 Flower Playing Cards
🔇 Muted Speaker
🔈 Speaker Low Volume
🔉 Speaker Medium Volume
🔊 Speaker High Volume
📢 Loudspeaker
📣 Megaphone
📯 Postal Horn
🔔 Bell
🔕 Bell With Slash
🎼 Musical Score
🎵 Musical Note
🎶 Musical Notes
🎙 Studio Microphone
🎚 Level Slider
🎛 Control Knobs
🎤 Microphone
🎧 Headphone
📻 Radio
🎷 Saxophone
🎸 Guitar
🎹 Musical Keyboard
🎺 Trumpet
🎻 Violin
🥁 Drum
📱 Mobile Phone
📲 Mobile Phone With Arrow
☎ Telephone
📞 Telephone Receiver
📟 Pager
📠 Fax Machine
🔋 Battery
🔌 Electric Plug
💻 Laptop Computer
🖥 Desktop Computer
🖨 Printer
⌨ Keyboard
🖱 Computer Mouse
🖲 Trackball
💽 Computer Disk
💾 Floppy Disk
💿 Optical Disk
📀 DVD
🎥 Movie Camera
🎞 Film Frames
📽 Film Projector
🎬 Clapper Board
📺 Television
📷 Camera
📸 Camera With Flash
📹 Video Camera
📼 Videocassette
🔍 Left-Pointing Magnifying Glass
🔎 Right-Pointing Magnifying Glass
🔬 Microscope
🔭 Telescope
📡 Satellite Antenna
🕯 Candle
💡 Light Bulb
🔦 Flashlight
🏮 Red Paper Lantern
📔 Notebook With Decorative Cover
📕 Closed Book
📖 Open Book
📗 Green Book
📘 Blue Book
📙 Orange Book
📚 Books
📓 Notebook
📒 Ledger
📃 Page With Curl
📜 Scroll
📄 Page Facing Up
📰 Newspaper
🗞 Rolled-Up Newspaper
📑 Bookmark Tabs
🔖 Bookmark
🏷 Label
💰 Money Bag
💴 Yen Banknote
💵 Dollar Banknote
💶 Euro Banknote
💷 Pound Banknote
💸 Money With Wings
💳 Credit Card
💹 Chart Increasing With Yen
💱 Currency Exchange
💲 Heavy Dollar Sign
✉ Envelope
📧 E-Mail
📨 Incoming Envelope
📩 Envelope With Arrow
📤 Outbox Tray
📥 Inbox Tray
📦 Package
📫 Closed Mailbox With Raised Flag
📪 Closed Mailbox With Lowered Flag
📬 Open Mailbox With Raised Flag
📭 Open Mailbox With Lowered Flag
📮 Postbox
🗳 Ballot Box With Ballot
✏ Pencil
✒ Black Nib
🖋 Fountain Pen
🖊 Pen
🖌 Paintbrush
🖍 Crayon
📝 Memo
💼 Briefcase
📁 File Folder
📂 Open File Folder
🗂 Card Index Dividers
📅 Calendar
📆 Tear-Off Calendar
🗒 Spiral Notepad
🗓 Spiral Calendar
📇 Card Index
📈 Chart Increasing
📉 Chart Decreasing
📊 Bar Chart
📋 Clipboard
📌 Pushpin
📍 Round Pushpin
📎 Paperclip
🖇 Linked Paperclips
📏 Straight Ruler
📐 Triangular Ruler
✂ Scissors
🗃 Card File Box
🗄 File Cabinet
🗑 Wastebasket
🔒 Locked
🔓 Unlocked
🔏 Locked With Pen
🔐 Locked With Key
🔑 Key
🗝 Old Key
🔨 Hammer
⛏ Pick
⚒ Hammer and Pick
🛠 Hammer and Wrench
🗡 Dagger
⚔ Crossed Swords
🔫 Pistol
🏹 Bow and Arrow
🛡 Shield
🔧 Wrench
🔩 Nut and Bolt
⚙ Gear
🗜 Clamp
⚗ Alembic
⚖ Balance Scale
🔗 Link
⛓ Chains
💉 Syringe
💊 Pill
🚬 Cigarette
⚰ Coffin
⚱ Funeral Urn
🗿 Moai
🛢 Oil Drum
🔮 Crystal Ball
🛒 Shopping Cart
🏧 Atm Sign
🚮 Litter in Bin Sign
🚰 Potable Water
♿ Wheelchair Symbol
🚹 Men’s Room
🚺 Women’s Room
🚻 Restroom
🚼 Baby Symbol
🚾 Water Closet
🛂 Passport Control
🛃 Customs
🛄 Baggage Claim
🛅 Left Luggage
⚠ Warning
🚸 Children Crossing
⛔ No Entry
🚫 Prohibited
🚳 No Bicycles
🚭 No Smoking
🚯 No Littering
🚱 Non-Potable Water
🚷 No Pedestrians
📵 No Mobile Phones
🔞 No One Under Eighteen
☢ Radioactive
☣ Biohazard
⬆ Up Arrow
↗ Up-Right Arrow
➡ Right Arrow
↘ Down-Right Arrow
⬇ Down Arrow
↙ Down-Left Arrow
⬅ Left Arrow
↖ Up-Left Arrow
↕ Up-Down Arrow
↔ Left-Right Arrow
↩ Right Arrow Curving Left
↪ Left Arrow Curving Right
⤴ Right Arrow Curving Up
⤵ Right Arrow Curving Down
🔃 Clockwise Vertical Arrows
🔄 Anticlockwise Arrows Button
🔙 Back Arrow
🔚 End Arrow
🔛 On! Arrow
🔜 Soon Arrow
🔝 Top Arrow
🛐 Place of Worship
⚛ Atom Symbol
🕉 Om
✡ Star of David
☸ Wheel of Dharma
☯ Yin Yang
✝ Latin Cross
☦ Orthodox Cross
☪ Star and Crescent
☮ Peace Symbol
🕎 Menorah
🔯 Dotted Six-Pointed Star
♈ Aries
♉ Taurus
♊ Gemini
♋ Cancer
♌ Leo
♍ Virgo
♎ Libra
♏ Scorpius
♐ Sagittarius
♑ Capricorn
♒ Aquarius
♓ Pisces
⛎ Ophiuchus
🔀 Shuffle Tracks Button
🔁 Repeat Button
🔂 Repeat Single Button
▶ Play Button
⏩ Fast-Forward Button
⏭ Next Track Button
⏯ Play or Pause Button
◀ Reverse Button
⏪ Fast Reverse Button
⏮ Last Track Button
🔼 Up Button
⏫ Fast Up Button
🔽 Down Button
⏬ Fast Down Button
⏸ Pause Button
⏹ Stop Button
⏺ Record Button
⏏ Eject Button
🎦 Cinema
🔅 Dim Button
🔆 Bright Button
📶 Antenna Bars
📳 Vibration Mode
📴 Mobile Phone Off
♀ Female Sign
♂ Male Sign
⚕ Medical Symbol
♻ Recycling Symbol
⚜ Fleur-De-Lis
🔱 Trident Emblem
📛 Name Badge
🔰 Japanese Symbol for Beginner
⭕ Heavy Large Circle
✅ White Heavy Check Mark
☑ Ballot Box With Check
✔ Heavy Check Mark
✖ Heavy Multiplication X
❌ Cross Mark
❎ Cross Mark Button
➕ Heavy Plus Sign
➖ Heavy Minus Sign
➗ Heavy Division Sign
➰ Curly Loop
➿ Double Curly Loop
〽 Part Alternation Mark
✳ Eight-Spoked Asterisk
✴ Eight-Pointed Star
❇ Sparkle
‼ Double Exclamation Mark
⁉ Exclamation Question Mark
❓ Question Mark
❔ White Question Mark
❕ White Exclamation Mark
❗ Exclamation Mark
〰 Wavy Dash
© Copyright
® Registered
™ Trade Mark
#️⃣ Keycap Number Sign
*️⃣ Keycap Asterisk
0️⃣ Keycap Digit Zero
1️⃣ Keycap Digit One
2️⃣ Keycap Digit Two
3️⃣ Keycap Digit Three
4️⃣ Keycap Digit Four
5️⃣ Keycap Digit Five
6️⃣ Keycap Digit Six
7️⃣ Keycap Digit Seven
8️⃣ Keycap Digit Eight
9️⃣ Keycap Digit Nine
🔟 Keycap 10
💯 Hundred Points
🔠 Input Latin Uppercase
🔡 Input Latin Lowercase
🔢 Input Numbers
🔣 Input Symbols
🔤 Input Latin Letters
🅰 A Button (blood Type)
🆎 Ab Button (blood Type)
🅱 B Button (blood Type)
🆑 CL Button
🆒 Cool Button
🆓 Free Button
ℹ Information
🆔 ID Button
Ⓜ Circled M
🆕 New Button
🆖 NG Button
🅾 O Button (blood Type)
🆗 OK Button
🅿 P Button
🆘 SOS Button
🆙 Up! Button
🆚 Vs Button
🈁 Japanese “here” Button
🈂 Japanese “service Charge” Button
🈷 Japanese “monthly Amount” Button
🈶 Japanese “not Free of Charge” Button
🈯 Japanese “reserved” Button
🉐 Japanese “bargain” Button
🈹 Japanese “discount” Button
🈚 Japanese “free of Charge” Button
🈲 Japanese “prohibited” Button
🉑 Japanese “acceptable” Button
🈸 Japanese “application” Button
🈴 Japanese “passing Grade” Button
🈳 Japanese “vacancy” Button
㊗ Japanese “congratulations” Button
㊙ Japanese “secret” Button
🈺 Japanese “open for Business” Button
🈵 Japanese “no Vacancy” Button
▪ Black Small Square
▫ White Small Square
◻ White Medium Square
◼ Black Medium Square
◽ White Medium-Small Square
◾ Black Medium-Small Square
⬛ Black Large Square
⬜ White Large Square
🔶 Large Orange Diamond
🔷 Large Blue Diamond
🔸 Small Orange Diamond
🔹 Small Blue Diamond
🔺 Red Triangle Pointed Up
🔻 Red Triangle Pointed Down
💠 Diamond With a Dot
🔘 Radio Button
🔲 Black Square Button
🔳 White Square Button
⚪ White Circle
⚫ Black Circle
🔴 Red Circle
🔵 Blue Circle
🏁 Chequered Flag
🚩 Triangular Flag
🎌 Crossed Flags
🏴 Black Flag
🏳 White Flag
🏳️🌈 Rainbow Flag
🇦🇨 Ascension Island
🇦🇩 Andorra
🇦🇪 United Arab Emirates
🇦🇫 Afghanistan
🇦🇬 Antigua & Barbuda
🇦🇮 Anguilla
🇦🇱 Albania
🇦🇲 Armenia
🇦🇴 Angola
🇦🇶 Antarctica
🇦🇷 Argentina
🇦🇸 American Samoa
🇦🇹 Austria
🇦🇺 Australia
🇦🇼 Aruba
🇦🇽 Åland Islands
🇦🇿 Azerbaijan
🇧🇦 Bosnia & Herzegovina
🇧🇧 Barbados
🇧🇩 Bangladesh
🇧🇪 Belgium
🇧🇫 Burkina Faso
🇧🇬 Bulgaria
🇧🇭 Bahrain
🇧🇮 Burundi
🇧🇯 Benin
🇧🇱 St. Barthélemy
🇧🇲 Bermuda
🇧🇳 Brunei
🇧🇴 Bolivia
🇧🇶 Caribbean Netherlands
🇧🇷 Brazil
🇧🇸 Bahamas
🇧🇹 Bhutan
🇧🇻 Bouvet Island
🇧🇼 Botswana
🇧🇾 Belarus
🇧🇿 Belize
🇨🇦 Canada
🇨🇨 Cocos (Keeling) Islands
🇨🇩 Congo - Kinshasa
🇨🇫 Central African Republic
🇨🇬 Congo - Brazzaville
🇨🇭 Switzerland
🇨🇮 Côte D’Ivoire
🇨🇰 Cook Islands
🇨🇱 Chile
🇨🇲 Cameroon
🇨🇳 China
🇨🇴 Colombia
🇨🇵 Clipperton Island
🇨🇷 Costa Rica
🇨🇺 Cuba
🇨🇻 Cape Verde
🇨🇼 Curaçao
🇨🇽 Christmas Island
🇨🇾 Cyprus
🇨🇿 Czechia
🇩🇪 Germany
🇩🇬 Diego Garcia
🇩🇯 Djibouti
🇩🇰 Denmark
🇩🇲 Dominica
🇩🇴 Dominican Republic
🇩🇿 Algeria
🇪🇦 Ceuta & Melilla
🇪🇨 Ecuador
🇪🇪 Estonia
🇪🇬 Egypt
🇪🇭 Western Sahara
🇪🇷 Eritrea
🇪🇸 Spain
🇪🇹 Ethiopia
🇪🇺 European Union
🇫🇮 Finland
🇫🇯 Fiji
🇫🇰 Falkland Islands
🇫🇲 Micronesia
🇫🇴 Faroe Islands
🇫🇷 France
🇬🇦 Gabon
🇬🇧 United Kingdom
🇬🇩 Grenada
🇬🇪 Georgia
🇬🇫 French Guiana
🇬🇬 Guernsey
🇬🇭 Ghana
🇬🇮 Gibraltar
🇬🇱 Greenland
🇬🇲 Gambia
🇬🇳 Guinea
🇬🇵 Guadeloupe
🇬🇶 Equatorial Guinea
🇬🇷 Greece
🇬🇸 South Georgia & South Sandwich Islands
🇬🇹 Guatemala
🇬🇺 Guam
🇬🇼 Guinea-Bissau
🇬🇾 Guyana
🇭🇰 Hong Kong Sar China
🇭🇲 Heard & Mcdonald Islands
🇭🇳 Honduras
🇭🇷 Croatia
🇭🇹 Haiti
🇭🇺 Hungary
🇮🇨 Canary Islands
🇮🇩 Indonesia
🇮🇪 Ireland
🇮🇱 Israel
🇮🇲 Isle of Man
🇮🇳 India
🇮🇴 British Indian Ocean Territory
🇮🇶 Iraq
🇮🇷 Iran
🇮🇸 Iceland
🇮🇹 Italy
🇯🇪 Jersey
🇯🇲 Jamaica
🇯🇴 Jordan
🇯🇵 Japan
🇰🇪 Kenya
🇰🇬 Kyrgyzstan
🇰🇭 Cambodia
🇰🇮 Kiribati
🇰🇲 Comoros
🇰🇳 St. Kitts & Nevis
🇰🇵 North Korea
🇰🇷 South Korea
🇰🇼 Kuwait
🇰🇾 Cayman Islands
🇰🇿 Kazakhstan
🇱🇦 Laos
🇱🇧 Lebanon
🇱🇨 St. Lucia
🇱🇮 Liechtenstein
🇱🇰 Sri Lanka
🇱🇷 Liberia
🇱🇸 Lesotho
🇱🇹 Lithuania
🇱🇺 Luxembourg
🇱🇻 Latvia
🇱🇾 Libya
🇲🇦 Morocco
🇲🇨 Monaco
🇲🇩 Moldova
🇲🇪 Montenegro
🇲🇫 St. Martin
🇲🇬 Madagascar
🇲🇭 Marshall Islands
🇲🇰 Macedonia
🇲🇱 Mali
🇲🇲 Myanmar (Burma)
🇲🇳 Mongolia
🇲🇴 Macau Sar China
🇲🇵 Northern Mariana Islands
🇲🇶 Martinique
🇲🇷 Mauritania
🇲🇸 Montserrat
🇲🇹 Malta
🇲🇺 Mauritius
🇲🇻 Maldives
🇲🇼 Malawi
🇲🇽 Mexico
🇲🇾 Malaysia
🇲🇿 Mozambique
🇳🇦 Namibia
🇳🇨 New Caledonia
🇳🇪 Niger
🇳🇫 Norfolk Island
🇳🇬 Nigeria
🇳🇮 Nicaragua
🇳🇱 Netherlands
🇳🇴 Norway
🇳🇵 Nepal
🇳🇷 Nauru
🇳🇺 Niue
🇳🇿 New Zealand
🇴🇲 Oman
🇵🇦 Panama
🇵🇪 Peru
🇵🇫 French Polynesia
🇵🇬 Papua New Guinea
🇵🇭 Philippines
🇵🇰 Pakistan
🇵🇱 Poland
🇵🇲 St. Pierre & Miquelon
🇵🇳 Pitcairn Islands
🇵🇷 Puerto Rico
🇵🇸 Palestinian Territories
🇵🇹 Portugal
🇵🇼 Palau
🇵🇾 Paraguay
🇶🇦 Qatar
🇷🇪 Réunion
🇷🇴 Romania
🇷🇸 Serbia
🇷🇺 Russia
🇷🇼 Rwanda
🇸🇦 Saudi Arabia
🇸🇧 Solomon Islands
🇸🇨 Seychelles
🇸🇩 Sudan
🇸🇪 Sweden
🇸🇬 Singapore
🇸🇭 St. Helena
🇸🇮 Slovenia
🇸🇯 Svalbard & Jan Mayen
🇸🇰 Slovakia
🇸🇱 Sierra Leone
🇸🇲 San Marino
🇸🇳 Senegal
🇸🇴 Somalia
🇸🇷 Suriname
🇸🇸 South Sudan
🇸🇹 São Tomé & Príncipe
🇸🇻 El Salvador
🇸🇽 Sint Maarten
🇸🇾 Syria
🇸🇿 Swaziland
🇹🇦 Tristan Da Cunha
🇹🇨 Turks & Caicos Islands
🇹🇩 Chad
🇹🇫 French Southern Territories
🇹🇬 Togo
🇹🇭 Thailand
🇹🇯 Tajikistan
🇹🇰 Tokelau
🇹🇱 Timor-Leste
🇹🇲 Turkmenistan
🇹🇳 Tunisia
🇹🇴 Tonga
🇹🇷 Turkey
🇹🇹 Trinidad & Tobago
🇹🇻 Tuvalu
🇹🇼 Taiwan
🇹🇿 Tanzania
🇺🇦 Ukraine
🇺🇬 Uganda
🇺🇲 U.S. Outlying Islands
🇺🇳 United Nations
🇺🇸 United States
🇺🇾 Uruguay
🇺🇿 Uzbekistan
🇻🇦 Vatican City
🇻🇨 St. Vincent & Grenadines
🇻🇪 Venezuela
🇻🇬 British Virgin Islands
🇻🇮 U.S. Virgin Islands
🇻🇳 Vietnam
🇻🇺 Vanuatu
🇼🇫 Wallis & Futuna
🇼🇸 Samoa
🇽🇰 Kosovo
🇾🇪 Yemen
🇾🇹 Mayotte
🇿🇦 South Africa
🇿🇲 Zambia
🇿🇼 Zimbabwe
🏴 Flag for England (GB-ENG)
🏴 Flag for Scotland (GB-SCT)
🏴 Flag for Wales (GB-WLS)
🥆 Rifle
🤻 Modern Pentathlon
🏴☠️ Pirate Flag
🇦 Regional Indicator Symbol Letter A
🇧 Regional Indicator Symbol Letter B
🇨 Regional Indicator Symbol Letter C
🇩 Regional Indicator Symbol Letter D
🇪 Regional Indicator Symbol Letter E
🇫 Regional Indicator Symbol Letter F
🇬 Regional Indicator Symbol Letter G
🇭 Regional Indicator Symbol Letter H
🇮 Regional Indicator Symbol Letter I
🇯 Regional Indicator Symbol Letter J
🇰 Regional Indicator Symbol Letter K
🇱 Regional Indicator Symbol Letter L
🇲 Regional Indicator Symbol Letter M
🇳 Regional Indicator Symbol Letter N
🇴 Regional Indicator Symbol Letter O
🇵 Regional Indicator Symbol Letter P
🇶 Regional Indicator Symbol Letter Q
🇷 Regional Indicator Symbol Letter R
🇸 Regional Indicator Symbol Letter S
🇹 Regional Indicator Symbol Letter T
🇺 Regional Indicator Symbol Letter U
🇻 Regional Indicator Symbol Letter V
🇼 Regional Indicator Symbol Letter W
🇽 Regional Indicator Symbol Letter X
🇾 Regional Indicator Symbol Letter Y
🇿 Regional Indicator Symbol Letter Z
🐱🐉 Dino Cat
🐱🚀 Astro Cat
🐱👤 Ninja Cat
🐱💻 Hacker Cat
🐱🏍 Stunt Cat
🐱👓 Hipster Cat
◯◯◯◯◯ Olympic Rings
🏴 Flag for Baiti (NR-05)
🏴 Flag for Nord-Trøndelag (NO-17)
🏴 Flag for Hordaland (NO-12)
🏴 Flag for Akershus (NO-02)
🏴 Flag for Sør-Trøndelag (NO-16)
🏴 Flag for Telemark (NO-08)
🏴 Flag for Utrecht (NL-UT)
🏴 Flag for Møre og Romsdal (NO-15)
🏴 Flag for Svalbard (NO-21)
🏴 Flag for Purwanchal (NP-4)
🏴 Flag for Central (NP-1)
🏴 Flag for Oslo (NO-03)
🏴 Flag for Boe (NR-06)
👨🏾👨🏾👦🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
🏴 Flag for North Brabant (NL-NB)
🏴 Flag for Aust-Agder (NO-09)
🏴 Flag for Anabar (NR-02)
🏴 Flag for Limburg (NL-LI)
🏴 Flag for Buskerud (NO-06)
🏴 Flag for Hedmark (NO-04)
🏴 Flag for Vestfold (NO-07)
🏴 Flag for Anibare (NR-04)
🏴 Flag for Finnmark (NO-20)
🏴 Flag for Overijssel (NL-OV)
🏴 Flag for Rogaland (NO-11)
🏴 Flag for Østfold (NO-01)
🏴 Flag for Aiwo (NR-01)
🏴 Flag for Zeeland (NL-ZE)
🏴 Flag for Buada (NR-07)
🏴 Flag for Troms (NO-19)
🏴 Flag for Oppland (NO-05)
🏴 Flag for Madhya Pashchimanchal (NP-2)
🏴 Flag for Anetan (NR-03)
🏴 Flag for Western (NP-3)
🏴 Flag for Jan Mayen (NO-22)
🏴 Flag for Nordland (NO-18)
🏴 Flag for Bocas del Toro (PA-1)
🏴 Flag for Colón (PA-3)
🏴 Flag for Ad Dakhiliyah (OM-DA)
🏴 Flag for Muscat (OM-MA)
🏴 Flag for Ewa (NR-09)
🏴 Flag for Taranaki (NZ-TKI)
🏴 Flag for Ijuw (NR-10)
🏴 Flag for West Coast (NZ-WTC)
🏴 Flag for Southland (NZ-STL)
🏴 Flag for Tasman (NZ-TAS)
🏴 Flag for Manawatu-Wanganui (NZ-MWT)
🏴 Flag for Waikato (NZ-WKO)
🏴 Flag for Marl (NZ-MBH)
🏴 Flag for Bay of Plenty (NZ-BOP)
🏴 Flag for Nibok (NR-12)
🏴 Flag for Al Buraimi (OM-BU)
🏴 Flag for Auckland (NZ-AUK)
🏴 Flag for Janub ash Sharqiyah (OM-SJ)
🏴 Flag for Shamal ash Sharqiyah (OM-SS)
🏴 Flag for Coclé (PA-2)
🏴 Flag for Meneng (NR-11)
🏴 Flag for West Panamá (PA-10)
🏴 Flag for Ad Dhahirah (OM-ZA)
🏴 Flag for Northland (NZ-NTL)
🏴 Flag for Canterbury (NZ-CAN)
🏴 Flag for Gisborne (NZ-GIS)
🏴 Flag for Chatham Islands (NZ-CIT)
🏴 Flag for Uaboe (NR-13)
🏴 Flag for Denigomodu (NR-08)
🏴 Flag for Musandam (OM-MU)
🏴 Flag for Shamal al Batinah (OM-BS)
🏴 Flag for Hawke’s Bay (NZ-HKB)
🏴 Flag for Otago (NZ-OTA)
🏴 Flag for Janub al Batinah (OM-BJ)
🏴 Flag for Dhofar (OM-ZU)
🏴 Flag for Darién (PA-5)
🏴 Flag for El Callao (PE-CAL)
🏴 Flag for Herrera (PA-6)
🏴 Flag for Guna Yala (PA-KY)
🏴 Flag for Emberá (PA-EM)
🏴 Flag for La Libertad (PE-LAL)
🏴 Flag for Veraguas (PA-9)
🏴 Flag for Loreto (PE-LOR)
🏴 Flag for Amazonas (PE-AMA)
🏴 Flag for Chiriquí (PA-4)
🏴 Flag for Chimbu (PG-CPK)
🏴 Flag for Eastern Highlands (PG-EHG)
🏴 Flag for San Martín (PE-SAM)
🏴 Flag for Junín (PE-JUN)
🏴 Flag for Huánuco (PE-HUC)
🏴 Flag for Pasco (PE-PAS)
🏴 Flag for Ngöbe-Buglé (PA-NB)
🏴 Flag for Cajamarca (PE-CAJ)
🏴 Flag for Ica (PE-ICA)
🏴 Flag for Lima Region (PE-LIM)
🏴 Flag for Moquegua (PE-MOQ)
🏴 Flag for Puno (PE-PUN)
🏴 Flag for Ucayali (PE-UCA)
🏴 Flag for Lima (PE-LMA)
🏴 Flag for Piura (PE-PIU)
🏴 Flag for Tumbes (PE-TUM)
🏴 Flag for Cusco (PE-CUS)
🏴 Flag for Panamá (PA-8)
🏴 Flag for Tacna (PE-TAC)
🏴 Flag for Central (PG-CPM)
🏴 Flag for Los Santos (PA-7)
🏴 Flag for Lambayeque (PE-LAM)
🏴 Flag for Huancavelica (PE-HUV)
🏴 Flag for Ancash (PE-ANC)
🏴 Flag for Hela (PG-HLA)
🏴 Flag for Port Moresby (PG-NCD)
🏴 Flag for Islamabad (PK-IS)
🏴 Flag for Metro Manila (PH-00)
🏴 Flag for Bicol (PH-05)
🏴 Flag for Gulf (PG-GPK)
🏴 Flag for Zamboanga Peninsula (PH-09)
🏴 Flag for Bougainville (PG-NSB)
🏴 Flag for Gilgit-Baltistan (PK-GB)
🏴 Flag for Madang (PG-MPM)
🏴 Flag for Western (FJ-W)
🏴 Flag for Soccsksargen (PH-12)
🏴 Flag for Eastern Visayas (PH-08)
🏴 Flag for Enga (PG-EPW)
🏴 Flag for Milne Bay (PG-MBA)
🏴 Flag for Calabarzon (PH-40)
🏴 Flag for Jiwaka (PG-JWK)
🏴 Flag for Cagayan Valley (PH-02)
👨🏿👨🏿👦🏿👧🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Boy: Dark Skin Tone, Girl: Dark Skin Tone
🏴 Flag for Morobe (PG-MPL)
🏴 Flag for Northern Mindanao (PH-10)
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Tag Latin Small Letter X
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☿️ Mercury
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👨🏻❤️👨🏼 Couple With Heart - Man: Light Skin Tone, Man: Medium-Light Skin Tone
👨🏽👨🏽👧🏽👧🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Girl: Medium Skin Tone, Girl: Medium Skin Tone
👩🏻❤️👩🏽 Couple With Heart - Woman: Light Skin Tone, Woman: Medium Skin Tone
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👨🏿👩🏿👶🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone
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߷ NKo Symbol Gbakurunen
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👨🏻👨🏻👧🏻👶🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Girl: Light Skin Tone, Baby: Light Skin Tone
👨🏼👨🏼👧🏼👶🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
🏴 Flag for San Marcos (GT-SM)
👨🏼👨🏼👦🏼👦🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
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👨👨👶👧 Family: Man, Man, Baby, Girl
️ Variation Selector-16
👨🏽👨🏽👧🏽👶🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Girl: Medium Skin Tone, Baby: Medium Skin Tone
👨🏾👨🏾👧🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👨🏿👨🏿👧🏿👶🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Girl: Dark Skin Tone, Baby: Dark Skin Tone
👨🏻👨🏻👶🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone
👨🏼👨🏼👶🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👨🏽👨🏽👶🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone
👨🏾👨🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👨🏿👨🏿👶🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone
👩❤️👨🏿 Couple With Heart - Woman, Man: Dark Skin Tone
🏴 Flag for Cantabria (ES-CB)
🏴 Flag for Unity (SS-UY)
👩🏼👶🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏽👶🏽👦🏽 Family - Woman: Medium Skin Tone, Baby: Medium Skin Tone, Boy: Medium Skin Tone
👩🏾👶🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👶🏿👦🏿 Family - Woman: Dark Skin Tone, Baby: Dark Skin Tone, Boy: Dark Skin Tone
👩🏻👶🏻👧🏻 Family - Woman: Light Skin Tone, Baby: Light Skin Tone, Girl: Light Skin Tone
👩🏼👶🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👩🏽👶🏽👧🏽 Family - Woman: Medium Skin Tone, Baby: Medium Skin Tone, Girl: Medium Skin Tone
👩🏾👶🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👩🏽👶🏽👶🏽 Family - Woman: Medium Skin Tone, Baby: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👶🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏿👶🏿👶🏿 Family - Woman: Dark Skin Tone, Baby: Dark Skin Tone, Baby: Dark Skin Tone
👩🏻👨🏻👦🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Boy: Light Skin Tone
👩🏼👨🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏽👨🏽👦🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Boy: Medium Skin Tone
👩🏾👨🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👨🏿👦🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Boy: Dark Skin Tone
👩🏻👨🏻👦🏻👦🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Boy: Light Skin Tone, Boy: Light Skin Tone
👩🏼👶🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏼👨🏼👦🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏽👨🏽👦🏽👦🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Boy: Medium Skin Tone, Boy: Medium Skin Tone
👩🏾👨🏾👦🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👨🏿👦🏿👦🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Boy: Dark Skin Tone, Boy: Dark Skin Tone
👩🏽👨🏽👦🏽👧🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Boy: Medium Skin Tone, Girl: Medium Skin Tone
👩🏾👨🏾👦🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👩🏿👨🏿👦🏿👧🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Boy: Dark Skin Tone, Girl: Dark Skin Tone
👩🏼👨🏼👦🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👨🏽👦🏽👶🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Boy: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👨🏾👦🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏻👨🏻👧🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Girl: Light Skin Tone
👩🏽👨🏽👧🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Girl: Medium Skin Tone
👩🏻👨🏻👦🏻👶🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Boy: Light Skin Tone, Baby: Light Skin Tone
👩🏼👨🏼👦🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👩🏼👨🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👩🏻👨🏻👧🏻👦🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Girl: Light Skin Tone, Boy: Light Skin Tone
👩🏼👨🏼👧🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏽👨🏽👧🏽👦🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Girl: Medium Skin Tone, Boy: Medium Skin Tone
👩🏾👨🏾👧🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👨🏿👧🏿👦🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Girl: Dark Skin Tone, Boy: Dark Skin Tone
👩🏻👨🏻👧🏻👧🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Girl: Light Skin Tone, Girl: Light Skin Tone
👩🏽👨🏽👧🏽👧🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Girl: Medium Skin Tone, Girl: Medium Skin Tone
👩🏿👨🏿👧🏿👧🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Girl: Dark Skin Tone, Girl: Dark Skin Tone
👩🏻👨🏻👧🏻👶🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Girl: Light Skin Tone, Baby: Light Skin Tone
👩🏼👨🏼👧🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👨🏽👧🏽👶🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Girl: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👨🏾👧🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏿👨🏿👧🏿👶🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Girl: Dark Skin Tone, Baby: Dark Skin Tone
👩🏻👨🏻👶🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone
👩🏼👨🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏻👨🏻👶🏻👦🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone, Boy: Light Skin Tone
👩🏼👨🏼👶🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏾👨🏾👶🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👨🏿👶🏿👦🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone, Boy: Dark Skin Tone
👩🏻👨🏻👶🏻👧🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone, Girl: Light Skin Tone
👩🏼👨🏼👶🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👩🏽👨🏽👶🏽👧🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone, Girl: Medium Skin Tone
👩🏿👨🏿👶🏿👧🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone, Girl: Dark Skin Tone
👩🏻👨🏻👶🏻👶🏻 Family - Woman: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone, Baby: Light Skin Tone
👩🏼👨🏼👶🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👨🏽👶🏽👶🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👨🏾👶🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏿👨🏿👶🏿👶🏿 Family - Woman: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone, Baby: Dark Skin Tone
👩🏼👩🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏻👩🏻👦🏻👧🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone, Girl: Light Skin Tone
👩🏼👩🏼👦🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏾👩🏾👦🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👩🏿👦🏿👦🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone, Boy: Dark Skin Tone
👩🏿👩🏿👦🏿👶🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone, Baby: Dark Skin Tone
👩🏽👩🏽👦🏽👧🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone, Girl: Medium Skin Tone
👩🏾👩🏾👦🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👩🏿👩🏿👦🏿👧🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone, Girl: Dark Skin Tone
👩🏻👩🏻👦🏻👶🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone, Baby: Light Skin Tone
👩🏼👩🏼👦🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👩🏽👦🏽👶🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👩🏾👦🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏻👩🏻👧🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Girl: Light Skin Tone
👩🏼👩🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👩🏽👩🏽👦🏽👦🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone, Boy: Medium Skin Tone
👩🏽👩🏽👧🏽👦🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone, Boy: Medium Skin Tone
👩🏻👩🏻👧🏻👧🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Girl: Light Skin Tone, Girl: Light Skin Tone
👩🏽👩🏽👧🏽👧🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone, Girl: Medium Skin Tone
👩🏾👩🏾👧🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👩🏿👩🏿👧🏿👧🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone, Girl: Dark Skin Tone
👩🏻👩🏻👧🏻👶🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Girl: Light Skin Tone, Baby: Light Skin Tone
👩🏼👩🏼👧🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👩🏽👧🏽👶🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👩🏾👧🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏿👩🏿👧🏿👶🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone, Baby: Dark Skin Tone
👩🏻👩🏻👶🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone
👨🏾👩🏾👧🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👩🏼👩🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👩🏽👶🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👩🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏿👩🏿👶🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone
👩🏻👩🏻👶🏻👦🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone, Boy: Light Skin Tone
👩🏼👩🏼👶🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏽👩🏽👶🏽👦🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone, Boy: Medium Skin Tone
👩🏾👩🏾👶🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏿👩🏿👶🏿👦🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone, Boy: Dark Skin Tone
👩🏻👩🏻👶🏻👧🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone, Girl: Light Skin Tone
👩🏽👩🏽👶🏽👧🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone, Girl: Medium Skin Tone
👩🏾👩🏾👶🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👩🏿👩🏿👶🏿👧🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone, Girl: Dark Skin Tone
👩🏻👩🏻👶🏻👶🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone, Baby: Light Skin Tone
👩🏼👩🏼👶🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👩🏽👩🏽👶🏽👶🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👩🏾👶🏾👶🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩🏿👩🏿👶🏿👶🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone, Baby: Dark Skin Tone
👩🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
🏴 Flag for Maluku Islands (ID-ML)
👩🏿👶🏿👧🏿 Family - Woman: Dark Skin Tone, Baby: Dark Skin Tone, Girl: Dark Skin Tone
🏴 Flag for Southern Denmark (DK-83)
🏴 Flag for Skopje (MK-85)
👨🏼❤️💋👩 Kiss - Man: Medium-Light Skin Tone, Woman
🏴 Flag for Beja (PT-02)
🏴 Flag for Sardinia (IT-88)
🏴 Flag for Bavaria (DE-BY)
🏴 Flag for East New Britain (PG-EBR)
🏴 Flag for Trentino-South Tyrol (IT-32)
🏴 Flag for Tennessee (US-TN)
🏴 Flag for Saskatchewan (CA-SK)
🏴 Flag for Funafuti (TV-FUN)
🏴 Flag for Gorno-Badakhshan (TJ-GB)
🏴 Flag for Banaadir (SO-BN)
🏴 Flag for Radenci (SI-100)
🏴 Flag for Baden-Württemberg (DE-BW)
👩🏿👧🏿 Family - Woman: Dark Skin Tone, Girl: Dark Skin Tone
🏴 Flag for Carabobo (VE-G)
Zero Width Joiner
🏴 Flag for Nakuru (KE-31)
🏴 Flag for Maritime (TG-M)
🏴 Flag for Borno (NG-BO)
🏴 Flag for Transnistria (MD-SN)
🏴 Flag for Tehran (IR-07)
🏴 Flag for Dagestan (RU-DA)
🏴 Flag for Al Wusta (OM-WU)
🏴 Flag for Ústecký kraj (CZ-42)
🏴 Flag for Kuala Lumpur (MY-14)
🏴 Flag for Ayacucho (PE-AYA)
🏴 Flag for Kiev (UA-30)
🏴 Flag for Saint Philip (AG-08)
🏴 Flag for Mdina (MT-29)
🏴 Flag for Northern Ireland (GB-NIR)
🏴 Flag for Auvergne-Rhône-Alpes (FR-ARA)
🏴 Flag for Durango (MX-DUR)
👨🏼👩🏼👧🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
🏴 Flag for Eastern (LK-5)
🏴 Flag for Ogun (NG-OG)
🏴 Flag for Jafara (LY-JI)
🏴 Flag for Skåne (SE-M)
👨🏽👩🏽👧🏽👦🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone, Boy: Medium Skin Tone
👩🏾👩🏾👧🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
🏴 Flag for Mato Grosso do Sul (BR-MS)
🏴 Flag for Santa Rosa (GT-SR)
👨🏼👩🏼👧🏼👧🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
🏴 Flag for Braslovče (SI-151)
🏴 Flag for Madeira (PT-30)
🏴 Flag for San Vicente (SV-SV)
🏴 Flag for Alborz (IR-32)
🏴 Flag for Fa’asaleleaga (WS-FA)
👨🏼👨🏼👦🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Newfoundland and Labrador (CA-NL)
🏴 Flag for Peloponnese (GR-J)
🏴 Flag for Sint Maarten (NL-SX)
🏴 Flag for St. Julian’s (MT-48)
🏴 Flag for Adamawa (NG-AD)
👩🏿👩🏿👧🏿👦🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for São Tomé (ST-S)
👩🏻👩🏻👧🏻👦🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Girl: Light Skin Tone, Boy: Light Skin Tone
🏴 Flag for Auce (LV-010)
🏴 Flag for Cordillera Administrative (PH-15)
🏴 Flag for Fukui (JP-18)
👨🏿👩🏿👦🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for Kakheti (GE-KA)
🏴 Flag for Jeju (KR-49)
🏴 Flag for Souss-Massa-Drâa (MA-13)
🏴 Flag for Inčukalns (LV-037)
🏴 Flag for French Southern Territories (FR-TF)
🏴 Flag for Quintana Roo (MX-ROO)
👩🏻👶🏻👶🏻 Family - Woman: Light Skin Tone, Baby: Light Skin Tone, Baby: Light Skin Tone
👨🏾👨🏾👦🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
🏴 Flag for Győr-Moson-Sopron (HU-GS)
👩🏿👩🏿👧🏿 Family - Woman: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone
👩🏻👩🏻👦🏻👦🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone, Boy: Light Skin Tone
Shibuya
👩❤️👨🏽 Couple With Heart - Woman, Man: Medium Skin Tone
🏴 Flag for Gaga’ifomauga (WS-GI)
🏴 Flag for Nord-Est (HT-NE)
🏴 Flag for Central Singapore (SG-01)
🏴 Flag for Tungurahua (EC-T)
# Number Sign
👨🏻👨🏻👶🏻👦🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone, Boy: Light Skin Tone
1 Digit One
🏴 Flag for Tarija (BO-T)
👨🏾👩🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
🏴 Flag for Cibitoke (BI-CI)
🏴 Flag for Upper South Province (MV-US)
🏴 Flag for Canillo (AD-02)
🏴 Flag for Bamyan (AF-BAM)
🏴 Flag for Encamp (AD-03)
🏴 Flag for Northern Mariana Islands (US-MP)
🏴 Flag for Babīte (LV-012)
🏴 Flag for Cotopaxi (EC-X)
🏴 Flag for Ngounié (GA-4)
* Asterisk
Tag Latin Small Letter Z
🏴 Flag for La Massana (AD-04)
Tag Digit Three
👩🏼❤️💋👩🏻 Kiss - Woman: Medium-Light Skin Tone, Woman: Light Skin Tone
🏴 Flag for Berane (ME-03)
👨🏿❤️💋👨🏽 Kiss - Man: Dark Skin Tone, Man: Medium Skin Tone
🏴 Flag for El Valle (DO-37)
👩🏾❤️👩🏻 Couple With Heart - Woman: Medium-Dark Skin Tone, Woman: Light Skin Tone
🏴 Flag for Baringo (KE-01)
🏴 Flag for Amanat Al Asimah (YE-SA)
👨🏼👨🏼👶🏼👦🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
Tag Digit Two
🏴 Flag for Senglea (MT-20)
🕴️♀️ Woman in Business Suit Levitating
🏴 Flag for Haut-Mbomou (CF-HM)
Tag Digit One
Tag Digit Four
🏴 Flag for Absheron (AZ-ABS)
6 Digit Six
🏴 Flag for Savannakhet (LA-SV)
🏴 Flag for Kayes (ML-1)
🏴 Flag for Abu Dhabi (AE-AZ)
🏴 Flag for Asturias (ES-AS)
🏴 Flag for Kirkuk (IQ-KI)
👩❤️👩🏽 Couple With Heart - Woman, Woman: Medium Skin Tone
🏴 Flag for Berlin (DE-BE)
8 Digit Eight
🏴 Flag for Escaldes-Engordany (AD-08)
🏴 Flag for Ningxia (CN-64)
🏴 Flag for Cañar (EC-F)
🏴 Flag for Ajman (AE-AJ)
🕴🏻♀️ Woman in Business Suit Levitating: Light Skin Tone
👨🏻❤️💋👩 Kiss - Man: Light Skin Tone, Woman
Tag Digit Eight
🏴 Flag for Fars (IR-14)
🏴 Flag for Fujairah (AE-FU)
👨🏼👦🏼👦🏼 Family - Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Virovitica-Podravina (HR-10)
Tag Latin Small Letter I
7 Digit Seven
Tag Digit Seven
Tag Latin Small Letter E
👩🏼👩🏼👧🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Ratak Chain (MH-T)
🏴 Flag for Sharjah (AE-SH)
Tag Latin Small Letter F
🏴 Flag for Vilniaus Municipality (LT-57)
🏴 Flag for Westfjords (IS-4)
🏴 Flag for British Columbia (CA-BC)
4 Digit Four
🏴 Flag for Balkh (AF-BAL)
👨👶👦 Family: Man, Baby, Boy
🏴 Flag for Hsinchu County (TW-HSQ)
👩👶👧 Family: Woman, Baby, Girl
🏴 Flag for Jalisco (MX-JAL)
🏴 Flag for Kitui (KE-18)
🏴 Flag for Azores (PT-20)
🏴 Flag for Manipur (IN-MN)
🏴 Flag for Badakhshan (AF-BDS)
👩🏻❤️👩🏼 Couple With Heart - Woman: Light Skin Tone, Woman: Medium-Light Skin Tone
🏴 Flag for Ordino (AD-05)
👩🏽❤️💋👩 Kiss - Woman: Medium Skin Tone, Woman
🏴 Flag for Baghlan (AF-BGL)
🏴 Flag for Cross River (NG-CR)
🏴 Flag for Colorado (US-CO)
Tag Latin Small Letter T
🏴 Flag for Radoviš (MK-64)
🏴 Flag for Wellington (NZ-WGN)
👨🏽👨🏽👶🏽👦🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone, Boy: Medium Skin Tone
🏴 Flag for Kurdistan (IR-16)
👨🏽❤️💋👨🏿 Kiss - Man: Medium Skin Tone, Man: Dark Skin Tone
Tag Latin Small Letter S
👩👶👶 Family: Woman, Baby, Baby
🏴 Flag for Daykundi (AF-DAY)
👨🏻❤️💋👨🏾 Kiss - Man: Light Skin Tone, Man: Medium-Dark Skin Tone
🏴 Flag for Farah (AF-FRA)
Tag Latin Small Letter Q
🏴 Flag for Guatemala (GT-GU)
🏴 Flag for Thurgau (CH-TG)
🏴 Flag for Chechen (RU-CE)
Tag Digit Five
🏴 Flag for Ghōr (AF-GHO)
🏴 Flag for Vienna (AT-9)
🏴 Flag for Ghazni (AF-GHA)
Tag Latin Small Letter U
🏴 Flag for Gaborone (BW-GA)
Tag Latin Small Letter Y
Cancel Tag
Tag Latin Small Letter W
👩🏽❤️👩🏿 Couple With Heart - Woman: Medium Skin Tone, Woman: Dark Skin Tone
🏴 Flag for Amazonas (CO-AMA)
Tag Latin Small Letter N
👩❤️💋👩🏽 Kiss - Woman, Woman: Medium Skin Tone
👨👶 Family: Man, Baby
🏴 Flag for Burgenland (AT-1)
🏴 Flag for Helmand (AF-HEL)
Tag Digit Six
🏴 Flag for Jowzjan (AF-JOW)
🧕♀️ Woman With Headscarf
Tag Latin Small Letter B
Tag Digit Zero
🏴 Flag for Herat (AF-HER)
🏴 Flag for Saint Mark (GD-05)
3 Digit Three
Tag Latin Small Letter G
🕴🏾♀️ Woman in Business Suit Levitating: Medium-Dark Skin Tone
👩🏽❤️💋👨🏽 Kiss - Woman: Medium Skin Tone, Man: Medium Skin Tone
🏴 Flag for Alaska (US-AK)
Tag Latin Small Letter R
🏴 Flag for Lautém (TL-LA)
🏴 Flag for Kabul (AF-KAB)
👨❤️💋👨🏿 Kiss - Man, Man: Dark Skin Tone
🧕♂️ Man With Headscarf
Tag Latin Small Letter V
Tag Latin Small Letter D
🏴 Flag for Kandahar (AF-KAN)
🏴 Flag for Kapisa (AF-KAP)
🏴 Flag for Saint Roman (MC-SR)
🏴 Flag for Hiiu (EE-39)
Tag Latin Small Letter M
🏴 Flag for Khost (AF-KHO)
🧕🏻♂️ Man With Headscarf: Light Skin Tone
🏴 Flag for Kunduz (AF-KDZ)
👩🏿❤️👨 Couple With Heart - Woman: Dark Skin Tone, Man
🏴 Flag for South Dakota (US-SD)
🏴 Flag for Badghis (AF-BDG)
🏴 Flag for Southern (IS-8)
🏴 Flag for Kunar (AF-KNR)
👨👨👶👶 Family: Man, Man, Baby, Baby
🏴 Flag for Tokyo (JP-13)
🏴 Flag for Laghman (AF-LAG)
🧕🏽♂️ Man With Headscarf: Medium Skin Tone
🏴 Flag for Logar (AF-LOG)
5 Digit Five
Tag Latin Small Letter C
🏴 Flag for Faryab (AF-FYB)
Tag Latin Small Letter P
🏴 Flag for Nangarhar (AF-NAN)
Tag Digit Nine
🏴 Flag for Navarra Chartered Community (ES-NC)
👩🏼👦🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
🏴 Flag for Nayarit (MX-NAY)
🏴 Flag for Pernambuco (BR-PE)
🏴 Flag for Campania (IT-72)
🧕🏾♂️ Man With Headscarf: Medium-Dark Skin Tone
👩🏽❤️💋👩🏾 Kiss - Woman: Medium Skin Tone, Woman: Medium-Dark Skin Tone
🏴 Flag for Nuristan (AF-NUR)
👨👨👧👶 Family: Man, Man, Girl, Baby
🏴 Flag for West New Britain (PG-WBK)
👨🏼👩🏼👧🏼👦🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Upper Demerara-Berbice (GY-UD)
👨❤️💋👩 Kiss - Man, Woman
🏴 Flag for Afar (ET-AF)
🏴 Flag for Parwan (AF-PAR)
🏴 Flag for Nimruz (AF-NIM)
🏴 Flag for Karlovac (HR-04)
🏴 Flag for Paktia (AF-PIA)
🧕🏿♂️ Man With Headscarf: Dark Skin Tone
🧕🏼♂️ Man With Headscarf: Medium-Light Skin Tone
🏴 Flag for Baja California (MX-BCN)
🏴 Flag for Paktika (AF-PKA)
🏴 Flag for Phoenix Islands (KI-P)
Tag Latin Small Letter O
🏴 Flag for Panjshir (AF-PAN)
🏴 Flag for Ticino (CH-TI)
🏴 Flag for Žirovnica (SI-192)
🏴 Flag for Halland (SE-N)
Tag Latin Small Letter J
👩🏽❤️💋👩🏻 Kiss - Woman: Medium Skin Tone, Woman: Light Skin Tone
👨🏾👨🏾👶🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👨🏿👨🏿👶🏿👦🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for Northern Bahr el Ghazal (SS-BN)
👨🏽❤️💋👩 Kiss - Man: Medium Skin Tone, Woman
🏴 Flag for Basse-Kotto (CF-BK)
👨❤️👨🏻 Couple With Heart - Man, Man: Light Skin Tone
👨🏽❤️👨 Couple With Heart - Man: Medium Skin Tone, Man
🏴 Flag for Butnan (LY-BU)
👩👶 Family: Woman, Baby
🏴 Flag for Sabaragamuwa (LK-9)
🏴 Flag for Samangan (AF-SAM)
🏴 Flag for Nukulaelae (TV-NKL)
🏴 Flag for Ras al-Khaimah (AE-RK)
🏴 Flag for Ceuta (ES-CE)
🏴 Flag for Dubai (AE-DU)
👨🏻👨🏻👶🏻👧🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone, Girl: Light Skin Tone
🏴 Flag for Okinawa (JP-47)
🏴 Flag for Sar-e Pol (AF-SAR)
👩🏼👩🏼👦🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
Tag Latin Small Letter L
🏴 Flag for Urozgan (AF-URU)
9 Digit Nine
👩🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👨❤️💋👨🏽 Kiss - Man, Man: Medium Skin Tone
🏴 Flag for Saint Joseph (DM-06)
🏴 Flag for Saint John (AG-04)
🏴 Flag for Vichada (CO-VID)
🏴 Flag for Ngarchelong (PW-218)
🏴 Flag for Arkhangelsk (RU-ARK)
🏴 Flag for Zabul (AF-ZAB)
🏴 Flag for Saint George (AG-03)
🏴 Flag for Lombardy (IT-25)
👨🏻❤️💋👨🏻 Kiss - Man: Light Skin Tone, Man: Light Skin Tone
🏴 Flag for Pardubický kraj (CZ-53)
🏴 Flag for Saint Paul (AG-06)
🏴 Flag for Trà Vinh (VN-51)
👩👨👶👧 Family: Woman, Man, Baby, Girl
🏴 Flag for South Gyeongsang (KR-48)
🏴 Flag for Saint Mary (AG-05)
🏴 Flag for North Aegean (GR-K)
👩👩👶👧 Family: Woman, Woman, Baby, Girl
🏴 Flag for Zamora-Chinchipe (EC-Z)
🏴 Flag for Masaya (NI-MS)
🏴 Flag for Gilbert Islands (KI-G)
🏴 Flag for Chihuahua (MX-CHH)
👨🏼👨🏼👶🏼👧🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👨🏽👨🏽👶🏽👧🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone, Girl: Medium Skin Tone
👩🏽👧🏽👧🏽 Family - Woman: Medium Skin Tone, Girl: Medium Skin Tone, Girl: Medium Skin Tone
👩👨👶👶 Family: Woman, Man, Baby, Baby
🏴 Flag for Redonda (AG-11)
👩👩👶 Family: Woman, Woman, Baby
👨❤️💋👩🏻 Kiss - Man, Woman: Light Skin Tone
👨❤️💋👨🏾 Kiss - Man, Man: Medium-Dark Skin Tone
🏴 Flag for Berat County (AL-01)
Tag Latin Small Letter A
🏴 Flag for Barbuda (AG-10)
🏴 Flag for San Andrés & Providencia (CO-SAP)
🏴 Flag for Elbasan County (AL-03)
👨🏾👨🏾👶🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👨🏿👨🏿👦🏿👶🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Boy: Dark Skin Tone, Baby: Dark Skin Tone
🏴 Flag for Karnataka (IN-KA)
🏴 Flag for Gjirokastër County (AL-05)
🏴 Flag for Hokkaidō (JP-01)
👩🏾👨🏾👶🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
🏴 Flag for Central (UG-C)
👨🏼❤️💋👨 Kiss - Man: Medium-Light Skin Tone, Man
🏴 Flag for Durrës County (AL-02)
🏴 Flag for Fier County (AL-04)
🏴 Flag for Korçë County (AL-06)
🏴 Flag for Alto Paraguay (PY-16)
🏴 Flag for Kukës County (AL-07)
👨🏿❤️💋👨 Kiss - Man: Dark Skin Tone, Man
🏴 Flag for Upper Takutu-Upper Essequibo (GY-UT)
👨🏾👶🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👨🏿👨🏿👶🏿👧🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone, Girl: Dark Skin Tone
👨🏻👨🏻👶🏻👶🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Baby: Light Skin Tone, Baby: Light Skin Tone
🏴 Flag for Dibër County (AL-09)
🏴 Flag for Lezhë County (AL-08)
👨🏼👨🏼👶🏼👶🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
🏴 Flag for Tirana County (AL-11)
🏴 Flag for Sant Julià de Lòria (AD-06)
🏴 Flag for Bahia (BR-BA)
🏴 Flag for Shkodër County (AL-10)
👩❤️💋👨🏿 Kiss - Woman, Man: Dark Skin Tone
👨🏽👨🏽👶🏽👶🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone, Baby: Medium Skin Tone
👨🏾👨🏾👶🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👩❤️💋👨🏽 Kiss - Woman, Man: Medium Skin Tone
🏴 Flag for Vlorë County (AL-12)
🏴 Flag for Trat (TH-23)
🏴 Flag for Gegharkunik (AM-GR)
👨🏿👨🏿👶🏿👶🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Baby: Dark Skin Tone, Baby: Dark Skin Tone
🏴 Flag for Aragatsotn (AM-AG)
🏴 Flag for Ararat (AM-AR)
🏴 Flag for Yerevan (AM-ER)
🏴 Flag for Kotayk (AM-KT)
🏴 Flag for Corse (FR-COR)
🏴 Flag for Armavir (AM-AV)
👩❤️💋👩🏿 Kiss - Woman, Woman: Dark Skin Tone
🏴 Flag for Minas Gerais (BR-MG)
🏴 Flag for Pointe-Noire (CG-16)
🏴 Flag for Lori (AM-LO)
🏴 Flag for Skikda (DZ-21)
🏴 Flag for Shirak (AM-SH)
👩❤️💋👩🏾 Kiss - Woman, Woman: Medium-Dark Skin Tone
🏴 Flag for Andorra la Vella (AD-07)
🏴 Flag for Altai Krai (RU-ALT)
🏴 Flag for Lovrenc na Pohorju (SI-167)
👩❤️💋👩🏼 Kiss - Woman, Woman: Medium-Light Skin Tone
👨🏿❤️💋👩🏻 Kiss - Man: Dark Skin Tone, Woman: Light Skin Tone
🏴 Flag for Panevėžys County (LT-PN)
🏴 Flag for Cibao Norte (DO-35)
🏴 Flag for Vest-Agder (NO-10)
👨❤️💋👩🏿 Kiss - Man, Woman: Dark Skin Tone
🏴 Flag for Vayots Dzor (AM-VD)
👩🏻❤️💋👩🏻 Kiss - Woman: Light Skin Tone, Woman: Light Skin Tone
🏴 Flag for Vermont (US-VT)
👨🏽❤️💋👨 Kiss - Man: Medium Skin Tone, Man
🏴 Flag for Bengo (AO-BGO)
👩🏻❤️💋👩 Kiss - Woman: Light Skin Tone, Woman
🏴 Flag for Meta (CO-MET)
🏴 Flag for Saba (NL-BQ2)
👩🏽❤️💋👩🏼 Kiss - Woman: Medium Skin Tone, Woman: Medium-Light Skin Tone
👨🏽👩🏽👦🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone
🏴 Flag for Benguela (AO-BGU)
🏴 Flag for Sucre (CO-SUC)
🏴 Flag for Cuando Cubango (AO-CCU)
🏴 Flag for Madre de Dios (PE-MDD)
🏴 Flag for Vaud (CH-VD)
🏴 Flag for Bié (AO-BIE)
🏴 Flag for Cabinda (AO-CAB)
🏴 Flag for Huíla (AO-HUI)
🏴 Flag for Cuanza Sul (AO-CUS)
👨❤️💋👩🏽 Kiss - Man, Woman: Medium Skin Tone
👩👩👦👶 Family: Woman, Woman, Boy, Baby
🏴 Flag for Huambo (AO-HUA)
👨🏼❤️👩🏾 Couple With Heart - Man: Medium-Light Skin Tone, Woman: Medium-Dark Skin Tone
🏴 Flag for Kyrenia (CY-06)
👩🏼❤️💋👨🏻 Kiss - Woman: Medium-Light Skin Tone, Man: Light Skin Tone
🏴 Flag for Umm al-Quwain (AE-UQ)
🏴 Flag for Lunda Sul (AO-LSU)
🏴 Flag for Grand Cape Mount (LR-CM)
🏴 Flag for Lunda Norte (AO-LNO)
👩🏽❤️👨🏿 Couple With Heart - Woman: Medium Skin Tone, Man: Dark Skin Tone
👨🏾❤️👩🏾 Couple With Heart - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone
🏴 Flag for Cuanza Norte (AO-CNO)
🏴 Flag for Malanje (AO-MAL)
👩🏼❤️💋👩 Kiss - Woman: Medium-Light Skin Tone, Woman
👨🏼👩🏼👦🏼👦🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Moxico (AO-MOX)
🏴 Flag for Namibe (AO-NAM)
👨🏾👩🏾👦🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
Tag Latin Small Letter K
🕴🏼♀️ Woman in Business Suit Levitating: Medium-Light Skin Tone
🏴 Flag for Salta (AR-A)
👨🏾👩🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
🏴 Flag for Lualaba (CD-LU)
🏴 Flag for Buenos Aires Province (AR-B)
👨🏿👩🏿👦🏿👦🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for San Luis (AR-D)
🏴 Flag for Zaire (AO-ZAI)
🏴 Flag for Afyonkarahisar (TR-03)
0 Digit Zero
🏴 Flag for Quảng Trị (VN-25)
🕴🏿♀️ Woman in Business Suit Levitating: Dark Skin Tone
🏴 Flag for Uíge (AO-UIG)
👩🏾👧🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
🏴 Flag for Zhytomyrshchyna (UA-18)
👨🏾❤️💋👨🏽 Kiss - Man: Medium-Dark Skin Tone, Man: Medium Skin Tone
🏴 Flag for Cesar (CO-CES)
🏴 Flag for Syunik (AM-SU)
🏴 Flag for Entre Ríos (AR-E)
👨🏿❤️💋👩 Kiss - Man: Dark Skin Tone, Woman
🏴 Flag for La Rioja (AR-F)
🏴 Flag for East Kazakhstan (KZ-VOS)
🏴 Flag for Maidan Wardak (AF-WAR)
🏴 Flag for San Juan (AR-J)
👩🏾👩🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
🏴 Flag for Luanda (AO-LUA)
🏴 Flag for La Pampa (AR-L)
👩🏼❤️💋👩🏽 Kiss - Woman: Medium-Light Skin Tone, Woman: Medium Skin Tone
👨🏼👩🏼👦🏼👧🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👨🏼👩🏼👦🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Catamarca (AR-K)
🏴 Flag for Río Negro (AR-R)
🏴 Flag for Chaco (AR-H)
🏴 Flag for Formosa (AR-P)
🏴 Flag for Mendoza (AR-M)
🏴 Flag for Misiones (AR-N)
🏴 Flag for Neuquén (AR-Q)
👨🏽👩🏽👦🏽👧🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone, Girl: Medium Skin Tone
🏴 Flag for Tucumán (AR-T)
🏴 Flag for Santa Fe (AR-S)
🏴 Flag for Corrientes (AR-W)
🏴 Flag for Jujuy (AR-Y)
🏴 Flag for Tierra del Fuego (AR-V)
🏴 Flag for Chubut (AR-U)
🏴 Flag for Córdoba (AR-X)
🏴 Flag for Santa Cruz (AR-Z)
🏴 Flag for Santiago del Estero (AR-G)
🏴 Flag for Carinthia (AT-2)
🏴 Flag for Basel-Landschaft (CH-BL)
👩🏿👧🏿👧🏿 Family - Woman: Dark Skin Tone, Girl: Dark Skin Tone, Girl: Dark Skin Tone
👨🏻👩🏻👦🏻👶🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone, Baby: Light Skin Tone
👩🏻👧🏻👶🏻 Family - Woman: Light Skin Tone, Girl: Light Skin Tone, Baby: Light Skin Tone
👨👨👦👧 Family: Man, Man, Boy, Girl
🏴 Flag for Lower Austria (AT-3)
👩👶👦 Family: Woman, Baby, Boy
🏴 Flag for Nouakchott Ouest (MR-13)
👨🏼👩🏼👦🏼👶🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
🏴 Flag for Mbomou (CF-MB)
🏴 Flag for Styria (AT-6)
🏴 Flag for Ilocos (PH-01)
🏴 Flag for Tyrol (AT-7)
🏴 Flag for Guizhou (CN-52)
🏴 Flag for Xaisomboun (LA-XS)
🏴 Flag for Vorarlberg (AT-8)
👨🏼👨🏼👦🏼👧🏼 Family - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
🏴 Flag for Salzburg (AT-5)
👨🏿👩🏿👦🏿👧🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone, Girl: Dark Skin Tone
👩👩👶👶 Family: Woman, Woman, Baby, Baby
👩👨👧👦 Family: Woman, Man, Girl, Boy
👩👨👧 Family: Woman, Man, Girl
👩👦👶 Family: Woman, Boy, Baby
🏴 Flag for New South Wales (AU-NSW)
👩👨👧👶 Family: Woman, Man, Girl, Baby
👩🏽👧🏽👶🏽 Family - Woman: Medium Skin Tone, Girl: Medium Skin Tone, Baby: Medium Skin Tone
🏴 Flag for Northern Territory (AU-NT)
👩🏿👧🏿👦🏿 Family - Woman: Dark Skin Tone, Girl: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for Queensland (AU-QLD)
2 Digit Two
👩👨👧👧 Family: Woman, Man, Girl, Girl
👩🏼👧🏼👶🏼 Family - Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
🏴 Flag for Upper Austria (AT-4)
🏴 Flag for East Macedonia and Thrace (GR-A)
👨🏽👩🏽👦🏽👶🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone, Baby: Medium Skin Tone
👨🏾👩🏾👦🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👨👶👧 Family: Man, Baby, Girl
👨🏻👩🏻👧🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Girl: Light Skin Tone
👨🏿👩🏿👦🏿👶🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Boy: Dark Skin Tone, Baby: Dark Skin Tone
👩👨👶 Family: Woman, Man, Baby
🏴 Flag for Nebraska (US-NE)
🏴 Flag for Agstafa (AZ-AGA)
🏴 Flag for Takhar (AF-TAK)
🏴 Flag for Western Australia (AU-WA)
🏴 Flag for Aghjabadi (AZ-AGC)
🏴 Flag for Astara (AZ-AST)
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👨🏽👩🏽👧🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone
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👩🏽❤️💋👨🏾 Kiss - Woman: Medium Skin Tone, Man: Medium-Dark Skin Tone
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Tag Latin Small Letter H
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👩🏿❤️💋👨🏻 Kiss - Woman: Dark Skin Tone, Man: Light Skin Tone
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👨❤️👩🏽 Couple With Heart - Man, Woman: Medium Skin Tone
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👩🏽👶🏽 Family - Woman: Medium Skin Tone, Baby: Medium Skin Tone
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👨🏿❤️💋👨🏻 Kiss - Man: Dark Skin Tone, Man: Light Skin Tone
👩🏼👧🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👨🏽👩🏽👧🏽👶🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone, Baby: Medium Skin Tone
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👨🏾👩🏾👧🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
👨🏿👩🏿👧🏿👶🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone, Baby: Dark Skin Tone
👩🏿👶🏿 Family - Woman: Dark Skin Tone, Baby: Dark Skin Tone
🏴 Flag for Republika Srpska (BA-SRP)
👨🏽❤️👩 Couple With Heart - Man: Medium Skin Tone, Woman
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🏴 Flag for Andalusia (ES-AN)
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👨👩👶👦 Family: Man, Woman, Baby, Boy
👨🏽👩🏽👶🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone
🏴 Flag for Saint John (BB-05)
👨🏾👩🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
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👨🏻👩🏻👶🏻👦🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone, Boy: Light Skin Tone
👩🏻👧🏻👧🏻 Family - Woman: Light Skin Tone, Girl: Light Skin Tone, Girl: Light Skin Tone
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👨🏼👩🏼👶🏼👦🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
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👨🏽❤️👩🏿 Couple With Heart - Man: Medium Skin Tone, Woman: Dark Skin Tone
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👨🏾👩🏾👶🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
🏴 Flag for Vidin (BG-05)
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👨🏽👩🏽👧🏽👧🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone, Girl: Medium Skin Tone
🏴 Flag for Gabrovo (BG-07)
👨🏿👩🏿👶🏿👦🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for Dobrich (BG-08)
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🏴 Flag for Tasmania (AU-TAS)
👨🏿❤️👩🏻 Couple With Heart - Man: Dark Skin Tone, Woman: Light Skin Tone
👩🏻👧🏻👦🏻 Family - Woman: Light Skin Tone, Girl: Light Skin Tone, Boy: Light Skin Tone
👨🏻👩🏻👶🏻👧🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone, Girl: Light Skin Tone
👨🏼👩🏼👶🏼👧🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👨🏾❤️💋👩🏾 Kiss - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone
🏴 Flag for Khojavend (AZ-XVD)
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🏴 Flag for Libertador General Bernardo O’Higgins (CL-LI)
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👨🏿❤️👩🏿 Couple With Heart - Man: Dark Skin Tone, Woman: Dark Skin Tone
🏴 Flag for Pernik (BG-14)
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🏴 Flag for Red Sea (EG-BA)
🏴 Flag for Zanzibar Central/South (TZ-11)
👨🏿👩🏿👧🏿👦🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for Pleven (BG-15)
👨🏿👨🏿👦🏿👦🏿 Family - Man: Dark Skin Tone, Man: Dark Skin Tone, Boy: Dark Skin Tone, Boy: Dark Skin Tone
👨🏽👩🏽👶🏽👧🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone, Girl: Medium Skin Tone
🏴 Flag for Smolyan (BG-21)
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👩❤️👨🏼 Couple With Heart - Woman, Man: Medium-Light Skin Tone
🏴 Flag for Razgrad (BG-17)
👨🏾❤️👨 Couple With Heart - Man: Medium-Dark Skin Tone, Man
🏴 Flag for Cunene (AO-CNN)
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🧕🏻♀️ Woman With Headscarf: Light Skin Tone
🏴 Flag for Targovishte (BG-25)
👩🏼👩🏼👶🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👨🏾👩🏾👶🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
🏴 Flag for Sofia District (BG-23)
🏴 Flag for Sofia (BG-22)
👨🏿👩🏿👧🏿👧🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Girl: Dark Skin Tone, Girl: Dark Skin Tone
👨🏻❤️💋👩🏾 Kiss - Man: Light Skin Tone, Woman: Medium-Dark Skin Tone
🧕🏽♀️ Woman With Headscarf: Medium Skin Tone
🏴 Flag for Yambol (BG-28)
🏴 Flag for Capital (BH-13)
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👨🏿👩🏿👶🏿👧🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone, Girl: Dark Skin Tone
🏴 Flag for Muharraq (BH-15)
🏴 Flag for Southern (BH-14)
🧕🏾♀️ Woman With Headscarf: Medium-Dark Skin Tone
🏴 Flag for Sibiu (RO-SB)
🧕🏼♀️ Woman With Headscarf: Medium-Light Skin Tone
👩🏻❤️👨🏿 Couple With Heart - Woman: Light Skin Tone, Man: Dark Skin Tone
🏴 Flag for Northern (BH-17)
🏴 Flag for Bubanza (BI-BB)
👩🏻❤️👩 Couple With Heart - Woman: Light Skin Tone, Woman
🏴 Flag for Flanders (BE-VLG)
👩🏽👧🏽 Family - Woman: Medium Skin Tone, Girl: Medium Skin Tone
👨🏻👩🏻👶🏻👶🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Baby: Light Skin Tone, Baby: Light Skin Tone
🏴 Flag for Bujumbura (BI-BM)
🧕🏿♀️ Woman With Headscarf: Dark Skin Tone
🏴 Flag for Bujumbura Rural (BI-BL)
👨🏾❤️💋👩🏽 Kiss - Man: Medium-Dark Skin Tone, Woman: Medium Skin Tone
👨🏼👩🏼👶🏼👶🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👨🏻👨🏻👦🏻👶🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Boy: Light Skin Tone, Baby: Light Skin Tone
🏴 Flag for Cankuzo (BI-CA)
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⃣ Combining Enclosing Keycap
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🏴 Flag for Laâyoune-Boujdour-Sakia El Hamra (MA-15)
👨🏽👩🏽👶🏽👶🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Baby: Medium Skin Tone, Baby: Medium Skin Tone
👩🏾👨🏾👧🏾 Family - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👨🏾👩🏾👶🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
🏴 Flag for Donga (BJ-DO)
👩🏽👨🏽👶🏽👦🏽 Family - Woman: Medium Skin Tone, Man: Medium Skin Tone, Baby: Medium Skin Tone, Boy: Medium Skin Tone
👨🏽❤️💋👩🏼 Kiss - Man: Medium Skin Tone, Woman: Medium-Light Skin Tone
🏴 Flag for Hauts-de-France (FR-HDF)
🏴 Flag for Alibori (BJ-AL)
🏴 Flag for Atakora (BJ-AK)
👨🏿👩🏿👶🏿👶🏿 Family - Man: Dark Skin Tone, Woman: Dark Skin Tone, Baby: Dark Skin Tone, Baby: Dark Skin Tone
🏴 Flag for Littoral (BJ-LI)
🏴 Flag for Borgou (BJ-BO)
👩👩👧👶 Family: Woman, Woman, Girl, Baby
🏴 Flag for North Dakota (US-ND)
👨🏼❤️💋👨🏾 Kiss - Man: Medium-Light Skin Tone, Man: Medium-Dark Skin Tone
🏴 Flag for Kouffo (BJ-KO)
🏴 Flag for Plateau (BJ-PL)
🏴 Flag for Carriacou and Petite Martinique (GD-10)
🏴 Flag for Zou (BJ-ZO)
👩🏼❤️👨🏻 Couple With Heart - Woman: Medium-Light Skin Tone, Man: Light Skin Tone
👩🏽❤️👨🏽 Couple With Heart - Woman: Medium Skin Tone, Man: Medium Skin Tone
👨🏽❤️👩🏼 Couple With Heart - Man: Medium Skin Tone, Woman: Medium-Light Skin Tone
👩🏽❤️👨🏻 Couple With Heart - Woman: Medium Skin Tone, Man: Light Skin Tone
🏴 Flag for Beqaa (LB-BI)
🏴 Flag for Temburong (BN-TE)
👩🏻👦🏻 Family - Woman: Light Skin Tone, Boy: Light Skin Tone
🏴 Flag for Tutong (BN-TU)
🏴 Flag for Brunei-Muara (BN-BM)
👨🏻👩🏻👦🏻👦🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone, Boy: Light Skin Tone
🏴 Flag for Vratsa (BG-06)
👩🏽❤️👨🏼 Couple With Heart - Woman: Medium Skin Tone, Man: Medium-Light Skin Tone
🏴 Flag for Beni (BO-B)
🏴 Flag for Belait (BN-BE)
👩🏼❤️👨 Couple With Heart - Woman: Medium-Light Skin Tone, Man
🏴 Flag for Ouémé (BJ-OU)
👩🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Roche Caiman (SC-25)
👩🏻❤️👨🏾 Couple With Heart - Woman: Light Skin Tone, Man: Medium-Dark Skin Tone
🏴 Flag for Cochabamba (BO-C)
👨🏾👩🏾👧🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
🏴 Flag for Pando (BO-N)
👩🏽❤️👩🏻 Couple With Heart - Woman: Medium Skin Tone, Woman: Light Skin Tone
👩🏾❤️👨🏽 Couple With Heart - Woman: Medium-Dark Skin Tone, Man: Medium Skin Tone
🏴 Flag for Chuquisaca (BO-H)
🏴 Flag for La Paz (BO-L)
🏴 Flag for Khentii (MN-039)
🕴🏽♀️ Woman in Business Suit Levitating: Medium Skin Tone
🏴 Flag for Dolneni (MK-27)
🏴 Flag for Stara Zagora (BG-24)
👩🏽👦🏽 Family - Woman: Medium Skin Tone, Boy: Medium Skin Tone
🏴 Flag for Sistan and Baluchestan (IR-13)
👩🏾❤️👨🏼 Couple With Heart - Woman: Medium-Dark Skin Tone, Man: Medium-Light Skin Tone
🏴 Flag for Potosí (BO-P)
🏴 Flag for Bonaire (BQ-BO)
👩❤️💋👨🏻 Kiss - Woman, Man: Light Skin Tone
👩🏾❤️👨 Couple With Heart - Woman: Medium-Dark Skin Tone, Man
👩🏼👦🏼👦🏼 Family - Woman: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
🏴 Flag for Brčko District (BA-BRC)
🏴 Flag for Saba (BQ-SA)
👩🏽❤️👨🏾 Couple With Heart - Woman: Medium Skin Tone, Man: Medium-Dark Skin Tone
👩🏾❤️👨🏿 Couple With Heart - Woman: Medium-Dark Skin Tone, Man: Dark Skin Tone
🏴 Flag for Acre (BR-AC)
🏴 Flag for Gitega (BI-GI)
👩🏿👦🏿 Family - Woman: Dark Skin Tone, Boy: Dark Skin Tone
👩🏿❤️👨🏻 Couple With Heart - Woman: Dark Skin Tone, Man: Light Skin Tone
🏴 Flag for Amazonas (BR-AM)
🏴 Flag for Buenos Aires (AR-C)
👨🏼👩🏼👧🏼👶🏼 Family - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👨🏼❤️💋👨🏼 Kiss - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone
🏴 Flag for Espírito Santo (BR-ES)
👨🏿❤️💋👨🏾 Kiss - Man: Dark Skin Tone, Man: Medium-Dark Skin Tone
👨🏼❤️💋👨🏽 Kiss - Man: Medium-Light Skin Tone, Man: Medium Skin Tone
👩🏾👦🏾👦🏾 Family - Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👨🏻❤️👩 Couple With Heart - Man: Light Skin Tone, Woman
👨🏿❤️💋👩🏾 Kiss - Man: Dark Skin Tone, Woman: Medium-Dark Skin Tone
👩🏻❤️💋👩🏽 Kiss - Woman: Light Skin Tone, Woman: Medium Skin Tone
👨🏼❤️💋👨🏿 Kiss - Man: Medium-Light Skin Tone, Man: Dark Skin Tone
👩🏽👦🏽👦🏽 Family - Woman: Medium Skin Tone, Boy: Medium Skin Tone, Boy: Medium Skin Tone
👩🏿❤️👩🏼 Couple With Heart - Woman: Dark Skin Tone, Woman: Medium-Light Skin Tone
🏴 Flag for Maranhão (BR-MA)
👩🏿❤️👩🏽 Couple With Heart - Woman: Dark Skin Tone, Woman: Medium Skin Tone
👩🏿❤️👩 Couple With Heart - Woman: Dark Skin Tone, Woman
🏴 Flag for Amapá (BR-AP)
👨🏽❤️👨🏻 Couple With Heart - Man: Medium Skin Tone, Man: Light Skin Tone
👩🏻❤️💋👨🏻 Kiss - Woman: Light Skin Tone, Man: Light Skin Tone
👨🏽❤️💋👨🏽 Kiss - Man: Medium Skin Tone, Man: Medium Skin Tone
👩🏿❤️💋👩🏻 Kiss - Woman: Dark Skin Tone, Woman: Light Skin Tone
👨🏽❤️💋👩🏿 Kiss - Man: Medium Skin Tone, Woman: Dark Skin Tone
👩🏼❤️💋👨🏾 Kiss - Woman: Medium-Light Skin Tone, Man: Medium-Dark Skin Tone
👨🏿❤️💋👨🏼 Kiss - Man: Dark Skin Tone, Man: Medium-Light Skin Tone
👨🏾❤️💋👨🏿 Kiss - Man: Medium-Dark Skin Tone, Man: Dark Skin Tone
👩🏽❤️💋👩🏿 Kiss - Woman: Medium Skin Tone, Woman: Dark Skin Tone
👩🏼❤️💋👨🏿 Kiss - Woman: Medium-Light Skin Tone, Man: Dark Skin Tone
👨🏽❤️💋👩🏽 Kiss - Man: Medium Skin Tone, Woman: Medium Skin Tone
👨🏾❤️💋👨🏼 Kiss - Man: Medium-Dark Skin Tone, Man: Medium-Light Skin Tone
👨🏽❤️💋👩🏻 Kiss - Man: Medium Skin Tone, Woman: Light Skin Tone
👨🏾❤️💋👨 Kiss - Man: Medium-Dark Skin Tone, Man
👨🏾❤️💋👨🏾 Kiss - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone
👩❤️💋👨🏾 Kiss - Woman, Man: Medium-Dark Skin Tone
👩❤️💋👩🏻 Kiss - Woman, Woman: Light Skin Tone
👩🏽❤️💋👨🏻 Kiss - Woman: Medium Skin Tone, Man: Light Skin Tone
👩🏿❤️💋👨🏿 Kiss - Woman: Dark Skin Tone, Man: Dark Skin Tone
👩🏻❤️💋👩🏿 Kiss - Woman: Light Skin Tone, Woman: Dark Skin Tone
👩🏻❤️💋👩🏼 Kiss - Woman: Light Skin Tone, Woman: Medium-Light Skin Tone
👩🏾❤️💋👩🏿 Kiss - Woman: Medium-Dark Skin Tone, Woman: Dark Skin Tone
👩🏾❤️💋👩 Kiss - Woman: Medium-Dark Skin Tone, Woman
👩🏾❤️💋👩🏻 Kiss - Woman: Medium-Dark Skin Tone, Woman: Light Skin Tone
👩🏻❤️👨 Couple With Heart - Woman: Light Skin Tone, Man
👩🏻👩🏻👦🏻 Family - Woman: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone
👩🏾❤️💋👨🏾 Kiss - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone
👨🏻❤️👨🏽 Couple With Heart - Man: Light Skin Tone, Man: Medium Skin Tone
🏴 Flag for Mato Grosso (BR-MT)
👨🏽❤️👩🏻 Couple With Heart - Man: Medium Skin Tone, Woman: Light Skin Tone
👨❤️👨🏿 Couple With Heart - Man, Man: Dark Skin Tone
👩🏿❤️💋👨🏼 Kiss - Woman: Dark Skin Tone, Man: Medium-Light Skin Tone
👩🏿❤️💋👩🏾 Kiss - Woman: Dark Skin Tone, Woman: Medium-Dark Skin Tone
👩🏻👦🏻👧🏻 Family - Woman: Light Skin Tone, Boy: Light Skin Tone, Girl: Light Skin Tone
🏴 Flag for Santa Cruz (BO-S)
👨🏻❤️👩🏽 Couple With Heart - Man: Light Skin Tone, Woman: Medium Skin Tone
👨🏽❤️👩🏽 Couple With Heart - Man: Medium Skin Tone, Woman: Medium Skin Tone
👩🏾❤️💋👩🏽 Kiss - Woman: Medium-Dark Skin Tone, Woman: Medium Skin Tone
🏴 Flag for Collines (BJ-CO)
👨🏻👩🏻👦🏻 Family - Man: Light Skin Tone, Woman: Light Skin Tone, Boy: Light Skin Tone
👨❤️👨🏽 Couple With Heart - Man, Man: Medium Skin Tone
👨🏾👩🏾👦🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👨🏼❤️👨 Couple With Heart - Man: Medium-Light Skin Tone, Man
👨🏾❤️👩🏽 Couple With Heart - Man: Medium-Dark Skin Tone, Woman: Medium Skin Tone
🏴 Flag for Pará (BR-PA)
👩🏽👦🏽👧🏽 Family - Woman: Medium Skin Tone, Boy: Medium Skin Tone, Girl: Medium Skin Tone
👨🏼❤️👨🏼 Couple With Heart - Man: Medium-Light Skin Tone, Man: Medium-Light Skin Tone
👨🏿❤️👨🏻 Couple With Heart - Man: Dark Skin Tone, Man: Light Skin Tone
👩🏽❤️👩🏽 Couple With Heart - Woman: Medium Skin Tone, Woman: Medium Skin Tone
👨🏾❤️👨🏽 Couple With Heart - Man: Medium-Dark Skin Tone, Man: Medium Skin Tone
👨🏽❤️👨🏽 Couple With Heart - Man: Medium Skin Tone, Man: Medium Skin Tone
👨🏻❤️👩🏼 Couple With Heart - Man: Light Skin Tone, Woman: Medium-Light Skin Tone
👨🏾❤️👩🏿 Couple With Heart - Man: Medium-Dark Skin Tone, Woman: Dark Skin Tone
👨🏾❤️👨🏼 Couple With Heart - Man: Medium-Dark Skin Tone, Man: Medium-Light Skin Tone
👩🏾❤️💋👩🏾 Kiss - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone
👩🏼❤️👩🏻 Couple With Heart - Woman: Medium-Light Skin Tone, Woman: Light Skin Tone
👨🏿❤️👩🏼 Couple With Heart - Man: Dark Skin Tone, Woman: Medium-Light Skin Tone
👨🏼❤️👨🏾 Couple With Heart - Man: Medium-Light Skin Tone, Man: Medium-Dark Skin Tone
👨🏽❤️👨🏾 Couple With Heart - Man: Medium Skin Tone, Man: Medium-Dark Skin Tone
👩❤️👨🏾 Couple With Heart - Woman, Man: Medium-Dark Skin Tone
🏴 Flag for Alagoas (BR-AL)
👩❤️👨🏻 Couple With Heart - Woman, Man: Light Skin Tone
🏴 Flag for Hauts-Bassins (BF-09)
👨🏼👦🏼 Family - Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone
👩🏾❤️👩🏾 Couple With Heart - Woman: Medium-Dark Skin Tone, Woman: Medium-Dark Skin Tone
🏴 Flag for Rio de Janeiro (BR-RJ)
👨🏾❤️💋👩🏻 Kiss - Man: Medium-Dark Skin Tone, Woman: Light Skin Tone
🏴 Flag for Rondônia (BR-RO)
👨🏾❤️👨🏿 Couple With Heart - Man: Medium-Dark Skin Tone, Man: Dark Skin Tone
👨🏽👦🏽 Family - Man: Medium Skin Tone, Boy: Medium Skin Tone
👨🏼❤️👨🏽 Couple With Heart - Man: Medium-Light Skin Tone, Man: Medium Skin Tone
🏴 Flag for Piauí (BR-PI)
👨🏽👩🏽👦🏽👦🏽 Family - Man: Medium Skin Tone, Woman: Medium Skin Tone, Boy: Medium Skin Tone, Boy: Medium Skin Tone
🏴 Flag for Rio Grande do Norte (BR-RN)
👩🏻❤️👨🏻 Couple With Heart - Woman: Light Skin Tone, Man: Light Skin Tone
👨🏻👦🏻 Family - Man: Light Skin Tone, Boy: Light Skin Tone
👩🏼❤️👩🏾 Couple With Heart - Woman: Medium-Light Skin Tone, Woman: Medium-Dark Skin Tone
👨🏿❤️👩🏾 Couple With Heart - Man: Dark Skin Tone, Woman: Medium-Dark Skin Tone
🏴 Flag for Sergipe (BR-SE)
🏴 Flag for Paraná (BR-PR)
👨🏿👦🏿 Family - Man: Dark Skin Tone, Boy: Dark Skin Tone
👩🏼❤️👩🏽 Couple With Heart - Woman: Medium-Light Skin Tone, Woman: Medium Skin Tone
👩🏾❤️👩🏼 Couple With Heart - Woman: Medium-Dark Skin Tone, Woman: Medium-Light Skin Tone
🏴 Flag for Moscow Province (RU-MOS)
👩🏽❤️💋👩🏽 Kiss - Woman: Medium Skin Tone, Woman: Medium Skin Tone
👩🏿👦🏿👦🏿 Family - Woman: Dark Skin Tone, Boy: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for São Paulo (BR-SP)
🏴 Flag for East Azerbaijan (IR-01)
🏴 Flag for Rio Grande do Sul (BR-RS)
👩🏼❤️👨🏿 Couple With Heart - Woman: Medium-Light Skin Tone, Man: Dark Skin Tone
🏴 Flag for Sogn og Fjordane (NO-14)
🏴 Flag for Tocantins (BR-TO)
🏴 Flag for Sveti Andraž v Slovenskih Goricah (SI-182)
👨🏼❤️👩🏻 Couple With Heart - Man: Medium-Light Skin Tone, Woman: Light Skin Tone
👨🏿❤️👨🏽 Couple With Heart - Man: Dark Skin Tone, Man: Medium Skin Tone
👨🏽👦🏽👦🏽 Family - Man: Medium Skin Tone, Boy: Medium Skin Tone, Boy: Medium Skin Tone
👨🏿👦🏿👦🏿 Family - Man: Dark Skin Tone, Boy: Dark Skin Tone, Boy: Dark Skin Tone
🏴 Flag for Bimini (BS-BI)
👨🏿❤️👩 Couple With Heart - Man: Dark Skin Tone, Woman
👩🏻👦🏻👦🏻 Family - Woman: Light Skin Tone, Boy: Light Skin Tone, Boy: Light Skin Tone
🏴 Flag for Roraima (BR-RR)
🏴 Flag for Oruro (BO-O)
🏴 Flag for Exuma (BS-EX)
👨🏾👦🏾 Family - Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone
👩🏽❤️👨 Couple With Heart - Woman: Medium Skin Tone, Man
🏴 Flag for Central Eleuthera (BS-CE)
🏴 Flag for Berry Islands (BS-BY)
🏴 Flag for Makamba (BI-MA)
🏴 Flag for Federal District (BR-DF)
👩🏻❤️👩🏾 Couple With Heart - Woman: Light Skin Tone, Woman: Medium-Dark Skin Tone
👨🏼❤️💋👩🏼 Kiss - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone
🏴 Flag for Central Abaco (BS-CO)
🏴 Flag for East Grand Bahama (BS-EG)
🏴 Flag for Central Andros (BS-CS)
👨🏻👦🏻👧🏻 Family - Man: Light Skin Tone, Boy: Light Skin Tone, Girl: Light Skin Tone
🏴 Flag for Crooked Island (BS-CK)
🏴 Flag for Black Point (BS-BP)
👨🏼👦🏼👧🏼 Family - Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
👨🏽👦🏽👧🏽 Family - Man: Medium Skin Tone, Boy: Medium Skin Tone, Girl: Medium Skin Tone
👩🏿❤️👨🏾 Couple With Heart - Woman: Dark Skin Tone, Man: Medium-Dark Skin Tone
👩🏾❤️💋👨🏼 Kiss - Woman: Medium-Dark Skin Tone, Man: Medium-Light Skin Tone
🏴 Flag for North Eleuthera (BS-NE)
🏴 Flag for North Abaco (BS-NO)
🏴 Flag for Mayaguana (BS-MG)
👨🏾👦🏾👧🏾 Family - Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Girl: Medium-Dark Skin Tone
👨🏼❤️💋👩🏻 Kiss - Man: Medium-Light Skin Tone, Woman: Light Skin Tone
🏴 Flag for Grand Cay (BS-GC)
🏴 Flag for Freeport (BS-FP)
🏴 Flag for Inagua (BS-IN)
🏴 Flag for Hope Town (BS-HT)
👩🏾❤️👩🏿 Couple With Heart - Woman: Medium-Dark Skin Tone, Woman: Dark Skin Tone
🏴 Flag for Long Island (BS-LI)
👨🏿👦🏿👧🏿 Family - Man: Dark Skin Tone, Boy: Dark Skin Tone, Girl: Dark Skin Tone
👨🏾❤️👩 Couple With Heart - Man: Medium-Dark Skin Tone, Woman
👩🏿❤️👨🏿 Couple With Heart - Woman: Dark Skin Tone, Man: Dark Skin Tone
👨🏻👦🏻👶🏻 Family - Man: Light Skin Tone, Boy: Light Skin Tone, Baby: Light Skin Tone
👨👨👶 Family: Man, Man, Baby
👩👧👶 Family: Woman, Girl, Baby
👨👦👶 Family: Man, Boy, Baby
👨👨👶👦 Family: Man, Man, Baby, Boy
👨👦👧 Family: Man, Boy, Girl
👨👶👶 Family: Man, Baby, Baby
🏴 Flag for Ragged Island (BS-RI)
👩🏿❤️👩🏿 Couple With Heart - Woman: Dark Skin Tone, Woman: Dark Skin Tone
👩🏿❤️👨🏽 Couple With Heart - Woman: Dark Skin Tone, Man: Medium Skin Tone
👩🏼❤️👨🏼 Couple With Heart - Woman: Medium-Light Skin Tone, Man: Medium-Light Skin Tone
🏴 Flag for North Andros (BS-NS)
👩🏿❤️👩🏻 Couple With Heart - Woman: Dark Skin Tone, Woman: Light Skin Tone
👨🏻❤️💋👨 Kiss - Man: Light Skin Tone, Man
🏴 Flag for South Andros (BS-SA)
👨🏻❤️💋👨🏼 Kiss - Man: Light Skin Tone, Man: Medium-Light Skin Tone
🏴 Flag for South Eleuthera (BS-SE)
👨🏼👦🏼👶🏼 Family - Man: Medium-Light Skin Tone, Boy: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👨🏻❤️💋👩🏻 Kiss - Man: Light Skin Tone, Woman: Light Skin Tone
👨🏼❤️💋👩🏾 Kiss - Man: Medium-Light Skin Tone, Woman: Medium-Dark Skin Tone
👨🏾❤️💋👩🏼 Kiss - Man: Medium-Dark Skin Tone, Woman: Medium-Light Skin Tone
👨🏾❤️💋👨🏻 Kiss - Man: Medium-Dark Skin Tone, Man: Light Skin Tone
🏴 Flag for Santa Catarina (BR-SC)
👩👩👦👧 Family: Woman, Woman, Boy, Girl
👨❤️💋👩🏾 Kiss - Man, Woman: Medium-Dark Skin Tone
🏴 Flag for Rum Cay (BS-RC)
👩👩👶👦 Family: Woman, Woman, Baby, Boy
👨🏻❤️💋👩🏽 Kiss - Man: Light Skin Tone, Woman: Medium Skin Tone
🏴 Flag for Cat Island (BS-CI)
👩🏽❤️👩 Couple With Heart - Woman: Medium Skin Tone, Woman
👨🏽👦🏽👶🏽 Family - Man: Medium Skin Tone, Boy: Medium Skin Tone, Baby: Medium Skin Tone
👩👨👦👶 Family: Woman, Man, Boy, Baby
👨🏾❤️💋👩 Kiss - Man: Medium-Dark Skin Tone, Woman
👨❤️💋👨🏻 Kiss - Man, Man: Light Skin Tone
👨🏻❤️💋👨🏿 Kiss - Man: Light Skin Tone, Man: Dark Skin Tone
👨🏼❤️💋👩🏽 Kiss - Man: Medium-Light Skin Tone, Woman: Medium Skin Tone
👨🏾👦🏾👶🏾 Family - Man: Medium-Dark Skin Tone, Boy: Medium-Dark Skin Tone, Baby: Medium-Dark Skin Tone
🏴 Flag for South Abaco (BS-SO)
👩🏾❤️💋👩🏼 Kiss - Woman: Medium-Dark Skin Tone, Woman: Medium-Light Skin Tone
👨🏻❤️👨🏿 Couple With Heart - Man: Light Skin Tone, Man: Dark Skin Tone
👨🏿❤️💋👨🏿 Kiss - Man: Dark Skin Tone, Man: Dark Skin Tone
👩🏾❤️💋👨🏿 Kiss - Woman: Medium-Dark Skin Tone, Man: Dark Skin Tone
👩🏼❤️💋👨🏽 Kiss - Woman: Medium-Light Skin Tone, Man: Medium Skin Tone
👩🏾❤️💋👨🏻 Kiss - Woman: Medium-Dark Skin Tone, Man: Light Skin Tone
👩🏽❤️💋👨 Kiss - Woman: Medium Skin Tone, Man
👨👧👶 Family: Man, Girl, Baby
👩🏻❤️💋👨🏾 Kiss - Woman: Light Skin Tone, Man: Medium-Dark Skin Tone
👨❤️👨🏼 Couple With Heart - Man, Man: Medium-Light Skin Tone
👩🏼❤️💋👩🏼 Kiss - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone
👨🏿❤️💋👩🏿 Kiss - Man: Dark Skin Tone, Woman: Dark Skin Tone
👨❤️💋👩🏼 Kiss - Man, Woman: Medium-Light Skin Tone
🏴 Flag for Abidjan (CI-AB)
👩🏻❤️💋👨 Kiss - Woman: Light Skin Tone, Man
👩🏼❤️💋👩🏾 Kiss - Woman: Medium-Light Skin Tone, Woman: Medium-Dark Skin Tone
👨🏻❤️💋👩🏼 Kiss - Man: Light Skin Tone, Woman: Medium-Light Skin Tone
👩🏽❤️💋👨🏿 Kiss - Woman: Medium Skin Tone, Man: Dark Skin Tone
👩🏿❤️💋👩🏼 Kiss - Woman: Dark Skin Tone, Woman: Medium-Light Skin Tone
👩🏿❤️💋👨🏾 Kiss - Woman: Dark Skin Tone, Man: Medium-Dark Skin Tone
👩🏼❤️💋👨 Kiss - Woman: Medium-Light Skin Tone, Man
👩❤️👩🏾 Couple With Heart - Woman, Woman: Medium-Dark Skin Tone
👨🏿❤️👨🏼 Couple With Heart - Man: Dark Skin Tone, Man: Medium-Light Skin Tone
👨🏿👦🏿👶🏿 Family - Man: Dark Skin Tone, Boy: Dark Skin Tone, Baby: Dark Skin Tone
👨🏼❤️👩🏼 Couple With Heart - Man: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone
👩🏼❤️👨🏽 Couple With Heart - Woman: Medium-Light Skin Tone, Man: Medium Skin Tone
🏴 Flag for Spanish Wells (BS-SW)
👨🏿❤️👨🏿 Couple With Heart - Man: Dark Skin Tone, Man: Dark Skin Tone
👨🏼❤️👨🏿 Couple With Heart - Man: Medium-Light Skin Tone, Man: Dark Skin Tone
👨🏼❤️👩 Couple With Heart - Man: Medium-Light Skin Tone, Woman
👩🏼❤️👩🏼 Couple With Heart - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone
👨🏼❤️👨🏻 Couple With Heart - Man: Medium-Light Skin Tone, Man: Light Skin Tone
👨🏾❤️👨🏾 Couple With Heart - Man: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone
👩❤️👩🏼 Couple With Heart - Woman, Woman: Medium-Light Skin Tone
👨🏼❤️👩🏿 Couple With Heart - Man: Medium-Light Skin Tone, Woman: Dark Skin Tone
👨🏻❤️👨🏾 Couple With Heart - Man: Light Skin Tone, Man: Medium-Dark Skin Tone
👨🏽❤️👩🏾 Couple With Heart - Man: Medium Skin Tone, Woman: Medium-Dark Skin Tone
👩❤️👩🏿 Couple With Heart - Woman, Woman: Dark Skin Tone
👨🏽❤️👨🏿 Couple With Heart - Man: Medium Skin Tone, Man: Dark Skin Tone
👨👨👦👶 Family: Man, Man, Boy, Baby
👨🏿❤️👨 Couple With Heart - Man: Dark Skin Tone, Man
👩🏻❤️👩🏿 Couple With Heart - Woman: Light Skin Tone, Woman: Dark Skin Tone
🏴 Flag for San Salvador (BS-SS)
🏴 Flag for Samtse (BT-14)
👩🏻❤️👨🏽 Couple With Heart - Woman: Light Skin Tone, Man: Medium Skin Tone
👩🏼❤️👩🏿 Couple With Heart - Woman: Medium-Light Skin Tone, Woman: Dark Skin Tone
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👩🏻❤️💋👨🏽 Kiss - Woman: Light Skin Tone, Man: Medium Skin Tone
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👨👩👶👧 Family: Man, Woman, Baby, Girl
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👨🏼❤️💋👩🏿 Kiss - Man: Medium-Light Skin Tone, Woman: Dark Skin Tone
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👩🏾❤️👨🏾 Couple With Heart - Woman: Medium-Dark Skin Tone, Man: Medium-Dark Skin Tone
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👨🏻👧🏻👧🏻 Family - Man: Light Skin Tone, Girl: Light Skin Tone, Girl: Light Skin Tone
👨🏼👧🏼👶🏼 Family - Man: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Baby: Medium-Light Skin Tone
👨🏽👧🏽👶🏽 Family - Man: Medium Skin Tone, Girl: Medium Skin Tone, Baby: Medium Skin Tone
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🏴 Flag for Češinovo-Obleševo (MK-81)
🏴 Flag for Kidal (ML-8)
🏴 Flag for Bago (MM-02)
🏴 Flag for Struga (MK-72)
🏴 Flag for Tearce (MK-75)
🏴 Flag for Studeničani (MK-74)
🏴 Flag for Ohrid (MK-58)
🏴 Flag for Sveti Nikole (MK-69)
🏴 Flag for Strumica (MK-73)
🏴 Flag for Sikasso (ML-3)
🏴 Flag for Kachin (MM-11)
🏴 Flag for Resen (MK-66)
🏴 Flag for Bamako (ML-BKO)
🏴 Flag for Magway (MM-03)
🏴 Flag for Sopište (MK-70)
🏴 Flag for Staro Nagoričane (MK-71)
🏴 Flag for Ayeyarwady (MM-07)
🏴 Flag for Gao (ML-7)
🏴 Flag for Mopti (ML-5)
🏴 Flag for Štip (MK-83)
🏴 Flag for Kayah (MM-12)
🏴 Flag for Tanintharyi (MM-05)
🏴 Flag for Koulikoro (ML-2)
🏴 Flag for Probištip (MK-63)
🏴 Flag for Pehčevo (MK-60)
🏴 Flag for Sagaing (MM-01)
🏴 Flag for Čaška (MK-80)
🏴 Flag for Rankovce (MK-65)
🏴 Flag for Yangon (MM-06)
🏴 Flag for Tetovo (MK-76)
🏴 Flag for Rosoman (MK-67)
🏴 Flag for Assaba (MR-03)
🏴 Flag for Shan (MM-17)
🏴 Flag for Rakhine (MM-16)
🏴 Flag for Khövsgöl (MN-041)
🏴 Flag for Bayan-Ölgii (MN-071)
🏴 Flag for Bayankhongor (MN-069)
🏴 Flag for Dornod (MN-061)
🏴 Flag for Selenge (MN-049)
🏴 Flag for Ulaanbaatar (MN-1)
🏴 Flag for Darkhan-Uul (MN-037)
🏴 Flag for Töv (MN-047)
🏴 Flag for Mon (MM-15)
🏴 Flag for Trarza (MR-06)
🏴 Flag for Sükhbaatar (MN-051)
🏴 Flag for Gorgol (MR-04)
🏴 Flag for Övörkhangai (MN-055)
🏴 Flag for Chin (MM-14)
🏴 Flag for Bulgan (MN-067)
🏴 Flag for Zavkhan (MN-057)
🏴 Flag for Dornogovi (MN-063)
🏴 Flag for Ömnögovi (MN-053)
🏴 Flag for Kayin (MM-13)
🏴 Flag for Govi-Altai (MN-065)
🏴 Flag for Tiris Zemmour (MR-11)
🏴 Flag for Dundgovi (MN-059)
🏴 Flag for Arkhangai (MN-073)
🏴 Flag for Tagant (MR-09)
🏴 Flag for Khovd (MN-043)
🏴 Flag for Uvs (MN-046)
🏴 Flag for Govisümber (MN-064)
🏴 Flag for Brakna (MR-05)
🏴 Flag for Dakhlet Nouadhibou (MR-08)
🏴 Flag for Hodh Ech Chargui (MR-01)
🏴 Flag for Orkhon (MN-035)
🏴 Flag for Hodh El Gharbi (MR-02)
🏴 Flag for Naypyidaw (MM-18)
🏴 Flag for Adrar (MR-07)
🏴 Flag for Inchiri (MR-12)
🏴 Flag for Iklin (MT-19)
🏴 Flag for Għarb (MT-14)
🏴 Flag for Mqabba (MT-33)
🏴 Flag for Kerċem (MT-22)
🏴 Flag for Għasri (MT-16)
🏴 Flag for Lija (MT-24)
🏴 Flag for Birżebbuġa (MT-05)
🏴 Flag for Birkirkara (MT-04)
🏴 Flag for Mġarr (MT-31)
🏴 Flag for Balzan (MT-02)
🏴 Flag for Munxar (MT-36)
🏴 Flag for Għajnsielem (MT-13)
🏴 Flag for Naxxar (MT-38)
🏴 Flag for Floriana (MT-09)
🏴 Flag for Marsa (MT-26)
🏴 Flag for Dingli (MT-07)
🏴 Flag for Gudja (MT-11)
🏴 Flag for Kirkop (MT-23)
🏴 Flag for Marsaskala (MT-27)
🏴 Flag for Paola (MT-39)
🏴 Flag for Fontana (MT-10)
🏴 Flag for Msida (MT-34)
🏴 Flag for Nadur (MT-37)
🏴 Flag for Mosta (MT-32)
🏴 Flag for Imtarfa (MT-35)
🏴 Flag for Cospicua (MT-06)
🏴 Flag for Birgu (MT-03)
🏴 Flag for Nouakchott Nord (MR-14)
🏴 Flag for Gżira (MT-12)
🏴 Flag for Mellieħa (MT-30)
🏴 Flag for Għaxaq (MT-17)
🏴 Flag for Ħamrun (MT-18)
🏴 Flag for Fgura (MT-08)
🏴 Flag for Attard (MT-01)
🏴 Flag for Għargħur (MT-15)
🏴 Flag for Kalkara (MT-21)
🏴 Flag for Nouakchott Sud (MR-15)
🏴 Flag for Marsaxlokk (MT-28)
🏴 Flag for Victoria (MT-45)
🏴 Flag for Qala (MT-42)
🏴 Flag for Żabbar (MT-64)
🏴 Flag for Agaléga (MU-AG)
🏴 Flag for Ta’ Xbiex (MT-58)
🏴 Flag for Pietà (MT-41)
🏴 Flag for Sannat (MT-52)
🏴 Flag for Port Louis District (MU-PL)
🏴 Flag for Xagħra (MT-61)
🏴 Flag for Rivière Noire (MU-BL)
🏴 Flag for Sliema (MT-56)
🏴 Flag for Safi (MT-47)
🏴 Flag for Flacq (MU-FL)
🏴 Flag for Pembroke (MT-40)
🏴 Flag for Swieqi (MT-57)
🏴 Flag for Curepipe (MU-CU)
🏴 Flag for Żurrieq (MT-68)
🏴 Flag for San Ġwann (MT-49)
🏴 Flag for Grand Port (MU-GP)
🏴 Flag for Cargados Carajos (MU-CC)
🏴 Flag for Qrendi (MT-44)
🏴 Flag for Valletta (MT-60)
🏴 Flag for Pamplemousses (MU-PA)
🏴 Flag for Qormi (MT-43)
🏴 Flag for Port Louis (MU-PU)
🏴 Flag for Tarxien (MT-59)
🏴 Flag for Żebbuġ Gozo (MT-65)
🏴 Flag for Saint Lawrence (MT-50)
🏴 Flag for Żejtun (MT-67)
🏴 Flag for St. Paul’s Bay (MT-51)
🏴 Flag for Santa Luċija (MT-53)
🏴 Flag for Żebbuġ (MT-66)
🏴 Flag for Rabat (MT-46)
🏴 Flag for Siġġiewi (MT-55)
👩🏽👩🏽👧🏽 Family - Woman: Medium Skin Tone, Woman: Medium Skin Tone, Girl: Medium Skin Tone
🏴 Flag for Santa Venera (MT-54)
🏴 Flag for Xgħajra (MT-63)
🏴 Flag for Moka (MU-MO)
🏴 Flag for Michoacán (MX-MIC)
🏴 Flag for Northern (MW-N)
🏴 Flag for Upper North Province (MV-UN)
🏴 Flag for Colima (MX-COL)
🏴 Flag for Rodrigues (MU-RO)
🏴 Flag for Guanajuato (MX-GUA)
🏴 Flag for Ciudad de Mexico (MX-CMX)
🏴 Flag for Puebla (MX-PUE)
🏴 Flag for Quatre Bornes (MU-QB)
🏴 Flag for Oaxaca (MX-OAX)
🏴 Flag for Central (MW-C)
🏴 Flag for Savanne (MU-SA)
🏴 Flag for Morelos (MX-MOR)
🏴 Flag for Hidalgo (MX-HID)
🏴 Flag for Aguascalientes (MX-AGU)
🏴 Flag for Campeche (MX-CAM)
🏴 Flag for Nuevo León (MX-NLE)
🏴 Flag for Malé (MV-MLE)
🏴 Flag for Guerrero (MX-GRO)
🏴 Flag for Vacoas-Phoenix (MU-VP)
👨🏻👨🏻👦🏻👧🏻 Family - Man: Light Skin Tone, Man: Light Skin Tone, Boy: Light Skin Tone, Girl: Light Skin Tone
🏴 Flag for North Central Province (MV-NC)
🏴 Flag for Mexico State (MX-MEX)
🏴 Flag for Plaines Wilhems (MU-PW)
🏴 Flag for Central Province (MV-CE)
🏴 Flag for Coahuila (MX-COA)
🏴 Flag for South Province (MV-SU)
🏴 Flag for Chiapas (MX-CHP)
🏴 Flag for Southern (MW-S)
🏴 Flag for Sofala (MZ-S)
🏴 Flag for Perlis (MY-09)
🏴 Flag for Veracruz (MX-VER)
🏴 Flag for Sarawak (MY-13)
🏴 Flag for Kelantan (MY-03)
🏴 Flag for Zambezi (NA-CA)
🏴 Flag for Manica (MZ-B)
🏴 Flag for Labuan (MY-15)
🏴 Flag for Cabo Delgado (MZ-P)
🏴 Flag for Hardap (NA-HA)
🏴 Flag for Tete (MZ-T)
🏴 Flag for Kedah (MY-02)
🏴 Flag for Pahang (MY-06)
🏴 Flag for Penang (MY-07)
🏴 Flag for Perak (MY-08)
🏴 Flag for Maputo Province (MZ-L)
🏴 Flag for Goiás (BR-GO)
🏴 Flag for Terengganu (MY-11)
🏴 Flag for Inhambane (MZ-I)
🏴 Flag for Malacca (MY-04)
🏴 Flag for Erongo (NA-ER)
🏴 Flag for Tlaxcala (MX-TLA)
🏴 Flag for Negeri Sembilan (MY-05)
🏴 Flag for Zacatecas (MX-ZAC)
🏴 Flag for Tamaulipas (MX-TAM)
🏴 Flag for Niassa (MZ-A)
🏴 Flag for Maputo (MZ-MPM)
🏴 Flag for Nampula (MZ-N)
🏴 Flag for Putrajaya (MY-16)
🏴 Flag for Sinaloa (MX-SIN)
🏴 Flag for Yucatán (MX-YUC)
🏴 Flag for Sabah (MY-12)
👩🏼👩🏼👧🏼👧🏼 Family - Woman: Medium-Light Skin Tone, Woman: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone, Girl: Medium-Light Skin Tone
🏴 Flag for Zambezia (MZ-Q)
🏴 Flag for Querétaro (MX-QUE)
🏴 Flag for Gaza (MZ-G)
🏴 Flag for Otjozondjupa (NA-OD)
🏴 Flag for Maradi (NE-4)
🏴 Flag for Kunene (NA-KU)
🏴 Flag for Akwa Ibom (NG-AK)
🏴 Flag for Tahoua (NE-5)
🏴 Flag for Rivière du Rempart (MU-RR)
🏴 Flag for Imo (NG-IM)
🏴 Flag for Katsina (NG-KT)
🏴 Flag for Dosso (NE-3)
🏴 Flag for Tillabéri (NE-6)
🏴 Flag for Ekiti (NG-EK)
🏴 Flag for Omaheke (NA-OH)
🏴 Flag for Bauchi (NG-BA)
🏴 Flag for Karas (NA-KA)
🏴 Flag for Bayelsa (NG-BY)
🏴 Flag for Ohangwena (NA-OW)
🏴 Flag for Benue (NG-BE)
🏴 Flag for Enugu (NG-EN)
🏴 Flag for Oshana (NA-ON)
🏴 Flag for Kaduna (NG-KD)
👨🏻👶🏻👦🏻 Family - Man: Light Skin Tone, Baby: Light Skin Tone, Boy: Light Skin Tone
🏴 Flag for Kebbi (NG-KE)
🏴 Flag for Jigawa (NG-JI)
🏴 Flag for Niamey (NE-8)
🏴 Flag for Anambra (NG-AN)
🏴 Flag for Gombe (NG-GO)
🏴 Flag for Agadez (NE-1)
🏴 Flag for Khomas (NA-KH)
🏴 Flag for Diffa (NE-2)
🏴 Flag for Johor (MY-01)
🏴 Flag for Kano (NG-KN)
🏴 Flag for Omusati (NA-OS)
🏴 Flag for Kogi (NG-KO)
🏴 Flag for Edo (NG-ED)
🏴 Flag for Abia (NG-AB)
🏴 Flag for Oshikoto (NA-OT)
🏴 Flag for Kavango West (NA-KW)
🏴 Flag for Ebonyi (NG-EB)
🏴 Flag for Zinder (NE-7)
🏴 Flag for Jinotega (NI-JI)
🏴 Flag for Nasarawa (NG-NA)
🏴 Flag for Friesland (NL-FR)
🏴 Flag for Sokoto (NG-SO)
🏴 Flag for Rivas (NI-RI)
🏴 Flag for Nueva Segovia (NI-NS)
🏴 Flag for Plateau (NG-PL)
🏴 Flag for Yobe (NG-YO)
🏴 Flag for Bonaire (NL-BQ1)
🏴 Flag for Atlántico Norte (NI-AN)
🏴 Flag for Zamfara (NG-ZA)
🏴 Flag for Gelderland (NL-GE)
🏴 Flag for Oyo (NG-OY)
🏴 Flag for Madriz (NI-MD)
🏴 Flag for Chinandega (NI-CI)
🏴 Flag for Ondo (NG-ON)
👨🏽👨🏽👦🏽👧🏽 Family - Man: Medium Skin Tone, Man: Medium Skin Tone, Boy: Medium Skin Tone, Girl: Medium Skin Tone
🏴 Flag for North Rhine-Westphalia (DE-NW)
🏴 Flag for Lagos (NG-LA)
🏴 Flag for Managua (NI-MN)
🏴 Flag for Atlántico Sur (NI-AS)
🏴 Flag for Curaçao (NL-CW)
🏴 Flag for Boaco (NI-BO)
🏴 Flag for Rivers (NG-RI)
🏴 Flag for Granada (NI-GR)
🏴 Flag for Chontales (NI-CO)
🏴 Flag for Groningen (NL-GR)
🏴 Flag for Sint Eustatius (NL-BQ3)
🏴 Flag for Río San Juan (NI-SJ)
🏴 Flag for Osun (NG-OS)
🏴 Flag for Taraba (NG-TA)
🏴 Flag for Flevoland (NL-FL)
🏴 Flag for Matagalpa (NI-MT)
🏴 Flag for Drenthe (NL-DR)
🏴 Flag for Carazo (NI-CA)
🏴 Flag for Kwara (NG-KW)
🏴 Flag for Niger (NG-NI)
🏴 Flag for Estelí (NI-ES)
🏴 Flag for South Holland (NL-ZH)
"""
for line in emojis.splitlines():
words = line.split()
char = words[0]
desc = " ".join(words[1:])
print("{}\t:{}".format(desc, char))
| [] |
HubTou/ngc | src/ngc/main.py | 9917adfbaff61e7b20b9f06a4be6b51237e4e768 | #!/usr/bin/env python
""" ngc - n-grams count
License: 3-clause BSD (see https://opensource.org/licenses/BSD-3-Clause)
Author: Hubert Tournier
"""
import getopt
import logging
import os
import re
import string
import sys
import unicode2ascii
# Version string used by the what(1) and ident(1) commands:
ID = "@(#) $Id: ngc - n-grams count v1.0.2 (September 26, 2021) by Hubert Tournier $"
# Default parameters. Can be superseded by command line options
parameters = {
"Convert": {
"Unicode to ASCII": False,
"Upper to lower case": False,
"Lower to upper case": False,
"Spaces to one space": False,
},
"Discard": {
"Unicode characters": False,
"Upper case letters": False,
"Lower case letters": False,
"Connection symbols": False, # ' -
"Digits": False,
"Punctuation": False, # . , ; : ! ?
"Other printable symbols": False,
"Spaces": False, # space tab return formfeed vtab
"Control characters": False,
},
"Length": 1,
"Fixed block": False, # Sliding-window mode by default
"Word boundary": False,
"Partial": {
"Discard": False,
"Keep": True,
"Justify": False,
},
"Show": {
"Text": False,
"N-grams": True,
"Summary": False,
},
}
occurrences = {}
summary = {
"Upper case letters": 0,
"Lower case letters": 0,
"Connection symbols": 0,
"Digits": 0,
"Punctuation": 0,
"Other printable symbols": 0,
"Spaces": 0,
"Other spaces": 0,
"Control characters": 0,
"Unicode letters": 0,
"Unicode marks": 0,
"Unicode numbers": 0,
"Unicode punctuations": 0,
"Unicode symbols": 0,
"Unicode separators": 0,
"Unicode others": 0,
"All unicode characters": 0,
"All characters": 0,
"All n-grams": 0
}
################################################################################
def initialize_debugging(program_name):
"""Debugging set up"""
console_log_format = program_name + ": %(levelname)s: %(message)s"
logging.basicConfig(format=console_log_format, level=logging.DEBUG)
logging.disable(logging.INFO)
################################################################################
def display_help():
"""Displays usage and help"""
print("usage: ngc [-b|--block] [-c|--convert ARGS] [--debug]", file=sys.stderr)
print(" [-d|--discard ARGS] [--help|-?] [-l|--length ARG]", file=sys.stderr)
print(" [-p|--partial ARG] [-q|--quiet] [-s|--summary] [-t|--text]", file=sys.stderr)
print(" [--version] [-w|--word] [--] [filename ...]", file=sys.stderr)
print(" ----------------- ----------------------------------------------------",
file=sys.stderr
)
print(" -b|--block Use fixed- instead of sliding-windows blocks", file=sys.stderr)
print(" -c|--convert ARGS Convert text input. A combination of:", file=sys.stderr)
print(" ARG = a - Unicode characters to ASCII (remove accents)", file=sys.stderr)
print(" ARG = l - Upper case letters to lower", file=sys.stderr)
print(" ARG = u - Lower case letters to upper", file=sys.stderr)
print(" ARG = s - Spaces-like characters to 1 space", file=sys.stderr)
print(" ARGS l and u can't be used at the same time", file=sys.stderr)
print(" -d|--discard ARGS Discard characters. A combination of:", file=sys.stderr)
print(" ARG = U - Unicode characters", file=sys.stderr)
print(" ARG = u - Upper case letters", file=sys.stderr)
print(" ARG = l - Lower case letters", file=sys.stderr)
print(" ARG = L - All letters", file=sys.stderr)
print(" ARG = c - Connection symbols ('-)", file=sys.stderr)
print(" ARG = d - Digits", file=sys.stderr)
print(" ARG = p - Punctuation (.,;:!?)", file=sys.stderr)
print(" ARG = o - Other printable symbols", file=sys.stderr)
print(" ARG = s - Spaces (space, tab, return, formfeed, vtab)", file=sys.stderr)
print(" ARG = n - Non printable Control characters", file=sys.stderr)
print(" -l|--length ARG Length of the n-gram. Defaults to 1", file=sys.stderr)
print(" -p|--partial ARG What to do with partial blocks? One among:", file=sys.stderr)
print(" ARG = d - Discard", file=sys.stderr)
print(" ARG = k - Keep as-is", file=sys.stderr)
print(" ARG = j - Keep but right-justify with spaces", file=sys.stderr)
print(" -q|--quiet Don't show occurrences and frequency by n-gram", file=sys.stderr)
print(" -s|--summary Show a summary of what was processed", file=sys.stderr)
print(" -t|--text Show modified text input", file=sys.stderr)
print(" -w|--word Respect Word boundaries (delimited by spaces)", file=sys.stderr)
print(" --debug Enable debug mode", file=sys.stderr)
print(" --help|-? Print usage and this help message and exit", file=sys.stderr)
print(" --version Print version and exit", file=sys.stderr)
print(" -- Options processing terminator", file=sys.stderr)
print(file=sys.stderr)
################################################################################
def process_environment_variables():
"""Process environment variables"""
if "NGC_DEBUG" in os.environ.keys():
logging.disable(logging.NOTSET)
################################################################################
def process_command_line():
"""Process command line"""
# pylint: disable=C0103
global parameters
# pylint: enable=C0103
# option letters followed by : expect an argument
# same for option strings followed by =
character_options = "bc:d:l:p:qstw?"
string_options = [
"block",
"convert=",
"debug",
"discard=",
"help",
"length=",
"partial=",
"quiet",
"summary",
"text",
"version",
"word",
]
try:
options, remaining_arguments = getopt.getopt(
sys.argv[1:], character_options, string_options
)
except getopt.GetoptError as error:
logging.critical(error)
display_help()
sys.exit(1)
for option, argument in options:
if option in ("-b", "--block"):
parameters["Fixed block"] = True
elif option in ("-c", "--convert"):
if 'l' in argument and 'u' in argument:
logging.critical("-c|--convert parameter can't contain [lu] at the same time")
sys.exit(1)
if 'a' in argument:
parameters["Convert"]["Unicode to ASCII"] = True
if 'l' in argument:
parameters["Convert"]["Upper to lower case"] = True
if 'u' in argument:
parameters["Convert"]["Lower to upper case"] = True
if 's' in argument:
parameters["Convert"]["Spaces to one space"] = True
elif option in ("-d", "--discard"):
if 'U' in argument:
parameters["Discard"]["Unicode characters"] = True
if 'u' in argument:
parameters["Discard"]["Upper case letters"] = True
if 'l' in argument:
parameters["Discard"]["Lower case letters"] = True
if 'L' in argument:
parameters["Discard"]["Upper case letters"] = True
parameters["Discard"]["Lower case letters"] = True
if 'c' in argument:
parameters["Discard"]["Connection symbols"] = True
if 'd' in argument:
parameters["Discard"]["Digits"] = True
if 'p' in argument:
parameters["Discard"]["Punctuation"] = True
if 'o' in argument:
parameters["Discard"]["Other printable symbols"] = True
if 's' in argument:
parameters["Discard"]["Spaces"] = True
if 'n' in argument:
parameters["Discard"]["Control characters"] = True
elif option in ("-l", "--length"):
if argument.isdigit() and int(argument) >= 0:
parameters["Length"] = int(argument)
else:
logging.critical("-l|--length parameter must be a strictly positive integer")
sys.exit(1)
elif option in ("-p", "--partial"):
if len(argument) > 1 or argument not in ('d', 'k', 'j'):
logging.critical("-p|--partial parameter must be a single character among [dkj]")
sys.exit(1)
if argument == 'd':
parameters["Partial"]["Discard"] = True
parameters["Partial"]["Keep"] = False
elif argument == 'j':
parameters["Partial"]["Justify"] = True
parameters["Partial"]["Keep"] = False
elif option in ("-q", "--quiet"):
parameters["Show"]["N-grams"] = False
elif option in ("-s", "--summary"):
parameters["Show"]["Summary"] = True
elif option in ("-t", "--text"):
parameters["Show"]["Text"] = True
elif option in ("-w", "--word"):
parameters["Word boundary"] = True
elif option == "--debug":
logging.disable(logging.NOTSET)
elif option in ("--help", "-?"):
display_help()
sys.exit(0)
elif option == "--version":
print(ID.replace("@(" + "#)" + " $" + "Id" + ": ", "").replace(" $", ""))
sys.exit(0)
logging.debug("process_command_line(): parameters:")
logging.debug(parameters)
logging.debug("process_command_line(): remaining_arguments:")
logging.debug(remaining_arguments)
return remaining_arguments
################################################################################
def handle_partial_n_gram(text):
"""Analyze n-grams frequency in a string"""
# pylint: disable=C0103
global occurrences, summary
# pylint: enable=C0103
if not parameters["Partial"]["Discard"]:
if parameters["Partial"]["Justify"]:
for _ in range(parameters["Length"] - len(text)):
text += " "
if text in occurrences:
occurrences[text] += 1
else:
occurrences[text] = 1
summary["All n-grams"] += 1
################################################################################
def frequency_analysis(text):
"""Analyze n-grams frequency in a string"""
# pylint: disable=C0103
global occurrences, summary
# pylint: enable=C0103
if parameters["Show"]["Summary"]:
for character in text:
if ord(character) < 128:
if character in string.ascii_uppercase:
summary["Upper case letters"] += 1
elif character in string.ascii_lowercase:
summary["Lower case letters"] += 1
elif character in ("'", "-"):
summary["Connection symbols"] += 1
elif character in string.digits:
summary["Digits"] += 1
elif character in (".", ",", ";", ":", "!", "?"):
summary["Punctuation"] += 1
elif character == " ":
summary["Spaces"] += 1
elif character in string.whitespace:
summary["Other spaces"] += 1
elif (ord(character) < 32 and ord(character) not in (9, 11, 12, 13)) \
or ord(character) == 127:
summary["Control characters"] += 1
else:
summary["Other printable symbols"] += 1
else:
summary["All unicode characters"] += 1
if unicode2ascii.is_unicode_letter(character):
summary["Unicode letters"] += 1
elif unicode2ascii.is_unicode_mark(character):
summary["Unicode marks"] += 1
elif unicode2ascii.is_unicode_number(character):
summary["Unicode numbers"] += 1
elif unicode2ascii.is_unicode_punctuation(character):
summary["Unicode punctuations"] += 1
elif unicode2ascii.is_unicode_symbol(character):
summary["Unicode symbols"] += 1
elif unicode2ascii.is_unicode_separator(character):
summary["Unicode separators"] += 1
else:
summary["Unicode others"] += 1
if len(text) <= parameters["Length"]:
if text:
handle_partial_n_gram(text)
else:
i = 0
while i < len(text) + 1 - parameters["Length"]:
sequence = text[i:i + parameters["Length"]]
if sequence in occurrences:
occurrences[sequence] += 1
else:
occurrences[sequence] = 1
summary["All n-grams"] += 1
if parameters["Fixed block"]:
i += parameters["Length"]
else:
i += 1
if i < len(text):
handle_partial_n_gram(text[i:])
################################################################################
def process_line(line):
"""Process a text line"""
# pylint: disable=C0103
global summary
# pylint: enable=C0103
line = line.rstrip(os.linesep)
# Conversions:
if parameters["Convert"]["Unicode to ASCII"]:
line = unicode2ascii.unicode_to_ascii_string(line)
if parameters["Convert"]["Upper to lower case"]:
line = line.lower()
if parameters["Convert"]["Lower to upper case"]:
line = line.upper()
# Discards:
if parameters["Discard"]["Unicode characters"]:
line = "".join([c for c in line if ord(c) < 128])
if parameters["Discard"]["Upper case letters"]:
line = re.sub(r"[A-Z]+", "", line)
if parameters["Discard"]["Lower case letters"]:
line = re.sub(r"[a-z]+", "", line)
if parameters["Discard"]["Connection symbols"]:
line = re.sub(r"[-']+", "", line)
if parameters["Discard"]["Digits"]:
line = re.sub(r"[0-9]+", "", line)
if parameters["Discard"]["Punctuation"]:
line = re.sub(r"[\.,;:!\?]+", "", line)
if parameters["Discard"]["Other printable symbols"]:
line = re.sub(r"[\"#$&@\[\\\]_`{|}~%()\*+/<=>^]+", "", line)
if parameters["Discard"]["Spaces"]:
line = re.sub(r"[" + string.whitespace + r"]+", "", line)
if parameters["Discard"]["Control characters"]:
line = "".join(
[c for c in line if not (ord(c) < 9 or (ord(c) > 13 and ord(c) < 32) or ord(c) == 127)]
)
# Late conversions:
if parameters["Convert"]["Spaces to one space"]:
line = re.sub(r"[" + string.whitespace + r"]+", " ", line)
if parameters["Show"]["Text"]:
print(line)
if parameters["Word boundary"]:
# Splitting words on all kind of whitespaces:
for word in line.split():
if word:
frequency_analysis(word)
summary["All characters"] += len(word)
else:
frequency_analysis(line)
summary["All characters"] += len(line)
################################################################################
def process_file(filename):
"""Process the file designated by filename, line by line"""
with open(filename, "r") as file:
for line in file.readlines():
process_line(line)
################################################################################
def compute_kappa_plaintext():
"""Return kappa_plaintext for the processed input stream"""
# pylint: disable=C0103
global occurrences, summary
# pylint: enable=C0103
# See https://en.wikipedia.org/wiki/Index_of_coincidence
index = 0.0
for occurrence in occurrences.values():
index += occurrence * (occurrence - 1)
return index / (summary["All n-grams"] * (summary["All n-grams"] - 1))
################################################################################
def compute_coincidence_index(kappa_plaintext):
"""Return coincidence index for a given kappa_plaintext and alphabet"""
# pylint: disable=C0103
global summary
# pylint: enable=C0103
if summary["Unicode separators"]:
# Unknown alphabet size
return 0
alphabet_size = 0
if summary["Upper case letters"]:
alphabet_size += len(string.ascii_uppercase)
if summary["Lower case letters"]:
alphabet_size += len(string.ascii_lowercase)
if summary["Digits"]:
alphabet_size += len(string.digits)
if summary["Connection symbols"]:
alphabet_size += len("'-")
if summary["Punctuation"]:
alphabet_size += len(".,;:?!")
if summary["Other printable symbols"]:
alphabet_size += len("\"#$&@[\\]_`{|}~%()*+/<=>^")
if summary["Spaces"]:
alphabet_size += 1
if summary["Other spaces"]:
alphabet_size += len(string.whitespace) - 1
if summary["Control characters"]:
alphabet_size += 29
return kappa_plaintext * alphabet_size
################################################################################
def main():
"""The program's main entry point"""
program_name = os.path.basename(sys.argv[0])
initialize_debugging(program_name)
process_environment_variables()
arguments = process_command_line()
exit_status = 0
# Reading from files whose name were given as arguments:
if len(arguments):
for filename in arguments:
if os.path.isfile(filename):
process_file(filename)
else:
logging.error("The argument '%s' is not a filename", filename)
exit_status = 1
# Reading from standard input as there are no arguments:
else:
for line in sys.stdin:
process_line(line)
# Displaying occurrences and frequency by n-gram:
if parameters["Show"]["N-grams"]:
if parameters["Show"]["Text"]:
print("--")
decreasing_occurrences = dict(sorted(occurrences.items(), key=lambda t: t[1], reverse=True))
for key, value in decreasing_occurrences.items():
print("'{}'\t{}\t{:.2f}%".format(key, value, (value/summary["All n-grams"])*100))
# Displaying summary:
if parameters["Show"]["Summary"]:
print("==")
for key, value in summary.items():
print("{:23s}\t{:d}".format(key, value))
print()
kappa_plaintext = compute_kappa_plaintext()
coincidence_index = compute_coincidence_index(kappa_plaintext)
print("{:23s}\t{}".format("Kappa-plaintext", kappa_plaintext))
print("{:23s}\t{}".format("Index of coincidence", coincidence_index))
sys.exit(exit_status)
if __name__ == "__main__":
main()
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rainzhop/ConvNetQuake | openquake.hazardlib/openquake/hazardlib/tests/gsim/campbell_2003_test.py | a3e6de3f7992eac72f1b9883fec36b8c7fdefd48 | # -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# Copyright (C) 2012-2016 GEM Foundation
#
# OpenQuake is free software: you can redistribute it and/or modify it
# under the terms of the GNU Affero General Public License as published
# by the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# OpenQuake is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>.
from openquake.hazardlib.gsim.campbell_2003 import (
Campbell2003,
Campbell2003SHARE,
Campbell2003MblgAB1987NSHMP2008,
Campbell2003MblgJ1996NSHMP2008,
Campbell2003MwNSHMP2008
)
from openquake.hazardlib.tests.gsim.utils import BaseGSIMTestCase
import numpy
# Test data generated from OpenSHA implementation.
class Campbell2003TestCase(BaseGSIMTestCase):
GSIM_CLASS = Campbell2003
def test_mean(self):
self.check('C03/C03_MEAN.csv',
max_discrep_percentage=0.1)
def test_std_total(self):
self.check('C03/C03_STD_TOTAL.csv',
max_discrep_percentage=0.1)
class Campbell2003SHARETestCase(BaseGSIMTestCase):
GSIM_CLASS = Campbell2003SHARE
def test_mean(self):
self.check('C03/C03SHARE_MEAN.csv',
max_discrep_percentage=0.1)
def test_std_total(self):
self.check('C03/C03SHARE_STD_TOTAL.csv',
max_discrep_percentage=0.1)
class Campbell2003MblgAB1987NSHMP2008TestCase(BaseGSIMTestCase):
GSIM_CLASS = Campbell2003MblgAB1987NSHMP2008
# test data generated from ``subroutine getCampCEUS`` in ``hazgridXnga2.f``
def test_mean(self):
self.check('C03/C03MblgAB1987NSHMP2008_MEAN.csv',
max_discrep_percentage=0.1)
def test_std_total(self):
self.check('C03/C03MblgAB1987NSHMP2008_STD_TOTAL.csv',
max_discrep_percentage=0.1)
class Campbell2003MblgJ1996NSHMP2008TestCase(BaseGSIMTestCase):
GSIM_CLASS = Campbell2003MblgJ1996NSHMP2008
# test data generated from ``subroutine getCampCEUS`` in ``hazgridXnga2.f``
def test_mean(self):
self.check('C03/C03MblgJ1996NSHMP2008_MEAN.csv',
max_discrep_percentage=0.1)
def test_std_total(self):
self.check('C03/C03MblgJ1996NSHMP2008_STD_TOTAL.csv',
max_discrep_percentage=0.1)
class Campbell2003MwNSHMP2008TestCase(BaseGSIMTestCase):
GSIM_CLASS = Campbell2003MwNSHMP2008
# test data generated from ``subroutine getCampCEUS`` in ``hazgridXnga2.f``
def test_mean(self):
self.check('C03/C03MwNSHMP2008_MEAN.csv',
max_discrep_percentage=0.1)
def test_std_total(self):
self.check('C03/C03MwNSHMP2008_STD_TOTAL.csv',
max_discrep_percentage=0.1)
| [] |
khrapovs/sktime | sktime/regression/interval_based/_tsf.py | 1589d007ef5dbcdc1f42f2c8278919ebed516358 | # -*- coding: utf-8 -*-
"""Time Series Forest Regressor (TSF)."""
__author__ = ["Tony Bagnall", "kkoziara", "luiszugasti", "kanand77", "Markus Löning"]
__all__ = ["TimeSeriesForestRegressor"]
import numpy as np
from joblib import Parallel, delayed
from sklearn.ensemble._forest import ForestRegressor
from sklearn.tree import DecisionTreeRegressor
from sktime.regression.base import BaseRegressor
from sktime.series_as_features.base.estimators.interval_based._tsf import (
BaseTimeSeriesForest,
_transform,
)
class TimeSeriesForestRegressor(BaseTimeSeriesForest, ForestRegressor, BaseRegressor):
"""Time series forest regressor.
A time series forest is an ensemble of decision trees built on random intervals.
Overview: For input data with n series of length m, for each tree:
- sample sqrt(m) intervals,
- find mean, std and slope for each interval, concatenate to form new data set,
- build decision tree on new data set.
Ensemble the trees with averaged probability estimates.
This implementation deviates from the original in minor ways. It samples
intervals with replacement and does not use the splitting criteria tiny
refinement described in [1]_. This is an intentionally stripped down, non
configurable version for use as a HIVE-COTE component.
Parameters
----------
n_estimators : int, default=200
Number of estimators.
min_interval : int, default=3
Minimum width of an interval.
n_jobs : int, default=1
The number of jobs to run in parallel for both `fit` and `predict`.
``-1`` means using all processors.
random_state : int, default=None
Attributes
----------
n_classes : int
Number of classes.
n_intervals : int
Number of intervals.
classes_ : list
List of classes for a given problem.
See Also
--------
TimeSeriesForestClassifier
References
----------
.. [1] H.Deng, G.Runger, E.Tuv and M.Vladimir, "A time series forest for
classification and feature extraction", Information Sciences, 239, 2013
.. [2] Java implementation https://github.com/uea-machine-learning/tsml
.. [3] Arxiv paper: https://arxiv.org/abs/1302.2277
"""
_tags = {
"capability:multivariate": False,
"X_inner_mtype": "numpy3D",
}
_base_estimator = DecisionTreeRegressor()
def fit(self, X, y):
"""Override sklearn forest fit with BaseRegressor fit."""
return BaseRegressor.fit(self, X, y)
def _fit(self, X, y):
"""Wrap BaseForest._fit.
This is a temporary measure prior to the BaseRegressor refactor.
"""
return BaseTimeSeriesForest._fit(self, X, y)
def predict(self, X):
"""Override sklearn forest predict with BaseRegressor predict."""
return BaseRegressor.predict(self, X)
def _predict(self, X):
"""Predict.
Parameters
----------
X : pd.DataFrame or np.ndarray
Panel data
Returns
-------
np.ndarray
Predictions.
"""
X = X.squeeze(1)
_, series_length = X.shape
if series_length != self.series_length:
raise TypeError(
"The number of time points in the training data does not match "
"that in the test data."
)
y_pred = Parallel(n_jobs=self.n_jobs)(
delayed(_predict)(X, self.estimators_[i], self.intervals_[i])
for i in range(self.n_estimators)
)
return np.mean(y_pred, axis=0)
def _predict(X, estimator, intervals):
Xt = _transform(X, intervals)
return estimator.predict(Xt)
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sebastiankruk/vectorc2 | vectorc2/vectorc2/settings.py | 13232cd63ebed32346fb4a669511b102b8ed24c0 | """
Django settings for vectorc2 project.
Copyright 2019 Sebastian Ryszard Kruk <vectorc2@kruk.me>
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '#9iml9@=i%x#i57qi1zm)&)p46hrf(g=pn7jioagsh*))6+z9('
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = [
"localhost",
"127.0.0.1",
"0.0.0.0"
]
# Application definition
INSTALLED_APPS = [
'space',
'command',
'bootstrap4',
'octicons',
'nonicons',
'blocks',
'photos',
'morse',
'webview.apps.WebviewConfig',
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'channels',
# 'compressor',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.locale.LocaleMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'vectorc2.urls'
STATICFILES_DIRS = [
os.path.join(BASE_DIR, "static")
]
MEDIA_ROOT = os.path.join(BASE_DIR, 'media')
MEDIA_URL = '/media/'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [
os.path.join(BASE_DIR, 'webview', 'templates')
],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.contrib.auth.context_processors.auth',
'django.template.context_processors.debug',
'django.template.context_processors.i18n',
'django.template.context_processors.media',
'django.template.context_processors.static',
'django.template.context_processors.request',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'vectorc2.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.1/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
# Password validation
# https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/2.1/topics/i18n/
LANGUAGE_CODE = 'en'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.1/howto/static-files/
STATIC_URL = '/static/'
# languages
from django.utils.translation import gettext_lazy as _
LANGUAGES = [
('pl', _('Polish')),
('en', _('English')),
]
# Default settings
BOOTSTRAP4 = {
# The complete URL to the Bootstrap CSS file
# Note that a URL can be either a string,
# e.g. "https://stackpath.bootstrapcdn.com/bootstrap/4.1.1/css/bootstrap.min.css",
# or a dict like the default value below.
"css_url": {
"href": "/static/style/bootstrap/bootstrap.min.css",
# "integrity": "sha384-WskhaSGFgHYWDcbwN70/dfYBj47jz9qbsMId/iRN3ewGhXQFZCSftd1LZCfmhktB",
"crossorigin": "anonymous",
},
# The complete URL to the Bootstrap JavaScript file
"javascript_url": {
"url": "/static/script/bootstrap/bootstrap.min.js",
# "integrity": "sha384-smHYKdLADwkXOn1EmN1qk/HfnUcbVRZyYmZ4qpPea6sjB/pTJ0euyQp0Mk8ck+5T",
"crossorigin": "anonymous",
},
# The complete URL to the Bootstrap CSS file (None means no theme)
"theme_url": None,
# The URL to the jQuery JavaScript file (full)
"jquery_url": {
"url": "/static/script/bootstrap/jquery-3.3.1.min.js",
# "integrity": "sha384-tsQFqpEReu7ZLhBV2VZlAu7zcOV+rXbYlF2cqB8txI/8aZajjp4Bqd+V6D5IgvKT",
"crossorigin": "anonymous",
},
# The URL to the jQuery JavaScript file (slim)
"jquery_slim_url": {
"url": "/static/script/bootstrap/jquery-3.3.1.slim.min.js",
# "integrity": "sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo",
"crossorigin": "anonymous",
},
# The URL to the Popper.js JavaScript file (slim)
"popper_url": {
"url": "/static/script/bootstrap/popper.min.js",
# "integrity": "sha384-ZMP7rVo3mIykV+2+9J3UJ46jBk0WLaUAdn689aCwoqbBJiSnjAK/l8WvCWPIPm49",
"crossorigin": "anonymous",
},
# Put JavaScript in the HEAD section of the HTML document (only relevant if you use bootstrap4.html)
'javascript_in_head': False,
# Include jQuery with Bootstrap JavaScript False|falsy|slim|full (default=False)
# False - means tag bootstrap_javascript use default value - `falsy` and does not include jQuery)
'include_jquery': False,
# Label class to use in horizontal forms
'horizontal_label_class': 'col-md-3',
# Field class to use in horizontal forms
'horizontal_field_class': 'col-md-9',
# Set placeholder attributes to label if no placeholder is provided
'set_placeholder': True,
# Class to indicate required (better to set this in your Django form)
'required_css_class': '',
# Class to indicate error (better to set this in your Django form)
'error_css_class': 'has-error',
# Class to indicate success, meaning the field has valid input (better to set this in your Django form)
'success_css_class': 'has-success',
# Renderers (only set these if you have studied the source and understand the inner workings)
'formset_renderers':{
'default': 'bootstrap4.renderers.FormsetRenderer',
},
'form_renderers': {
'default': 'bootstrap4.renderers.FormRenderer',
},
'field_renderers': {
'default': 'bootstrap4.renderers.FieldRenderer',
'inline': 'bootstrap4.renderers.InlineFieldRenderer',
},
}
ASGI_APPLICATION = "vectorc2.routing.application"
CHANNEL_LAYERS = {
'default': {
'BACKEND': 'channels_redis.core.RedisChannelLayer',
'CONFIG': {
"hosts": [('127.0.0.1', 6379)],
},
},
}
VECTOR = { }
# #TODO
# STATICFILES_FINDERS = [
# 'compressor.finders.CompressorFinder'
# ]
# COMPRESS_ENABLED = False
# COMPRESS_ROOT = os.path.join(BASE_DIR, 'static_collected') | [((2218, 2249), 'os.path.join', 'os.path.join', (['BASE_DIR', '"""media"""'], {}), "(BASE_DIR, 'media')\n", (2230, 2249), False, 'import os\n'), ((2169, 2201), 'os.path.join', 'os.path.join', (['BASE_DIR', '"""static"""'], {}), "(BASE_DIR, 'static')\n", (2181, 2201), False, 'import os\n'), ((772, 797), 'os.path.abspath', 'os.path.abspath', (['__file__'], {}), '(__file__)\n', (787, 797), False, 'import os\n'), ((3226, 3262), 'os.path.join', 'os.path.join', (['BASE_DIR', '"""db.sqlite3"""'], {}), "(BASE_DIR, 'db.sqlite3')\n", (3238, 3262), False, 'import os\n'), ((4186, 4197), 'django.utils.translation.gettext_lazy', '_', (['"""Polish"""'], {}), "('Polish')\n", (4187, 4197), True, 'from django.utils.translation import gettext_lazy as _\n'), ((4211, 4223), 'django.utils.translation.gettext_lazy', '_', (['"""English"""'], {}), "('English')\n", (4212, 4223), True, 'from django.utils.translation import gettext_lazy as _\n'), ((2393, 2439), 'os.path.join', 'os.path.join', (['BASE_DIR', '"""webview"""', '"""templates"""'], {}), "(BASE_DIR, 'webview', 'templates')\n", (2405, 2439), False, 'import os\n')] |
mikewoodson/ssl-transfer | datahandlers/wgisd.py | 524e2d57e9ffdbf0497cd4a1404eb1f85dc9fca7 | from torchvision.datasets.folder import pil_loader, accimage_loader, default_loader
from torch import Tensor
from pathlib import Path
from enum import Enum
from collections import namedtuple
from torchvision import transforms as T
import os
import numpy as np
import pdb
import functools
import torch.utils.data as data
import torch
class ConversionType(Enum):
centerToVert = 1
def convert_bbox_format(boxes: Tensor, conversionType: int) -> Tensor:
if conversionType > ConversionType.centerToVert.value:
raise ValueError(
f"conversionType must be less than" +
"{ConversionType.centerToVert.value}, received {conversionType}")
if conversionType == ConversionType.centerToVert.value:
# convert box annotations from (Cx,Cy,W,H) to (X0,Y0,X1,Y1)
box_centers = boxes[:, [0, 1, 0, 1]]
box_wh = 0.5 * boxes[:, [2, 3, 2, 3]]
box_wh[:, :2] *= -1
convertedBoxes = box_centers + box_wh
else:
raise ValueError
return convertedBoxes
class Wgisd(data.Dataset):
"""`FGVC-Aircraft <http://www.robots.ox.ac.uk/~vgg/data/fgvc-aircraft>`_ Dataset.
Args:
root (string): Root directory path to dataset.
transform (callable, optional): A function/transform that takes in a PIL image
and returns a transformed version. E.g. ``transforms.RandomCrop``
loader (callable, optional): A function to load an image given its path.
download (bool, optional): If true, downloads the dataset from the internet and
puts it in the root directory. If dataset is already downloaded, it is not
downloaded again.
"""
url = 'https://github.com/thsant/wgisd.git'
splits = ('train', 'test')
def __init__(self, root, split='train', transform=None,
loader=default_loader, download=False,
val_size=0.2):
if split not in self.splits:
raise ValueError(
'Split "{}" not found. Valid splits are: {}'.format(
split, ', '.join(
self.splits), ))
if val_size < 0 or val_size > 1:
raise ValueError('val_size should be a fraction between 0 and 1')
self.root = Path(root)
self.split = split
# There's no file specifying a validation dataset, so use a subset of the
# training dataset
dset_file = self.split
self.classes_file = self.root / f'{dset_file}.txt'
if download:
self.download()
self.transform = transform
self.loader = loader
self.id_to_fname = {}
self.val_size = val_size
self.total_set = None
self.samples = None
self.create_dataset()
self.mode = 'test' if self.split == 'test' else 'train'
@property
def mode(self):
return self._mode
@mode.setter
def mode(self, mode):
if self.split == 'test':
self._mode = 'test'
self.partition_dset()
return
supported_modes = ['train', 'val', 'trainval']
if mode not in supported_modes:
raise ValueError(f'mode must be one of {supported_modes}')
self._mode = mode
self.partition_dset()
def create_dataset(self):
image_names = []
samples = []
with open(self.classes_file, 'r') as f:
for line in f:
image_names.append(line.rstrip())
data_dir = self.root / 'data'
# Read bbox annotations from file
for idx, img_name in enumerate(image_names):
target = {}
gt_boxes = []
annotations = data_dir / f'{img_name}.txt'
img_path = data_dir / f'{img_name}.jpg'
with annotations.open() as f:
for line in f:
gt_boxes.append(line.split()[1:])
gt_np = np.array(gt_boxes, dtype=np.float32)
gt_tensor = torch.as_tensor(gt_np, dtype=torch.float32)
boxes = convert_bbox_format(gt_tensor, conversionType=1)
img = self.loader(img_path)
width, height = img.size
boxes[:, [0, 2]] = boxes[:, [0, 2]] * width
boxes[:, [1, 3]] = boxes[:, [1, 3]] * height
boxes = boxes.to(dtype=torch.int32)
numObjs = boxes.shape[0]
labels = torch.ones((numObjs,), dtype=torch.int64)
iscrowd = torch.zeros((numObjs,), dtype=torch.int64)
image_id = torch.tensor([idx])
self.id_to_fname[image_id.item()] = img_path.parts[-1]
area = (boxes[:, 3] - boxes[:, 1]) * (boxes[:, 2] - boxes[:, 0])
target['boxes'] = boxes
target['labels'] = labels
target['image_id'] = image_id
target['area'] = area
target['iscrowd'] = iscrowd
samples.append((img_path, target))
self.total_set = samples
def partition_dset(self):
num_images = len(self.total_set)
split = int(np.floor(self.val_size * num_images))
if self.mode == 'trainval':
self.samples = self.total_set
elif self.mode == 'train':
self.samples = self.total_set[split:]
elif self.mode == 'val':
self.samples = self.total_set[:split]
else:
self.samples = self.total_set
@functools.cached_property
def mean(self):
n_pixels = 0
pix_sum = torch.zeros([3])
for img_path, _ in self.total_set:
img = self.loader(img_path)
w,h = img.size
im_tensor = T.ToTensor()(img)
pix_sum += im_tensor.sum([1,2])
n_pixels += (w*h)
pix_avg = pix_sum / n_pixels
return pix_avg
@functools.cached_property
def stddev(self):
avg = self.mean
avg = avg.reshape([3, 1, 1])
var_sum = torch.zeros([3])
n_pixels = 0
for img_path, _ in self.total_set:
img = self.loader(img_path)
w,h = img.size
im_tensor = T.ToTensor()(img)
var_sum += ((im_tensor - avg)**2).sum([1,2])
n_pixels += (w*h)
var = var_sum / n_pixels
return torch.sqrt(var)
def get_fname(self, img_id):
return self.id_to_fname[img_id.item()]
def __getitem__(self, index):
"""
Args:
index (int): Index
Returns:
tuple: (sample, target) where target is class_index of the target class.
"""
path, target = self.samples[index]
sample = self.loader(path)
if self.transform is not None:
sample, target = self.transform(sample, target)
return sample, target
def __len__(self):
return len(self.samples)
def __repr__(self):
fmt_str = 'Dataset ' + self.__class__.__name__ + '\n'
fmt_str += ' Number of datapoints: {}\n'.format(self.__len__())
fmt_str += ' Root Location: {}\n'.format(self.root)
tmp = ' Transforms (if any): '
fmt_str += '{0}{1}\n'.format(tmp,
self.transform.__repr__().replace('\n',
'\n' + ' ' * len(tmp)))
return fmt_str
def _check_exists(self):
return self.root.exists() and self.classes_file.exists()
def download(self):
"""Download the wgisd data if it doesn't exist already."""
import requests
import tarfile
from git import Repo
if self._check_exists():
return
print('Downloading %s ... (may take a few minutes)' % self.url)
self.root.mkdir()
Repo.clone_from(self.url, str(self.root))
print('Done!')
| [((2248, 2258), 'pathlib.Path', 'Path', (['root'], {}), '(root)\n', (2252, 2258), False, 'from pathlib import Path\n'), ((5479, 5495), 'torch.zeros', 'torch.zeros', (['[3]'], {}), '([3])\n', (5490, 5495), False, 'import torch\n'), ((5915, 5931), 'torch.zeros', 'torch.zeros', (['[3]'], {}), '([3])\n', (5926, 5931), False, 'import torch\n'), ((6240, 6255), 'torch.sqrt', 'torch.sqrt', (['var'], {}), '(var)\n', (6250, 6255), False, 'import torch\n'), ((3906, 3942), 'numpy.array', 'np.array', (['gt_boxes'], {'dtype': 'np.float32'}), '(gt_boxes, dtype=np.float32)\n', (3914, 3942), True, 'import numpy as np\n'), ((3967, 4010), 'torch.as_tensor', 'torch.as_tensor', (['gt_np'], {'dtype': 'torch.float32'}), '(gt_np, dtype=torch.float32)\n', (3982, 4010), False, 'import torch\n'), ((4390, 4431), 'torch.ones', 'torch.ones', (['(numObjs,)'], {'dtype': 'torch.int64'}), '((numObjs,), dtype=torch.int64)\n', (4400, 4431), False, 'import torch\n'), ((4454, 4496), 'torch.zeros', 'torch.zeros', (['(numObjs,)'], {'dtype': 'torch.int64'}), '((numObjs,), dtype=torch.int64)\n', (4465, 4496), False, 'import torch\n'), ((4520, 4539), 'torch.tensor', 'torch.tensor', (['[idx]'], {}), '([idx])\n', (4532, 4539), False, 'import torch\n'), ((5048, 5084), 'numpy.floor', 'np.floor', (['(self.val_size * num_images)'], {}), '(self.val_size * num_images)\n', (5056, 5084), True, 'import numpy as np\n'), ((5630, 5642), 'torchvision.transforms.ToTensor', 'T.ToTensor', ([], {}), '()\n', (5640, 5642), True, 'from torchvision import transforms as T\n'), ((6087, 6099), 'torchvision.transforms.ToTensor', 'T.ToTensor', ([], {}), '()\n', (6097, 6099), True, 'from torchvision import transforms as T\n')] |
nikhilgk/SimpleCV | SimpleCV/MachineLearning/query_imgs/get_imgs_geo_gps_search.py | ee64451c16db1f40b4da221115273020a6a7b01a | #!/usr/bin/python
#
# So this script is in a bit of a hack state right now.
# This script reads
#
#
#
# Graciously copied and modified from:
# http://graphics.cs.cmu.edu/projects/im2gps/flickr_code.html
#Image querying script written by Tamara Berg,
#and extended heavily James Hays
#9/26/2007 added dynamic timeslices to query more efficiently.
#8/18/2008 added new fields and set maximum time slice.
#8/19/2008 this is a much simpler function which gets ALL geotagged photos of
# sufficient accuracy. No queries, no negative constraints.
# divides up the query results into multiple files
# 1/5/2009
# now uses date_taken instead of date_upload to get more diverse blocks of images
# 1/13/2009 - uses the original im2gps keywords, not as negative constraints though
import sys, string, math, time, socket
from flickrapi2 import FlickrAPI
from datetime import datetime
import pycurl
import os
import shutil
socket.setdefaulttimeout(30) #30 second time out on sockets before they throw
#an exception. I've been having trouble with urllib.urlopen hanging in the
#flickr API. This will show up as exceptions.IOError.
#the time out needs to be pretty long, it seems, because the flickr servers can be slow
#to respond to our big searches.
#returns a query and the search times to attempt to get a desired number of photos
#this needs serious refactoring -KAS
def DoSearch(fapi,query_string,desired_photos):
# number of seconds to skip per query
#timeskip = 62899200 #two years
#timeskip = 604800 #one week
timeskip = 172800 #two days
#timeskip = 86400 #one day
#timeskip = 3600 #one hour
#timeskip = 2257 #for resuming previous query
#mintime = 1121832000 #from im2gps
#mintime = 1167407788 # resume crash england
#mintime = 1177828976 #resume crash japan
#mintime = 1187753798 #resume crash greece
mintime = 1171416400 #resume crash WashingtonDC
maxtime = mintime+timeskip
endtime = 1192165200 #10/12/2007, at the end of im2gps queries
print datetime.fromtimestamp(mintime)
print datetime.fromtimestamp(endtime)
while (maxtime < endtime):
#new approach - adjust maxtime until we get the desired number of images
#within a block. We'll need to keep upper bounds and lower
#lower bound is well defined (mintime), but upper bound is not. We can't
#search all the way from endtime.
lower_bound = mintime + 900 #lower bound OF the upper time limit. must be at least 15 minutes or zero results
upper_bound = mintime + timeskip * 20 #upper bound of the upper time limit
maxtime = .95 * lower_bound + .05 * upper_bound
print '\nBinary search on time range upper bound'
print 'Lower bound is ' + str(datetime.fromtimestamp(lower_bound))
print 'Upper bound is ' + str(datetime.fromtimestamp(upper_bound))
keep_going = 6 #search stops after a fixed number of iterations
while( keep_going > 0 and maxtime < endtime):
try:
rsp = fapi.photos_search(api_key=flickrAPIKey,
ispublic="1",
media="photos",
per_page="250",
page="1",
has_geo = "0", #bbox="-180, -90, 180, 90",
text=query_string,
accuracy="6", #6 is region level.
min_upload_date=str(mintime),
max_upload_date=str(maxtime))
#we want to catch these failures somehow and keep going.
time.sleep(1)
fapi.testFailure(rsp)
total_images = rsp.photos[0]['total'];
null_test = int(total_images); #want to make sure this won't crash later on for some reason
null_test = float(total_images);
print '\nnumimgs: ' + total_images
print 'mintime: ' + str(mintime) + ' maxtime: ' + str(maxtime) + ' timeskip: ' + str(maxtime - mintime)
if( int(total_images) > desired_photos ):
print 'too many photos in block, reducing maxtime'
upper_bound = maxtime
maxtime = (lower_bound + maxtime) / 2 #midpoint between current value and lower bound.
if( int(total_images) < desired_photos):
print 'too few photos in block, increasing maxtime'
lower_bound = maxtime
maxtime = (upper_bound + maxtime) / 2
print 'Lower bound is ' + str(datetime.fromtimestamp(lower_bound))
print 'Upper bound is ' + str(datetime.fromtimestamp(upper_bound))
if( int(total_images) > 0): #only if we're not in a degenerate case
keep_going = keep_going - 1
else:
upper_bound = upper_bound + timeskip;
except KeyboardInterrupt:
print('Keyboard exception while querying for images, exiting\n')
raise
except:
print sys.exc_info()[0]
#print type(inst) # the exception instance
#print inst.args # arguments stored in .args
#print inst # __str__ allows args to printed directly
print ('Exception encountered while querying for images\n')
#end of while binary search
print 'finished binary search'
return([mintime,maxtime,total_images,rsp])
###########################################################################
# Modify this section to reflect your data and specific search
###########################################################################
# flickr auth information:
# change these to your flickr api keys and secret
flickrAPIKey = "fa33550d413b36b3fddc473a931a3b3b" # API key
flickrSecret = "7fd481bff0916055" # shared "secret"
rootpath = "../data/" #where do you want the data
desired_photos = 1000 #how many photos do you want to try and get
query_file_name = 'query.dat' #The file to get the queries from
#query_file_name = 'place_rec_queries_fall08.txt'
query_file = open(query_file_name, 'r')
#aggregate all of the positive and negative queries together.
pos_queries = [] #an empty list
neg_queries = '' #a string
num_queries = 0
for line in query_file:
if line[0] != '#' and len(line) > 1: #line end character is 2 long?
print line[0:len(line)-1]
if line[0] != '-':
pos_queries = pos_queries + [line[0:len(line)-1]]
num_queries = num_queries + 1
if line[0] == '-':
neg_queries = neg_queries + ' ' + line[0:len(line)-1]
query_file.close()
print 'positive queries: '
print pos_queries
print 'negative queries: ' + neg_queries
print 'num_queries = ' + str(num_queries)
#this is the desired number of photos in each block
# make a new FlickrAPI instance
fapi = FlickrAPI(flickrAPIKey, flickrSecret)
for current_tag in range(0, num_queries):
print('TOP OF LOOP')
# change this to the location where you want to put your output file
try:
stats = os.stat(rootpath)
except OSError:
os.mkdir(rootpath)
outpath = rootpath+pos_queries[current_tag]+'/'
try:
os.mkdir(outpath)
except OSError:
shutil.rmtree(outpath,True)
os.mkdir(outpath)
out_file = open(rootpath + pos_queries[current_tag] + '.txt','w')
###########################################################################
#form the query string.
query_string = pos_queries[current_tag] + ' ' + neg_queries
print '\n\nquery_string is ' + query_string
total_images_queried = 0;
[mintime,maxtime,total_images,rsp] = DoSearch(fapi,query_string,desired_photos)
print('GETTING TOTATL IMAGES:'+str(total_images))
s = '\nmintime: ' + str(mintime) + ' maxtime: ' + str(maxtime)
print s
out_file.write(s + '\n')
i = getattr(rsp,'photos',None)
if i:
s = 'numimgs: ' + total_images
print s
out_file.write(s + '\n')
current_image_num = 1;
num = 4 # CHANGE THIS BACK int(rsp.photos[0]['pages'])
s = 'total pages: ' + str(num)
print s
out_file.write(s + '\n')
#only visit 16 pages max, to try and avoid the dreaded duplicate bug
#16 pages = 4000 images, should be duplicate safe. Most interesting pictures will be taken.
num_visit_pages = min(16,num)
s = 'visiting only ' + str(num_visit_pages) + ' pages ( up to ' + str(num_visit_pages * 250) + ' images)'
print s
out_file.write(s + '\n')
total_images_queried = total_images_queried + min((num_visit_pages * 250), int(total_images))
#print 'stopping before page ' + str(int(math.ceil(num/3) + 1)) + '\n'
pagenum = 1;
counter = -1
while( pagenum <= num_visit_pages ):
#for pagenum in range(1, num_visit_pages + 1): #page one is searched twice
print ' page number ' + str(pagenum)
try:
print("PAGE")
print(pagenum)
# WARNING THIS QUERY HAS TO MATCH THE SEARCH QUERY!!!!
rsp = fapi.photos_search(api_key=flickrAPIKey,
ispublic="1",
media="photos",
per_page="250",
page=str(pagenum),
has_geo = "0",
text=query_string,
#extras = "tags, original_format, license, geo, date_taken, date_upload, o_dims, views",
#accuracy="6", #6 is region level.
min_upload_date=str(1121832000),#mintime),
max_upload_date=str(1192165200))#maxtime))
#rsp = fapi.photos_search(api_key=flickrAPIKey,
# ispublic="1",
# media="photos",
# per_page="250",
# page='0', #str(pagenum),
# sort="interestingness-desc",
# has_geo = "0", #bbox="-180, -90, 180, 90",
# text=query_string,
# #accuracy="6", #6 is region level. most things seem 10 or better.
# extras = "tags, original_format, license, geo, date_taken, date_upload, o_dims, views",
# min_upload_date=str(mintime),
# max_upload_date=str(maxtime))
##min_taken_date=str(datetime.fromtimestamp(mintime)),
##max_taken_date=str(datetime.fromtimestamp(maxtime)))
time.sleep(1)
fapi.testFailure(rsp)
except KeyboardInterrupt:
print('Keyboard exception while querying for images, exiting\n')
raise
except:
print sys.exc_info()[0]
#print type(inst) # the exception instance
#print inst.args # arguments stored in .args
#print inst # __str__ allows args to printed directly
print ('Exception encountered while querying for images\n')
else:
print('got a response')
# and print them
k = getattr(rsp,'photos',None)
if k:
print('In K')
m = getattr(rsp.photos[0],'photo',None)
if m:
print('In M')
for b in rsp.photos[0].photo:
print('In b')
if b!=None:
counter = counter + 1
##print(http://farm{farm-id}.static.flickr.com/{server-id}/{id}_{secret}.jpg)
myurl = 'http://farm'+b['farm']+".static.flickr.com/"+b['server']+"/"+b['id']+"_"+b['secret']+'.jpg'
fname = outpath+pos_queries[current_tag]+str(counter)+'.jpg' #b['id']+"_"+b['secret']+'.jpg'
print(myurl)
print(fname)
mycurl = pycurl.Curl()
mycurl.setopt(pycurl.URL, str(myurl))
myfile = open(fname,"wb")
mycurl.setopt(pycurl.WRITEDATA, myfile)
mycurl.setopt(pycurl.FOLLOWLOCATION, 1)
mycurl.setopt(pycurl.MAXREDIRS, 5)
mycurl.setopt(pycurl.NOSIGNAL, 1)
mycurl.perform()
mycurl.close()
myfile.close()
out_file.write('URL: '+myurl+'\n')
out_file.write('File: '+ fname+'\n')
out_file.write('photo: ' + b['id'] + ' ' + b['secret'] + ' ' + b['server'] + '\n')
out_file.write('owner: ' + b['owner'] + '\n')
out_file.write('title: ' + b['title'].encode("ascii","replace") + '\n')
out_file.write('originalsecret: ' + b['originalsecret'] + '\n')
out_file.write('originalformat: ' + b['originalformat'] + '\n')
out_file.write('o_height: ' + b['o_height'] + '\n')
out_file.write('o_width: ' + b['o_width'] + '\n')
out_file.write('datetaken: ' + b['datetaken'].encode("ascii","replace") + '\n')
out_file.write('dateupload: ' + b['dateupload'].encode("ascii","replace") + '\n')
out_file.write('tags: ' + b['tags'].encode("ascii","replace") + '\n')
out_file.write('license: ' + b['license'].encode("ascii","replace") + '\n')
out_file.write('latitude: ' + b['latitude'].encode("ascii","replace") + '\n')
out_file.write('longitude: ' + b['longitude'].encode("ascii","replace") + '\n')
out_file.write('accuracy: ' + b['accuracy'].encode("ascii","replace") + '\n')
out_file.write('views: ' + b['views'] + '\n')
out_file.write('interestingness: ' + str(current_image_num) + ' out of ' + str(total_images) + '\n');
out_file.write('\n')
current_image_num = current_image_num + 1;
print('')
pagenum = pagenum + 1; #this is in the else exception block. Itwon't increment for a failure.
#this block is indented such that it will only run if there are no exceptions
#in the original query. That means if there are exceptions, mintime won't be incremented
#and it will try again
timeskip = maxtime - mintime #used for initializing next binary search
mintime = maxtime
out_file.write('Total images queried: ' + str(total_images_queried) + '\n')
out_file.close
| [] |
quguiliang/Machine-Learning-with-Spark-Second-Edition | Chapter04/python/2.0.0/com/sparksamples/util.py | 0ba131e6c15a3de97609c6cb5d976806ccc14f09 | import os
import sys
from pyspark.sql.types import *
PATH = "/home/ubuntu/work/ml-resources/spark-ml/data"
SPARK_HOME = "/home/ubuntu/work/spark-2.0.0-bin-hadoop2.7/"
os.environ['SPARK_HOME'] = SPARK_HOME
sys.path.append(SPARK_HOME + "/python")
from pyspark import SparkContext
from pyspark import SparkConf
from pyspark.sql import SparkSession
conf = SparkConf().setAppName("First Spark App").setMaster("local")
sc = SparkContext(conf=conf)
spark = SparkSession(sc)
def get_user_data():
custom_schema = StructType([
StructField("no", StringType(), True),
StructField("age", IntegerType(), True),
StructField("gender", StringType(), True),
StructField("occupation", StringType(), True),
StructField("zipCode", StringType(), True)
])
from pyspark.sql import SQLContext
from pyspark.sql.types import *
sql_context = SQLContext(sc)
user_df = sql_context.read \
.format('com.databricks.spark.csv') \
.options(header='false', delimiter='|') \
.load("%s/ml-100k/u.user" % PATH, schema = custom_schema)
return user_df
def get_movie_data_df():
custom_schema = StructType([
StructField("no", StringType(), True),
StructField("moviename", StringType(), True),
StructField("date", StringType(), True),
StructField("f1", StringType(), True), StructField("url", StringType(), True),
StructField("f2", IntegerType(), True), StructField("f3", IntegerType(), True),
StructField("f4", IntegerType(), True), StructField("f5", IntegerType(), True),
StructField("f6", IntegerType(), True), StructField("f7", IntegerType(), True),
StructField("f8", IntegerType(), True), StructField("f9", IntegerType(), True),
StructField("f10", IntegerType(), True), StructField("f11", IntegerType(), True),
StructField("f12", IntegerType(), True), StructField("f13", IntegerType(), True),
StructField("f14", IntegerType(), True), StructField("f15", IntegerType(), True),
StructField("f16", IntegerType(), True), StructField("f17", IntegerType(), True),
StructField("f18", IntegerType(), True), StructField("f19", IntegerType(), True)
])
from pyspark.sql import SQLContext
from pyspark.sql.types import *
sql_context = SQLContext(sc)
movie_df = sql_context.read \
.format('com.databricks.spark.csv') \
.options(header='false', delimiter='|') \
.load("%s/ml-100k/u.item" % PATH, schema = custom_schema)
return movie_df
def get_movie_data():
return sc.textFile("%s/ml-100k/u.item" % PATH)
def get_rating_data():
return sc.textFile("%s/ml-100k/u.data" % PATH)
| [((206, 245), 'sys.path.append', 'sys.path.append', (["(SPARK_HOME + '/python')"], {}), "(SPARK_HOME + '/python')\n", (221, 245), False, 'import sys\n'), ((421, 444), 'pyspark.SparkContext', 'SparkContext', ([], {'conf': 'conf'}), '(conf=conf)\n', (433, 444), False, 'from pyspark import SparkContext\n'), ((453, 469), 'pyspark.sql.SparkSession', 'SparkSession', (['sc'], {}), '(sc)\n', (465, 469), False, 'from pyspark.sql import SparkSession\n'), ((880, 894), 'pyspark.sql.SQLContext', 'SQLContext', (['sc'], {}), '(sc)\n', (890, 894), False, 'from pyspark.sql import SQLContext\n'), ((2309, 2323), 'pyspark.sql.SQLContext', 'SQLContext', (['sc'], {}), '(sc)\n', (2319, 2323), False, 'from pyspark.sql import SQLContext\n'), ((355, 366), 'pyspark.SparkConf', 'SparkConf', ([], {}), '()\n', (364, 366), False, 'from pyspark import SparkConf\n')] |
Safemasks/safemasks-app | safemasks/resources/rest/router.py | 44c1cf16f81b15b74fa5eb38d36eaa078180e975 | """
"""
from rest_framework import routers
from safemasks.resources.rest.serializers import SupplierViewSet, TrustedSupplierViewSet
# Routers provide an easy way of automatically determining the URL conf.
ROUTER = routers.DefaultRouter()
ROUTER.register(r"suppliers", SupplierViewSet, "suppliers")
ROUTER.register(r"suppliers-trusted", TrustedSupplierViewSet, "suppliers-trusted")
| [((217, 240), 'rest_framework.routers.DefaultRouter', 'routers.DefaultRouter', ([], {}), '()\n', (238, 240), False, 'from rest_framework import routers\n')] |
jamesjer/zope.testrunner | src/zope/testrunner/formatter.py | af8bfec49d90613633b76e914a6f54884463ba94 | ##############################################################################
#
# Copyright (c) 2004-2008 Zope Foundation and Contributors.
# All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE.
#
##############################################################################
"""Output formatting.
"""
from __future__ import print_function
try:
from collections.abc import MutableMapping
except ImportError:
from collections import MutableMapping
from contextlib import contextmanager
import doctest
import os
import re
import sys
import tempfile
import traceback
from datetime import datetime, timedelta
from zope.testrunner.exceptions import DocTestFailureException
try:
unicode
except NameError:
unicode = str
doctest_template = """
File "%s", line %s, in %s
%s
Want:
%s
Got:
%s
"""
class OutputFormatter(object):
"""Test runner output formatter."""
# Implementation note: be careful about printing stuff to sys.stderr.
# It is used for interprocess communication between the parent and the
# child test runner, when you run some test layers in a subprocess.
# resume_layer() reasigns sys.stderr for this reason, but be careful
# and don't store the original one in __init__ or something.
max_width = 80
def __init__(self, options):
self.options = options
self.last_width = 0
self.compute_max_width()
progress = property(lambda self: self.options.progress)
verbose = property(lambda self: self.options.verbose)
in_subprocess = property(
lambda self: (
self.options.resume_layer is not None and
self.options.processes > 1))
def compute_max_width(self):
"""Try to determine the terminal width."""
# Note that doing this every time is more test friendly.
self.max_width = tigetnum('cols', self.max_width)
def getShortDescription(self, test, room):
"""Return a description of a test that fits in ``room`` characters."""
room -= 1
s = str(test)
if len(s) > room:
pos = s.find(" (")
if pos >= 0:
w = room - (pos + 5)
if w < 1:
# first portion (test method name) is too long
s = s[:room-3] + "..."
else:
pre = s[:pos+2]
post = s[-w:]
s = "%s...%s" % (pre, post)
else:
w = room - 4
s = '... ' + s[-w:]
return ' ' + s[:room]
def info(self, message):
"""Print an informative message."""
print(message)
def info_suboptimal(self, message):
"""Print an informative message about losing some of the features.
For example, when you run some tests in a subprocess, you lose the
ability to use the debugger.
"""
print(message)
def error(self, message):
"""Report an error."""
print(message)
def error_with_banner(self, message):
"""Report an error with a big ASCII banner."""
print()
print('*'*70)
self.error(message)
print('*'*70)
print()
def profiler_stats(self, stats):
"""Report profiler stats."""
stats.print_stats(50)
def import_errors(self, import_errors):
"""Report test-module import errors (if any)."""
if import_errors:
print("Test-module import failures:")
for error in import_errors:
self.print_traceback("Module: %s\n" % error.module,
error.exc_info),
print()
def tests_with_errors(self, errors):
"""Report names of tests with errors (if any)."""
if errors:
print()
print("Tests with errors:")
for test, exc_info in errors:
print(" ", test)
def tests_with_failures(self, failures):
"""Report names of tests with failures (if any)."""
if failures:
print()
print("Tests with failures:")
for test, exc_info in failures:
print(" ", test)
def modules_with_import_problems(self, import_errors):
"""Report names of modules with import problems (if any)."""
if import_errors:
print()
print("Test-modules with import problems:")
for test in import_errors:
print(" " + test.module)
def format_seconds(self, n_seconds):
"""Format a time in seconds."""
if n_seconds >= 60:
n_minutes, n_seconds = divmod(n_seconds, 60)
return "%d minutes %.3f seconds" % (n_minutes, n_seconds)
else:
return "%.3f seconds" % n_seconds
def format_seconds_short(self, n_seconds):
"""Format a time in seconds (short version)."""
return "%.3f s" % n_seconds
def summary(self, n_tests, n_failures, n_errors, n_seconds,
n_skipped=0):
"""Summarize the results of a single test layer."""
print(" Ran %s tests with %s failures, %s errors and "
"%s skipped in %s."
% (n_tests, n_failures, n_errors, n_skipped,
self.format_seconds(n_seconds)))
def totals(self, n_tests, n_failures, n_errors, n_seconds,
n_skipped=0):
"""Summarize the results of all layers."""
print("Total: %s tests, %s failures, %s errors and %s skipped in %s."
% (n_tests, n_failures, n_errors, n_skipped,
self.format_seconds(n_seconds)))
def list_of_tests(self, tests, layer_name):
"""Report a list of test names."""
print("Listing %s tests:" % layer_name)
for test in tests:
print(' ', test)
def garbage(self, garbage):
"""Report garbage generated by tests."""
if garbage:
print("Tests generated new (%d) garbage:" % len(garbage))
print(garbage)
def test_garbage(self, test, garbage):
"""Report garbage generated by a test."""
if garbage:
print("The following test left garbage:")
print(test)
print(garbage)
def test_threads(self, test, new_threads):
"""Report threads left behind by a test."""
if new_threads:
print("The following test left new threads behind:")
print(test)
print("New thread(s):", new_threads)
def refcounts(self, rc, prev):
"""Report a change in reference counts."""
print(" sys refcount=%-8d change=%-6d" % (rc, rc - prev))
def detailed_refcounts(self, track, rc, prev):
"""Report a change in reference counts, with extra detail."""
print((" sum detail refcount=%-8d"
" sys refcount=%-8d"
" change=%-6d"
% (track.n, rc, rc - prev)))
track.output()
def start_set_up(self, layer_name):
"""Report that we're setting up a layer.
The next output operation should be stop_set_up().
"""
print(" Set up %s" % layer_name, end=' ')
sys.stdout.flush()
def stop_set_up(self, seconds):
"""Report that we've set up a layer.
Should be called right after start_set_up().
"""
print("in %s." % self.format_seconds(seconds))
def start_tear_down(self, layer_name):
"""Report that we're tearing down a layer.
The next output operation should be stop_tear_down() or
tear_down_not_supported().
"""
print(" Tear down %s" % layer_name, end=' ')
sys.stdout.flush()
def stop_tear_down(self, seconds):
"""Report that we've tore down a layer.
Should be called right after start_tear_down().
"""
print("in %s." % self.format_seconds(seconds))
def tear_down_not_supported(self):
"""Report that we could not tear down a layer.
Should be called right after start_tear_down().
"""
print("... not supported")
def start_test(self, test, tests_run, total_tests):
"""Report that we're about to run a test.
The next output operation should be test_success(), test_error(), or
test_failure().
"""
self.test_width = 0
if self.progress:
if self.last_width:
sys.stdout.write('\r' + (' ' * self.last_width) + '\r')
s = " %d/%d (%.1f%%)" % (tests_run, total_tests,
tests_run * 100.0 / total_tests)
sys.stdout.write(s)
self.test_width += len(s)
if self.verbose == 1:
room = self.max_width - self.test_width - 1
s = self.getShortDescription(test, room)
sys.stdout.write(s)
self.test_width += len(s)
elif self.verbose == 1:
sys.stdout.write('.' * test.countTestCases())
elif self.in_subprocess:
sys.stdout.write('.' * test.countTestCases())
# Give the parent process a new line so it sees the progress
# in a timely manner.
sys.stdout.write('\n')
if self.verbose > 1:
s = str(test)
sys.stdout.write(' ')
sys.stdout.write(s)
self.test_width += len(s) + 1
sys.stdout.flush()
def test_success(self, test, seconds):
"""Report that a test was successful.
Should be called right after start_test().
The next output operation should be stop_test().
"""
if self.verbose > 2:
s = " (%s)" % self.format_seconds_short(seconds)
sys.stdout.write(s)
self.test_width += len(s) + 1
def test_skipped(self, test, reason):
"""Report that a test was skipped.
Should be called right after start_test().
The next output operation should be stop_test().
"""
if self.verbose > 2:
s = " (skipped: %s)" % reason
elif self.verbose > 1:
s = " (skipped)"
else:
return
sys.stdout.write(s)
self.test_width += len(s) + 1
def test_error(self, test, seconds, exc_info, stdout=None, stderr=None):
"""Report that an error occurred while running a test.
Should be called right after start_test().
The next output operation should be stop_test().
"""
if self.verbose > 2:
print(" (%s)" % self.format_seconds_short(seconds))
print()
self.print_traceback("Error in test %s" % test, exc_info)
self.print_std_streams(stdout, stderr)
self.test_width = self.last_width = 0
def test_failure(self, test, seconds, exc_info, stdout=None, stderr=None):
"""Report that a test failed.
Should be called right after start_test().
The next output operation should be stop_test().
"""
if self.verbose > 2:
print(" (%s)" % self.format_seconds_short(seconds))
print()
self.print_traceback("Failure in test %s" % test, exc_info)
self.print_std_streams(stdout, stderr)
self.test_width = self.last_width = 0
def print_traceback(self, msg, exc_info):
"""Report an error with a traceback."""
print()
print(msg)
print(self.format_traceback(exc_info))
def print_std_streams(self, stdout, stderr):
"""Emit contents of buffered standard streams."""
if stdout:
sys.stdout.write("Stdout:\n")
sys.stdout.write(stdout)
if not stdout.endswith("\n"):
sys.stdout.write("\n")
sys.stdout.write("\n")
if stderr:
sys.stderr.write("Stderr:\n")
sys.stderr.write(stderr)
if not stderr.endswith("\n"):
sys.stderr.write("\n")
sys.stderr.write("\n")
def format_traceback(self, exc_info):
"""Format the traceback."""
v = exc_info[1]
if isinstance(v, DocTestFailureException):
tb = v.args[0]
elif isinstance(v, doctest.DocTestFailure):
tb = doctest_template % (
v.test.filename,
v.test.lineno + v.example.lineno + 1,
v.test.name,
v.example.source,
v.example.want,
v.got,
)
else:
tb = "".join(traceback.format_exception(*exc_info))
return tb
def stop_test(self, test):
"""Clean up the output state after a test."""
if self.progress:
self.last_width = self.test_width
elif self.verbose > 1:
print()
sys.stdout.flush()
def stop_tests(self):
"""Clean up the output state after a collection of tests."""
if self.progress and self.last_width:
sys.stdout.write('\r' + (' ' * self.last_width) + '\r')
if self.verbose == 1 or self.progress:
print()
def tigetnum(attr, default=None):
"""Return a value from the terminfo database.
Terminfo is used on Unix-like systems to report various terminal attributes
(such as width, height or the number of supported colors).
Returns ``default`` when the ``curses`` module is not available, or when
sys.stdout is not a terminal.
"""
try:
import curses
except ImportError:
# avoid reimporting a broken module in python 2.3
sys.modules['curses'] = None
else:
# If sys.stdout is not a real file object (e.g. in unit tests that
# use various wrappers), you get an error, different depending on
# Python version:
expected_exceptions = (curses.error, TypeError, AttributeError)
if sys.version_info >= (3,):
import io
expected_exceptions += (io.UnsupportedOperation, )
try:
curses.setupterm()
except expected_exceptions:
# You get curses.error when $TERM is set to an unknown name
pass
else:
try:
return curses.tigetnum(attr)
except expected_exceptions:
# You get TypeError on PyPy3 due to a bug:
# https://bitbucket.org/pypy/pypy/issue/2016/pypy3-cursestigetnum-raises-ctype
pass
return default
def terminal_has_colors():
"""Determine whether the terminal supports colors.
Some terminals (e.g. the emacs built-in one) don't.
"""
return tigetnum('colors', -1) >= 8
class ColorfulOutputFormatter(OutputFormatter):
"""Output formatter that uses ANSI color codes.
Like syntax highlighting in your text editor, colorizing
test failures helps the developer.
"""
# These colors are carefully chosen to have enough contrast
# on terminals with both black and white background.
colorscheme = {'normal': 'normal',
'default': 'default',
'info': 'normal',
'suboptimal-behaviour': 'magenta',
'error': 'brightred',
'number': 'green',
'slow-test': 'brightmagenta',
'ok-number': 'green',
'error-number': 'brightred',
'filename': 'lightblue',
'lineno': 'lightred',
'testname': 'lightcyan',
'failed-example': 'cyan',
'expected-output': 'green',
'actual-output': 'red',
'character-diffs': 'magenta',
'diff-chunk': 'magenta',
'exception': 'red',
'skipped': 'brightyellow',
}
# Map prefix character to color in diff output. This handles ndiff and
# udiff correctly, but not cdiff. In cdiff we ought to highlight '!' as
# expected-output until we see a '-', then highlight '!' as actual-output,
# until we see a '*', then switch back to highlighting '!' as
# expected-output. Nevertheless, coloried cdiffs are reasonably readable,
# so I'm not going to fix this.
# -- mgedmin
diff_color = {'-': 'expected-output',
'+': 'actual-output',
'?': 'character-diffs',
'@': 'diff-chunk',
'*': 'diff-chunk',
'!': 'actual-output',
}
prefixes = [('dark', '0;'),
('light', '1;'),
('bright', '1;'),
('bold', '1;'),
]
colorcodes = {'default': 0, 'normal': 0,
'black': 30,
'red': 31,
'green': 32,
'brown': 33, 'yellow': 33,
'blue': 34,
'magenta': 35,
'cyan': 36,
'grey': 37, 'gray': 37, 'white': 37}
slow_test_threshold = 10.0 # seconds
def color_code(self, color):
"""Convert a color description (e.g. 'lightred') to a terminal code."""
prefix_code = ''
for prefix, code in self.prefixes:
if color.startswith(prefix):
color = color[len(prefix):]
prefix_code = code
break
color_code = self.colorcodes[color]
return '\033[%s%sm' % (prefix_code, color_code)
def color(self, what):
"""Pick a named color from the color scheme"""
return self.color_code(self.colorscheme[what])
def colorize(self, what, message, normal='normal'):
"""Wrap message in color."""
return self.color(what) + message + self.color(normal)
def error_count_color(self, n):
"""Choose a color for the number of errors."""
if n:
return self.color('error-number')
else:
return self.color('ok-number')
def skip_count_color(self, n):
"""Choose a color for the number of skipped tests."""
if n:
return self.color('skipped')
else:
return self.color('ok-number')
def test_skipped(self, test, reason):
"""Report that a test was skipped.
Should be called right after start_test().
The next output operation should be stop_test().
"""
if self.verbose > 2:
s = " (%sskipped: %s%s)" % (
self.color('skipped'), reason, self.color('info'))
elif self.verbose > 1:
s = " (%sskipped%s)" % (
self.color('skipped'), self.color('info'))
else:
return
sys.stdout.write(s)
self.test_width += len(s) + 1
def info(self, message):
"""Print an informative message."""
print(self.colorize('info', message))
def info_suboptimal(self, message):
"""Print an informative message about losing some of the features.
For example, when you run some tests in a subprocess, you lose the
ability to use the debugger.
"""
print(self.colorize('suboptimal-behaviour', message))
def error(self, message):
"""Report an error."""
print(self.colorize('error', message))
def error_with_banner(self, message):
"""Report an error with a big ASCII banner."""
print()
print(self.colorize('error', '*'*70))
self.error(message)
print(self.colorize('error', '*'*70))
print()
def tear_down_not_supported(self):
"""Report that we could not tear down a layer.
Should be called right after start_tear_down().
"""
print("...", self.colorize('suboptimal-behaviour', "not supported"))
def format_seconds(self, n_seconds, normal='normal'):
"""Format a time in seconds."""
if n_seconds >= 60:
n_minutes, n_seconds = divmod(n_seconds, 60)
return "%s minutes %s seconds" % (
self.colorize('number', '%d' % n_minutes, normal),
self.colorize('number', '%.3f' % n_seconds, normal))
else:
return "%s seconds" % (
self.colorize('number', '%.3f' % n_seconds, normal))
def format_seconds_short(self, n_seconds):
"""Format a time in seconds (short version)."""
if n_seconds >= self.slow_test_threshold:
color = 'slow-test'
else:
color = 'number'
return self.colorize(color, "%.3f s" % n_seconds)
def summary(self, n_tests, n_failures, n_errors, n_seconds,
n_skipped=0):
"""Summarize the results."""
sys.stdout.writelines([
self.color('info'), ' Ran ',
self.color('number'), str(n_tests),
self.color('info'), ' tests with ',
self.error_count_color(n_failures), str(n_failures),
self.color('info'), ' failures, ',
self.error_count_color(n_errors), str(n_errors),
self.color('info'), ' errors, ',
self.skip_count_color(n_skipped), str(n_skipped),
self.color('info'), ' skipped in ',
self.format_seconds(n_seconds, 'info'), '.',
self.color('normal'), '\n',
])
def totals(self, n_tests, n_failures, n_errors, n_seconds,
n_skipped=0):
"""Report totals (number of tests, failures, and errors)."""
sys.stdout.writelines([
self.color('info'), 'Total: ',
self.color('number'), str(n_tests),
self.color('info'), ' tests, ',
self.error_count_color(n_failures), str(n_failures),
self.color('info'), ' failures, ',
self.error_count_color(n_errors), str(n_errors),
self.color('info'), ' errors, ',
self.skip_count_color(n_skipped), str(n_skipped),
self.color('info'), ' skipped in ',
self.format_seconds(n_seconds, 'info'), '.',
self.color('normal'), '\n'])
def print_traceback(self, msg, exc_info):
"""Report an error with a traceback."""
print()
print(self.colorize('error', msg))
v = exc_info[1]
if isinstance(v, DocTestFailureException):
self.print_doctest_failure(v.args[0])
elif isinstance(v, doctest.DocTestFailure):
# I don't think these are ever used... -- mgedmin
tb = self.format_traceback(exc_info)
print(tb)
else:
tb = self.format_traceback(exc_info)
self.print_colorized_traceback(tb)
def print_doctest_failure(self, formatted_failure):
"""Report a doctest failure.
``formatted_failure`` is a string -- that's what
DocTestSuite/DocFileSuite gives us.
"""
color_of_indented_text = 'normal'
colorize_diff = False
for line in formatted_failure.splitlines():
if line.startswith('File '):
m = re.match(r'File "(.*)", line (\d*), in (.*)$', line)
if m:
filename, lineno, test = m.groups()
sys.stdout.writelines([
self.color('normal'), 'File "',
self.color('filename'), filename,
self.color('normal'), '", line ',
self.color('lineno'), lineno,
self.color('normal'), ', in ',
self.color('testname'), test,
self.color('normal'), '\n'])
else:
print(line)
elif line.startswith(' ') or line.strip() == '':
if colorize_diff and len(line) > 4:
color = self.diff_color.get(
line[4], color_of_indented_text)
print(self.colorize(color, line))
else:
if line.strip() != '':
print(self.colorize(color_of_indented_text, line))
else:
print(line)
else:
colorize_diff = False
if line.startswith('Failed example'):
color_of_indented_text = 'failed-example'
elif line.startswith('Expected:'):
color_of_indented_text = 'expected-output'
elif line.startswith('Got:'):
color_of_indented_text = 'actual-output'
elif line.startswith('Exception raised:'):
color_of_indented_text = 'exception'
elif line.startswith('Differences '):
color_of_indented_text = 'normal'
colorize_diff = True
else:
color_of_indented_text = 'normal'
print(line)
print()
def print_colorized_traceback(self, formatted_traceback):
"""Report a test failure.
``formatted_traceback`` is a string.
"""
for line in formatted_traceback.splitlines():
if line.startswith(' File'):
m = re.match(r' File "(.*)", line (\d*), in (.*)$', line)
if m:
filename, lineno, test = m.groups()
sys.stdout.writelines([
self.color('normal'), ' File "',
self.color('filename'), filename,
self.color('normal'), '", line ',
self.color('lineno'), lineno,
self.color('normal'), ', in ',
self.color('testname'), test,
self.color('normal'), '\n'])
else:
print(line)
elif line.startswith(' '):
print(self.colorize('failed-example', line))
elif line.startswith('Traceback (most recent call last)'):
print(line)
else:
print(self.colorize('exception', line))
print()
class FakeTest(object):
"""A fake test object that only has an id."""
failureException = None
def __init__(self, test_id):
self._id = test_id
def id(self):
return self._id
# Conditional imports: we don't want zope.testrunner to have a hard
# dependency on subunit.
try:
import subunit
from subunit.iso8601 import Utc
subunit.StreamResultToBytes
except (ImportError, AttributeError):
subunit = None
# testtools is a hard dependency of subunit itself, but we guard it
# separately for richer error messages.
try:
import testtools
from testtools.content import (
Content,
ContentType,
content_from_file,
text_content,
)
testtools.StreamToExtendedDecorator
except (ImportError, AttributeError):
testtools = None
class _RunnableDecorator(object):
"""Permit controlling the runnable annotation on tests.
This decorates a StreamResult, adding a setRunnable context manager to
indicate whether a test is runnable. (A context manager is unidiomatic
here, but it's just about the simplest way to stuff the relevant state
through the various layers of decorators involved without accidentally
affecting later test results.)
"""
def __init__(self, decorated):
self.decorated = decorated
self._runnable = True
def __getattr__(self, name):
return getattr(self.decorated, name)
@contextmanager
def setRunnable(self, runnable):
orig_runnable = self._runnable
try:
self._runnable = runnable
yield
finally:
self._runnable = orig_runnable
def status(self, **kwargs):
kwargs = dict(kwargs)
kwargs['runnable'] = self._runnable
self.decorated.status(**kwargs)
class _SortedDict(MutableMapping, object):
"""A dict that always returns items in sorted order.
This differs from collections.OrderedDict in that it returns items in
*sorted* order, not in insertion order.
We use this as a workaround for the fact that
testtools.ExtendedToStreamDecorator doesn't sort the details dict when
encoding it, which makes it difficult to write stable doctests for
subunit v2 output.
"""
def __init__(self, items):
self._dict = dict(items)
def __getitem__(self, key):
return self._dict[key]
def __setitem__(self, key, value):
self._dict[key] = value
def __delitem__(self, key):
del self._dict[key]
def __iter__(self):
return iter(sorted(self._dict))
def __len__(self):
return len(self._dict)
class SubunitOutputFormatter(object):
"""A subunit output formatter.
This output formatter generates subunit-compatible output (see
https://launchpad.net/subunit). Subunit output is essentially a stream
of results of unit tests.
In this formatter, non-test events (such as layer set up) are encoded as
specially-tagged tests. In particular, for a layer 'foo', the fake
tests related to layer setup and teardown are tagged with 'zope:layer'
and are called 'foo:setUp' and 'foo:tearDown'. Any tests within layer
'foo' are tagged with 'zope:layer:foo'.
Note that all tags specific to this formatter begin with 'zope:'.
"""
# subunit output is designed for computers, so displaying a progress bar
# isn't helpful.
progress = False
verbose = property(lambda self: self.options.verbose)
TAG_INFO_SUBOPTIMAL = 'zope:info_suboptimal'
TAG_ERROR_WITH_BANNER = 'zope:error_with_banner'
TAG_LAYER = 'zope:layer'
TAG_IMPORT_ERROR = 'zope:import_error'
TAG_PROFILER_STATS = 'zope:profiler_stats'
TAG_GARBAGE = 'zope:garbage'
TAG_THREADS = 'zope:threads'
TAG_REFCOUNTS = 'zope:refcounts'
def __init__(self, options, stream=None):
if subunit is None:
raise Exception('Requires subunit 0.0.11 or better')
if testtools is None:
raise Exception('Requires testtools 0.9.30 or better')
self.options = options
if stream is None:
stream = sys.stdout
self._stream = stream
self._subunit = self._subunit_factory(self._stream)
# Used to track the last layer that was set up or torn down. Either
# None or (layer_name, last_touched_time).
self._last_layer = None
self.UTC = Utc()
# Content types used in the output.
self.TRACEBACK_CONTENT_TYPE = ContentType(
'text', 'x-traceback', {'language': 'python', 'charset': 'utf8'})
self.PROFILE_CONTENT_TYPE = ContentType(
'application', 'x-binary-profile')
self.PLAIN_TEXT = ContentType('text', 'plain', {'charset': 'utf8'})
@classmethod
def _subunit_factory(cls, stream):
"""Return a TestResult attached to the given stream."""
return _RunnableDecorator(subunit.TestProtocolClient(stream))
def _emit_timestamp(self, now=None):
"""Emit a timestamp to the subunit stream.
If 'now' is not specified, use the current time on the system clock.
"""
if now is None:
now = datetime.now(self.UTC)
self._subunit.time(now)
return now
def _emit_fake_test(self, message, tag, details=None):
"""Emit a successful fake test to the subunit stream.
Use this to print tagged informative messages.
"""
test = FakeTest(message)
with self._subunit.setRunnable(False):
self._subunit.startTest(test)
self._subunit.tags([tag], [])
self._subunit.addSuccess(test, details=details)
self._subunit.stopTest(test)
def _emit_error(self, error_id, tag, exc_info, runnable=False):
"""Emit an error to the subunit stream.
Use this to pass on information about errors that occur outside of
tests.
"""
test = FakeTest(error_id)
with self._subunit.setRunnable(runnable):
self._subunit.startTest(test)
self._subunit.tags([tag], [])
self._subunit.addError(test, exc_info)
self._subunit.stopTest(test)
def _emit_failure(self, failure_id, tag, exc_info):
"""Emit an failure to the subunit stream.
Use this to pass on information about failures that occur outside of
tests.
"""
test = FakeTest(failure_id)
self._subunit.addFailure(test, exc_info)
def _enter_layer(self, layer_name):
"""Tell subunit that we are entering a layer."""
self._subunit.tags(['zope:layer:%s' % (layer_name,)], [])
def _exit_layer(self, layer_name):
"""Tell subunit that we are exiting a layer."""
self._subunit.tags([], ['zope:layer:%s' % (layer_name,)])
def info(self, message):
"""Print an informative message."""
# info() output is not relevant to actual test results. It only
# says things like "Running tests" or "Tearing down left over
# layers", things that are communicated already by the subunit
# stream. Just suppress the info() output.
pass
def info_suboptimal(self, message):
"""Print an informative message about losing some of the features.
For example, when you run some tests in a subprocess, you lose the
ability to use the debugger.
"""
# Used _only_ to indicate running in a subprocess.
self._emit_fake_test(message.strip(), self.TAG_INFO_SUBOPTIMAL)
def error(self, message):
"""Report an error."""
# XXX: Mostly used for user errors, sometimes used for errors in the
# test framework, sometimes used to record layer setUp failure (!!!).
self._stream.write('%s\n' % (message,))
def error_with_banner(self, message):
"""Report an error with a big ASCII banner."""
# Either "Could not communicate with subprocess"
# Or "Can't post-mortem debug when running a layer as a subprocess!"
self._emit_fake_test(message, self.TAG_ERROR_WITH_BANNER)
def profiler_stats(self, stats):
"""Report profiler stats."""
fd, filename = tempfile.mkstemp(prefix='zope.testrunner-')
os.close(fd)
try:
stats.dump_stats(filename)
profile_content = content_from_file(
filename, content_type=self.PROFILE_CONTENT_TYPE)
details = {'profiler-stats': profile_content}
# Name the test 'zope:profiler_stats' just like its tag.
self._emit_fake_test(
self.TAG_PROFILER_STATS, self.TAG_PROFILER_STATS, details)
finally:
os.unlink(filename)
def import_errors(self, import_errors):
"""Report test-module import errors (if any)."""
if import_errors:
for error in import_errors:
self._emit_error(
error.module, self.TAG_IMPORT_ERROR, error.exc_info,
runnable=True)
def tests_with_errors(self, errors):
"""Report names of tests with errors (if any).
Simply not supported by the subunit formatter. Fancy summary output
doesn't make sense.
"""
pass
def tests_with_failures(self, failures):
"""Report names of tests with failures (if any).
Simply not supported by the subunit formatter. Fancy summary output
doesn't make sense.
"""
pass
def modules_with_import_problems(self, import_errors):
"""Report names of modules with import problems (if any)."""
# This is simply a summary method, and subunit output doesn't
# benefit from summaries.
pass
def summary(self, n_tests, n_failures, n_errors, n_seconds,
n_skipped=0):
"""Summarize the results of a single test layer.
Since subunit is a stream protocol format, it has no need for a
summary. When the stream is finished other tools can generate a
summary if so desired.
"""
pass
def totals(self, n_tests, n_failures, n_errors, n_seconds, n_skipped=0):
"""Summarize the results of all layers.
Simply not supported by the subunit formatter. Fancy summary output
doesn't make sense.
"""
pass
def _emit_exists(self, test):
"""Emit an indication that a test exists.
With the v1 protocol, we just emit a fake success line.
"""
self._subunit.addSuccess(test)
def list_of_tests(self, tests, layer_name):
"""Report a list of test names."""
self._enter_layer(layer_name)
for test in tests:
self._subunit.startTest(test)
self._emit_exists(test)
self._subunit.stopTest(test)
self._exit_layer(layer_name)
def garbage(self, garbage):
"""Report garbage generated by tests."""
# XXX: Really, 'garbage', 'profiler_stats' and the 'refcounts' twins
# ought to add extra details to a fake test that represents the
# summary information for the whole suite. However, there's no event
# on output formatters for "everything is really finished, honest". --
# jml, 2010-02-14
details = {'garbage': text_content(unicode(garbage))}
self._emit_fake_test(self.TAG_GARBAGE, self.TAG_GARBAGE, details)
def test_garbage(self, test, garbage):
"""Report garbage generated by a test.
Encoded in the subunit stream as a test error. Clients can filter
out these tests based on the tag if they don't think garbage should
fail the test run.
"""
# XXX: Perhaps 'test_garbage' and 'test_threads' ought to be within
# the output for the actual test, appended as details to whatever
# result the test gets. Not an option with the present API, as there's
# no event for "no more output for this test". -- jml, 2010-02-14
self._subunit.startTest(test)
self._subunit.tags([self.TAG_GARBAGE], [])
self._subunit.addError(
test, details={'garbage': text_content(unicode(garbage))})
self._subunit.stopTest(test)
def test_threads(self, test, new_threads):
"""Report threads left behind by a test.
Encoded in the subunit stream as a test error. Clients can filter
out these tests based on the tag if they don't think left-over
threads should fail the test run.
"""
self._subunit.startTest(test)
self._subunit.tags([self.TAG_THREADS], [])
self._subunit.addError(
test, details={'threads': text_content(unicode(new_threads))})
self._subunit.stopTest(test)
def refcounts(self, rc, prev):
"""Report a change in reference counts."""
details = _SortedDict({
'sys-refcounts': text_content(str(rc)),
'changes': text_content(str(rc - prev)),
})
# XXX: Emit the details dict as JSON?
self._emit_fake_test(self.TAG_REFCOUNTS, self.TAG_REFCOUNTS, details)
def detailed_refcounts(self, track, rc, prev):
"""Report a change in reference counts, with extra detail."""
details = _SortedDict({
'sys-refcounts': text_content(str(rc)),
'changes': text_content(str(rc - prev)),
'track': text_content(str(track.delta)),
})
self._emit_fake_test(self.TAG_REFCOUNTS, self.TAG_REFCOUNTS, details)
def start_set_up(self, layer_name):
"""Report that we're setting up a layer.
We do this by emitting a fake test of the form '$LAYER_NAME:setUp'
and adding a tag of the form 'zope:layer:$LAYER_NAME' to the current
tag context.
The next output operation should be stop_set_up().
"""
test = FakeTest('%s:setUp' % (layer_name,))
now = self._emit_timestamp()
with self._subunit.setRunnable(False):
self._subunit.startTest(test)
self._subunit.tags([self.TAG_LAYER], [])
self._last_layer = (layer_name, now)
def stop_set_up(self, seconds):
"""Report that we've set up a layer.
Should be called right after start_set_up().
"""
layer_name, start_time = self._last_layer
self._last_layer = None
test = FakeTest('%s:setUp' % (layer_name,))
self._emit_timestamp(start_time + timedelta(seconds=seconds))
with self._subunit.setRunnable(False):
self._subunit.addSuccess(test)
self._subunit.stopTest(test)
self._enter_layer(layer_name)
def layer_failure(self, failure_type, exc_info):
layer_name, start_time = self._last_layer
self._emit_failure(
'%s:%s' % (layer_name, failure_type), self.TAG_LAYER, exc_info)
def start_tear_down(self, layer_name):
"""Report that we're tearing down a layer.
We do this by emitting a fake test of the form
'$LAYER_NAME:tearDown' and removing a tag of the form
'layer:$LAYER_NAME' from the current tag context.
The next output operation should be stop_tear_down() or
tear_down_not_supported().
"""
test = FakeTest('%s:tearDown' % (layer_name,))
self._exit_layer(layer_name)
now = self._emit_timestamp()
with self._subunit.setRunnable(False):
self._subunit.startTest(test)
self._subunit.tags([self.TAG_LAYER], [])
self._last_layer = (layer_name, now)
def stop_tear_down(self, seconds):
"""Report that we've torn down a layer.
Should be called right after start_tear_down().
"""
layer_name, start_time = self._last_layer
self._last_layer = None
test = FakeTest('%s:tearDown' % (layer_name,))
self._emit_timestamp(start_time + timedelta(seconds=seconds))
with self._subunit.setRunnable(False):
self._subunit.addSuccess(test)
self._subunit.stopTest(test)
def tear_down_not_supported(self):
"""Report that we could not tear down a layer.
Should be called right after start_tear_down().
"""
layer_name, start_time = self._last_layer
self._last_layer = None
test = FakeTest('%s:tearDown' % (layer_name,))
self._emit_timestamp()
with self._subunit.setRunnable(False):
self._subunit.addSkip(test, 'tearDown not supported')
self._subunit.stopTest(test)
def start_test(self, test, tests_run, total_tests):
"""Report that we're about to run a test.
The next output operation should be test_success(), test_error(), or
test_failure().
"""
self._emit_timestamp()
self._subunit.startTest(test)
def test_success(self, test, seconds):
"""Report that a test was successful.
Should be called right after start_test().
The next output operation should be stop_test().
"""
self._emit_timestamp()
self._subunit.addSuccess(test)
def test_skipped(self, test, reason):
"""Report that a test was skipped.
Should be called right after start_test().
The next output operation should be stop_test().
"""
self._subunit.addSkip(test, reason)
def _exc_info_to_details(self, exc_info):
"""Translate 'exc_info' into a details dict usable with subunit."""
# In an ideal world, we'd use the pre-bundled 'TracebackContent'
# class from testtools. However, 'OutputFormatter' contains special
# logic to handle errors from doctests, so we have to use that and
# manually create an object equivalent to an instance of
# 'TracebackContent'.
formatter = OutputFormatter(None)
traceback = formatter.format_traceback(exc_info)
# We have no idea if the traceback is a unicode object or a
# bytestring with non-ASCII characters. We had best be careful when
# handling it.
if isinstance(traceback, bytes):
# Assume the traceback was UTF-8-encoded, but still be careful.
unicode_tb = traceback.decode('utf-8', 'replace')
else:
unicode_tb = traceback
return _SortedDict({
'traceback': Content(
self.TRACEBACK_CONTENT_TYPE,
lambda: [unicode_tb.encode('utf8')]),
})
def _add_std_streams_to_details(self, details, stdout, stderr):
"""Add buffered standard stream contents to a subunit details dict."""
if stdout:
if isinstance(stdout, bytes):
stdout = stdout.decode('utf-8', 'replace')
details['test-stdout'] = Content(
self.PLAIN_TEXT, lambda: [stdout.encode('utf-8')])
if stderr:
if isinstance(stderr, bytes):
stderr = stderr.decode('utf-8', 'replace')
details['test-stderr'] = Content(
self.PLAIN_TEXT, lambda: [stderr.encode('utf-8')])
def test_error(self, test, seconds, exc_info, stdout=None, stderr=None):
"""Report that an error occurred while running a test.
Should be called right after start_test().
The next output operation should be stop_test().
"""
self._emit_timestamp()
details = self._exc_info_to_details(exc_info)
self._add_std_streams_to_details(details, stdout, stderr)
self._subunit.addError(test, details=details)
def test_failure(self, test, seconds, exc_info, stdout=None, stderr=None):
"""Report that a test failed.
Should be called right after start_test().
The next output operation should be stop_test().
"""
self._emit_timestamp()
details = self._exc_info_to_details(exc_info)
self._add_std_streams_to_details(details, stdout, stderr)
self._subunit.addFailure(test, details=details)
def stop_test(self, test):
"""Clean up the output state after a test."""
self._subunit.stopTest(test)
def stop_tests(self):
"""Clean up the output state after a collection of tests."""
# subunit handles all of this itself.
pass
class SubunitV2OutputFormatter(SubunitOutputFormatter):
"""A subunit v2 output formatter."""
@classmethod
def _subunit_factory(cls, stream):
"""Return a TestResult attached to the given stream."""
stream_result = _RunnableDecorator(subunit.StreamResultToBytes(stream))
result = testtools.ExtendedToStreamDecorator(stream_result)
# Lift our decorating method up so that we can get at it easily.
result.setRunnable = stream_result.setRunnable
result.startTestRun()
return result
def error(self, message):
"""Report an error."""
# XXX: Mostly used for user errors, sometimes used for errors in the
# test framework, sometimes used to record layer setUp failure (!!!).
self._subunit.status(
file_name='error', file_bytes=unicode(message).encode('utf-8'),
eof=True, mime_type=repr(self.PLAIN_TEXT))
def _emit_exists(self, test):
"""Emit an indication that a test exists."""
now = datetime.now(self.UTC)
self._subunit.status(
test_id=test.id(), test_status='exists',
test_tags=self._subunit.current_tags, timestamp=now)
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'sys.stdout.write', 'sys.stdout.write', (['stdout'], {}), '(stdout)\n', (12016, 12024), False, 'import sys\n'), ((12118, 12140), 'sys.stdout.write', 'sys.stdout.write', (['"""\n"""'], {}), "('\\n')\n", (12134, 12140), False, 'import sys\n'), ((12172, 12201), 'sys.stderr.write', 'sys.stderr.write', (['"""Stderr:\n"""'], {}), "('Stderr:\\n')\n", (12188, 12201), False, 'import sys\n'), ((12214, 12238), 'sys.stderr.write', 'sys.stderr.write', (['stderr'], {}), '(stderr)\n', (12230, 12238), False, 'import sys\n'), ((12332, 12354), 'sys.stderr.write', 'sys.stderr.write', (['"""\n"""'], {}), "('\\n')\n", (12348, 12354), False, 'import sys\n'), ((13335, 13388), 'sys.stdout.write', 'sys.stdout.write', (["('\\r' + ' ' * self.last_width + '\\r')"], {}), "('\\r' + ' ' * self.last_width + '\\r')\n", (13351, 13388), False, 'import sys\n'), ((14362, 14380), 'curses.setupterm', 'curses.setupterm', ([], {}), '()\n', (14378, 14380), False, 'import curses\n'), ((31372, 31406), 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'(stream)\n', (47016, 47024), False, 'import subunit\n'), ((8777, 8830), 'sys.stdout.write', 'sys.stdout.write', (["('\\r' + ' ' * self.last_width + '\\r')"], {}), "('\\r' + ' ' * self.last_width + '\\r')\n", (8793, 8830), False, 'import sys\n'), ((9208, 9227), 'sys.stdout.write', 'sys.stdout.write', (['s'], {}), '(s)\n', (9224, 9227), False, 'import sys\n'), ((12083, 12105), 'sys.stdout.write', 'sys.stdout.write', (['"""\n"""'], {}), "('\\n')\n", (12099, 12105), False, 'import sys\n'), ((12297, 12319), 'sys.stderr.write', 'sys.stderr.write', (['"""\n"""'], {}), "('\\n')\n", (12313, 12319), False, 'import sys\n'), ((14560, 14581), 'curses.tigetnum', 'curses.tigetnum', (['attr'], {}), '(attr)\n', (14575, 14581), False, 'import curses\n'), ((23395, 23447), 're.match', 're.match', (['"""File "(.*)", line (\\\\d*), in (.*)$"""', 'line'], {}), '(\'File "(.*)", line (\\\\d*), in (.*)$\', line)\n', (23403, 23447), False, 'import re\n'), ((25539, 25593), 're.match', 're.match', (['""" File "(.*)", line (\\\\d*), in (.*)$"""', 'line'], {}), '(\' File "(.*)", line (\\\\d*), in (.*)$\', line)\n', (25547, 25593), False, 'import re\n'), ((40897, 40923), 'datetime.timedelta', 'timedelta', ([], {'seconds': 'seconds'}), '(seconds=seconds)\n', (40906, 40923), False, 'from datetime import datetime, timedelta\n'), ((42337, 42363), 'datetime.timedelta', 'timedelta', ([], {'seconds': 'seconds'}), '(seconds=seconds)\n', (42346, 42363), False, 'from datetime import datetime, timedelta\n'), ((9572, 9594), 'sys.stdout.write', 'sys.stdout.write', (['"""\n"""'], {}), "('\\n')\n", (9588, 9594), False, 'import sys\n'), ((12888, 12925), 'traceback.format_exception', 'traceback.format_exception', (['*exc_info'], {}), '(*exc_info)\n', (12914, 12925), False, 'import traceback\n')] |
csisarep/groundwater_dashboard | waterApp/migrations/0011_auto_20210911_1043.py | 4f93d7b7c9fd6b48ace54e7b62cae717decc98d2 | # Generated by Django 2.2 on 2021-09-11 04:58
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('waterApp', '0010_auto_20210911_1041'),
]
operations = [
migrations.AlterField(
model_name='gwmonitoring',
name='id',
field=models.BigAutoField(primary_key=True, serialize=False),
),
]
| [((337, 391), 'django.db.models.BigAutoField', 'models.BigAutoField', ([], {'primary_key': '(True)', 'serialize': '(False)'}), '(primary_key=True, serialize=False)\n', (356, 391), False, 'from django.db import migrations, models\n')] |
shubhamtalbar96/geomstats | geomstats/geometry/stratified/__init__.py | 9c17ccede7e3f0fddf31487c59227c677216a2b9 | """The Stratified Space Geometry Package."""
| [] |
xmdy/h9eNi8F5Ut | src/exporter/management/commands/test_export.py | 4128d7cbc6105ec0fe69157bd88ef8e30415d6ca | from django.core.management import BaseCommand
import logging
# These two lines enable debugging at httplib level (requests->urllib3->http.client)
# You will see the REQUEST, including HEADERS and DATA, and RESPONSE with HEADERS but without DATA.
# The only thing missing will be the response.body which is not logged.
try:
import http.client as http_client
except ImportError:
# Python 2
import httplib as http_client
http_client.HTTPConnection.debuglevel = 1
# You must initialize logging, otherwise you'll not see debug output.
logging.basicConfig()
logging.getLogger().setLevel(logging.DEBUG)
requests_log = logging.getLogger("requests.packages.urllib3")
requests_log.setLevel(logging.DEBUG)
requests_log.propagate = True
class Command(BaseCommand):
def handle(self, *args, **options):
from exporter.tasks import GenerateModelExportTask
gmet = GenerateModelExportTask()
gmet.run(1) | [((545, 566), 'logging.basicConfig', 'logging.basicConfig', ([], {}), '()\n', (564, 566), False, 'import logging\n'), ((626, 672), 'logging.getLogger', 'logging.getLogger', (['"""requests.packages.urllib3"""'], {}), "('requests.packages.urllib3')\n", (643, 672), False, 'import logging\n'), ((567, 586), 'logging.getLogger', 'logging.getLogger', ([], {}), '()\n', (584, 586), False, 'import logging\n'), ((883, 908), 'exporter.tasks.GenerateModelExportTask', 'GenerateModelExportTask', ([], {}), '()\n', (906, 908), False, 'from exporter.tasks import GenerateModelExportTask\n')] |
ianthomas23/dask | dask/tests/test_highgraph.py | 7968e85e2edab95565ebbab1f936c9c549e29126 | from functools import partial
import os
import pytest
import dask
import dask.array as da
from dask.utils_test import inc
from dask.highlevelgraph import HighLevelGraph, BasicLayer, Layer
from dask.blockwise import Blockwise
from dask.array.utils import assert_eq
def test_visualize(tmpdir):
pytest.importorskip("graphviz")
fn = str(tmpdir)
a = da.ones(10, chunks=(5,))
b = a + 1
c = a + 2
d = b + c
d.dask.visualize(fn)
assert os.path.exists(fn)
def test_basic():
a = {"x": 1}
b = {"y": (inc, "x")}
layers = {"a": a, "b": b}
dependencies = {"a": set(), "b": {"a"}}
hg = HighLevelGraph(layers, dependencies)
assert dict(hg) == {"x": 1, "y": (inc, "x")}
assert all(isinstance(layer, Layer) for layer in hg.layers.values())
def test_keys_values_items_methods():
a = da.ones(10, chunks=(5,))
b = a + 1
c = a + 2
d = b + c
hg = d.dask
keys, values, items = hg.keys(), hg.values(), hg.items()
assert all(isinstance(i, list) for i in [keys, values, items])
assert keys == [i for i in hg]
assert values == [hg[i] for i in hg]
assert items == [(k, v) for k, v in zip(keys, values)]
def test_cull():
a = {"x": 1, "y": (inc, "x")}
layers = {
"a": BasicLayer(
a, dependencies={"x": set(), "y": {"x"}}, global_dependencies=set()
)
}
dependencies = {"a": set()}
hg = HighLevelGraph(layers, dependencies)
culled_by_x = hg.cull({"x"})
assert dict(culled_by_x) == {"x": 1}
culled_by_y = hg.cull({"y"})
assert dict(culled_by_y) == a
@pytest.mark.parametrize("inject_dict", [True, False])
def test_map_basic_layers(inject_dict):
"""Check map_basic_layers() by injecting an inc() call"""
y = da.ones(3, chunks=(3,), dtype="int") + 40
def inject_inc(dsk):
assert isinstance(dsk, BasicLayer)
dsk = dict(dsk)
k = next(iter(dsk))
dsk[k] = (inc, dsk[k])
if inject_dict:
return dsk # map_basic_layers() should automatically convert it to a `BasicLayer`
else:
return BasicLayer(dsk)
dsk = y.__dask_graph__()
y.dask = dsk.map_basic_layers(inject_inc)
layers = list(y.dask.layers.values())
assert isinstance(layers[0], BasicLayer)
assert isinstance(layers[1], Blockwise)
assert_eq(y, [42] * 3)
@pytest.mark.parametrize("use_layer_map_task", [True, False])
def test_map_tasks(use_layer_map_task):
"""Check map_tasks() by injecting an +1 to the `40` literal"""
y = da.ones(3, chunks=(3,), dtype="int") + 40
def plus_one(tasks):
ret = []
for t in tasks:
if t == 40:
t += 1
ret.append(t)
return tuple(ret)
dsk = y.__dask_graph__()
if use_layer_map_task:
# In order to test the default map_tasks() implementation on a Blockwise Layer,
# we overwrite Blockwise.map_tasks with Layer.map_tasks
blockwise_layer = list(dsk.layers.values())[1]
blockwise_layer.map_tasks = partial(Layer.map_tasks, blockwise_layer)
y.dask = dsk.map_tasks(plus_one)
assert_eq(y, [42] * 3)
def annot_map_fn(key):
return key[1:]
@pytest.mark.parametrize(
"annotation",
[
{"worker": "alice"},
{"block_id": annot_map_fn},
],
)
def test_single_annotation(annotation):
with dask.annotate(**annotation):
A = da.ones((10, 10), chunks=(5, 5))
alayer = A.__dask_graph__().layers[A.name]
assert alayer.annotations == annotation
assert dask.config.get("annotations", None) is None
def test_multiple_annotations():
with dask.annotate(block_id=annot_map_fn):
with dask.annotate(resource="GPU"):
A = da.ones((10, 10), chunks=(5, 5))
B = A + 1
C = B + 1
assert dask.config.get("annotations", None) is None
alayer = A.__dask_graph__().layers[A.name]
blayer = B.__dask_graph__().layers[B.name]
clayer = C.__dask_graph__().layers[C.name]
assert alayer.annotations == {"resource": "GPU", "block_id": annot_map_fn}
assert blayer.annotations == {"block_id": annot_map_fn}
assert clayer.annotations is None
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webpwnized/cryptography | transference.py | 52660c14aa71afe087cf380bb1e9d067fa639bc6 | # Requires pip install bitarray
from bitarray import bitarray
import argparse, math
def derive_transfer_function(pTransferFunctionString: str) -> list:
lTransferFunction = list(map(int, pTransferFunctionString.split(',')))
lTransferFunctionValid = True
lLengthTransferFunction = len(lTransferFunction)
for i in range(0, lLengthTransferFunction):
if i not in lTransferFunction:
lTransferFunctionValid = False
break
# end if
# end for
if not lTransferFunctionValid:
raise Exception('Transfer function must contain all integers from 0 to N where (N - 1) is length of the substitution array.')
lExponent = math.log(lLengthTransferFunction, 2)
if lExponent != math.floor(lExponent):
raise Exception('Transfer function length must be even power of 2.')
return lTransferFunction
def print_transfer_function_table(pTransferFunction: list) -> None:
lLengthTransferFunction = len(pTransferFunction)
lNumberBits = int(math.log(lLengthTransferFunction, 2))
lFormat = '0' + str(lNumberBits) + 'b'
# print column headers
print()
for i in range(0, lNumberBits):
print("x=" + str(i) + "\t", end="")
for i in range(0, lNumberBits):
print("y=" + str(i) + "\t", end="")
print()
# print values for transfer function
for lIndex, lSubstitutionValue in enumerate(pTransferFunction):
lBinaryIndex = bitarray(format(lIndex, lFormat))
lBinarySV = bitarray(format(lSubstitutionValue, lFormat))
for i in range(0, lNumberBits):
print(int(lBinaryIndex[i]), end="")
print("\t", end="")
for i in range(0, lNumberBits):
print(int(lBinarySV[i]), end="")
print("\t", end="")
print()
print()
def print_linear_approximation_table(pTransferFunction: list) -> None:
lLengthTransferFunction = len(pTransferFunction)
lNumberBits = int(math.log(lLengthTransferFunction, 2))
lFormat = '0' + str(lNumberBits) + 'b'
# print column headers
print("\t", end="")
for i in range(0, lLengthTransferFunction):
print("b=" + str(i) + "\t", end="")
print()
for lA in range(0, lLengthTransferFunction):
# print row header
print("a=" + str(lA) + "\t", end="")
for lB in range(0, lLengthTransferFunction):
a = bitarray(format(lA, lFormat))
b = bitarray(format(lB, lFormat))
lCount = 0
for lX, lY in enumerate(pTransferFunction):
x = bitarray(format(lX, lFormat))
y = bitarray(format(lY, lFormat))
lVectorXorOfAX = 0
for i in range(0, lNumberBits):
lVectorXorOfAX ^= int(a[i]) * int(x[i])
lVectorXorOfBY = 0
for i in range(0, lNumberBits):
lVectorXorOfBY ^= int(b[i]) * int(y[i])
lAXxorBY = lVectorXorOfAX ^ lVectorXorOfBY
if lAXxorBY == 0:
lCount += 1
# end looping through transfer function
print(str(lCount) + "\t", end="")
# end for b
print()
# end for a
if __name__ == '__main__':
lArgParser = argparse.ArgumentParser(description='Transference: A tool to help visualize s-boxes (substitution boxes or transfer functions)')
lArgParser.add_argument('-tft', '--transfer-function-table', help='Print the transfer function table for the s-box', action='store_true')
lArgParser.add_argument('-lat', '--linear-approximation-table', help='Calculate the linear transformation table for the s-box', action='store_true')
lArgParser.add_argument('-all', '--all', help='Calculate the linear transformation table for the s-box', action='store_true')
lArgParser.add_argument('-v', '--verbose', help='Enables verbose output', action='store_true')
lArgParser.add_argument('INPUT', action='store', type=str, help='The substitution table (s-box) represented as a comma delimted list of integers. The length of the list is the number of bits in the substitution. Required. Example: 3,2,0,1 means substitute 3 for 0, 2 for 1, 0 for 2 and 1 for 3. ')
lArgs = lArgParser.parse_args()
lTransferFunction = derive_transfer_function(lArgs.INPUT)
if lArgs.all:
lArgs.transfer_function_table = lArgs.linear_approximation_table = True
if lArgs.transfer_function_table:
print_transfer_function_table(lTransferFunction)
if lArgs.linear_approximation_table:
print_linear_approximation_table(lTransferFunction)
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mjcaley/spamc | tests/test_client.py | 67c4f2b13d569238ea24794eb5253a1416226a2a | import pytest
from aiospamc.client import Client
from aiospamc.exceptions import (
BadResponse,
UsageException,
DataErrorException,
NoInputException,
NoUserException,
NoHostException,
UnavailableException,
InternalSoftwareException,
OSErrorException,
OSFileException,
CantCreateException,
IOErrorException,
TemporaryFailureException,
ProtocolException,
NoPermissionException,
ConfigException,
ServerTimeoutException,
ResponseException,
)
from aiospamc.responses import Response
async def test_request_sent_to_connection(mock_client_dependency, mocker, hostname):
mock_req = mocker.MagicMock()
await mock_client_dependency.request(mock_req, host=hostname)
assert (
bytes(mock_req)
== mock_client_dependency.connection_factory().request.await_args[0][0]
)
async def test_request_response_sent_to_parser(
mock_client_dependency, mocker, hostname
):
mock_req = mocker.MagicMock()
connection = mock_client_dependency.connection_factory()
parser = mock_client_dependency.parser_factory()
mocker.spy(parser, "parse")
await mock_client_dependency.request(mock_req, host=hostname)
response = connection.request.return_value
assert response == parser.parse.call_args[0][0]
async def test_request_returns_response(mock_client_dependency, mocker, hostname):
mock_req = mocker.MagicMock()
connection = mock_client_dependency.connection_factory()
parser = mock_client_dependency.parser_factory()
parse_spy = mocker.spy(parser, "parse")
result = await mock_client_dependency.request(mock_req, host=hostname)
expected = Response(**parse_spy.spy_return)
assert expected == result
async def test_request_raises_usage(mock_client_response, mocker, ex_usage, hostname):
mock_client = mock_client_response(ex_usage)
with pytest.raises(UsageException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_data_err(
mock_client_response, mocker, ex_data_err, hostname
):
mock_client = mock_client_response(ex_data_err)
with pytest.raises(DataErrorException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_no_input(
mock_client_response, mocker, ex_no_input, hostname
):
mock_client = mock_client_response(ex_no_input)
with pytest.raises(NoInputException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_no_user(
mock_client_response, mocker, ex_no_user, hostname
):
mock_client = mock_client_response(ex_no_user)
with pytest.raises(NoUserException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_no_host(
mock_client_response, mocker, ex_no_host, hostname
):
mock_client = mock_client_response(ex_no_host)
with pytest.raises(NoHostException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_unavailable(
mock_client_response, mocker, ex_unavailable, hostname
):
mock_client = mock_client_response(ex_unavailable)
with pytest.raises(UnavailableException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_software(
mock_client_response, mocker, ex_software, hostname
):
mock_client = mock_client_response(ex_software)
with pytest.raises(InternalSoftwareException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_os_error(
mock_client_response, mocker, ex_os_err, hostname
):
mock_client = mock_client_response(ex_os_err)
with pytest.raises(OSErrorException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_os_file(
mock_client_response, mocker, ex_os_file, hostname
):
mock_client = mock_client_response(ex_os_file)
with pytest.raises(OSFileException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_cant_create(
mock_client_response, mocker, ex_cant_create, hostname
):
mock_client = mock_client_response(ex_cant_create)
with pytest.raises(CantCreateException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_io_error(
mock_client_response, mocker, ex_io_err, hostname
):
mock_client = mock_client_response(ex_io_err)
with pytest.raises(IOErrorException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_temporary_failure(
mock_client_response, mocker, ex_temp_fail, hostname
):
mock_client = mock_client_response(ex_temp_fail)
with pytest.raises(TemporaryFailureException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_protocol(
mock_client_response, mocker, ex_protocol, hostname
):
mock_client = mock_client_response(ex_protocol)
with pytest.raises(ProtocolException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_no_permission(
mock_client_response, mocker, ex_no_perm, hostname
):
mock_client = mock_client_response(ex_no_perm)
with pytest.raises(NoPermissionException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_config(mock_client_response, mocker, ex_config, hostname):
mock_client = mock_client_response(ex_config)
with pytest.raises(ConfigException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_timeout(
mock_client_response, mocker, ex_timeout, hostname
):
mock_client = mock_client_response(ex_timeout)
with pytest.raises(ServerTimeoutException):
await mock_client.request(mocker.MagicMock(), host=hostname)
async def test_request_raises_undefined(
mock_client_response, mocker, ex_undefined, hostname
):
mock_client = mock_client_response(ex_undefined)
with pytest.raises(ResponseException):
await mock_client.request(mocker.MagicMock(), host=hostname)
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tacaswell/sunpy | sunpy/conftest.py | 1e06d75408d1a621749a5d4e743ae44a31886100 | import os
import tempfile
import importlib
import pytest
import astropy
import astropy.config.paths
# Force MPL to use non-gui backends for testing.
try:
import matplotlib
except ImportError:
pass
else:
matplotlib.use('Agg')
# Don't actually import pytest_remotedata because that can do things to the
# entrypoints code in pytest.
remotedata_spec = importlib.util.find_spec("pytest_remotedata")
HAVE_REMOTEDATA = remotedata_spec is not None
# Do not collect the sample data file because this would download the sample data.
collect_ignore = ["data/sample.py"]
@pytest.fixture(scope='session', autouse=True)
def tmp_config_dir(request):
"""
Globally set the default config for all tests.
"""
tmpdir = tempfile.TemporaryDirectory()
os.environ["SUNPY_CONFIGDIR"] = str(tmpdir.name)
astropy.config.paths.set_temp_config._temp_path = str(tmpdir.name)
astropy.config.paths.set_temp_cache._temp_path = str(tmpdir.name)
yield
del os.environ["SUNPY_CONFIGDIR"]
tmpdir.cleanup()
astropy.config.paths.set_temp_config._temp_path = None
astropy.config.paths.set_temp_cache._temp_path = None
@pytest.fixture()
def sunpy_cache(mocker, tmp_path):
"""
Provide a way to add local files to the cache. This can be useful when mocking
remote requests.
"""
from types import MethodType
from sunpy.data.data_manager.cache import Cache
from sunpy.data.data_manager.downloader import ParfiveDownloader
from sunpy.data.data_manager.storage import InMemStorage
cache = Cache(
ParfiveDownloader(),
InMemStorage(),
tmp_path,
None
)
def add(self, url, path):
self._storage.store({
'url': url,
'file_path': path,
'file_hash': 'none', # hash doesn't matter
})
cache.add = MethodType(add, cache)
def func(mocked):
mocker.patch(mocked, cache)
return cache
yield func
@pytest.fixture()
def undo_config_dir_patch():
"""
Provide a way for certain tests to not have the config dir.
"""
oridir = os.environ["SUNPY_CONFIGDIR"]
del os.environ["SUNPY_CONFIGDIR"]
yield
os.environ["SUNPY_CONFIGDIR"] = oridir
@pytest.fixture(scope='session', autouse=True)
def hide_parfive_progress(request):
"""
Globally set the HIDE_PARFIVE_PROGESS to hide the parfive progress bar in tests.
Used by the parfive helper class only.
"""
os.environ["HIDE_PARFIVE_PROGESS"] = "True"
yield
del os.environ["HIDE_PARFIVE_PROGESS"]
@pytest.fixture(scope='session', autouse=True)
def tmp_dl_dir(request):
"""
Globally set the default download directory for the test run to a tmp dir.
"""
with tempfile.TemporaryDirectory() as tmpdir:
os.environ["SUNPY_DOWNLOADDIR"] = tmpdir
yield tmpdir
del os.environ["SUNPY_DOWNLOADDIR"]
@pytest.fixture()
def undo_download_dir_patch():
"""
Provide a way for certain tests to not have tmp download dir.
"""
oridir = os.environ["SUNPY_DOWNLOADDIR"]
del os.environ["SUNPY_DOWNLOADDIR"]
yield
os.environ["SUNPY_DOWNLOADDIR"] = oridir
def pytest_runtest_setup(item):
"""
pytest hook to skip all tests that have the mark 'remotedata' if the
pytest_remotedata plugin is not installed.
"""
if isinstance(item, pytest.Function):
if 'remote_data' in item.keywords and not HAVE_REMOTEDATA:
pytest.skip("skipping remotedata tests as pytest-remotedata is not installed")
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asmateus/PyQtCalendar | qtcalendar/models.py | b8e5e468082f08159744f692e8edaf2ad52fccbb | '''
Models for QtWidgets
'''
from collections import deque
from math import ceil
import datetime as dt
import calendar
class EventInCalendar__Model:
class Text:
@staticmethod
def getDefault():
return EventInCalendar__Model.Text()
def __init__(self, event=None, overflow=False):
if event is None:
self.init_date = dt.datetime(1, 1, 1)
self.end_date = dt.datetime(9999, 12, 31)
self.place = Event__Model.Place()
else:
if overflow:
self.init_date = dt.datetime.combine(
event.getInitDate().date(), dt.time(0, 0, 0))
else:
self.init_date = event.getInitDate()
self.end_date = event.getEndDate()
self.place = event.getPlace()
def __str__(self):
init_time, end_time = self.init_date.time(), self.end_date.time()
return ' '.join([str(i) for i in [init_time, end_time, self.place]])
@staticmethod
def colorOf(val):
range_list = [
(0.0, 0.2, 'rgb(178, 0, 0)'),
(0.2, 0.5, 'rgb(255, 40, 40)'),
(0.5, 0.7, 'rgb(191, 165, 0)'),
(0.7, 1.0, 'rgb(252, 224, 45)'),
(1.0, 1.1, 'rgb(46, 234, 81)'),
]
for lw, hi, c in range_list:
if lw <= val and hi > val:
return c
def __init__(self, master, overflow):
self._fulfillment = 0.0
self._overflow = overflow
self._master = master
self._event = None
def getFulFillmentStatus(self, numeric=False):
if not numeric:
return EventInCalendar__Model.colorOf(self._fulfillment)
return self._fulfillment
def setEvent(self, event):
self._event = event.getModel()
self._fulfillment = self._event.getFulFillmentStatus()
def __str__(self):
if self._event is None:
return EventInCalendar__Model.Text().__str__()
return EventInCalendar__Model.Text(self._event, self._overflow).__str__()
class Event__Model:
class Place:
def __init__(self, name='NA', people=0):
self.name = name
self.people = people
def __str__(self):
return self.name
def __init__(self, init_date, end_date, place, fulfillment=0.0):
self._init_date = init_date
self._end_date = end_date
self._place = place
self._fulfillment = fulfillment
def getFulFillmentStatus(self):
return self._fulfillment
def getInitDate(self):
return self._init_date
def getEndDate(self):
return self._end_date
def getPlace(self):
return self._place
class Date__Model:
TYPE_WEEKDAY = 0
TYPE_WEEKEND = 1
TYPE_HOLYDAY = 2
TYPE_FREEDAY = 3
TYPE_GRAYDAY = 4
@staticmethod
def colorOf(val):
color_list = [
(Date__Model.TYPE_WEEKDAY, (219, 219, 219)),
(Date__Model.TYPE_WEEKEND, (183, 183, 183)),
(Date__Model.TYPE_HOLYDAY, (183, 183, 183)),
(Date__Model.TYPE_FREEDAY, (0, 216, 255)),
(Date__Model.TYPE_GRAYDAY, (255, 255, 255)),
]
for d, c in color_list:
if d == val:
return c
return color_list[0][1]
def __init__(self, master, date):
self._master = master
self._events = list()
self._date = date
self._date_type = Date__Model.TYPE_WEEKDAY
def setDate(self, date, datetype=TYPE_WEEKDAY):
self._date = date
self._date_type = datetype
def getDate(self):
return self._date
def getDateType(self, numeric=False):
if numeric is False:
return Date__Model.colorOf(self._date_type)
return self._date_type
def addEvent(self, event):
self._events.append(event)
def getEvents(self):
return self._events
class Calendar__Model:
TYPE_MONDAY_LEADING = 0
TYPE_TUESDAY_LEADING = 1
TYPE_WEDNESDAY_LEADING = 2
TYPE_THURSDAY_LEADING = 3
TYPE_FRIDAY_LEADING = 4
TYPE_SATURDAY_LEADING = 5
TYPE_SUNDAY_LEADING = 6
MAX_DIM_X = 7
MAX_DIM_Y = 6
WEEKENDS = [5, 6]
@staticmethod
def dayOf(date, init, datatree):
'''
Returns the day of the week of a given date and the position
of that day in the calendar grid.
The returned text value of the day is recovered from the stringer module.
'''
days = datatree['str']['days']
# Get the day of the week of the selected date
datetuple = tuple([int(s) for s in str(date).split(' ')[0].split('-')])
day = days[list(zip(*days))[0].index(calendar.weekday(*datetuple))][1]
# Horizontal position in the grid is deduced from the selected leading day
days_dq = deque(days)
days_dq.rotate(7 - init)
pos_x = list(zip(*days_dq))[0].index(calendar.weekday(*datetuple))
# Vertical position is deduced from the selected leading day and the
# day of the first date of that month
firstmonthday = (datetuple[0], datetuple[1], 1)
fday = list(zip(*days_dq))[0].index(calendar.weekday(*firstmonthday))
pos_y = ceil((fday + date.day) / 7) - 1
# Return the place in the calendar grid depending on the offset
return day, pos_x, pos_y
def __init__(self, master, ctype=TYPE_SUNDAY_LEADING, holidays=list()):
'''
Calendar constructor, a calendar is an array of dates that should
always be full, thus, initialy an array of empty dates (6x7), is
array is called holders; a second empty array of dates is created
and will replace eventually the dates of the respective holder date.
Both arrays are validated through a snapshot array, the snapshot refers
to the dates that fill the Calendar grid for a current month, be those
dates from the actual month or the adjacent months
'''
self._master = master
self._type = ctype
self._holidays = holidays
# Assume month as current month
self._month = tuple([dt.date.today().year, dt.date.today().month])
# Generate the snapshot for the current month
self._snapshot = self.generateSnapshot()
# Create empty dates from the snapshot
self._dates = self.generateDefaultDates()
def generateSnapshot(self):
rt = list()
if self._month is None:
return rt
# First day of month
first_day = dt.date(self._month[0], self._month[1], 1)
# Find day of first position in calendar grid
offset = Calendar__Model.dayOf(first_day, self._type, self._master.getDataTree())[1]
first_day -= dt.timedelta(offset)
# Once first position is encountered, fill the holder array
for i in range(Calendar__Model.MAX_DIM_X * Calendar__Model.MAX_DIM_Y):
rt.append(first_day)
first_day += dt.timedelta(1)
return rt
def generateDefaultDates(self):
rt = list()
for date in self._snapshot:
created_date = self._master.createDate(date)
self.setDateType(created_date)
rt.append(created_date)
return rt
def addDate(self, date):
if self._month is not None:
if date.getModel().getDate() in self._snapshot:
index = self._snapshot.index(date.getModel().getDate())
self.setDateType(date)
self._dates[index] = date
def addEventInCalendar(self, date, eic):
if self._month is not None:
if date in self._snapshot:
index = self._snapshot.index(date)
self._dates[index].addCalendarEvent(eic)
def setDateType(self, date):
current_type = date.getModel().getDateType(numeric=True)
deduced_type = Date__Model.TYPE_WEEKDAY
dt_date = date.getModel().getDate()
dt_tuple = (dt_date.year, dt_date.month, dt_date.day)
if calendar.weekday(*dt_tuple) in Calendar__Model.WEEKENDS:
deduced_type = Date__Model.TYPE_WEEKEND
if dt_date in self._holidays:
deduced_type = Date__Model.TYPE_HOLYDAY
if (dt_date.year, dt_date.month) != self._month:
deduced_type = Date__Model.TYPE_GRAYDAY
if current_type < deduced_type:
current_type = deduced_type
date.changeDateType(current_type)
def _update(self):
self._snapshot = self.generateSnapshot()
self._dates = self.generateDefaultDates()
# Add the required events
events = self._master.getEvents()
events_to_add = list()
for event in events:
if event.getModel().getInitDate().date() in self._snapshot:
events_to_add.append(event)
self._master.createEvents(events_to_add)
def setMonth(self, month):
self._month = month
self._update()
def getMonth(self):
return self._month
def monthSubtract(self):
month = self._month
if month[1] == 1:
if month[0] == 1:
return month
else:
return (month[0] - 1, 12)
else:
return (month[0], month[1] - 1)
def monthAdd(self):
month = self._month
if month[1] == 12:
if month[0] == 9999:
return month
else:
return (month[0] + 1, 1)
else:
return (month[0], month[1] + 1)
def setDataTree(self, datatree):
self._datatree = datatree
self._update()
def getDataTree(self):
return self._datatree
def posInSnapshot(self, date):
i = self._snapshot.index(date)
return ceil((i + 1) / 7) - 1, (i) % 7
def getHolderDimensions(self):
return Calendar__Model.MAX_DIM_X, Calendar__Model.MAX_DIM_Y
def getDates(self):
return self._dates
def getType(self):
return self._type
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Forest216/BigDL | python/orca/src/bigdl/orca/data/tf/data.py | 840da9a2eaf395978dd83730b02aa5e5dfbd7989 | #
# Copyright 2016 The BigDL Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import tensorflow as tf
from bigdl.orca.tfpark.tf_dataset import TensorMeta
from bigdl.dllib.utils import nest
from bigdl.orca.data import SparkXShards
from bigdl.dllib.utils import log4Error
class Dataset(object):
"""
Represents a distributed set of elements backed by an RDD,
which is created by applying tensorflow dataset transformations
on each partitions.
"""
def __init__(self, xshards, create_dataset_fn):
self.xshards = xshards
self.create_dataset_fn = create_dataset_fn
def as_graph_rdd(self, batch_per_shard, drop_remainder=True):
create_dataset_fn = self.create_dataset_fn
def to_dataset(iter):
data_list = list(iter)
import tensorflow as tf
if not data_list:
return []
datasets = [create_dataset_fn(data) for data in data_list]
from functools import reduce
dataset = reduce(lambda x, y: x.concatenate(y), datasets)
dataset = dataset.batch(batch_per_shard, drop_remainder)
iterator = dataset.make_initializable_iterator()
train_next_ops = nest.flatten(iterator.get_next())
output_types = [t for t in nest.flatten(dataset.output_types)]
output_types_enum = [t.as_datatype_enum for t in output_types]
init_op_name = iterator.initializer.name
table_init_op = tf.tables_initializer().name
output_names = [op.name for op in train_next_ops]
graph = train_next_ops[0].graph
flatten_shapes = nest.flatten(dataset.output_shapes)
flatten_shapes = [shape[1:] for shape in flatten_shapes]
flatten_tensor_structure = [TensorMeta(dtype=output_types[i],
shape=list(flatten_shapes[i]),
name="zoo_input_{}".format(i))
for i in range(len(flatten_shapes))]
structure = dataset.output_types
if isinstance(structure, tf.DType):
structure = (structure,)
tensor_structure = nest.pack_sequence_as(structure,
flatten_tensor_structure)
meta_info = {
"init_op_name": init_op_name,
"table_init_op": table_init_op,
"output_names": output_names,
"output_types": output_types_enum,
"tensor_structure": tensor_structure
}
return [(bytearray(graph.as_graph_def().SerializeToString()), meta_info)]
graph_rdd_and_meta = self.xshards.rdd.mapPartitions(to_dataset)
return graph_rdd_and_meta
def as_tf_dataset_rdd(self):
create_dataset_fn = self.create_dataset_fn
def to_dataset(iter):
data_list = list(iter)
if not data_list:
return []
from tensorflow.python.distribute.coordinator.values import serialize_dataset_to_graph
datasets = [create_dataset_fn(data) for data in data_list]
from functools import reduce
dataset = reduce(lambda x, y: x.concatenate(y), datasets)
ds_def = serialize_dataset_to_graph(dataset).numpy()
elem_spec = dataset.element_spec
return [{"ds_def": ds_def, "elem_spec": elem_spec}]
tf_dataset_rdd = self.xshards.rdd.mapPartitions(to_dataset)
return tf_dataset_rdd
@staticmethod
def from_tensor_slices(xshards):
return TensorSliceDataset(xshards)
@staticmethod
def from_feature_table(tbl):
from bigdl.friesian.feature import FeatureTable
from bigdl.friesian.feature.utils import featuretable_to_xshards
log4Error.invalidInputError(isinstance(tbl, FeatureTable),
"Only Friesian FeatureTable is supported")
xshards = featuretable_to_xshards(tbl)
return TensorSliceDataset(xshards)
def map(self, map_func):
return MapDataset(self, map_func)
class TensorSliceDataset(Dataset):
def __init__(self, xshards):
assert isinstance(xshards, SparkXShards), \
"only datasets backed by a SparkXShards are supported"
self.xshards = xshards
def create_dataset_fn(data):
return tf.data.Dataset.from_tensor_slices(data)
super().__init__(xshards, create_dataset_fn)
class MapDataset(Dataset):
def __init__(self, input_dataset, map_func):
create_pre_dataset_fn = input_dataset.create_dataset_fn
def create_dataset_fn(data):
dataset = create_pre_dataset_fn(data)
return dataset.map(map_func)
super().__init__(xshards=input_dataset.xshards,
create_dataset_fn=create_dataset_fn)
| [((4548, 4576), 'bigdl.friesian.feature.utils.featuretable_to_xshards', 'featuretable_to_xshards', (['tbl'], {}), '(tbl)\n', (4571, 4576), False, 'from bigdl.friesian.feature.utils import featuretable_to_xshards\n'), ((2163, 2198), 'bigdl.dllib.utils.nest.flatten', 'nest.flatten', (['dataset.output_shapes'], {}), '(dataset.output_shapes)\n', (2175, 2198), False, 'from bigdl.dllib.utils import nest\n'), ((2750, 2808), 'bigdl.dllib.utils.nest.pack_sequence_as', 'nest.pack_sequence_as', (['structure', 'flatten_tensor_structure'], {}), '(structure, flatten_tensor_structure)\n', (2771, 2808), False, 'from bigdl.dllib.utils import nest\n'), ((4972, 5012), 'tensorflow.data.Dataset.from_tensor_slices', 'tf.data.Dataset.from_tensor_slices', (['data'], {}), '(data)\n', (5006, 5012), True, 'import tensorflow as tf\n'), ((1997, 2020), 'tensorflow.tables_initializer', 'tf.tables_initializer', ([], {}), '()\n', (2018, 2020), True, 'import tensorflow as tf\n'), ((1804, 1838), 'bigdl.dllib.utils.nest.flatten', 'nest.flatten', (['dataset.output_types'], {}), '(dataset.output_types)\n', (1816, 1838), False, 'from bigdl.dllib.utils import nest\n'), ((3852, 3887), 'tensorflow.python.distribute.coordinator.values.serialize_dataset_to_graph', 'serialize_dataset_to_graph', (['dataset'], {}), '(dataset)\n', (3878, 3887), False, 'from tensorflow.python.distribute.coordinator.values import serialize_dataset_to_graph\n')] |
StableCoder/vulkan-mini-libs-2 | tools/generate_serialization_header.py | e048f45149816e100d3f4f51306626ebf547b032 | #!/usr/bin/env python3
import sys
import getopt
import xml.etree.ElementTree as ET
def processVendors(outFile, vendors):
outFile.writelines(["\nconstexpr std::array<std::string_view, ", str(
len(vendors)), "> vendors = {{\n"])
for vendor in vendors:
outFile.writelines([' \"', vendor.tag, '\",\n'])
outFile.write('}};\n')
def processEnumValue(outFile, enum, value):
if not value.get('value') is None:
# Spitting out plain values
outFile.write(value.get('value'))
elif not value.get('bitpos') is None:
# Bitflag
outFile.writelines(
['0x', format(1 << int(value.get('bitpos')), '08X')])
elif not value.get('alias') is None:
processEnumValue(outFile, enum, enum.find(value.get('alias')))
def processEnums(outFile, enums, vendors, first, last):
for enum in enums:
# Skip VkResult
if enum.tag == 'VkResult':
continue
# Skip if there's no values, MSVC can't do zero-sized arrays
if len(enum.findall('./')) == 0:
continue
outFile.writelines(
['\nconstexpr EnumValueSet ', enum.tag, 'Sets[] = {\n'])
# Determine how much to chop off the front
strName = enum.tag
typeDigit = ''
# Determine if type ends with vendor tag
vendorName = ''
for vendor in vendors:
if strName.endswith(vendor.tag):
vendorName = vendor.tag
strName = strName[:-len(vendorName)]
if strName[-1].isdigit():
typeDigit = strName[-1]
strName = strName[:-1]
if strName.endswith('FlagBits'):
strName = strName[:-8]
# Construct most likely enum prefix
mainPrefix = ''
for char in strName:
if mainPrefix == '':
mainPrefix += char
elif char.isupper():
mainPrefix += '_'
mainPrefix += char.upper()
else:
mainPrefix += char.upper()
mainPrefix += '_'
if typeDigit != '':
mainPrefix += typeDigit
mainPrefix += '_'
current = first
while current <= last:
for value in enum.findall('./'):
if int(value.get('first')) != current:
continue
outFile.write(" {\"")
valueStr = value.tag
if valueStr.startswith(mainPrefix):
valueStr = valueStr[len(mainPrefix):]
if vendorName != '' and valueStr.endswith(vendorName):
valueStr = valueStr[:-len(vendorName)-1]
if valueStr.endswith('_BIT'):
valueStr = valueStr[:-4]
outFile.write(valueStr)
outFile.write("\", ")
processEnumValue(outFile, enum, value)
outFile.write("},\n")
current += 1
outFile.write('};\n')
def main(argv):
inputFile = ''
outputFile = ''
try:
opts, args = getopt.getopt(argv, 'i:o:', [])
except getopt.GetoptError:
print('Error parsing options')
sys.exit(1)
for opt, arg in opts:
if opt == '-i':
inputFile = arg
elif opt == '-o':
outputFile = arg
if(inputFile == ''):
print("Error: No Vulkan XML file specified")
sys.exit(1)
if(outputFile == ''):
print("Error: No output file specified")
sys.exit(1)
try:
dataXml = ET.parse(inputFile)
dataRoot = dataXml.getroot()
except:
print("Error: Could not open input file: ", inputFile)
sys.exit(1)
firstVersion = int(dataRoot.get('first'))
lastVersion = int(dataRoot.get('last'))
outFile = open(outputFile, "w")
# Common Header
with open("common_header.txt") as fd:
outFile.write(fd.read())
outFile.write('\n')
#
outFile.write("""#ifndef VK_VALUE_SERIALIZATION_HPP
#define VK_VALUE_SERIALIZATION_HPP
/* USAGE:
To use, include this header where the declarations for the boolean checks are required.
On *ONE* compilation unit, include the definition of `#define VK_VALUE_SERIALIZATION_CONFIG_MAIN`
so that the definitions are compiled somewhere following the one definition rule.
*/
#include <vulkan/vulkan.h>
#include <string>
#include <string_view>
""")
# Static Asserts
outFile.writelines(["\nstatic_assert(VK_HEADER_VERSION >= ", str(
firstVersion), ", \"VK_HEADER_VERSION is from before the supported range.\");\n"])
outFile.writelines(["static_assert(VK_HEADER_VERSION <= ", str(
lastVersion), ", \"VK_HEADER_VERSION is from after the supported range.\");\n"])
# Function Declarataions
outFile.write("""
/**
* @brief Macro that automatically stringifies the given Vulkan type for serialization
* @param VKTYPE Actual Vulkan type
* @param VALUE Value to be serialized
* @param STRPTR Pointer to the string to store the serialization in. Only modified if true is
* returned.
* @return True if serialization was successful. False otherwise.
*/
#define VK_SERIALIZE(VKTYPE, VALUE, STRPTR) vk_serialize<VKTYPE>(#VKTYPE, VALUE, STRPTR)
/**
* @brief Macro that automatically stringifies the given Vulkan type for parsing
* @param VKTYPE Actual Vulkan type
* @param STRING String to be parsed
* @param VALPTR Pointer to the value to store the parsed value in. Only modified if true is
* returned.
* @return True if serialization was successful. False otherwise.
*/
#define VK_PARSE(VKTYPE, STRING, VALPTR) vk_parse<VKTYPE>(#VKTYPE, STRING, VALPTR)
/**
* @brief Serializes a Vulkan enumerator/flag type (32-bit)
* @param vkType Name of the Vulkan enumerator/flag type
* @param vkValue Value being serialized
* @param pString Pointer to a string that will be modified with the serialized value. Only modified
* if true is returned.
* @return True the value was successfully serialized. False otherwise.
*/
bool vk_serialize(std::string_view vkType, uint32_t vkValue, std::string *pString);
/**
* @brief Parses a Vulkan enumerator/flag serialized string (32-bit)
* @param vkType Name of the Vulkan enumerator/flag type
* @param vkString String being parsed
* @param pValue Pointer to a value that will be modified with the parsed value. Only modified if
* true is returned.
* @return True the value was successfully serialized. False otherwise.
*/
bool vk_parse(std::string_view vkType, std::string vkString, uint32_t *pValue);
/**
* @brief Serializes a Vulkan enumerator/flag type (64-bit)
* @param vkType Name of the Vulkan enumerator/flag type
* @param vkValue Value being serialized
* @param pString Pointer to a string that will be modified with the serialized value. Only modified
* if true is returned.
* @return True the value was successfully serialized. False otherwise.
*/
bool vk_serialize(std::string_view vkType, uint64_t vkValue, std::string *pString);
/**
* @brief Parses a Vulkan enumerator/flag serialized string (64-bit)
* @param vkType Name of the Vulkan enumerator/flag type
* @param vkString String being parsed
* @param pValue Pointer to a value that will be modified with the parsed value. Only modified if
* true is returned.
* @return True the value was successfully serialized. False otherwise.
*/
bool vk_parse(std::string_view vkType, std::string vkString, uint64_t *pValue);
/**
* @brief Serializes a Vulkan enumerator/flag type
* @tparam Vulkan type being serialized
* @param vkType Name of the Vulkan enumerator/flag type
* @param vkValue Value being serialized
* @param pString Pointer to a string that will be modified with the serialized value. Only modified
* if true is returned.
* @return True the value was successfully serialized. False otherwise.
*/
template <typename T>
bool vk_serialize(std::string_view vkType, T vkValue, std::string *pString) {
return vk_serialize(vkType, static_cast<uint32_t>(vkValue), pString);
}
/**
* @brief Parses a Vulkan enumerator/flag serialized string
* @tparam Vulkan type being parsed
* @param vkType Name of the Vulkan enumerator/flag type
* @param vkString String being parsed
* @param pValue Pointer to a value that will be modified with the parsed value. Only modified if
* true is returned.
* @return True the value was successfully serialized. False otherwise.
*/
template <typename T>
bool vk_parse(std::string_view vkType, std::string vkString, T *pValue) {
uint32_t retVal = 0;
auto found = vk_parse(vkType, vkString, &retVal);
if (found) {
*pValue = static_cast<T>(retVal);
}
return found;
}
""")
# Definition Start
outFile.write("\n#ifdef VK_VALUE_SERIALIZATION_CONFIG_MAIN\n")
outFile.write("\n#include <algorithm>\n")
outFile.write("#include <array>\n")
outFile.write("#include <cstring>\n")
outFile.write("\nnamespace {\n")
# Vendors
vendors = dataRoot.findall('vendors/')
processVendors(outFile, vendors)
# EnumSet Declaration
outFile.write("\nstruct EnumValueSet {\n")
outFile.write(" std::string_view name;\n")
outFile.write(" int64_t value;\n")
outFile.write("};\n")
# Enums
enums = dataRoot.findall('enums/')
processEnums(outFile, enums, vendors, firstVersion, lastVersion)
# Enum Type Declaration
outFile.write("\nstruct EnumType {\n")
outFile.write(" std::string_view name;\n")
outFile.write(" EnumValueSet const* data;\n")
outFile.write(" uint32_t count;\n")
outFile.write(" bool allowEmpty;\n")
outFile.write("};\n")
# Enum Pointer Array
outFile.writelines(["\nconstexpr std::array<EnumType, ", str(
len(enums)-1), "> enumTypes = {{\n"]) # -1 for not doing VkResult
for enum in enums:
if enum.tag == 'VkResult':
continue
valueCount = len(enum.findall('./'))
if valueCount == 0:
outFile.writelines(
[" {\"", str(enum.tag), "\", nullptr, 0, true},\n"])
else:
allowEmpty = "true"
for enumVal in enum.findall('./'):
if enumVal.get('first') == enum.get('first'):
allowEmpty = "false"
outFile.writelines([" {\"", str(enum.tag), "\", ", str(
enum.tag), "Sets, ", str(valueCount), ", ", allowEmpty, "},\n"])
outFile.write('}};\n')
# Function definitions
outFile.write("""
/**
* @brief Removes a vendor tag from the end of the given string view
* @param view String view to remove the vendor tag from
* @return A string_view without the vendor tag, if it was suffixed
*/
std::string_view stripVendor(std::string_view view) {
for (auto const &it : vendors) {
// Don't strip if it's all that's left
if (view == it)
break;
if (strncmp(view.data() + view.size() - it.size(), it.data(), it.size()) == 0) {
view = view.substr(0, view.size() - it.size());
break;
}
}
return view;
}
/**
* @brief Strips '_BIT' from the end of a string, if there
*/
std::string_view stripBit(std::string_view view) {
if (view.size() > strlen("_BIT")) {
if (view.substr(view.size() - strlen("_BIT")) == "_BIT") {
return view.substr(0, view.size() - strlen("_BIT"));
}
}
return view;
}
bool getEnumType(std::string_view vkType,
EnumValueSet const **ppStart,
EnumValueSet const **ppEnd,
bool *pAllowEmpty) {
// Check for a conversion from Flags -> FlagBits
std::string localString;
if (vkType.rfind("Flags") != std::string::npos) {
localString = vkType;
auto it = localString.rfind("Flags");
localString = localString.replace(it, strlen("Flags"), "FlagBits");
vkType = localString;
}
// Try the original name
for (auto const &it : enumTypes) {
if (vkType == std::string_view{it.name}) {
*ppStart = it.data;
*ppEnd = it.data + it.count;
*pAllowEmpty = it.allowEmpty;
return true;
}
}
// Try a vendor-stripped name
vkType = stripVendor(vkType);
for (auto const &it : enumTypes) {
if (vkType == std::string_view{it.name}) {
*ppStart = it.data;
*ppEnd = it.data + it.count;
*pAllowEmpty = it.allowEmpty;
return true;
}
}
return false;
}
/**
* @brief Converts a Vulkan Flag typename into the prefix that is used for it's enums
* @param typeName Name of the type to generate the Vk enum prefix for
* @return Generated prefix string
*
* Any capitalized letters except for the first has an underscore inserted before it, an underscore
* is added to the end, and all characters are converted to upper case.
*
* It also removed the 'Flags' or 'FlagBits' suffixes.
*/
std::string processEnumPrefix(std::string_view typeName) {
// Flag Bits
std::size_t flagBitsSize = strlen("FlagBits");
if (typeName.size() > flagBitsSize) {
if (strncmp(typeName.data() + typeName.size() - flagBitsSize, "FlagBits", flagBitsSize) ==
0) {
typeName = typeName.substr(0, typeName.size() - strlen("FlagBits"));
}
}
// Flags
std::size_t flagsSize = strlen("Flags");
if (typeName.size() > flagsSize) {
if (strncmp(typeName.data() + typeName.size() - flagsSize, "Flags", flagsSize) == 0) {
typeName = typeName.substr(0, typeName.size() - strlen("Flags"));
}
}
std::string retStr;
for (auto it = typeName.begin(); it != typeName.end(); ++it) {
if (it == typeName.begin()) {
retStr += ::toupper(*it);
} else if (::isupper(*it)) {
retStr += '_';
retStr += *it;
} else {
retStr += toupper(*it);
}
}
retStr += '_';
return retStr;
}
bool findValue(std::string_view findValue,
std::string_view prefix,
uint64_t *pValue,
EnumValueSet const *start,
EnumValueSet const *end) {
// Remove the vendor tag suffix if it's on the value
findValue = stripVendor(findValue);
if (findValue[findValue.size() - 1] == '_')
findValue = findValue.substr(0, findValue.size() - 1);
// Remove '_BIT' if it's there
findValue = stripBit(findValue);
// Iterate until we find the value
while (start != end) {
if (findValue == start->name) {
*pValue |= start->value;
return true;
}
std::string prefixedName{prefix};
prefixedName += start->name;
if (findValue == prefixedName) {
*pValue |= start->value;
return true;
}
++start;
}
return false;
}
/**
* @brief Takes a given string and formats it for use with parsing
* @param str The string to format
* @return Formatted string
*
* First, any non alphanumeric characters are trimmed from both ends of the string.
* After than, any spaces are replaced with underscores, and finally all the characters are
* capitalized. This will generate the string closest to the original ones found in the XML spec.
*/
std::string formatString(std::string str) {
// Trim left
std::size_t cutOffset = 0;
for (auto c : str) {
if (::isalnum(c))
break;
else
++cutOffset;
}
str = str.substr(cutOffset);
// Trim right
cutOffset = 0;
for (std::size_t i = 0; i < str.size(); ++i) {
if (::isalnum(str[i]))
cutOffset = i + 1;
}
str = str.substr(0, cutOffset);
std::replace(str.begin(), str.end(), ' ', '_');
std::for_each(str.begin(), str.end(), [](char &c) { c = ::toupper(c); });
return str;
}
bool serializeBitmask(EnumValueSet const *end,
EnumValueSet const *start,
bool allowEmpty,
uint64_t vkValue,
std::string *pString) {
--end;
--start;
if(start == end) {
// If this is a non-existing bitmask, then return an empty string
*pString = {};
return true;
}
std::string retStr;
while (start != end) {
if(vkValue == 0 && !retStr.empty()) {
break;
}
if ((start->value & vkValue) == start->value) {
// Found a compatible bit mask, add it
if (!retStr.empty()) {
retStr += " | ";
}
retStr += start->name;
vkValue = vkValue ^ start->value;
}
--start;
}
if (vkValue != 0 || (retStr.empty() && !allowEmpty)) {
// Failed to find a valid bitmask for the value
return false;
}
*pString = retStr;
return true;
}
bool serializeEnum(EnumValueSet const *start,
EnumValueSet const *end,
uint64_t vkValue,
std::string *pString) {
while (start != end) {
if (start->value == vkValue) {
*pString = start->name;
return true;
}
++start;
}
return false;
}
bool parseBitmask(std::string_view vkString,
EnumValueSet const *start,
EnumValueSet const *end,
std::string_view prefix,
uint64_t *pValue) {
uint64_t retVal = 0;
auto startCh = vkString.begin();
auto endCh = startCh;
for (; endCh != vkString.end(); ++endCh) {
if (*endCh == '|') {
std::string token(startCh, endCh);
token = formatString(token);
bool foundVal = findValue(token, prefix, &retVal, start, end);
if (!foundVal)
return false;
startCh = endCh + 1;
}
}
if (startCh != endCh) {
std::string token(startCh, endCh);
token = formatString(token);
bool foundVal = findValue(token, prefix, &retVal, start, end);
if (!foundVal)
return false;
}
*pValue = retVal;
return true;
}
bool parseEnum(std::string_view vkString,
EnumValueSet const *start,
EnumValueSet const *end,
std::string_view prefix,
uint64_t *pValue) {
uint64_t retVal = 0;
std::string token = formatString(std::string{vkString});
bool found = findValue(token, prefix, &retVal, start, end);
if (found) {
*pValue = retVal;
}
return found;
}
} // namespace
bool vk_serialize(std::string_view vkType, uint64_t vkValue, std::string *pString) {
if (vkType.empty()) {
return false;
}
EnumValueSet const *start, *end;
bool allowEmpty;
if (!getEnumType(vkType, &start, &end, &allowEmpty)) {
return false;
}
if (vkType.find("Flags") != std::string::npos || vkType.find("FlagBits") != std::string::npos) {
return serializeBitmask(start, end, allowEmpty, vkValue, pString);
}
return serializeEnum(start, end, vkValue, pString);
}
bool vk_serialize(std::string_view vkType, uint32_t vkValue, std::string *pString) {
return vk_serialize(vkType, static_cast<uint64_t>(vkValue), pString);
}
bool vk_parse(std::string_view vkType, std::string vkString, uint64_t *pValue) {
if (vkType.empty()) {
return false;
}
EnumValueSet const *start, *end;
bool allowEmpty;
if (!getEnumType(vkType, &start, &end, &allowEmpty)) {
return false;
}
if (vkString.empty()) {
if (allowEmpty) {
*pValue = 0;
return true;
} else {
return false;
}
}
std::string prefix = processEnumPrefix(stripVendor(vkType));
if (vkType.find("Flags") != std::string::npos || vkType.find("FlagBits") != std::string::npos) {
return parseBitmask(vkString, start, end, prefix, pValue);
}
return parseEnum(vkString, start, end, prefix, pValue);
}
bool vk_parse(std::string_view vkType, std::string vkString, uint32_t *pValue) {
uint64_t tempValue;
if (vk_parse(vkType, vkString, &tempValue)) {
*pValue = static_cast<uint32_t>(tempValue);
return true;
}
return false;
}
""")
# endif
outFile.write("\n#endif // VK_VALUE_SERIALIZATION_CONFIG_MAIN\n")
outFile.write("#endif // VK_VALUE_SERIALIZATION_HPP\n")
outFile.close()
if __name__ == "__main__":
main(sys.argv[1:])
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AmpelProject/Ampel-core | ampel/cli/AbsStockCommand.py | dcbfbe38ba400b7f8e44e641b90217ca1bed4f8f | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# File : Ampel-core/ampel/cli/AbsStockCommand.py
# License : BSD-3-Clause
# Author : vb <vbrinnel@physik.hu-berlin.de>
# Date : 25.03.2021
# Last Modified Date: 25.03.2021
# Last Modified By : vb <vbrinnel@physik.hu-berlin.de>
from typing import Dict, Any, Optional, Union, Literal
from ampel.cli.ArgParserBuilder import ArgParserBuilder
from ampel.cli.MaybeIntAction import MaybeIntAction
from ampel.cli.LoadJSONAction import LoadJSONAction
from ampel.cli.AbsCoreCommand import AbsCoreCommand
from ampel.mongo.utils import maybe_match_array
from ampel.model.UnitModel import UnitModel
from ampel.model.time.UnixTimeModel import UnixTimeModel
from ampel.model.time.TimeStringModel import TimeStringModel
from ampel.model.time.TimeLastRunModel import TimeLastRunModel
from ampel.model.time.TimeDeltaModel import TimeDeltaModel
from ampel.model.time.TimeConstraintModel import TimeConstraintModel
class AbsStockCommand(AbsCoreCommand, abstract=True):
"""
Base class for commands selecting/matching stock(s)
"""
@staticmethod
def get_select_args_help() -> Dict[str, str]:
return {
# Required
'config': 'Path to an ampel config file (yaml/json)',
# Optional
'secrets': 'Path to a YAML secrets store in sops format',
'log-profile': 'One of: default, compact, headerless, verbose, debug',
'id-mapper': 'Convert stock ids using the provided id mapper (ex: ZTFIdMapper)',
# Selection
'stock': 'Stock id(s) (OR matched if multi-valued)',
'channel': 'Channel(s)',
'created-after-ts': 'Created after unix timestamp',
'created-after-str': 'Created after date-time iso string',
'created-after-delta': 'Created after time delta',
'created-after-process': 'Created after last run of process with name',
'created-before-ts': 'Created before unix timestamp',
'created-before-str': 'Created before date-time iso string',
'created-before-delta': 'Created before time delta',
'created-before-process': 'Created before last run of process with name',
'updated-after-ts': 'Updated after unix timestamp',
'updated-after-str': 'Updated after date-time iso string',
'updated-after-delta': 'Updated after time delta',
'updated-after-process': 'Updated after last run of process with name',
'updated-before-ts': 'Updated before unix timestamp',
'updated-before-str': 'Updated before date-time iso string',
'updated-before-delta': 'Updated before time delta',
'updated-before-process': 'Updated before last run of process with name',
'custom-match': 'Custom mongodb match as JSON string (ex: {"body.aKey": {"$gt": 1}})',
}
def add_selection_args(self, builder: ArgParserBuilder) -> None:
# Selection args
builder.add_group('match', 'Stock selection arguments')
builder.add_arg('match', "stock", action=MaybeIntAction, nargs="+")
builder.add_x_args('match',
{'name': 'created-before-str'}, {'name': 'created-before-ts', 'type': int},
{'name': 'created-before-delta', 'action': LoadJSONAction},
{'name': 'created-before-process'}
)
builder.add_x_args('match',
{'name': 'created-after-str'}, {'name': 'created-after-ts', 'type': int},
{'name': 'created-after-delta', 'action': LoadJSONAction},
{'name': 'created-after-process'}
)
builder.add_x_args('match',
{'name': 'updated-before-str'}, {'name': 'updated-before-ts', 'type': int},
{'name': 'updated-before-delta', 'action': LoadJSONAction},
{'name': 'updated-before-process'}
)
builder.add_x_args('match',
{'name': 'updated-after-str'}, {'name': 'updated-after-ts', 'type': int},
{'name': 'updated-after-delta', 'action': LoadJSONAction},
{'name': 'updated-after-process'}
)
builder.create_logic_args('match', "channel", "Channel")
builder.create_logic_args('match', "with-tag", "Tag")
builder.create_logic_args('match', "without-tag", "Tag", excl=True)
builder.add_arg('match', "custom-match", metavar="#", action=LoadJSONAction)
def get_tag(self, args: Dict[str, Any]) -> Optional[Dict[Union[Literal['with'], Literal['without']], Dict]]:
tag: Optional[Dict[Union[Literal['with'], Literal['without']], Dict]] = None
if args.get('with_tag'):
tag = {'with': args['with_tag']}
if args.get('without_tag'):
if tag is None:
tag = {}
tag['without'] = args['without_tag']
return tag
def build_select_model(self, args: Dict[str, Any]) -> UnitModel:
conf = {
"created": self.get_time_model("created", args),
"updated": self.get_time_model("updated", args),
'channel': args['channel'],
'custom': args['custom_match']
}
if args.get('tag'):
conf['tag'] = self.get_tag(args)
if (stock := args.get('stock')):
conf['custom'] = {
'_id': stock if isinstance(stock, (int, bytes, str))
else maybe_match_array(stock)
}
return UnitModel(unit="T3StockSelector", config=conf)
def get_time_model(self, prefix: str, args: Dict[str, Any]) -> TimeConstraintModel:
d: Dict[str, Any] = {'after': None, 'before': None}
for when in ('after', 'before'):
if args.get(x := f"{prefix}_{when}_ts"):
d[when] = UnixTimeModel(match_type='unix_time', value=args[x])
elif args.get(x := f"{prefix}_{when}_str"):
d[when] = TimeStringModel(match_type='time_string', dateTimeStr=args[x], dateTimeFormat="%Y%m%dT%H%M%S")
elif args.get(x := f"{prefix}_{when}_delta"):
d[when] = TimeDeltaModel(match_type='time_delta', **args[x])
elif args.get(x := f"{prefix}_{when}_process"):
d[when] = TimeLastRunModel(match_type='time_last_run', process_name=args[x])
return TimeConstraintModel(**d)
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KLumy/Basic-Algorithm | programmers/lv2/42888.py | e52e4200c1955a9062569814ff3418dd06666845 | from typing import List
def solution(records: List[str]):
logger = []
id_name = dict()
message = {"Enter": "님이 들어왔습니다.", "Leave": "님이 나갔습니다."}
for record in records:
op, id, *name = record.split()
if name:
id_name[id] = name[0]
if op in message:
logger.append((id, op))
answer = []
for log in logger:
id, msg = log
answer.append(id_name[id] + message[msg])
return answer
if __name__ == "__main__":
i = [
"Enter uid1234 Muzi",
"Enter uid4567 Prodo",
"Leave uid1234",
"Enter uid1234 Prodo",
"Change uid4567 Ryan",
]
print(solution(i)) | [] |
bobosoft/intrepyd | app/nets.py | 13f0912b31f86f9bcc50f52ef4ad870e33f0cf65 | """
Implementation of REST API for nets creation
"""
from flask import Blueprint, request
from .utils import typename_to_type
from .contexts import contexts
nr = Blueprint('nets', __name__)
def _create_bool_constant(func):
context = request.get_json()['context']
if context is None:
return {'result': 'error'}, 400
ctx = contexts[context]['context']
net = func(ctx)
return {'result': ctx.net2name[net]}, 201
def _create_unary_gate(func):
context = request.get_json()['context']
x = request.get_json()['x']
if context is None or x is None:
return {'result': 'error'}, 400
ctx = contexts[context]['context']
x = ctx.nets[x]
assert x is not None
net = func(ctx, x)
return {'result': ctx.net2name[net]}, 201
def _create_binary_gate(func):
context = request.get_json()['context']
x = request.get_json()['x']
y = request.get_json()['y']
if context is None or x is None or y is None:
return {'result': 'error'}, 400
ctx = contexts[context]['context']
x = ctx.nets[x]
y = ctx.nets[y]
assert x is not None
assert y is not None
net = func(ctx, x, y)
return {'result': ctx.net2name[net]}, 201
@nr.route('', methods=['GET'])
def list_nets():
"""
Gets the list of the available nets
"""
context = request.args.get('context')
ctx = contexts[context]['context']
return {'nets': [key for key, _ in ctx.nets.items()]}, 200
@nr.route('/true', methods=['POST'])
def create_true():
"""
Creates the net true
"""
return _create_bool_constant(lambda ctx : ctx.mk_true())
@nr.route('/false', methods=['POST'])
def create_false():
"""
Creates the net false
"""
return _create_bool_constant(lambda ctx : ctx.mk_false())
@nr.route('/numbers/create', methods=['POST'])
def create_number():
"""
Creates a number
"""
context = request.get_json()['context']
value = request.get_json()['value']
typ = request.get_json()['type']
if context is None or value is None or typ is None:
return {'result': 'error'}, 400
ctx = contexts[context]['context']
assert value is not None
assert typ is not None
net = ctx.mk_number(value, typename_to_type(ctx, typ))
return {'result': ctx.net2name[net]}, 201
@nr.route('/nots/create', methods=['POST'])
def create_not():
"""
Creates a logical not
"""
return _create_unary_gate(lambda ctx, x : ctx.mk_not(x))
@nr.route('/minuses/create', methods=['POST'])
def create_minus():
"""
Creates an arithmetic minus
"""
return _create_unary_gate(lambda ctx, x : ctx.mk_minus(x))
@nr.route('/ands/create', methods=['POST'])
def create_and():
"""
Creates a logical and
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_and(x, y))
@nr.route('/ors/create', methods=['POST'])
def create_or():
"""
Creates a logical or
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_or(x, y))
@nr.route('/implieses/create', methods=['POST'])
def create_implies():
"""
Creates a logical implies
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_implies(x, y))
@nr.route('/xors/create', methods=['POST'])
def create_xor():
"""
Creates a logical xor
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_xor(x, y))
@nr.route('/iffs/create', methods=['POST'])
def create_iff():
"""
Creates a logical iff
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_iff(x, y))
@nr.route('/adds/create', methods=['POST'])
def create_add():
"""
Creates an addition
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_add(x, y))
@nr.route('/muls/create', methods=['POST'])
def create_mul():
"""
Creates a multiplication
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_mul(x, y))
@nr.route('/divs/create', methods=['POST'])
def create_div():
"""
Creates a division
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_div(x, y))
@nr.route('/mods/create', methods=['POST'])
def create_mod():
"""
Creates a modulus
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_mod(x, y))
@nr.route('/subs/create', methods=['POST'])
def create_sub():
"""
Creates a subtraction
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_sub(x, y))
@nr.route('/eqs/create', methods=['POST'])
def create_eq():
"""
Creates an equality
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_eq(x, y))
@nr.route('/leqs/create', methods=['POST'])
def create_leq():
"""
Creates an less or equal
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_leq(x, y))
@nr.route('/geqs/create', methods=['POST'])
def create_geq():
"""
Creates a greater or equal
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_geq(x, y))
@nr.route('/lts/create', methods=['POST'])
def create_lt():
"""
Creates a less than
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_lt(x, y))
@nr.route('/gts/create', methods=['POST'])
def create_gt():
"""
Creates a greater than
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_gt(x, y))
@nr.route('/neqs/create', methods=['POST'])
def create_neq():
"""
Creates a not equal
"""
return _create_binary_gate(lambda ctx, x, y : ctx.mk_neq(x, y))
@nr.route('/ites/create', methods=['POST'])
def create_ite():
"""
Creates an if then else
"""
context = request.get_json()['context']
x = request.get_json()['x']
y = request.get_json()['y']
z = request.get_json()['z']
if context is None or x is None or y is None or z is None:
return {'result': 'error'}, 400
ctx = contexts[context]['context']
i = ctx.nets[x]
t = ctx.nets[y]
e = ctx.nets[z]
assert i is not None
assert t is not None
assert e is not None
net = ctx.mk_ite(i, t, e)
return {'result': ctx.net2name[net]}, 201
@nr.route('/casts/create', methods=['POST'])
def create_cast():
"""
Creates a type cast
"""
context = request.get_json()['context']
x = request.get_json()['x']
t = request.get_json()['type']
if context is None or x is None or t is None:
return {'result': 'error'}, 400
ctx = contexts[context]['context']
x = ctx.nets[x]
assert ctx is not None
assert x is not None
net = None
if t == 'int8':
net = ctx.mk_cast_to_int8(x)
elif t == 'int16':
net = ctx.mk_cast_to_int16(x)
elif t == 'int32':
net = ctx.mk_cast_to_int32(x)
elif t == 'int64':
net = ctx.mk_cast_to_int64(x)
elif t == 'uint8':
net = ctx.mk_cast_to_uint8(x)
elif t == 'uint16':
net = ctx.mk_cast_to_uint16(x)
elif t == 'uint32':
net = ctx.mk_cast_to_uint32(x)
elif t == 'uint64':
net = ctx.mk_cast_to_uint64(x)
else:
return {'result': 'unhandled type {}'.format(t)}, 400
assert net is not None
return {'result': ctx.net2name[net]}, 201
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Soroosh129/addons | tensorflow_addons/image/utils.py | d92ae02d04e9052f6ca5ea272873efd15eaa35ce | # Copyright 2019 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Image util ops."""
import tensorflow as tf
def get_ndims(image):
return image.get_shape().ndims or tf.rank(image)
def to_4D_image(image):
"""Convert 2/3/4D image to 4D image.
Args:
image: 2/3/4D tensor.
Returns:
4D tensor with the same type.
"""
with tf.control_dependencies(
[
tf.debugging.assert_rank_in(
image, [2, 3, 4], message="`image` must be 2/3/4D tensor"
)
]
):
ndims = image.get_shape().ndims
if ndims is None:
return _dynamic_to_4D_image(image)
elif ndims == 2:
return image[None, :, :, None]
elif ndims == 3:
return image[None, :, :, :]
else:
return image
def _dynamic_to_4D_image(image):
shape = tf.shape(image)
original_rank = tf.rank(image)
# 4D image => [N, H, W, C] or [N, C, H, W]
# 3D image => [1, H, W, C] or [1, C, H, W]
# 2D image => [1, H, W, 1]
left_pad = tf.cast(tf.less_equal(original_rank, 3), dtype=tf.int32)
right_pad = tf.cast(tf.equal(original_rank, 2), dtype=tf.int32)
new_shape = tf.concat(
[
tf.ones(shape=left_pad, dtype=tf.int32),
shape,
tf.ones(shape=right_pad, dtype=tf.int32),
],
axis=0,
)
return tf.reshape(image, new_shape)
def from_4D_image(image, ndims):
"""Convert back to an image with `ndims` rank.
Args:
image: 4D tensor.
ndims: The original rank of the image.
Returns:
`ndims`-D tensor with the same type.
"""
with tf.control_dependencies(
[tf.debugging.assert_rank(image, 4, message="`image` must be 4D tensor")]
):
if isinstance(ndims, tf.Tensor):
return _dynamic_from_4D_image(image, ndims)
elif ndims == 2:
return tf.squeeze(image, [0, 3])
elif ndims == 3:
return tf.squeeze(image, [0])
else:
return image
def _dynamic_from_4D_image(image, original_rank):
shape = tf.shape(image)
# 4D image <= [N, H, W, C] or [N, C, H, W]
# 3D image <= [1, H, W, C] or [1, C, H, W]
# 2D image <= [1, H, W, 1]
begin = tf.cast(tf.less_equal(original_rank, 3), dtype=tf.int32)
end = 4 - tf.cast(tf.equal(original_rank, 2), dtype=tf.int32)
new_shape = shape[begin:end]
return tf.reshape(image, new_shape)
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fossabot/MolVS | tests/test_charge.py | dc5afca7fcea93ebb0a342b766d70e88d2c0b841 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Tests for charge.py"""
from __future__ import print_function
from __future__ import unicode_literals
from __future__ import division
import logging
from rdkit import Chem
from molvs.standardize import Standardizer, standardize_smiles
from molvs.charge import Reionizer
logging.basicConfig(level=logging.DEBUG)
def charge_parent_smiles(smiles, prefer_organic=False):
"""Utility function that returns the charge parent SMILES for given a SMILES string."""
mol = Chem.MolFromSmiles(smiles.encode('utf8'), sanitize=False)
mol = Standardizer(prefer_organic=prefer_organic).charge_parent(mol)
if mol:
return Chem.MolToSmiles(mol, isomericSmiles=True)
def test_charge_parent():
"""Test neutralization of ionized acids and bases."""
assert charge_parent_smiles('C(C(=O)[O-])(Cc1n[n-]nn1)(C[NH3+])(C[N+](=O)[O-])') == 'NCC(Cc1nn[nH]n1)(C[N+](=O)[O-])C(=O)O'
def test_charge_parent2():
"""Test preservation of zwitterion."""
assert charge_parent_smiles('n(C)1cc[n+]2cccc([O-])c12') == 'Cn1cc[n+]2cccc([O-])c12'
def test_charge_parent3():
"""Choline should be left with a positive charge."""
assert charge_parent_smiles('C[N+](C)(C)CCO') == 'C[N+](C)(C)CCO'
def test_charge_parent4():
"""This should have the hydrogen removed to give deanol as a charge parent."""
assert charge_parent_smiles('C[NH+](C)CCO') == 'CN(C)CCO'
def test_charge_parent5():
"""Sodium benzoate to benzoic acid."""
assert charge_parent_smiles('[Na+].O=C([O-])c1ccccc1') == 'O=C(O)c1ccccc1'
def test_charge_parent6():
"""Benzoate ion to benzoic acid."""
assert charge_parent_smiles('O=C([O-])c1ccccc1') == 'O=C(O)c1ccccc1'
def test_charge_parent7():
"""Charges in histidine should be neutralized."""
assert charge_parent_smiles('[NH3+]C(Cc1cnc[nH]1)C(=O)[O-]') == 'NC(Cc1cnc[nH]1)C(=O)O'
def test_charge_parent8():
""""""
assert charge_parent_smiles('C[NH+](C)(C).[Cl-]') == 'CN(C)C'
def test_charge_parent9():
"""No organic fragments."""
assert charge_parent_smiles('[N+](=O)([O-])[O-]') == 'O=[N+]([O-])[O-]'
def test_charge_parent10():
"""No organic fragments."""
assert charge_parent_smiles('[N+](=O)([O-])[O-]', prefer_organic=True) == 'O=[N+]([O-])[O-]'
def test_charge_parent11():
"""Larger inorganic fragment should be chosen."""
assert charge_parent_smiles('[N+](=O)([O-])[O-].[CH2]') == 'O=[N+]([O-])[O-]'
def test_charge_parent12():
"""Smaller organic fragment should be chosen over larger inorganic fragment."""
assert charge_parent_smiles('[N+](=O)([O-])[O-].[CH2]', prefer_organic=True) == '[CH2]'
def test_standardize():
"""Test table salt."""
assert standardize_smiles('[Na].[Cl]') == '[Cl-].[Na+]'
def test_reionize():
"""Test reionizer moves proton to weaker acid."""
mol = Chem.MolFromSmiles('C1=C(C=CC(=C1)[S]([O-])=O)[S](O)(=O)=O')
r = Reionizer()
mol = r.reionize(mol)
assert Chem.MolToSmiles(mol) == 'O=S(O)c1ccc(S(=O)(=O)[O-])cc1'
def test_reionize2():
"""Test charged carbon doesn't get recognised as alpha-carbon-hydrogen-keto."""
mol = Chem.MolFromSmiles('CCOC(=O)C(=O)[CH-]C#N')
r = Reionizer()
mol = r.reionize(mol)
assert Chem.MolToSmiles(mol) == 'CCOC(=O)C(=O)[CH-]C#N'
def test_reionize3():
""""""
mol = Chem.MolFromSmiles('C[N+]1=C[CH-]N(C(=N)N)/C1=C/[N+](=O)[O-]')
r = Reionizer()
mol = r.reionize(mol)
assert Chem.MolToSmiles(mol) == 'C[N+]1=CCN(C(=N)N)C1=[C-][N+](=O)[O-]'
def test_should_complete():
"""Reionization should not infinitely loop forever on these molecules."""
# GitHub Issue #14
assert standardize_smiles('CCCCCCCCCCCCCCCCCC(=O)CC(=C)C(=O)O[Ti](=O)(OC(C)C)C(C)C') == 'C=C(CC(=O)[CH-]CCCCCCCCCCCCCCCC)C(=O)[O-].CC(C)[O-].CCC.[O-2].[Ti+5]'
assert standardize_smiles('OP(=O)(O)[O-].OP(=O)([O-])[O-].[O-]S(=O)(=O)[O-].[Na+].[Na+].[Na+].[Mg+2].[Cl-].[Cl-].[K+].[K+]') == 'O=P([O-])(O)O.O=P([O-])([O-])O.O=S(=O)([O-])[O-].[Cl-].[Cl-].[K+].[K+].[Mg+2].[Na+].[Na+].[Na+]'
def test_forced_charge1():
"""Test forced charge correction maintaining overall neutral charge."""
assert standardize_smiles('[Na].O=C(O)c1ccccc1') == 'O=C([O-])c1ccccc1.[Na+]'
def test_forced_charge2():
"""Test forced charge correction with no corresponding proton for neutralization."""
# GitHub Issue #15
assert standardize_smiles('[Na].[Na]') == '[Na+].[Na+]'
# TODO: Arguably should become selenite ion... O=[Se]([O-])[O-]. Need an AcidBasePair?
assert standardize_smiles('[Na].[Na].O[Se](O)=O') == 'O=[Se](O)O.[Na+].[Na+]'
# def test_reionize3():
# """Test canonical ionization position when multiple equivalent possibilities."""
# mol = Chem.MolFromSmiles('CC1=CC(=CC=C1S(O)=O)S([O-])=O')
# mol2 = Chem.MolFromSmiles('CC1=CC(=CC=C1S([O-])=O)S(O)=O')
# r = Reionizer()
# mol = r.reionize(mol)
# mol2 = r.reionize(mol2)
# assert Chem.MolToSmiles(mol) == 'Cc1cc(S(=O)[O-])ccc1S(=O)O'
# assert Chem.MolToSmiles(mol2) == 'Cc1cc(S(=O)[O-])ccc1S(=O)O'
# assert Chem.MolToSmiles(mol) == Chem.MolToSmiles(mol2)
#
#
# def test_reionize4():
# """Test canonical ionization position when multiple equivalent possibilities."""
# mol = Chem.MolFromSmiles('CCOC(=O)C(=O)[CH-]C#N')
# mol2 = Chem.MolFromSmiles('[CH2-]COC(=O)C(=O)CC#N')
# r = Reionizer()
# mol = r.reionize(mol)
# mol2 = r.reionize(mol2)
# assert Chem.MolToSmiles(mol) == '[CH2-]COC(=O)C(=O)CC#N'
# assert Chem.MolToSmiles(mol2) == ''
# assert Chem.MolToSmiles(mol) == Chem.MolToSmiles(mol2)
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jochanmin/Blog | backend/users/views.py | 465dcb951ebe2e2fabcd81d0c4e0221decc66ccc | from django.shortcuts import render
from django.core import serializers
from .models import User
from django.forms.models import model_to_dict
from rest_framework import status
from rest_framework.response import Response
from rest_framework.decorators import api_view, permission_classes
from rest_framework.permissions import IsAuthenticated
#회원가입 /users/auth/
#아이디를 등록하는곳 /users/register
@api_view(['POST'])
def register(request):
data=request.data
if all(i in data for i in ('email','nickname','password')):
email_check=User.objects.filter(email=data['email'])
nick_check=User.objects.filter(nickname=data['nickname'])
if email_check.exists():
return Response({"message": "email already exists"}, status=status.HTTP_409_CONFLICT)
elif nick_check.exists():
return Response({"message": "nickname already exists"}, status=status.HTTP_409_CONFLICT)
else:
user = User.objects.create_user(
data['email'],
data['nickname'],
data['password'],
)
user.save()
return Response(model_to_dict(user), status=status.HTTP_201_CREATED)
else:
return Response({"message": "key error"}, status=status.HTTP_400_BAD_REQUEST)
# 토큰을 주면 해당 유저의 정보를 얻는 곳 /users/users
@api_view(['GET'])
@permission_classes((IsAuthenticated,))
def info(request):
user = request.user
data = request.data
try:
searchU=User.objects.filter(email=user.email)
if searchU.count==0:
return Response({"message": "Can't find info"}, status=status.HTTP_404_NOT_FOUND)
data = {
'email': user.email,
'nickname':user.nickname
}
return Response((data), status=status.HTTP_200_OK)
except User.DoesNotExist:
return Response({"message": "info does not exists"}, status=status.HTTP_404_NOT_FOUND)
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MrRollyPanda/astral | src/test/test_Location.py | 5a1b013c945fa902b475ff0fa6769f0d43fe2999 | # -*- coding: utf-8 -*-
from pytest import raises
from astral import Astral, AstralError, Location
import datetime
import pytz
def datetime_almost_equal(datetime1, datetime2, seconds=60):
dd = datetime1 - datetime2
sd = (dd.days * 24 * 60 * 60) + dd.seconds
return abs(sd) <= seconds
def test_Location_Name():
c = Location()
assert c.name == 'Greenwich'
c.name = 'London'
assert c.name == 'London'
c.name = 'Köln'
assert c.name == 'Köln'
def test_Location_Country():
c = Location()
assert c.region == 'England'
c.region = 'Australia'
assert c.region == 'Australia'
def test_Location_Elevation():
dd = Astral()
c = dd['London']
assert c.elevation == 24
def test_Location_TimezoneName():
c = Location()
assert c.timezone == 'Europe/London'
c.name = 'Asia/Riyadh'
assert c.name == 'Asia/Riyadh'
def test_Location_TimezoneNameNoLocation():
c = Location()
c._timezone_group = 'Europe'
c._timezone_location = ''
assert c.timezone == 'Europe'
def test_Location_TimezoneNameBad():
c = Location()
with raises(ValueError):
c.timezone = 'bad/timezone'
def test_Location_TimezoneLookup():
c = Location()
assert c.tz == pytz.timezone('Europe/London')
c.timezone='Europe/Stockholm'
assert c.tz == pytz.timezone('Europe/Stockholm')
def test_Location_TimezoneLookupBad():
c = Location()
c._timezone_group = 'bad'
c._timezone_location = 'timezone'
with raises(AstralError):
c.tz
def test_Location_Sun():
c = Location()
c.sun()
def test_Location_Dawn():
c = Location()
c.dawn()
def test_Location_DawnUTC():
c = Location()
c.dawn(local=False)
def test_Location_Sunrise():
c = Location()
c.sunrise()
def test_Location_SunriseUTC():
c = Location()
c.sunrise(local=False)
def test_Location_SolarNoon():
c = Location()
c.solar_noon()
def test_Location_SolarNoonUTC():
c = Location()
c.solar_noon(local=False)
def test_Location_Dusk():
c = Location()
c.dusk()
def test_Location_DuskUTC():
c = Location()
c.dusk(local=False)
def test_Location_Sunset():
c = Location()
c.sunset()
def test_Location_SunsetUTC():
c = Location()
c.sunset(local=False)
def test_Location_SolarElevation():
dd = Astral()
location = dd['Riyadh']
dt = datetime.datetime(2015, 12, 14, 8, 0, 0)
dt = location.tz.localize(dt)
elevation = location.solar_elevation(dt)
assert abs(elevation - 17) < 0.5
def test_Location_SolarAzimuth():
dd = Astral()
location = dd['Riyadh']
dt = datetime.datetime(2015, 12, 14, 8, 0, 0)
dt = location.tz.localize(dt)
azimuth = location.solar_azimuth(dt)
assert abs(azimuth - 126) < 0.5
def test_Location_TimeAtElevation():
dd = Astral()
location = dd['New Delhi']
test_data = {
datetime.date(2016, 1, 5): datetime.datetime(2016, 1, 5, 10, 0),
}
for day, cdt in test_data.items():
cdt = location.tz.localize(cdt)
dt = location.time_at_elevation(28, date=day)
assert datetime_almost_equal(dt, cdt, seconds=600)
def test_Location_SolarDepression():
c = Location(("Heidelberg", "Germany", 49.412, -8.71, "Europe/Berlin"))
c.solar_depression = 'nautical'
assert c.solar_depression == 12
c.solar_depression = 18
assert c.solar_depression == 18
def test_Location_Moon():
d = datetime.date(2017, 12, 1)
c=Location()
assert c.moon_phase(date=d) == 11
def test_Location_TzError():
with raises(AttributeError):
c = Location()
c.tz = 1
def test_Location_equality():
c1 = Location()
c2 = Location()
t = (c1, c2)
assert c1 == c2
assert len(set(t)) == 1
c1 = Location(["Oslo", "Norway", 59.9, 10.7, "Europe/Oslo", 0])
c2 = Location(["Oslo", "Norway", 59.9, 10.7, "Europe/Oslo", 0])
c3 = Location(["Stockholm", "Sweden", 59.3, 18, "Europe/Stockholm", 0])
t1 = (c1, c2)
t2 = (c1, c3)
assert c1 == c2
assert len(set(t1)) == 1
assert c1 != c3
assert len(set(t2)) == 2
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'Astral', ([], {}), '()\n', (2605, 2607), False, 'from astral import Astral, AstralError, Location\n'), ((2645, 2685), 'datetime.datetime', 'datetime.datetime', (['(2015)', '(12)', '(14)', '(8)', '(0)', '(0)'], {}), '(2015, 12, 14, 8, 0, 0)\n', (2662, 2685), False, 'import datetime\n'), ((2845, 2853), 'astral.Astral', 'Astral', ([], {}), '()\n', (2851, 2853), False, 'from astral import Astral, AstralError, Location\n'), ((3223, 3290), 'astral.Location', 'Location', (["('Heidelberg', 'Germany', 49.412, -8.71, 'Europe/Berlin')"], {}), "(('Heidelberg', 'Germany', 49.412, -8.71, 'Europe/Berlin'))\n", (3231, 3290), False, 'from astral import Astral, AstralError, Location\n'), ((3464, 3490), 'datetime.date', 'datetime.date', (['(2017)', '(12)', '(1)'], {}), '(2017, 12, 1)\n', (3477, 3490), False, 'import datetime\n'), ((3497, 3507), 'astral.Location', 'Location', ([], {}), '()\n', (3505, 3507), False, 'from astral import Astral, AstralError, Location\n'), ((3691, 3701), 'astral.Location', 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minjunli/jsonc | __init__.py | a61b72e92729f9177d8d8685deae744244d6be16 | from .jsonc import load, loads, dump, dumps
| [] |
prahal/apitrace | specs/d3d9caps.py | e9426dd61586757d23d7dddc85b3076f477e7f07 | ##########################################################################
#
# Copyright 2008-2009 VMware, Inc.
# All Rights Reserved.
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
#
##########################################################################/
"""d3d9caps.h"""
from winapi import *
from d3d9types import *
D3DVS20CAPS = Flags(DWORD, [
"D3DVS20CAPS_PREDICATION",
])
D3DVSHADERCAPS2_0 = Struct("D3DVSHADERCAPS2_0", [
(D3DVS20CAPS, "Caps"),
(INT, "DynamicFlowControlDepth"),
(INT, "NumTemps"),
(INT, "StaticFlowControlDepth"),
])
D3DPS20CAPS = Flags(DWORD, [
"D3DPS20CAPS_ARBITRARYSWIZZLE",
"D3DPS20CAPS_GRADIENTINSTRUCTIONS",
"D3DPS20CAPS_PREDICATION",
"D3DPS20CAPS_NODEPENDENTREADLIMIT",
"D3DPS20CAPS_NOTEXINSTRUCTIONLIMIT",
])
D3DPSHADERCAPS2_0 = Struct("D3DPSHADERCAPS2_0", [
(D3DPS20CAPS, "Caps"),
(INT, "DynamicFlowControlDepth"),
(INT, "NumTemps"),
(INT, "StaticFlowControlDepth"),
(INT, "NumInstructionSlots"),
])
D3DCAPS = Flags(DWORD, [
"D3DCAPS_READ_SCANLINE",
])
D3DCAPS2 = Flags(DWORD, [
"D3DCAPS2_FULLSCREENGAMMA",
"D3DCAPS2_CANCALIBRATEGAMMA",
"D3DCAPS2_RESERVED",
"D3DCAPS2_CANMANAGERESOURCE",
"D3DCAPS2_DYNAMICTEXTURES",
"D3DCAPS2_CANAUTOGENMIPMAP",
"D3DCAPS2_CANSHARERESOURCE",
])
D3DCAPS3 = Flags(DWORD, [
"D3DCAPS3_RESERVED",
"D3DCAPS3_ALPHA_FULLSCREEN_FLIP_OR_DISCARD",
"D3DCAPS3_LINEAR_TO_SRGB_PRESENTATION",
"D3DCAPS3_COPY_TO_VIDMEM",
"D3DCAPS3_COPY_TO_SYSTEMMEM",
])
D3DPRESENT_INTERVAL = Flags(DWORD, [
#"D3DPRESENT_INTERVAL_DEFAULT", # 0
"D3DPRESENT_INTERVAL_ONE",
"D3DPRESENT_INTERVAL_TWO",
"D3DPRESENT_INTERVAL_THREE",
"D3DPRESENT_INTERVAL_FOUR",
"D3DPRESENT_INTERVAL_IMMEDIATE",
])
D3DCURSORCAPS = Flags(DWORD, [
"D3DCURSORCAPS_COLOR",
"D3DCURSORCAPS_LOWRES",
])
D3DDEVCAPS = Flags(DWORD, [
"D3DDEVCAPS_EXECUTESYSTEMMEMORY",
"D3DDEVCAPS_EXECUTEVIDEOMEMORY",
"D3DDEVCAPS_TLVERTEXSYSTEMMEMORY",
"D3DDEVCAPS_TLVERTEXVIDEOMEMORY",
"D3DDEVCAPS_TEXTURESYSTEMMEMORY",
"D3DDEVCAPS_TEXTUREVIDEOMEMORY",
"D3DDEVCAPS_DRAWPRIMTLVERTEX",
"D3DDEVCAPS_CANRENDERAFTERFLIP",
"D3DDEVCAPS_TEXTURENONLOCALVIDMEM",
"D3DDEVCAPS_DRAWPRIMITIVES2",
"D3DDEVCAPS_SEPARATETEXTUREMEMORIES",
"D3DDEVCAPS_DRAWPRIMITIVES2EX",
"D3DDEVCAPS_HWTRANSFORMANDLIGHT",
"D3DDEVCAPS_CANBLTSYSTONONLOCAL",
"D3DDEVCAPS_HWRASTERIZATION",
"D3DDEVCAPS_PUREDEVICE",
"D3DDEVCAPS_QUINTICRTPATCHES",
"D3DDEVCAPS_RTPATCHES",
"D3DDEVCAPS_RTPATCHHANDLEZERO",
"D3DDEVCAPS_NPATCHES",
])
D3DPMISCCAPS = Flags(DWORD, [
"D3DPMISCCAPS_MASKZ",
"D3DPMISCCAPS_CULLNONE",
"D3DPMISCCAPS_CULLCW",
"D3DPMISCCAPS_CULLCCW",
"D3DPMISCCAPS_COLORWRITEENABLE",
"D3DPMISCCAPS_CLIPPLANESCALEDPOINTS",
"D3DPMISCCAPS_CLIPTLVERTS",
"D3DPMISCCAPS_TSSARGTEMP",
"D3DPMISCCAPS_BLENDOP",
"D3DPMISCCAPS_NULLREFERENCE",
"D3DPMISCCAPS_INDEPENDENTWRITEMASKS",
"D3DPMISCCAPS_PERSTAGECONSTANT",
"D3DPMISCCAPS_FOGANDSPECULARALPHA",
"D3DPMISCCAPS_SEPARATEALPHABLEND",
"D3DPMISCCAPS_MRTINDEPENDENTBITDEPTHS",
"D3DPMISCCAPS_MRTPOSTPIXELSHADERBLENDING",
"D3DPMISCCAPS_FOGVERTEXCLAMPED",
"D3DPMISCCAPS_POSTBLENDSRGBCONVERT",
])
D3DLINECAPS = Flags(DWORD, [
"D3DLINECAPS_TEXTURE",
"D3DLINECAPS_ZTEST",
"D3DLINECAPS_BLEND",
"D3DLINECAPS_ALPHACMP",
"D3DLINECAPS_FOG",
"D3DLINECAPS_ANTIALIAS",
])
D3DPRASTERCAPS = Flags(DWORD, [
"D3DPRASTERCAPS_DITHER",
"D3DPRASTERCAPS_ZTEST",
"D3DPRASTERCAPS_FOGVERTEX",
"D3DPRASTERCAPS_FOGTABLE",
"D3DPRASTERCAPS_MIPMAPLODBIAS",
"D3DPRASTERCAPS_ZBUFFERLESSHSR",
"D3DPRASTERCAPS_FOGRANGE",
"D3DPRASTERCAPS_ANISOTROPY",
"D3DPRASTERCAPS_WBUFFER",
"D3DPRASTERCAPS_WFOG",
"D3DPRASTERCAPS_ZFOG",
"D3DPRASTERCAPS_COLORPERSPECTIVE",
"D3DPRASTERCAPS_SCISSORTEST",
"D3DPRASTERCAPS_SLOPESCALEDEPTHBIAS",
"D3DPRASTERCAPS_DEPTHBIAS",
"D3DPRASTERCAPS_MULTISAMPLE_TOGGLE",
])
D3DPCMPCAPS = Flags(DWORD, [
"D3DPCMPCAPS_NEVER",
"D3DPCMPCAPS_LESS",
"D3DPCMPCAPS_EQUAL",
"D3DPCMPCAPS_LESSEQUAL",
"D3DPCMPCAPS_GREATER",
"D3DPCMPCAPS_NOTEQUAL",
"D3DPCMPCAPS_GREATEREQUAL",
"D3DPCMPCAPS_ALWAYS",
])
D3DPBLENDCAPS = Flags(DWORD, [
"D3DPBLENDCAPS_ZERO",
"D3DPBLENDCAPS_ONE",
"D3DPBLENDCAPS_SRCCOLOR",
"D3DPBLENDCAPS_INVSRCCOLOR",
"D3DPBLENDCAPS_SRCALPHA",
"D3DPBLENDCAPS_INVSRCALPHA",
"D3DPBLENDCAPS_DESTALPHA",
"D3DPBLENDCAPS_INVDESTALPHA",
"D3DPBLENDCAPS_DESTCOLOR",
"D3DPBLENDCAPS_INVDESTCOLOR",
"D3DPBLENDCAPS_SRCALPHASAT",
"D3DPBLENDCAPS_BOTHSRCALPHA",
"D3DPBLENDCAPS_BOTHINVSRCALPHA",
"D3DPBLENDCAPS_BLENDFACTOR",
"D3DPBLENDCAPS_SRCCOLOR2",
"D3DPBLENDCAPS_INVSRCCOLOR2",
])
D3DPSHADECAPS = Flags(DWORD, [
"D3DPSHADECAPS_COLORGOURAUDRGB",
"D3DPSHADECAPS_SPECULARGOURAUDRGB",
"D3DPSHADECAPS_ALPHAGOURAUDBLEND",
"D3DPSHADECAPS_FOGGOURAUD",
])
D3DPTEXTURECAPS = Flags(DWORD, [
"D3DPTEXTURECAPS_PERSPECTIVE",
"D3DPTEXTURECAPS_POW2",
"D3DPTEXTURECAPS_ALPHA",
"D3DPTEXTURECAPS_SQUAREONLY",
"D3DPTEXTURECAPS_TEXREPEATNOTSCALEDBYSIZE",
"D3DPTEXTURECAPS_ALPHAPALETTE",
"D3DPTEXTURECAPS_NONPOW2CONDITIONAL",
"D3DPTEXTURECAPS_PROJECTED",
"D3DPTEXTURECAPS_CUBEMAP",
"D3DPTEXTURECAPS_VOLUMEMAP",
"D3DPTEXTURECAPS_MIPMAP",
"D3DPTEXTURECAPS_MIPVOLUMEMAP",
"D3DPTEXTURECAPS_MIPCUBEMAP",
"D3DPTEXTURECAPS_CUBEMAP_POW2",
"D3DPTEXTURECAPS_VOLUMEMAP_POW2",
"D3DPTEXTURECAPS_NOPROJECTEDBUMPENV",
])
D3DPTFILTERCAPS = Flags(DWORD, [
"D3DPTFILTERCAPS_MINFPOINT",
"D3DPTFILTERCAPS_MINFLINEAR",
"D3DPTFILTERCAPS_MINFANISOTROPIC",
"D3DPTFILTERCAPS_MINFPYRAMIDALQUAD",
"D3DPTFILTERCAPS_MINFGAUSSIANQUAD",
"D3DPTFILTERCAPS_MIPFPOINT",
"D3DPTFILTERCAPS_MIPFLINEAR",
"D3DPTFILTERCAPS_CONVOLUTIONMONO",
"D3DPTFILTERCAPS_MAGFPOINT",
"D3DPTFILTERCAPS_MAGFLINEAR",
"D3DPTFILTERCAPS_MAGFANISOTROPIC",
"D3DPTFILTERCAPS_MAGFPYRAMIDALQUAD",
"D3DPTFILTERCAPS_MAGFGAUSSIANQUAD",
])
D3DPTADDRESSCAPS = Flags(DWORD, [
"D3DPTADDRESSCAPS_WRAP",
"D3DPTADDRESSCAPS_MIRROR",
"D3DPTADDRESSCAPS_CLAMP",
"D3DPTADDRESSCAPS_BORDER",
"D3DPTADDRESSCAPS_INDEPENDENTUV",
"D3DPTADDRESSCAPS_MIRRORONCE",
])
D3DSTENCILCAPS = Flags(DWORD, [
"D3DSTENCILCAPS_KEEP",
"D3DSTENCILCAPS_ZERO",
"D3DSTENCILCAPS_REPLACE",
"D3DSTENCILCAPS_INCRSAT",
"D3DSTENCILCAPS_DECRSAT",
"D3DSTENCILCAPS_INVERT",
"D3DSTENCILCAPS_INCR",
"D3DSTENCILCAPS_DECR",
"D3DSTENCILCAPS_TWOSIDED",
])
D3DTEXOPCAPS = Flags(DWORD, [
"D3DTEXOPCAPS_DISABLE",
"D3DTEXOPCAPS_SELECTARG1",
"D3DTEXOPCAPS_SELECTARG2",
"D3DTEXOPCAPS_MODULATE",
"D3DTEXOPCAPS_MODULATE2X",
"D3DTEXOPCAPS_MODULATE4X",
"D3DTEXOPCAPS_ADD",
"D3DTEXOPCAPS_ADDSIGNED",
"D3DTEXOPCAPS_ADDSIGNED2X",
"D3DTEXOPCAPS_SUBTRACT",
"D3DTEXOPCAPS_ADDSMOOTH",
"D3DTEXOPCAPS_BLENDDIFFUSEALPHA",
"D3DTEXOPCAPS_BLENDTEXTUREALPHA",
"D3DTEXOPCAPS_BLENDFACTORALPHA",
"D3DTEXOPCAPS_BLENDTEXTUREALPHAPM",
"D3DTEXOPCAPS_BLENDCURRENTALPHA",
"D3DTEXOPCAPS_PREMODULATE",
"D3DTEXOPCAPS_MODULATEALPHA_ADDCOLOR",
"D3DTEXOPCAPS_MODULATECOLOR_ADDALPHA",
"D3DTEXOPCAPS_MODULATEINVALPHA_ADDCOLOR",
"D3DTEXOPCAPS_MODULATEINVCOLOR_ADDALPHA",
"D3DTEXOPCAPS_BUMPENVMAP",
"D3DTEXOPCAPS_BUMPENVMAPLUMINANCE",
"D3DTEXOPCAPS_DOTPRODUCT3",
"D3DTEXOPCAPS_MULTIPLYADD",
"D3DTEXOPCAPS_LERP",
])
D3DFVFCAPS = Flags(DWORD, [
"D3DFVFCAPS_TEXCOORDCOUNTMASK",
"D3DFVFCAPS_DONOTSTRIPELEMENTS",
"D3DFVFCAPS_PSIZE",
])
D3DVTXPCAPS = Flags(DWORD, [
"D3DVTXPCAPS_TEXGEN",
"D3DVTXPCAPS_MATERIALSOURCE7",
"D3DVTXPCAPS_DIRECTIONALLIGHTS",
"D3DVTXPCAPS_POSITIONALLIGHTS",
"D3DVTXPCAPS_LOCALVIEWER",
"D3DVTXPCAPS_TWEENING",
"D3DVTXPCAPS_TEXGEN_SPHEREMAP",
"D3DVTXPCAPS_NO_TEXGEN_NONLOCALVIEWER",
])
D3DDEVCAPS2 = Flags(DWORD, [
"D3DDEVCAPS2_STREAMOFFSET",
"D3DDEVCAPS2_DMAPNPATCH",
"D3DDEVCAPS2_ADAPTIVETESSRTPATCH",
"D3DDEVCAPS2_ADAPTIVETESSNPATCH",
"D3DDEVCAPS2_CAN_STRETCHRECT_FROM_TEXTURES",
"D3DDEVCAPS2_PRESAMPLEDDMAPNPATCH",
"D3DDEVCAPS2_VERTEXELEMENTSCANSHARESTREAMOFFSET",
])
D3DDTCAPS = Flags(DWORD, [
"D3DDTCAPS_UBYTE4",
"D3DDTCAPS_UBYTE4N",
"D3DDTCAPS_SHORT2N",
"D3DDTCAPS_SHORT4N",
"D3DDTCAPS_USHORT2N",
"D3DDTCAPS_USHORT4N",
"D3DDTCAPS_UDEC3",
"D3DDTCAPS_DEC3N",
"D3DDTCAPS_FLOAT16_2",
"D3DDTCAPS_FLOAT16_4",
])
#D3DPS_VERSION = Enum("DWORD", [
# "D3DPS_VERSION(0,0)",
# "D3DPS_VERSION(1,0)",
# "D3DPS_VERSION(1,1)",
# "D3DPS_VERSION(1,2)",
# "D3DPS_VERSION(1,3)",
# "D3DPS_VERSION(1,4)",
# "D3DPS_VERSION(2,0)",
# "D3DPS_VERSION(3,0)",
#])
D3DPS_VERSION = DWORD
#D3DVS_VERSION = Enum("DWORD", [
# "D3DVS_VERSION(0,0)",
# "D3DVS_VERSION(1,0)",
# "D3DVS_VERSION(1,1)",
# "D3DVS_VERSION(2,0)",
# "D3DVS_VERSION(3,0)",
#])
D3DVS_VERSION = DWORD
D3DCAPS9 = Struct("D3DCAPS9", [
(D3DDEVTYPE, "DeviceType"),
(UINT, "AdapterOrdinal"),
(D3DCAPS, "Caps"),
(D3DCAPS2, "Caps2"),
(D3DCAPS3, "Caps3"),
(D3DPRESENT_INTERVAL, "PresentationIntervals"),
(D3DCURSORCAPS, "CursorCaps"),
(D3DDEVCAPS, "DevCaps"),
(D3DPMISCCAPS, "PrimitiveMiscCaps"),
(D3DPRASTERCAPS, "RasterCaps"),
(D3DPCMPCAPS, "ZCmpCaps"),
(D3DPBLENDCAPS, "SrcBlendCaps"),
(D3DPBLENDCAPS, "DestBlendCaps"),
(D3DPCMPCAPS, "AlphaCmpCaps"),
(D3DPSHADECAPS, "ShadeCaps"),
(D3DPTEXTURECAPS, "TextureCaps"),
(D3DPTFILTERCAPS, "TextureFilterCaps"),
(D3DPTFILTERCAPS, "CubeTextureFilterCaps"),
(D3DPTFILTERCAPS, "VolumeTextureFilterCaps"),
(D3DPTADDRESSCAPS, "TextureAddressCaps"),
(D3DPTADDRESSCAPS, "VolumeTextureAddressCaps"),
(D3DLINECAPS, "LineCaps"),
(DWORD, "MaxTextureWidth"),
(DWORD, "MaxTextureHeight"),
(DWORD, "MaxVolumeExtent"),
(DWORD, "MaxTextureRepeat"),
(DWORD, "MaxTextureAspectRatio"),
(DWORD, "MaxAnisotropy"),
(Float, "MaxVertexW"),
(Float, "GuardBandLeft"),
(Float, "GuardBandTop"),
(Float, "GuardBandRight"),
(Float, "GuardBandBottom"),
(Float, "ExtentsAdjust"),
(D3DSTENCILCAPS, "StencilCaps"),
(D3DFVFCAPS, "FVFCaps"),
(D3DTEXOPCAPS, "TextureOpCaps"),
(DWORD, "MaxTextureBlendStages"),
(DWORD, "MaxSimultaneousTextures"),
(D3DVTXPCAPS, "VertexProcessingCaps"),
(DWORD, "MaxActiveLights"),
(DWORD, "MaxUserClipPlanes"),
(DWORD, "MaxVertexBlendMatrices"),
(DWORD, "MaxVertexBlendMatrixIndex"),
(Float, "MaxPointSize"),
(DWORD, "MaxPrimitiveCount"),
(DWORD, "MaxVertexIndex"),
(DWORD, "MaxStreams"),
(DWORD, "MaxStreamStride"),
(D3DVS_VERSION, "VertexShaderVersion"),
(DWORD, "MaxVertexShaderConst"),
(D3DPS_VERSION, "PixelShaderVersion"),
(Float, "PixelShader1xMaxValue"),
(D3DDEVCAPS2, "DevCaps2"),
(Float, "MaxNpatchTessellationLevel"),
(DWORD, "Reserved5"),
(UINT, "MasterAdapterOrdinal"),
(UINT, "AdapterOrdinalInGroup"),
(UINT, "NumberOfAdaptersInGroup"),
(D3DDTCAPS, "DeclTypes"),
(DWORD, "NumSimultaneousRTs"),
(D3DPTFILTERCAPS, "StretchRectFilterCaps"),
(D3DVSHADERCAPS2_0, "VS20Caps"),
(D3DPSHADERCAPS2_0, "PS20Caps"),
(D3DPTFILTERCAPS, "VertexTextureFilterCaps"),
(DWORD, "MaxVShaderInstructionsExecuted"),
(DWORD, "MaxPShaderInstructionsExecuted"),
(DWORD, "MaxVertexShader30InstructionSlots"),
(DWORD, "MaxPixelShader30InstructionSlots"),
])
| [] |
NimBuzz01/Project-Miika_SDGP | miika_nlu/venv/Lib/site-packages/tqdm/_dist_ver.py | 08ad1aafafbe9f47c59bd1568b8ac367fefe5503 | __version__ = '4.64.0'
| [] |
katetolstaya/gym-flock | gym_flock/envs/old/mapping.py | 3236d1dafcb1b9be0cf78b471672e8becb2d37af | import gym
from gym import spaces, error, utils
from gym.utils import seeding
import numpy as np
import configparser
from os import path
import matplotlib.pyplot as plt
from matplotlib.pyplot import gca
font = {'family': 'sans-serif',
'weight': 'bold',
'size': 14}
class MappingEnv(gym.Env):
def __init__(self):
# config_file = path.join(path.dirname(__file__), "params_flock.cfg")
# config = configparser.ConfigParser()
# config.read(config_file)
# config = config['flock']
self.nearest_agents = 7
self.nearest_targets = 7
self.mean_pooling = True # normalize the adjacency matrix by the number of neighbors or not
self.centralized = True
# number states per agent
self.nx_system = 4
# number of actions per agent
self.nu = 2
# default problem parameters
self.n_agents = 100 # int(config['network_size'])
# self.comm_radius = 0.9 # float(config['comm_radius'])
self.dt = 0.1 # #float(config['system_dt'])
self.v_max = 5.0 # float(config['max_vel_init'])
self.v_bias = self.v_max
# intitialize state matrices
self.x = None
self.u = None
self.mean_vel = None
self.init_vel = None
self.greedy_action = None
self.diff = None
self.r2 = None
self.adj_mat = None
self.adj_mat_mean = None
self.diff_targets = None
self.r2_targets = None
self.target_observed = None
self.state_network = None
self.state_values = None
self.reward = None
self.max_accel = 1
# self.action_space = spaces.Box(low=-self.max_accel, high=self.max_accel, shape=(2 * self.n_agents,),
# dtype=np.float32)
#
# self.observation_space = spaces.Box(low=-np.Inf, high=np.Inf, shape=(self.n_agents, ),
# dtype=np.float32)
# target initialization
self.px_max = 100
self.py_max = 100
x = np.linspace(-1.0 * self.px_max, self.px_max, self.n_agents)
y = np.linspace(-1.0 * self.py_max, self.py_max, self.n_agents)
tx, ty = np.meshgrid(x, y)
tx = tx.reshape((-1, 1))
ty = ty.reshape((-1, 1))
self.obs_rad = 2.0
self.obs_rad2 = self.obs_rad * self.obs_rad
self.target_x = np.stack((tx, ty), axis=1).reshape((-1, 2))
self.target_unobserved = np.ones((self.n_agents * self.n_agents, 2), dtype=np.bool)
# rendering initialization
self.fig = None
self.ax = None
self.line1 = None
self.line2 = None
self.action_scalar = 10.0
self.seed()
def reset(self):
x = np.zeros((self.n_agents, self.nx_system))
self.target_unobserved = np.ones((self.n_agents * self.n_agents, 2), dtype=np.bool)
x[:, 0] = np.random.uniform(low=-self.px_max, high=self.px_max, size=(self.n_agents,))
x[:, 1] = np.random.uniform(low=-self.py_max, high=self.py_max, size=(self.n_agents,))
#bias = np.random.uniform(low=-self.v_bias, high=self.v_bias, size=(2,))
x[:, 2] = np.random.uniform(low=-self.v_max, high=self.v_max, size=(self.n_agents,)) #+ bias[0]
x[:, 3] = np.random.uniform(low=-self.v_max, high=self.v_max, size=(self.n_agents,)) #+ bias[1]
# keep good initialization
self.mean_vel = np.mean(x[:, 2:4], axis=0)
self.init_vel = x[:, 2:4]
self.x = x
# self.a_net = self.get_connectivity(self.x)
self.compute_helpers()
return self.state_values, self.state_network
def params_from_cfg(self, args):
# TODO
pass
# # self.comm_radius = args.getfloat('comm_radius')
# # self.comm_radius2 = self.comm_radius * self.comm_radius
# # self.vr = 1 / self.comm_radius2 + np.log(self.comm_radius2)
# #
# # self.n_agents = args.getint('n_agents')
# # self.r_max = self.r_max * np.sqrt(self.n_agents)
#
# # self.action_space = spaces.Box(low=-self.max_accel, high=self.max_accel, shape=(2 * self.n_agents,),
# # dtype=np.float32)
# #
# # self.observation_space = spaces.Box(low=-np.Inf, high=np.Inf, shape=(self.n_agents, self.n_features),
# # dtype=np.float32)
#
# self.v_max = args.getfloat('v_max')
# self.v_bias = self.v_max
# self.dt = args.getfloat('dt')
def seed(self, seed=None):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def step(self, u):
# u = np.reshape(u, (-1, 2))
assert u.shape == (self.n_agents, self.nu)
u = np.clip(u, a_min=-self.max_accel, a_max=self.max_accel)
self.u = u * self.action_scalar
old_x = np.copy(self.x)
# x position
self.x[:, 0] = self.x[:, 0] + self.x[:, 2] * self.dt + self.u[:, 0] * self.dt * self.dt * 0.5
# y position
self.x[:, 1] = self.x[:, 1] + self.x[:, 3] * self.dt + self.u[:, 1] * self.dt * self.dt * 0.5
# x velocity
self.x[:, 2] = self.x[:, 2] + self.u[:, 0] * self.dt
# y velocity
self.x[:, 3] = self.x[:, 3] + self.u[:, 1] * self.dt
# clip velocities
self.x[:, 2:4] = np.clip(self.x[:, 2:4], -1.0*self.v_max, self.v_max)
dist_traveled = np.sum(np.linalg.norm(self.x[:, 0:2] - old_x[:, 0:2], axis=1))
self.compute_helpers()
done = (0 == np.sum(self.target_unobserved))
return (self.state_values, self.state_network), 10.0 * self.reward - dist_traveled, done, {}
def compute_helpers(self):
# TODO - check this, and initialize stuff in the init(), and try to make more efficient
# Neighbors computations
self.diff = self.x.reshape((self.n_agents, 1, self.nx_system)) - self.x.reshape(
(1, self.n_agents, self.nx_system))
self.r2 = np.multiply(self.diff[:, :, 0], self.diff[:, :, 0]) + np.multiply(self.diff[:, :, 1],
self.diff[:, :, 1])
np.fill_diagonal(self.r2, np.Inf)
nearest = np.argsort(self.r2, axis=1)
obs_neigh = np.zeros((self.n_agents, self.nearest_agents * 4))
self.adj_mat = np.zeros((self.n_agents, self.n_agents))
for i in range(self.nearest_agents):
ind2, ind3 = np.meshgrid(nearest[:, i], range(4), indexing='ij')
ind1, _ = np.meshgrid(range(self.n_agents), range(4), indexing='ij')
obs_neigh[:, i * self.nx_system:(i + 1) * self.nx_system] = np.reshape(
self.diff[ind1.flatten(), ind2.flatten(), ind3.flatten()], (-1, 4))
self.adj_mat[:, nearest[:, i]] = 1.0
# Normalize the adjacency matrix by the number of neighbors - results in mean pooling, instead of sum pooling
n_neighbors = np.reshape(np.sum(self.adj_mat, axis=1), (self.n_agents, 1)) # correct - checked this
n_neighbors[n_neighbors == 0] = 1
self.adj_mat_mean = self.adj_mat / n_neighbors
# Targets computations
self.diff_targets = self.x[:, 0:2].reshape((self.n_agents, 1, 2)) - self.target_x[
self.target_unobserved].reshape(
(1, -1, 2))
self.r2_targets = np.multiply(self.diff_targets[:, :, 0], self.diff_targets[:, :, 0]) + np.multiply(
self.diff_targets[:, :, 1],
self.diff_targets[:, :, 1])
nearest_targets = np.argsort(self.r2_targets, axis=1)
obs_target = np.zeros((self.n_agents, self.nearest_targets * 2))
for i in range(min(self.nearest_targets, np.shape(nearest_targets)[1])):
ind2, ind3 = np.meshgrid(nearest_targets[:, i], range(2), indexing='ij')
ind1, _ = np.meshgrid(range(self.n_agents), range(2), indexing='ij')
obs_target[:, i * 2:(i + 1) * 2] = np.reshape(
self.diff_targets[ind1.flatten(), ind2.flatten(), ind3.flatten()], (-1, 2))
self.target_observed = np.any(self.r2_targets < self.obs_rad2, axis=0).reshape((-1, 1))
self.target_unobserved[self.target_unobserved] = np.tile(np.logical_not(self.target_observed), (1, 2)).flatten()
self.reward = np.sum(self.target_observed.astype(np.int))
self.state_values = np.hstack((obs_neigh, obs_target))
self.greedy_action = -1.0 * obs_target[:, 0:2]
if self.mean_pooling:
self.state_network = self.adj_mat_mean
else:
self.state_network = self.adj_mat
def controller(self):
"""
The controller for flocking from Turner 2003.
Returns: the optimal action
"""
# TODO
# return np.zeros((self.n_agents, 2))
return self.greedy_action / 10.0
def render(self, mode='human'):
"""
Render the environment with agents as points in 2D space
"""
if self.fig is None:
plt.ion()
fig = plt.figure()
self.ax = fig.add_subplot(111)
line1, = self.ax.plot(self.x[:, 0], self.x[:, 1], 'bo')
locs = self.target_x[self.target_unobserved].reshape((-1, 2))
line2, = self.ax.plot(locs[:, 0], locs[:, 1], 'rx')
plt.ylim(-1.0 * self.py_max, 1.0 * self.py_max)
plt.xlim(-1.0 * self.px_max, 1.0 * self.px_max)
a = gca()
a.set_xticklabels(a.get_xticks(), font)
a.set_yticklabels(a.get_yticks(), font)
plt.title('GNN Controller')
self.fig = fig
self.line1 = line1
self.line2 = line2
# TODO render unobserved targets
else:
self.line1.set_xdata(self.x[:, 0])
self.line1.set_ydata(self.x[:, 1])
locs = self.target_x[self.target_unobserved].reshape((-1,2))
self.line2.set_xdata(locs[:, 0])
self.line2.set_ydata(locs[:, 1])
self.fig.canvas.draw()
self.fig.canvas.flush_events()
def close(self):
pass
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PaulWang1905/tensorflow | tensorflow/python/kernel_tests/lu_op_test.py | ebf12d22b4801fb8dab5034cc94562bf7cc33fa0 | # Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for tensorflow.ops.tf.Lu."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.client import session
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
from tensorflow.python.framework import ops
from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import linalg_ops
from tensorflow.python.ops import map_fn
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import random_ops
from tensorflow.python.ops import variables
from tensorflow.python.platform import benchmark
from tensorflow.python.platform import test
class LuOpTest(test.TestCase):
@property
def float_types(self):
return set((np.float64, np.float32, np.complex64, np.complex128))
def _verifyLuBase(self, x, lower, upper, perm, verification,
output_idx_type):
lower_np, upper_np, perm_np, verification_np = self.evaluate(
[lower, upper, perm, verification])
self.assertAllClose(x, verification_np)
self.assertShapeEqual(x, lower)
self.assertShapeEqual(x, upper)
self.assertAllEqual(x.shape[:-1], perm.shape.as_list())
# Check dtypes are as expected.
self.assertEqual(x.dtype, lower_np.dtype)
self.assertEqual(x.dtype, upper_np.dtype)
self.assertEqual(output_idx_type.as_numpy_dtype, perm_np.dtype)
# Check that the permutation is valid.
if perm_np.shape[-1] > 0:
perm_reshaped = np.reshape(perm_np, (-1, perm_np.shape[-1]))
for perm_vector in perm_reshaped:
self.assertAllClose(np.arange(len(perm_vector)), np.sort(perm_vector))
def _verifyLu(self, x, output_idx_type=dtypes.int64):
# Verify that Px = LU.
lu, perm = linalg_ops.lu(x, output_idx_type=output_idx_type)
# Prepare the lower factor of shape num_rows x num_rows
lu_shape = np.array(lu.shape.as_list())
batch_shape = lu_shape[:-2]
num_rows = lu_shape[-2]
num_cols = lu_shape[-1]
lower = array_ops.matrix_band_part(lu, -1, 0)
if num_rows > num_cols:
eye = linalg_ops.eye(
num_rows, batch_shape=batch_shape, dtype=lower.dtype)
lower = array_ops.concat([lower, eye[..., num_cols:]], axis=-1)
elif num_rows < num_cols:
lower = lower[..., :num_rows]
# Fill the diagonal with ones.
ones_diag = array_ops.ones(
np.append(batch_shape, num_rows), dtype=lower.dtype)
lower = array_ops.matrix_set_diag(lower, ones_diag)
# Prepare the upper factor.
upper = array_ops.matrix_band_part(lu, 0, -1)
verification = math_ops.matmul(lower, upper)
# Permute the rows of product of the Cholesky factors.
if num_rows > 0:
# Reshape the product of the triangular factors and permutation indices
# to a single batch dimension. This makes it easy to apply
# invert_permutation and gather_nd ops.
perm_reshaped = array_ops.reshape(perm, [-1, num_rows])
verification_reshaped = array_ops.reshape(verification,
[-1, num_rows, num_cols])
# Invert the permutation in each batch.
inv_perm_reshaped = map_fn.map_fn(array_ops.invert_permutation,
perm_reshaped)
batch_size = perm_reshaped.shape.as_list()[0]
# Prepare the batch indices with the same shape as the permutation.
# The corresponding batch index is paired with each of the `num_rows`
# permutation indices.
batch_indices = math_ops.cast(
array_ops.broadcast_to(
math_ops.range(batch_size)[:, None], perm_reshaped.shape),
dtype=output_idx_type)
permuted_verification_reshaped = array_ops.gather_nd(
verification_reshaped,
array_ops.stack([batch_indices, inv_perm_reshaped], axis=-1))
# Reshape the verification matrix back to the original shape.
verification = array_ops.reshape(permuted_verification_reshaped,
lu_shape)
self._verifyLuBase(x, lower, upper, perm, verification,
output_idx_type)
def testBasic(self):
data = np.array([[4., -1., 2.], [-1., 6., 0], [10., 0., 5.]])
for dtype in (np.float32, np.float64):
for output_idx_type in (dtypes.int32, dtypes.int64):
self._verifyLu(data.astype(dtype), output_idx_type=output_idx_type)
for dtype in (np.complex64, np.complex128):
for output_idx_type in (dtypes.int32, dtypes.int64):
complex_data = np.tril(1j * data, -1).astype(dtype)
complex_data += np.triu(-1j * data, 1).astype(dtype)
complex_data += data
self._verifyLu(complex_data, output_idx_type=output_idx_type)
def testPivoting(self):
# This matrix triggers partial pivoting because the first diagonal entry
# is small.
data = np.array([[1e-9, 1., 0.], [1., 0., 0], [0., 1., 5]])
self._verifyLu(data.astype(np.float32))
for dtype in (np.float32, np.float64):
self._verifyLu(data.astype(dtype))
_, p = linalg_ops.lu(data)
p_val = self.evaluate([p])
# Make sure p_val is not the identity permutation.
self.assertNotAllClose(np.arange(3), p_val)
for dtype in (np.complex64, np.complex128):
complex_data = np.tril(1j * data, -1).astype(dtype)
complex_data += np.triu(-1j * data, 1).astype(dtype)
complex_data += data
self._verifyLu(complex_data)
_, p = linalg_ops.lu(data)
p_val = self.evaluate([p])
# Make sure p_val is not the identity permutation.
self.assertNotAllClose(np.arange(3), p_val)
def testInvalidMatrix(self):
# LU factorization gives an error when the input is singular.
# Note: A singular matrix may return without error but it won't be a valid
# factorization.
for dtype in self.float_types:
with self.assertRaises(errors.InvalidArgumentError):
self.evaluate(
linalg_ops.lu(
np.array([[1., 2., 3.], [2., 4., 6.], [2., 3., 4.]],
dtype=dtype)))
with self.assertRaises(errors.InvalidArgumentError):
self.evaluate(
linalg_ops.lu(
np.array([[[1., 2., 3.], [2., 4., 6.], [1., 2., 3.]],
[[1., 2., 3.], [3., 4., 5.], [5., 6., 7.]]],
dtype=dtype)))
def testBatch(self):
simple_array = np.array([[[1., -1.], [2., 5.]]]) # shape (1, 2, 2)
self._verifyLu(simple_array)
self._verifyLu(np.vstack((simple_array, simple_array)))
odd_sized_array = np.array([[[4., -1., 2.], [-1., 6., 0], [2., 0., 5.]]])
self._verifyLu(np.vstack((odd_sized_array, odd_sized_array)))
batch_size = 200
# Generate random matrices.
np.random.seed(42)
matrices = np.random.rand(batch_size, 5, 5)
self._verifyLu(matrices)
# Generate random complex valued matrices.
np.random.seed(52)
matrices = np.random.rand(batch_size, 5,
5) + 1j * np.random.rand(batch_size, 5, 5)
self._verifyLu(matrices)
def testLargeMatrix(self):
# Generate random matrices.
n = 500
np.random.seed(64)
data = np.random.rand(n, n)
self._verifyLu(data)
# Generate random complex valued matrices.
np.random.seed(129)
data = np.random.rand(n, n) + 1j * np.random.rand(n, n)
self._verifyLu(data)
@test_util.run_v1_only("b/120545219")
def testEmpty(self):
self._verifyLu(np.empty([0, 2, 2]))
self._verifyLu(np.empty([2, 0, 0]))
@test_util.run_deprecated_v1
def testConcurrentExecutesWithoutError(self):
matrix1 = random_ops.random_normal([5, 5], seed=42)
matrix2 = random_ops.random_normal([5, 5], seed=42)
lu1, p1 = linalg_ops.lu(matrix1)
lu2, p2 = linalg_ops.lu(matrix2)
lu1_val, p1_val, lu2_val, p2_val = self.evaluate([lu1, p1, lu2, p2])
self.assertAllEqual(lu1_val, lu2_val)
self.assertAllEqual(p1_val, p2_val)
class LuBenchmark(test.Benchmark):
shapes = [
(4, 4),
(10, 10),
(16, 16),
(101, 101),
(256, 256),
(1000, 1000),
(1024, 1024),
(2048, 2048),
(4096, 4096),
(513, 2, 2),
(513, 8, 8),
(513, 256, 256),
(4, 513, 2, 2),
]
def _GenerateMatrix(self, shape):
batch_shape = shape[:-2]
shape = shape[-2:]
assert shape[0] == shape[1]
n = shape[0]
matrix = np.ones(shape).astype(np.float32) / (2.0 * n) + np.diag(
np.ones(n).astype(np.float32))
return np.tile(matrix, batch_shape + (1, 1))
def benchmarkLuOp(self):
for shape in self.shapes:
with ops.Graph().as_default(), \
session.Session(config=benchmark.benchmark_config()) as sess, \
ops.device("/cpu:0"):
matrix = variables.Variable(self._GenerateMatrix(shape))
lu, p = linalg_ops.lu(matrix)
variables.global_variables_initializer().run()
self.run_op_benchmark(
sess,
control_flow_ops.group(lu, p),
min_iters=25,
name="lu_cpu_{shape}".format(shape=shape))
if test.is_gpu_available(True):
with ops.Graph().as_default(), \
session.Session(config=benchmark.benchmark_config()) as sess, \
ops.device("/device:GPU:0"):
matrix = variables.Variable(self._GenerateMatrix(shape))
lu, p = linalg_ops.lu(matrix)
variables.global_variables_initializer().run()
self.run_op_benchmark(
sess,
control_flow_ops.group(lu, p),
min_iters=25,
name="lu_gpu_{shape}".format(shape=shape))
if __name__ == "__main__":
test.main()
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|
zhouyangnk/Montreal-Forced-Aligner | aligner/features/processing.py | 4f8733409e79a50744616921a04fccf115e8af6f | import multiprocessing as mp
import subprocess
import shutil
import os
from ..helper import make_path_safe, thirdparty_binary, filter_scp
from ..exceptions import CorpusError
def mfcc_func(directory, job_name, mfcc_config_path): # pragma: no cover
log_directory = os.path.join(directory, 'log')
raw_mfcc_path = os.path.join(directory, 'raw_mfcc.{}.ark'.format(job_name))
raw_scp_path = os.path.join(directory, 'feats.{}.scp'.format(job_name))
log_path = os.path.join(log_directory, 'make_mfcc.{}.log'.format(job_name))
segment_path = os.path.join(directory, 'segments.{}'.format(job_name))
scp_path = os.path.join(directory, 'wav.{}.scp'.format(job_name))
with open(log_path, 'w') as f:
if os.path.exists(segment_path):
seg_proc = subprocess.Popen([thirdparty_binary('extract-segments'),
'scp,p:' + scp_path, segment_path, 'ark:-'],
stdout=subprocess.PIPE, stderr=f)
comp_proc = subprocess.Popen([thirdparty_binary('compute-mfcc-feats'), '--verbose=2',
'--config=' + mfcc_config_path,
'ark:-', 'ark:-'],
stdout=subprocess.PIPE, stderr=f, stdin=seg_proc.stdout)
else:
comp_proc = subprocess.Popen([thirdparty_binary('compute-mfcc-feats'), '--verbose=2',
'--config=' + mfcc_config_path,
'scp,p:' + scp_path, 'ark:-'],
stdout=subprocess.PIPE, stderr=f)
copy_proc = subprocess.Popen([thirdparty_binary('copy-feats'),
'--compress=true', 'ark:-',
'ark,scp:{},{}'.format(raw_mfcc_path, raw_scp_path)],
stdin=comp_proc.stdout, stderr=f)
copy_proc.wait()
def init(env):
os.environ = env
def mfcc(mfcc_directory, num_jobs, feature_config, frequency_configs):
"""
Multiprocessing function that converts wav files into MFCCs
See http://kaldi-asr.org/doc/feat.html and
http://kaldi-asr.org/doc/compute-mfcc-feats_8cc.html for more details on how
MFCCs are computed.
Also see https://github.com/kaldi-asr/kaldi/blob/master/egs/wsj/s5/steps/make_mfcc.sh
for the bash script this function was based on.
Parameters
----------
mfcc_directory : str
Directory to save MFCC feature matrices
log_directory : str
Directory to store log files
num_jobs : int
The number of processes to use in calculation
mfcc_configs : list of :class:`~aligner.config.MfccConfig`
Configuration object for generating MFCCs
Raises
------
CorpusError
If the files per speaker exceeds the number of files that are
allowed to be open on the computer (for Unix-based systems)
"""
child_env = os.environ.copy()
os.makedirs(os.path.join(mfcc_directory, 'log'), exist_ok=True)
paths = []
for j, p in frequency_configs:
paths.append(feature_config.write(mfcc_directory, j, p))
jobs = [(mfcc_directory, x, paths[x])
for x in range(num_jobs)]
with mp.Pool(processes=num_jobs, initializer=init, initargs=(child_env,)) as pool:
r = False
try:
results = [pool.apply_async(mfcc_func, args=i) for i in jobs]
output = [p.get() for p in results]
except OSError as e:
print(dir(e))
if e.errno == 24:
r = True
else:
raise
if r:
raise (CorpusError(
'There were too many files per speaker to process based on your OS settings. Please try to split your data into more speakers.'))
def apply_cmvn_func(directory, job_name, config):
normed_scp_path = os.path.join(directory, config.raw_feature_id + '.{}.scp'.format(job_name))
normed_ark_path = os.path.join(directory, config.raw_feature_id + '.{}.ark'.format(job_name))
with open(os.path.join(directory, 'log', 'norm.{}.log'.format(job_name)), 'w') as logf:
utt2spkpath = os.path.join(directory, 'utt2spk.{}'.format(job_name))
cmvnpath = os.path.join(directory, 'cmvn.{}.scp'.format(job_name))
featspath = os.path.join(directory, 'feats.{}.scp'.format(job_name))
if not os.path.exists(normed_scp_path):
cmvn_proc = subprocess.Popen([thirdparty_binary('apply-cmvn'),
'--utt2spk=ark:' + utt2spkpath,
'scp:' + cmvnpath,
'scp:' + featspath,
'ark,scp:{},{}'.format(normed_ark_path, normed_scp_path)],
stderr=logf
)
cmvn_proc.communicate()
def apply_cmvn(directory, num_jobs, config):
child_env = os.environ.copy()
jobs = [(directory, x, config)
for x in range(num_jobs)]
with mp.Pool(processes=num_jobs, initializer=init, initargs=(child_env,)) as pool:
results = [pool.apply_async(apply_cmvn_func, args=i) for i in jobs]
output = [p.get() for p in results]
def add_deltas_func(directory, job_name, config):
normed_scp_path = os.path.join(directory, config.raw_feature_id + '.{}.scp'.format(job_name))
ark_path = os.path.join(directory, config.feature_id + '.{}.ark'.format(job_name))
scp_path = os.path.join(directory, config.feature_id + '.{}.scp'.format(job_name))
with open(os.path.join(directory, 'log', 'add_deltas.{}.log'.format(job_name)), 'w') as logf:
if config.fmllr_path is not None and os.path.exists(config.fmllr_path):
deltas_proc = subprocess.Popen([thirdparty_binary('add-deltas'),
'scp:' + normed_scp_path, 'ark:-'],
stderr=logf,
stdout=subprocess.PIPE)
trans_proc = subprocess.Popen([thirdparty_binary('transform-feats'),
'ark:' + config.fmllr_path, 'ark:-',
'ark,scp:{},{}'.format(ark_path, scp_path)],
stdin=deltas_proc.stdout,
stderr=logf)
trans_proc.communicate()
else:
deltas_proc = subprocess.Popen([thirdparty_binary('add-deltas'),
'scp:' + normed_scp_path, 'ark,scp:{},{}'.format(ark_path, scp_path)],
stderr=logf)
deltas_proc.communicate()
def add_deltas(directory, num_jobs, config):
child_env = os.environ.copy()
jobs = [(directory, x, config)
for x in range(num_jobs)]
with mp.Pool(processes=num_jobs, initializer=init, initargs=(child_env,)) as pool:
results = [pool.apply_async(add_deltas_func, args=i) for i in jobs]
output = [p.get() for p in results]
def apply_lda_func(directory, job_name, config):
normed_scp_path = os.path.join(directory, config.raw_feature_id + '.{}.scp'.format(job_name))
ark_path = os.path.join(directory, config.feature_id + '.{}.ark'.format(job_name))
scp_path = os.path.join(directory, config.feature_id + '.{}.scp'.format(job_name))
ivector_scp_path = os.path.join(directory, 'ivector.{}.scp'.format(job_name))
with open(os.path.join(directory, 'log', 'lda.{}.log'.format(job_name)), 'a') as logf:
if os.path.exists(config.lda_path):
splice_feats_proc = subprocess.Popen([thirdparty_binary('splice-feats'),
'--left-context={}'.format(config.splice_left_context),
'--right-context={}'.format(config.splice_right_context),
'scp:' + normed_scp_path,
'ark:-'],
stdout=subprocess.PIPE,
stderr=logf)
if config.ivectors and os.path.exists(ivector_scp_path):
transform_feats_proc = subprocess.Popen([thirdparty_binary("transform-feats"),
config.lda_path,
'ark:-',
'ark:-'],
stdin=splice_feats_proc.stdout,
stdout=subprocess.PIPE,
stderr=logf)
paste_proc = subprocess.Popen([thirdparty_binary('paste-feats'),
'ark:-',
'scp:' + ivector_scp_path,
'ark,scp:{},{}'.format(ark_path, scp_path)],
stdin=transform_feats_proc.stdout,
stderr=logf)
paste_proc.communicate()
else:
transform_feats_proc = subprocess.Popen([thirdparty_binary("transform-feats"),
config.lda_path,
'ark:-',
'ark,scp:{},{}'.format(ark_path, scp_path)],
stdin=splice_feats_proc.stdout,
stderr=logf)
transform_feats_proc.communicate()
else:
logf.write('could not find "{}"\n'.format(config.lda_path))
splice_feats_proc = subprocess.Popen([thirdparty_binary('splice-feats'),
'--left-context={}'.format(config.splice_left_context),
'--right-context={}'.format(config.splice_right_context),
'scp:' + normed_scp_path,
'ark,scp:{},{}'.format(ark_path, scp_path)],
stderr=logf)
splice_feats_proc.communicate()
def apply_lda(directory, num_jobs, config):
jobs = [(directory, x, config)
for x in range(num_jobs)]
with mp.Pool(processes=num_jobs, initializer=init, initargs=(os.environ.copy(),)) as pool:
results = [pool.apply_async(apply_lda_func, args=i) for i in jobs]
output = [p.get() for p in results]
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tysen2k/ffai | ffai/util/bothelper.py | 2fa1fd45a8877986fdb21e3fea5e01cbf819d3ec | """
A number of static methods for interpretting the state of the fantasy football pitch that aren't required directly by
the client
"""
from ffai.core import Game, Action, ActionType
from ffai.core.procedure import *
from ffai.util.pathfinding import *
from typing import Optional, List, Dict
class ActionSequence:
def __init__(self, action_steps: List[Action], score: float = 0, description: str = ''):
""" Creates a new ActionSequence - an ordered list of sequential Actions to attempt to undertake.
:param action_steps: Sequence of action steps that form this action.
:param score: A score representing the attractiveness of the move (default: 0)
:param description: A debug string (default: '')
"""
# Note the intention of this object is that when the object is acting, as steps are completed,
# they are removed from the move_sequence so the next move is always the top of the move_sequence
# lis
self.action_steps = action_steps
self.score = score
self.description = description
def is_valid(self, game: Game) -> bool:
pass
def popleft(self):
return self.action_steps.pop(0)
#val = self.action_steps[0]
#del self.action_steps[0]
#return val
def is_empty(self):
return not self.action_steps
class FfHeatMap:
""" A heat map of a Blood Bowl field.
A class for analysing zones of control for both teams
"""
def __init__(self, game: Game, team: Team):
self.game=game
self.team = team
# Note that the edges are not on the field, but represent crowd squares
self.units_friendly: List[List[float]] = [[0.0 for y in range(game.state.pitch.height)] for x in range(game.state.pitch.width)]
self.units_opponent: List[List[float]] = [[0.0 for y in range(game.state.pitch.height)] for x in range(game.state.pitch.width)]
def add_unit_paths(self, player:Player, paths: List[Path]):
is_friendly: bool = player.team == self.team
for path in paths:
if is_friendly:
self.units_friendly[path.steps[-1].x][path.steps[-1].y] += (1.0 - path.cost)*(1.0 - path.cost)
else:
self.units_opponent[path.steps[-1].x][path.steps[-1].y] += (1.0 - path.cost)*(1.0 - path.cost)
def add_unit_by_paths(self, game: Game, paths: Dict[Player, List[Path]]):
for player in paths.keys():
self.add_unit_paths(player, paths[player])
def add_players_moved(self, game: Game, players: List[Player]):
for player in players:
adjacents: List[Square] = game.get_adjacent_squares(player.position, occupied=True)
self.units_friendly[player.position.x][player.position.y] += 1.0
for adjacent in adjacents:
self.units_friendly[player.position.x][player.position.y] += 0.5
def get_ball_move_square_safety_score(self, square: Square) -> float:
# Basic idea - identify safe regions to move the ball towards
friendly_heat: float = self.units_friendly[square.x][square.y]
opponent_heat: float = self.units_opponent[square.x][square.y]
score: float = 30.0 * max(0.0, (1.0 - opponent_heat/2))
return score
#score: float=0.0
#if opponent_heat < 0.25: score += 15.0
#if opponent_heat < 0.05: score += 15.0
#if opponent_heat < 1.5: score += 5
#if friendly_heat > 3.5: score += 10.0
#score += max(30.0, 5.0*(friendly_heat-opponent_heat))
return score
def get_cage_necessity_score(self, square: Square) -> float:
opponent_friendly: float = self.units_friendly[square.x][square.y]
opponent_heat: float = self.units_opponent[square.x][square.y]
score: float = 0.0
if opponent_heat < 0.4: score -= 80.0
# if opponent_friendly > opponent_heat: score -= max(30.0, 10.0*(opponent_friendly-opponent_heat))
# if opponent_heat <1.5: score -=5
# if opponent_heat > opponent_friendly: score += 10.0*(opponent_friendly-opponent_heat)
return score
def blitz_used(game: Game) -> bool:
for action in game.state.available_actions:
if action.action_type == ActionType.START_BLITZ:
return False
return True
def handoff_used(game: Game) -> bool:
for action in game.state.available_actions:
if action.action_type == ActionType.START_HANDOFF:
return False
return True
def foul_used(game: Game) -> bool:
for action in game.state.available_actions:
if action.action_type == ActionType.START_FOUL:
return False
return True
def pass_used(game: Game) -> bool:
for action in game.state.available_actions:
if action.action_type == ActionType.START_PASS:
return False
return True
def get_players(game: Game, team: Team, include_own: bool = True, include_opp: bool = True, include_stunned: bool = True, include_used: bool = True, include_off_pitch: bool = False, only_blockable: bool = False, only_used: bool = False) -> List[Player]:
players: List[Player] = []
selected_players: List[Player] = []
for iteam in game.state.teams:
if iteam == team and include_own:
players.extend(iteam.players)
if iteam != team and include_opp:
players.extend(iteam.players)
for player in players:
if only_blockable and not player.state.up:
continue
if only_used and not player.state.used:
continue
if include_stunned or not player.state.stunned:
if include_used or not player.state.used:
if include_off_pitch or (player.position is not None and not game.is_out_of_bounds(player.position)):
selected_players.append(player)
return selected_players
def caging_squares_north_east(game: Game, protect_square: Square) -> List[Square]:
# * At it's simplest, a cage requires 4 platers in the North-East, South-East, South-West and North-West
# * positions, relative to the ball carrier, such that there is no more than 3 squares between the players in
# * each of those adjacent compass directions.
# *
# * 1 3
# * xx-xx
# * xx-xx
# * --o--
# * xx-xx
# * xx-xx
# * 3 4
# *
# * pitch is 26 long
# *
# *
# * Basically we need one player in each of the corners: 1-4, but spaced such that there is no gap of 3 squares.
# * If the caging player is in 1-4, but next to ball carrier, he ensures this will automatically be me
# *
# * The only exception to this is when the ball carrier is on, or near, the sideline. Then return the squares
# * that can otherwise form the cage.
# *
caging_squares: List[Square] = []
x = protect_square.x
y = protect_square.y
if x <= game.state.pitch.width - 3:
if y == game.state.pitch.height-2:
caging_squares.append(game.get_square(x + 1, y + 1))
caging_squares.append(game.get_square(x + 2, y + 1))
caging_squares.append(game.get_square(x + 1, y))
caging_squares.append(game.get_square(x + 2, y))
elif y == game.state.pitch.height-1:
caging_squares.append(game.get_square(x + 1, y))
caging_squares.append(game.get_square(x + 2, y))
else:
caging_squares.append(game.get_square(x + 1, y + 1))
caging_squares.append(game.get_square(x + 1, y + 2))
caging_squares.append(game.get_square(x + 2, y + 1))
# caging_squares.append(game.state.pitch.get_square(x + 3, y + 3))
return caging_squares
def caging_squares_north_west(game: Game, protect_square: Square) -> List[Square]:
caging_squares: List[Square] = []
x = protect_square.x
y = protect_square.y
if x >= 3:
if y == game.state.pitch.height-2:
caging_squares.append(game.get_square(x - 1, y + 1))
caging_squares.append(game.get_square(x - 2, y + 1))
caging_squares.append(game.get_square(x - 1, y))
caging_squares.append(game.get_square(x - 2, y))
elif y == game.state.pitch.height-1:
caging_squares.append(game.get_square(x - 1, y))
caging_squares.append(game.get_square(x - 2, y))
else:
caging_squares.append(game.get_square(x - 1, y + 1))
caging_squares.append(game.get_square(x - 1, y + 2))
caging_squares.append(game.get_square(x - 2, y + 1))
# caging_squares.append(game.state.pitch.get_square(x - 3, y + 3))
return caging_squares
def caging_squares_south_west(game: Game, protect_square: Square) -> List[Square]:
caging_squares: List[Square] = []
x = protect_square.x
y = protect_square.y
if x >= 3:
if y == 2:
caging_squares.append(game.get_square(x - 1, y - 1))
caging_squares.append(game.get_square(x - 2, y - 1))
caging_squares.append(game.get_square(x - 1, y))
caging_squares.append(game.get_square(x - 2, y))
elif y == 1:
caging_squares.append(game.get_square(x - 1, y))
caging_squares.append(game.get_square(x - 2, y))
else:
caging_squares.append(game.get_square(x - 1, y - 1))
caging_squares.append(game.get_square(x - 1, y - 2))
caging_squares.append(game.get_square(x - 2, y - 1))
# caging_squares.append(game.state.pitch.get_square(x - 3, y - 3))
return caging_squares
def caging_squares_south_east(game: Game, protect_square: Square) -> List[Square]:
caging_squares: List[Square] = []
x = protect_square.x
y = protect_square.y
if x <= game.state.pitch.width-3:
if y == 2:
caging_squares.append(game.get_square(x + 1, y - 1))
caging_squares.append(game.get_square(x + 2, y - 1))
caging_squares.append(game.get_square(x + 1, y))
caging_squares.append(game.get_square(x + 2, y))
elif y == 1:
caging_squares.append(game.get_square(x + 1, y))
caging_squares.append(game.get_square(x + 2, y))
else:
caging_squares.append(game.get_square(x + 1, y - 1))
caging_squares.append(game.get_square(x + 1, y - 2))
caging_squares.append(game.get_square(x + 2, y - 1))
# caging_squares.append(game.get_square(x + 3, y - 3))
return caging_squares
def is_caging_position(game: Game, player: Player, protect_player: Player) -> bool:
return player.position.distance(protect_player.position) <= 2 and not is_castle_position_of(game, player, protect_player)
def has_player_within_n_squares(game: Game, units: List[Player], square: Square, num_squares: int) -> bool:
for cur in units:
if cur.position.distance(square) <= num_squares:
return True
return False
def has_adjacent_player(game: Game, square: Square) -> bool:
return not game.get_adjacent_players(square)
def is_castle_position_of(game: Game, player1: Player, player2: Player) -> bool:
return player1.position.x == player2.position.x or player1.position.y == player2.position.y
def is_bishop_position_of(game: Game, player1: Player, player2: Player) -> bool:
return abs(player1.position.x - player2.position.x) == abs(player1.position.y - player2.position.y)
def attacker_would_surf(game: Game, attacker: Player, defender: Player) -> bool:
if (defender.has_skill(Skill.SIDE_STEP) and not attacker.has_skill(Skill.GRAB)) or defender.has_skill(Skill.STAND_FIRM):
return False
if not attacker.position.is_adjacent(defender.position):
return False
return direct_surf_squares(game, attacker.position, defender.position)
def direct_surf_squares(game: Game, attack_square: Square, defend_square: Square) -> bool:
defender_on_sideline: bool = on_sideline(game, defend_square)
defender_in_endzone: bool = on_endzone(game, defend_square)
if defender_on_sideline and defend_square.x == attack_square.x:
return True
if defender_in_endzone and defend_square.y == attack_square.y:
return True
if defender_in_endzone and defender_on_sideline:
return True
return False
def reverse_x_for_right(game: Game, team: Team, x: int) -> int:
if not game.is_team_side(Square(13, 3), team):
res = game.state.pitch.width - 1 - x
else:
res = x
return res
def reverse_x_for_left(game: Game, team: Team, x: int) -> int:
if game.is_team_side(Square(13, 3), team):
res = game.state.pitch.width - 1 - x
else:
res = x
return res
def on_sideline(game: Game, square: Square) -> bool:
return square.y == 1 or square.y == game.state.pitch.height - 1
def on_endzone(game: Game, square: Square) -> bool:
return square.x == 1 or square.x == game.state.pitch.width - 1
def on_los(game: Game, team: Team, square: Square) -> bool:
return (reverse_x_for_right(game, team, square.x) == 13) and 4 < square.y < 21
def los_squares(game: Game, team: Team) -> List[Square]:
squares: List[Square] = [
game.get_square(reverse_x_for_right(game, team, 13), 5),
game.get_square(reverse_x_for_right(game, team, 13), 6),
game.get_square(reverse_x_for_right(game, team, 13), 7),
game.get_square(reverse_x_for_right(game, team, 13), 8),
game.get_square(reverse_x_for_right(game, team, 13), 9),
game.get_square(reverse_x_for_right(game, team, 13), 10),
game.get_square(reverse_x_for_right(game, team, 13), 11)
]
return squares
def distance_to_sideline(game: Game, square: Square) -> int:
return min(square.y - 1, game.state.pitch.height - square.y - 2)
def is_endzone(game, square: Square) -> bool:
return square.x == 1 or square.x == game.state.pitch.width - 1
def last_block_proc(game) -> Optional[Block]:
for i in range(len(game.state.stack.items) - 1, -1, -1):
if isinstance(game.state.stack.items[i], Block):
block_proc = game.state.stack.items[i]
return block_proc
return None
def is_adjacent_ball(game: Game, square: Square) -> bool:
ball_square = game.get_ball_position()
return ball_square is not None and ball_square.is_adjacent(square)
def squares_within(game: Game, square: Square, distance: int) -> List[Square]:
squares: List[Square] = []
for i in range(-distance, distance+1):
for j in range(-distance, distance+1):
cur_square = game.get_square(square.x+i, square.y+j)
if cur_square != square and not game.is_out_of_bounds(cur_square):
squares.append(cur_square)
return squares
def distance_to_defending_endzone(game: Game, team: Team, position: Square) -> int:
res = reverse_x_for_right(game, team, position.x) - 1
return res
def distance_to_scoring_endzone(game: Game, team: Team, position: Square) -> int:
res = reverse_x_for_left(game, team, position.x) - 1
return res
#return game.state.pitch.width - 1 - reverse_x_for_right(game, team, position.x)
def players_in_scoring_endzone(game: Game, team: Team, include_own: bool = True, include_opp: bool = False) -> List[Player]:
players: List[Player] = get_players(game, team, include_own=include_own, include_opp=include_opp)
selected_players: List[Player] = []
for player in players:
if in_scoring_endzone(game, team, player.position): selected_players.append(player)
return selected_players
def in_scoring_endzone(game: Game, team: Team, square: Square) -> bool:
return reverse_x_for_left(game, team, square.x) == 1
def players_in_scoring_distance(game: Game, team: Team, include_own: bool = True, include_opp: bool = True, include_stunned: bool = False) -> List[Player]:
players: List[Player] = get_players(game, team, include_own=include_own, include_opp=include_opp, include_stunned=include_stunned)
selected_players: List[Player] = []
for player in players:
if distance_to_scoring_endzone(game, team, player.position) <= player.num_moves_left(): selected_players.append(player)
return selected_players
def distance_to_nearest_player(game: Game, team: Team, square: Square, include_own: bool = True, include_opp: bool = True, only_used: bool = False, include_used: bool = True, include_stunned: bool = True, only_blockable: bool = False) -> int:
opps: List[Player] = get_players(game, team, include_own=include_own, include_opp=include_opp, only_used=only_used, include_used=include_used, include_stunned=include_stunned, only_blockable=only_blockable)
cur_max = 100
for opp in opps:
dist = opp.position.distance(square)
cur_max = min(cur_max, dist)
return cur_max
def screening_distance(game: Game, from_square: Square, to_square: Square) -> float:
# Return the "screening distance" between 3 squares. (To complete)
# float dist =math.sqrt(math.pow(square.x - cur.position.x, 3) + math.pow(square.y - cur.position.y, 3))
return 0.0
def num_opponents_can_reach(game: Game, team: Team, square: Square) -> int:
opps: List[Player] = get_players(game, team, include_own=False, include_opp=True)
num_opps_reach: int = 0
for cur in opps:
dist = max(square.x - cur.position.x, square.y - cur.position.y)
if cur.state.stunned: continue
move_allowed = cur.get_ma() + 2
if not cur.state.up: move_allowed -= 3
if dist < move_allowed: num_opps_reach += 1
return num_opps_reach
def num_opponents_on_field(game: Game, team: Team) -> int:
opps: List[Player] = get_players(game, team, include_own=False, include_opp=True)
num_opponents = 0
for cur in opps:
if cur.position is not None: num_opponents += 1
return num_opponents
def number_opponents_closer_than_to_endzone(game: Game, team: Team, square: Square) -> int:
opponents: List[Player] = get_players(game, team, include_own=False, include_opp=True)
num_opps = 0
distance_square_endzone = distance_to_defending_endzone(game, team, square)
for opponent in opponents:
distance_opponent_endzone = distance_to_defending_endzone(game, team, opponent.position)
if distance_opponent_endzone < distance_square_endzone: num_opps += 1
return num_opps
def in_scoring_range(game: Game, player: Player) -> bool:
return player.num_moves_left() >= distance_to_scoring_endzone(game, player.team, player.position)
def players_in_scoring_range(game: Game, team: Team, include_own=True, include_opp=True, include_used=True, include_stunned=True) -> List[Player]:
players: List[Player] = get_players(game, team, include_own=include_own, include_opp=include_opp, include_stunned=include_stunned, include_used=include_used)
res: List[Player] = []
for player in players:
if in_scoring_range(game, player): res.append(player)
return res
def players_in(game: Game, team: Team, squares: List[Square], include_own=True, include_opp=True, include_used=True, include_stunned=True, only_blockable=False) -> List[Player]:
allowed_players: List[Player] = get_players(game, team, include_own=include_own, include_opp=include_opp, include_used=include_used, include_stunned=include_stunned, only_blockable=only_blockable)
res: List[Player] = []
for square in squares:
player: Optional[Player] = game.get_player_at(square)
if player is None:
continue
if player in allowed_players:
res.append(player)
return res
| [] |
DmitriyGrigoriev/sb-fastapi | sb_backend/cli/cli.py | 1aef3db6ce26ea054e048e5927552d48c2eccbfb | # -*- coding: utf-8 -*-
"""sb-fastapi CLI root."""
import logging
import click
from sb_backend.cli.commands.serve import serve
@click.group()
@click.option(
"-v",
"--verbose",
help="Enable verbose logging.",
is_flag=True,
default=False,
)
def cli(**options):
"""sb-fastapi CLI root."""
if options["verbose"]:
level = logging.DEBUG
else:
level = logging.INFO
logging.basicConfig(
level=level,
format="[%(asctime)s] [%(process)s] [%(levelname)s] %(message)s",
datefmt="%Y-%m-%d %H:%M:%S %z",
)
cli.add_command(serve)
| [((131, 144), 'click.group', 'click.group', ([], {}), '()\n', (142, 144), False, 'import click\n'), ((146, 243), 'click.option', 'click.option', (['"""-v"""', '"""--verbose"""'], {'help': '"""Enable verbose logging."""', 'is_flag': '(True)', 'default': '(False)'}), "('-v', '--verbose', help='Enable verbose logging.', is_flag=\n True, default=False)\n", (158, 243), False, 'import click\n'), ((414, 554), 'logging.basicConfig', 'logging.basicConfig', ([], {'level': 'level', 'format': '"""[%(asctime)s] [%(process)s] [%(levelname)s] %(message)s"""', 'datefmt': '"""%Y-%m-%d %H:%M:%S %z"""'}), "(level=level, format=\n '[%(asctime)s] [%(process)s] [%(levelname)s] %(message)s', datefmt=\n '%Y-%m-%d %H:%M:%S %z')\n", (433, 554), False, 'import logging\n')] |
DSandovalFlavio/Dashboards-Plotly-Dash | 1-Chapter/htmlcomponents.py | 58867c2e813bc9273838dec12e7bd15be25504fa | import dash
from dash import html
app = dash.Dash(__name__)
app.layout = html.Div(children=[html.H1('Data Science',
style = {'textAlign': 'center',
'color': '#0FD08D',
'font-size': '50px'}),
html.H2('La carrera mas sexy del siglo XXI',
style = {'textAlign': 'center',
'color' : '#009A64'}),
html.P('Factores clave:'),
html.Ul(children = [html.Li('Factor 1'),
html.Li('Factor 2'),
html.Li('Factor 3'),
html.Li(['Source: ',
html.A('https://www.excelsior.com.mx/nacional/ciencia-de-datos-la-carrera-mas-sexy-del-xxi-en-la-unam/1323946',
href = 'https://www.excelsior.com.mx/nacional/ciencia-de-datos-la-carrera-mas-sexy-del-xxi-en-la-unam/1323946')
])
])
])
if __name__ == '__main__':
app.run_server(debug=True) | [((41, 60), 'dash.Dash', 'dash.Dash', (['__name__'], {}), '(__name__)\n', (50, 60), False, 'import dash\n'), ((94, 193), 'dash.html.H1', 'html.H1', (['"""Data Science"""'], {'style': "{'textAlign': 'center', 'color': '#0FD08D', 'font-size': '50px'}"}), "('Data Science', style={'textAlign': 'center', 'color': '#0FD08D',\n 'font-size': '50px'})\n", (101, 193), False, 'from dash import html\n'), ((361, 460), 'dash.html.H2', 'html.H2', (['"""La carrera mas sexy del siglo XXI"""'], {'style': "{'textAlign': 'center', 'color': '#009A64'}"}), "('La carrera mas sexy del siglo XXI', style={'textAlign': 'center',\n 'color': '#009A64'})\n", (368, 460), False, 'from dash import html\n'), ((581, 606), 'dash.html.P', 'html.P', (['"""Factores clave:"""'], {}), "('Factores clave:')\n", (587, 606), False, 'from dash import html\n'), ((660, 679), 'dash.html.Li', 'html.Li', (['"""Factor 1"""'], {}), "('Factor 1')\n", (667, 679), False, 'from dash import html\n'), ((729, 748), 'dash.html.Li', 'html.Li', (['"""Factor 2"""'], {}), "('Factor 2')\n", (736, 748), False, 'from dash import html\n'), ((798, 817), 'dash.html.Li', 'html.Li', (['"""Factor 3"""'], {}), "('Factor 3')\n", (805, 817), False, 'from dash import html\n'), ((944, 1185), 'dash.html.A', 'html.A', (['"""https://www.excelsior.com.mx/nacional/ciencia-de-datos-la-carrera-mas-sexy-del-xxi-en-la-unam/1323946"""'], {'href': '"""https://www.excelsior.com.mx/nacional/ciencia-de-datos-la-carrera-mas-sexy-del-xxi-en-la-unam/1323946"""'}), "(\n 'https://www.excelsior.com.mx/nacional/ciencia-de-datos-la-carrera-mas-sexy-del-xxi-en-la-unam/1323946'\n , href=\n 'https://www.excelsior.com.mx/nacional/ciencia-de-datos-la-carrera-mas-sexy-del-xxi-en-la-unam/1323946'\n )\n", (950, 1185), False, 'from dash import html\n')] |
iitd-plos/baadal2.0 | baadalinstallation/baadal/modules/vm_helper.py | 0496a8ddb5c0620f3448f018ba48b080b96cbe61 | # -*- coding: utf-8 -*-
###################################################################################
from gluon import current
from helper import get_constant, execute_remote_cmd, config, get_datetime, \
log_exception, is_pingable, get_context_path
from libvirt import * # @UnusedWildImport
from log_handler import logger
from nat_mapper import create_mapping, remove_mapping
import math, shutil, libvirt, os, time, random
import xml.etree.ElementTree as etree
def _choose_datastore():
"""
Chooses datastore from a list of available datastores
"""
# datastore_capacity = current.db(current.db.datastore.id >= 0).select(orderby = current.db.datastore.used
datastores = current.db(current.db.datastore.id >= 0).select()
datastore_length = len(datastores)
logger.debug("datastore_lengtn" + str(datastore_length))
if(datastore_length == 0):
raise Exception("No datastore found.")
else:
count = datastore_length
available_datastores = {}
while count != 0:
available = datastores[datastore_length-count].capacity - datastores[datastore_length-count].used
available_datastores[datastores[datastore_length-count]] = available
count = count-1
z = [(i,available_datastores[i]) for i in available_datastores]
z.sort(key=lambda x: x[1])
available_datastores = z
logger.debug("available d" + str(available_datastores[-1]))
first_elts = available_datastores[-1]
first_elts = first_elts[0]
logger.debug("selected database" + str(first_elts))
return first_elts
def host_resources_used(host_id):
"""
Returns resources utilization of a host in MB, Count
"""
RAM = 0.0
CPU = 0.0
vms = current.db((current.db.vm_data.host_id == host_id) & (current.db.vm_data.status != current.VM_STATUS_UNKNOWN) & (current.db.vm_data.status != current.VM_STATUS_IN_QUEUE)).select()
logger.debug("vms selected are: " + str(vms))
for vm_data in vms:
RAM += vm_data.RAM
CPU += vm_data.vCPU
return (math.ceil(RAM),math.ceil(CPU))
def getVirshDomainConn(vm_details, host_ip=None, domain_name=None):
"""
Generic method to establish libvirt connection
"""
if vm_details != None:
host_ip = vm_details.host_id.host_ip.private_ip
domain_name = vm_details.vm_identity
connection_object = libvirt.open("qemu+ssh://root@" + host_ip + "/system")
domain = connection_object.lookupByName(domain_name)
return (connection_object, domain)
def getVirshDomain(vm_details):
"""
Generic method to establish libvirt connection
"""
(connection_object, domain) = getVirshDomainConn(vm_details)
connection_object.close()
return domain
def _set_portgroup_in_vm(domain_name, portgroup, host_ip, vlan_tag):
"""
Set the vlan tag in network configuration of VM
This is required to ensure that VM fetches IP of its vlan from DHCP
"""
(connection_object, domain) = getVirshDomainConn(None, host_ip, domain_name)
xml = etree.fromstring(domain.XMLDesc(0))
source_network_element = xml.find('.//interface/source')
source_network_string=etree.tostring(source_network_element)
logger.debug("Source network is " + source_network_string)
if source_network_string.find(" bridge=") != -1:
logger.debug("Source is set to bridge adding <vlan><tag_id> to the interface tag ")
root_new = xml.find('.//interface')
root_new_vlan= etree.SubElement(root_new, 'vlan')
root_new_tag= etree.SubElement(root_new_vlan, 'tag')
root_new_tag.set('id',vlan_tag)
logger.debug("After append root_new_vlan is " + etree.tostring(root_new_vlan))
elif source_network_string.find(" network=") != -1:
logger.debug("Source is set to network adding portgroup to the source tag ")
source_network_element.set('portgroup', portgroup)
logger.debug("Changed source network is " + etree.tostring(source_network_element))
else:
logger.debug("Neither VM nor vlan tagId is added in the xml" )
domain = connection_object.defineXML(etree.tostring(xml))
domain.destroy()
domain.create()
domain.isActive()
connection_object.close()
def _get_private_ip_mac(security_domain_id):
"""
Chooses a random Private IP from the pool, such that:
- It is not assigned to any VM or host
- It belongs to VLAN of given security domain
"""
vlans = current.db(current.db.security_domain.id == security_domain_id)._select(current.db.security_domain.vlan)
private_ip_pool = current.db((~current.db.private_ip_pool.id.belongs(current.db(current.db.vm_data.private_ip != None)._select(current.db.vm_data.private_ip)))
& (~current.db.private_ip_pool.id.belongs(current.db(current.db.host.host_ip != None)._select(current.db.host.host_ip)))
& (current.db.private_ip_pool.vlan.belongs(vlans))).select(current.db.private_ip_pool.ALL, orderby='<random>').first()
if private_ip_pool:
return private_ip_pool
else:
sd = current.db.security_domain[security_domain_id]
raise Exception(("Available MACs are exhausted for security domain '%s'." % sd.name))
def _choose_random_public_ip():
"""
Chooses a random Public IP from the pool, such that:
- It is not assigned to any VM
- It is not assigned to any host
- IP is marked active.
"""
public_ip_pool = current.db((~current.db.public_ip_pool.id.belongs(current.db(current.db.vm_data.public_ip != None)._select(current.db.vm_data.public_ip)))
& (~current.db.public_ip_pool.id.belongs(current.db(current.db.host.public_ip != None)._select(current.db.host.public_ip)))
& (current.db.public_ip_pool.is_active == True)) \
.select(current.db.public_ip_pool.ALL, orderby='<random>').first()
return public_ip_pool
def _choose_mac_ip(vm_properties):
"""
Chooses mac address and ip address for a vm to be installed.
It also chooses a random public IP if requested
"""
if not 'private_ip' in vm_properties:
private_ip_info = _get_private_ip_mac(vm_properties['security_domain'])
vm_properties['private_ip'] = private_ip_info.private_ip
vm_properties['mac_addr'] = private_ip_info.mac_addr
vm_properties['vlan_name'] = private_ip_info.vlan.name
vm_properties['vlan_tag'] = private_ip_info.vlan.vlan_tag
if vm_properties['public_ip_req']:
if 'public_ip' not in vm_properties:
public_ip_pool = _choose_random_public_ip()
if public_ip_pool:
vm_properties['public_ip'] = public_ip_pool.public_ip
else:
raise Exception("Available Public IPs are exhausted.")
else:
vm_properties['public_ip'] = None
def _choose_mac_ip_vncport(vm_properties):
"""
Chooses mac address, ip address and vncport for a vm to be installed
"""
_choose_mac_ip(vm_properties)
start_range = int(get_constant('vncport_start_range'))
end_range = int(get_constant('vncport_end_range'))
vnc_ports_taken = current.db().select(current.db.vm_data.vnc_port)
while True:
random_vnc_port = random.randrange(start_range, end_range, 1)
if not random_vnc_port in vnc_ports_taken:
break;
vm_properties['vnc_port'] = str(random_vnc_port)
def find_new_host(RAM, vCPU):
"""
Select a random host from list of 3 hosts with available RAM and CPU
Availability is checked with 200 percent over-commitment.
"""
hosts = current.db(current.db.host.status == 1).select()
hosts = hosts.as_list(True,False)
count = 3
selected_hosts = []
while count != 0 and hosts:
host = random.choice(hosts)
logger.debug("Checking host =" + host['host_name'])
(used_ram, used_cpu) = host_resources_used(host['id'])
logger.debug("used ram: " + str(used_ram) + " used cpu: " + str(used_cpu) + " host ram: " + str(host['RAM']) + " host cpu "+ str(host['CPUs']))
host_ram_after_200_percent_overcommitment = math.floor((host['RAM'] * 1024) * 2)
host_cpu_after_200_percent_overcommitment = math.floor(host['CPUs'] * 2)
logger.debug("ram available: %s cpu available: %s cpu < max cpu: %s" % ((( host_ram_after_200_percent_overcommitment - used_ram) >= RAM), ((host_cpu_after_200_percent_overcommitment - used_cpu) >= vCPU), (vCPU <= host['CPUs']) ))
if((( host_ram_after_200_percent_overcommitment - used_ram) >= RAM) and ((host_cpu_after_200_percent_overcommitment - used_cpu) >= vCPU) and (vCPU <= host['CPUs'])):
selected_hosts.append(host)
count = count -1
hosts.remove(host)
if selected_hosts:
#Sort selected host list by Ram first then Cpu
selected_host = sorted(selected_hosts,key=lambda k: k['RAM'])[0]
return selected_host['id']
#If no suitable host found
raise Exception("No active host is available for a new vm.")
def allocate_vm_properties(vm_details):
"""
Allocates vm properties ( datastore, host, ip address, mac address, vnc port, ram, vcpus)
"""
logger.debug("Inside allocate_vm_properties()...")
vm_properties = {}
vm_properties['datastore'] = _choose_datastore()
logger.debug("Datastore selected is: " + str(vm_properties['datastore']))
vm_properties['host'] = find_new_host(vm_details.RAM, vm_details.vCPU)
logger.debug("Host selected is: " + str(vm_properties['host']))
vm_properties['public_ip_req'] = False if (vm_details.public_ip == None) else True
vm_properties['security_domain'] = vm_details.security_domain
_choose_mac_ip_vncport(vm_properties)
logger.debug("MAC is : " + str(vm_properties['mac_addr']) + " IP is : " + str(vm_properties['private_ip']) + " VNCPORT is : " \
+ str(vm_properties['vnc_port']) + " Vlan tag is " + str(vm_properties['vlan_tag']) )
vm_properties['ram'] = vm_details.RAM
vm_properties['vcpus'] = vm_details.vCPU
return vm_properties
def create_vm_image(vm_details, datastore):
"""
Create a VM image
- Creates a directory for the new VM using vm_identity
- Find the location of template image requested for
- Copy the template image from its location to new vm directory
"""
# Creates a directory for the new vm
vm_directory_path = datastore.system_mount_point + '/' + get_constant('vms') + '/' + vm_details.vm_identity
logger.debug("Creating vm directory...")
if not os.path.exists (vm_directory_path):
os.makedirs(vm_directory_path)
else:
raise Exception("Directory with same name as vmname already exists.")
# Finds the location of template image that the user has requested for its vm.
template = current.db.template[vm_details.template_id]
vm_image_name = vm_directory_path + '/' + vm_details.vm_identity + '.qcow2'
# Copies the template image from its location to new vm directory
storage_type = config.get("GENERAL_CONF","storage_type")
copy_command = 'ndmpcopy ' if storage_type == current.STORAGE_NETAPP_NFS else 'cp '
#template_dir = get_constant('vm_templates_datastore')
if copy_command == 'cp ':
template_location = datastore.system_mount_point + '/' + get_constant('templates_dir') + '/' + template.hdfile
logger.debug("cp %s %s" % (template_location, vm_image_name))
rc = os.system("cp %s %s" % (template_location, vm_image_name))
if rc != 0:
logger.error("Copy not successful")
raise Exception("Copy not successful")
else:
logger.debug("Copied successfully")
elif copy_command == 'ndmpcopy ':
template_dir = template.datastore_id.path
logger.debug(template_dir)
logger.debug("Copy in progress when storage type is " + str(storage_type))
command_to_execute = copy_command + template_dir + '/' + get_constant("templates_dir") + '/' + \
template.hdfile + ' ' + datastore.path + '/' + get_constant('vms') + '/' + \
vm_details.vm_identity
logger.debug("ndmpcopy command: " + str(command_to_execute))
command_output = execute_remote_cmd(datastore.ds_ip, datastore.username, command_to_execute, datastore.password)
logger.debug(command_output)
logger.debug("Copied successfully.")
try:
vm_template_name = datastore.system_mount_point + '/' + get_constant('vms') + '/' + vm_details.vm_identity + '/' + template.hdfile
os.rename(vm_template_name, vm_image_name)
logger.debug("Template renamed successfully")
except:
logger.debug("Template rename not successful")
raise Exception("Template rename not successful")
return (template, vm_image_name)
def _get_install_command(vm_details, vm_image_location, vm_properties):
"""
Generates install command for vm
"""
template = vm_properties['template']
bus = ',bus=virtio'
optional = ' --import --os-type=' + template.os
model = ',model=virtio'
if (template.arch != 'amd64' and template.os == 'Linux'):
optional = optional + ' --arch=' + template.arch + ' '
format_command = ''
if (template.type == 'QCOW2'):
format_command = ',format=qcow2'
if (template.os == 'Windows'):
bus = ''
model = ''
install_command = 'virt-install \
--name=' + vm_details.vm_identity + ' \
--ram=' + str(vm_properties['ram']) + ' \
--vcpus=' + str(vm_properties['vcpus']) + optional + ' \
--disk path=' + vm_image_location + format_command + bus + ',cache=none' + ' \
--network network='+current.LIBVIRT_NETWORK + model + ',mac=' + vm_properties['mac_addr'] + ' \
--graphics vnc,port=' + vm_properties['vnc_port'] + ',listen=0.0.0.0,password=duolc \
--noautoconsole \
--autostart \
--force'
return install_command
def _generate_disk_xml(diskpath,target_disk):
"""
Generates xml for defining new disk
"""
root_element = etree.Element('disk',attrib = {'type':'block','device':'disk'})
etree.SubElement(root_element, 'driver',attrib = {'name':'qemu','cache':'none', 'type':'qcow2'})
etree.SubElement(root_element, 'source', attrib = {'dev':diskpath})
etree.SubElement(root_element, 'target', attrib = {'dev': target_disk})
return (etree.tostring(root_element))
def create_extra_disk_image(vm_details, disk_name, size, datastore):
"""
Create extra disk image
"""
vm_extra_disks_directory_path = datastore.system_mount_point + '/' + get_constant('extra_disks_dir') + '/' + \
datastore.ds_name + '/' + vm_details.vm_identity
if not os.path.exists (vm_extra_disks_directory_path):
logger.debug("Making Directory")
os.makedirs(vm_extra_disks_directory_path)
diskpath = vm_extra_disks_directory_path + '/' + disk_name
command= "qemu-img create -f qcow2 "+ diskpath + " " + str(size) + "G"
output = os.system(command)
return False if output != 0 else True
def attach_disk(vm_details, disk_name, hostip, already_attached_disks, new_vm):
"""
Attach given disk to the VM
"""
try:
(connection_object, domain) = getVirshDomainConn(None, hostip, vm_details.vm_identity)
#already_attached_disks = len(current.db(current.db.attached_disks.vm_id == vm.id).select())
logger.debug("Value of alreadyattached is : " + str(already_attached_disks))
(diskpath, device_present, disk_size) = get_extra_disk_location(vm_details.datastore_id, vm_details.vm_identity, disk_name, True)
if not device_present:
raise Exception("Device to be attached %s missing" %(diskpath))
# Attaching disk to vm using libvirt API
target_disk = "vd" + chr(97 + already_attached_disks + 1)
logger.debug(target_disk)
logger.debug("...................")
xmlDescription = _generate_disk_xml(diskpath, target_disk)
logger.debug(xmlDescription)
logger.debug("new vm is %s " % new_vm)
if new_vm:
logger.debug("Starting to attach disk on new vm request.")
domain.destroy()
logger.debug("VM destroyed")
domain.attachDeviceFlags(xmlDescription, VIR_DOMAIN_AFFECT_CONFIG)
logger.debug("Disk attached")
logger.debug("Turn on vm")
domain.create()
logger.debug("VM started")
domain.isActive()
elif vm_details.status == current.VM_STATUS_SHUTDOWN:
logger.debug("Starting to attach disk while vm is shutdown.")
domain.attachDeviceFlags(xmlDescription, VIR_DOMAIN_AFFECT_CONFIG)
logger.debug("Disk attached")
else:
raise Exception("VM is not in shutdown state. Check its status on host")
xmlfile = domain.XMLDesc(0)
domain = connection_object.defineXML(xmlfile)
logger.debug("VM XML redefined")
connection_object.close()
return disk_size
except:
logger.exception('Exception: ')
return 0
def serve_extra_disk_request(vm_details, disk_size, host_ip, new_vm = False):
"""
Serves extra disk request and updates db
"""
logger.debug("Starting to serve extra disk request...")
logger.debug("new vm is %s " % new_vm)
datastore = _choose_datastore()
already_attached_disks = len(current.db(current.db.attached_disks.vm_id == vm_details.id).select())
disk_name = vm_details.vm_identity + "_disk" + str(already_attached_disks + 1) + ".qcow2"
disk_created = create_extra_disk_image(vm_details, disk_name, disk_size, datastore)
vm_details.datastore_id = datastore.id
if disk_created:
if (attach_disk(vm_details, disk_name, host_ip, already_attached_disks, new_vm)):
current.db.attached_disks.insert(vm_id = vm_details.id, datastore_id = datastore.id , attached_disk_name = disk_name, capacity = disk_size)
current.db(current.db.datastore.id == datastore.id).update(used = int(datastore.used) + int(disk_size))
return True
return False
def launch_vm_on_host(vm_details, vm_image_location, vm_properties):
"""
Launches a vm image on host
"""
attach_disk_status_message = ''
install_command = _get_install_command(vm_details, vm_image_location, vm_properties)
# Starts installing a vm
host_ip = current.db.host[vm_properties['host']].host_ip.private_ip
logger.debug("Installation started...")
logger.debug("Host is "+ host_ip)
logger.debug("Installation command : " + install_command)
command_output = execute_remote_cmd(host_ip, 'root', install_command)
logger.debug(command_output)
logger.debug("Starting to set portgroup in vm...")
_set_portgroup_in_vm(vm_details['vm_identity'], vm_properties['vlan_name'], host_ip, vm_properties['vlan_tag'])
logger.debug("Portgroup set in vm")
# Serving HDD request
if (int(vm_details.extra_HDD) != 0):
if (serve_extra_disk_request(vm_details, vm_details.extra_HDD, host_ip, new_vm = True)):
message = "Attached extra disk successfully."
attach_disk_status_message += message
logger.debug(message)
else:
attach_disk_status_message += "Attached extra disk failed."
return attach_disk_status_message
def check_if_vm_defined(hostip, vmname):
"""
Checks if a newly created vm is successfully defined
"""
vm_defined = False
try:
connection_object = libvirt.openReadOnly('qemu+ssh://root@'+ hostip +'/system')
domain = connection_object.lookupByName(vmname)
if domain.ID() in connection_object.listDomainsID():
vm_defined = True
connection_object.close()
return vm_defined
except:
return False
def _free_vm_properties(vm_details, vm_properties):
"""
Frees vm properties in-case installation has failed mid-way
"""
logger.debug("VM installation fails..Starting to free vm properties")
if vm_properties:
host_ip_of_vm = current.db.host[vm_properties['host']].host_ip.private_ip
logger.debug("Host IP of vm is " + str(host_ip_of_vm))
if check_if_vm_defined(host_ip_of_vm, vm_details.vm_identity):
connection_object = libvirt.open('qemu+ssh://root@'+ host_ip_of_vm +'/system')
domain = connection_object.lookupByName(vm_details.vm_identity)
logger.debug("Starting to delete vm from host..")
domain.destroy()
domain.undefine()
connection_object.close()
logger.debug("VM deleted.")
current.db(current.db.attached_disks.vm_id == vm_details.id).delete()
if 'datastore' in vm_properties:
vm_directory_path = vm_properties['datastore'].system_mount_point + '/' + get_constant('vms') + '/' + vm_details.vm_identity
vm_extra_disk_dir_path = vm_properties['datastore'].system_mount_point + '/' + get_constant('extra_disks_dir') + '/' + vm_properties['datastore'].ds_name + '/' + vm_details.vm_identity
if os.path.exists (vm_directory_path):
logger.debug("Starting to delete vm directory.")
shutil.rmtree(vm_directory_path)
if os.path.exists (vm_extra_disk_dir_path):
logger.debug("Starting to delete vm extra disk directory.")
shutil.rmtree(vm_extra_disk_dir_path)
return
def update_db_after_vm_installation(vm_details, vm_properties, parent_id = None):
"""
Updates db after a vm is installed successfully
"""
logger.debug("Starting to update db after vm installation..")
hostid = vm_properties['host']
datastore = vm_properties['datastore']
template_hdd = vm_properties['template'].hdd
logger.debug("Inside update db after installation")
logger.debug(vm_properties)
# Updating the used entry of datastore
current.db(current.db.datastore.id == datastore.id).update(used = int(datastore.used) + int(vm_details.extra_HDD) +
int(template_hdd))
private_ip_id = current.db.private_ip_pool(private_ip=vm_properties['private_ip']).id
public_ip_id = None
if vm_properties['public_ip'] != None:
public_ip_id = current.db.public_ip_pool(public_ip=vm_properties['public_ip']).id
if parent_id:
vm_status = current.VM_STATUS_SHUTDOWN
else:
vm_status = current.VM_STATUS_RUNNING
# Update vm_data table
current.db(current.db.vm_data.id == vm_details.id).update( host_id = hostid,
extra_HDD = vm_details.extra_HDD,
datastore_id = datastore.id,
vnc_port = vm_properties['vnc_port'],
private_ip = private_ip_id,
public_ip = public_ip_id,
start_time = get_datetime(),
parent_id = parent_id,
status = vm_status)
logger.debug("Updated db")
return
def create_object_store(parameters,object_data):
try:
logger.debug("In create_object_store() function...")
object_name=object_data['object_store_name']
size_limit=object_data['object_store_size']
sh_path = os.path.join(get_context_path(), 'private/object_storage.sh')
command = 'sh %s %s %s' %(sh_path, object_name, str(size_limit))
logger.debug("command :%s" %command)
file_name= object_data['object_store_name'] + "_key.txt"
file_path = os.path.join(get_context_path(), 'private/Object_keys/' + file_name)
cp = os.open(file_path,os.O_RDWR|os.O_CREAT)
co = os.fdopen(cp,"rw+")
fd = os.open('/home/key.txt',os.O_RDWR|os.O_CREAT)
fo = os.fdopen(fd,"r+")
key_s3_secret= fo.readline();
co.write(key_s3_secret);
key_s3_access= fo.readline();
co.write(key_s3_access);
key_swift_secret= fo.readline();
co.write(key_swift_secret);
swift_user= 'Swift_user: ' + object_name + ':swift'
co.write(swift_user)
co.close()
a,b,key_swift_secret= key_swift_secret.partition(' ') # @UnusedVariable
a,b,key_s3_secret= key_s3_secret.partition(' ') # @UnusedVariable
a,b,key_s3_access= key_s3_access.partition(' ') # @UnusedVariable
#print key_s3_secret, key_s3_access , key_swift_secret
object_data.update_record(swift_access_key= key_swift_secret.strip() , s3_secret_key= key_s3_secret.strip(), s3_access_key= key_s3_access.strip(), status=3)
fo.close()
message = "Object Store is created successfully."
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
# Installs a vm
def install(parameters):
"""
Installs a vm
"""
vmid = parameters['vm_id']
logger.debug("In install() function...")
vm_details = current.db.vm_data[vmid]
vm_properties = None
try:
# Fetches vm details from vm_data table
logger.debug("VM details are: " + str(vm_details))
# Calling allocate_vm_properties function
vm_properties = allocate_vm_properties(vm_details)
# Calling create_vm_image function
(vm_properties['template'], vm_image_location) = create_vm_image(vm_details, vm_properties['datastore'])
# Calling launch_vm_on_host
attach_disk_status_message = launch_vm_on_host(vm_details, vm_image_location, vm_properties)
# Checking if vm has been installed successfully
assert(check_if_vm_defined(current.db.host[vm_properties['host']].host_ip.private_ip, vm_details.vm_identity)), "VM is not installed. Check logs."
if vm_properties['public_ip_req']:
create_mapping(vm_properties['public_ip'], vm_properties['private_ip'])
# Update database after vm installation
update_db_after_vm_installation(vm_details, vm_properties)
message = "VM is installed successfully." + attach_disk_status_message
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
if vm_properties != None:
_free_vm_properties(vm_details, vm_properties)
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def start(parameters):
"""
Starts a vm
"""
logger.debug("Inside start() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
try:
domain = getVirshDomain(vm_details)
if domain.info()[0] == VIR_DOMAIN_RUNNING:
raise Exception("VM is already running. Check vm status on host.")
domain.create()
current.db(current.db.vm_data.id == vm_id).update(status = current.VM_STATUS_RUNNING)
message = vm_details.vm_identity + " is started successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def suspend(parameters):
"""
Suspends a vm
"""
logger.debug("Inside suspend() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
try:
domain = getVirshDomain(vm_details)
if domain.info()[0] == VIR_DOMAIN_PAUSED:
raise Exception("VM is already paused. Check vm status on host.")
domain.suspend()
current.db(current.db.vm_data.id == vm_id).update(status = current.VM_STATUS_SUSPENDED)
message = vm_details.vm_identity + " is suspended successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def resume(parameters):
"""
Resumes a vm
"""
logger.debug("Inside resume() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
try:
domain = getVirshDomain(vm_details)
if domain.info()[0] == VIR_DOMAIN_RUNNING:
raise Exception("VM is already running. Check vm status on host.")
domain.resume()
current.db(current.db.vm_data.id == vm_id).update(status = current.VM_STATUS_RUNNING)
message = vm_details.vm_identity + " is resumed successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def destroy(parameters):
"""
Destroys a vm forcefully
"""
logger.debug("Inside destroy() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
logger.debug(str(vm_details))
try:
domain = getVirshDomain(vm_details)
if domain.info()[0] == VIR_DOMAIN_SHUTOFF:
raise Exception("VM is already shutoff. Check vm status on host.")
domain.destroy()
current.db(current.db.vm_data.id == vm_id).update(status = current.VM_STATUS_SHUTDOWN)
message = vm_details.vm_identity + " is destroyed successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def shutdown(parameters):
"""
Destroys a vm gracefully
"""
logger.debug("Inside shutdown() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
logger.debug(str(vm_details))
try:
domain = getVirshDomain(vm_details)
if domain.info()[0] == VIR_DOMAIN_SHUTOFF:
raise Exception("VM is already shutoff. Check vm status on host.")
domain.managedSave()
current.db(current.db.vm_data.id == vm_id).update(status = current.VM_STATUS_SHUTDOWN)
message = vm_details.vm_identity + " is shutdown successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def _clean_up_database_after_vm_deletion(vm_details):
"""
Cleans up database after vm deletion
"""
logger.debug("Inside clean up database after vm deletion () function...")
# moving vm image folder to archives folder
archive_directory_path = vm_details.datastore_id.system_mount_point + '/' + get_constant('archives_dir')
if not os.path.exists(archive_directory_path):
os.makedirs(archive_directory_path)
source_file = vm_details.datastore_id.system_mount_point + '/' + get_constant('vms') + '/' + vm_details.vm_identity
archive_filename = vm_details.vm_identity + str(get_datetime())
logger.debug(archive_filename)
destination_file = archive_directory_path + '/' + archive_filename
shutil.move(source_file, destination_file)
# removing hdd
vm_extra_disks_directory_path = vm_details.datastore_id.system_mount_point + '/' + get_constant('extra_disks_dir') + '/' + \
vm_details.datastore_id.ds_name + "/" + vm_details.vm_identity
if os.path.exists(vm_extra_disks_directory_path):
shutil.rmtree(vm_extra_disks_directory_path)
# updating the used entry of database
current.db(current.db.datastore.id == vm_details.datastore_id).update(used = int(vm_details.datastore_id.used) - \
(int(vm_details.extra_HDD) + int(vm_details.template_id.hdd)))
# updating task_queue_event entry to remove reference of VM
current.db(current.db.task_queue_event.vm_id == vm_details.id).update(vm_id = None)
# deleting entry of extra disk of vm
current.db(current.db.attached_disks.vm_id == vm_details.id).delete()
logger.debug("Database cleaned")
def vm_has_snapshots(vm_id):
"""
Checks if a vm has snapshot(s)
"""
if (current.db(current.db.snapshot.vm_id == vm_id).select()):
return True
else:
return False
def delete(parameters):
"""
Deletes a vm
"""
logger.debug("Inside delete() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
try:
domain = getVirshDomain(vm_details)
logger.debug(str(vm_details.status))
if (vm_details.status == current.VM_STATUS_RUNNING or vm_details.status == current.VM_STATUS_SUSPENDED):
logger.debug("Vm is not shutoff. Shutting it off first.")
domain.destroy()
logger.debug("Starting to delete it...")
domain.undefineFlags(VIR_DOMAIN_UNDEFINE_SNAPSHOTS_METADATA )
if vm_details.public_ip:
remove_mapping(vm_details.public_ip.public_ip, vm_details.private_ip.private_ip)
message = vm_details.vm_identity + " is deleted successfully."
logger.debug(message)
_clean_up_database_after_vm_deletion(vm_details)
current.db(current.db.vm_data.id == vm_id).delete()
current.db.commit()
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def migrate_domain_with_snapshots(vm_details, destination_host_ip, domain, domain_snapshots_list, current_snapshot_name, flags, vm_backup_during_migration):
"""
Migrate domain with snapshots
"""
# XML dump of snapshot(s) of the vm
logger.debug("Starting to take xml dump of the snapshot(s) of the vm... ")
if not os.path.exists(vm_backup_during_migration):
os.makedirs(vm_backup_during_migration)
for domain_snapshot in domain_snapshots_list:
logger.debug("snapshot name is " + str(domain_snapshot))
dump_xml_path = vm_backup_during_migration + '/' + 'dump_' + domain_snapshot
snapshot_dumpxml_command = 'virsh snapshot-dumpxml %s %s > %s' % ( vm_details.vm_identity, domain_snapshot, dump_xml_path)
logger.debug("Taking xml dump of" + str(domain_snapshot))
command_output = execute_remote_cmd(vm_details.host_id.host_ip.private_ip, 'root', snapshot_dumpxml_command)
logger.debug(command_output)
logger.debug("XML dump of " + str(domain_snapshot) + "succeeded.")
# Delete snapshot(s) of the vm and migrate it to destination host
logger.debug("Starting to delete snapshots of the vm....")
for domain_snapshot in domain_snapshots_list:
snapshot = domain.snapshotLookupByName(domain_snapshot, 0)
snapshot.delete(0)
logger.debug("Migrating the vm to destination host...")
domain.migrateToURI("qemu+ssh://root@" + destination_host_ip + "/system", flags , None, 0)
# Redefine all the snapshot(s) of the vm on the destination host and set current snapshot
logger.debug("Starting to redefine all the snapshot(s) of the domain...")
for domain_snapshot in domain_snapshots_list:
redefine_xml_path = vm_backup_during_migration + '/' + 'dump_' + domain_snapshot
snapshot_redefine_command = 'virsh snapshot-create --redefine %s %s ' % (vm_details.vm_identity, redefine_xml_path)
command_output = execute_remote_cmd(destination_host_ip, 'root', snapshot_redefine_command)
logger.debug(command_output)
snapshot_current_command = 'virsh snapshot-current %s %s' % (vm_details.vm_identity, current_snapshot_name)
command_output = execute_remote_cmd(destination_host_ip, 'root', snapshot_current_command)
logger.debug(command_output)
return
def _clean_migration_directory(vm_backup_during_migration):
"""
Delete directory created for storing dumpxml of vm snapshots
"""
if os.path.exists(vm_backup_during_migration):
shutil.rmtree(vm_backup_during_migration)
return
def undo_migration(vm_details, domain_snapshots_list, current_snapshot_name, vm_backup_during_migration):
"""
Undo the migration
"""
if domain_snapshots_list:
# Redefine the snapshots of the vm on the source host
logger.debug("Starting to redefine all the snapshot(s) of the vm on the source host...")
for domain_snapshot in domain_snapshots_list:
redefine_xml_path = vm_backup_during_migration + '/' + 'dump_' + domain_snapshot
snapshot_redefine_command = 'virsh snapshot-create --redefine %s %s ' % (vm_details.vm_identity, redefine_xml_path)
command_output = execute_remote_cmd(vm_details.host_id.host_ip.private_ip, 'root', snapshot_redefine_command, None, True)
logger.debug(command_output)
snapshot_current_command = 'virsh snapshot-current %s %s' % (vm_details.vm_identity, current_snapshot_name)
command_output = execute_remote_cmd(vm_details.host_id.host_ip.private_ip, 'root', snapshot_current_command, None, True)
logger.debug(command_output)
# Delete directory created for storing dumpxml of vm snapshots
_clean_migration_directory(vm_backup_during_migration)
return
def migrate_domain(vm_id, destination_host_id=None, live_migration=False):
"""
Migrate domain
"""
vm_details = current.db.vm_data[vm_id]
domain_snapshots_list = []
current_snapshot_name = ''
vm_migration_directory = get_constant('vm_migration_data')
vm_backup_during_migration = vm_details.datastore_id.system_mount_point + '/' + vm_migration_directory + '/' + \
vm_details.vm_identity
if destination_host_id == None:
destination_host_id = find_new_host(vm_details.RAM, vm_details.vCPU)
destination_host_ip = current.db.host[destination_host_id].host_ip.private_ip
flags = VIR_MIGRATE_PEER2PEER|VIR_MIGRATE_PERSIST_DEST|VIR_MIGRATE_UNDEFINE_SOURCE|VIR_MIGRATE_UNSAFE
if live_migration:
flags |= VIR_MIGRATE_TUNNELLED|VIR_MIGRATE_LIVE
if vm_details.status == current.VM_STATUS_SUSPENDED:
logger.debug("Vm is suspended")
flags |= VIR_MIGRATE_TUNNELLED|VIR_MIGRATE_PAUSED
elif vm_details.status == current.VM_STATUS_SHUTDOWN:
logger.debug("Vm is shut off")
flags |= VIR_MIGRATE_OFFLINE
logger.debug("Flags: " + str(flags))
try:
domain = getVirshDomain(vm_details)
dom_snapshot_names = domain.snapshotListNames(0)
for snapshot in current.db(current.db.snapshot.vm_id == vm_id).select():
logger.debug("snapshot:" + str(snapshot.snapshot_name))
domain_snapshots_list.append(snapshot.snapshot_name)
dom_snapshot_names.remove(snapshot.snapshot_name)
logger.debug("domain snapshot list is " + str(domain_snapshots_list))
for dom_snapshot in dom_snapshot_names:
logger.debug("Deleting orphan snapshot %s" %(dom_snapshot))
snapshot = domain.snapshotLookupByName(dom_snapshot, 0)
snapshot.delete(0)
if domain_snapshots_list:
current_snapshot = domain.snapshotCurrent(0)
current_snapshot_name = current_snapshot.getName()
migrate_domain_with_snapshots(vm_details, destination_host_ip, domain, domain_snapshots_list, current_snapshot_name, flags, vm_backup_during_migration)
else:
domain.migrateToURI("qemu+ssh://root@" + destination_host_ip + "/system", flags , None, 0)
vm_details.update_record(host_id = destination_host_id)
current.db.commit()
# Delete directory created for storing dumpxml of vm snapshot
_clean_migration_directory(vm_backup_during_migration)
message = vm_details.vm_identity + " is migrated successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
undo_migration(vm_details, domain_snapshots_list, current_snapshot_name, vm_backup_during_migration)
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def migrate_domain_datastore(vmid, destination_datastore_id, live_migration=False):
"""
Migrate VM domain from one datastore to another.
- Copy VM Image to new datastore
- Update VM XML definition
- Update database
"""
logger.debug(sys.path)
vm_details = current.db.vm_data[vmid]
# datastore_id = vm_details["datastore_id"]
logger.debug("Inside live disk migration block")
try:
(connection_object, domain) = getVirshDomainConn(vm_details)
datastore = current.db.datastore[destination_datastore_id]
vm_directory_path = datastore.system_mount_point + get_constant('vms') + '/' + vm_details.vm_identity
logger.debug("Creating vm directory on other datastore...")
if not os.path.exists (vm_directory_path):
os.makedirs(vm_directory_path)
diskpath = vm_directory_path + '/' + vm_details.vm_identity + '.qcow2'
current_disk_path = vm_details.datastore_id.system_mount_point + get_constant('vms') + '/' + vm_details.vm_identity
current_disk_file = current_disk_path + '/' + vm_details.vm_identity + '.qcow2'
logger.debug(current_disk_file)
xmlfile = domain.XMLDesc(0)
if(live_migration==False):
rc = os.system("cp %s %s" % (current_disk_file, diskpath))
if rc != 0:
logger.error("Copy not successful")
raise Exception("Copy not successful")
else:
logger.debug("Copied successfully")
else:
if domain.isActive:
domain.undefine()
root = etree.fromstring(xmlfile)
target_elem = root.find("devices/disk/target")
target_disk = target_elem.get('dev')
#
# destxml = generate_blockcopy_xml(diskpath,target_disk)
flag = VIR_DOMAIN_BLOCK_REBASE_SHALLOW | VIR_DOMAIN_BLOCK_REBASE_COPY
domain.blockRebase(target_disk, diskpath, 0, flag)
block_info_list = domain.blockJobInfo(current_disk_file,0)
while(block_info_list['end'] != block_info_list['cur']):
logger.debug("time to sleep")
time.sleep(60)
block_info_list = domain.blockJobInfo(current_disk_file,0)
domain.blockJobAbort(current_disk_file, VIR_DOMAIN_BLOCK_JOB_ABORT_PIVOT)
source_elem = root.find("devices/disk/source")
source_elem.set('file',diskpath)
newxml_file = etree.tostring(root)
domain = connection_object.defineXML(newxml_file)
vm_details.update_record(datastore_id=destination_datastore_id)
if os.path.exists (diskpath):
os.remove(current_disk_file)
restore_symboltable_path = current_disk_path+"/restore_symboltable"
if os.path.exists (restore_symboltable_path):
logger.debug(restore_symboltable_path)
os.remove(restore_symboltable_path)
os.rmdir(current_disk_path)
connection_object.close()
message = vm_details.vm_identity + " is migrated successfully to new datastore."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
#undo_datastore_migration(vm_details, domain, diskpath, current_disk_file, vm_directory_path, datastore_id)
connection_object.close()
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def undo_datastore_migration(vm_details, domain, diskpath, current_disk_file, vm_directory_path, datastore_id):
"""
Undo migration in case of any issue
"""
# undo databse changes
vm_details.update_record(datastore_id=datastore_id)
if domain.isActive:
logger.debug("domain is active")
block_info_list = domain.blockJobInfo(current_disk_file,0)
if(bool(block_info_list) == True):
while(block_info_list['end'] != block_info_list['cur']):
logger.debug("time to sleep")
time.sleep(60)
block_info_list = domain.blockJobInfo(current_disk_file,0)
if(block_info_list['end'] == block_info_list['cur']):
domain.blockJobAbort(current_disk_file)
block_info_list = domain.blockJobInfo(current_disk_file,0)
if os.path.exists (diskpath):
os.remove(diskpath)
os.rmdir(vm_directory_path)
def migrate(parameters):
"""
Migrates VM to new host
"""
vmid = parameters['vm_id']
logger.debug("Inside migrate() function for vm_id: "+str(vmid))
destination_host_id = parameters['destination_host']
if parameters['live_migration'] == 'on':
live_migration = True
else:
live_migration = False
return migrate_domain(vmid, destination_host_id, live_migration)
def migrate_datastore(parameters):
"""
Migrates VM to new datastore
"""
logger.debug("Inside migrate_datastore() function")
vmid = parameters['vm_id']
destination_ds_id = parameters['destination_ds']
if parameters['live_migration'] == 'on':
live_migration = True
else:
live_migration = False
return migrate_domain_datastore(vmid, destination_ds_id, live_migration)
def snapshot(parameters):
"""
Snapshots a vm
"""
logger.debug("Inside snapshot() function")
vm_id = parameters['vm_id']
snapshot_type = parameters['snapshot_type']
try:
vm_details = current.db.vm_data[vm_id]
if is_pingable(str(vm_details.private_ip.private_ip)):
logger.debug("VM is pingable. Starting to start with snapshotting...")
if snapshot_type != current.SNAPSHOT_USER:
snapshots = current.db((current.db.snapshot.vm_id == vm_id) & (current.db.snapshot.type == snapshot_type)).select()
#Delete the existing Daily/Monthly/Yearly snapshot
for snapshot_cron in snapshots:
logger.debug(snapshot_cron)
delete_snapshot({'vm_id':vm_id, 'snapshot_id':snapshot_cron.id})
snapshot_name = get_datetime().strftime("%I:%M%p_%B%d,%Y")
domain = getVirshDomain(vm_details)
xmlDesc = "<domainsnapshot><name>%s</name></domainsnapshot>" % (snapshot_name)
domain.snapshotCreateXML(xmlDesc, 0)
message = "Snapshotted successfully."
current.db.snapshot.insert(vm_id = vm_id, datastore_id = vm_details.datastore_id, snapshot_name = snapshot_name, type = snapshot_type)
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
else:
message = "Unable to ping VM before snapshoting: %s" % (vm_details.private_ip.private_ip)
raise Exception("Unable to ping VM before snapshoting: %s" % (vm_details.private_ip.private_ip))
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def revert(parameters):
"""
Reverts to snapshot
"""
logger.debug("Inside revert snapshot() function")
vm_id = parameters['vm_id']
snapshotid = parameters['snapshot_id']
vm_details = current.db.vm_data[vm_id]
try:
domain = getVirshDomain(vm_details)
snapshot_name = current.db(current.db.snapshot.id == snapshotid).select().first()['snapshot_name']
snapshot = domain.snapshotLookupByName(snapshot_name, 0)
domain.revertToSnapshot(snapshot, 0)
message = "Reverted to snapshot successfully."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def delete_snapshot(parameters):
"""
Deletes a snapshot
"""
logger.debug("Inside delete snapshot() function")
vm_id = parameters['vm_id']
snapshotid = parameters['snapshot_id']
vm_details = current.db.vm_data[vm_id]
logger.debug(str(vm_details))
try:
domain = getVirshDomain(vm_details)
snapshot_name = current.db(current.db.snapshot.id == snapshotid).select().first()['snapshot_name']
snapshot = None
try:
snapshot = domain.snapshotLookupByName(snapshot_name, 0)
except libvirtError:
logger.debug("Snapshot %s not found" %(snapshot_name))
if snapshot != None:
snapshot.delete(0)
message = "Deleted snapshot successfully."
logger.debug(message)
current.db(current.db.snapshot.id == snapshotid).delete()
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def update_security_domain(vm_details, security_domain_id, xmlDesc=None):
"""
Get new IP for given security domain.
Update the VM XML with new mac_address and update the information in DB
"""
# fetch new private IP from db from given security domain
private_ip_info = _get_private_ip_mac(security_domain_id)
# update vm config to add new mac address.
root = etree.fromstring(xmlDesc)
mac_elem = root.find("devices/interface[@type='bridge']/mac")
mac_elem.set('address', private_ip_info.mac_addr)
vlan_tag_elem = root.find("devices/interface[@type='bridge']/vlan/tag")
vlan_tag_elem.set('id', private_ip_info.vlan.vlan_tag)
# update NAT IP mapping, if public IP present
if vm_details.public_ip:
remove_mapping(vm_details.public_ip.public_ip, vm_details.private_ip.private_ip)
create_mapping(vm_details.public_ip.public_ip, private_ip_info.private_ip)
# update vm_data
current.db(current.db.vm_data.id == vm_details.id).update(security_domain = security_domain_id,
private_ip = private_ip_info.id)
return etree.tostring(root)
def edit_vm_config(parameters):
"""
Edits vm configuration
"""
logger.debug("Inside edit vm config() function")
vm_id = parameters['vm_id']
vm_details = current.db.vm_data[vm_id]
message = ""
try:
connection_object, domain = getVirshDomainConn(vm_details)
if 'vcpus' in parameters:
new_vcpus = int(parameters['vcpus'])
domain.setVcpusFlags(new_vcpus, VIR_DOMAIN_VCPU_MAXIMUM)
domain.setVcpusFlags(new_vcpus, VIR_DOMAIN_AFFECT_CONFIG)
message += "Edited vCPU successfully."
current.db(current.db.vm_data.id == vm_id).update(vCPU = new_vcpus)
if 'ram' in parameters:
new_ram = int(parameters['ram']) * 1024
logger.debug(str(new_ram))
domain.setMemoryFlags(new_ram, VIR_DOMAIN_MEM_MAXIMUM)
domain.setMemoryFlags(new_ram, VIR_DOMAIN_AFFECT_CONFIG)
message += " And edited RAM successfully."
current.db(current.db.vm_data.id == vm_id).update(RAM = int(parameters['ram']))
if 'public_ip' in parameters:
enable_public_ip = parameters['public_ip']
if enable_public_ip:
public_ip_pool = _choose_random_public_ip()
if public_ip_pool:
create_mapping(public_ip_pool.public_ip, vm_details.private_ip.private_ip)
current.db.vm_data[vm_id] = dict(public_ip=public_ip_pool.id)
message += "Edited Public IP successfully."
else:
raise Exception("Available Public IPs are exhausted.")
else:
remove_mapping(vm_details.public_ip.public_ip, vm_details.private_ip.private_ip)
current.db.vm_data[vm_id] = dict(public_ip = None)
if 'security_domain' in parameters:
logger.debug('Updating security domain')
xmlfile = update_security_domain(vm_details, parameters['security_domain'], domain.XMLDesc(0))
domain = connection_object.defineXML(xmlfile)
if domain.isActive():
domain.reboot(0)
message += "Edited security domain successfully"
connection_object.close()
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def _get_clone_properties(vm_details, cloned_vm_details, vm_properties):
"""
Get properties for Cloned VM.
"""
datastore = _choose_datastore()
vm_properties['datastore'] = datastore
logger.debug("Datastore selected is: " + str(datastore))
vm_properties['security_domain'] = vm_details.security_domain
vm_properties['public_ip_req'] = False
# Finds mac address, ip address and vnc port for the cloned vm
_choose_mac_ip_vncport(vm_properties)
logger.debug("MAC is : " + str(vm_properties['mac_addr']) + " IP is : " + str(vm_properties['private_ip']) + \
" VNCPORT is : " + str(vm_properties['vnc_port']))
# Template and host of parent vm
vm_properties['template'] = current.db(current.db.template.id == vm_details.template_id).select()[0]
vm_properties['vm_host_details'] = current.db.host[vm_details.host_id]
vm_properties['host'] = vm_properties['vm_host_details'].id
# Creates a directory for the cloned vm
logger.debug("Creating directory for cloned vm...")
cloned_vm_directory_path = datastore.system_mount_point + '/' + get_constant('vms') + '/' + cloned_vm_details.vm_identity
if not os.path.exists (cloned_vm_directory_path):
os.makedirs(cloned_vm_directory_path)
clone_file_parameters = ' --file ' + cloned_vm_directory_path + '/' + cloned_vm_details.vm_identity + '.qcow2'
else:
raise Exception("Directory with same name as vmname already exists.")
# Creates a folder for additional disks of the cloned vm
vm = current.db(current.db.vm_data.vm_identity == vm_details.vm_identity).select().first()
disk_details_of_cloning_vm = current.db(current.db.attached_disks.vm_id == vm.id).select(orderby=current.db.attached_disks.attached_disk_name)
logger.debug(disk_details_of_cloning_vm)
already_attached_disks = len(disk_details_of_cloning_vm)
cloned_vm_extra_disks_directory = datastore.system_mount_point + '/' + get_constant('extra_disks_dir') + '/' + \
datastore.ds_name + '/' + cloned_vm_details.vm_identity
if already_attached_disks > 0:
if not os.path.exists (cloned_vm_extra_disks_directory):
logger.debug("Making Directory")
os.makedirs(cloned_vm_extra_disks_directory)
count = already_attached_disks
while already_attached_disks > 0:
disk_name = cloned_vm_details.vm_identity + '_disk' + str(count - already_attached_disks + 1) + '.qcow2'
clone_file_parameters += ' --file ' + cloned_vm_extra_disks_directory + '/' + disk_name
current.db.attached_disks.insert(vm_id = cloned_vm_details.id,
datastore_id = datastore.id ,
attached_disk_name = disk_name,
capacity = disk_details_of_cloning_vm[count - already_attached_disks].capacity)
already_attached_disks -= 1
return (clone_file_parameters)
def migrate_clone_to_new_host(vm_details, cloned_vm_details, new_host_id_for_cloned_vm,vm_properties):
"""
Migrates cloned vm to new host
"""
try:
new_host_ip_for_cloned_vm = current.db.host[new_host_id_for_cloned_vm].host_ip.private_ip
logger.debug("New host ip for cloned vm is: " + str(new_host_ip_for_cloned_vm))
flags = VIR_MIGRATE_PEER2PEER|VIR_MIGRATE_PERSIST_DEST|VIR_MIGRATE_UNDEFINE_SOURCE|VIR_MIGRATE_OFFLINE|VIR_MIGRATE_UNSAFE
logger.debug("Clone currently on: " + str(vm_details.host_id.host_ip))
(current_host_connection_object, domain) = getVirshDomainConn(None, vm_details.host_id.host_ip, cloned_vm_details.vm_identity)
logger.debug("Starting to migrate cloned vm to host " + str(new_host_ip_for_cloned_vm))
domain.migrateToURI("qemu+ssh://root@" + new_host_ip_for_cloned_vm + "/system", flags , None, 0)
current_host_connection_object.close()
logger.debug("Successfully migrated cloned vm to host " + str(new_host_ip_for_cloned_vm))
cloned_vm_details.update_record(host_id = new_host_id_for_cloned_vm)
vm_properties['host'] = new_host_id_for_cloned_vm
return True
except libvirt.libvirtError,e:
message = e.get_error_message()
logger.debug("Error: " + message)
return False
def clone(vmid):
"""
Clones vm
"""
vm_properties = {}
logger.debug("Inside clone() function")
cloned_vm_details = current.db.vm_data[vmid]
vm_details = current.db(current.db.vm_data.id == cloned_vm_details.parent_id).select().first()
try:
domain = getVirshDomain(vm_details)
if domain.info()[0] != VIR_DOMAIN_SHUTOFF:
raise Exception("VM is not shutoff. Check vm status.")
clone_file_parameters = _get_clone_properties(vm_details, cloned_vm_details, vm_properties)
logger.debug("cloned vm properties after clone_file_parameters" + str(vm_properties))
host = vm_properties['vm_host_details']
logger.debug("host is: " + str(host))
logger.debug("host details are: " + str(host))
(used_ram, used_cpu) = host_resources_used(host.id)
logger.debug("uram: " + str(used_ram) + " used_cpu: " + str(used_cpu) + " host ram: " + str(host.RAM) +" host cpu: " + str(host.CPUs))
host_ram_after_200_percent_overcommitment = math.floor((host.RAM * 1024) * 2)
host_cpu_after_200_percent_overcommitment = math.floor(host.CPUs * 2)
logger.debug("host_ram_after_200_percent_overcommitment in MB " + str(host_ram_after_200_percent_overcommitment))
logger.debug("host_cpu_after_200_percent_overcommitment " + str(host_cpu_after_200_percent_overcommitment))
logger.debug("Available RAM on host: %s, Requested RAM: %s" % ((host_ram_after_200_percent_overcommitment - used_ram), vm_details.RAM))
logger.debug("Available CPUs on host: %s, Requested CPU: %s " % ((host_cpu_after_200_percent_overcommitment - used_cpu), vm_details.vCPU))
if((( host_ram_after_200_percent_overcommitment - used_ram) >= vm_details.RAM) and ((host_cpu_after_200_percent_overcommitment - used_cpu) >= vm_details.vCPU) and (vm_details.vCPU <= host.CPUs)):
clone_command = "virt-clone --original " + vm_details.vm_identity + " --name " + cloned_vm_details.vm_identity + \
clone_file_parameters + " --mac " + vm_properties['mac_addr']
command_output = execute_remote_cmd(vm_details.host_id.host_ip.private_ip, 'root', clone_command, None, True)
logger.debug(command_output)
logger.debug("Updating db after cloning")
update_db_after_vm_installation(cloned_vm_details, vm_properties, parent_id = vm_details.id)
message = "Cloned successfully. "
try:
new_host_id_for_cloned_vm = find_new_host(cloned_vm_details.RAM, cloned_vm_details.vCPU)
if new_host_id_for_cloned_vm != host.id:
if migrate_clone_to_new_host(vm_details, cloned_vm_details, new_host_id_for_cloned_vm,vm_properties):
message += "Found new host and migrated successfully."
else:
message += "Found new host but not migrated successfully."
else:
message += "New host selected to migrate cloned vm is same as the host on which it currently resides."
except:
message += "Could not find host to migrate cloned vm."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
else:
raise Exception("Host resources exhausted. Migrate the host vms and then try.")
except:
_free_vm_properties(cloned_vm_details, vm_properties)
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def attach_extra_disk(parameters):
"""
Attaches extra disk to VM
"""
logger.debug("Inside attach extra disk() function")
vmid = parameters['vm_id']
disk_size = parameters['disk_size']
vm_details = current.db.vm_data[vmid]
logger.debug(str(vm_details))
try:
if (serve_extra_disk_request(vm_details, disk_size, vm_details.host_id.host_ip.private_ip)):
current.db(current.db.vm_data.id == vmid).update(extra_HDD = vm_details.extra_HDD + disk_size)
message = "Attached extra disk successfully"
logger.debug(message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
else:
message = " Your request for additional HDD could not be completed at this moment. Check logs."
logger.debug("Task Status: SUCCESS Message: %s " % message)
return (current.TASK_QUEUE_STATUS_FAILED, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def get_vm_image_location(datastore_id, vm_identity):
"""
Get the file path for qcow2 image of a VM
"""
datastore = current.db.datastore[datastore_id]
vm_directory_path = datastore.system_mount_point + '/' + get_constant('vms') + '/' + vm_identity
vm_image_name = vm_directory_path + '/' + vm_identity + '.qcow2'
image_present = True if os.path.exists(vm_image_name) else False
return (vm_image_name, image_present)
def get_extra_disk_location(datastore_id, vm_identity, disk_name, get_disk_size=False):
"""
Get the file path for qcow2 image of teh extra disk
"""
datastore = current.db.datastore[datastore_id]
if datastore:
vm_extra_disks_directory_path = datastore.system_mount_point + '/' + get_constant('extra_disks_dir') + '/' + \
datastore.ds_name + '/' + vm_identity
ext = '' if disk_name.endswith('.qcow2') else '.qcow2'
disk_image_path = vm_extra_disks_directory_path + '/' + disk_name + ext
image_present = True if os.path.exists(disk_image_path) else False
disk_size = 0
if image_present & get_disk_size:
command = "qemu-img info " + disk_image_path + " | grep 'virtual size'"
ret = os.popen(command).read() # Returns e.g. virtual size: 40G (42949672960 bytes)
disk_size = int(ret[ret.index(':')+1:ret.index('G ')].strip())
return (disk_image_path, image_present, disk_size)
else:
return (None, False, 0)
def launch_existing_vm_image(vm_details):
"""
Launch existing VM image
- Choose new private_ip & mac_addr if not provided
- Get location for VM image
- Launch VM on given host
- Attach extra disk to VM if defined
- Create mapping between public IP and private IP if required
"""
logger.debug('Launch existing VM image')
vm_properties = {}
vm_properties['ram'] = vm_details.RAM
vm_properties['vcpus'] = vm_details.vCPU
vm_properties['security_domain'] = vm_details.security_domain
#If Private IP was already chosen previously and DHCP entry is done
if vm_details.private_ip != None:
private_ip_info = current.db.private_ip_pool[vm_details.private_ip]
if private_ip_info:
vm_properties['private_ip'] = private_ip_info.private_ip
vm_properties['mac_addr'] = private_ip_info.mac_addr
vm_properties['vlan_name'] = private_ip_info.vlan.name
vm_properties['vlan_tag'] = private_ip_info.vlan.vlan_tag
if vm_details.public_ip == None:
vm_properties['public_ip_req'] = False
else:
vm_properties['public_ip_req'] = True
if vm_details.public_ip.is_active:
vm_properties['public_ip'] = vm_details.public_ip.public_ip
_choose_mac_ip_vncport(vm_properties)
vm_properties['template'] = current.db.template[vm_details.template_id]
vm_properties['datastore'] = current.db.datastore[vm_details.datastore_id]
vm_properties['host'] = find_new_host(vm_details.RAM, vm_details.vCPU)
(vm_image_name, image_present) = get_vm_image_location(vm_details.datastore_id, vm_details.vm_identity)
if image_present:
launch_vm_on_host(vm_details, vm_image_name, vm_properties)
#Check if extra disk needs to be attached
attached_disks = current.db((current.db.attached_disks.vm_id == vm_details.id)).select()
if attached_disks:
#Extra disk to be attached to the VM
host_ip = current.db.host[vm_properties['host']].host_ip.private_ip
disk_counter = 1
for attached_disk in attached_disks:
disk_size = attach_disk(vm_details, attached_disk.attached_disk_name, host_ip, disk_counter, True)
current.db(current.db.attached_disks.vm_id == attached_disk.vm_id and
current.db.attached_disks.attached_disk_name==attached_disk.attached_disk_name
).update(capacity = disk_size)
vm_details.extra_HDD += disk_size
disk_counter += 1
#Create mapping of Private_IP and Public_IP
if vm_properties['public_ip_req']:
create_mapping(vm_properties['public_ip'], vm_properties['private_ip'])
update_db_after_vm_installation(vm_details, vm_properties)
def save_vm_as_template(parameters):
"""
Save VM as template
If template for given VM already exists, replace with new template.
"""
logger.debug("Inside save_as_template() function")
vm_id = parameters['vm_id']
vm_data = current.db.vm_data[vm_id]
user_list = []
vm_details = current.db.vm_data[vm_id]
logger.debug(str(vm_details))
try:
(is_templated_created, new_template, old_template) = create_new_template(vm_details)
if (is_templated_created):
#remove old template
if os.path.exists (old_template):
os.remove(old_template)
else:
for user in current.db(current.db.user_vm_map.vm_id == vm_id).select(current.db.user_vm_map.user_id):
user_list.append(user.user_id)
new_template_id = current.db.template.insert(name = vm_data.vm_name + "_template" ,
os = vm_data.template_id.os ,
os_name = vm_data.template_id.os_name ,
os_version = vm_data.template_id.os_version ,
os_type = vm_data.template_id.os_type ,
arch = vm_data.template_id.arch ,
hdd = vm_data.template_id.hdd ,
hdfile = new_template ,
type = vm_data.template_id.type ,
tag = vm_data.vm_name + "_template" ,
datastore_id = vm_data.template_id.datastore_id,
owner = user_list)
current.db.vm_data[vm_id] = dict(saved_template = new_template_id)
message = "User Template saved successfully"
logger.debug(message)
return (current.TASK_QUEUE_STATUS_SUCCESS, message)
else:
message = " Vm Template not saved "
logger.debug("Task Status: %s " % message)
return (current.TASK_QUEUE_STATUS_FAILED, message)
except:
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (current.TASK_QUEUE_STATUS_FAILED, log_exception())
def delete_template(parameters):
"""
Delete template
"""
logger.debug("Inside delete_template() function")
template_id = parameters['template_id']
template_details = current.db.template[template_id]
template_path = template_details["hdfile"]
if os.path.exists(template_path):
os.remove(template_path)
# set value in db also
parent_vm = current.db.vm_data(saved_template = template_id)
if parent_vm:
parent_vm.update_record(saved_template = None)
del current.db.template[template_id]
return (current.TASK_QUEUE_STATUS_SUCCESS, "")
def create_new_template(vm_details):
"""
Create a new template from the VM image
- Create template directory
- Copy VM Image to directory(Live copy if VM is running)
- Update database to define new template
"""
try:
(connection_object, domain) = getVirshDomainConn(vm_details)
xmlfile = domain.XMLDesc(0)
logger.debug("connection object created")
datastore = _choose_datastore()
logger.debug(datastore)
new_template_dir = datastore.system_mount_point + '/' +get_constant('templates_dir') + '/' + vm_details.requester_id.first_name
logger.debug("Creating user template directory...")
if not os.path.exists (new_template_dir):
os.makedirs(new_template_dir)
template = new_template_dir + '/' + vm_details.vm_identity + '_template.qcow2'
template_location = '/' + vm_details.requester_id.first_name + '/' + vm_details.vm_identity + '_template.qcow2'
old_template = new_template_dir + '/' + vm_details.vm_identity + '_template_old.qcow2'
if os.path.exists (template):
# move template to some other path
logger.debug("move template to some other file")
shutil.move(template, old_template)
logger.debug("template " + template)
current_disk_path = vm_details.datastore_id.system_mount_point + get_constant('vms') + '/' + vm_details.vm_identity
current_disk_file = current_disk_path + '/' + vm_details.vm_identity + '.qcow2'
if (vm_details.status == current.VM_STATUS_RUNNING or vm_details.status == current.VM_STATUS_SUSPENDED):
logger.debug("vm is active in db")
if domain.isActive():
domain.undefine()
root = etree.fromstring(xmlfile)
target_elem = root.find("devices/disk/target")
target_disk = target_elem.get('dev')
flag = VIR_DOMAIN_BLOCK_REBASE_SHALLOW | VIR_DOMAIN_BLOCK_REBASE_COPY
domain.blockRebase(target_disk, template, 0, flag)
block_info_list = domain.blockJobInfo(current_disk_file,0)
while(block_info_list['end'] != block_info_list['cur']):
logger.debug("time to sleep")
time.sleep(60)
block_info_list = domain.blockJobInfo(current_disk_file,0)
domain.blockJobAbort(current_disk_file)
domain = connection_object.defineXML(xmlfile)
connection_object.close()
return (True, template_location, old_template)
else:
logger.debug("domain is not running on host")
return (False, template_location, old_template)
elif(vm_details.status == current.VM_STATUS_SHUTDOWN):
if domain.isActive():
logger.debug("Domain is still active...Please try again after some time!!!")
return (False, template_location, old_template)
else:
logger.debug("copying")
copy_command = "cp "+current_disk_file+" "+template
logger.debug("copy_command"+copy_command)
#rc = os.system("cp %s %s" % (current_disk_file, template))
logger.debug("copy command running on " + vm_details.host_id.host_ip.private_ip + " host")
command_output = execute_remote_cmd(vm_details.host_id.host_ip.private_ip, 'root', copy_command)
logger.debug(command_output)
return (True, template_location, old_template)
except:
if not domain.isPersistent():
domain = connection_object.defineXML(xmlfile)
connection_object.close()
logger.debug("Task Status: FAILED Error: %s " % log_exception())
return (False, template_location, old_template)
| [] |
bopopescu/webrtc-streaming-node | third_party/webrtc/src/chromium/src/build/android/devil/android/sdk/aapt.py | 727a441204344ff596401b0253caac372b714d91 | # Copyright 2015 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""This module wraps the Android Asset Packaging Tool."""
import os
from devil.utils import cmd_helper
from pylib import constants
_AAPT_PATH = os.path.join(constants.ANDROID_SDK_TOOLS, 'aapt')
def _RunAaptCmd(args):
"""Runs an aapt command.
Args:
args: A list of arguments for aapt.
Returns:
The output of the command.
"""
cmd = [_AAPT_PATH] + args
status, output = cmd_helper.GetCmdStatusAndOutput(cmd)
if status != 0:
raise Exception('Failed running aapt command: "%s" with output "%s".' %
(' '.join(cmd), output))
return output
def Dump(what, apk, assets=None):
"""Returns the output of the aapt dump command.
Args:
what: What you want to dump.
apk: Path to apk you want to dump information for.
assets: List of assets in apk you want to dump information for.
"""
assets = assets or []
if isinstance(assets, basestring):
assets = [assets]
return _RunAaptCmd(['dump', what, apk] + assets).splitlines()
| [((310, 359), 'os.path.join', 'os.path.join', (['constants.ANDROID_SDK_TOOLS', '"""aapt"""'], {}), "(constants.ANDROID_SDK_TOOLS, 'aapt')\n", (322, 359), False, 'import os\n'), ((556, 593), 'devil.utils.cmd_helper.GetCmdStatusAndOutput', 'cmd_helper.GetCmdStatusAndOutput', (['cmd'], {}), '(cmd)\n', (588, 593), False, 'from devil.utils import cmd_helper\n')] |
esayui/mworks | examples/Tests/Misc/Resources/PythonFile/basic.py | 0522e5afc1e30fdbf1e67cedd196ee50f7924499 | setvar('nsamples', getvar('a') + getvar('b'))
| [] |
arosen93/HT-ASE | quacc/recipes/psi4/core.py | a76542e7a2bc5bf6e7382d8f1387374eb2abc713 | """Core recipes for Psi4"""
from __future__ import annotations
from dataclasses import dataclass
from typing import Any, Dict
from ase.atoms import Atoms
from ase.calculators.psi4 import Psi4
from jobflow import Maker, job
from monty.dev import requires
try:
import psi4
except:
psi4 = None
from quacc.schemas.calc import summarize_run
from quacc.util.basics import merge_dicts
from quacc.util.calc import run_calc
@dataclass
class StaticMaker(Maker):
"""
Class to carry out a single-point calculation.
Parameters
----------
name
Name of the job.
method
The level of theory to use.
basis
Basis set
swaps
Dictionary of custom kwargs for the calculator.
"""
name: str = "Psi4-Static"
method: str = "wb97x-v"
basis: str = "def2-tzvp"
swaps: Dict[str, Any] = None
@job
@requires(psi4, "Psi4 be installed. Try conda install -c psi4 psi4")
def make(
self, atoms: Atoms, charge: int = None, mult: int = None
) -> Dict[str, Any]:
"""
Make the run.
Parameters
----------
atoms
.Atoms object`
charge
Charge of the system. If None, this is determined from the sum of
atoms.get_initial_charges().
mult
Multiplicity of the system. If None, this is determined from 1+ the sum
of atoms.get_initial_magnetic_moments().
Returns
-------
Dict
Summary of the run.
"""
swaps = self.swaps or {}
defaults = {
"mem": "16GB",
"num_threads": "max",
"method": self.method,
"basis": self.basis,
"charge": charge if charge else round(sum(atoms.get_initial_charges())),
"multiplicity": mult
if mult
else round(1 + sum(atoms.get_initial_magnetic_moments())),
}
flags = merge_dicts(defaults, swaps, remove_none=True)
atoms.calc = Psi4(**flags)
new_atoms = run_calc(atoms)
summary = summarize_run(
new_atoms, input_atoms=atoms, additional_fields={"name": self.name}
)
return summary
| [((874, 941), 'monty.dev.requires', 'requires', (['psi4', '"""Psi4 be installed. Try conda install -c psi4 psi4"""'], {}), "(psi4, 'Psi4 be installed. Try conda install -c psi4 psi4')\n", (882, 941), False, 'from monty.dev import requires\n'), ((1952, 1998), 'quacc.util.basics.merge_dicts', 'merge_dicts', (['defaults', 'swaps'], {'remove_none': '(True)'}), '(defaults, swaps, remove_none=True)\n', (1963, 1998), False, 'from quacc.util.basics import merge_dicts\n'), ((2021, 2034), 'ase.calculators.psi4.Psi4', 'Psi4', ([], {}), '(**flags)\n', (2025, 2034), False, 'from ase.calculators.psi4 import Psi4\n'), ((2055, 2070), 'quacc.util.calc.run_calc', 'run_calc', (['atoms'], {}), '(atoms)\n', (2063, 2070), False, 'from quacc.util.calc import run_calc\n'), ((2089, 2176), 'quacc.schemas.calc.summarize_run', 'summarize_run', (['new_atoms'], {'input_atoms': 'atoms', 'additional_fields': "{'name': self.name}"}), "(new_atoms, input_atoms=atoms, additional_fields={'name': self\n .name})\n", (2102, 2176), False, 'from quacc.schemas.calc import summarize_run\n')] |
Archedar/UAS | UAS/UAS 11 & 12/main.py | 3237d9304026340acc93c8f36b358578dc0ae66f | #Main Program
from Class import Barang
import Menu
histori = list()
listBarang = [
Barang('Rinso', 5000, 20),
Barang('Sabun', 3000, 20),
Barang('Pulpen', 2500, 20),
Barang('Tisu', 10000, 20),
Barang('Penggaris', 1000, 20)
]
while True:
print('''
Menu
1. Tampilkan Barang
2. Tambahkan Barang
3. Tambah Stock Barang
4. Hapus Barang
5. Cari Barang Berdasarkan Keyword
6. Hitung Barang Belanjaan
7. Histori Keluar Masuk Barang
0. Keluar Program
''')
choice = input('Masukan No Menu: ')
if choice == '1':
Menu.menu1(listBarang)
elif choice == '2':
Menu.menu2(listBarang, histori)
elif choice == '3':
Menu.menu3(listBarang, histori)
elif choice == '4':
Menu.menu4(listBarang, histori)
elif choice == '5':
Menu.menu5(listBarang)
elif choice == '6':
Menu.menu6(listBarang, histori)
elif choice == '7':
Menu.menu7(histori)
elif choice == '0':
print('Keluar Program')
break
else:
print('Invalid Input!') | [((90, 115), 'Class.Barang', 'Barang', (['"""Rinso"""', '(5000)', '(20)'], {}), "('Rinso', 5000, 20)\n", (96, 115), False, 'from Class import Barang\n'), ((118, 143), 'Class.Barang', 'Barang', (['"""Sabun"""', '(3000)', '(20)'], {}), "('Sabun', 3000, 20)\n", (124, 143), False, 'from Class import Barang\n'), ((146, 172), 'Class.Barang', 'Barang', (['"""Pulpen"""', '(2500)', '(20)'], {}), "('Pulpen', 2500, 20)\n", (152, 172), False, 'from Class import Barang\n'), ((175, 200), 'Class.Barang', 'Barang', (['"""Tisu"""', '(10000)', '(20)'], {}), "('Tisu', 10000, 20)\n", (181, 200), False, 'from Class import Barang\n'), ((203, 232), 'Class.Barang', 'Barang', (['"""Penggaris"""', '(1000)', '(20)'], {}), "('Penggaris', 1000, 20)\n", (209, 232), False, 'from Class import Barang\n'), ((548, 570), 'Menu.menu1', 'Menu.menu1', (['listBarang'], {}), '(listBarang)\n', (558, 570), False, 'import Menu\n'), ((596, 627), 'Menu.menu2', 'Menu.menu2', (['listBarang', 'histori'], {}), '(listBarang, histori)\n', (606, 627), False, 'import Menu\n'), ((653, 684), 'Menu.menu3', 'Menu.menu3', (['listBarang', 'histori'], {}), '(listBarang, histori)\n', (663, 684), False, 'import Menu\n'), ((710, 741), 'Menu.menu4', 'Menu.menu4', (['listBarang', 'histori'], {}), '(listBarang, histori)\n', (720, 741), False, 'import Menu\n'), ((767, 789), 'Menu.menu5', 'Menu.menu5', (['listBarang'], {}), '(listBarang)\n', (777, 789), False, 'import Menu\n'), ((815, 846), 'Menu.menu6', 'Menu.menu6', (['listBarang', 'histori'], {}), '(listBarang, histori)\n', (825, 846), False, 'import Menu\n'), ((872, 891), 'Menu.menu7', 'Menu.menu7', (['histori'], {}), '(histori)\n', (882, 891), False, 'import Menu\n')] |
thunlp/JointNRE | original/baselines/train/JointE+ONE.py | 29e2070910d0940bf4d32a8b8c97800bceff98fb | #coding:utf-8
import numpy as np
import tensorflow as tf
import os
import time
import datetime
import ctypes
import threading
import json
ll1 = ctypes.cdll.LoadLibrary
lib_cnn = ll1("./init_cnn.so")
ll2 = ctypes.cdll.LoadLibrary
lib_kg = ll2("./init_know.so")
class Config(object):
def __init__(self):
self.instanceTot = lib_cnn.getInstanceTot()
self.sequence_size = lib_cnn.getLenLimit()
self.num_classes = lib_cnn.getRelationTotal()
self.num_words = lib_cnn.getWordTotal()
self.num_positions = 2 * lib_cnn.getPositionLimit() + 1
self.word_size = lib_cnn.getWordDimension()
self.position_size = 5
self.embedding_size = self.word_size + self.position_size * 2
self.filter_size = 3
self.num_filters = 230
self.relation_size = self.word_size#230
self.dropout_keep_prob = 0.5
self.l2_lambda = 0.0001
self.NA = 51
lib_cnn.setNA(self.NA)
lib_cnn.setRate(3)
self.margin = 1.0
self.nbatches = 100
self.trainTimes = 15
self.entityTotal = 0
self.relationTotal = 0
class Model(object):
def __init__(self, config):
sequence_size = config.sequence_size
num_classes = config.num_classes
num_words = config.num_words
num_positions = config.num_positions
embedding_size = config.embedding_size
word_size = config.word_size
position_size = config.position_size
relation_size = config.relation_size
filter_size = config.filter_size
num_filters = config.num_filters
dropout_keep_prob = config.dropout_keep_prob
margin = config.margin
l2_lambda = config.l2_lambda
self.input_x = tf.placeholder(tf.int32, [None, sequence_size], name = "input_x")
self.input_p_h = tf.placeholder(tf.int32, [None, sequence_size], name = "input_p_h")
self.input_p_t = tf.placeholder(tf.int32, [None, sequence_size], name = "input_p_t")
self.input_r = tf.placeholder(tf.float32, [1, 1], name = "input_r")
self.input_r_n = tf.placeholder(tf.float32, [1, 1], name = "input_r_n")
self.input_h = tf.placeholder(tf.int32, [1, 1], name = "input_h")
self.input_t = tf.placeholder(tf.int32, [1, 1], name = "input_t")
self.input_y = tf.placeholder(tf.float32, [1, num_classes], name = "input_y")
self.pos_h = tf.placeholder(tf.int32, [None])
self.pos_t = tf.placeholder(tf.int32, [None])
self.pos_r = tf.placeholder(tf.int32, [None])
self.neg_h = tf.placeholder(tf.int32, [None])
self.neg_t = tf.placeholder(tf.int32, [None])
self.neg_r = tf.placeholder(tf.int32, [None])
l2_loss = tf.constant(0.0)
with tf.name_scope("embedding-lookup"):
self.word_embeddings = tf.Variable(word_embeddings, name="word_embeddings")
self.relation_embeddings = tf.get_variable("relation_embeddings", [config.relationTotal, word_size])
self.position_embeddings = tf.get_variable("position_embeddings", [num_positions, position_size])
self.relation_attention = tf.get_variable("relation_attention", [num_classes, relation_size])
self.NAattention = tf.get_variable("NAattention", [relation_size, 1])
self.attention = tf.get_variable("attention", [num_filters, relation_size])
#know
pos_h_e = tf.nn.embedding_lookup(self.word_embeddings, self.pos_h)
pos_t_e = tf.nn.embedding_lookup(self.word_embeddings, self.pos_t)
pos_r_e = tf.nn.embedding_lookup(self.relation_embeddings, self.pos_r)
neg_h_e = tf.nn.embedding_lookup(self.word_embeddings, self.neg_h)
neg_t_e = tf.nn.embedding_lookup(self.word_embeddings, self.neg_t)
neg_r_e = tf.nn.embedding_lookup(self.relation_embeddings, self.neg_r)
#cnn
self.x_initial = tf.nn.embedding_lookup(self.word_embeddings, self.input_x)
self.x_p_h = tf.nn.embedding_lookup(self.position_embeddings, self.input_p_h)
self.x_p_t = tf.nn.embedding_lookup(self.position_embeddings, self.input_p_t)
self.x = tf.expand_dims(tf.concat(2, [self.x_initial, self.x_p_h, self.x_p_t]), -1)
self.head = tf.nn.embedding_lookup(self.word_embeddings, self.input_h)
self.tail = tf.nn.embedding_lookup(self.word_embeddings, self.input_t)
l2_loss += tf.nn.l2_loss(self.attention)
with tf.name_scope("conv-maxpool"):
self.W = tf.get_variable("W", [filter_size, embedding_size, 1, num_filters])
self.b = tf.get_variable("b", [num_filters])
conv = tf.nn.conv2d(self.x, self.W, strides=[1, 1, 1, 1], padding="VALID", name="conv")
h = tf.nn.tanh(tf.nn.bias_add(conv, self.b), name="tanh")
self.y = tf.nn.max_pool(h, ksize=[1, sequence_size - filter_size + 1, 1, 1], strides=[1, 1, 1, 1], padding='VALID', name="pool")
l2_loss += tf.nn.l2_loss(self.W)
l2_loss += tf.nn.l2_loss(self.b)
self.y = tf.reshape(self.y, [-1, num_filters])
with tf.name_scope('attention'):
self.y_attention = tf.reduce_max(self.y, 0 , keep_dims = True)
with tf.name_scope("dropout"):
self.y_attention = tf.nn.l2_normalize(self.y_attention, 1)
self.h_drop = tf.nn.dropout(self.y_attention, dropout_keep_prob)
self.transfer_w = tf.get_variable("transfer_w", [num_filters, num_classes])
self.scores = tf.matmul(self.h_drop, self.transfer_w)
l2_loss += tf.nn.l2_loss(self.transfer_w)
with tf.name_scope("loss"):
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(self.scores, self.input_y)
self.loss_cnn = tf.reduce_mean(cross_entropy) + l2_lambda * l2_loss
pos = tf.reduce_sum(abs(pos_h_e + pos_r_e - pos_t_e), 1, keep_dims = True)
neg = tf.reduce_sum(abs(neg_h_e + neg_r_e - neg_t_e), 1, keep_dims = True)
self.loss_kg = tf.reduce_sum(tf.maximum(pos - neg + margin, 0))
with tf.name_scope("accuracy"):
self.predictions = tf.argmax(self.scores, 1, name="predictions")
correct_predictions = tf.equal(self.predictions, tf.argmax(self.input_y, 1))
self.accuracy = tf.reduce_mean(tf.cast(correct_predictions, "float"), name="accuracy")
bags_sum = 0.0
bags_hit_NA = 0.0
sum_NA = 0.0
sum_fNA = 0.0
bags_hit = 0.0
loss_sum = 0.0
if __name__ == "__main__":
lib_cnn.readWordVec()
lib_cnn.readFromFile()
lib_kg.init()
np.random.seed(0)
tf.set_random_seed(0)
config = Config()
word_embeddings = np.zeros(config.num_words * config.word_size, dtype = np.float32)
lib_cnn.getWordVec.argtypes = [ctypes.c_void_p]
lib_cnn.getWordVec(word_embeddings.__array_interface__['data'][0])
word_embeddings.resize((config.num_words,config.word_size))
config.batch_size = lib_kg.getTripleTotal() / config.nbatches
config.entityTotal = lib_kg.getEntityTotal()
config.relationTotal = lib_kg.getRelationTotal()
with tf.Graph().as_default():
conf = tf.ConfigProto()
sess = tf.Session(config=conf)
with sess.as_default():
initializer = tf.contrib.layers.xavier_initializer()
with tf.variable_scope("model", reuse=None, initializer = initializer):
m = Model(config = config)
global_step_cnn = tf.Variable(0, name="global_step_cnn", trainable=False)
optimizer_cnn = tf.train.GradientDescentOptimizer(0.01)
grads_and_vars_cnn = optimizer_cnn.compute_gradients(m.loss_cnn)
train_op_cnn = optimizer_cnn.apply_gradients(grads_and_vars_cnn, global_step = global_step_cnn)
global_step_kg = tf.Variable(0, name="global_step_kg", trainable=False)
optimizer_kg = tf.train.GradientDescentOptimizer(0.001)
grads_and_vars_kg = optimizer_kg.compute_gradients(m.loss_kg)
train_op_kg = optimizer_kg.apply_gradients(grads_and_vars_kg, global_step=global_step_kg)
sess.run(tf.initialize_all_variables())
def outEmbedding(str1):
word_embeddings, relation_embeddings, position_embeddings, relation_attention, attention, W, B, transfer_w, transfer_b, softmax_w, softmax_b = sess.run([m.word_embeddings, m.relation_embeddings, m.position_embeddings, m.relation_attention, m.attention, m.W, m.b, m.transfer_w, m.transfer_b, m.softmax_w, m.softmax_b])
log = open("log"+str1+".txt", "w")
log.write(json.dumps(word_embeddings.tolist())+"\n")
log.write(json.dumps(relation_embeddings.tolist())+"\n")
log.write(json.dumps(position_embeddings.tolist())+"\n")
log.write(json.dumps(relation_attention.tolist())+"\n")
log.write(json.dumps(attention.tolist())+"\n")
log.write(json.dumps(W.tolist())+"\n")
log.write(json.dumps(B.tolist())+"\n")
log.write(json.dumps(transfer_w.tolist())+"\n")
NAattention = sess.run(m.NAattention)
log.write(json.dumps(NAattention.tolist()) + "\n")
log.close()
x_batch = np.zeros((config.instanceTot,config.sequence_size), dtype = np.int32)
p_t_batch = np.zeros((config.instanceTot,config.sequence_size), dtype = np.int32)
p_h_batch = np.zeros((config.instanceTot,config.sequence_size), dtype = np.int32)
r_batch = np.zeros((1, 1), dtype = np.int32)
y_batch = np.zeros((1, config.num_classes), dtype = np.int32)
r_n_batch = np.zeros((1, 1), dtype = np.float32)
h_batch = np.zeros((1, 1), dtype = np.int32)
t_batch = np.zeros((1, 1), dtype = np.int32)
x_batch_addr = x_batch.__array_interface__['data'][0]
p_t_batch_addr = p_t_batch.__array_interface__['data'][0]
p_h_batch_addr = p_h_batch.__array_interface__['data'][0]
y_batch_addr = y_batch.__array_interface__['data'][0]
r_batch_addr = r_batch.__array_interface__['data'][0]
r_n_batch_addr = r_n_batch.__array_interface__['data'][0]
h_batch_addr = h_batch.__array_interface__['data'][0]
t_batch_addr = t_batch.__array_interface__['data'][0]
lib_cnn.batch_iter.argtypes = [ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p]
tipTotal = lib_cnn.getTipTotal()
loop = 0
def train_cnn(coord):
def train_step_cnn(x_batch, p_h_batch, p_t_batch, y_batch, r_batch, r_n_batch, h_batch, t_batch):
global bags_sum, bags_hit, loss_sum, bags_hit_NA, bags_hit, sum_fNA, sum_NA
feed_dict = {
m.input_x: x_batch,
m.input_p_h: p_h_batch,
m.input_p_t: p_t_batch,
m.input_r: r_batch,
m.input_r_n: r_n_batch,
m.input_y: y_batch,
m.input_h: h_batch,
m.input_t: t_batch
}
_, step, loss, accuracy = sess.run(
[train_op_cnn, global_step_cnn, m.loss_cnn, m.accuracy], feed_dict)
time_str = datetime.datetime.now().isoformat()
loss_sum += loss
bags_sum += 1
if (r_batch[0]!=config.NA):
sum_fNA += 1
if accuracy > 0.5:
bags_hit += 1.0
else:
sum_NA += 1
if accuracy > 0.5:
bags_hit_NA += 1.0
if bags_sum % 1000 == 0:
if (sum_NA == 0):
sum_NA+=1
if (sum_fNA == 0):
sum_fNA+=1
print("{}: step {}, loss {:g}, acc {:g} acc {:g} {} {}".format(time_str, step, loss_sum/bags_sum, bags_hit_NA/sum_NA, bags_hit/sum_fNA, sum_NA, sum_fNA))
global loop
while not coord.should_stop():
print 'Looping ', loop
outEmbedding(str(loop))
for i in range(tipTotal):
length = lib_cnn.batch_iter(x_batch_addr, p_h_batch_addr, p_t_batch_addr, y_batch_addr, r_batch_addr, r_n_batch_addr, h_batch_addr, t_batch_addr)
train_step_cnn(x_batch[0:length,], p_h_batch[0:length,], p_t_batch[0:length,], y_batch, r_batch, r_n_batch, h_batch, t_batch)
global bags_sum, bags_hit, loss_sum, bags_hit_NA, bags_hit, sum_fNA, sum_NA
bags_sum = 0
bags_hit = 0
bags_hit_NA = 0
loss_sum = 0
sum_fNA = 0
sum_NA = 0
loop += 1
if loop == config.trainTimes:
coord.request_stop()
ph = np.zeros(config.batch_size * 2, dtype = np.int32)
pt = np.zeros(config.batch_size * 2, dtype = np.int32)
pr = np.zeros(config.batch_size * 2, dtype = np.int32)
nh = np.zeros(config.batch_size * 2, dtype = np.int32)
nt = np.zeros(config.batch_size * 2, dtype = np.int32)
nr = np.zeros(config.batch_size * 2, dtype = np.int32)
ph_addr = ph.__array_interface__['data'][0]
pt_addr = pt.__array_interface__['data'][0]
pr_addr = pr.__array_interface__['data'][0]
nh_addr = nh.__array_interface__['data'][0]
nt_addr = nt.__array_interface__['data'][0]
nr_addr = nr.__array_interface__['data'][0]
lib_kg.getBatch.argtypes = [ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_void_p, ctypes.c_int]
times_kg = 0
def train_kg(coord):
def train_step_kg(pos_h_batch, pos_t_batch, pos_r_batch, neg_h_batch, neg_t_batch, neg_r_batch):
feed_dict = {
m.pos_h: pos_h_batch,
m.pos_t: pos_t_batch,
m.pos_r: pos_r_batch,
m.neg_h: neg_h_batch,
m.neg_t: neg_t_batch,
m.neg_r: neg_r_batch
}
_, step, loss = sess.run(
[train_op_kg, global_step_kg, m.loss_kg], feed_dict)
return loss
global times_kg
while not coord.should_stop():
times_kg += 1
res = 0.0
for batch in range(config.nbatches):
lib_kg.getBatch(ph_addr, pt_addr, pr_addr, nh_addr, nt_addr, nr_addr, config.batch_size)
res += train_step_kg(ph, pt, pr, nh, nt, nr)
coord = tf.train.Coordinator()
threads = []
threads.append(threading.Thread(target=train_kg, args=(coord,)))
threads.append(threading.Thread(target=train_cnn, args=(coord,)))
for t in threads: t.start()
coord.join(threads)
| [] |
rachmadaniHaryono/i2vec_cli | i2vec_cli/__main__.py | 9e03ca1c930e5eab8e42ac882c66e18f7c7435ba | #!/usr/bin/env python3
"""get tag from http://demo.illustration2vec.net/."""
# note:
# - error 'ERROR: Request Entity Too Large' for file 1.1 mb
# <span style="color:red;">ERROR: Request Entity Too Large</span>
from collections import OrderedDict
from pathlib import Path
from pprint import pformat
import imghdr
import logging
import os
import shutil
import time
import urllib
import hashlib
import click
import requests
import structlog
import peewee
from PIL import Image
from i2vec_cli import models
from i2vec_cli.requests_session import Session, convert_raw_to_hydrus
from i2vec_cli.sha256 import sha256_checksum
from i2vec_cli.utils import user_data_dir, thumb_folder
def is_url(path):
"""Return True if path is url, False otherwise."""
scheme = urllib.parse.urlparse(path).scheme
if scheme in ('http', 'https'):
return True
return False
def is_ext_equal(file_ext, imghdr_ext):
"""compare file extension with result from imghdr_ext."""
if not imghdr_ext:
return False
if file_ext.lower() == '.{}'.format(imghdr_ext):
return True
if file_ext.lower() in ('.jpg', '.jpeg') and imghdr_ext == 'jpeg':
return True
return False
def download(url, no_clobber):
"""download url.
Args:
url: URL to be downloaded.
no_clobber: Skip download if file already exist.
Returns:
Downloaded filename or existing file if `no_clobber` is `True`
"""
log = structlog.getLogger()
basename = os.path.basename(url)
if os.path.isfile(basename) and no_clobber:
return basename
response = requests.get(url, stream=True)
with open(basename, 'wb') as out_file:
shutil.copyfileobj(response.raw, out_file)
name, ext = os.path.splitext(basename)
imghdr_ext = imghdr.what(basename)
ext_equal = is_ext_equal(file_ext=ext, imghdr_ext=imghdr_ext)
if not imghdr_ext:
log.debug("imghdr can't recognize file", file=basename)
return basename
else:
new_basename = '{}.{}'.format(name, imghdr_ext)
new_basename_exist = os.path.isfile(new_basename)
if ext_equal:
log.debug('Extension is equal', file_ext=ext, imghdr_ext=imghdr_ext)
return basename
elif not ext_equal:
if new_basename_exist and not no_clobber:
log.debug('Replace existing file', old=basename, new=new_basename)
shutil.move(basename, new_basename)
elif not new_basename_exist:
log.debug('Rename file ext', file=basename, new_ext=imghdr_ext)
shutil.move(basename, new_basename)
else:
log.debug('Not replace/rename file', no_clobber=no_clobber, new_basename=new_basename)
return new_basename
else:
log.debug(
'Unknown condition',
file=basename,
ext_equal=ext_equal,
new_basename_exist=new_basename_exist,
imghdr_ext=imghdr_ext
)
# just return base name if any error happen
return basename
def validate_close_delay(ctx, param, value):
"""validate close delay."""
try:
value = int(value)
except Exception as e:
raise click.BadParameter(
'Error when validate close delay: value={}, error={}'.format(value, e))
if value >= -1:
return value
else:
raise click.BadParameter('Close delay have to be bigger or equal than -1')
def delay_close(close_delay):
"""delay when closing the program."""
log = structlog.getLogger()
if close_delay == -1:
click.pause()
elif close_delay == 0:
log.debug('No close delay')
elif close_delay > 0:
time.sleep(close_delay)
else:
log.error('Invalid close delay', v=close_delay)
def md5_checksum(fname):
hash_md5 = hashlib.md5()
with open(fname, "rb") as f:
for chunk in iter(lambda: f.read(4096), b""):
hash_md5.update(chunk)
return hash_md5.hexdigest()
def create_thumbnail(path, thumb_path):
"""create thumbnail."""
size = 320, 320
try:
im = Image.open(path)
im.thumbnail(size)
im.save(thumb_path, "JPEG")
except IOError:
raise IOError("cannot create thumbnail for", path)
def get_print_result(path, db_path, format, session):
"""get print result."""
# compatibility
p = path
sha256 = sha256_checksum(p)
md5 = md5_checksum(p)
thumb_path = os.path.join(user_data_dir, 'thumb', '{}.jpg'.format(sha256))
try:
load_res = models.load_result(db=db_path, sha256=sha256, md5=md5)
except models.Image.DoesNotExist:
load_res = None
if load_res:
tags = {'prediction': load_res}
else:
tags = session.get_tags(path=p)
try:
models.save_result(
db=db_path, sha256=sha256, md5=md5, prediction=tags['prediction'])
except peewee.IntegrityError as e:
log.debug(str(e))
except keyError as e:
log.debug(str(tags))
if not os.path.isfile(thumb_path):
create_thumbnail(p, thumb_path)
if format == 'dict':
return tags
if format == 'hydrus':
return convert_raw_to_hydrus(tags)
else:
return pformat(tags['prediction'])
@click.command()
@click.option('--format', type=click.Choice(['raw', 'hydrus']), default='raw')
@click.option('-d', '--debug', is_flag=True, help="Enable debug.")
@click.option('-nc', '--no-clobber', is_flag=True, help="Skip download url when file exist.")
@click.option(
'--close-delay', default=0, help="Close delay of the program.", callback=validate_close_delay)
@click.option(
'--driver', default=None, help="Driver for browser (deprecated).",
type=click.Choice(['firefox', 'phantomjs', 'chrome', 'zope.testbrowser', 'django']))
@click.option('--dump-html', is_flag=True, help="Dump html table for debugging (deprecated).")
@click.argument('path', nargs=-1)
def main(format, path, debug, no_clobber, close_delay, driver=None, dump_html=False):
"""get tag from illustration2vec."""
if debug:
logging.basicConfig(level=logging.DEBUG)
else:
logging.basicConfig(level=logging.INFO)
structlog.configure_once(logger_factory=structlog.stdlib.LoggerFactory())
log = structlog.getLogger()
if not path:
raise ValueError('PATH required.')
# init folder
os.makedirs(user_data_dir, exist_ok=True)
os.makedirs(thumb_folder, exist_ok=True)
# database
db_path = os.path.join(user_data_dir, 'main.db')
if not os.path.isfile(db_path):
Path(db_path).touch()
models.database.init(db_path)
try:
models.init_all_tables()
except peewee.OperationalError:
log.debug('Table already created')
session = Session(driver=driver)
try:
for p in path:
if os.path.isfile(p):
print('path:{}'.format(os.path.basename(p)))
elif is_url(p):
print('url:{}'.format(p))
p = download(p, no_clobber=no_clobber)
else:
log.error('Unknown path format or path is not exist', path=p)
continue
result = get_print_result(
path=p, db_path=db_path, format=format, session=session)
print(result)
finally:
delay_close(close_delay)
if hasattr(session, 'browser'):
session.browser.quit()
if __name__ == '__main__':
main()
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debrando/cherrypy | cherrypy/lib/cptools.py | a92c5cc5d888b0aad327bce34e94da4a1f961e43 | """Functions for builtin CherryPy tools."""
import logging
import re
from hashlib import md5
import six
from six.moves import urllib
import cherrypy
from cherrypy._cpcompat import text_or_bytes
from cherrypy.lib import httputil as _httputil
from cherrypy.lib import is_iterator
# Conditional HTTP request support #
def validate_etags(autotags=False, debug=False):
"""Validate the current ETag against If-Match, If-None-Match headers.
If autotags is True, an ETag response-header value will be provided
from an MD5 hash of the response body (unless some other code has
already provided an ETag header). If False (the default), the ETag
will not be automatic.
WARNING: the autotags feature is not designed for URL's which allow
methods other than GET. For example, if a POST to the same URL returns
no content, the automatic ETag will be incorrect, breaking a fundamental
use for entity tags in a possibly destructive fashion. Likewise, if you
raise 304 Not Modified, the response body will be empty, the ETag hash
will be incorrect, and your application will break.
See :rfc:`2616` Section 14.24.
"""
response = cherrypy.serving.response
# Guard against being run twice.
if hasattr(response, 'ETag'):
return
status, reason, msg = _httputil.valid_status(response.status)
etag = response.headers.get('ETag')
# Automatic ETag generation. See warning in docstring.
if etag:
if debug:
cherrypy.log('ETag already set: %s' % etag, 'TOOLS.ETAGS')
elif not autotags:
if debug:
cherrypy.log('Autotags off', 'TOOLS.ETAGS')
elif status != 200:
if debug:
cherrypy.log('Status not 200', 'TOOLS.ETAGS')
else:
etag = response.collapse_body()
etag = '"%s"' % md5(etag).hexdigest()
if debug:
cherrypy.log('Setting ETag: %s' % etag, 'TOOLS.ETAGS')
response.headers['ETag'] = etag
response.ETag = etag
# "If the request would, without the If-Match header field, result in
# anything other than a 2xx or 412 status, then the If-Match header
# MUST be ignored."
if debug:
cherrypy.log('Status: %s' % status, 'TOOLS.ETAGS')
if status >= 200 and status <= 299:
request = cherrypy.serving.request
conditions = request.headers.elements('If-Match') or []
conditions = [str(x) for x in conditions]
if debug:
cherrypy.log('If-Match conditions: %s' % repr(conditions),
'TOOLS.ETAGS')
if conditions and not (conditions == ['*'] or etag in conditions):
raise cherrypy.HTTPError(412, 'If-Match failed: ETag %r did '
'not match %r' % (etag, conditions))
conditions = request.headers.elements('If-None-Match') or []
conditions = [str(x) for x in conditions]
if debug:
cherrypy.log('If-None-Match conditions: %s' % repr(conditions),
'TOOLS.ETAGS')
if conditions == ['*'] or etag in conditions:
if debug:
cherrypy.log('request.method: %s' %
request.method, 'TOOLS.ETAGS')
if request.method in ('GET', 'HEAD'):
raise cherrypy.HTTPRedirect([], 304)
else:
raise cherrypy.HTTPError(412, 'If-None-Match failed: ETag %r '
'matched %r' % (etag, conditions))
def validate_since():
"""Validate the current Last-Modified against If-Modified-Since headers.
If no code has set the Last-Modified response header, then no validation
will be performed.
"""
response = cherrypy.serving.response
lastmod = response.headers.get('Last-Modified')
if lastmod:
status, reason, msg = _httputil.valid_status(response.status)
request = cherrypy.serving.request
since = request.headers.get('If-Unmodified-Since')
if since and since != lastmod:
if (status >= 200 and status <= 299) or status == 412:
raise cherrypy.HTTPError(412)
since = request.headers.get('If-Modified-Since')
if since and since == lastmod:
if (status >= 200 and status <= 299) or status == 304:
if request.method in ('GET', 'HEAD'):
raise cherrypy.HTTPRedirect([], 304)
else:
raise cherrypy.HTTPError(412)
# Tool code #
def allow(methods=None, debug=False):
"""Raise 405 if request.method not in methods (default ['GET', 'HEAD']).
The given methods are case-insensitive, and may be in any order.
If only one method is allowed, you may supply a single string;
if more than one, supply a list of strings.
Regardless of whether the current method is allowed or not, this
also emits an 'Allow' response header, containing the given methods.
"""
if not isinstance(methods, (tuple, list)):
methods = [methods]
methods = [m.upper() for m in methods if m]
if not methods:
methods = ['GET', 'HEAD']
elif 'GET' in methods and 'HEAD' not in methods:
methods.append('HEAD')
cherrypy.response.headers['Allow'] = ', '.join(methods)
if cherrypy.request.method not in methods:
if debug:
cherrypy.log('request.method %r not in methods %r' %
(cherrypy.request.method, methods), 'TOOLS.ALLOW')
raise cherrypy.HTTPError(405)
else:
if debug:
cherrypy.log('request.method %r in methods %r' %
(cherrypy.request.method, methods), 'TOOLS.ALLOW')
def proxy(base=None, local='X-Forwarded-Host', remote='X-Forwarded-For',
scheme='X-Forwarded-Proto', debug=False):
"""Change the base URL (scheme://host[:port][/path]).
For running a CP server behind Apache, lighttpd, or other HTTP server.
For Apache and lighttpd, you should leave the 'local' argument at the
default value of 'X-Forwarded-Host'. For Squid, you probably want to set
tools.proxy.local = 'Origin'.
If you want the new request.base to include path info (not just the host),
you must explicitly set base to the full base path, and ALSO set 'local'
to '', so that the X-Forwarded-Host request header (which never includes
path info) does not override it. Regardless, the value for 'base' MUST
NOT end in a slash.
cherrypy.request.remote.ip (the IP address of the client) will be
rewritten if the header specified by the 'remote' arg is valid.
By default, 'remote' is set to 'X-Forwarded-For'. If you do not
want to rewrite remote.ip, set the 'remote' arg to an empty string.
"""
request = cherrypy.serving.request
if scheme:
s = request.headers.get(scheme, None)
if debug:
cherrypy.log('Testing scheme %r:%r' % (scheme, s), 'TOOLS.PROXY')
if s == 'on' and 'ssl' in scheme.lower():
# This handles e.g. webfaction's 'X-Forwarded-Ssl: on' header
scheme = 'https'
else:
# This is for lighttpd/pound/Mongrel's 'X-Forwarded-Proto: https'
scheme = s
if not scheme:
scheme = request.base[:request.base.find('://')]
if local:
lbase = request.headers.get(local, None)
if debug:
cherrypy.log('Testing local %r:%r' % (local, lbase), 'TOOLS.PROXY')
if lbase is not None:
base = lbase.split(',')[0]
if not base:
default = urllib.parse.urlparse(request.base).netloc
base = request.headers.get('Host', default)
if base.find('://') == -1:
# add http:// or https:// if needed
base = scheme + '://' + base
request.base = base
if remote:
xff = request.headers.get(remote)
if debug:
cherrypy.log('Testing remote %r:%r' % (remote, xff), 'TOOLS.PROXY')
if xff:
if remote == 'X-Forwarded-For':
# Grab the first IP in a comma-separated list. Ref #1268.
xff = next(ip.strip() for ip in xff.split(','))
request.remote.ip = xff
def ignore_headers(headers=('Range',), debug=False):
"""Delete request headers whose field names are included in 'headers'.
This is a useful tool for working behind certain HTTP servers;
for example, Apache duplicates the work that CP does for 'Range'
headers, and will doubly-truncate the response.
"""
request = cherrypy.serving.request
for name in headers:
if name in request.headers:
if debug:
cherrypy.log('Ignoring request header %r' % name,
'TOOLS.IGNORE_HEADERS')
del request.headers[name]
def response_headers(headers=None, debug=False):
"""Set headers on the response."""
if debug:
cherrypy.log('Setting response headers: %s' % repr(headers),
'TOOLS.RESPONSE_HEADERS')
for name, value in (headers or []):
cherrypy.serving.response.headers[name] = value
response_headers.failsafe = True
def referer(pattern, accept=True, accept_missing=False, error=403,
message='Forbidden Referer header.', debug=False):
"""Raise HTTPError if Referer header does/does not match the given pattern.
pattern
A regular expression pattern to test against the Referer.
accept
If True, the Referer must match the pattern; if False,
the Referer must NOT match the pattern.
accept_missing
If True, permit requests with no Referer header.
error
The HTTP error code to return to the client on failure.
message
A string to include in the response body on failure.
"""
try:
ref = cherrypy.serving.request.headers['Referer']
match = bool(re.match(pattern, ref))
if debug:
cherrypy.log('Referer %r matches %r' % (ref, pattern),
'TOOLS.REFERER')
if accept == match:
return
except KeyError:
if debug:
cherrypy.log('No Referer header', 'TOOLS.REFERER')
if accept_missing:
return
raise cherrypy.HTTPError(error, message)
class SessionAuth(object):
"""Assert that the user is logged in."""
session_key = 'username'
debug = False
def check_username_and_password(self, username, password):
pass
def anonymous(self):
"""Provide a temporary user name for anonymous users."""
pass
def on_login(self, username):
pass
def on_logout(self, username):
pass
def on_check(self, username):
pass
def login_screen(self, from_page='..', username='', error_msg='',
**kwargs):
return (six.text_type("""<html><body>
Message: %(error_msg)s
<form method="post" action="do_login">
Login: <input type="text" name="username" value="%(username)s" size="10" />
<br />
Password: <input type="password" name="password" size="10" />
<br />
<input type="hidden" name="from_page" value="%(from_page)s" />
<br />
<input type="submit" />
</form>
</body></html>""") % vars()).encode('utf-8')
def do_login(self, username, password, from_page='..', **kwargs):
"""Login. May raise redirect, or return True if request handled."""
response = cherrypy.serving.response
error_msg = self.check_username_and_password(username, password)
if error_msg:
body = self.login_screen(from_page, username, error_msg)
response.body = body
if 'Content-Length' in response.headers:
# Delete Content-Length header so finalize() recalcs it.
del response.headers['Content-Length']
return True
else:
cherrypy.serving.request.login = username
cherrypy.session[self.session_key] = username
self.on_login(username)
raise cherrypy.HTTPRedirect(from_page or '/')
def do_logout(self, from_page='..', **kwargs):
"""Logout. May raise redirect, or return True if request handled."""
sess = cherrypy.session
username = sess.get(self.session_key)
sess[self.session_key] = None
if username:
cherrypy.serving.request.login = None
self.on_logout(username)
raise cherrypy.HTTPRedirect(from_page)
def do_check(self):
"""Assert username. Raise redirect, or return True if request handled.
"""
sess = cherrypy.session
request = cherrypy.serving.request
response = cherrypy.serving.response
username = sess.get(self.session_key)
if not username:
sess[self.session_key] = username = self.anonymous()
self._debug_message('No session[username], trying anonymous')
if not username:
url = cherrypy.url(qs=request.query_string)
self._debug_message(
'No username, routing to login_screen with from_page %(url)r',
locals(),
)
response.body = self.login_screen(url)
if 'Content-Length' in response.headers:
# Delete Content-Length header so finalize() recalcs it.
del response.headers['Content-Length']
return True
self._debug_message('Setting request.login to %(username)r', locals())
request.login = username
self.on_check(username)
def _debug_message(self, template, context={}):
if not self.debug:
return
cherrypy.log(template % context, 'TOOLS.SESSAUTH')
def run(self):
request = cherrypy.serving.request
response = cherrypy.serving.response
path = request.path_info
if path.endswith('login_screen'):
self._debug_message('routing %(path)r to login_screen', locals())
response.body = self.login_screen()
return True
elif path.endswith('do_login'):
if request.method != 'POST':
response.headers['Allow'] = 'POST'
self._debug_message('do_login requires POST')
raise cherrypy.HTTPError(405)
self._debug_message('routing %(path)r to do_login', locals())
return self.do_login(**request.params)
elif path.endswith('do_logout'):
if request.method != 'POST':
response.headers['Allow'] = 'POST'
raise cherrypy.HTTPError(405)
self._debug_message('routing %(path)r to do_logout', locals())
return self.do_logout(**request.params)
else:
self._debug_message('No special path, running do_check')
return self.do_check()
def session_auth(**kwargs):
sa = SessionAuth()
for k, v in kwargs.items():
setattr(sa, k, v)
return sa.run()
session_auth.__doc__ = (
"""Session authentication hook.
Any attribute of the SessionAuth class may be overridden via a keyword arg
to this function:
""" + '\n'.join(['%s: %s' % (k, type(getattr(SessionAuth, k)).__name__)
for k in dir(SessionAuth) if not k.startswith('__')])
)
def log_traceback(severity=logging.ERROR, debug=False):
"""Write the last error's traceback to the cherrypy error log."""
cherrypy.log('', 'HTTP', severity=severity, traceback=True)
def log_request_headers(debug=False):
"""Write request headers to the cherrypy error log."""
h = [' %s: %s' % (k, v) for k, v in cherrypy.serving.request.header_list]
cherrypy.log('\nRequest Headers:\n' + '\n'.join(h), 'HTTP')
def log_hooks(debug=False):
"""Write request.hooks to the cherrypy error log."""
request = cherrypy.serving.request
msg = []
# Sort by the standard points if possible.
from cherrypy import _cprequest
points = _cprequest.hookpoints
for k in request.hooks.keys():
if k not in points:
points.append(k)
for k in points:
msg.append(' %s:' % k)
v = request.hooks.get(k, [])
v.sort()
for h in v:
msg.append(' %r' % h)
cherrypy.log('\nRequest Hooks for ' + cherrypy.url() +
':\n' + '\n'.join(msg), 'HTTP')
def redirect(url='', internal=True, debug=False):
"""Raise InternalRedirect or HTTPRedirect to the given url."""
if debug:
cherrypy.log('Redirecting %sto: %s' %
({True: 'internal ', False: ''}[internal], url),
'TOOLS.REDIRECT')
if internal:
raise cherrypy.InternalRedirect(url)
else:
raise cherrypy.HTTPRedirect(url)
def trailing_slash(missing=True, extra=False, status=None, debug=False):
"""Redirect if path_info has (missing|extra) trailing slash."""
request = cherrypy.serving.request
pi = request.path_info
if debug:
cherrypy.log('is_index: %r, missing: %r, extra: %r, path_info: %r' %
(request.is_index, missing, extra, pi),
'TOOLS.TRAILING_SLASH')
if request.is_index is True:
if missing:
if not pi.endswith('/'):
new_url = cherrypy.url(pi + '/', request.query_string)
raise cherrypy.HTTPRedirect(new_url, status=status or 301)
elif request.is_index is False:
if extra:
# If pi == '/', don't redirect to ''!
if pi.endswith('/') and pi != '/':
new_url = cherrypy.url(pi[:-1], request.query_string)
raise cherrypy.HTTPRedirect(new_url, status=status or 301)
def flatten(debug=False):
"""Wrap response.body in a generator that recursively iterates over body.
This allows cherrypy.response.body to consist of 'nested generators';
that is, a set of generators that yield generators.
"""
def flattener(input):
numchunks = 0
for x in input:
if not is_iterator(x):
numchunks += 1
yield x
else:
for y in flattener(x):
numchunks += 1
yield y
if debug:
cherrypy.log('Flattened %d chunks' % numchunks, 'TOOLS.FLATTEN')
response = cherrypy.serving.response
response.body = flattener(response.body)
def accept(media=None, debug=False):
"""Return the client's preferred media-type (from the given Content-Types).
If 'media' is None (the default), no test will be performed.
If 'media' is provided, it should be the Content-Type value (as a string)
or values (as a list or tuple of strings) which the current resource
can emit. The client's acceptable media ranges (as declared in the
Accept request header) will be matched in order to these Content-Type
values; the first such string is returned. That is, the return value
will always be one of the strings provided in the 'media' arg (or None
if 'media' is None).
If no match is found, then HTTPError 406 (Not Acceptable) is raised.
Note that most web browsers send */* as a (low-quality) acceptable
media range, which should match any Content-Type. In addition, "...if
no Accept header field is present, then it is assumed that the client
accepts all media types."
Matching types are checked in order of client preference first,
and then in the order of the given 'media' values.
Note that this function does not honor accept-params (other than "q").
"""
if not media:
return
if isinstance(media, text_or_bytes):
media = [media]
request = cherrypy.serving.request
# Parse the Accept request header, and try to match one
# of the requested media-ranges (in order of preference).
ranges = request.headers.elements('Accept')
if not ranges:
# Any media type is acceptable.
if debug:
cherrypy.log('No Accept header elements', 'TOOLS.ACCEPT')
return media[0]
else:
# Note that 'ranges' is sorted in order of preference
for element in ranges:
if element.qvalue > 0:
if element.value == '*/*':
# Matches any type or subtype
if debug:
cherrypy.log('Match due to */*', 'TOOLS.ACCEPT')
return media[0]
elif element.value.endswith('/*'):
# Matches any subtype
mtype = element.value[:-1] # Keep the slash
for m in media:
if m.startswith(mtype):
if debug:
cherrypy.log('Match due to %s' % element.value,
'TOOLS.ACCEPT')
return m
else:
# Matches exact value
if element.value in media:
if debug:
cherrypy.log('Match due to %s' % element.value,
'TOOLS.ACCEPT')
return element.value
# No suitable media-range found.
ah = request.headers.get('Accept')
if ah is None:
msg = 'Your client did not send an Accept header.'
else:
msg = 'Your client sent this Accept header: %s.' % ah
msg += (' But this resource only emits these media types: %s.' %
', '.join(media))
raise cherrypy.HTTPError(406, msg)
class MonitoredHeaderMap(_httputil.HeaderMap):
def transform_key(self, key):
self.accessed_headers.add(key)
return super(MonitoredHeaderMap, self).transform_key(key)
def __init__(self):
self.accessed_headers = set()
super(MonitoredHeaderMap, self).__init__()
def autovary(ignore=None, debug=False):
"""Auto-populate the Vary response header based on request.header access.
"""
request = cherrypy.serving.request
req_h = request.headers
request.headers = MonitoredHeaderMap()
request.headers.update(req_h)
if ignore is None:
ignore = set(['Content-Disposition', 'Content-Length', 'Content-Type'])
def set_response_header():
resp_h = cherrypy.serving.response.headers
v = set([e.value for e in resp_h.elements('Vary')])
if debug:
cherrypy.log(
'Accessed headers: %s' % request.headers.accessed_headers,
'TOOLS.AUTOVARY')
v = v.union(request.headers.accessed_headers)
v = v.difference(ignore)
v = list(v)
v.sort()
resp_h['Vary'] = ', '.join(v)
request.hooks.attach('before_finalize', set_response_header, 95)
def convert_params(exception=ValueError, error=400):
"""Convert request params based on function annotations, with error handling.
exception
Exception class to catch.
status
The HTTP error code to return to the client on failure.
"""
request = cherrypy.serving.request
types = request.handler.callable.__annotations__
with cherrypy.HTTPError.handle(exception, error):
for key in set(types).intersection(request.params):
request.params[key] = types[key](request.params[key])
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'cherrypy.log', (['"""Status not 200"""', '"""TOOLS.ETAGS"""'], {}), "('Status not 200', 'TOOLS.ETAGS')\n", (1761, 1794), False, 'import cherrypy\n'), ((1921, 1975), 'cherrypy.log', 'cherrypy.log', (["('Setting ETag: %s' % etag)", '"""TOOLS.ETAGS"""'], {}), "('Setting ETag: %s' % etag, 'TOOLS.ETAGS')\n", (1933, 1975), False, 'import cherrypy\n'), ((4443, 4473), 'cherrypy.HTTPRedirect', 'cherrypy.HTTPRedirect', (['[]', '(304)'], {}), '([], 304)\n', (4464, 4473), False, 'import cherrypy\n'), ((4522, 4545), 'cherrypy.HTTPError', 'cherrypy.HTTPError', (['(412)'], {}), '(412)\n', (4540, 4545), False, 'import cherrypy\n'), ((10959, 11361), 'six.text_type', 'six.text_type', (['"""<html><body>\nMessage: %(error_msg)s\n<form method="post" action="do_login">\n Login: <input type="text" name="username" value="%(username)s" size="10" />\n <br />\n Password: <input type="password" name="password" size="10" />\n <br />\n <input type="hidden" name="from_page" value="%(from_page)s" />\n <br />\n <input type="submit" />\n</form>\n</body></html>"""'], {}), '(\n """<html><body>\nMessage: %(error_msg)s\n<form method="post" action="do_login">\n Login: <input type="text" name="username" value="%(username)s" size="10" />\n <br />\n Password: <input type="password" name="password" size="10" />\n <br />\n <input type="hidden" name="from_page" value="%(from_page)s" />\n <br />\n <input type="submit" />\n</form>\n</body></html>"""\n )\n', (10972, 11361), False, 'import six\n'), ((14380, 14403), 'cherrypy.HTTPError', 'cherrypy.HTTPError', (['(405)'], {}), '(405)\n', (14398, 14403), False, 'import cherrypy\n'), ((16400, 16414), 'cherrypy.url', 'cherrypy.url', ([], {}), '()\n', (16412, 16414), False, 'import cherrypy\n'), ((17687, 17730), 'cherrypy.url', 'cherrypy.url', (['pi[:-1]', 'request.query_string'], {}), '(pi[:-1], request.query_string)\n', (17699, 17730), False, 'import cherrypy\n'), ((17753, 17805), 'cherrypy.HTTPRedirect', 'cherrypy.HTTPRedirect', (['new_url'], {'status': '(status or 301)'}), '(new_url, status=status or 301)\n', (17774, 17805), False, 'import cherrypy\n'), ((14684, 14707), 'cherrypy.HTTPError', 'cherrypy.HTTPError', (['(405)'], {}), '(405)\n', (14702, 14707), False, 'import cherrypy\n'), ((20464, 20512), 'cherrypy.log', 'cherrypy.log', (['"""Match due to */*"""', '"""TOOLS.ACCEPT"""'], {}), "('Match due to */*', 'TOOLS.ACCEPT')\n", (20476, 20512), False, 'import cherrypy\n'), ((1869, 1878), 'hashlib.md5', 'md5', (['etag'], {}), '(etag)\n', (1872, 1878), False, 'from hashlib import md5\n'), ((21180, 21243), 'cherrypy.log', 'cherrypy.log', (["('Match due to %s' % element.value)", '"""TOOLS.ACCEPT"""'], {}), "('Match due to %s' % element.value, 'TOOLS.ACCEPT')\n", (21192, 21243), False, 'import cherrypy\n'), ((20861, 20924), 'cherrypy.log', 'cherrypy.log', (["('Match due to %s' % element.value)", '"""TOOLS.ACCEPT"""'], {}), "('Match due to %s' % element.value, 'TOOLS.ACCEPT')\n", (20873, 20924), False, 'import cherrypy\n')] |
benstear/pyiomica | pyiomica/utilityFunctions.py | bc26032b610fc911cc03b54115d6abdf53a56fce | '''Utility functions'''
import multiprocessing
from .globalVariables import *
def readMathIOmicaData(fileName):
'''Read text files exported by MathIOmica and convert to Python data
Parameters:
fileName: str
Path of directories and name of the file containing data
Returns:
data
Python data
Usage:
data = readMathIOmicaData("../../MathIOmica/MathIOmica/MathIOmicaData/ExampleData/rnaExample")
'''
if os.path.isfile(fileName):
with open(fileName, 'r') as tempFile:
data = tempFile.read()
data = data.replace('\n','').replace('{','(').replace('}',')').replace('->',':').replace('|>','}')
data = data.replace('<|','{').replace('^','*').replace('`','*').replace('Missing[]','"Missing[]"')
data = data.replace("\\",'')
else:
print('File not found (%s)'%(fileName))
returning = None
try:
returning = eval(data)
except:
print('Error occured while converting data (%s)'%(fileName))
return returning
def runCPUs(NumberOfAvailableCPUs, func, list_of_tuples_of_func_params):
"""Parallelize function call with multiprocessing.Pool.
Parameters:
NumberOfAvailableCPUs: int
Number of processes to create
func: function
Function to apply, must take at most one argument
list_of_tuples_of_func_params: list
Function parameters
Returns:
2d numpy.array
Results of func in a numpy array
Usage:
results = runCPUs(4, pAutocorrelation, [(times[i], data[i], allTimes) for i in range(10)])
"""
instPool = multiprocessing.Pool(processes = NumberOfAvailableCPUs)
return_values = instPool.map(func, list_of_tuples_of_func_params)
instPool.close()
instPool.join()
return np.vstack(return_values)
def createReverseDictionary(inputDictionary):
"""Efficient way to create a reverse dictionary from a dictionary.
Utilizes Pandas.Dataframe.groupby and Numpy arrays indexing.
Parameters:
inputDictionary: dictionary
Dictionary to reverse
Returns:
dictionary
Reversed dictionary
Usage:
revDict = createReverseDictionary(Dict)
"""
keys, values = np.array(list(inputDictionary.keys())), np.array(list(inputDictionary.values()))
df = pd.DataFrame(np.array([[keys[i], value] for i in range(len(keys)) for value in values[i]]))
dfGrouped = df.groupby(df.columns[1])
keys, values = list(dfGrouped.indices.keys()), list(dfGrouped.indices.values())
GOs = df.values.T[0]
return dict(zip(keys, [GOs[value].tolist() for value in values]))
def createDirectories(path):
"""Create a path of directories, unless the path already exists.
Parameters:
path: str
Path directory
Returns:
None
Usage:
createDirectories("/pathToFolder1/pathToSubFolder2")
"""
if path=='':
return None
if not os.path.exists(path):
os.makedirs(path)
return None
| [((1738, 1791), 'multiprocessing.Pool', 'multiprocessing.Pool', ([], {'processes': 'NumberOfAvailableCPUs'}), '(processes=NumberOfAvailableCPUs)\n', (1758, 1791), False, 'import multiprocessing\n')] |
deapplegate/wtgpipeline | CRNitschke/get_sextract_thresholds.py | 9693e8562022cc97bf5a96427e22965e1a5e8497 | #! /usr/bin/env python
#adam-does# runs SeeingClearly to get the seeing and rms of the image, then uses those to get sextractor thresholds for CR detection
#adam-use# use with CRNitschke pipeline
#adam-call_example# call it like ./get_sextract_thresholds.py /path/flname.fits output_file.txt
#IO stuff:
import sys ; sys.path.append('/u/ki/awright/InstallingSoftware/pythons')
###saveout = sys.stdout
saveout = sys.stdout
###logout = open('SeeingClearly_stdout.log','w')
###sys.stdout = logout
saveerr = sys.stderr
###logerr = open('SeeingClearly_stderr.log','w')
###sys.stderr = logerr
sys.stdout = sys.stderr
#the basics
import hashlib
import os
import SeeingClearly
from copy import deepcopy
def seeing_to_ft_dt(x):
y1_dt,m_dt,x1_dt= 5900, -16551.7, 0.48
min_dt= 3500
max_dt= 6000
yy_dts=y1_dt+m_dt*(x-x1_dt)
if yy_dts<min_dt:yy_dts=min_dt
if yy_dts>max_dt:yy_dts=max_dt
y1_ft,m_ft,x1_ft,min_ft= 850, -7000.0, 0.48, 450
min_ft= 450
max_ft= 1000
yy_fts=y1_ft+m_ft*(x-x1_ft)
if yy_fts<min_ft:yy_fts=min_ft
if yy_fts>max_ft:yy_fts=max_ft
return yy_fts,yy_dts
import imagetools
import glob
import astropy
from astropy.io import ascii
from numpy import asarray
if __name__ == "__main__":
args=deepcopy(sys.argv[1:])
for false_arg in ['-i', '--']:
if false_arg in args: args.remove(false_arg)
if len(args)<1:
sys.exit()
if not os.path.isfile(args[0]):
print "sys.argv[1]=",args[0]
raise Exception(args[0]+" is not a file!")
else:
fl=args[0]
fl2save=args[1]
#start tmp
print "Using SeeingClearly to get seeing for: "+fl
print "saving output to: " +fl2save
try:
FILTER=astropy.io.fits.open(fl)[0].header['FILTER']
except:
FILTER="UnknownFilt"
BASE,ending=os.path.basename(fl).split('OCF')
ending="OCF"+ending
ending=ending.replace('.fits','')
fls_dir=os.path.dirname(fl)
basename=os.path.basename(fl)
CCDnum=imagetools.GetCCD(fl)
globthis='_'+str(CCDnum)
glob_basename=basename.replace(globthis,'_*')
fls=sorted(glob.glob(fls_dir+"/"+glob_basename))
if not len(fls)==10:
raise Exception('cannot find 10 files like this from different CCDs')
#adam-old# seeing,back_rms=SeeingClearly.seeing_clearly_withplot(fls,checkplots=1,saveas='pltSeeingClearly_%s_%s' % (FILTER,BASE[:-1]+"ALL"))
import adam_stars_from_cat
import numpy
seeing,back_rms=adam_stars_from_cat.get_seeing_backrms(fls)
back_rms=numpy.array(back_rms)
ft,dt=seeing_to_ft_dt(seeing)
detect_thresh=dt/back_rms #convert to S2N ratio
filter_thresh=ft/back_rms #convert to S2N ratio
if FILTER=='W-J-B':
detect_thresh=asarray([min(170.0,detect_thresh[i]) for i in range(len(detect_thresh))])
filter_thresh=asarray([min(20.0,filter_thresh[i]) for i in range(len(filter_thresh))])
elif (detect_thresh>170.0).any() or (filter_thresh>20.0).any():
print 'checkit: filter=%s and %.2f %% of the detection thresholds are above 170.0 and %.2f %% of the filter thresholds are above 20.0' % (FILTER,(detect_thresh>170.0).mean()*100, (filter_thresh>20.0).mean()*100)
dict_out={}
dict_out['seeing']=[seeing]*10
dict_out['rms']=back_rms
dict_out['dt']=detect_thresh
dict_out['ft']=filter_thresh
dict_out['#files']=fls
t=astropy.table.Table(data=dict_out,names=['#files','rms','seeing','dt','ft'],dtype=[str,float,float,float,float])
t.write(fl2save,format="ascii.basic")
#adam-2014#detect_thresh_cap=min(detect_thresh,150.0) #cap is now set in the function seeing_to_ft_dt
#PIXSCALE=float(os.environ['PIXSCALE'])
#if seeing>PIXSCALE*2.5: #I have no check for being undersampled, should I?
#if seeing>.4:
# sys.stdout=saveout #back to printing to terminal
# ###sys.stdout.write(str(seeing))
# print "'0 "+str(back_rms)+" "+str(seeing)+" "+str(detect_thresh)+" "+str(filter_thresh)+"'"
#
#else:
# #print "exit 1;"
# #raise Exception('Seeing less than 2.5xPIXSCALE. The image is undersampled')
# #sys.stderr=saveerr #back to printing to terminal
# #sys.stderr.write('1')
# sys.stdout=saveout #back to printing to terminal
# print "0 "+str(back_rms)+" "+str(seeing)+" "+str(detect_thresh)+" "+str(filter_thresh)
| [] |
flatironinstitute/labbox | python/labbox/api/_session.py | d8b331d55a5cca543567c3b2e92bcdc02b46e799 | import time
import multiprocessing
class Session:
def __init__(self, *, labbox_config, default_feed_name: str):
self._labbox_config = labbox_config
pipe_to_parent, pipe_to_child = multiprocessing.Pipe()
self._worker_process = multiprocessing.Process(target=_run_worker_session, args=(pipe_to_parent, labbox_config, default_feed_name))
self._worker_process.start()
self._pipe_to_worker_process = pipe_to_child
self._incoming_keepalive_timestamp = time.time()
def elapsed_sec_since_incoming_keepalive(self):
return time.time() - self._incoming_keepalive_timestamp
def cleanup(self):
self._pipe_to_worker_process.send('exit')
pass
def check_for_outgoing_messages(self):
ret = []
while self._pipe_to_worker_process.poll():
msg = self._pipe_to_worker_process.recv()
if isinstance(msg, dict):
if msg['type'] == 'outgoing_messages':
ret.extend(msg['messages'])
else:
print(msg)
raise Exception('Unexpected message from worker session')
else:
print(msg)
raise Exception('Unexpected message from worker session')
return ret
def handle_message(self, msg):
if msg['type'] == 'keepAlive':
self._handle_keepalive()
else:
self._pipe_to_worker_process.send(dict(
type='incoming_message',
message=msg
))
def _handle_keepalive(self):
self._incoming_keepalive_timestamp = time.time()
def _run_worker_session(pipe_to_parent, labbox_config, default_feed_name: str):
from ._workersession import WorkerSession
WS = WorkerSession(labbox_config=labbox_config, default_feed_name=default_feed_name)
def handle_messages(msgs):
pipe_to_parent.send(dict(
type='outgoing_messages',
messages=msgs
))
WS.on_messages(handle_messages)
WS.initialize()
while True:
while pipe_to_parent.poll():
x = pipe_to_parent.recv()
if isinstance(x, str):
if x == 'exit':
WS.cleanup()
return
else:
print(x)
raise Exception('Unexpected message in _run_worker_session')
elif isinstance(x, dict):
if x['type'] == 'incoming_message':
WS.handle_message(x['message'])
else:
print(x)
raise Exception('Unexpected message in _run_worker_session')
else:
print(x)
raise Exception('Unexpected message in _run_worker_session')
WS.iterate()
time.sleep(0.05)
| [((202, 224), 'multiprocessing.Pipe', 'multiprocessing.Pipe', ([], {}), '()\n', (222, 224), False, 'import multiprocessing\n'), ((257, 369), 'multiprocessing.Process', 'multiprocessing.Process', ([], {'target': '_run_worker_session', 'args': '(pipe_to_parent, labbox_config, default_feed_name)'}), '(target=_run_worker_session, args=(pipe_to_parent,\n labbox_config, default_feed_name))\n', (280, 369), False, 'import multiprocessing\n'), ((501, 512), 'time.time', 'time.time', ([], {}), '()\n', (510, 512), False, 'import time\n'), ((1629, 1640), 'time.time', 'time.time', ([], {}), '()\n', (1638, 1640), False, 'import time\n'), ((2826, 2842), 'time.sleep', 'time.sleep', (['(0.05)'], {}), '(0.05)\n', (2836, 2842), False, 'import time\n'), ((580, 591), 'time.time', 'time.time', ([], {}), '()\n', (589, 591), False, 'import time\n')] |
GabrielDumbrava/aldryn-newsblog | aldryn_newsblog/tests/test_reversion.py | f3be5ff78e88fde532ce4c45e5eeb88d98fa6d93 | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from unittest import skipIf
try:
from django.core.urlresolvers import reverse
except ModuleNotFoundError:
from django.urls import reverse
from django.db import transaction
from aldryn_reversion.core import create_revision as aldryn_create_revision
from parler.utils.context import switch_language
import six
from . import NewsBlogTestCase
from aldryn_newsblog.cms_appconfig import NewsBlogConfig
from ..settings import ENABLE_REVERSION
if ENABLE_REVERSION:
try:
from reversion import create_revision
from reversion import default_revision_manager
except ImportError:
from reversion.revisions import create_revision
from reversion.revisions import default_revision_manager
@skipIf(not ENABLE_REVERSION, 'django-reversion not enabled')
class TestVersioning(NewsBlogTestCase):
def create_revision(self, article, content=None, language=None, **kwargs):
with transaction.atomic():
with create_revision():
for k, v in six.iteritems(kwargs):
setattr(article, k, v)
if content:
plugins = article.content.get_plugins()
plugin = plugins[0].get_plugin_instance()[0]
plugin.body = content
plugin.save()
# TODO: Cover both cases (plugin modification/recreation)
# if content:
# article.content.get_plugins().delete()
# api.add_plugin(article.content, 'TextPlugin',
# self.language, body=content)
article.save()
def revert_to(self, article, revision):
(default_revision_manager.get_for_object(article)[revision]
.revision.revert())
def test_revert_revision(self):
title1 = self.rand_str(prefix='title1_')
title2 = self.rand_str(prefix='title2_')
content0 = self.rand_str(prefix='content0_')
content1 = self.rand_str(prefix='content1_')
content2 = self.rand_str(prefix='content2_')
article = self.create_article(content=content0)
# Revision 1
self.create_revision(article, title=title1, content=content1)
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1)
self.assertContains(response, content1)
self.assertNotContains(response, content0)
# Revision 2
self.create_revision(article, title=title2, content=content2)
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title2)
self.assertContains(response, content2)
self.assertNotContains(response, content1)
# Revert to revision 1
self.revert_to(article, 1)
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1)
self.assertContains(response, content1)
self.assertNotContains(response, content0)
self.assertNotContains(response, content2)
def test_revert_translated_revision(self):
title1_en = self.rand_str(prefix='title1_en_')
title1_de = self.rand_str(prefix='title1_de_')
title2_en = self.rand_str(prefix='title2_en_')
title2_de = self.rand_str(prefix='title2_de_')
article = self.create_article()
# Revision 1
article.set_current_language('en')
self.create_revision(article, title=title1_en)
article.set_current_language('de')
self.create_revision(article, title=title1_de)
with switch_language(article, 'en'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1_en)
with switch_language(article, 'de'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1_de)
# Revision 2a (modify just EN)
article.set_current_language('en')
self.create_revision(article, title=title2_en)
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title2_en)
with switch_language(article, 'de'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1_de)
# Revision 2b (modify just DE)
article.set_current_language('de')
self.create_revision(article, title=title2_de)
with switch_language(article, 'en'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title2_en)
with switch_language(article, 'de'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title2_de)
# Revert to revision 2a (EN=2, DE=1)
self.revert_to(article, 1)
with switch_language(article, 'en'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title2_en)
with switch_language(article, 'de'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1_de)
# Revert to revision 1 (EN=1, DE=1)
self.revert_to(article, 2)
with switch_language(article, 'en'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1_en)
with switch_language(article, 'de'):
response = self.client.get(article.get_absolute_url())
self.assertContains(response, title1_de)
def test_edit_plugin_directly(self):
content0 = self.rand_str(prefix='content0_')
content1 = self.rand_str(prefix='content1_')
content2 = self.rand_str(prefix='content2_')
article = self.create_article(content=content0)
# Revision 1
self.create_revision(article, content=content1)
self.assertEqual(
len(default_revision_manager.get_for_object(article)), 1)
# Revision 2
with transaction.atomic():
plugins = article.content.get_plugins()
plugin = plugins[0].get_plugin_instance()[0]
plugin.body = content2
plugin.save()
aldryn_create_revision(article)
self.assertEqual(
len(default_revision_manager.get_for_object(article)), 2)
response = self.client.get(article.get_absolute_url())
self.assertContains(response, content2)
self.assertNotContains(response, content1)
# Revert to revision 1
self.revert_to(article, 1)
response = self.client.get(article.get_absolute_url())
self.assertContains(response, content1)
self.assertNotContains(response, content2)
def test_blog_config_recovery_accessible(self):
with transaction.atomic():
with create_revision():
new_conf = NewsBlogConfig(
namespace='test_revocery_admin_url', paginate_by=15)
new_conf.save()
new_config_version = (default_revision_manager
.get_for_object(new_conf)[0])
new_config_pk = new_conf.pk
self.assertEqual(NewsBlogConfig.objects.filter(
pk=new_config_pk).count(), 1)
new_conf.delete()
self.assertEqual(NewsBlogConfig.objects.filter(
pk=new_config_pk).count(), 0)
# check that there is a a way to access recovery view
obj = new_config_version.object_version.object
opts = obj._meta
url = reverse(
'admin:{0}_{1}_{2}'.format(
opts.app_label,
obj._meta.model_name,
'recover'),
args=[new_config_version.pk])
# ust in case check the length, but at this step either a
# NoReverseMatch should occur or other error,
# if no exception is raised, it is a good sign
self.assertGreater(len(url), 4)
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VirtualEmbryo/lumen_network | network/network.py | 35b1dadccd087c9ef234f12c2735098b82890b34 | # Library for the dynamics of a lumen network
# The lumen are 2 dimensional and symmetric and connected with 1 dimensional tubes
#
# Created by A. Mielke, 2018
# Modified by M. Le Verge--Serandour on 8/04/2019
"""
network.py conf.init
Defines the class network and associated functions
Imports
-------
Libraries : numpy, os, math
Created by A. Mielke
Modified by H. Turlier on 8/06/2018
Modified by M. Le Verge--Serandour on 8/04/2019
"""
import numpy as np
import math
import os
class network:
def __init__(self, network_folder, out_path, t_step, tube_radius = 0.01, friction = 1, swelling = False, swelling_rate=0., save_area_dat=False):
"""
Initialization of the object network
All properties needed for the simulation are read and initialized
Input
-----
network_folder : str
out_path : str, path-like
t_step : float
Time step of the simulation. Note that if the simulation is adaptative, this time step will change.
tube_radius : float, optional, default = 0.01
Radius of the tube connecting lumens. Define the condition for empty lumens.
friction : float, optional, default = 1
Friction constant for the fluid circulating through pipes.
swelling : bool, optional, default = False
Swelling option for the simulation. True if swelling is included, False otherwise.
swelling_rate : float, optional, default = 0.
Swelling rate value in case the swelling is considered. Make sure the rate is not to big to avoid non-converging simulations.
save_area_dat : bool, optional, default = False
Save area option. True if areas are saved in area.dat, False otherwise.
"""
self.network_folder = network_folder
# Reading properties of the lumen
self.gamma_lumen, self.gamma_contact, self.area = np.loadtxt(os.path.join(network_folder, 'lumen.dat'), dtype = float, usecols = [0,2,3], unpack = True)
# Reading links between two lumen
self.lumen_lumen = self.read_lumen_lumen(os.path.join(network_folder, 'lumen_lumen.dat'))
# Reading links between bridge and lumen
self.bridge_lumen, self.num_bridges = self.read_bridge_lumen(os.path.join(network_folder, 'bridge_lumen.dat'))
# Reading links between two bridges
self.bridge_bridge, self.num_bridges = self.read_bridge_bridge(os.path.join(network_folder, 'bridge_bridge.dat'), self.num_bridges)
# Surface tension ratio
self.alpha = self.gamma_contact/(2*self.gamma_lumen)
self.delta = np.full(len(self.alpha), 1) # Possibility of asymmetric lumen is not included
# Resistances
self.tube_radius = tube_radius # Radius of the tube connecting the lumen and the bridges
self.friction = friction # Friction coefficient; friction * length = resistance
# Opening angle of the lumen (angle between curvature and tube)
self.theta = self.set_theta()
# Area factor for expressing the pressure in terms of the area instead of the radius
self.area_factor = self.set_area_factor()
# Ending time: time at which only one lumen is remaining
self.end_time = 0
# Time step for the output of the area evolution
self.time_step = t_step
# Creating output file for the area evolution, events, error messages
self.save_area(start = True, out_path = out_path)
self.save_event('', start = True, out_path = out_path)
self.save_error('', start = True, out_path = out_path)
# Area distribution after only one lumen is remaining
self.final_area = []
# Current time step of the simulation
self.current_time = 0
# List of empty lumen (area < tube_radius **2)
self.empty_list = np.zeros(len(self.alpha))
# Swelling
self.swelling_bool = swelling
self.swelling_rate = swelling_rate
# Save area
self.save_area_dat = save_area_dat
############################################################################################################################
########################################################## Dynamics ########################################################
############################################################################################################################
def flux(self, t, state):
"""
Determines the flux/ area change for each lumen of the network, main function of network.py
Input
-----
self : network object
Needs to be called by a class object
t : float
Actual time step (not needed for the calculation of the flux, but required for the used integration method in network_simulation.py
state : float array
The current area of the lumens
Returns
-------
flux : float array
Contains the area change for each lumen in dt
"""
# Initialization of the array containing the area change (index == lumen ID)
flux = []
self.current_time = t
for i in range(len(self.alpha)):
flux.append(0)
# If only one lumen remains -> End of simulation, flux is zero (needed as for the integration method used, no dynamic stop is possible)
if(np.sum(self.empty_list) >= len(self.alpha) - 1):
if(self.end_time == 0):
# Setting the end time for the output file area.log
self.end_time = t
# more than one lumen remaining: calculation of the flux
else:
# Adapting network to new state: Empty lumen are removed and graph is reconnected
self.area = state
self.remove_empty_lumen()
# Area change between directly connected lumen
flux = self.flux_lumen(flux)
# Calculating artificial pressure at each bridge; linear system of equations, with flux(bridge) = 0, the bridge does not gain or loose area
pressure_bridges = self.pressure_bridges()
# Area change between lumen-bridges
flux = self.flux_bridges(flux, pressure_bridges)
# Area change due to swelling
if self.swelling_bool :
flux = self.flux_swelling(flux)
# Saving area for the time step given in the configuration file
if self.save_area_dat :
self.save_area()
self.t_old = t
if(np.abs(np.sum(flux)) > self.tube_radius ** 2):
error = 'total flux is non-zero: total flux = %f' % (np.sum(flux))
self.save_error(error)
return flux
def flux_lumen(self,flux):
"""
Determines the flux/ area change for each lumen due to the connection between lumen and lumen
Input
-----
self network object
needs to be called by a class object
flux float array
vector containing the area change for each lumen; index = lumen ID
Returns
-------
flux float array
area changes due to lumen-lumen connection added to the vector passed
"""
# for each connection between two lumen
for line in range(len(self.lumen_lumen)):
lumen_1 = int (self.lumen_lumen[line][0]) # first lumen
lumen_2 = int (self.lumen_lumen[line][1]) # second lumen
# flux from lumen 2 to lumen 1
fl = (self.pressure(lumen_2) - self.pressure(lumen_1))*self.friction/self.lumen_lumen[line][2]
flux[lumen_1] += fl
flux[lumen_2] -= fl
return flux
def pressure_bridges(self):
"""
Determines the pressure at each bridge
for each bridge the total flux is 0, meaning that the bridge does not gain or loose area
this gives a linear equation system, which can be solved
The connections are taken from the files bridge_lumen.dat and bridge_bridge.dat
For Information about the equations see the documentation to the code
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
pressure_bridges : float array
Pressure at each bridge
"""
R_sum = np.zeros(self.num_bridges, dtype = float) # sum of the resistences around one bridge
P_over_R_sum = np.zeros(self.num_bridges, dtype = float) # sum of pressure over resistance between one bridge and all directly connected lumen
matrix_bridges = np.zeros([self.num_bridges, self.num_bridges], dtype= float) # matrix to calculate the pressure at each bridge
# For each connection between bridge and lumen
for line in self.bridge_lumen:
bridge = int(line[0])
lumen = int(line[1])
R_sum[bridge] += 1./line[2]*self.friction
P_over_R_sum[bridge] += self.pressure(lumen)/line[2]*self.friction
# For each connection between bridge and bridge
for line in self.bridge_bridge:
bridge1 = int(line[0])
bridge2 = int(line[1])
matrix_bridges[bridge1][bridge2] = 1./line[2]*self.friction
matrix_bridges[bridge2][bridge1] = 1./line[2]*self.friction
R_sum[bridge1] += 1./line[2]*self.friction
R_sum[bridge2] += 1./line[2]*self.friction
for line in range(self.num_bridges):
matrix_bridges[line][line] = -R_sum[line]
# Solving linear problem with the pressure at each bridge as solution
pressure_bridges = np.linalg.solve(matrix_bridges, -P_over_R_sum)
return pressure_bridges;
def flux_bridges(self, flux, pressure_bridges):
"""
Determines the flux/ area change for each lumen due to the connection between lumen and bridge
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
flux : float array
Area changes due to bridge-lumen connection added to the vector passed
"""
# Area change in one bridge; should be 0; calculated as control value
flux_bridge = np.zeros(self.num_bridges, dtype = float)
# For each connection between bridge and bridge
for line in self.bridge_bridge:
bridge1 = int(line[0])
bridge2 = int(line[1])
fb = (pressure_bridges[bridge2] - pressure_bridges[bridge1])*self.friction/line[2]
flux_bridge[bridge1] += fb
flux_bridge[bridge2] -= fb
# For each connection between bridge and lumen
for line in self.bridge_lumen:
bridge = int(line[0])
lumen = int(line[1])
fl = (pressure_bridges[bridge] - self.pressure(lumen))*self.friction/line[2]
flux[lumen] += fl
flux_bridge[bridge] -= fl
for i in range(len(flux_bridge)):
if (np.abs(flux_bridge[i]) > self.tube_radius ** 2):
error = 'total flux of bridge %d is non-zero: total flux = %f' % (i,flux_bridge[i])
self.save_error(error)
return flux
def flux_swelling(self, flux) :
"""
Determines the flux/ area change for each lumen due to sewlling
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
flux : float array
Area changes due to bridge-lumen connection added to the vector passed
"""
# for each lumen (lumen is the index of the lumen's area)
for lumen in range(len(self.area)) :
# if not empty
if not self.area[lumen] < 2*self.tube_radius ** 2 :
# then add the swelling contribution
flux[lumen] += self.swelling(lumen)
return flux
############################################################################################################################
###################################################### Removing Functions #####################################################
############################################################################################################################
def remove_empty_lumen(self):
"""
Determines and removes empty lumen
Calls a function to obtain a list of empty lumen and passes the list to a function to remove them and reconnect the network
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
no return
"""
empty_lumen_list = []
# Creating a list of empty lumen
empty_lumen_list = self.get_empty_lumen()
# Removing empty lumen and reconnecting the network
if (len(empty_lumen_list) > 0 ):
event = 'empty lumen: ' + ' '.join(map(str, empty_lumen_list))
#print event
self.save_event(event)
self.remove_lumen(empty_lumen_list)
return;
def remove_lumen(self, lumen_to_remove):
"""
Removes the lumen that are passed and connects the neighbors of these lumen
Input
-----
self : network object
Needs to be called by a class object
lumen_to_remove : int list
List of lumen to be removed
Returns
-------
no return
"""
# For each lumen that has to be removed
for lumen in lumen_to_remove:
neighbours = self.get_neighbours(lumen) # List of connected lumen
bridges = self.get_bridges(lumen) # List of connected bridges
self.save_event('lumen ' + str(lumen) + ' neighbours ' + str(neighbours))
self.save_event('lumen ' + str(lumen) + ' bridges ' + str(bridges))
# Lumen had two connections, this means that it disappears and the two connected parts get directly connected, the resistance for the new link is the sum of the resistance of the two previous connections
test=True
if(len(neighbours) + len(bridges) == 2):
# Lumen was connected to two lumen -> new connection between lumen and lumen
if(len(neighbours) == 2):
self.create_link([neighbours[0][0], neighbours[1][0], neighbours[0][1] + neighbours[1][1]])
#print 'lumen_lumen connexion (' + str(neighbours[0][0]) + ', ' + str(neighbours[1][0]) + ')'
# Lumen was connected to a lumen and a bridge -> new connection between lumen and bridge
if(len(neighbours) == 1 and len(bridges)==1):
self.create_bridge_lumen([bridges[0][0], neighbours[0][0], bridges[0][1] + neighbours[0][1]])
#print 'lumen_bridge connexion (' + str(bridges[0][0]) + ', ' + str(neighbours[0][0]) + ')'
# Lumen was connected to two bridges -> new connection between bridge and bridge
if(len(bridges)==2):
self.create_bridge_bridge([bridges[0][0], bridges[1][0], bridges[0][1] + bridges[1][1]])
#print 'bridge_bridge connexion (' + str(bridges[0][0]) + ', ' + str(bridges[1][0]) + ')'
self.create_bridge(neighbours, bridges, lumid=lumen)
# Lumen had more than two connections -> becomes a bridge, the resistances remain the same but the connections are changed to connections to a bridge
if(len(neighbours) + len(bridges) > 2):
self.create_bridge(neighbours, bridges, lumid=lumen)
return;
def remove_link(self, lumen_1, lumen_2):
"""
Removes a connection between two lumen
Input
-----
self : network object
Needs to be called by a class object
lumen_1 : int
First lumen of the connection
lumen_2 :
Second lumen of the connection
Returns
-------
no return
"""
# Due to data structure first lumen must be smaller than second lumen
if(lumen_1 > lumen_2):
n = lumen_1
lumen_1 = lumen_2
lumen_2 = n
# Find connection in lumen_lumen file and remove it
line = 0
# For each line in lumen_lumen until connection is found
while (line < len(self.lumen_lumen)):
# If connection is found removing it
if(self.lumen_lumen[line][0] == lumen_1 and self.lumen_lumen[line][1] == lumen_2):
event = 'link lumen %d to lumen %d removed' % (lumen_1, lumen_2)
#print event
self.save_event(event)
link = [lumen_1, lumen_2, self.lumen_lumen[line][2]]
self.lumen_lumen.remove(link)
break;
# Look at next line
else: line += 1
############################################################################################################################
###################################################### Get Functions #####################################################
############################################################################################################################
def get_empty_lumen(self):
"""
Gets the IDs of the empty lumen
Empty means that the area is smaller than the tube_radius^2
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
empty_lumen_list : int list
Contains the IDs of the empty lumens
"""
empty_lumen_list = []
# For each lumen ID
for i in range(len(self.area)):
# If area is smaller than the treshhold
if(self.area[i] < self.tube_radius ** 2 and self.empty_list[i] == 0):
self.empty_list[i] = 1
self.area[i] = 0
empty_lumen_list.append(i)
return empty_lumen_list
def get_neighbours(self, lumen):
"""
Gets the lumen that are directly connected to the lumen passed on and deletes the connections
Input
-----
self : network object
Needs to be called by a class object
lumen : int
ID of a lumen
Returns
-------
neighbour_list : int list
ID of all lumen that are directly connected to the lumen passed on
"""
neighbour_list = []
line = 0
# Going through links in lumen_lumen.dat
while line < len(self.lumen_lumen) and self.lumen_lumen[line][0] < lumen :
if self.lumen_lumen[line][1] == lumen :
neighbour_list.append([self.lumen_lumen[line][0], self.lumen_lumen[line][2]])
event = 'link lumen %d to lumen %d removed' % (self.lumen_lumen[line][0], lumen)
self.save_event(event)
link = [self.lumen_lumen[line][0], self.lumen_lumen[line][1], self.lumen_lumen[line][2]]
self.lumen_lumen.remove(link)
else : line += 1
while line < len(self.lumen_lumen) and self.lumen_lumen[line][0] < lumen :
line += 1
while(line < len(self.lumen_lumen) and self.lumen_lumen[line][0] == lumen):
neighbour_list.append([self.lumen_lumen[line][1], self.lumen_lumen[line][2]])
event = 'link lumen %d to lumen %d removed' % (lumen, self.lumen_lumen[line][1])
self.save_event(event)
link = [self.lumen_lumen[line][0], self.lumen_lumen[line][1], self.lumen_lumen[line][2]]
self.lumen_lumen.remove(link)
return neighbour_list
def get_bridges(self, lumen):
"""
Gets the bridges that are directly connected to the lumen passed on
Input
-----
self : network object
Needs to be called by a class object
lumen : int
ID of a lumen
Returns
-------
neighbour_list : int list
ID of all lumen that are directly connected to the lumen passed on
"""
bridge_list = []
line = 0
# Going through the links in bridge_lumen.dat
while(line < len(self.bridge_lumen)):
if (self.bridge_lumen[line][1] == lumen):
bridge_list.append([self.bridge_lumen[line][0], self.bridge_lumen[line][2]])
event = 'link bridge %d to lumen %d removed' % (self.bridge_lumen[line][0], lumen)
self.save_event(event)
self.bridge_lumen.remove(self.bridge_lumen[line])
else: line += 1
return bridge_list
############################################################################################################################
#################################################### Creating Functions ###################################################
############################################################################################################################
def create_link(self, link):
"""
Creates a link between two lumen in lumen_lumen.dat
Input
-----
self : network object
Needs to be called by a class object
link : float array
[ID lumen1, ID lumen2, length]
Returns
-------
no return
"""
# no self-loops allowed
if(len(link) == 4 and link[0] != link[1]):
# Ensuring: lumen_1 < lumen_2
if(link[0] < link[2]):
lumen_1 = link[0]
lumen_2 = link[1]
else:
lumen_1 = link[1]
lumen_2 = link[0]
length = link[2]
line = 0
# Finding line in lumen_lumen.dat, to keep the sorting
while(line < len(self.lumen_lumen) and lumen_1 > self.lumen_lumen[line][0]): line += 1
if(line < len(self.lumen_lumen) - 1):
while(line < len(self.lumen_lumen) and lumen_2 > self.lumen_lumen[line][1] and lumen_1 == self.lumen_lumen[line][0]): line += 1
# Creating the link in lumen_lumen.dat
self.lumen_lumen.append([lumen_1,lumen_2, length])
self.lumen_lumen.sort()
event = 'link lumen %d to lumen %d created' % (lumen_1,lumen_2)
self.save_event(event)
return;
def create_bridge_lumen(self, link):
"""
Creates a link between a lumen and a bridge in bridge_lumen.dat
Input
-----
self : network object
Needs to be called by a class object
link : float array
[ID bridge, ID lumen, length]
Returns
-------
no return
"""
bridge = link[0]
lumen = link[1]
length = link[2]
line = 0
# Creating the link in bridge_lumen.dat
self.bridge_lumen.append(link)
self.bridge_lumen.sort()
event = 'link bridge %d to lumen %d created' % (bridge,lumen)
self.save_event(event)
return;
def create_bridge_bridge(self, link):
"""
Creates a link between two bridges in bridge_bridge.dat
Input
-----
self : network object
Needs to be called by a class object
link : float array
[ID bridge1, ID bridge2, length]
Returns
-------
no return
"""
if(link[0] == link[1]): return;
if(link[0] < link[1]):
bridge_1 = link[0]
bridge_2 = link[1]
else:
bridge_1 = link[1]
bridge_2 = link[0]
length = link[2]
line = 0
# Creating the link in bridge_bridge.dat
self.bridge_bridge.append([bridge_1,bridge_2, length])
self.bridge_bridge.sort()
event = 'link bridge %d to bridge %d created' % (bridge_1,bridge_2)
self.save_event(event)
return;
def create_bridge(self, lumen, bridge, lumid):
"""
Creates a new bridge connected with the lumen and bridges passed on
Input
-----
self : network object
Needs to be called by a class object
lumen : int list
[[lumen ID, length], [lumen ID, length],.....]
lumen IDs to which the new bridge should be connected to
bridge : int list
[[bridge ID, length], [bridge ID, length],.....]
bridge IDs to which the new bridge should be connected to
Returns
-------
no return
"""
#####
bridge_conversionfile = os.path.join(self.network_folder,'bridgesconversion.txt')
# ID of the new bridge
bridge_number = self.num_bridges
# Bridge ID counter, contains the ID of the next new bridge
self.num_bridges += 1
event = 'new bridge %d' % (bridge_number) + ' (' + str(lumid) + ')'
self.save_event(event)
line = 0
lumen.sort()
bridge.sort()
# For each lumen that should be connected to the new bridge
for i in range(len(lumen)):
new_link = [bridge_number, lumen[i][0], lumen[i][1]]
# Create link in bridge_lumen.dat
self.create_bridge_lumen(new_link)
# For each lumen that should be connected to the new bridge
for i in range(len(bridge)):
new_link = [bridge[i][0], bridge_number, bridge[i][1]]
# Create link in bridge_bridge.dat
self.create_bridge_bridge(new_link)
open(bridge_conversionfile, 'a').write(str(bridge_number) + ' ' + str(lumid)+ '\n')
return;
############################################################################################################################
################################ Geometric Functions for area and Pressure ###############################################
############################################################################################################################
def set_theta(self):
"""
Sets the angle theta
Calculates the angle theta, angle between the lumen and the tube
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
theta : float list
Theta value for each lumen
"""
theta = []
for i in range(len(self.alpha)):
#cos = (2*self.alpha[i]-(4*self.alpha[i]**2-self.delta[i]**2+1)/(4*self.alpha[i]))/self.delta[i] ## Old version, for assymmetric lumen
#theta.append(math.acos(cos))
theta.append(np.arccos(self.alpha[i]))
return theta;
def set_area_factor(self):
"""
Sets the area factor, needed to express the pressure in terms of the area instead of the curvature radius
Input
-----
self : network object
Needs to be called by a class object
Returns
-------
area_factor : float list
Area factor for each lumen
"""
area_factor = []
for i in range(len(self.alpha)):
area_factor.append(np.sqrt((2*self.theta[i]-np.sin(2*self.theta[i]))))
return area_factor;
def opening_radius(self, lumen):
"""
Calculates the length/2 parallel to the 'tube' where the membrane is not attached for a given lumen
Input
-----
lumen : int
ID of the lumen
Returns
-------
radius : float
Length/2 of the opening radius
"""
return np.sqrt(2*self.area[lumen]/(2*self.theta[lumen]-np.sin(2*self.theta[lumen])))*np.sin(self.theta[lumen])
def get_area(self, lumen):
"""
Calculates the area in one half of the lumen (for symmetric lumen)
Input
-----
lumen : int
ID of the lumen
Returns
-------
area : float
Area/2 of the lumen
"""
area = self.area[lumen]
return area
def pressure(self,lumen):
"""
Calculates the pressure inside the lumen (for symmetric lumen)
Input
-----
lumen : int
ID of the lumen
Returns
-------
pressure : float
Pressure of the lumen
"""
area = self.get_area(lumen)
# Avoid dividing by zero
if(area < 0.1 * self.tube_radius**2 ):
error = 'division by zero in pressure: lumen ID: %d' % (lumen)
self.save_error(error)
pressure = self.gamma_lumen[lumen]*self.area_factor[lumen]/np.sqrt(area)
return pressure
############################################################################################################################
################################################# Reading Functions ########################################################
############################################################################################################################
def read_lumen_lumen(self, lumen_lumen_file):
"""
Reading the file with links between two lumens
Input
-----
lumen_lumen_file : str
File path to file with the links between two lumens
Returns
-------
lumen_lumen : float list [lumen1, lumen2, length]
Information about the links between two lumens
"""
if (os.path.getsize(lumen_lumen_file)>0): # If the file is not empty
lumen_1, lumen_2 = np.loadtxt(lumen_lumen_file, dtype = int, usecols = [0,1], unpack = True)
length = np.loadtxt(lumen_lumen_file, dtype = float, usecols = [2])
lumen_lumen = np.column_stack([lumen_1, lumen_2, length]).tolist()
else:
lumen_lumen = []
return lumen_lumen
def read_bridge_lumen(self, bridge_lumen_file):
"""
Reading the file with links between bridge and lumen
Input
-----
bridge_lumen_file : str
File path to file with the links between bridge and lumen
Returns
-------
bridge_lumen : float list [bridge, lumen, length]
Information about the links between bridge and lumen
num_bridges : int
Number of bridge_lumen links
"""
with open(bridge_lumen_file, 'r') as f:
lines = f.read().splitlines()
last_line = lines[-1]
if ('#' in last_line): # If the file is empty
bridge_lumen = []
num_bridges = 0 # number of existing bridges
else:
bridge, lumen = np.loadtxt(bridge_lumen_file, dtype = int, usecols = [0,1], unpack = True)
length = np.loadtxt(bridge_lumen_file, dtype = float, usecols = [2])
bridge_lumen = np.column_stack([bridge, lumen, length]).tolist()
num_bridges = max(bridge)+1 # number of existing bridges
return bridge_lumen, num_bridges
def read_bridge_bridge(self, bridge_bridge_file, num_bridges):
"""
Reading the file with links between two bridge
Input
-----
bridge_bridge_file : str
File path to file with the links between two bridge
Returns
-------
bridge_bridge : float list [bridge1, bridge2, length]
Information about the links between two bridge
num : int
Number of bridge_bridge links
"""
with open(bridge_bridge_file, 'r') as f:
lines = f.read().splitlines()
last_line = lines[-1]
if ('#' in last_line>0): # If the file is empty
bridge_bridge = []
num = num_bridges
else:
bridge1, bridge2 = np.loadtxt(bridge_bridge_file, dtype = int, usecols = [0,1], unpack = True)
length = np.loadtxt(bridge_bridge_file, dtype = float, usecols = [2])
bridge_bridge = np.column_stack([bridge1, bridge2, length]).tolist()
if (max(bridge2)+1 > num_bridges): num = max(bridge2)+1
return bridge_bridge, num
############################################################################################################################
################################################# Output functions #########################################################
############################################################################################################################
def save_event(self, event, start = False, out_path = ''):
"""
Saves each event in the output folder in the file event.dat
Events like a lumen disappearing, reconnections in the graph
Input
-----
event : str
Message of the event
start : boolean
True: File is created
False: the message is stored in the file
Returns
------
no return
"""
if(start):
header_event = '# Saves each event during the simulation; event is a disappearing lumen, graph reconnection \n'
self.file_event = os.path.join(out_path, 'event.dat')
fevent = open(self.file_event, 'w')
fevent.write(header_event)
fevent.close()
else:
fevent = open(self.file_event, 'a')
fevent.write('%.5f' % self.current_time)
fevent.write(' ')
fevent.write(event)
fevent.write('\n')
fevent.close()
return;
def save_error(self, error, start = False, out_path = ''):
"""
Saves errors in the output folder in the file error.dat
Errors like volume loss
Input
-----
error : string
Message of the event
start : boolean
True: File is created
False: the message is stored in the file
Returns
------
no return
"""
if(start):
header_error = '# Saves each warning like volume loss \n'
self.file_error = os.path.join(out_path, 'error.dat')
ferror = open(self.file_error, 'w')
ferror.write(header_error)
ferror.close()
else:
ferror = open(self.file_error, 'a')
ferror.write('%.5f' % self.current_time)
ferror.write(' ')
ferror.write(error)
ferror.write('\n')
ferror.close()
return;
def save_area(self, start = False, out_path = ''):
"""
Saves the volume evolution in the output folder in the file area.dat
Input
-----
start : boolean
True: File is created
False: the message is stored in the file
Returns
------
no return
"""
if(start):
header_volume = '# Saves the volume evolution of each lumen for the time step %f \n' %(self.time_step)
self.file_area = os.path.join(out_path, 'area.dat')
farea = open(self.file_area, 'w')
farea.write(header_volume)
farea.close()
self.t_old = 0
else:
farea = open(self.file_area, 'a')
farea.write('%.5f' % self.current_time)
farea.write(' ')
farea.write(' '.join(map(str, self.area)))
farea.write('\n')
farea.close()
return;
############################################################################################################################
################################################# Swelling functions #######################################################
############################################################################################################################
def swelling(self, lumen) :
"""
self.swelling(lumen)
Calculates the input flux for the area fo a given lumen, due to swelling.
Input
-----
lumen : int
Index of the lumen
"""
area = self.get_area(lumen)
theta = self.theta[lumen]
flux_swelling = self.swelling_rate * 4 * theta * np.sqrt(area)/ self.area_factor[lumen]
#print flux_swelling
return flux_swelling
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'"""bridgesconversion.txt"""'], {}), "(self.network_folder, 'bridgesconversion.txt')\n", (26442, 26488), False, 'import os\n'), ((2077, 2118), 'os.path.join', 'os.path.join', (['network_folder', '"""lumen.dat"""'], {}), "(network_folder, 'lumen.dat')\n", (2089, 2118), False, 'import os\n'), ((2270, 2317), 'os.path.join', 'os.path.join', (['network_folder', '"""lumen_lumen.dat"""'], {}), "(network_folder, 'lumen_lumen.dat')\n", (2282, 2317), False, 'import os\n'), ((2446, 2494), 'os.path.join', 'os.path.join', (['network_folder', '"""bridge_lumen.dat"""'], {}), "(network_folder, 'bridge_lumen.dat')\n", (2458, 2494), False, 'import os\n'), ((2612, 2661), 'os.path.join', 'os.path.join', (['network_folder', '"""bridge_bridge.dat"""'], {}), "(network_folder, 'bridge_bridge.dat')\n", (2624, 2661), False, 'import os\n'), ((5711, 5734), 'numpy.sum', 'np.sum', (['self.empty_list'], {}), '(self.empty_list)\n', (5717, 5734), True, 'import numpy as np\n'), ((29787, 29812), 'numpy.sin', 'np.sin', (['self.theta[lumen]'], {}), '(self.theta[lumen])\n', (29793, 29812), True, 'import numpy as np\n'), ((30876, 30889), 'numpy.sqrt', 'np.sqrt', (['area'], {}), '(area)\n', (30883, 30889), True, 'import numpy as np\n'), ((31777, 31810), 'os.path.getsize', 'os.path.getsize', (['lumen_lumen_file'], {}), '(lumen_lumen_file)\n', (31792, 31810), False, 'import os\n'), ((31873, 31941), 'numpy.loadtxt', 'np.loadtxt', (['lumen_lumen_file'], {'dtype': 'int', 'usecols': '[0, 1]', 'unpack': '(True)'}), '(lumen_lumen_file, dtype=int, usecols=[0, 1], unpack=True)\n', (31883, 31941), True, 'import numpy as np\n'), ((31968, 32022), 'numpy.loadtxt', 'np.loadtxt', (['lumen_lumen_file'], {'dtype': 'float', 'usecols': '[2]'}), '(lumen_lumen_file, dtype=float, usecols=[2])\n', (31978, 32022), True, 'import numpy as np\n'), ((33062, 33131), 'numpy.loadtxt', 'np.loadtxt', (['bridge_lumen_file'], {'dtype': 'int', 'usecols': '[0, 1]', 'unpack': '(True)'}), '(bridge_lumen_file, dtype=int, usecols=[0, 1], unpack=True)\n', (33072, 33131), True, 'import numpy as np\n'), ((33158, 33213), 'numpy.loadtxt', 'np.loadtxt', (['bridge_lumen_file'], {'dtype': 'float', 'usecols': '[2]'}), '(bridge_lumen_file, dtype=float, usecols=[2])\n', (33168, 33213), True, 'import numpy as np\n'), ((34248, 34318), 'numpy.loadtxt', 'np.loadtxt', (['bridge_bridge_file'], {'dtype': 'int', 'usecols': '[0, 1]', 'unpack': '(True)'}), '(bridge_bridge_file, dtype=int, usecols=[0, 1], unpack=True)\n', (34258, 34318), True, 'import numpy as np\n'), ((34345, 34401), 'numpy.loadtxt', 'np.loadtxt', (['bridge_bridge_file'], {'dtype': 'float', 'usecols': '[2]'}), '(bridge_bridge_file, dtype=float, usecols=[2])\n', (34355, 34401), True, 'import numpy as np\n'), ((35661, 35696), 'os.path.join', 'os.path.join', (['out_path', '"""event.dat"""'], {}), "(out_path, 'event.dat')\n", (35673, 35696), False, 'import os\n'), ((36666, 36701), 'os.path.join', 'os.path.join', (['out_path', '"""error.dat"""'], {}), "(out_path, 'error.dat')\n", (36678, 36701), False, 'import os\n'), ((37625, 37659), 'os.path.join', 'os.path.join', (['out_path', '"""area.dat"""'], {}), "(out_path, 'area.dat')\n", (37637, 37659), False, 'import os\n'), ((6969, 6981), 'numpy.sum', 'np.sum', (['flux'], {}), '(flux)\n', (6975, 6981), True, 'import numpy as np\n'), ((7074, 7086), 'numpy.sum', 'np.sum', (['flux'], {}), '(flux)\n', (7080, 7086), True, 'import numpy as np\n'), ((11750, 11772), 'numpy.abs', 'np.abs', (['flux_bridge[i]'], {}), '(flux_bridge[i])\n', (11756, 11772), True, 'import numpy as np\n'), ((28599, 28623), 'numpy.arccos', 'np.arccos', (['self.alpha[i]'], {}), '(self.alpha[i])\n', (28608, 28623), True, 'import numpy as np\n'), ((38874, 38887), 'numpy.sqrt', 'np.sqrt', (['area'], {}), '(area)\n', (38881, 38887), True, 'import numpy as np\n'), ((32053, 32096), 'numpy.column_stack', 'np.column_stack', (['[lumen_1, lumen_2, length]'], {}), '([lumen_1, lumen_2, length])\n', (32068, 32096), True, 'import numpy as np\n'), ((33245, 33285), 'numpy.column_stack', 'np.column_stack', (['[bridge, lumen, length]'], {}), '([bridge, lumen, length])\n', (33260, 33285), True, 'import numpy as np\n'), ((34434, 34477), 'numpy.column_stack', 'np.column_stack', (['[bridge1, bridge2, length]'], {}), '([bridge1, bridge2, length])\n', (34449, 34477), True, 'import numpy as np\n'), ((29229, 29254), 'numpy.sin', 'np.sin', (['(2 * self.theta[i])'], {}), '(2 * self.theta[i])\n', (29235, 29254), True, 'import numpy as np\n'), ((29757, 29786), 'numpy.sin', 'np.sin', (['(2 * self.theta[lumen])'], {}), '(2 * self.theta[lumen])\n', (29763, 29786), True, 'import numpy as np\n')] |
always-newbie161/pyprobml | scripts/upsampling_demo.py | eb70c84f9618d68235ef9ba7da147c009b2e4a80 | # Illustrate upsampling in 2d
# Code from Jason Brownlee
# https://machinelearningmastery.com/generative_adversarial_networks/
import tensorflow as tf
from tensorflow import keras
from numpy import asarray
#from keras.models import Sequential
from tensorflow.keras.models import Sequential
#from keras.layers import UpSampling2D
from tensorflow.keras.layers import UpSampling2D
X = asarray([[1, 2],
[3, 4]])
X = asarray([[1, 2, 3],
[4, 5, 6],
[7,8,9]])
print(X)
nr = X.shape[0]
nc = X.shape[1]
# reshape input data into one sample a sample with a channel
X = X.reshape((1, nr, nc, 1))
model = Sequential()
model.add(UpSampling2D(input_shape=(nr, nc, 1))) # nearest neighbor
yhat = model.predict(X)
yhat = yhat.reshape((2*nr, 2*nc))
print(yhat)
model = Sequential()
model.add(UpSampling2D(input_shape=(nc, nc, 1), interpolation='bilinear'))
yhat = model.predict(X)
yhat = yhat.reshape((2*nr, 2*nc))
print(yhat) | [((388, 413), 'numpy.asarray', 'asarray', (['[[1, 2], [3, 4]]'], {}), '([[1, 2], [3, 4]])\n', (395, 413), False, 'from numpy import asarray\n'), ((423, 465), 'numpy.asarray', 'asarray', (['[[1, 2, 3], [4, 5, 6], [7, 8, 9]]'], {}), '([[1, 2, 3], [4, 5, 6], [7, 8, 9]])\n', (430, 465), False, 'from numpy import asarray\n'), ((624, 636), 'tensorflow.keras.models.Sequential', 'Sequential', ([], {}), '()\n', (634, 636), False, 'from tensorflow.keras.models import Sequential\n'), ((785, 797), 'tensorflow.keras.models.Sequential', 'Sequential', ([], {}), '()\n', (795, 797), False, 'from tensorflow.keras.models import Sequential\n'), ((647, 684), 'tensorflow.keras.layers.UpSampling2D', 'UpSampling2D', ([], {'input_shape': '(nr, nc, 1)'}), '(input_shape=(nr, nc, 1))\n', (659, 684), False, 'from tensorflow.keras.layers import UpSampling2D\n'), ((808, 871), 'tensorflow.keras.layers.UpSampling2D', 'UpSampling2D', ([], {'input_shape': '(nc, nc, 1)', 'interpolation': '"""bilinear"""'}), "(input_shape=(nc, nc, 1), interpolation='bilinear')\n", (820, 871), False, 'from tensorflow.keras.layers import UpSampling2D\n')] |
njchj/V2RayCloudSpider | V2RaycSpider1225/src/BusinessCentralLayer/scaffold.py | 16154cf48c74fa2c8cf2f6792d2db3632501f5d6 | __all__ = ['scaffold', 'command_set']
from gevent import monkey
monkey.patch_all()
import csv
import os
import sys
import time
import shutil
from typing import List
import gevent
from src.BusinessCentralLayer.setting import logger, DEFAULT_POWER, CHROMEDRIVER_PATH, \
REDIS_MASTER, SERVER_DIR_DATABASE_CACHE, SERVER_DIR_CLIENT_DEPORT, SERVER_PATH_DEPOT_VCS, SERVER_DIR_CACHE_BGPIC, \
REDIS_SLAVER_DDT, CRAWLER_SEQUENCE, terminal_echo, SERVER_DIR_DATABASE_LOG, SERVER_DIR_SSPANEL_MINING
command_set = {
# ---------------------------------------------
# 部署接口
# ---------------------------------------------
'deploy': "部署项目（定时任务/Flask 开启与否取决于yaml配置文件）",
# ---------------------------------------------
# 调试接口
# ---------------------------------------------
"clear": "清理系统运行缓存",
"decouple": "立即唤醒一次subs_ddt链接解耦任务",
"overdue": "立即执行一次过时链接清洗任务",
"run": "[请使用spawn命令替代]立即执行一次采集任务（强制使用协程加速）",
"force_run": "[请使用spawn命令替代]强制执行采集任务",
"remain": "读取剩余订阅数量",
"ping": "测试数据库连接",
"entropy": "打印采集队列",
"exile": "执行队列运维脚本（高饱和强阻塞任务）",
"spawn": "并发执行所有在列的采集任务",
"mining": "启动一次针对STAFF host的SEO全站挖掘任务",
# ---------------------------------------------
# 随参调试接口
# ---------------------------------------------
# usage: 解析某条订阅链接 python main.py --parse https://domain/link/token?sub=3
# usage: 解析多条订阅链接 python main.py --parse https://domain/link/token?sub=3 https://domain/link/token2?sub=3
# "--parse": """解析链接。若是订阅链接，则检测节点数量并测试ping延时""",
# ---------------------------------------------
# Windows 功能接口
# ---------------------------------------------
"panel": "[for Windows] 打开桌面前端面板",
"ash": "[for Windows] 一键清洗订阅池,并将所有类型订阅转换为Clash yaml配置文件,"
"借由URL Scheme自动打开Clash并下载配置文件",
# ---------------------------------------------
# 调用示例
# ---------------------------------------------
"example": "python main.py ping"
}
class _ConfigQuarantine:
def __init__(self):
self.root = [
SERVER_DIR_CLIENT_DEPORT, SERVER_PATH_DEPOT_VCS,
SERVER_DIR_DATABASE_CACHE, SERVER_DIR_CACHE_BGPIC
]
self.flag = False
def set_up_file_tree(self, root):
"""
--/qinse/V2RaycSpider{verNum}
--BCL
--BLL
--BVL
--Database
--client_depot
--vcs.csv
--logs
--*error.log
--*runtime.log
--temp_cache
--*AnyTempCacheFile...
--*CrawlFetchHistory.txt
--fake_useragent_0.1.11.json
--*tests
"""
# 检查默认下载地址是否残缺 深度优先初始化系统文件
for child_ in root:
if not os.path.exists(child_):
self.flag = True
try:
# 初始化文件夹
if os.path.isdir(child_) or not os.path.splitext(child_)[-1]:
os.mkdir(child_)
logger.success(f"系统文件链接成功->{child_}")
# 初始化文件
else:
if child_ == SERVER_PATH_DEPOT_VCS:
try:
with open(child_, 'w', encoding='utf-8', newline='') as fpx:
csv.writer(fpx).writerow(['version', 'title'])
logger.success(f"系统文件链接成功->{child_}")
except Exception as ep:
logger.exception(f"Exception{child_}{ep}")
except Exception as ep:
logger.exception(ep)
@staticmethod
def check_config(call_driver: bool = False):
chromedriver_not_found_error = "<ScaffoldGuider> ForceRun || ChromedriverNotFound ||" \
"未查找到chromedriver驱动，请根据技术文档正确配置\n" \
">>> https://github.com/QIN2DIM/V2RayCloudSpider"
# if not all(SMTP_ACCOUNT.values()):
# logger.warning('您未正确配置<通信邮箱>信息(SMTP_ACCOUNT)')
# if not SERVERCHAN_SCKEY:
# logger.warning("您未正确配置<Server酱>的SCKEY")
if not all([REDIS_SLAVER_DDT.get("host"), REDIS_SLAVER_DDT.get("password")]):
logger.warning('您未正确配置<Redis-Slave> 本项目资源拷贝功能无法使用，但不影响系统正常运行。')
if not all([REDIS_MASTER.get("host"), REDIS_MASTER.get("password")]):
logger.error("您未正确配置<Redis-Master> 此配置为“云彩姬”的核心组件，请配置后重启项目！")
sys.exit()
# 当需要调用的接口涉及到driver操作时抛出
if call_driver and not os.path.exists(CHROMEDRIVER_PATH):
logger.error(chromedriver_not_found_error)
sys.exit()
def run(self):
try:
if [cq for cq in reversed(self.root) if not os.path.exists(cq)]:
logger.warning('系统文件残缺！')
logger.debug("启动<工程重构>模块...")
self.set_up_file_tree(self.root)
self.check_config()
finally:
if self.flag:
logger.success(">>> 运行环境链接完成，请重启项目")
logger.warning(">>> 提醒您正确配置Chrome及对应版本的ChromeDriver")
sys.exit()
_ConfigQuarantine().run()
class _ScaffoldGuider:
# __slots__ = list(command_set.keys())
def __init__(self):
# 脚手架公开接口
self.scaffold_ruler = [i for i in self.__dir__() if i.startswith('_scaffold_')]
self.command2solution = {
'deploy': self._scaffold_deploy,
'decouple': self._scaffold_decouple,
'overdue': self._scaffold_overdue,
'spawn': self._scaffold_spawn,
# 'run': self._scaffold_run,
# 'force_run': self._scaffold_force_run,
'remain': self._scaffold_remain,
'ping': self._scaffold_ping,
'panel': self._scaffold_panel,
'entropy': self._scaffold_entropy,
'ash': self._scaffold_ash,
'mining': self._scaffold_mining,
}
def startup(self, driver_command_set: List[str]):
"""
仅支持单进程使用
@param driver_command_set: 在空指令时列表仅有1个元素，表示启动路径
@return:
"""
# logger.info(f">>> {' '.join(driver_command_set)}")
# -------------------------------
# TODO 优先级0：预处理指令集
# -------------------------------
# CommandId or List[CommandId]
driver_command: List[str] = []
# 未输入任何指令 列出脚手架简介
if len(driver_command_set) == 1:
print("\n".join([f">>> {menu[0].ljust(20, '-')}|| {menu[-1]}" for menu in command_set.items()]))
return True
# 输入立即指令 转译指令
if len(driver_command_set) == 2:
driver_command = [driver_command_set[-1].lower(), ]
# 输入指令集 转译指令集
elif len(driver_command_set) > 2:
driver_command = list({command.lower() for command in driver_command_set[1:]})
# 捕获意料之外的情况
if not isinstance(driver_command, list):
return True
# -------------------------------
# TODO 优先级1：解析运行参数
# -------------------------------
# TODO --help 帮助菜单（继续完善相关功能）
# 使用该参数时系统不解析运行指令
if '--help' in driver_command:
logger.info(">>>GuiderHelp || 帮助菜单")
driver_command.remove("--help")
for command_ in driver_command:
introduction = command_set.get(command_)
if introduction:
print(f"> {command_.ljust(20, '-')}|| {introduction}")
else:
print(f"> {command_}指令不存在")
return True
# 智能采集 解析目标
if '--parse' in driver_command:
driver_command.remove('--parse')
task_list = []
for url_ in reversed(driver_command):
if url_.startswith("http") or url_.startswith("ssr") or url_.startswith("vmess"):
task_list.append(gevent.spawn(self._scaffold_parse, url=url_))
gevent.joinall(task_list)
return True
# 清除系统缓存
if 'clear' in driver_command:
driver_command.remove('clear')
self._scaffold_clear()
return True
# -------------------------------
# TODO 优先级2：运行单线程指令
# -------------------------------
# 协程任务队列
task_list = []
# 测试数据库连接
while driver_command.__len__() > 0:
_pending_command = driver_command.pop()
try:
task_list.append(gevent.spawn(self.command2solution[_pending_command]))
except KeyError as e:
logger.warning(f'脚手架暂未授权指令<{_pending_command}> {e}')
# 并发执行以上指令
gevent.joinall(task_list)
# -------------------------------
# TODO 优先级3：自定义参数部署（阻塞线程）
# -------------------------------
if 'deploy' in driver_command:
self._scaffold_deploy()
@staticmethod
def _scaffold_deploy():
# logger.info("<ScaffoldGuider> Deploy || MainProcess")
from src.BusinessCentralLayer.middleware.interface_io import SystemInterface
SystemInterface.run(deploy_=True)
@staticmethod
def _scaffold_clear():
_permission = {
"logs": input(terminal_echo("是否清除所有运行日志[y]?", 2)),
"cache": input(terminal_echo("是否清除所有运行缓存[y]?", 2))
}
# 清除日志 ~/database/logs
if os.path.exists(SERVER_DIR_DATABASE_LOG) and _permission['logs'].startswith("y"):
history_logs = os.listdir(SERVER_DIR_DATABASE_LOG)
for _log_file in history_logs:
if len(_log_file.split('.')) > 2:
_log_path = os.path.join(SERVER_DIR_DATABASE_LOG, _log_file)
os.remove(_log_path)
terminal_echo(f"清除运行日志-->{_log_path}", 3)
# 清除运行缓存 ~/database/
if _permission['cache'].startswith("y"):
cache_blocks = {
# ~/database/temp_cache/
SERVER_DIR_DATABASE_CACHE,
# ~/database/staff_hosts/
SERVER_DIR_SSPANEL_MINING,
}
for block in cache_blocks:
# 扫描文件
if os.path.exists(block):
_files = [os.path.join(block, i) for i in os.listdir(block)]
# 清除文件
for _file in _files:
if os.path.isfile(_file):
os.remove(_file)
else:
shutil.rmtree(_file)
os.mkdir(_file)
terminal_echo(f"清除运行缓存-->{_file}", 3)
terminal_echo("系统缓存文件清理完毕", 1)
@staticmethod
def _scaffold_decouple():
logger.info("<ScaffoldGuider> Decouple || General startup")
from src.BusinessLogicLayer.plugins.accelerator import SubscribesCleaner
SubscribesCleaner(debug=True).interface(power=DEFAULT_POWER)
@staticmethod
def _scaffold_overdue():
logger.info("<ScaffoldGuider> Overdue || Redis DDT")
from src.BusinessCentralLayer.middleware.interface_io import SystemInterface
SystemInterface.ddt()
@staticmethod
def _scaffold_spawn():
_ConfigQuarantine.check_config(call_driver=True)
logger.info("<ScaffoldGuider> Spawn || MainCollector")
from src.BusinessLogicLayer.cluster.slavers import __entropy__
from src.BusinessLogicLayer.plugins.accelerator import booster
booster(docker=__entropy__, silence=True, power=DEFAULT_POWER, assault=True)
@staticmethod
def _scaffold_run():
_ConfigQuarantine.check_config(call_driver=True)
logger.info("<ScaffoldGuider> Run || MainCollector")
from src.BusinessCentralLayer.middleware.interface_io import SystemInterface
SystemInterface.run(deploy_=False)
@staticmethod
def _scaffold_force_run():
_ConfigQuarantine.check_config(call_driver=True)
logger.info("<ScaffoldGuider> ForceRun || MainCollector")
from src.BusinessLogicLayer.plugins.accelerator import ForceRunRelease
ForceRunRelease(task_docker=CRAWLER_SEQUENCE).interface()
@staticmethod
def _scaffold_remain():
from src.BusinessCentralLayer.middleware.subscribe_io import select_subs_to_admin
tracer = [f"{tag[0]}\n采集类型：{info_[0]}\n存活数量：{tag[-1]}" for info_ in
select_subs_to_admin(select_netloc=None, _debug=False)['info'].items() for tag in info_[-1].items()]
for i, tag in enumerate(tracer):
print(f">>> [{i + 1}/{tracer.__len__()}]{tag}")
@staticmethod
def _scaffold_ping():
from src.BusinessCentralLayer.middleware.redis_io import RedisClient
logger.info(f"<ScaffoldGuider> Ping || {RedisClient().test()}")
@staticmethod
def _scaffold_parse(url, _unused_mode: str = "subscribe"):
logger.info(f">>> PARSE --> {url}")
from src.BusinessLogicLayer.plugins.accelerator import cleaner
# 检查路径完整性
if not os.path.exists(SERVER_DIR_DATABASE_CACHE):
os.mkdir(SERVER_DIR_DATABASE_CACHE)
# 调取API解析链接
result = cleaner.subs2node(url)
if result and isinstance(result, dict):
_, info, nodes = result.values()
# 节点数量 减去无效的注释项
_unused_node_num = nodes.__len__() - 2 if nodes.__len__() - 2 >= 0 else 0
token_ = '' if info.get('token') is None else info.get('token')
# 缓存数据
cache_sub2node = os.path.join(SERVER_DIR_DATABASE_CACHE, f'sub2node_{token_}.txt')
with open(cache_sub2node, 'w', encoding="utf8") as f:
for node in nodes:
f.write(f"{node}\n")
# 自动打开缓存文件，仅在parse一个链接时启用
# os.startfile(cache_sub2node)
cleaner.node2detail(nodes[0])
else:
return False
@staticmethod
def _scaffold_panel():
from src.BusinessCentralLayer.middleware.interface_io import SystemInterface
SystemInterface.system_panel()
@staticmethod
def _scaffold_entropy(_debug=False):
from src.BusinessLogicLayer.cluster.slavers import __entropy__
for i, host_ in enumerate(__entropy__):
print(f">>> [{i + 1}/{__entropy__.__len__()}]{host_['name']}")
print(f"注册链接: {host_['register_url']}")
print(f"存活周期: {host_['life_cycle']}天")
print(f"采集类型: {'&'.join([f'{j[0].lower()}' for j in host_['hyper_params'].items() if j[-1]])}\n")
@staticmethod
def _scaffold_exile(task_sequential=4):
logger.debug(f"<ScaffoldGuider> Exile[0/{task_sequential}] || Running scaffold exile...")
time.sleep(0.3)
# task1: 检查队列任务
logger.debug(f"<ScaffoldGuider> Exile[1/{task_sequential}] || Checking the task queue...")
time.sleep(0.3)
_ScaffoldGuider._scaffold_entropy(_debug=True)
# logger.success(f">>> [Mission Completed] || entropy")
# task2: decouple
logger.debug(f"<ScaffoldGuider> Exile[2/{task_sequential}] || Cleaning the subscribe pool...")
time.sleep(0.3)
_ScaffoldGuider._scaffold_decouple()
# logger.success(f">>> [Mission Completed] || decouple")
# task3: overdue
logger.debug(f"<ScaffoldGuider> Exile[3/{task_sequential}] || Cleaning timed out subscribes...")
time.sleep(0.3)
_ScaffoldGuider._scaffold_overdue()
# logger.success(">>> [Mission Completed] || overdue")
# finally: print task-queue， remaining subscribes
logger.debug(f"<ScaffoldGuider> Exile[{task_sequential}/{task_sequential}] || Outputting debug data...")
_ScaffoldGuider._scaffold_entropy()
_ScaffoldGuider._scaffold_remain()
logger.success("<ScaffoldGuider> Exile[Mission Completed] || exile")
@staticmethod
@logger.catch()
def _scaffold_ash():
"""
无尽套娃
"""
from src.BusinessLogicLayer.apis import scaffold_api
logger.info("<ScaffoldGuider> ash | Clash订阅堆一键生成脚本")
# --------------------------------------------------
# 参数清洗
# --------------------------------------------------
if 'win' not in sys.platform:
return
# --------------------------------------------------
# 运行脚本
# --------------------------------------------------
return scaffold_api.ash(debug=True, decouple=True)
@staticmethod
def _scaffold_mining():
"""
“国外”服务器：直接运行
大陆主机：开启代理后运行
:return:
"""
from src.BusinessLogicLayer.apis.staff_mining import staff_api
use_collector = staff_api.is_first_run()
classify_dir, staff_info = staff_api.go(
debug=False,
silence=True,
power=os.cpu_count() * 2,
identity_recaptcha=False,
use_collector=use_collector,
use_checker=True,
use_generator=False,
)
staff_api.refresh_cache(mode='de-dup')
print(f"\n\nSTAFF INFO\n{'_' * 32}")
for element in staff_info.items():
for i, tag in enumerate(element[-1]):
print(f">>> [{i + 1}/{len(element[-1])}]{element[0]}: {tag}")
print(f">>> 文件导出目录: {classify_dir}")
scaffold = _ScaffoldGuider()
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daniestevez/gr-csp | python/swap_header.py | 0a10e4d2e5cf4a51256e5dc72aa42f8d3d54c232 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2016 Daniel Estevez <daniel@destevez.net>.
#
# This is free and unencumbered software released into the public domain.
#
# Anyone is free to copy, modify, publish, use, compile, sell, or
# distribute this software, either in source code form or as a compiled
# binary, for any purpose, commercial or non-commercial, and by any
# means.
#
# In jurisdictions that recognize copyright laws, the author or authors
# of this software dedicate any and all copyright interest in the
# software to the public domain. We make this dedication for the benefit
# of the public at large and to the detriment of our heirs and
# successors. We intend this dedication to be an overt act of
# relinquishment in perpetuity of all present and future rights to this
# software under copyright law.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
# IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
# OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
# ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
#
# For more information, please refer to <http://unlicense.org>
#
import numpy
from gnuradio import gr
import pmt
import array
class swap_header(gr.basic_block):
"""
docstring for block swap_header
"""
def __init__(self):
gr.basic_block.__init__(self,
name="swap_crc",
in_sig=[],
out_sig=[])
self.message_port_register_in(pmt.intern('in'))
self.set_msg_handler(pmt.intern('in'), self.handle_msg)
self.message_port_register_out(pmt.intern('out'))
def handle_msg(self, msg_pmt):
msg = pmt.cdr(msg_pmt)
if not pmt.is_u8vector(msg):
print "[ERROR] Received invalid message type. Expected u8vector"
return
packet = array.array("B", pmt.u8vector_elements(msg))
header = packet[:4]
header.reverse()
packet = header + packet[4:]
msg_pmt = pmt.cons(pmt.PMT_NIL, pmt.init_u8vector(len(packet), bytearray(packet)))
self.message_port_pub(pmt.intern('out'), msg_pmt)
| [] |
gleenn/dfplayer | start.py | dd390a6f54b3bd8b2a3397fddd6caacfba01b29d | #!/usr/bin/python
#
# Start dfplayer.
import argparse
import os
import shutil
import subprocess
import sys
import time
_PROJ_DIR = os.path.dirname(__file__)
def main():
os.chdir(_PROJ_DIR)
os.environ['LD_LIBRARY_PATH'] = '/lib:/usr/lib:/usr/local/lib'
arg_parser = argparse.ArgumentParser(description='Start player')
arg_parser.add_argument('--gdb', action='store_true')
arg_parser.add_argument('--no-reset', action='store_true')
arg_parser.add_argument('--disable-net', action='store_true')
arg_parser.add_argument('--mpd', action='store_true')
arg_parser.add_argument('--disable-fin', action='store_true')
arg_parser.add_argument('--max', action='store_true')
arg_parser.add_argument('--no-sound', action='store_true')
arg_parser.add_argument('--no-sound-config', action='store_true')
arg_parser.add_argument('--prod', action='store_true')
arg_parser.add_argument('--enable-kinect', action='store_true')
args = arg_parser.parse_args()
if args.prod:
print 'dfplayer is sleeping for 30 seconds before startup'
time.sleep(30)
if not args.no_sound_config and not args.no_sound:
shutil.copyfile(
'dfplayer/asoundrc.sample', '/home/' + os.getlogin() + '/.asoundrc')
params = ['env/bin/dfplayer', '--listen=0.0.0.0:8081']
if args.no_reset:
params.append('--no-reset')
if args.no_sound:
params.append('--no-sound')
if args.disable_net:
params.append('--disable-net')
if args.disable_fin:
params.append('--disable-fin')
if args.enable_kinect or args.prod:
params.append('--enable-kinect')
if args.mpd:
params.append('--mpd')
if args.max or args.prod:
params.append('--max')
try:
if args.gdb:
subprocess.check_call(
['gdb', '-ex', 'run', '--args', 'env/bin/python'] + params)
#['gdb', '--args', 'env/bin/python'] + params)
else:
subprocess.check_call(params)
except KeyboardInterrupt:
print 'Player is exiting via KeyboardInterrupt'
except Exception, err:
print sys.exc_info()[0]
if args.prod:
print 'dfplayer has exited and start.py script is now sleeping'
time.sleep(3600)
main()
| [] |
Finnder/Console-Based-Story-Game | Game_Mechanics.py | fe5341faf82783880872560d43d286e917f5e3d7 | def attack():
pass
def defend():
pass
def pass_turn():
pass
def use_ability_One(kit):
pass
def use_ability_Two(kit):
pass
def end_Of_Battle():
pass | [] |
Pougnator/Prometheus | AIY/voice/cloudspeech_demo.py | d7c59f3a97b4f60958f130741ccc16b81d65f505 | #!/usr/bin/env python3
# Copyright 2017 Google Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""A demo of the Google CloudSpeech recognizer."""
import aiy.audio
import aiy.cloudspeech
import aiy.voicehat
import aiy.i18n
import aiy.audio
CONFIRM_SOUND_PATH = '/home/pi/Music/R2D2/R2_Understood.wav'
CONFUSED_SOUND_PATH = '/home/pi/Music/R2D2/R2_Confused.wav'
UNRECOGNISED_SOUND_PATH = '/home/pi/Music/R2D2/R2_FastBip.wav'
def main():
status_ui = aiy.voicehat.get_status_ui()
status_ui.status('starting')
aiy.i18n.set_language_code("fr-FR")
recognizer = aiy.cloudspeech.get_recognizer()
recognizer.expect_phrase('allumer le feu')
recognizer.expect_phrase('éteindre')
recognizer.expect_phrase('clignotter')
recognizer.expect_phrase('cuir')
recognizer.expect_phrase('R2')
button = aiy.voicehat.get_button()
led = aiy.voicehat.get_led()
aiy.audio.get_recorder().start()
while True:
status_ui.status('ready')
print('Press the button and speak')
button.wait_for_press()
aiy.voicehat.get_status_ui().set_trigger_sound_wave('/home/pi/Music/R2D2/hotword.wav')
status_ui.status('listening')
WaitingForHotword = True
while WaitingForHotword == True:
print('Say the hotword to start')
hotword = recognizer.recognize()
if not hotword:
print('I recognised nothing ... looping')
else:
if ('R2') in hotword:
WaitingForHotword = False
print('Playing a test sound...')
aiy.audio.play_wave(CONFIRM_SOUND_PATH)
print('Listening...')
text = recognizer.recognize()
if not text:
print('Sorry, I did not hear you.')
aiy.audio.play_wave(CONFUSED_SOUND_PATH)
else:
WaitingForHotword = True
print('You said "', text, '"')
if 'allumer le feu' in text:
led.set_state(aiy.voicehat.LED.ON)
elif 'éteindre' in text:
led.set_state(aiy.voicehat.LED.OFF)
elif 'clignotter' in text:
led.set_state(aiy.voicehat.LED.BLINK)
elif 'cuir' in text:
# led.set_state(aiy.voicehat.LED.BLINK)
aiy.audio.say('cuir cuir cuir moustache')
elif 'goodbye' in text:
break
else: aiy.audio.play_wave(UNRECOGNISED_SOUND_PATH)
else: print('Hotword not detected .... looping')
if __name__ == '__main__':
main()
| [] |
lime-j/YTMT-Strategy-1 | options/base_option.py | aacc38c4e61b91e187cac81aa95500e0422d4d0f | import argparse
import models
model_names = sorted(name for name in models.__dict__
if name.islower() and not name.startswith("__")
and callable(models.__dict__[name]))
class BaseOptions():
def __init__(self):
self.parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
self.initialized = False
def initialize(self):
# experiment specifics
self.parser.add_argument('--name', type=str, default=None,
help='name of the experiment. It decides where to store samples and models')
self.parser.add_argument('--gpu_ids', type=str, default='0', help='gpu ids: e.g. 0 0,1,2, 0,2. use -1 for CPU')
self.parser.add_argument('--model', type=str, default='errnet_model', help='chooses which model to use.')
self.parser.add_argument('--checkpoints_dir', type=str, default='./checkpoints', help='models are saved here')
self.parser.add_argument('--resume', '-r', action='store_true', help='resume from checkpoint')
self.parser.add_argument('--resume_epoch', '-re', type=int, default=None,
help='checkpoint to use. (default: latest')
self.parser.add_argument('--seed', type=int, default=2018, help='random seed to use. Default=2018')
self.parser.add_argument('--supp_eval', action='store_true', help='supplementary evaluation')
self.parser.add_argument('--start_now', action='store_true', help='supplementary evaluation')
self.parser.add_argument('--testr', action='store_true', help='test for reflections')
self.parser.add_argument('--select', type=str, default=None)
# for setting input
self.parser.add_argument('--serial_batches', action='store_true',
help='if true, takes images in order to make batches, otherwise takes them randomly')
self.parser.add_argument('--nThreads', default=8, type=int, help='# threads for loading data')
self.parser.add_argument('--max_dataset_size', type=int, default=None,
help='Maximum number of samples allowed per dataset. If the dataset directory contains more than max_dataset_size, only a subset is loaded.')
# for display
self.parser.add_argument('--no-log', action='store_true', help='disable tf logger?')
self.parser.add_argument('--no-verbose', action='store_true', help='disable verbose info?')
self.parser.add_argument('--display_winsize', type=int, default=256, help='display window size')
self.parser.add_argument('--display_port', type=int, default=8097, help='visdom port of the web display')
self.parser.add_argument('--display_id', type=int, default=0,
help='window id of the web display (use 0 to disable visdom)')
self.parser.add_argument('--display_single_pane_ncols', type=int, default=0,
help='if positive, display all images in a single visdom web panel with certain number of images per row.')
self.initialized = True
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JanhaviSoni/Book-Recommendation-Analysis | bookstore/__init__.py | d2697e1f2eb9b9b4e0bafc0dd43d486ceb3d1707 |
from flask import Flask, Response
from flask_basicauth import BasicAuth
from flask_cors import CORS, cross_origin
import os
#from flask_admin import Admin,AdminIndexView
#from flask_admin.contrib.sqla import ModelView
from flask_sqlalchemy import SQLAlchemy as _BaseSQLAlchemy
from flask_migrate import Migrate, MigrateCommand
from flask_script import Manager
from werkzeug.exceptions import HTTPException
from flask_login import LoginManager
from itsdangerous import URLSafeSerializer
# import psycopg2
# import pymysql
# import logging
# import warnings
# warnings.filterwarnings("ignore")
# Initializing Flask App
app = Flask(__name__)
app.secret_key="Vampire"
# This video demonstrates why we use CORS in our Flask App - https://www.youtube.com/watch?v=vWl5XcvQBx0
CORS(app)
app.config.from_object("config.DevelopmentConfig")
class SQLAlchemy(_BaseSQLAlchemy):
"""
This class is defined so that we can set "pool_pre_ping" to True.
pool_pre_ping is a boolean flag, which when set to True,
will enable the connection pool 'pre-ping' feature
that tests connections for liveness upon each checkout.
This prevents from dropping of database connection with our app.
This class inherits the original SQLAlchemy class,
and nothing else is changed except pool_pre_ping flag
https://docs.sqlalchemy.org/en/13/core/pooling.html#dealing-with-disconnects
https://github.com/pallets/flask-sqlalchemy/issues/589
"""
def apply_pool_defaults(self, app, options):
super(SQLAlchemy, self).apply_pool_defaults(app, options)
options["pool_pre_ping"] = True
# Creating and Initializing db object of SQLAlchemy class
db = SQLAlchemy(app)
db.init_app(app)
migrate = Migrate(app, db, render_as_batch=True)
with app.app_context():
if db.engine.url.drivername == 'sqlite':
migrate.init_app(app, db, render_as_batch=True)
else:
migrate.init_app(app, db)
manager = Manager(app)
manager.add_command('db', MigrateCommand)
# Creating serializer object of URLSafeSerializer class for serializing session_token
serializer = URLSafeSerializer(app.secret_key)
# Here we set session_token as our user_loader.
from bookstore.client.views import client
from bookstore.admin.views import admin
app.register_blueprint(client)
app.register_blueprint(admin)
| [((631, 646), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (636, 646), False, 'from flask import Flask, Response\n'), ((781, 790), 'flask_cors.CORS', 'CORS', (['app'], {}), '(app)\n', (785, 790), False, 'from flask_cors import CORS, cross_origin\n'), ((1685, 1723), 'flask_migrate.Migrate', 'Migrate', (['app', 'db'], {'render_as_batch': '(True)'}), '(app, db, render_as_batch=True)\n', (1692, 1723), False, 'from flask_migrate import Migrate, MigrateCommand\n'), ((1887, 1899), 'flask_script.Manager', 'Manager', (['app'], {}), '(app)\n', (1894, 1899), False, 'from flask_script import Manager\n'), ((2046, 2079), 'itsdangerous.URLSafeSerializer', 'URLSafeSerializer', (['app.secret_key'], {}), '(app.secret_key)\n', (2063, 2079), False, 'from itsdangerous import URLSafeSerializer\n')] |
Bibiko/CoBL-public | cobl/lexicon/management/commands/stats236.py | 5092a0d01b7a13565c7da6bf2f6c52d648a2debe | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.core.management import BaseCommand
from cobl.lexicon.models import LanguageList, \
MeaningList, \
Meaning, \
Lexeme, \
CognateClass, \
CognateJudgement, \
LanguageClade, \
Clade
class Command(BaseCommand):
help = "Computes statistics for https://github.com/lingdb/CoBL/issues/236"\
"\nPossible parameters are: {1, 2, 3} for task number."
def add_arguments(self, parser):
parser.add_argument('task', type=int)
missing_args_message = "Please provide a task number of {1,2,3}."
def handle(self, *args, **options):
# Data to work with:
current = LanguageList.objects.get(name='Current')
jena200 = MeaningList.objects.get(name='Jena200')
languageIds = set(current.languages.values_list('id', flat=True))
meaningIds = jena200.meanings.values_list('id', flat=True)
lexemeIds = Lexeme.objects.filter(
language_id__in=languageIds,
meaning_id__in=meaningIds).values_list('id', flat=True)
cognateClassIds = CognateJudgement.objects.filter(
lexeme_id__in=lexemeIds).values_list(
'cognate_class_id', flat=True)
cognateClasses = CognateClass.objects.filter(
id__in=cognateClassIds,
root_form='').all() # Only without root_form is wanted.
if options['task'] == 1:
self.stdout.write('Task 1')
self.report(self.compute(2, cognateClasses,
meaningIds, languageIds), meaningIds)
elif options['task'] == 2:
self.stdout.write('Task 2')
task1 = self.compute(2, cognateClasses, meaningIds, languageIds)
task1CCIds = set([c.id for c in task1 if c is not None])
self.report([c for c in self.compute(
1, cognateClasses, meaningIds, languageIds)
if c is not None and c.id not in task1CCIds], meaningIds)
elif options['task'] == 3:
self.stdout.write('Task 3')
unwantedCognateClassIds = set(
[c.id for c in self.compute(1, cognateClasses,
meaningIds,
languageIds) if c is not None])
cIdcladeMap = {c.id: c for c in Clade.objects.exclude(
cladeLevel0=0).all()}
# Computing ._cognateClasses for each clade:
for _, clade in cIdcladeMap.items():
inCladeLanguageIds = set(LanguageClade.objects.filter(
clade=clade).values_list('language_id', flat=True))
lexemes = Lexeme.objects.filter(
language_id__in=languageIds & inCladeLanguageIds,
meaning_id__in=meaningIds,
not_swadesh_term=False).all()
cognateClassIds = set(CognateJudgement.objects.filter(
lexeme__in=lexemes).values_list(
'cognate_class_id', flat=True))
clade._cognateClassIds = set(CognateClass.objects.filter(
id__in=cognateClassIds - unwantedCognateClassIds,
root_form='').order_by('id').values_list('id', flat=True))
# Removing cognate class IDs we don't want:
for _, clade in cIdcladeMap.items():
cogIdCounts = {cId: 0 for cId in clade._cognateClassIds}
childIds = clade.queryChildren().values_list('id', flat=True)
for childId in childIds:
child = cIdcladeMap[childId]
for cId in child._cognateClassIds:
if cId in cogIdCounts:
cogIdCounts[cId] += 1
# Setting ._cognateClassIds for current clade:
clade._cognateClassIds = set([cId for cId, count
in cogIdCounts.items()
if count != 1])
# Updating children:
for childId in childIds:
child = cIdcladeMap[childId]
child._cognateClassIds = child._cognateClassIds & \
set([cId for cId, count
in cogIdCounts.items()
if count == 1])
# Creating .txt files:
for _, clade in cIdcladeMap.items():
# Grouping by meaning:
meaningMarkdowns = {}
for c in clade._cognateClassIds:
s = '- [ ] cog. class '\
'[%s](http://cobl.info/cognate/%s/)' % (c, c)
meanings = Meaning.objects.filter(
lexeme__cognate_class=c,
lexeme__language_id__in=languageIds,
lexeme__not_swadesh_term=False,
id__in=meaningIds).distinct().all()
s += ''.join([
' = meaning [%s](http://cobl.info/meaning/%s/)' %
(m.gloss, m.gloss) for m in meanings])
for m in meanings:
if m.gloss not in meaningMarkdowns:
meaningMarkdowns[m.gloss] = []
meaningMarkdowns[m.gloss].append(s)
# Composing markdown:
markdown = []
for k in sorted(meaningMarkdowns.keys()):
markdown += meaningMarkdowns[k]
# Writing if content:
if len(markdown) > 0:
fname = '/tmp/%s.txt' % clade.taxonsetName
self.stdout.write("Writing file '%s'." % fname)
with open(fname, 'w') as f:
f.write("\n".join(markdown)+"\n")
def compute(self, lowerBranchBound,
cognateClasses, meaningIds, languageIds):
# The computation we want to perform twice
for cognateClass in cognateClasses:
lexemeIds = CognateJudgement.objects.filter(
cognate_class_id=cognateClass.id).values_list(
'lexeme_id', flat=True)
# Need to investigate lexemes:
cladeNamesSet = set()
for lexeme in Lexeme.objects.filter(
id__in=lexemeIds,
language_id__in=languageIds,
meaning_id__in=meaningIds).all():
# Need to investigate clades:
clades = Clade.objects.filter(
id__in=LanguageClade.objects.filter(
language_id=lexeme.language_id,
language_id__in=languageIds).values_list(
'clade_id', flat=True),
cladeLevel1=0).exclude(
cladeLevel0=0 # Ignore PIE
).all()
if len(clades) > 0:
cladeNamesSet.add(', '.join([
c.cladeName for c in clades]))
# Yield interesting clades:
if len(cladeNamesSet) > lowerBranchBound:
cognateClass.bNames = ', '.join('"%s"' % n for
n in cladeNamesSet)
yield(cognateClass)
yield(None) # EOG
def report(self, cognateClasses, meaningIds):
# Print given cognateClasses:
for cognateClass in cognateClasses:
if cognateClass is None:
continue
lexemeIds = CognateJudgement.objects.filter(
cognate_class_id=cognateClass.id).values_list(
'lexeme_id', flat=True)
meaningNames = Meaning.objects.filter(
lexeme__id__in=lexemeIds,
id__in=meaningIds).distinct().values_list('gloss', flat=True)
meaningNames = ', '.join(['"%s"' % m for m in meaningNames])
self.stdout.write("Cognate set id: %s "
"meanings: %s branches: %s" %
(cognateClass.id,
meaningNames,
cognateClass.bNames))
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enabling-languages/dinka | collation/test2.py | 981ffd07e7468f692c4d17472083a3c5485987f8 | import pandas as pd
from icu import Collator, Locale, RuleBasedCollator
ddf = pd.read_csv("../word_frequency/unilex/din.txt", sep='\t', skiprows = range(2,5))
collator = Collator.createInstance(Locale('en_AU.UTF-8'))
# https://stackoverflow.com/questions/13838405/custom-sorting-in-pandas-dataframe/27009771#27009771
# https://gist.github.com/seanpue/e1cb846f676194ae77eb
def sort_pd(key=None,reverse=False):
def sorter(series):
series_list = list(series)
return [series_list.index(i)
for i in sorted(series_list,key=key,reverse=reverse)]
return sorter
sort_by_custom_dict = sort_pd(key=collator.getSortKey)
#ddf.iloc[sort_by_custom_dict(ddf.index)]
# ddf.iloc[sort_by_custom_dict(ddf['Form'])]
ddf.iloc[sort_by_custom_dict(ddf['Form'])]
#https://python3.wannaphong.com/2015/03/sort-python.html
# https://pyerror.com/detail/1316/
lexemes = ddf.Form
#lexemes2 = ddf['Form']
temp = lexemes.sort_values()
collation_rules = "&A<<aa<<<aA<<<Aa<<<AA<<ä<<<Ä<<ää<<<äÄ<<<Ää<<<ÄÄ\n&D<dh<<<dH<<<Dh<<<DH\n&E<<ee<<<eE<<<Ee<<<EE<<ë<<<Ë<<ëë<<<ëË<<<Ëë<<<ËË<ɛ<<<Ɛ<<ɛɛ<<<ɛƐ<<<Ɛɛ<<<ƐƐ<<ɛ̈<<<Ɛ̈<<ɛ̈ɛ̈<<<ɛ̈Ɛ̈<<<Ɛ̈ɛ̈<<<Ɛ̈Ɛ̈\n&G<ɣ<<<Ɣ\n&I<<ii<<<iI<<<Ii<<<II<<ï<<<Ï<<ïï<<<ïÏ<<<Ïï<<<ÏÏ\n&N<nh<<<nH<<<Nh<<<NH<ny<<<nY<<<Ny<<<NH<ŋ<<<Ŋ\n&O<<oo<<<oO<<<Oo<<<OO<<ö<<<Ö<<öö<<<öÖ<<<Öö<<<ÖÖ<ɔ<<<Ɔ<<ɔɔ<<<ɔƆ<<<Ɔɔ<<<ƆƆ<<ɔ̈<<<Ɔ̈<<ɔ̈ɔ̈<<<ɔ̈Ɔ̈<<<Ɔ̈ɔ̈<<<Ɔ̈Ɔ̈\n&T<th<<<tH<<<Th<<<TH\n&U<<uu<<<uU<<<Uu<<<UU"
custom_collator = RuleBasedCollator(collation_rules)
temp.sort_values(key=lambda x: custom_collator.getSortKey(x) )
def sort_pd(key=None,reverse=False):
def sorter(series):
series_list = list(series)
return [series_list.index(i)
for i in sorted(series_list,key=key,reverse=reverse)]
return sorter
sort_by_custom_dict = sort_pd(key=custom_collator.getSortKey) | [((1429, 1463), 'icu.RuleBasedCollator', 'RuleBasedCollator', (['collation_rules'], {}), '(collation_rules)\n', (1446, 1463), False, 'from icu import Collator, Locale, RuleBasedCollator\n'), ((196, 217), 'icu.Locale', 'Locale', (['"""en_AU.UTF-8"""'], {}), "('en_AU.UTF-8')\n", (202, 217), False, 'from icu import Collator, Locale, RuleBasedCollator\n')] |
jbronikowski/genielibs | pkgs/ops-pkg/src/genie/libs/ops/dot1x/ios/tests/test_dot1x.py | 200a34e5fe4838a27b5a80d5973651b2e34ccafb | # Python
import unittest
from copy import deepcopy
from unittest.mock import Mock
# ATS
from pyats.topology import Device
# Genie
from genie.libs.ops.dot1x.ios.dot1x import Dot1X
from genie.libs.ops.dot1x.ios.tests.dot1x_output import Dot1xOutput
# Parser
from genie.libs.parser.ios.show_dot1x import ShowDot1xAllDetail, \
ShowDot1xAllStatistics, \
ShowDot1xAllSummary, \
ShowDot1xAllCount
class test_dot1x(unittest.TestCase):
def setUp(self):
self.device = Device(name='aDevice')
self.device.os = 'ios'
self.device.custom['abstraction'] = {'order':['os']}
self.device.mapping={}
self.device.mapping['cli']='cli'
# Give the device as a connection type
# This is done in order to call the parser on the output provided
self.device.connectionmgr.connections['cli'] = self.device
def test_complete_output(self):
self.maxDiff = None
dot1x = Dot1X(device=self.device)
# Get outputs
dot1x.maker.outputs[ShowDot1xAllDetail] = \
{'': Dot1xOutput.ShowDot1xAllDetail}
dot1x.maker.outputs[ShowDot1xAllStatistics] = \
{'': Dot1xOutput.ShowDot1xAllStatistics}
dot1x.maker.outputs[ShowDot1xAllSummary] = \
{'': Dot1xOutput.ShowDot1xAllSummary}
dot1x.maker.outputs[ShowDot1xAllCount] = \
{'': Dot1xOutput.ShowDot1xAllCount}
# Learn the feature
dot1x.learn()
# Verify Ops was created successfully
self.assertEqual(dot1x.info, Dot1xOutput.Dot1x_info)
# Check Selected Attributes
self.assertEqual(dot1x.info['version'], 3)
# info - mdot1x default
self.assertEqual(dot1x.info['interfaces']['GigabitEthernet1/0/9']\
['max_start'], 3)
def test_empty_output(self):
self.maxDiff = None
dot1x = Dot1X(device=self.device)
dot1x.maker.outputs[ShowDot1xAllDetail] = \
{'': {}}
dot1x.maker.outputs[ShowDot1xAllStatistics] = \
{'': {}}
dot1x.maker.outputs[ShowDot1xAllSummary] = \
{'': {}}
dot1x.maker.outputs[ShowDot1xAllCount] = \
{'': {}}
# Learn the feature
dot1x.learn()
# Check no attribute not found
with self.assertRaises(AttributeError):
dot1x.info['version']
def test_incomplete_output(self):
self.maxDiff = None
dot1x = Dot1X(device=self.device)
# Get outputs
dot1x.maker.outputs[ShowDot1xAllDetail] = \
{'': Dot1xOutput.ShowDot1xAllDetail}
dot1x.maker.outputs[ShowDot1xAllStatistics] = \
{'': Dot1xOutput.ShowDot1xAllStatistics}
dot1x.maker.outputs[ShowDot1xAllSummary] = \
{'': Dot1xOutput.ShowDot1xAllSummary}
dot1x.maker.outputs[ShowDot1xAllCount] = \
{'': {}}
# Learn the feature
dot1x.learn()
# Delete missing specific attribute values
expect_dict = deepcopy(Dot1xOutput.Dot1x_info)
del(expect_dict['sessions'])
# Verify Ops was created successfully
self.assertEqual(dot1x.info, expect_dict)
if __name__ == '__main__':
unittest.main()
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lanl/nubhlight | script/analysis/check_transformation_matrices.py | 6c0f2abc05884538fe8e4e2e70a021b7c48a72c2 | # ======================================================================
# copyright 2020. Triad National Security, LLC. All rights
# reserved. This program was produced under U.S. Government contract
# 89233218CNA000001 for Los Alamos National Laboratory (LANL), which
# is operated by Triad National Security, LLC for the U.S. Department
# of Energy/National Nuclear Security Administration. All rights in
# the program are reserved by Triad National Security, LLC, and the
# U.S. Department of Energy/National Nuclear Security
# Administration. The Government is granted for itself and others
# acting on its behalf a nonexclusive, paid-up, irrevocable worldwide
# license in this material to reproduce, prepare derivative works,
# distribute copies to the public, perform publicly and display
# publicly, and to permit others to do so.
# ======================================================================
# Authors: Oleg Korobkin (korobkin@lanl.gov)
# Purpose:
# Provides a check of whether a coordinate transformation of the metric
# from code coordinates to Kerr-Schild coordinates produces correct
# metric, consistent with the closed form (as in e.g. Eq.(3)
# McKinney & Gammie 2004, https://arxiv.org/abs/astro-ph/0404512)
#
# Functions:
# - print_matrix
# - check_transformation_matrices
#
from math import *
import numpy as np
def print_matrix(matrix,fmt="%19.11e",tostdout=True) -> str:
"""Pretty-prints a matrix to a string (optinally, to stdout)
Parameters
----------
matrix : numpy.array([N,M])
matrix to print
fmt : str
C-style format of each element (default: "%19.11e")
tostdout : bool
output to stdout (default: true)
Returns
-------
str
formatted output string
"""
N = matrix.shape[0]
M = matrix.shape[1]
s = "["
for i in range(N):
s+= "["
for j in range(M):
s+= (fmt % matrix[i,j])
if j < M - 1: s += ", "
s+= "]"
if i < N - 1: s += ",\n "
s+="]"
if tostdout: print(s)
return s
def check_transformation_matrices(geom, a, ir, jth,
verbose=True, tol=1e-12) -> bool:
"""Transforms the metric to spherical KS and compares with analytic formula
Test 1: covariant metric, gcov, at A = {ir, jth}
1.1 sample gcov and Lambda_h2bl_cov at A
1.2 transform gcov to gks using transofmration matrices
1.3 compare to expected values at {r,th} at A
Parameters
----------
geom : dictionary
nubhlight geom object
a : Float
dimensionless Kerr spin parameter
ir : Integer
index of sample point in radial direction
jth : Integer
index of sample point in angular theta-direction
verbose : bool
output steps to stdout
tol : Float
tolerance to relative error (wrt det g)
Returns
-------
bool
True if all checks passed
Examples
--------
import hdf5_to_dict as io
hdr = io.load_hdr("dump_00000010.h5")
geom = io.load_geom(hdr,recalc=True)
check_transformation_matrices(geom, -1, 64)
"""
# sample gcov and h2bl at point A
gcov_A = geom['gcov'][ir,jth]
h2bl_A = geom['Lambda_h2bl_cov'][ir,jth]
# sample r and theta, compute BL metric-related quantities
r = geom['r'][ir,jth,0]; r2 = r*r
a2 = a*a
th= geom['th'][ir,jth,0]
sth2= sin(th)**2
Delta= r2 - 2*r + a2
Sigma= r2 + a2*cos(th)**2
A = (r2 + a2)**2 - a2*Delta*sin(th)**2
if verbose:
print ("r = %19.11e" % r)
print ("theta = %19.11e" % th)
print ("a = %19.11e" % a)
print ("Delta = %19.11e" % Delta)
print ("Sigma = %19.11e" % Sigma)
print ("A = %19.11e" % A)
# output metric
print ("gcov_A = ")
print_matrix (gcov_A)
print ("")
# output transformation matrix
print ("h2bl_A = ")
print_matrix (h2bl_A)
print ("")
# compute BL metric at A
gks_A = np.zeros([4,4])
for i in range(4):
for j in range(4):
for k in range(4):
for l in range(4):
gks_A[i,j] = gks_A[i,j] + h2bl_A[k,i]*h2bl_A[l,j]*gcov_A[k,l]
if verbose:
print ("gks_A = ")
print_matrix (gks_A)
print("")
# expected values at {r, th}
g_tt = -1. + 2.*r/Sigma
g_rr = 1. + 2.*r/Sigma
g_ff = sth2*(Sigma + a2*g_rr*sth2)
g_thth = Sigma
g_tr = 2*r/Sigma
g_tf = -2*a*r*sth2/Sigma
g_rf = -a*g_rr*sth2
det_g = -Sigma**2*sth2
if verbose:
print ("Expected:")
print (" g_tt = %19.11e" % g_tt )
print (" g_rr = %19.11e" % g_rr )
print (" g_thth = %19.11e" % g_thth)
print (" g_ff = %19.11e" % g_ff )
print (" g_tr = %19.11e" % g_tr )
print (" g_rf = %19.11e" % g_rf )
print (" g_tf = %19.11e" % g_tf )
print ("")
# check gks_A
gks_expected = np.array(
[[ g_tt, g_tr, 0.0, g_tf],
[ g_tr, g_rr, 0.0, g_rf],
[ 0.0, 0.0, g_thth, 0.0],
[ g_tf, g_rf, 0.0, g_ff]]
)
passed = True
for i in range(4):
for j in range(4):
if abs(gks_A[i,j] - gks_expected[i,j])/abs(det_g) > tol:
passed = False
if verbose:
print (f"WARNING: Significant mismatch in gks_A[{i},{j}]:")
print (" -- expected: %19.11e" % gks_expected[i,j])
print (" -- actual: %19.11e" % gks_A[i,j])
return passed
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rexor12/holobot | holobot/discord/sdk/models/channel.py | 89b7b416403d13ccfeee117ef942426b08d3651d | from dataclasses import dataclass
@dataclass
class Channel:
id: str
| [] |
claireguichon/pynet | pynet/models/braingengan.py | 92706375e61fb5cb523548303b7d04769c9de134 | # -*- coding: utf-8 -*-
##########################################################################
# NSAp - Copyright (C) CEA, 2020
# Distributed under the terms of the CeCILL-B license, as published by
# the CEA-CNRS-INRIA. Refer to the LICENSE file or to
# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html
# for details.
##########################################################################
"""
3D MRI Brain Generation with Generative Adversarial Networks (BGGAN) with
Variational Auto Encoder (VAE).
"""
# Imports
import logging
import collections
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as func
from pynet.utils import Networks
# Global parameters
logger = logging.getLogger("pynet")
@Networks.register
class BGDiscriminator(nn.Module):
""" This is the discriminator part of the BGGAN.
"""
def __init__(self, in_shape, in_channels=1, out_channels=1,
start_filts=64, with_logit=True):
""" Init class.
Parameters
----------
in_shape: uplet
the input tensor data shape (X, Y, Z).
in_channels: int, default 1
number of channels in the input tensor.
out_channels: int, default 1
number of channels in the output tensor.
start_filts: int, default 64
number of convolutional filters for the first conv.
with_logit: bool, default True
apply the logit function to the result.
"""
super(BGDiscriminator, self).__init__()
self.in_channels = in_channels
self.out_channels = out_channels
self.start_filts = start_filts
self.with_logit = with_logit
self.in_shape = in_shape
self.shapes = _downsample_shape(
self.in_shape, nb_iterations=4, scale_factor=2)
self.conv1 = nn.Conv3d(
self.in_channels, self.start_filts, kernel_size=4, stride=2,
padding=1)
self.conv2 = nn.Conv3d(
self.start_filts, self.start_filts * 2, kernel_size=4, stride=2,
padding=1)
self.bn2 = nn.BatchNorm3d(self.start_filts * 2)
self.conv3 = nn.Conv3d(
self.start_filts * 2, self.start_filts * 4, kernel_size=4,
stride=2, padding=1)
self.bn3 = nn.BatchNorm3d(self.start_filts * 4)
self.conv4 = nn.Conv3d(
self.start_filts * 4, self.start_filts * 8, kernel_size=4,
stride=2, padding=1)
self.bn4 = nn.BatchNorm3d(self.start_filts * 8)
self.conv5 = nn.Conv3d(
self.start_filts * 8, self.out_channels,
kernel_size=self.shapes[-1], stride=1, padding=0)
def forward(self, x):
logger.debug("BGGAN Discriminator...")
self.debug("input", x)
h1 = func.leaky_relu(self.conv1(x), negative_slope=0.2)
self.debug("conv1", h1)
h2 = func.leaky_relu(self.bn2(self.conv2(h1)), negative_slope=0.2)
self.debug("conv2", h2)
h3 = func.leaky_relu(self.bn3(self.conv3(h2)), negative_slope=0.2)
self.debug("conv3", h3)
h4 = func.leaky_relu(self.bn4(self.conv4(h3)), negative_slope=0.2)
self.debug("conv4", h4)
h5 = self.conv5(h4)
self.debug("conv5", h5)
if self.with_logit:
output = torch.sigmoid(h5.view(h5.size(0), -1))
self.debug("output", output)
else:
output = h5
logger.debug("Done.")
return output
def debug(self, name, tensor):
logger.debug(" {3}: {0} - {1} - {2}".format(
tensor.shape, tensor.get_device(), tensor.dtype, name))
@Networks.register
class BGEncoder(nn.Module):
""" This is the encoder part of the BGGAN.
"""
def __init__(self, in_shape, in_channels=1, start_filts=64,
latent_dim=1000):
""" Init class.
Parameters
----------
in_shape: uplet
the input tensor data shape (X, Y, Z).
in_channels: int, default 1
number of channels in the input tensor.
start_filts: int, default 64
number of convolutional filters for the first conv.
latent_dim: int, default 1000
the latent variable sizes.
"""
super(BGEncoder, self).__init__()
self.in_channels = in_channels
self.start_filts = start_filts
self.latent_dim = latent_dim
self.in_shape = in_shape
self.shapes = _downsample_shape(
self.in_shape, nb_iterations=4, scale_factor=2)
self.dense_features = np.prod(self.shapes[-1])
logger.debug("BGGAN Encoder shapes: {0}".format(self.shapes))
self.conv1 = nn.Conv3d(
self.in_channels, self.start_filts, kernel_size=4, stride=2,
padding=1)
self.conv2 = nn.Conv3d(
self.start_filts, self.start_filts * 2, kernel_size=4, stride=2,
padding=1)
self.bn2 = nn.BatchNorm3d(self.start_filts * 2)
self.conv3 = nn.Conv3d(
self.start_filts * 2, self.start_filts * 4, kernel_size=4,
stride=2, padding=1)
self.bn3 = nn.BatchNorm3d(self.start_filts * 4)
self.conv4 = nn.Conv3d(
self.start_filts * 4, self.start_filts * 8, kernel_size=4,
stride=2, padding=1)
self.bn4 = nn.BatchNorm3d(self.start_filts * 8)
self.mean = nn.Sequential(
nn.Linear(self.start_filts * 8 * self.dense_features, 2048),
nn.BatchNorm1d(2048),
nn.ReLU(),
nn.Linear(2048, self.latent_dim))
self.logvar = nn.Sequential(
nn.Linear(self.start_filts * 8 * self.dense_features, 2048),
nn.BatchNorm1d(2048),
nn.ReLU(),
nn.Linear(2048, self.latent_dim))
def forward(self, x):
logger.debug("BGGAN Encoder...")
batch_size = x.size(0)
logger.debug(" batch_size: {0}".format(batch_size))
self.debug("input", x)
h1 = func.leaky_relu(self.conv1(x), negative_slope=0.2)
self.debug("conv1", h1)
h2 = func.leaky_relu(self.bn2(self.conv2(h1)), negative_slope=0.2)
self.debug("conv2", h2)
h3 = func.leaky_relu(self.bn3(self.conv3(h2)), negative_slope=0.2)
self.debug("conv3", h3)
h4 = func.leaky_relu(self.bn4(self.conv4(h3)), negative_slope=0.2)
self.debug("conv4", h4)
mean = self.mean(h4.view(batch_size, -1))
self.debug("mean", mean)
logvar = self.logvar(h4.view(batch_size, -1))
self.debug("logvar", logvar)
std = logvar.mul(0.5).exp_()
reparametrized_noise = Variable(
torch.randn((batch_size, self.latent_dim))).to(x.device)
reparametrized_noise = mean + std * reparametrized_noise
self.debug("reparametrization", reparametrized_noise)
logger.debug("Done.")
return mean, logvar, reparametrized_noise
def debug(self, name, tensor):
logger.debug(" {3}: {0} - {1} - {2}".format(
tensor.shape, tensor.get_device(), tensor.dtype, name))
@Networks.register
class BGCodeDiscriminator(nn.Module):
""" This is the code discriminator part of the BGGAN.
"""
def __init__(self, out_channels=1, code_size=1000, n_units=4096):
""" Init class.
Parameters
----------
out_channels: int, default 1
number of channels in the output tensor.
code_size: int, default 1000
the code sier.
n_units: int, default 4096
the number of hidden units.
"""
super(BGCodeDiscriminator, self).__init__()
self.out_channels = out_channels
self.code_size = code_size
self.n_units = n_units
self.layer1 = nn.Sequential(
nn.Linear(self.code_size, self.n_units),
nn.BatchNorm1d(self.n_units),
nn.LeakyReLU(0.2, inplace=True))
self.layer2 = nn.Sequential(
nn.Linear(self.n_units, self.n_units),
nn.BatchNorm1d(self.n_units),
nn.LeakyReLU(0.2, inplace=True))
self.layer3 = nn.Linear(self.n_units, self.out_channels)
def forward(self, x):
logger.debug("BGGAN Code Discriminator...")
self.debug("input", x)
h1 = self.layer1(x)
self.debug("layer1", h1)
h2 = self.layer2(h1)
self.debug("layer2", h2)
output = self.layer3(h2)
self.debug("layer3", output)
logger.debug("Done.")
return output
def debug(self, name, tensor):
logger.debug(" {3}: {0} - {1} - {2}".format(
tensor.shape, tensor.get_device(), tensor.dtype, name))
@Networks.register
class BGGenerator(nn.Module):
""" This is the generator part of the BGGAN.
"""
def __init__(self, in_shape, out_channels=1, start_filts=64,
latent_dim=1000, mode="trilinear", with_code=False):
""" Init class.
Parameters
----------
in_shape: uplet
the input tensor data shape (X, Y, Z).
out_channels: int, default 1
number of channels in the output tensor.
start_filts: int, default 64
number of convolutional filters for the first conv.
latent_dim: int, default 1000
the latent variable sizes.
mode: str, default 'trilinear'
the interpolation mode.
with_code: bool, default False
change the architecture if code discriminator is used.
"""
super(BGGenerator, self).__init__()
self.out_channels = out_channels
self.start_filts = start_filts
self.latent_dim = latent_dim
self.in_shape = in_shape
self.mode = mode
self.with_code = with_code
self.shapes = _downsample_shape(
self.in_shape, nb_iterations=4, scale_factor=2)
self.dense_features = np.prod(self.shapes[-1])
logger.debug("BGGAN Generator shapes: {0}".format(self.shapes))
if self.with_code:
self.tp_conv1 = nn.ConvTranspose3d(
self.latent_dim, self.start_filts * 8, kernel_size=4,
stride=1, padding=0, bias=False)
else:
self.fc = nn.Linear(
self.latent_dim, self.start_filts * 8 * self.dense_features)
self.bn1 = nn.BatchNorm3d(self.start_filts * 8)
self.tp_conv2 = nn.Conv3d(
self.start_filts * 8, self.start_filts * 4, kernel_size=3,
stride=1, padding=1, bias=False)
self.bn2 = nn.BatchNorm3d(self.start_filts * 4)
self.tp_conv3 = nn.Conv3d(
self.start_filts * 4, self.start_filts * 2, kernel_size=3,
stride=1, padding=1, bias=False)
self.bn3 = nn.BatchNorm3d(self.start_filts * 2)
self.tp_conv4 = nn.Conv3d(
self.start_filts * 2, self.start_filts, kernel_size=3, stride=1,
padding=1, bias=False)
self.bn4 = nn.BatchNorm3d(self.start_filts)
self.tp_conv5 = nn.Conv3d(
self.start_filts, self.out_channels, kernel_size=3, stride=1,
padding=1, bias=False)
def forward(self, noise):
logger.debug("BGGAN Generator...")
self.debug("input", noise)
if self.with_code:
noise = noise.view(-1, self.latent_dim, 1, 1, 1)
self.debug("view", noise)
h = self.tp_conv1(noise)
self.debug("tp_conv1", h)
else:
noise = noise.view(-1, self.latent_dim)
self.debug("view", noise)
h = self.fc(noise)
self.debug("dense", h)
h = h.view(-1, self.start_filts * 8, *self.shapes[-1])
self.debug("view", h)
h = func.relu(self.bn1(h))
h = nn.functional.interpolate(
h, size=self.shapes[-2], mode=self.mode, align_corners=False)
h = self.tp_conv2(h)
h = func.relu(self.bn2(h))
self.debug("tp_conv2", h)
h = nn.functional.interpolate(
h, size=self.shapes[-3], mode=self.mode, align_corners=False)
h = self.tp_conv3(h)
h = func.relu(self.bn3(h))
self.debug("tp_conv3", h)
h = nn.functional.interpolate(
h, size=self.shapes[-4], mode=self.mode, align_corners=False)
h = self.tp_conv4(h)
h = func.relu(self.bn4(h))
self.debug("tp_conv4", h)
h = nn.functional.interpolate(
h, size=self.shapes[-5], mode=self.mode, align_corners=False)
h = self.tp_conv5(h)
self.debug("tp_conv5", h)
h = torch.tanh(h)
self.debug("output", h)
logger.debug("Done.")
return h
def debug(self, name, tensor):
logger.debug(" {3}: {0} - {1} - {2}".format(
tensor.shape, tensor.get_device(), tensor.dtype, name))
def _downsample_shape(shape, nb_iterations=1, scale_factor=2):
shape = np.asarray(shape)
all_shapes = [shape.astype(int).tolist()]
for idx in range(nb_iterations):
shape = np.floor(shape / scale_factor)
all_shapes.append(shape.astype(int).tolist())
return all_shapes
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baranshad/models | research/object_detection/core/freezable_batch_norm_test.py | aaf008855e9764f32d974e86f8e1f9cfddfafd9a | # Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Tests for object_detection.core.freezable_batch_norm."""
import numpy as np
import tensorflow as tf
from object_detection.core import freezable_batch_norm
class FreezableBatchNormTest(tf.test.TestCase):
"""Tests for FreezableBatchNorm operations."""
def _build_model(self, training=None):
model = tf.keras.models.Sequential()
norm = freezable_batch_norm.FreezableBatchNorm(training=training,
input_shape=(10,),
momentum=0.8)
model.add(norm)
return model, norm
def _train_freezable_batch_norm(self, training_mean, training_var):
model, _ = self._build_model()
model.compile(loss='mse', optimizer='sgd')
# centered on training_mean, variance training_var
train_data = np.random.normal(
loc=training_mean,
scale=training_var,
size=(1000, 10))
model.fit(train_data, train_data, epochs=4, verbose=0)
return model.weights
def _test_batchnorm_layer(
self, norm, should_be_training, test_data,
testing_mean, testing_var, training_arg, training_mean, training_var):
out_tensor = norm(tf.convert_to_tensor(test_data, dtype=tf.float32),
training=training_arg)
out = tf.keras.backend.eval(out_tensor)
out -= tf.keras.backend.eval(norm.beta)
out /= tf.keras.backend.eval(norm.gamma)
if not should_be_training:
out *= training_var
out += (training_mean - testing_mean)
out /= testing_var
np.testing.assert_allclose(out.mean(), 0.0, atol=1.5e-1)
np.testing.assert_allclose(out.std(), 1.0, atol=1.5e-1)
def test_batchnorm_freezing_training_none(self):
with self.test_session():
training_mean = 5.0
training_var = 10.0
testing_mean = -10.0
testing_var = 5.0
# Initially train the batch norm, and save the weights
trained_weights = self._train_freezable_batch_norm(training_mean,
training_var)
# Load the batch norm weights, freezing training to True.
# Apply the batch norm layer to testing data and ensure it is normalized
# according to the batch statistics.
model, norm = self._build_model(training=True)
for trained_weight, blank_weight in zip(trained_weights, model.weights):
weight_copy = blank_weight.assign(tf.keras.backend.eval(trained_weight))
tf.keras.backend.eval(weight_copy)
# centered on testing_mean, variance testing_var
test_data = np.random.normal(
loc=testing_mean,
scale=testing_var,
size=(1000, 10))
# Test with training=True passed to the call method:
training_arg = True
should_be_training = True
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
# Test with training=False passed to the call method:
training_arg = False
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
# Test the layer in various Keras learning phase scopes:
training_arg = None
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
tf.keras.backend.set_learning_phase(True)
should_be_training = True
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
tf.keras.backend.set_learning_phase(False)
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
def test_batchnorm_freezing_training_false(self):
with self.test_session():
training_mean = 5.0
training_var = 10.0
testing_mean = -10.0
testing_var = 5.0
# Initially train the batch norm, and save the weights
trained_weights = self._train_freezable_batch_norm(training_mean,
training_var)
# Load the batch norm back up, freezing training to False.
# Apply the batch norm layer to testing data and ensure it is normalized
# according to the training data's statistics.
model, norm = self._build_model(training=False)
for trained_weight, blank_weight in zip(trained_weights, model.weights):
weight_copy = blank_weight.assign(tf.keras.backend.eval(trained_weight))
tf.keras.backend.eval(weight_copy)
# centered on testing_mean, variance testing_var
test_data = np.random.normal(
loc=testing_mean,
scale=testing_var,
size=(1000, 10))
# Make sure that the layer is never training
# Test with training=True passed to the call method:
training_arg = True
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
# Test with training=False passed to the call method:
training_arg = False
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
# Test the layer in various Keras learning phase scopes:
training_arg = None
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
tf.keras.backend.set_learning_phase(True)
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
tf.keras.backend.set_learning_phase(False)
should_be_training = False
self._test_batchnorm_layer(norm, should_be_training, test_data,
testing_mean, testing_var, training_arg,
training_mean, training_var)
if __name__ == '__main__':
tf.test.main()
| [((7572, 7586), 'tensorflow.test.main', 'tf.test.main', ([], {}), '()\n', (7584, 7586), True, 'import tensorflow as tf\n'), ((1002, 1030), 'tensorflow.keras.models.Sequential', 'tf.keras.models.Sequential', ([], {}), '()\n', (1028, 1030), True, 'import tensorflow as tf\n'), ((1042, 1138), 'object_detection.core.freezable_batch_norm.FreezableBatchNorm', 'freezable_batch_norm.FreezableBatchNorm', ([], {'training': 'training', 'input_shape': '(10,)', 'momentum': '(0.8)'}), '(training=training, input_shape=(10,\n ), momentum=0.8)\n', (1081, 1138), False, 'from object_detection.core import freezable_batch_norm\n'), ((1505, 1577), 'numpy.random.normal', 'np.random.normal', ([], {'loc': 'training_mean', 'scale': 'training_var', 'size': '(1000, 10)'}), '(loc=training_mean, scale=training_var, size=(1000, 10))\n', (1521, 1577), True, 'import numpy as np\n'), ((1971, 2004), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['out_tensor'], {}), '(out_tensor)\n', (1992, 2004), True, 'import tensorflow as tf\n'), ((2016, 2048), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['norm.beta'], {}), '(norm.beta)\n', (2037, 2048), True, 'import tensorflow as tf\n'), ((2060, 2093), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['norm.gamma'], {}), '(norm.gamma)\n', (2081, 2093), True, 'import tensorflow as tf\n'), ((1865, 1914), 'tensorflow.convert_to_tensor', 'tf.convert_to_tensor', (['test_data'], {'dtype': 'tf.float32'}), '(test_data, dtype=tf.float32)\n', (1885, 1914), True, 'import tensorflow as tf\n'), ((3251, 3321), 'numpy.random.normal', 'np.random.normal', ([], {'loc': 'testing_mean', 'scale': 'testing_var', 'size': '(1000, 10)'}), '(loc=testing_mean, scale=testing_var, size=(1000, 10))\n', (3267, 3321), True, 'import numpy as np\n'), ((4340, 4381), 'tensorflow.keras.backend.set_learning_phase', 'tf.keras.backend.set_learning_phase', (['(True)'], {}), '(True)\n', (4375, 4381), True, 'import tensorflow as tf\n'), ((4627, 4669), 'tensorflow.keras.backend.set_learning_phase', 'tf.keras.backend.set_learning_phase', (['(False)'], {}), '(False)\n', (4662, 4669), True, 'import tensorflow as tf\n'), ((5830, 5900), 'numpy.random.normal', 'np.random.normal', ([], {'loc': 'testing_mean', 'scale': 'testing_var', 'size': '(1000, 10)'}), '(loc=testing_mean, scale=testing_var, size=(1000, 10))\n', (5846, 5900), True, 'import numpy as np\n'), ((6971, 7012), 'tensorflow.keras.backend.set_learning_phase', 'tf.keras.backend.set_learning_phase', (['(True)'], {}), '(True)\n', (7006, 7012), True, 'import tensorflow as tf\n'), ((7259, 7301), 'tensorflow.keras.backend.set_learning_phase', 'tf.keras.backend.set_learning_phase', (['(False)'], {}), '(False)\n', (7294, 7301), True, 'import tensorflow as tf\n'), ((3142, 3176), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['weight_copy'], {}), '(weight_copy)\n', (3163, 3176), True, 'import tensorflow as tf\n'), ((5721, 5755), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['weight_copy'], {}), '(weight_copy)\n', (5742, 5755), True, 'import tensorflow as tf\n'), ((3095, 3132), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['trained_weight'], {}), '(trained_weight)\n', (3116, 3132), True, 'import tensorflow as tf\n'), ((5674, 5711), 'tensorflow.keras.backend.eval', 'tf.keras.backend.eval', (['trained_weight'], {}), '(trained_weight)\n', (5695, 5711), True, 'import tensorflow as tf\n')] |
translationalneurosurgery/tool-offspect | offspect/gui/VWidgets/message.py | 011dafb697e8542fc7c3cf8af8523af3ff704a14 | # from PyQt5.QtWidgets import QMessageBox
# def raise_error(message: str = "DEFAULT:Error Description:More Information"):
# box = QMessageBox()
# kind, msg, info = message.split(":")
# box.setIcon(QMessageBox.Critical)
# box.setWindowTitle(kind + " Error")
# box.setText(msg)
# box.setInformativeText(info)
# box.exec_()
| [] |
crazywiden/Leetcode_daily_submit | Widen/LC759_Employee_Free_Time.py | 15637e260ab547022ac0c828dd196337bd8d50a3 | """
759. Employee Free Time
We are given a list schedule of employees, which represents the working time for each employee.
Each employee has a list of non-overlapping Intervals, and these intervals are in sorted order.
Return the list of finite intervals representing common, positive-length free time for all employees, also in sorted order.
(Even though we are representing Intervals in the form [x, y], the objects inside are Intervals, not lists or arrays. For example, schedule[0][0].start = 1, schedule[0][0].end = 2, and schedule[0][0][0] is not defined). Also, we wouldn't include intervals like [5, 5] in our answer, as they have zero length.
"""
# Line Swap method
# if we met a start, cnt += 1
# if we met an end, cnt -= 1
# time complexity -- O(NlogN), need sort all intervals
# Runtime: 96 ms, faster than 87.95% of Python3 online submissions for Employee Free Time.
# Memory Usage: 14.7 MB, less than 25.00% of Python3 online submissions for Employee Free Time.
"""
# Definition for an Interval.
class Interval:
def __init__(self, start: int = None, end: int = None):
self.start = start
self.end = end
"""
class Solution:
def employeeFreeTime(self, schedule: '[[Interval]]') -> '[Interval]':
START, END = 0, 1
all_interval = []
for person in schedule:
for interval in person:
all_interval.append((interval.start, START))
all_interval.append((interval.end, END))
all_interval = sorted(all_interval, key=lambda x: x[0])
prev = None
cnt = 0
res = []
for i in range(len(all_interval)):
if cnt == 0 and prev is not None:
if prev != all_interval[i][0]:
res.append(Interval(prev, all_interval[i][0]))
if all_interval[i][1] == START:
cnt += 1
else:
cnt -= 1
prev = all_interval[i][0]
return res
# priority queue
# if the current end is less than the smallest start
# then means there is a free time
# use priority queue to maintain the smallest start
# also only stort one of jobs of each person in the queue to save memory
# time complexity -- O(NlogC), C is the number of employee
"""
# Definition for an Interval.
class Interval:
def __init__(self, start: int = None, end: int = None):
self.start = start
self.end = end
"""
import heapq
class Solution:
def employeeFreeTime(self, schedule: '[[Interval]]') -> '[Interval]':
res = []
job_start_q = [(emp[0].start, emp_id, 0) for emp_id, emp in enumerate(schedule)]
heapq.heapify(job_start_q)
largest_end = min(interval.start for emp in schedule for interval in emp)
while job_start_q:
start, emp_id, job_id = heapq.heappop(job_start_q)
if largest_end < start:
res.append(Interval(largest_end, start))
largest_end = max(largest_end, schedule[emp_id][job_id].end)
if job_id + 1 < len(schedule[emp_id]):
heapq.heappush(job_start_q, (schedule[emp_id][job_id+1].start, emp_id, job_id+1))
return res
| [((2646, 2672), 'heapq.heapify', 'heapq.heapify', (['job_start_q'], {}), '(job_start_q)\n', (2659, 2672), False, 'import heapq\n'), ((2818, 2844), 'heapq.heappop', 'heapq.heappop', (['job_start_q'], {}), '(job_start_q)\n', (2831, 2844), False, 'import heapq\n'), ((3078, 3168), 'heapq.heappush', 'heapq.heappush', (['job_start_q', '(schedule[emp_id][job_id + 1].start, emp_id, job_id + 1)'], {}), '(job_start_q, (schedule[emp_id][job_id + 1].start, emp_id, \n job_id + 1))\n', (3092, 3168), False, 'import heapq\n')] |
thomaserlang/storitch | storitch/config.py | dbcf97af547d9cb1ae5c3994654e8db03e43a253 | import os, yaml
config = {
'debug': False,
'port': 5000,
'store_path': '/var/storitch',
'pool_size': 5,
'logging': {
'level': 'warning',
'path': None,
'max_size': 100 * 1000 * 1000,# ~ 95 mb
'num_backups': 10,
},
'image_exts': [
'.jpg', '.jpeg', '.png', '.tiff', '.tif', '.gif',
'.bmp', '.bmp2', '.bmp3', '.dcm', '.dicom', '.webp',
],
}
def load(path=None):
default_paths = [
'~/storitch.yaml',
'./storitch.yaml',
'../storitch.yaml',
'/etc/storitch/storitch.yaml',
'/etc/storitch.yaml',
]
if not path:
path = os.environ.get('STORITCH_CONFIG', None)
if not path:
for p in default_paths:
p = os.path.expanduser(p)
if os.path.isfile(p):
path = p
break
if not path:
raise Exception('No config file specified.')
if not os.path.isfile(path):
raise Exception('Config: "{}" could not be found.'.format(path))
with open(path) as f:
data = yaml.load(f, Loader=yaml.FullLoader)
for key in data:
if key in config:
if isinstance(config[key], dict):
config[key].update(data[key])
else:
config[key] = data[key] | [((651, 690), 'os.environ.get', 'os.environ.get', (['"""STORITCH_CONFIG"""', 'None'], {}), "('STORITCH_CONFIG', None)\n", (665, 690), False, 'import os, yaml\n'), ((964, 984), 'os.path.isfile', 'os.path.isfile', (['path'], {}), '(path)\n', (978, 984), False, 'import os, yaml\n'), ((1100, 1136), 'yaml.load', 'yaml.load', (['f'], {'Loader': 'yaml.FullLoader'}), '(f, Loader=yaml.FullLoader)\n', (1109, 1136), False, 'import os, yaml\n'), ((768, 789), 'os.path.expanduser', 'os.path.expanduser', (['p'], {}), '(p)\n', (786, 789), False, 'import os, yaml\n'), ((809, 826), 'os.path.isfile', 'os.path.isfile', (['p'], {}), '(p)\n', (823, 826), False, 'import os, yaml\n')] |
PipelineAI/models | keras/lstm-securitai/model/pipeline_invoke_python.py | d8df07877aa8b10ce9b84983bb440af75e84dca7 | import io
import os
import numpy as np
import pandas
import json
import logging #<== Optional. Log to console, file, kafka
from pipeline_monitor import prometheus_monitor as monitor #<== Optional. Monitor runtime metrics
from pipeline_logger import log
import tensorflow as tf
from tensorflow.contrib import predictor
from keras.models import Sequential, load_model
from keras.preprocessing import sequence
from keras.preprocessing.text import Tokenizer
from collections import OrderedDict
_logger = logging.getLogger('pipeline-logger')
_logger.setLevel(logging.INFO)
_logger_stream_handler = logging.StreamHandler()
_logger_stream_handler.setLevel(logging.INFO)
_logger.addHandler(_logger_stream_handler)
__all__ = ['invoke'] #<== Optional. Being a good Python citizen.
_labels = { #<== Optional. Used for metrics/labels
'name': 'injection',
'tag': 'v1',
'type': 'tensorflow',
'runtime': 'python',
'chip': 'cpu',
}
def _initialize_upon_import(): #<== Optional. Called once upon server startup
''' Initialize / Restore Model Object.
'''
model = load_model('securitai-lstm-model.h5')
model.load_weights('securitai-lstm-weights.h5')
model.compile(loss = 'binary_crossentropy', optimizer = 'adam', metrics = ['accuracy'])
return model
# This is called unconditionally at *module import time*...
_model = _initialize_upon_import()
#@log(labels=_labels, logger=_logger) #<== Optional. Sample and compare predictions
def invoke(request): #<== Required. Called on every prediction
'''Where the magic happens...'''
with monitor(labels=_labels, name="transform_request"): #<== Optional. Expose fine-grained metrics
transformed_request = _transform_request(request) #<== Optional. Transform input (json) into TensorFlow (tensor)
with monitor(labels=_labels, name="invoke"): #<== Optional. Calls _model.predict()
response = _model.predict(transformed_request)
with monitor(labels=_labels, name="transform_response"): #<== Optional. Transform TensorFlow (tensor) into output (json)
transformed_response = _transform_response(response)
return transformed_response #<== Required. Returns the predicted value(s)
def _transform_request(request):
request_str = request.decode('utf-8')
# tokenize the csv request and create json
X = pandas.read_csv(io.StringIO(request_str), engine='python', quotechar='|', header=None).values[:,0]
for index, item in enumerate(X):
reqJson = json.loads(item, object_pairs_hook=OrderedDict)
del reqJson['http']['timestamp']
del reqJson['http']['headers']
del reqJson['http']['source']
del reqJson['http']['route']
del reqJson['http']['responsePayload']
X[index] = json.dumps(reqJson, separators=(',', ':'))
tokenizer = Tokenizer(filters='\t\n', char_level=True)
tokenizer.fit_on_texts(X)
# this used to be [log_entry]
seq = tokenizer.texts_to_sequences([request_str])
max_log_length = 1024
log_entry_processed = sequence.pad_sequences(seq, maxlen=max_log_length)
return log_entry_processed
def _transform_response(response):
return response[0]
if __name__ == '__main__':
with open('./pipeline_test_request.csv', 'rb') as fb:
request_bytes = fb.read()
response_bytes = invoke(request_bytes)
print(response_bytes)
| [((556, 592), 'logging.getLogger', 'logging.getLogger', (['"""pipeline-logger"""'], {}), "('pipeline-logger')\n", (573, 592), False, 'import logging\n'), ((649, 672), 'logging.StreamHandler', 'logging.StreamHandler', ([], {}), '()\n', (670, 672), False, 'import logging\n'), ((1310, 1347), 'keras.models.load_model', 'load_model', (['"""securitai-lstm-model.h5"""'], {}), "('securitai-lstm-model.h5')\n", (1320, 1347), False, 'from keras.models import Sequential, load_model\n'), ((3172, 3214), 'keras.preprocessing.text.Tokenizer', 'Tokenizer', ([], {'filters': '"""\t\n"""', 'char_level': '(True)'}), "(filters='\\t\\n', char_level=True)\n", (3181, 3214), False, 'from keras.preprocessing.text import Tokenizer\n'), ((3385, 3435), 'keras.preprocessing.sequence.pad_sequences', 'sequence.pad_sequences', (['seq'], {'maxlen': 'max_log_length'}), '(seq, maxlen=max_log_length)\n', (3407, 3435), False, 'from keras.preprocessing import sequence\n'), ((1872, 1921), 'pipeline_monitor.prometheus_monitor', 'monitor', ([], {'labels': '_labels', 'name': '"""transform_request"""'}), "(labels=_labels, name='transform_request')\n", (1879, 1921), True, 'from pipeline_monitor import prometheus_monitor as monitor\n'), ((2107, 2145), 'pipeline_monitor.prometheus_monitor', 'monitor', ([], {'labels': '_labels', 'name': '"""invoke"""'}), "(labels=_labels, name='invoke')\n", (2114, 2145), True, 'from pipeline_monitor import prometheus_monitor as monitor\n'), ((2265, 2315), 'pipeline_monitor.prometheus_monitor', 'monitor', ([], {'labels': '_labels', 'name': '"""transform_response"""'}), "(labels=_labels, name='transform_response')\n", (2272, 2315), True, 'from pipeline_monitor import prometheus_monitor as monitor\n'), ((2843, 2890), 'json.loads', 'json.loads', (['item'], {'object_pairs_hook': 'OrderedDict'}), '(item, object_pairs_hook=OrderedDict)\n', (2853, 2890), False, 'import json\n'), ((3112, 3154), 'json.dumps', 'json.dumps', (['reqJson'], {'separators': "(',', ':')"}), "(reqJson, separators=(',', ':'))\n", (3122, 3154), False, 'import json\n'), ((2705, 2729), 'io.StringIO', 'io.StringIO', (['request_str'], {}), '(request_str)\n', (2716, 2729), False, 'import io\n')] |
ATLASControlTower/aCT | src/act/common/aCTReport.py | fb841bddbe086db9f0d620167c4a11ae4634ef4f | import argparse
import importlib
import os
import re
import signal
import subprocess
import sys
import time
import logging
from act.common import aCTLogger
from act.common.aCTConfig import aCTConfigAPP
from act.arc import aCTDBArc
class aCTReport:
'''Print summary info on jobs in DB. Use --web to print html that is
automatically refreshed. Add filenames to query more than one aCT DB'''
def __init__(self, args):
self.output = ""
self.outfile = args.web
self.actconfs = args.conffiles or [''] # empty string for default behaviour
self.logger=aCTLogger.aCTLogger("aCTReport")
self.actlog=self.logger()
self.actlog.logger.setLevel(logging.INFO)
self.criticallogger = aCTLogger.aCTLogger('aCTCritical', arclog=False)
self.criticallog = self.criticallogger()
if self.outfile:
self.log('<META HTTP-EQUIV="refresh" CONTENT="60"><pre>')
self.log(time.asctime() + '\n')
self.db=aCTDBArc.aCTDBArc(self.actlog)
def log(self, message=''):
self.output += message + '\n'
def AppReport(self):
appconf = aCTConfigAPP()
apps = appconf.getList(["modules", "app"])
for app in apps:
try:
ap = importlib.import_module(f'{app}.aCTReport').report
self.log(ap(self.actconfs))
except ModuleNotFoundError as e:
self.actlog.info(f'No report in module {app}')
except AttributeError:
self.actlog.info(f'aCTReport.report() not found in {app}')
except Exception as e:
self.actlog.error(f'Exception running {app}.aCTReport.report: {e}')
def ProcessReport(self):
if self.actconfs != ['']:
return # don't print processes for combined report
actprocscmd = 'ps ax -ww -o pid,etime,args'
try:
out = subprocess.run(actprocscmd.split(), check=True, encoding='utf-8', stdout=subprocess.PIPE).stdout
except subprocess.CalledProcessError as e:
self.log('Error: could not run ps command: %s' % e.stderr)
return
# Group processes by cluster
cluster_procs = {}
longprocesses = []
for line in out.split('\n'):
reg = re.match(r'\s*(\d*)\s*(.*) .*python.* .*(aCT\w*)\.py\s?(\S*)', line)
if reg:
pid, runningtime, process, cluster = reg.groups()
# ignore Main and this process
if process in ['aCTReport', 'aCTMain', 'aCTHeartbeatWatchdog']:
continue
if cluster == '':
cluster = '(no cluster defined)'
elif not re.match(r'\d\d:\d\d$', runningtime):
# Check for overrunning processes
longprocesses.append((process, pid, cluster, runningtime))
if cluster in cluster_procs:
cluster_procs[cluster].append(process)
else:
cluster_procs[cluster] = [process]
for proc in longprocesses:
self.log('WARNING: %s (pid %s) for %s running for more than one hour (%s), this process will be killed' % proc)
# Kill process and log a critical message to send email
# Too many emails, disable
#self.criticallog.critical('Killing process %s (pid %s) for %s running for more than one hour (%s)' % proc)
try:
os.kill(int(proc[1]), signal.SIGKILL)
except OSError:
pass
self.log()
self.log('Active processes per cluster:')
for cluster in sorted(cluster_procs):
procs = cluster_procs[cluster]
procs.sort()
self.log(f'{cluster:>38.38}: {" ".join(procs)}')
self.log()
def ArcJobReport(self):
rep={}
rtot={}
states = ["Undefined", "Accepted", "Preparing", "Submitting",
"Queuing", "Running", "Finishing", "Finished", "Hold", "Killed",
"Failed", "Deleted", "Other"]
for conf in self.actconfs:
if conf:
os.environ['ACTCONFIGARC'] = conf
db=aCTDBArc.aCTDBArc(self.actlog)
c=db.db.conn.cursor()
c.execute("select jobid,state from arcjobs")
rows=c.fetchall()
for r in rows:
reg=re.search('.+//([^:]+)',str(r[0]))
cl=""
try:
cl=reg.group(1)
except:
cl='WaitingSubmission'
jid=str(r[1])
if jid == 'None':
jid="Other"
try:
rep[cl][jid]+=1
except:
try:
rep[cl][jid]=1
except:
rep[cl]={}
rep[cl][jid]=1
try:
rtot[jid]+=1
except:
rtot[jid]=1
if sum(rtot.values()) == 0:
return
self.log(f"All ARC jobs: {sum(rtot.values())}")
self.log(f"{'':39} {' '.join([f'{s:>9}' for s in states])}")
for k in sorted(rep, key=lambda x: x.split('.')[-1]):
log=f"{k:>38.38}:"
for s in states:
try:
log += f'{rep[k][s]:>10}'
except KeyError:
log += f'{"-":>10}'
self.log(log)
log = f"{'Totals':>38}:"
for s in states:
try:
log += f'{rtot[s]:>10}'
except:
log += f'{"-":>10}'
self.log(log+'\n\n')
def CondorJobReport(self):
rep = {}
rtot = {}
condorjobstatemap = ['Undefined', # used before real state is known
'Idle',
'Running',
'Removed',
'Completed',
'Held',
'Transferring',
'Suspended']
for conf in self.actconfs:
if conf:
os.environ['ACTCONFIGARC'] = conf
db=aCTDBArc.aCTDBArc(self.actlog)
c = db.db.conn.cursor()
c.execute("select cluster, JobStatus from condorjobs")
rows = c.fetchall()
for r in rows:
cl = str(r[0])
if not cl:
cl = 'WaitingSubmission'
jid = r[1]
try:
rep[cl][jid]+=1
except:
try:
rep[cl][jid]=1
except:
rep[cl]={}
rep[cl][jid]=1
try:
rtot[jid]+=1
except:
rtot[jid]=1
if sum(rtot.values()) == 0:
return
self.log(f"All Condor jobs: {sum(rtot.values())}")
self.log(f"{'':39} {' '.join([f'{s:>9}' for s in condorjobstatemap])}")
for k in sorted(rep, key=lambda x: x.split('.')[-1]):
log=f"{k:>38.38}:"
for s in range(8):
try:
log += f'{rep[k][s]:>10}'
except KeyError:
log += f'{"-":>10}'
self.log(log)
log = f"{'Totals':>38}:"
for s in range(8):
try:
log += f'{rtot[s]:>10}'
except:
log += f'{"-":>10}'
self.log(log+'\n\n')
def StuckReport(self):
# Query for lost jobs older than lostlimit
lostlimit = 86400
select = "(arcstate='submitted' or arcstate='running') and " \
+ self.db.timeStampLessThan("tarcstate", lostlimit) + \
" order by tarcstate"
columns = ['cluster']
jobs = self.db.getArcJobsInfo(select, columns)
if jobs:
self.log('Found %d jobs not updated in over %d seconds:\n' % (len(jobs), lostlimit))
clustercount = {}
for job in jobs:
try:
host = re.search('.+//([^:]+)', job['cluster']).group(1)
except:
host = None
if host in clustercount:
clustercount[host] += 1
else:
clustercount[host] = 1
for cluster, count in clustercount.items():
self.log(f'{count} {cluster}')
self.log()
def end(self):
if self.outfile:
self.log('</pre>')
def main():
parser = argparse.ArgumentParser(description='Report table of aCT jobs.')
parser.add_argument('conffiles', nargs='*', help='list of configuration files')
parser.add_argument('--web', help='Output suitable for web page')
parser.add_argument('--harvester', action='store_true', help='Dummy arg for backwards compatibility')
args = parser.parse_args(sys.argv[1:])
acts = aCTReport(args)
acts.AppReport()
acts.ArcJobReport()
acts.CondorJobReport()
acts.StuckReport()
acts.ProcessReport()
acts.end()
if acts.outfile is None:
sys.stdout.write(acts.output)
else:
f=open(acts.outfile,"w")
f.write(acts.output)
f.close()
if __name__ == '__main__':
main()
| [((8738, 8802), 'argparse.ArgumentParser', 'argparse.ArgumentParser', ([], {'description': '"""Report table of aCT jobs."""'}), "(description='Report table of aCT jobs.')\n", (8761, 8802), False, 'import argparse\n'), ((592, 624), 'act.common.aCTLogger.aCTLogger', 'aCTLogger.aCTLogger', (['"""aCTReport"""'], {}), "('aCTReport')\n", (611, 624), False, 'from act.common import aCTLogger\n'), ((739, 787), 'act.common.aCTLogger.aCTLogger', 'aCTLogger.aCTLogger', (['"""aCTCritical"""'], {'arclog': '(False)'}), "('aCTCritical', arclog=False)\n", (758, 787), False, 'from act.common import aCTLogger\n'), ((994, 1024), 'act.arc.aCTDBArc.aCTDBArc', 'aCTDBArc.aCTDBArc', (['self.actlog'], {}), '(self.actlog)\n', (1011, 1024), False, 'from act.arc import aCTDBArc\n'), ((1140, 1154), 'act.common.aCTConfig.aCTConfigAPP', 'aCTConfigAPP', ([], {}), '()\n', (1152, 1154), False, 'from act.common.aCTConfig import aCTConfigAPP\n'), ((9306, 9335), 'sys.stdout.write', 'sys.stdout.write', (['acts.output'], {}), '(acts.output)\n', (9322, 9335), False, 'import sys\n'), ((2297, 2371), 're.match', 're.match', (['"""\\\\s*(\\\\d*)\\\\s*(.*) .*python.* .*(aCT\\\\w*)\\\\.py\\\\s?(\\\\S*)"""', 'line'], {}), "('\\\\s*(\\\\d*)\\\\s*(.*) .*python.* .*(aCT\\\\w*)\\\\.py\\\\s?(\\\\S*)', line)\n", (2305, 2371), False, 'import re\n'), ((4226, 4256), 'act.arc.aCTDBArc.aCTDBArc', 'aCTDBArc.aCTDBArc', (['self.actlog'], {}), '(self.actlog)\n', (4243, 4256), False, 'from act.arc import aCTDBArc\n'), ((6282, 6312), 'act.arc.aCTDBArc.aCTDBArc', 'aCTDBArc.aCTDBArc', (['self.actlog'], {}), '(self.actlog)\n', (6299, 6312), False, 'from act.arc import aCTDBArc\n'), ((954, 968), 'time.asctime', 'time.asctime', ([], {}), '()\n', (966, 968), False, 'import time\n'), ((1269, 1312), 'importlib.import_module', 'importlib.import_module', (['f"""{app}.aCTReport"""'], {}), "(f'{app}.aCTReport')\n", (1292, 1312), False, 'import importlib\n'), ((2720, 2759), 're.match', 're.match', (['"""\\\\d\\\\d:\\\\d\\\\d$"""', 'runningtime'], {}), "('\\\\d\\\\d:\\\\d\\\\d$', runningtime)\n", (2728, 2759), False, 'import re\n'), ((8251, 8291), 're.search', 're.search', (['""".+//([^:]+)"""', "job['cluster']"], {}), "('.+//([^:]+)', job['cluster'])\n", (8260, 8291), False, 'import re\n')] |
mtcolman/django-DefectDojo | unittests/test_apiv2_user.py | 76175aca446e077884bdb5e1d8e2a671a0840775 | from rest_framework.test import APITestCase, APIClient
from django.urls import reverse
from rest_framework.authtoken.models import Token
class UserTest(APITestCase):
"""
Test the User APIv2 endpoint.
"""
fixtures = ['dojo_testdata.json']
def setUp(self):
token = Token.objects.get(user__username='admin')
self.client = APIClient()
self.client.credentials(HTTP_AUTHORIZATION='Token ' + token.key)
def test_user_list(self):
r = self.client.get(reverse('user-list'))
self.assertEqual(r.status_code, 200, r.content[:1000])
user_list = r.json()['results']
self.assertTrue(len(user_list) >= 1, r.content[:1000])
for user in user_list:
for item in ['username', 'first_name', 'last_name', 'email']:
self.assertIn(item, user, r.content[:1000])
for item in ['password']:
self.assertNotIn(item, user, r.content[:1000])
def test_user_add(self):
# simple user without password
r = self.client.post(reverse('user-list'), {
"username": "api-user-1"
}, format='json')
self.assertEqual(r.status_code, 201, r.content[:1000])
# user with good password
password = 'testTEST1234!@#$'
r = self.client.post(reverse('user-list'), {
"username": "api-user-2",
"password": password
}, format='json')
self.assertEqual(r.status_code, 201, r.content[:1000])
# test password by fetching API key
r = self.client.post(reverse('api-token-auth'), {
"username": "api-user-2",
"password": password
}, format='json')
self.assertEqual(r.status_code, 200, r.content[:1000])
# user with weak password
r = self.client.post(reverse('user-list'), {
"username": "api-user-3",
"password": "weakPassword"
}, format='json')
self.assertEqual(r.status_code, 400, r.content[:1000])
self.assertIn('The password must contain at least 1 digit, 0-9.', r.content.decode("utf-8"))
def test_user_change_password(self):
# some user
r = self.client.post(reverse('user-list'), {
"username": "api-user-4"
}, format='json')
self.assertEqual(r.status_code, 201, r.content[:1000])
user_id = r.json()['id']
r = self.client.put("{}{}/".format(reverse('user-list'), user_id), {
"username": "api-user-4",
"first_name": "first"
}, format='json',)
self.assertEqual(r.status_code, 200, r.content[:1000])
r = self.client.patch("{}{}/".format(reverse('user-list'), user_id), {
"last_name": "last"
}, format='json')
self.assertEqual(r.status_code, 200, r.content[:1000])
r = self.client.put("{}{}/".format(reverse('user-list'), user_id), {
"username": "api-user-4",
"password": "testTEST1234!@#$"
}, format='json')
self.assertEqual(r.status_code, 400, r.content[:1000])
self.assertIn("Update of password though API is not allowed", r.content.decode("utf-8"))
r = self.client.patch("{}{}/".format(reverse('user-list'), user_id), {
"password": "testTEST1234!@#$"
}, format='json')
self.assertEqual(r.status_code, 400, r.content[:1000])
self.assertIn("Update of password though API is not allowed", r.content.decode("utf-8"))
| [((294, 335), 'rest_framework.authtoken.models.Token.objects.get', 'Token.objects.get', ([], {'user__username': '"""admin"""'}), "(user__username='admin')\n", (311, 335), False, 'from rest_framework.authtoken.models import Token\n'), ((358, 369), 'rest_framework.test.APIClient', 'APIClient', ([], {}), '()\n', (367, 369), False, 'from rest_framework.test import APITestCase, APIClient\n'), ((502, 522), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (509, 522), False, 'from django.urls import reverse\n'), ((1054, 1074), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (1061, 1074), False, 'from django.urls import reverse\n'), ((1306, 1326), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (1313, 1326), False, 'from django.urls import reverse\n'), ((1564, 1589), 'django.urls.reverse', 'reverse', (['"""api-token-auth"""'], {}), "('api-token-auth')\n", (1571, 1589), False, 'from django.urls import reverse\n'), ((1817, 1837), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (1824, 1837), False, 'from django.urls import reverse\n'), ((2199, 2219), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (2206, 2219), False, 'from django.urls import reverse\n'), ((2426, 2446), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (2433, 2446), False, 'from django.urls import reverse\n'), ((2668, 2688), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (2675, 2688), False, 'from django.urls import reverse\n'), ((2867, 2887), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (2874, 2887), False, 'from django.urls import reverse\n'), ((3214, 3234), 'django.urls.reverse', 'reverse', (['"""user-list"""'], {}), "('user-list')\n", (3221, 3234), False, 'from django.urls import reverse\n')] |
ankit-kushwaha-51/RESTful_API | src/init.py | 4513e8a058cb0200b41d47830b93b8a23ea38d7b | from flask import Flask
from src.models import db
from . import config
def create_app():
flask_app = Flask(__name__)
flask_app.config['SQLALCHEMY_DATABASE_URI'] = config.DATABASE_CONNECTION_URI
flask_app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
flask_app.app_context().push()
db.init_app(flask_app)
db.create_all()
return flask_app
| [((108, 123), 'flask.Flask', 'Flask', (['__name__'], {}), '(__name__)\n', (113, 123), False, 'from flask import Flask\n'), ((307, 329), 'src.models.db.init_app', 'db.init_app', (['flask_app'], {}), '(flask_app)\n', (318, 329), False, 'from src.models import db\n'), ((334, 349), 'src.models.db.create_all', 'db.create_all', ([], {}), '()\n', (347, 349), False, 'from src.models import db\n')] |
nicoddemus/dependencies | tests/helpers/examples/order/tasks.py | 74180e2c6098d8ad03bc53c5703bdf8dc61c3ed9 | from dependencies import Injector
from dependencies import this
from dependencies.contrib.celery import shared_task
from examples.order.commands import ProcessOrder
@shared_task
class ProcessOrderTask(Injector):
name = "process_order"
run = ProcessOrder
bind = True
retry = this.task.retry
| [] |
SocrammBR/Desafios-Python-CursoEmVideo | 001 - 050/ex032.py | bd2454a24134500343ece91b936c169d3a66f89e | ano = int(input('Digite o ano: '))
if (ano%4) == 0:
print ('Ele é bissexto')
else:
print ('Ele não é bissexto') | [] |
vikneswaran20/rn | rn/__init__.py | 33e0bfaf58bb8a5ec54c6d010035693b35e9909d | __version__ = '0.0.1'
__license__ = 'BSD'
| [] |
FlexMeasures/flexmeasures | flexmeasures/cli/data_edit.py | a4367976d37ac5721b8eb3ce8a2414595e52c678 | from datetime import timedelta
from typing import Union, List, Optional
import click
import pandas as pd
from flask import current_app as app
from flask.cli import with_appcontext
from flexmeasures import Sensor
from flexmeasures.data import db
from flexmeasures.data.schemas.generic_assets import GenericAssetIdField
from flexmeasures.data.schemas.sensors import SensorIdField
from flexmeasures.data.models.generic_assets import GenericAsset
from flexmeasures.data.models.time_series import TimedBelief
from flexmeasures.data.utils import save_to_db
@click.group("edit")
def fm_edit_data():
"""FlexMeasures: Edit data."""
@fm_edit_data.command("attribute")
@with_appcontext
@click.option(
"--asset-id",
"assets",
required=False,
multiple=True,
type=GenericAssetIdField(),
help="Add/edit attribute to this asset. Follow up with the asset's ID.",
)
@click.option(
"--sensor-id",
"sensors",
required=False,
multiple=True,
type=SensorIdField(),
help="Add/edit attribute to this sensor. Follow up with the sensor's ID.",
)
@click.option(
"--attribute",
"attribute_key",
required=True,
help="Add/edit this attribute. Follow up with the name of the attribute.",
)
@click.option(
"--float",
"attribute_float_value",
required=False,
type=float,
help="Set the attribute to this float value.",
)
@click.option(
"--bool",
"attribute_bool_value",
required=False,
type=bool,
help="Set the attribute to this bool value.",
)
@click.option(
"--str",
"attribute_str_value",
required=False,
type=str,
help="Set the attribute to this string value.",
)
@click.option(
"--int",
"attribute_int_value",
required=False,
type=int,
help="Set the attribute to this integer value.",
)
@click.option(
"--null",
"attribute_null_value",
required=False,
is_flag=True,
default=False,
help="Set the attribute to a null value.",
)
def edit_attribute(
attribute_key: str,
assets: List[GenericAsset],
sensors: List[Sensor],
attribute_null_value: bool,
attribute_float_value: Optional[float] = None,
attribute_bool_value: Optional[bool] = None,
attribute_str_value: Optional[str] = None,
attribute_int_value: Optional[int] = None,
):
"""Edit (or add) an asset attribute or sensor attribute."""
if not assets and not sensors:
raise ValueError("Missing flag: pass at least one --asset-id or --sensor-id.")
# Parse attribute value
attribute_value = parse_attribute_value(
attribute_float_value=attribute_float_value,
attribute_bool_value=attribute_bool_value,
attribute_str_value=attribute_str_value,
attribute_int_value=attribute_int_value,
attribute_null_value=attribute_null_value,
)
# Set attribute
for asset in assets:
asset.attributes[attribute_key] = attribute_value
db.session.add(asset)
for sensor in sensors:
sensor.attributes[attribute_key] = attribute_value
db.session.add(sensor)
db.session.commit()
print("Successfully edited/added attribute.")
@fm_edit_data.command("resample-data")
@with_appcontext
@click.option(
"--sensor-id",
"sensor_ids",
multiple=True,
required=True,
help="Resample data for this sensor. Follow up with the sensor's ID. This argument can be given multiple times.",
)
@click.option(
"--event-resolution",
"event_resolution_in_minutes",
type=int,
required=True,
help="New event resolution as an integer number of minutes.",
)
@click.option(
"--from",
"start_str",
required=False,
help="Resample only data from this datetime onwards. Follow up with a timezone-aware datetime in ISO 6801 format.",
)
@click.option(
"--until",
"end_str",
required=False,
help="Resample only data until this datetime. Follow up with a timezone-aware datetime in ISO 6801 format.",
)
@click.option(
"--skip-integrity-check",
is_flag=True,
help="Whether to skip checking the resampled time series data for each sensor."
" By default, an excerpt and the mean value of the original"
" and resampled data will be shown for manual approval.",
)
def resample_sensor_data(
sensor_ids: List[int],
event_resolution_in_minutes: int,
start_str: Optional[str] = None,
end_str: Optional[str] = None,
skip_integrity_check: bool = False,
):
"""Assign a new event resolution to an existing sensor and resample its data accordingly."""
event_resolution = timedelta(minutes=event_resolution_in_minutes)
event_starts_after = pd.Timestamp(start_str) # note that "" or None becomes NaT
event_ends_before = pd.Timestamp(end_str)
for sensor_id in sensor_ids:
sensor = Sensor.query.get(sensor_id)
if sensor.event_resolution == event_resolution:
print(f"{sensor} already has the desired event resolution.")
continue
df_original = sensor.search_beliefs(
most_recent_beliefs_only=False,
event_starts_after=event_starts_after,
event_ends_before=event_ends_before,
).sort_values("event_start")
df_resampled = df_original.resample_events(event_resolution).sort_values(
"event_start"
)
if not skip_integrity_check:
message = ""
if sensor.event_resolution < event_resolution:
message += f"Downsampling {sensor} to {event_resolution} will result in a loss of data. "
click.confirm(
message
+ f"Data before:\n{df_original}\nData after:\n{df_resampled}\nMean before: {df_original['event_value'].mean()}\nMean after: {df_resampled['event_value'].mean()}\nContinue?",
abort=True,
)
# Update sensor
sensor.event_resolution = event_resolution
db.session.add(sensor)
# Update sensor data
query = TimedBelief.query.filter(TimedBelief.sensor == sensor)
if not pd.isnull(event_starts_after):
query = query.filter(TimedBelief.event_start >= event_starts_after)
if not pd.isnull(event_ends_before):
query = query.filter(
TimedBelief.event_start + sensor.event_resolution <= event_ends_before
)
query.delete()
save_to_db(df_resampled, bulk_save_objects=True)
db.session.commit()
print("Successfully resampled sensor data.")
app.cli.add_command(fm_edit_data)
def parse_attribute_value(
attribute_null_value: bool,
attribute_float_value: Optional[float] = None,
attribute_bool_value: Optional[bool] = None,
attribute_str_value: Optional[str] = None,
attribute_int_value: Optional[int] = None,
) -> Union[float, int, bool, str, None]:
"""Parse attribute value."""
if not single_true(
[attribute_null_value]
+ [
v is not None
for v in [
attribute_float_value,
attribute_bool_value,
attribute_str_value,
attribute_int_value,
]
]
):
raise ValueError("Cannot set multiple values simultaneously.")
if attribute_null_value:
return None
elif attribute_float_value is not None:
return float(attribute_float_value)
elif attribute_bool_value is not None:
return bool(attribute_bool_value)
elif attribute_int_value is not None:
return int(attribute_int_value)
return attribute_str_value
def single_true(iterable) -> bool:
i = iter(iterable)
return any(i) and not any(i)
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ArseniumGX/bluemer-modulo2 | semana2/mail_settings.py | 24e5071b734de362dc47ef9d402c191699d15b43 | mail_settings = {
"MAIL_SERVER": 'smtp.gmail.com',
"MAIL_PORT": 465,
"MAIL_USE_TLS": False,
"MAIL_USE_SSL": True,
"MAIL_USERNAME": 'c003.teste.jp@gmail.com',
"MAIL_PASSWORD": 'C003.teste'
} | [] |
dingjingmaster/blog_spider | frame/base/parser.py | 7a0885bf886166eac0caca4471ee9f6424be2225 | #!/usr/bin/env python3.6
# -*- encoding=utf8 -*-
import pyquery
"""
需求字段：
標題、發表日期、分類、標籤、內容、圖片
需要的字段信息
1. 网站根URL
2. 解析器名字
3. 解析器类型
1. PARSER_PASSAGE_URL 文章URL
2. PARSER_PASSAGE_TITLE 文章标题
3. PARSER_PASSAGE_DATE 发表日期
4. PARSER_PASSAGE_CATEGORY 文章分類
5. PARSER_PASSAGE_TAG 文章標籤
6. PARSER_PASSAGE_CONTENT 文章内容
7. PARSER_PASSAGE_IMGURL 文章中的图片 URL
"""
class Parser(object):
def __init__ (self):
self._webURL = ''
self._parserName = 'base_parser'
def _parser_passage_url (self, doc: str) -> (bool, str):
return
def _parser_passage_title (self, doc: str) -> (bool, str):
return
def _parser_passage_date (self, doc: str) -> (bool, str):
return
def _parser_passage_category (self, doc: str) -> (bool, str):
return
def _parser_passage_tag (self, doc: str) -> (bool, str):
return
def _parser_passage_content (self, doc: str) -> (bool, str):
return
def _parser_passage_img_url (self, doc: str) -> (bool, str, bytes):
return
def get_parser_name (self):
return self._parserName
@staticmethod
def _parser (doc: str, rule: str):
return pyquery.PyQuery(doc).find(rule)
def parse (self, doc: str, rule='', parse_type=-1):
if self.PARSER_PASSAGE_URL == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_url(doc)
elif self.PARSER_PASSAGE_TITLE == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_title(doc)
elif self.PARSER_PASSAGE_DATE == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_date(doc)
elif self.PARSER_PASSAGE_CATEGORY == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_category(doc)
elif self.PARSER_PASSAGE_TAG == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_tag(doc)
elif self.PARSER_PASSAGE_CONTENT == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_content(doc)
elif self.PARSER_PASSAGE_IMGURL == parse_type:
if doc == '' or doc == None:
return (False, '')
return self._parser_passage_img_url(doc)
else:
if doc == '' or doc == None:
return (False, '')
return Parser._parser(doc, rule)
PARSER_PASSAGE_URL = 1
PARSER_PASSAGE_TITLE = 2
PARSER_PASSAGE_DATE = 3
PARSER_PASSAGE_CATEGORY = 4
PARSER_PASSAGE_TAG = 5
PARSER_PASSAGE_CONTENT = 6
PARSER_PASSAGE_IMGURL = 7
| [((1374, 1394), 'pyquery.PyQuery', 'pyquery.PyQuery', (['doc'], {}), '(doc)\n', (1389, 1394), False, 'import pyquery\n')] |
Commodore-Bench/u5remastered | tools/mkblocks.py | 02c7ed86055e368b97d3c3c5ca26622782bd564d | #!/usr/bin/env python3
# ----------------------------------------------------------------------------
# Copyright 2019 Drunella
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ----------------------------------------------------------------------------
import os
import sys
import glob
import subprocess
import argparse
import hashlib
import traceback
import pprint
def readblockmap_info(filename):
directory = dict()
with open(filename) as f:
result = [line.split() for line in f]
for l in result:
directory[l[0]] = l[1:]
return directory
def readdisks_info(filename):
disks = []
with open(filename) as f:
result = [line.split() for line in f]
#pprint.pprint(result)
return result
def readdisks_getdiskinfo(disks, diskname):
for d in disks:
if d[0] == diskname:
return d
return []
def map_initialize():
global bank_data, map_data
map_data = bytearray([0xff] * 0x800)
def crtmap_appendentry(filename, block, name, address):
with open(filename, "at") as f:
content = "{0} f {1} addr 0x{2:04x}\n".format(block, name, address)
return f.write(content)
def load_file(filename):
with open(filename, "rb") as f:
return f.read()
def write_prg(dirname, lowhigh, data):
if lowhigh == 0:
# low
a = bytearray(2)
a[0] = 0
a[1] = 0x80
elif lowhigh == 1:
# high
a = bytearray(2)
a[0] = 0
a[1] = 0xA0
else:
raise Exception("lowhigh can only be 0 or 1")
with open(dirname, "wb") as f:
#f.write(a)
f.write(data)
def blockmap_appendentry(diskid, line, bank, highaddress):
global map_data
base = diskid * 256 + line * 2
map_data[base] = bank
map_data[base+1] = highaddress
#print("blockmap_appendentry: " + str(base) + ": " + str(bank) + " " + str(highaddress))
def calculate_address(lowhigh):
if lowhigh == 0:
# low
a = 0x80
elif lowhigh == 1:
# high
a = 0xA0
else:
raise Exception("lowhigh can only be 0 or 1")
return a
def main(argv):
global bank_data, map_data
p = argparse.ArgumentParser()
p.add_argument("-v", dest="verbose", action="store_true", help="Verbose output.")
p.add_argument("-o", dest="disks", action="store", required=True, help="disk configuration file.")
p.add_argument("-f", dest="files", action="store", required=True, help="files directory.")
p.add_argument("-m", dest="crtfile", action="store", required=True, help="crt.map file")
p.add_argument("-d", dest="destination", action="store", required=True, help="destination directory.")
p.add_argument("-b", dest="blockmap", action="store", required=True, help="blockmap file.")
#p.add_argument("-f", dest="fileoutput", action="store", required=True, help="output data content file.")
args = p.parse_args()
#temp_path = os.path.join(args.build, "temp")
#os.makedirs(temp_path, exist_ok=True)
files_path = args.files #os.path.join(args.build, "files")
os.makedirs(files_path, exist_ok=True)
destination_path = args.destination #os.path.join(args.build, "obj")
os.makedirs(destination_path, exist_ok=True)
disks = readdisks_info(args.disks)
blockmap = readblockmap_info(args.blockmap)
map_initialize()
if os.path.exists(args.crtfile):
os.remove(args.crtfile)
# add blocks file
for d in ("britannia", "towne", "dwelling", "castle", "keep", "dungeon", "underworld"):
diskinfo = readdisks_getdiskinfo(disks, d)
starttrack = int(diskinfo[2], 0)
height = int(diskinfo[4], 0) - int(diskinfo[2], 0) + 1
diskid = int(diskinfo[1], 0) - 0x41
startbank = int(blockmap[d][0], 0)
lowhigh = int(blockmap[d][1], 0)
block_data = load_file(os.path.join(files_path, d + ".data"))
# build map and blocks
map_data[diskid*256+255] = starttrack
for b in range(0, height, 2):
# double line or single line
#factor = 2
#if b+1 >= height:
# factor = 1
# make data
bank_data = bytearray([0xff] * 0x2000)
baseaddress = calculate_address(lowhigh)
if b+1 >= height:
# one line
s = b * 256*16
l = 0x1000
bank_data[0:l] = block_data[s:s+l]
blockmap_appendentry(diskid, b, startbank, baseaddress)
else:
# two lines
s = b * 256*16
l = 0x2000
bank_data[0:l] = block_data[s:s+l]
blockmap_appendentry(diskid, b, startbank, baseaddress)
blockmap_appendentry(diskid, b+1, startbank, baseaddress+0x10)
# write data and map
filename = "{0}_{1:02d}.aprg".format(d, b)
write_prg(os.path.join(destination_path, filename), lowhigh, bank_data)
crtmap_appendentry(args.crtfile, startbank, filename, baseaddress * 0x100)
# increase values
startbank += 1
# write block map
blockmap_bank = int(blockmap["blockmap"][0], 0)
blockmap_lowhigh = int(blockmap["blockmap"][1], 0)
blockmap_address = calculate_address(blockmap_lowhigh) * 256
#blockmap_appendentry(0, b, startbank, baseaddress)
blockmapname = os.path.join(destination_path, "blockmap.aprg")
write_prg(blockmapname, blockmap_lowhigh, map_data)
crtmap_appendentry(args.crtfile, blockmap_bank, "blockmap.aprg", blockmap_address)
return 0
if __name__ == '__main__':
try:
retval = main(sys.argv)
sys.exit(retval)
except Exception as e:
print(e)
traceback.print_exc()
sys.exit(1)
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boxingbeetle/apetest | src/apetest/decode.py | c6dd7aaca014c64eec4bde7e755c4a3dec72404a | # SPDX-License-Identifier: BSD-3-Clause
"""
Text decode functions.
These functions can be used to get Unicode strings from a series of bytes.
"""
from codecs import (
BOM_UTF8,
BOM_UTF16_BE,
BOM_UTF16_LE,
BOM_UTF32_BE,
BOM_UTF32_LE,
CodecInfo,
lookup as lookup_codec,
)
from collections import OrderedDict
from typing import Dict, Iterable, Optional, Tuple
from apetest.typing import LoggerT
def encoding_from_bom(data: bytes) -> Optional[str]:
"""
Look for a byte-order-marker at the start of the given C{bytes}.
If found, return the encoding matching that BOM, otherwise return C{None}.
"""
if data.startswith(BOM_UTF8):
return "utf-8"
elif data.startswith(BOM_UTF16_LE) or data.startswith(BOM_UTF16_BE):
return "utf-16"
elif data.startswith(BOM_UTF32_LE) or data.startswith(BOM_UTF32_BE):
return "utf-32"
else:
return None
def standard_codec_name(name: str) -> str:
"""
Map a codec name to the preferred standardized version.
The preferred names were taken from this list published by IANA:
U{http://www.iana.org/assignments/character-sets/character-sets.xhtml}
@param name:
Text encoding name, in lower case.
"""
if name.startswith("iso8859"):
return "iso-8859" + name[7:]
return {
"ascii": "us-ascii",
"euc_jp": "euc-jp",
"euc_kr": "euc-kr",
"iso2022_jp": "iso-2022-jp",
"iso2022_jp_2": "iso-2022-jp-2",
"iso2022_kr": "iso-2022-kr",
}.get(name, name)
def try_decode(data: bytes, encodings: Iterable[str]) -> Tuple[str, str]:
"""
Attempt to decode text using the given encodings in order.
@param data:
Encoded version of the text.
@param encodings:
Names of the encodings to try. Must all be lower case.
@return: C{(text, encoding)}
The decoded string and the encoding used to decode it.
The returned encoding is name the preferred name, which could differ
from the name used in the C{encodings} argument.
@raise ValueError:
If the text could not be decoded.
"""
# Build sequence of codecs to try.
codecs: Dict[str, CodecInfo] = OrderedDict()
for encoding in encodings:
try:
codec = lookup_codec(encoding)
except LookupError:
pass
else:
codecs[standard_codec_name(codec.name)] = codec
# Apply decoders to the document.
for name, codec in codecs.items():
try:
text, consumed = codec.decode(data, "strict")
except UnicodeDecodeError:
continue
if consumed == len(data):
return text, name
raise ValueError("Unable to determine document encoding")
def decode_and_report(
data: bytes,
encoding_options: Iterable[Tuple[Optional[str], str]],
logger: LoggerT,
) -> Tuple[str, str]:
"""
Attempt to decode text using several encoding options in order.
@param data:
Encoded version of the text.
@param encoding_options: C{(encoding | None, source)*}
Each option is a pair of encoding name and a description of
where this encoding suggestion originated.
If the encoding name is C{None}, the option is skipped.
@param logger:
Non-fatal problems are logged here.
Such problems include an unknown or differing encodings
among the options.
@return: C{(text, encoding)}
The decoded string and the encoding used to decode it.
@raise ValueError:
If the text could not be decoded.
"""
# Filter and remember encoding options.
options = [
(encoding, source)
for encoding, source in encoding_options
if encoding is not None
]
encodings = [encoding for encoding, source in options]
# Always try to decode as UTF-8, since that is the most common encoding
# these days, plus it's a superset of ASCII so it also works for old or
# simple documents.
encodings.append("utf-8")
text, used_encoding = try_decode(data, encodings)
# Report differences between suggested encodings and the one we
# settled on.
for encoding, source in options:
try:
codec = lookup_codec(encoding)
except LookupError:
logger.warning(
'%s specifies encoding "%s", which is unknown to Python',
source,
encoding,
)
continue
std_name = standard_codec_name(codec.name)
if std_name != used_encoding:
logger.warning(
'%s specifies encoding "%s", ' 'while actual encoding seems to be "%s"',
source,
encoding,
used_encoding,
)
elif std_name != encoding:
logger.info(
'%s specifies encoding "%s", ' 'which is not the standard name "%s"',
source,
encoding,
used_encoding,
)
return text, used_encoding
| [((2223, 2236), 'collections.OrderedDict', 'OrderedDict', ([], {}), '()\n', (2234, 2236), False, 'from collections import OrderedDict\n'), ((2301, 2323), 'codecs.lookup', 'lookup_codec', (['encoding'], {}), '(encoding)\n', (2313, 2323), True, 'from codecs import BOM_UTF8, BOM_UTF16_BE, BOM_UTF16_LE, BOM_UTF32_BE, BOM_UTF32_LE, CodecInfo, lookup as lookup_codec\n'), ((4266, 4288), 'codecs.lookup', 'lookup_codec', (['encoding'], {}), '(encoding)\n', (4278, 4288), True, 'from codecs import BOM_UTF8, BOM_UTF16_BE, BOM_UTF16_LE, BOM_UTF32_BE, BOM_UTF32_LE, CodecInfo, lookup as lookup_codec\n')] |
jiangycTarheel/Compositional-Auxseq | utils.py | e4645a92c21c893cd320eb186c19d392bc147b43 | import os
import json
import gzip
from copy import deepcopy, copy
import numpy as np
import csv
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader, RandomSampler
from transformers.tokenization_utils import trim_batch
class LabelSmoothingLoss(nn.Module):
def __init__(self, label_smooth, tgt_vocab_size, ignore_index=-100):
assert 0. < label_smooth <= 1.
self.ignore_index = ignore_index
super(LabelSmoothingLoss, self).__init__()
smoothing_value = label_smooth / (tgt_vocab_size - 2)
one_hot = torch.full((tgt_vocab_size,), smoothing_value)
one_hot[self.ignore_index] = 0
self.register_buffer('one_hot', one_hot.unsqueeze(0).unsqueeze(0))
self.confidence = 1.0 - label_smooth
self.lossfct = torch.nn.KLDivLoss(reduction='none')
def forward(self, pred, target):
"""
Args:
pred: [bsz, seq_len, vocab_size]
target: [bsz, seq_len]
Returns:
"""
model_prob = self.one_hot.repeat(target.size(0), target.size(1), 1) # [bsz, seq_len, vocab_size]
model_prob.scatter_(2, target.unsqueeze(2), self.confidence)
model_prob.masked_fill_((target == self.ignore_index).unsqueeze(2), 0)
pred_prob = F.log_softmax(pred, dim=2)
#return F.kl_div(pred_prob, model_prob, reduction='mean')
loss = self.lossfct(pred_prob, model_prob)
loss = torch.sum(loss, dim=2).masked_fill_((target == self.ignore_index), 0)
avg_loss = torch.sum(loss) / torch.sum((target != self.ignore_index).to(torch.float))
return avg_loss
# Special symbols
SOS_token = "<SOS>" # start of sentence
EOS_token = "<EOS>" # end of sentence
PAD_token = SOS_token # padding symbol
INPUT_TOKENS_SCAN = ['jump', 'opposite', 'right', 'twice', 'and', 'turn', 'thrice', 'run', 'after', 'around', 'left', 'walk', 'look']
OUTPUT_TOKENS_SCAN = ['I_TURN_RIGHT', 'I_JUMP', 'I_TURN_LEFT', 'I_RUN', 'I_WALK', 'I_LOOK']
# ACTION_TO_TEXT = {'I_TURN_RIGHT': 'right', 'I_JUMP': 'jump', 'I_TURN_LEFT': 'left', 'I_RUN': 'run', 'I_WALK': 'walk', 'I_LOOK': 'look'}
class Lang:
# Class for converting strings/words to numerical indices, and vice versa.
# Should use separate class for input language (English) and output language (actions)
#
def __init__(self, symbols, io_type):
# symbols : list of all possible symbols
n = len(symbols)
self.symbols = [_s.strip('\n') for _s in symbols]
self.io_type = io_type
if SOS_token not in self.symbols:
assert EOS_token not in self.symbols
self.index2symbol = {n: SOS_token, n+1: EOS_token}
self.symbol2index = {SOS_token: n, EOS_token: n + 1}
self.sos_id, self.eos_id = n, n + 1
else:
self.index2symbol = {}
self.symbol2index = {}
self.sos_id, self.eos_id = 0, 1
self.pad_token_id = self.sos_id
for idx,s in enumerate(self.symbols):
self.index2symbol[idx] = s
self.symbol2index[s] = idx
self.n_symbols = len(self.index2symbol)
def variableFromSymbols(self, mylist, add_eos=True):
# Convert a list of symbols to a tensor of indices (adding a EOS token at end)
#
# Input
# mylist : list of m symbols
# add_eos : true/false, if true add the EOS symbol at end
#
# Output
# output : [m or m+1 LongTensor] indices of each symbol (plus EOS if appropriate)
mylist = copy(mylist)
if add_eos:
mylist.append(EOS_token)
indices = [self.symbol2index[s] for s in mylist]
output = torch.LongTensor(indices)
#if USE_CUDA:
output = output.cuda()
return output
def symbolsFromVector(self, v):
# Convert indices to symbols, breaking where we get a EOS token
#
# Input
# v : list of m indices
#
# Output
# mylist : list of m or m-1 symbols (excluding EOS)
mylist = []
for x in v:
s = self.index2symbol[x]
if s == EOS_token:
break
mylist.append(s)
return mylist
def encode_scan_file(self, data, max_length):
encoded_data = []
for dp in data:
input, output = dp[0], dp[1]
if self.io_type == 'input':
raw = input
else:
assert self.io_type == 'output'
raw = output
encoded = self.variableFromSymbols(raw.split(' '))
encoded_data.append(encoded)
return encoded_data
def encode_scan_file_2_seg(self, data, max_length, cutoffs):
encoded_data_1, encoded_data_2 = [], []
for _id, dp in enumerate(data):
input, output, cutoff = dp[0], dp[1], cutoffs[_id]
assert self.io_type == 'output'
raw = output
encoded_1 = self.variableFromSymbols(raw.split(' ')[:cutoff])
encoded_2 = self.variableFromSymbols(raw.split(' ')[cutoff:])
encoded_data_1.append(encoded_1)
encoded_data_2.append(encoded_2)
return encoded_data_1, encoded_data_2
def encode_cfq_file(self, data, max_length):
encoded_data = []
for dp in data:
input, output = dp['query_ids'], dp['sparql_ids']
if self.io_type == 'input':
raw = input
else:
assert self.io_type == 'output'
raw = output + [self.eos_id]
encoded = torch.LongTensor(raw).cuda()
encoded_data.append(encoded)
return encoded_data
def encode_cogs_file(self, data, max_length):
encoded_data = []
for dp in data:
input, output = dp['src'], dp['trg']
if self.io_type == 'input':
raw = input
else:
assert self.io_type == 'output'
raw = output
encoded = self.variableFromSymbols(raw.split(' '))
encoded_data.append(encoded)
return encoded_data
def decode(self, ids):
out = self.symbolsFromVector(ids.cpu().numpy())
if out == []:
return out
if out[0] in ['<SOS>', '<SOS_2>']:
out = out[1:]
return out
def calculate_accuracy(preds, gts):
assert len(preds) == len(gts)
match = 0
for pred, gt in zip(preds, gts):
if pred == gt:
match += 1
return match / len(preds)
def encode_file(tokenizer, data_path, max_length, pad_to_max_length=True, return_tensors="pt", max_examples=None):
examples = []
if data_path[-3:] == '.gz':
print('Data file is gzipped')
f = gzip.open(data_path, "rt")
else:
print('Data file is plain text')
print(data_path)
f = open(data_path, "r", encoding='utf-8')
for i, text in enumerate(f.readlines()):
tokenized = tokenizer.batch_encode_plus( [text + ' </s>'], max_length=max_length,
pad_to_max_length=pad_to_max_length, return_tensors=return_tensors )
if max_examples and i >= max_examples:
break
examples.append(tokenized)
f.close()
return examples
# def encode_file_iterator(tokenizer, data_path, max_length, pad_to_max_length=True, return_tensors="pt", max_examples=None):
# '''
# This provides a low-memory usage way of iterating thru all of the source/target lines for processing by JIT loader.
# '''
# if data_path[-3:] == '.gz':
# print('Data file is gzipped')
# f = gzip.open(data_path, "rt")
# else:
# print('Data file is plain text')
# f = open(data_path, "r", encoding='utf-8')
#
# for i, text in enumerate(f):
#
# tokenized = tokenizer.batch_encode_plus( [text + ' </s>'], max_length=max_length,
# pad_to_max_length=pad_to_max_length, return_tensors=return_tensors )
#
# yield tokenized
#
# if max_examples and i >= max_examples:
# break
#
# f.close()
# def convert_scan_actions_to_text(actions):
# return ' '.join([ACTION_TO_TEXT[_action] for _action in actions.split(' ')])
# def encode_scan_file(tokenizer, data, io_type, max_length, pad_to_max_length=True, return_tensors="pt", max_examples=None):
# examples = []
# # a = tokenizer.batch_encode_plus( ['right jump left run walk look' + ' <s> </s>'], max_length=max_length,
# # pad_to_max_length=pad_to_max_length, return_tensors=return_tensors )
# # print(a)
# # exit()
# for dp in data:
# input, output = dp[0], dp[1]
# if io_type == 'input':
# raw = input
# else:
# assert io_type == 'output'
# raw = convert_scan_actions_to_text(output)
#
# tokenized = tokenizer.batch_encode_plus( [raw + ' </s>'], max_length=max_length,
# pad_to_max_length=pad_to_max_length, return_tensors=return_tensors )
#
# if max_examples and i >= max_examples:
# break
# examples.append(tokenized)
#
# return examples
def load_scan_file(mytype, split):
# Load SCAN dataset from file
#
# Input
# mytype : type of SCAN experiment
# split : 'train' or 'test'
#
# Output
# commands : list of input/output strings (as tuples)
assert mytype in ['simple', 'addprim_jump', 'length', 'addprim_turn_left', 'all', 'template_around_right', 'viz',
'examine', 'template_jump_around_right', 'template_right', 'template_around_right',
'mcd1', 'mcd2', 'mcd3', 'mcd1.1', 'mcd1.2', 'debug', 'attn_vis']
assert split in ['train', 'test', 'val']
if split == 'val' and mytype not in ['mcd1', 'mcd2', 'mcd3', 'mcd1.1', 'mcd1.2']:
split = 'test'
fn = 'data/scan/tasks_' + split + '_' + mytype + '.txt'
fid = open(fn, 'r')
lines = fid.readlines()
fid.close()
lines = [l.strip() for l in lines]
lines = [l.lstrip('IN: ') for l in lines]
commands = [l.split(' OUT: ') for l in lines]
return commands
class CompositionDataset(Dataset):
def __init__(
self,
src_lang,
trg_lang,
data_dir,
type_path,
sub_task,
max_source_length=20,
max_target_length=20,
tokenized=False,
):
super().__init__()
self.max_source_length = max_source_length
self.max_target_length = max_target_length
self.tokenized = tokenized
self.src_lang = src_lang
self.trg_lang = trg_lang
def __len__(self):
if self.tokenized:
return len(self.dataset)
else:
return len(self.source)
def __getitem__(self, index):
if self.tokenized:
dp = self.dataset[index]
source_ids, src_mask, target_ids = dp[0], dp[1], dp[2]
source_ids = source_ids[:self.max_source_length]
#src_mask = src_mask[:self.max_source_length]
target_ids = target_ids[:self.max_target_length]
else:
source_ids = self.source[index]
target_ids = self.target[index]
return {"source_ids": source_ids, "target_ids": target_ids}
@staticmethod
def trim_seq2seq_batch(batch, src_pad_token_id, trg_pad_token_id, trim_y=True):
if trim_y:
y = trim_batch(batch["target_ids"], trg_pad_token_id)
else:
y = batch["target_ids"]
source_ids, source_mask = trim_batch(batch["source_ids"], src_pad_token_id, attention_mask=batch["source_mask"])
return source_ids, source_mask, y
def pad_to_max_len(self, ids, max_len, pad_token_id):
ids_length = ids.size(0)
if ids_length == max_len:
return ids
pad_tokens = torch.tensor([pad_token_id] * (max_len - ids_length))
# if ids.type() == 'torch.cuda.FloatTensor':
# print(ids)
# exit()
padded_ids = torch.cat([ids, pad_tokens.cuda()])
return padded_ids
def create_mask(self, ids, max_len):
ids_length = ids.size(0)
mask = torch.tensor([1] * ids_length + [0] * (max_len - ids_length)).cuda()
return mask
def collate_fn(self, batch):
max_src_len = max(map(len, [x["source_ids"] for x in batch]))
max_trg_len = max(map(len, [x["target_ids"] for x in batch]))
src_mask = torch.stack([self.create_mask(x["source_ids"], max_src_len) for x in batch])
src_ids = torch.stack([self.pad_to_max_len(x["source_ids"], max_src_len, self.src_lang.pad_token_id) for x in batch])
#masks = torch.stack([x["source_mask"] for x in batch])
trg_ids = torch.stack([self.pad_to_max_len(x["target_ids"], max_trg_len, self.trg_lang.pad_token_id) for x in batch])
y = trim_batch(trg_ids, self.trg_lang.pad_token_id)
src_ids, src_mask = trim_batch(src_ids, self.src_lang.pad_token_id, attention_mask=src_mask)
return {"source_ids": src_ids, "source_mask": src_mask, "target_ids": y}
class ScanDataset(CompositionDataset):
def __init__(
self,
src_lang,
trg_lang,
data_dir="./data/scan/",
type_path="train",
sub_task="addprim_jump",
max_source_length=20,
max_target_length=20,
tokenized=False,
):
super().__init__(src_lang, trg_lang, data_dir, type_path, sub_task, max_source_length,
max_target_length, tokenized)
scan_data = load_scan_file(sub_task, type_path)
print(len(scan_data))
all_scan_dict = self.convert_to_dict(load_scan_file('all', 'train'))
self.action_count_labels, self.action_group_labels, self.action_type_labels = self.construct_count_label(scan_data, all_scan_dict)
if not tokenized:
self.source = self.src_lang.encode_scan_file(scan_data, max_source_length)
self.target = self.trg_lang.encode_scan_file(scan_data, max_target_length)
else:
self.dataset = torch.load(os.path.join(data_dir, type_path))
def construct_count_label(self, raw_data, all_data_dict):
all_count_labels = []
count_label_scheme = "v1"
group_label_scheme = "v2"
type_label_scheme = "v2"
all_action_group_labels, all_action_type_labels = [], []
# Group 1: single prim (jump), Group 2: prim + direction (jump left), Group 3: prim opposite, Group 4: prim around
#no_skip_id = np.random.randint(0, len(raw_data), int(len(raw_data)*0.05))
#no_skip_id = np.random.choice(range(len(raw_data)), int(len(raw_data)*0.07), replace=False)
# no_skip_id = np.random.choice(range(len(raw_data)), 10, replace=False)
skip_cnt, sup_cnt = 0, 0
for _id, dp in enumerate(raw_data):
input_text, output_text = dp[0], dp[1]
input_tok, output_tok = input_text.split(' '), output_text.split(' ')
count_labels, group_labels, type_labels = [], [], []
first_part_output_text, second_part_output_text = '', ''
if 'and' in input_tok:
first_part_input_tok = input_tok[:input_tok.index('and')]
second_part_input_tok = input_tok[input_tok.index('and')+1:]
first_part_output_text = all_data_dict[' '.join(first_part_input_tok)]
second_part_output_text = all_data_dict[' '.join(second_part_input_tok)]
elif 'after' in input_tok:
second_part_input_tok = input_tok[:input_tok.index('after')]
first_part_input_tok = input_tok[input_tok.index('after') + 1:]
first_part_output_text = all_data_dict[' '.join(first_part_input_tok)]
second_part_output_text = all_data_dict[' '.join(second_part_input_tok)]
else:
first_part_input_tok, second_part_input_tok = input_tok, []
first_part_output_text = output_text
first_part_output_tok, second_part_output_tok = first_part_output_text.split(' '), second_part_output_text.split(' ')
if second_part_output_text == '':
second_part_output_tok = []
assert len(first_part_output_tok) + len(second_part_output_tok) == len(output_tok), \
(len(first_part_output_tok), len(second_part_output_tok), len(output_tok), first_part_output_text, second_part_output_text, output_text)
### 1. Build the action count labels ###
if count_label_scheme == 'v1':
### For the first part output
if 'twice' in first_part_input_tok:
if 'after' in input_tok:
count_labels += ([4] * int(len(first_part_output_tok) / 2) + [3] * int(len(first_part_output_tok) / 2))
else:
count_labels += ([1] * int(len(first_part_output_tok) / 2) + [0] * int(len(first_part_output_tok) / 2))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok) / 2) - 1)) * 2
elif 'thrice' in first_part_input_tok:
if 'after' in input_tok:
count_labels += ([5] * int(len(first_part_output_tok) / 3) + [4] * int(len(first_part_output_tok) / 3) + \
[3] * int(len(first_part_output_tok) / 3))
else:
count_labels += ([2] * int(len(first_part_output_tok) / 3) + [1] * int(len(first_part_output_tok) / 3) + \
[0] * int(len(first_part_output_tok) / 3))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok) / 3) - 1)) * 3
else:
if 'after' in input_tok:
count_labels += ([3] * len(first_part_output_tok))
else:
count_labels += ([0] * len(first_part_output_tok))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok)) - 1))
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
if 'after' in input_tok:
count_labels += ([1] * int(len(second_part_output_tok) / 2) + [0] * int(len(second_part_output_tok) / 2))
else:
count_labels += ([4] * int(len(second_part_output_tok) / 2) + [3] * int(len(second_part_output_tok) / 2))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok) / 2) - 1)) * 2
elif 'thrice' in second_part_input_tok:
if 'after' in input_tok:
count_labels += ([2] * int(len(second_part_output_tok) / 3) + [1] * int(len(second_part_output_tok) / 3) + \
[0] * int(len(second_part_output_tok) / 3))
else:
count_labels += ([5] * int(len(second_part_output_tok) / 3) + [4] * int(len(second_part_output_tok) / 3) + \
[3] * int(len(second_part_output_tok) / 3))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok) / 3) - 1)) * 3
else:
if 'after' in input_tok:
count_labels += ([0] * len(second_part_output_tok))
else:
count_labels += ([3] * len(second_part_output_tok))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok)) - 1))
elif count_label_scheme == 'v2':
### For the first part output
if 'twice' in first_part_input_tok:
count_labels += ([1] * int(len(first_part_output_tok) / 2) + [0] * int(
len(first_part_output_tok) / 2))
elif 'thrice' in first_part_input_tok:
count_labels += ([2] * int(len(first_part_output_tok) / 3) + [1] * int(
len(first_part_output_tok) / 3) + \
[0] * int(len(first_part_output_tok) / 3))
else:
count_labels += ([0] * len(first_part_output_tok))
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
count_labels += ([1] * int(len(second_part_output_tok) / 2) + [0] * int(
len(second_part_output_tok) / 2))
elif 'thrice' in second_part_input_tok:
count_labels += ([2] * int(len(second_part_output_tok) / 3) + [1] * int(
len(second_part_output_tok) / 3) + [0] * int(len(second_part_output_tok) / 3))
else:
count_labels += ([0] * len(second_part_output_tok))
elif count_label_scheme == 'v3':
### For the first part output
if 'thrice' in first_part_input_tok and 'thrice' in second_part_input_tok:
start_count = 5
elif ('thrice' in first_part_input_tok and 'twice' in second_part_input_tok) or \
('twice' in first_part_input_tok and 'thrice' in second_part_input_tok):
start_count = 4
elif ('twice' in first_part_input_tok and 'twice' in second_part_input_tok) or \
('thrice' in first_part_input_tok) or ('thrice' in second_part_input_tok):
start_count = 3
elif 'twice' in first_part_input_tok or 'twice' in second_part_input_tok:
start_count = 2
else:
start_count = 1
if 'twice' in first_part_input_tok:
if 'after' in input_tok:
count_labels += ([start_count] * int(len(first_part_output_tok) / 2) + [start_count-1] * int(len(first_part_output_tok) / 2))
else:
count_labels += ([1] * int(len(first_part_output_tok) / 2) + [0] * int(len(first_part_output_tok) / 2))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok) / 2) - 1)) * 2
elif 'thrice' in first_part_input_tok:
if 'after' in input_tok:
count_labels += ([start_count] * int(len(first_part_output_tok) / 3) + [start_count-1] * int(len(first_part_output_tok) / 3) + \
[start_count-2] * int(len(first_part_output_tok) / 3))
else:
count_labels += ([2] * int(len(first_part_output_tok) / 3) + [1] * int(len(first_part_output_tok) / 3) + \
[0] * int(len(first_part_output_tok) / 3))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok) / 3) - 1)) * 3
else:
if 'after' in input_tok:
count_labels += ([start_count] * len(first_part_output_tok))
else:
count_labels += ([0] * len(first_part_output_tok))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok)) - 1))
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
if 'after' in input_tok:
count_labels += ([1] * int(len(second_part_output_tok) / 2) + [0] * int(len(second_part_output_tok) / 2))
else:
count_labels += ([start_count] * int(len(second_part_output_tok) / 2) + [start_count-1] * int(len(second_part_output_tok) / 2))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok) / 2) - 1)) * 2
elif 'thrice' in second_part_input_tok:
if 'after' in input_tok:
count_labels += ([2] * int(len(second_part_output_tok) / 3) + [1] * int(len(second_part_output_tok) / 3) + \
[0] * int(len(second_part_output_tok) / 3))
else:
count_labels += ([start_count] * int(len(second_part_output_tok) / 3) + [start_count-1] * int(len(second_part_output_tok) / 3) + \
[start_count-2] * int(len(second_part_output_tok) / 3))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok) / 3) - 1)) * 3
else:
if 'after' in input_tok:
count_labels += ([0] * len(second_part_output_tok))
else:
count_labels += ([start_count] * len(second_part_output_tok))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok)) - 1))
elif count_label_scheme == 'v3.1':
### For the first part output
if 'thrice' in first_part_input_tok and 'thrice' in second_part_input_tok:
start_count = 5
elif ('thrice' in first_part_input_tok and 'twice' in second_part_input_tok) or \
('twice' in first_part_input_tok and 'thrice' in second_part_input_tok):
start_count = 4
elif ('twice' in first_part_input_tok and 'twice' in second_part_input_tok) or \
('thrice' in first_part_input_tok) or ('thrice' in second_part_input_tok):
start_count = 3
elif 'twice' in first_part_input_tok or 'twice' in second_part_input_tok:
start_count = 2
else:
start_count = 1
if 'twice' in first_part_input_tok:
count_labels += ([start_count] * int(len(first_part_output_tok) / 2) + [start_count - 1] * int(
len(first_part_output_tok) / 2))
# count_labels += ([1] + [0] * (int(len(first_part_output_tok) / 2) - 1)) * 2
elif 'thrice' in first_part_input_tok:
count_labels += ([start_count] * int(len(first_part_output_tok) / 3) + [start_count - 1] * int(
len(first_part_output_tok) / 3) + \
[start_count - 2] * int(len(first_part_output_tok) / 3))
else:
count_labels += ([start_count] * len(first_part_output_tok))
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
count_labels += ([1] * int(len(second_part_output_tok) / 2) + [0] * int(
len(second_part_output_tok) / 2))
# count_labels += ([1] + [0] * (int(len(second_part_output_tok) / 2) - 1)) * 2
elif 'thrice' in second_part_input_tok:
count_labels += ([2] * int(len(second_part_output_tok) / 3) + [1] * int(
len(second_part_output_tok) / 3) + \
[0] * int(len(second_part_output_tok) / 3))
else:
count_labels += ([0] * len(second_part_output_tok))
else:
### For the first part output
if 'twice' in first_part_input_tok:
if 'after' in input_tok:
new_count_labels = list(range(int(len(first_part_output_tok) / 2)))[::-1] * 2
else:
new_count_labels = list(range(int(len(first_part_output_tok) / 2)))[::-1] * 2
elif 'thrice' in first_part_input_tok:
if 'after' in input_tok:
new_count_labels = list(range(int(len(first_part_output_tok) / 3)))[::-1] * 3
else:
new_count_labels = list(range(int(len(first_part_output_tok) / 3)))[::-1] * 3
else:
if 'after' in input_tok:
new_count_labels = list(range(len(first_part_output_tok)))[::-1]
else:
new_count_labels = list(range(len(first_part_output_tok)))[::-1]
count_labels += new_count_labels
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
if 'after' in input_tok:
new_count_labels = list(range(int(len(second_part_output_tok) / 2)))[::-1] * 2
new_count_labels = [_c + 8 for _c in new_count_labels]
else:
new_count_labels = list(range(int(len(second_part_output_tok) / 2)))[::-1] * 2
new_count_labels = [_c + 8 for _c in new_count_labels]
elif 'thrice' in second_part_input_tok:
if 'after' in input_tok:
new_count_labels = list(range(int(len(second_part_output_tok) / 3)))[::-1] * 3
new_count_labels = [_c + 8 for _c in new_count_labels]
else:
new_count_labels = list(range(int(len(second_part_output_tok) / 3)))[::-1] * 3
new_count_labels = [_c + 8 for _c in new_count_labels]
else:
if 'after' in input_tok:
new_count_labels = list(range(len(second_part_output_tok)))[::-1]
new_count_labels = [_c + 8 for _c in new_count_labels]
else:
new_count_labels = list(range(len(second_part_output_tok)))[::-1]
new_count_labels = [_c + 8 for _c in new_count_labels]
count_labels += new_count_labels
# count_labels = []
# count_labels += list(range(len(first_part_output_tok)))[::-1]
# count_labels += list(range(len(second_part_output_tok)))[::-1]
assert len(count_labels) == len(output_tok), (len(count_labels), len(output_tok), input_text, first_part_input_tok, count_labels, output_tok,
first_part_output_text, first_part_output_tok, second_part_output_text, second_part_output_tok)
count_labels.append(-1) # For the EOS token
# count_labels.append(7) # For the EOS token
### 2. Build the action group labels ###
if group_label_scheme == 'v1': ## As used in exp 9.0-9.4
if 'around' in first_part_input_tok:
if 'after' in input_tok:
group_labels += ([4] * len(first_part_output_tok))
else:
group_labels += ([0] * len(first_part_output_tok))
elif 'opposite' in first_part_input_tok:
if 'after' in input_tok:
group_labels += ([5] * len(first_part_output_tok))
else:
group_labels += ([1] * len(first_part_output_tok))
elif 'left' in first_part_input_tok or 'right' in first_part_input_tok:
if 'after' in input_tok:
group_labels += ([6] * len(first_part_output_tok))
else:
group_labels += ([2] * len(first_part_output_tok))
else:
if 'after' in input_tok:
group_labels += ([7] * len(first_part_output_tok))
else:
group_labels += ([3] * len(first_part_output_tok))
if 'around' in second_part_input_tok:
if 'after' in input_tok:
group_labels += ([0] * len(second_part_output_tok))
else:
group_labels += ([4] * len(second_part_output_tok))
elif 'opposite' in second_part_input_tok:
if 'after' in input_tok:
group_labels += ([1] * len(second_part_output_tok))
else:
group_labels += ([5] * len(second_part_output_tok))
elif 'left' in second_part_input_tok or 'right' in second_part_input_tok:
if 'after' in input_tok:
group_labels += ([2] * len(second_part_output_tok))
else:
group_labels += ([6] * len(second_part_output_tok))
else:
if 'after' in input_tok:
group_labels += ([3] * len(second_part_output_tok))
else:
group_labels += ([7] * len(second_part_output_tok))
else:
### For the first part output
if 'twice' in first_part_input_tok:
if 'after' in input_tok:
new_group_labels = list(range(int(len(first_part_output_tok) / 2)))[::-1] * 2
new_group_labels = [_c + 8 for _c in new_group_labels]
else:
new_group_labels = list(range(int(len(first_part_output_tok) / 2)))[::-1] * 2
elif 'thrice' in first_part_input_tok:
if 'after' in input_tok:
new_group_labels = list(range(int(len(first_part_output_tok) / 3)))[::-1] * 3
new_group_labels = [_c + 8 for _c in new_group_labels]
else:
new_group_labels = list(range(int(len(first_part_output_tok) / 3)))[::-1] * 3
else:
if 'after' in input_tok:
new_group_labels = list(range(len(first_part_output_tok)))[::-1]
new_group_labels = [_c + 8 for _c in new_group_labels]
else:
new_group_labels = list(range(len(first_part_output_tok)))[::-1]
group_labels += new_group_labels
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
if 'after' in input_tok:
new_group_labels = list(range(int(len(second_part_output_tok) / 2)))[::-1] * 2
else:
new_group_labels = list(range(int(len(second_part_output_tok) / 2)))[::-1] * 2
new_group_labels = [_c + 8 for _c in new_group_labels]
elif 'thrice' in second_part_input_tok:
if 'after' in input_tok:
new_group_labels = list(range(int(len(second_part_output_tok) / 3)))[::-1] * 3
else:
new_group_labels = list(range(int(len(second_part_output_tok) / 3)))[::-1] * 3
new_group_labels = [_c + 8 for _c in new_group_labels]
else:
if 'after' in input_tok:
new_group_labels = list(range(len(second_part_output_tok)))[::-1]
else:
new_group_labels = list(range(len(second_part_output_tok)))[::-1]
new_group_labels = [_c + 8 for _c in new_group_labels]
group_labels += new_group_labels
assert len(group_labels) == len(output_tok)
group_labels.append(-1) # For the EOS token
# group_labels.append(17) # For the EOS token
### 3. Build the action type labels ###
### For the first part output
if type_label_scheme == 'v1':
if 'around' in first_part_input_tok:
new_type_labels = [3] * len(first_part_output_tok)
elif 'opposite' in first_part_input_tok:
new_type_labels = [2] * len(first_part_output_tok)
elif 'left' in first_part_input_tok or 'right' in first_part_input_tok:
new_type_labels = [1] * len(first_part_output_tok)
else:
new_type_labels = [0] * len(first_part_output_tok)
# if 'after' in input_tok:
# new_type_labels = [_c + 4 for _c in new_type_labels]
type_labels += new_type_labels
### For the second part output
if len(second_part_output_tok) > 0:
if 'around' in second_part_input_tok:
new_type_labels = [3] * len(second_part_output_tok)
elif 'opposite' in second_part_input_tok:
new_type_labels = [2] * len(second_part_output_tok)
elif 'left' in second_part_input_tok or 'right' in second_part_input_tok:
new_type_labels = [1] * len(second_part_output_tok)
else:
new_type_labels = [0] * len(second_part_output_tok)
# if 'after' not in input_tok:
# new_type_labels = [_c + 4 for _c in new_type_labels]
type_labels += new_type_labels
elif type_label_scheme == 'v2':
if 'twice' in first_part_input_tok:
type_labels += ([1] * int(len(first_part_output_tok) / 2) + [0] * int(
len(first_part_output_tok) / 2))
elif 'thrice' in first_part_input_tok:
type_labels += ([2] * int(len(first_part_output_tok) / 3) + [1] * int(
len(first_part_output_tok) / 3) + \
[0] * int(len(first_part_output_tok) / 3))
else:
type_labels += ([0] * len(first_part_output_tok))
### For the second part output
if len(second_part_output_tok) > 0:
if 'twice' in second_part_input_tok:
type_labels += ([1] * int(len(second_part_output_tok) / 2) + [0] * int(
len(second_part_output_tok) / 2))
elif 'thrice' in second_part_input_tok:
type_labels += ([2] * int(len(second_part_output_tok) / 3) + [1] * int(
len(second_part_output_tok) / 3) + [0] * int(len(second_part_output_tok) / 3))
else:
type_labels += ([0] * len(second_part_output_tok))
assert len(type_labels) == len(output_tok)
type_labels.append(-1) # For the EOS token
# group_labels.append(17) # For the EOS token
# if _id not in no_skip_id:
# count_labels = [-1] * len(count_labels)
# group_labels = [-1] * len(group_labels)
# skip_cnt += 1
# else:
# sup_cnt += 1
all_action_type_labels.append(torch.tensor(type_labels).cuda())
all_count_labels.append(torch.tensor(count_labels).cuda())
all_action_group_labels.append(torch.tensor(group_labels).cuda())
print(skip_cnt, sup_cnt)
return all_count_labels, all_action_group_labels, all_action_type_labels
def convert_to_dict(self, raw_data):
dict_data = {}
for dp in raw_data:
input, output = dp[0], dp[1]
assert input not in dict_data
dict_data[input] = output
return dict_data
def __getitem__(self, index):
if self.tokenized:
dp = self.dataset[index]
source_ids, src_mask, target_ids = dp[0], dp[1], dp[2]
source_ids = source_ids[:self.max_source_length]
#src_mask = src_mask[:self.max_source_length]
target_ids = target_ids[:self.max_target_length]
else:
source_ids = self.source[index]
target_ids = self.target[index]
count_labels = self.action_count_labels[index]
group_labels = self.action_group_labels[index]
type_labels = self.action_type_labels[index]
return {"source_ids": source_ids, "target_ids": target_ids, "action_count_labels": count_labels,
"action_group_labels": group_labels, "action_type_labels": type_labels}
@staticmethod
def trim_seq2seq_batch(batch, src_pad_token_id, trg_pad_token_id, trim_y=True):
if trim_y:
y = trim_batch(batch["target_ids"], trg_pad_token_id)
else:
y = batch["target_ids"]
source_ids, source_mask = trim_batch(batch["source_ids"], src_pad_token_id, attention_mask=batch["source_mask"])
return source_ids, source_mask, y
def collate_fn(self, batch):
max_src_len = max(map(len, [x["source_ids"] for x in batch]))
max_trg_len = max(map(len, [x["target_ids"] for x in batch]))
src_mask = torch.stack([self.create_mask(x["source_ids"], max_src_len) for x in batch])
trg_mask = torch.stack([self.create_mask(x["target_ids"], max_trg_len) for x in batch])
src_ids = torch.stack([self.pad_to_max_len(x["source_ids"], max_src_len, self.src_lang.pad_token_id) for x in batch])
#masks = torch.stack([x["source_mask"] for x in batch])
trg_ids = torch.stack([self.pad_to_max_len(x["target_ids"], max_trg_len, self.trg_lang.pad_token_id) for x in batch])
action_count_labels = torch.stack([self.pad_to_max_len(x["action_count_labels"], max_trg_len, -1) for x in batch])
action_group_labels = torch.stack([self.pad_to_max_len(x["action_group_labels"], max_trg_len, -1) for x in batch])
action_type_labels = torch.stack(
[self.pad_to_max_len(x["action_type_labels"], max_trg_len, -1) for x in batch])
y = trim_batch(trg_ids, self.trg_lang.pad_token_id)
#action_count_labels = trim_batch(action_count_labels, -1)
# _src_ids, src_mask = trim_batch(src_ids, self.src_lang.pad_token_id, attention_mask=src_mask)
# print(_src_ids.size(), src_ids.size())
return {"source_ids": src_ids, "source_mask": src_mask, "target_ids": y, "target_mask": trg_mask,
"action_count_labels": action_count_labels, "action_group_labels": action_group_labels,
"action_type_labels": action_type_labels}
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intellineers/django-bridger | bridger/serializers/fields/related.py | ed097984a99df7da40a4d01bd00c56e3c6083056 | from typing import Dict
from rest_framework import serializers
from rest_framework.fields import empty
from rest_framework.relations import ManyRelatedField
from rest_framework.request import Request
from .mixins import BridgerSerializerFieldMixin
from .types import BridgerType, ReturnContentType
class BridgerManyRelatedField(ManyRelatedField):
def __init__(self, *args, **kwargs):
required = kwargs.get("required", True)
if not required:
kwargs["allow_null"] = True
super().__init__(*args, **kwargs)
def run_validation(self, data=empty):
# If the data is send through form data, we need to convert the data into a proper list of ids
if data not in [None, empty] and len(data) == 1 and isinstance(data[0], str) and "," in data[0]:
data = data[0].split(",")
# If the data is a list of an empty string we need to convert it (FORM DATA)
if data not in [None, empty] and len(data) == 1 and isinstance(data[0], str) and data[0] == "":
data = []
# If the data is a list and contains the string null, then we need to convert it (FORM DATA)
if data == ["null"]:
data = []
# If the data is None and null is an allowed value, data needs to be set to an empty list
if data is None and self.allow_null:
data = []
return super().run_validation(data)
def get_representation(self, request: Request, field_name: str) -> Dict:
representation = self.child_relation.get_representation(request, field_name)
representation["multiple"] = True
return representation
class PrimaryKeyRelatedField(BridgerSerializerFieldMixin, serializers.PrimaryKeyRelatedField):
MANY_RELATION_KWARGS = (
"read_only",
"write_only",
"required",
"default",
"initial",
"source",
"label",
"help_text",
"style",
"error_messages",
"allow_empty",
"html_cutoff",
"html_cutoff_text",
"allow_null",
)
def __init__(self, *args, **kwargs):
self.field_type = kwargs.pop("field_type", BridgerType.SELECT.value)
super().__init__(*args, **kwargs)
def __new__(cls, *args, **kwargs):
kwargs["style"] = {"base_template": "input.html"}
return super().__new__(cls, *args, **kwargs)
@classmethod
def many_init(cls, *args, **kwargs):
list_kwargs = {"child_relation": cls(*args, **kwargs)}
for key in kwargs:
if key in cls.MANY_RELATION_KWARGS:
list_kwargs[key] = kwargs[key]
return BridgerManyRelatedField(**list_kwargs)
def run_validation(self, data=empty):
if isinstance(data, str) and data == "null":
data = None
if data is empty:
parent_model_id = self.parent.context["view"].kwargs.get(f"{self.field_name}_id")
if parent_model_id:
data = parent_model_id
return super().run_validation(data)
class ListSerializer(serializers.ListSerializer):
"""
A Wrapper around the normal DRF ListSerializer which also return the child representation
"""
def get_representation(self, request: Request, field_name: str) -> Dict:
representation = self.child.get_representation(request, field_name)
representation["multiple"] = True
representation["related_key"] = self.source
return representation
| [] |
wenyuanyu/GraphScope | python/graphscope/experimental/nx/tests/algorithms/forward/operators/test_product.py | a40ccaf70557e608d8b091eb25ab04477f99ce21 | import networkx.algorithms.operators.tests.test_product
import pytest
from graphscope.experimental.nx.utils.compat import import_as_graphscope_nx
import_as_graphscope_nx(networkx.algorithms.operators.tests.test_product,
decorators=pytest.mark.usefixtures("graphscope_session"))
def test_tensor_product_combinations():
# basic smoke test, more realistic tests would be useful
P5 = nx.path_graph(5)
K3 = nx.complete_graph(3)
G = nx.tensor_product(P5, K3)
assert nx.number_of_nodes(G) == 5 * 3
G = nx.tensor_product(nx.DiGraph(P5), nx.DiGraph(K3))
assert nx.number_of_nodes(G) == 5 * 3
@pytest.mark.skip(reason="not support multigraph")
def test_cartesian_product_multigraph():
pass
def test_lexicographic_product_combinations():
P5 = nx.path_graph(5)
K3 = nx.complete_graph(3)
G = nx.lexicographic_product(P5, K3)
assert nx.number_of_nodes(G) == 5 * 3
def test_strong_product_combinations():
P5 = nx.path_graph(5)
K3 = nx.complete_graph(3)
G = nx.strong_product(P5, K3)
assert nx.number_of_nodes(G) == 5 * 3
@pytest.mark.skip(reason="not support multigraph")
def test_graph_power_raises():
pass
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schleising/banter-bot | Footy/UnsupportedBantzStrings.py | 3e51453ae993d2c26dc51464a3cef3875a6be3c9 | # {team} -> Name of team
# {name} -> Name of person who supports team
teamMatchStarted: list[str] = [
"{team} are shit",
"{team} cunts",
"Dirty {team}",
"Dirty {team}, dirty {name}",
]
drawing: list[str] = [
"{team} level, this is a shit match",
"Boring old {team}",
"Happy with how it's going, {name}?",
"Yawn...",
"{team} wankers",
"How can you support this rubbish, {name}?",
"You get the feeling that {team} don't really want this",
"No passion from {team}, {name}",
"If a game of football is like making love to a beautiful woman, this {team} game is a £10 hand job from a swivel-eyed misfit",
"This {team} match is like a game of chess. But with more players and only one piece",
]
teamLeadByOne: list[str] = [
"{team} cheats, the ref's a cunt",
"That was never a goal for {team}",
"{team} don't deserve that",
"Bollocks",
"That should go to VAR",
"Bit fortunuate for {team}",
"Can't imagine {team} will keep this lead",
"Lucky goal for {team}",
"{team} got lucky there",
"{team} aren't good enough to stay ahead",
"Offside!",
]
teamExtendingLead: list[str] = [
"There's no way {team} deserve this lead",
"Have {team} paid the ref?",
"This is bullshit",
"The ref's a cunt, {name}'s a cunt",
"The ref's a cunt, {team} are cunts, {name}'s a cunt",
"Something has gone seriously wrong with this country",
"When I voted for Brexit, I didn't vote for this",
"At least Boris remains in charge, we've still got that",
"Richard Wanger would be turning in his grave",
"Liberal elite bullshit",
"That was so offside",
"VAR!",
"Is the linesman OK?",
"If only {name}'s wife was as dirty as this game",
]
teamLosingLead: list[str] = [
"Lazy old {team}, lazy old {name}",
"{team} are throwing it away",
"{team} are rubbish",
"{team} fucking it up again",
"We really are being treated to some world class flouncing from {team} today",
"Brace yourself, {name}. This is going to hurt",
"This is brown trouser time for {team}",
"I hope {name} brought a spare pair of underpants",
"I see {team} are playing their B Team. B for Bullshit",
]
teamDeficitOfOne: list[str] = [
"This is more like it from {team}",
"Oh dear...",
"{team} wankers",
"How are you feeling, {name}?",
"Bit disappointing, {name}?",
"Not looking good for {team}, {name}",
"You must be furious, {name}",
"{team} have just got no heart",
"This is what happens when you try to buy success",
"All that money spent, {name}, and for what?",
]
teamExtendingDeficit: list[str] = [
"Starting to feel a bit sorry for {team}",
"Never mind, {name}, there's always the next game",
"Poor {team}",
"Whoops...",
"Oh dear, everything OK, {name}?",
"Hey {name}, where'd you get your keeper?\nPOUNDSHOP !! POUNDSHOP !!",
"{team} can't raise themselves for this game, typical",
"A team like {team} have such a proud history, but what we see today is just embarrassing",
"{team} clearly not up for it today",
"{team} are letting you down, {name}",
"Watching {team} is like watching a bunch of cavemen: Neanderthal",
]
teamLosingDeficit: list[str] = [
"Too little too late for {team}",
"{team} won't come back from here",
"The ref's a cunt",
"This is awful",
"What a mess",
"Well this is an unmitigated shit show",
]
teamWon: list[str] = [
"That was a shit game",
"There's no way {team} deserved that",
"Fuck you, {name} !!",
"This will go down in history...\nAs the most tedious game I have ever had the misfortune to witness",
]
teamLost: list[str] = [
"Justice done, {team} lost",
"Job done for {team}?",
"Job done, {name}?",
"{name} !!?",
"Probably the best {team} could hope for",
"Everything OK, {name}?",
"{team} continue to disappoint",
"Well if the football thing doesn't work out for {team}, they can always consider a career on the stage",
"{team} set the bar low",
"{team} fail to meet their already low expectations",
]
teamDrew: list [str] = [
"Another uninspiring result for {team}",
"Thanks for nothing, {team}",
"Well that's 90 minutes we won't get back, thanks {team}",
"Another draw for {team}",
"Boring old {team}",
"You should be happy with that result, {name}",
"If I could pick one highlight from this {team} game it would be when it finally ended.",
"I think {name} will be happy with {team}'s performance today.",
]
| [] |
codr7/alisp | bench/fibrec.py | 05ac47ab2c28683373af4ec80e5a94937390fa6c | from bench import bench
print(bench(100, '''
def fib(n):
return n if n < 2 else fib(n-1) + fib(n-2)
''', '''
fib(20)
'''))
| [((31, 128), 'bench.bench', 'bench', (['(100)', '"""\ndef fib(n):\n return n if n < 2 else fib(n-1) + fib(n-2)\n"""', '"""\n fib(20)\n"""'], {}), '(100, """\ndef fib(n):\n return n if n < 2 else fib(n-1) + fib(n-2)\n""",\n \'\\n fib(20)\\n\')\n', (36, 128), False, 'from bench import bench\n')] |
NLPIR-team/nlpir-python | nlpir/native/classifier.py | 029f81e69ee561725fa017dce09cfd55acb34d20 | # coding=utf-8
from nlpir.native.nlpir_base import NLPIRBase
from ctypes import c_bool, c_char_p, c_int, POINTER, Structure, c_float
class StDoc(Structure):
__fields__ = [
("sTitle", c_char_p),
("sContent", c_char_p),
("sAuthor", c_char_p),
("sBoard", c_char_p),
("sDatatype", c_char_p)
]
class Classifier(NLPIRBase):
@property
def dll_name(self):
return "LJClassifier"
@NLPIRBase.byte_str_transform
def init_lib(self, data_path: str, encode: int, license_code: str) -> int:
"""
Call **classifier_init**
:param data_path:
:param encode:
:param license_code:
:return: 1 success 0 fail
"""
return self.get_func("classifier_init", [c_char_p, c_char_p, c_int, c_char_p], c_bool)(
"rulelist.xml", data_path, encode, license_code)
@NLPIRBase.byte_str_transform
def exit_lib(self) -> bool:
"""
Call **classifier_exit**
:return: exit success or not
"""
return self.get_func("classifier_exit", None, None)()
@NLPIRBase.byte_str_transform
def get_last_error_msg(self) -> str:
return self.get_func("classifier_GetLastErrorMsg", None, c_char_p)()
@NLPIRBase.byte_str_transform
def exec_1(self, data: StDoc, out_type: int = 0):
"""
Call **classifier_exec1**
对输入的文章结构进行分类
:param data: 文章结构
:param out_type: 输出是否包括置信度, 0 没有置信度 1 有置信度
:return: 主题类别串 各类之间用\t隔开，类名按照置信度从高到低排序
举例：“要闻 敏感 诉讼”, “要闻 1.00 敏感 0.95 诉讼 0.82”
"""
return self.get_func("classifier_exec1", [POINTER(StDoc), c_int], c_char_p)(data, out_type)
@NLPIRBase.byte_str_transform
def exec(self, title: str, content: str, out_type: int):
"""
Call **classifier_exec**
对输入的文章进行分类
:param title: 文章标题
:param content: 文章内容
:param out_type: 输出知否包括置信度,同 :func:`exec_1`
:return: 同 :func:`exec_1`
"""
return self.get_func("classifier_exec", [c_char_p, c_char_p, c_int], c_char_p)(title, content, out_type)
@NLPIRBase.byte_str_transform
def exec_file(self, filename: str, out_type: int) -> str:
"""
Call **classifier_execFile**
:param filename: 文件名
:param out_type: 输出是否包括置信度, 0 没有置信度 1 有置信度
:return: 主题类别串 各类之间用\t隔开，类名按照置信度从高到低排序
举例：“要闻 敏感 诉讼”, “要闻 1.00 敏感 0.95 诉讼 0.82”
"""
return self.get_func("classifier_execFile", [c_char_p, c_int], c_char_p)(filename, out_type)
@NLPIRBase.byte_str_transform
def detail(self, class_name: str):
"""
Call **classifier_detail**
对于当前文档，输入类名，取得结果明细
:param class_name: 结果类名
:return: 结果明细 例如:
::
RULE3:
SUBRULE1: 内幕 1
SUBRULE2: 股市 1 基金 3 股票 8
SUBRULE3: 书摘 2
"""
return self.get_func("classifier_detail", [c_char_p], c_char_p)(class_name)
@NLPIRBase.byte_str_transform
def set_sim_thresh(self, sim: float):
"""
Call **classifier_setsimthresh**
设置阈值
:param sim: 阈值
:return:
"""
return self.get_func("classifier_setsimthresh", [c_float])(sim)
| [((1655, 1669), 'ctypes.POINTER', 'POINTER', (['StDoc'], {}), '(StDoc)\n', (1662, 1669), False, 'from ctypes import c_bool, c_char_p, c_int, POINTER, Structure, c_float\n')] |
nickgaya/bravado-core | tests/param/get_param_type_spec_test.py | 16e752963bfceb4adfa43724085bc4127eefcd59 | # -*- coding: utf-8 -*-
import pytest
from mock import Mock
from bravado_core.exception import SwaggerMappingError
from bravado_core.operation import Operation
from bravado_core.param import get_param_type_spec
from bravado_core.param import Param
from bravado_core.spec import Spec
@pytest.fixture
def body_param_spec():
return {
'name': 'body',
'in': 'body',
'description': 'pet id',
'required': True,
'schema': {
'type': 'string',
},
}
def test_location_is_body(empty_swagger_spec, body_param_spec):
param = Param(empty_swagger_spec, Mock(spec=Operation), body_param_spec)
assert body_param_spec['schema'] == get_param_type_spec(param)
def test_location_is_not_body(empty_swagger_spec):
for location in ('path', 'query', 'header', 'formData',):
param_spec = {
'name': 'petId',
'in': location,
'description': 'ID of pet that needs to be updated',
'required': True,
'type': 'string',
}
param = Param(empty_swagger_spec, Mock(spec=Operation), param_spec)
assert param_spec == get_param_type_spec(param)
def test_location_invalid(empty_swagger_spec, body_param_spec):
body_param_spec['in'] = 'foo'
param = Param(empty_swagger_spec, Mock(spec=Operation), body_param_spec)
with pytest.raises(SwaggerMappingError) as excinfo:
get_param_type_spec(param)
assert 'location foo' in str(excinfo.value)
def test_ref(minimal_swagger_dict, body_param_spec):
minimal_swagger_dict['parameters'] = {
'PetIdParam': body_param_spec,
}
param_ref_spec = {'$ref': '#/parameters/PetIdParam'}
swagger_spec = Spec(minimal_swagger_dict)
param = Param(swagger_spec, Mock(spec=Operation), param_ref_spec)
assert {'type': 'string'} == get_param_type_spec(param)
| [((1718, 1744), 'bravado_core.spec.Spec', 'Spec', (['minimal_swagger_dict'], {}), '(minimal_swagger_dict)\n', (1722, 1744), False, 'from bravado_core.spec import Spec\n'), ((614, 634), 'mock.Mock', 'Mock', ([], {'spec': 'Operation'}), '(spec=Operation)\n', (618, 634), False, 'from mock import Mock\n'), ((693, 719), 'bravado_core.param.get_param_type_spec', 'get_param_type_spec', (['param'], {}), '(param)\n', (712, 719), False, 'from bravado_core.param import get_param_type_spec\n'), ((1320, 1340), 'mock.Mock', 'Mock', ([], {'spec': 'Operation'}), '(spec=Operation)\n', (1324, 1340), False, 'from mock import Mock\n'), ((1369, 1403), 'pytest.raises', 'pytest.raises', (['SwaggerMappingError'], {}), '(SwaggerMappingError)\n', (1382, 1403), False, 'import pytest\n'), ((1424, 1450), 'bravado_core.param.get_param_type_spec', 'get_param_type_spec', (['param'], {}), '(param)\n', (1443, 1450), False, 'from bravado_core.param import get_param_type_spec\n'), ((1777, 1797), 'mock.Mock', 'Mock', ([], {'spec': 'Operation'}), '(spec=Operation)\n', (1781, 1797), False, 'from mock import Mock\n'), ((1848, 1874), 'bravado_core.param.get_param_type_spec', 'get_param_type_spec', (['param'], {}), '(param)\n', (1867, 1874), False, 'from bravado_core.param import get_param_type_spec\n'), ((1092, 1112), 'mock.Mock', 'Mock', ([], {'spec': 'Operation'}), '(spec=Operation)\n', (1096, 1112), False, 'from mock import Mock\n'), ((1155, 1181), 'bravado_core.param.get_param_type_spec', 'get_param_type_spec', (['param'], {}), '(param)\n', (1174, 1181), False, 'from bravado_core.param import get_param_type_spec\n')] |
truls/faas-profiler | functions/markdown-to-html/markdown2html.py | d54ca0d9926f38c693f616ba4d08414aea823f51 | # Copyright (c) 2019 Princeton University
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from markdown import markdown
import base64
import json
import base64
def main(params):
try:
md = json.loads(base64.decodebytes(params["__ow_body"].encode("utf-8")))["markdown"].encode("utf-8")
md_text = base64.decodebytes(md).decode("utf-8")
except KeyError:
return {'Error' : 'Possibly lacking markdown parameter in request.'}
test_id = params["__ow_query"].split("&")[0]
html = markdown(md_text)
return {"result": "ok", "html_response": html, "testid": test_id}
| [((593, 610), 'markdown.markdown', 'markdown', (['md_text'], {}), '(md_text)\n', (601, 610), False, 'from markdown import markdown\n'), ((394, 416), 'base64.decodebytes', 'base64.decodebytes', (['md'], {}), '(md)\n', (412, 416), False, 'import base64\n')] |