Saravanan666/pypi-org huggingface dataset:
Package: ler-arquivos
FormaÃ§Ã£o Python DeveloperDescomplicando a CriaÃ§Ã£o de Pacotes de Processamento de Imagens em PythonDesafio  proposto pelo mÃ³dulo "Tratamento de Dados com Python" da Digital Innovation OneAutor: [Luis Pontes]Perfil DIO: [https://web.dio.me/users/MAILTOLUISCARLOS]GitHub: [https://github.com/CientistaPY]package_nameDescription.
The package package_name is used to:
-
read a spreadsheet via url regardless of whether it has the extension csv, xls, or xlsx.InstallationUse the package managerpipto install ler_arquivospipinstall-rrequirements.txt
pipinstalller_arquivosUsagefromler_arquivosimportler_arquivosAuthorLuis Pontes
GitHub: [https://github.com/CientistaPY]##Licence
Copyright (c) 2018 The Python Packaging AuthorityPermission 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.
Package: lerMicrodados
lerMicrodadosPacote desenvolvido para extraÃ§Ã£o e leitura de microdados do IBGE utilizando Python.FunÃ§Ãµes:ler_POF(path, header=True):Realiza a leitura dos microdados da POF 2017/2018 diretamente do arquivo .zip baixado do site do IBGE
e exporta os dados como um arquivo .csv.path: caminho para o arquivo .zipheader: boolean, Default True - acrescenta o cÃ³digo da variÃ¡vel como nome de cada coluna.format: formato do arquivo gerado..csva.xlsxdisponÃ­veis.Atualizada em 23/10/2020.ler_PNAD(path, ano, header=True):Realiza a leitura dos microdados da PNAD 2013, 2014 ou 2015 diretamente do arquivo .zip baixado do site do IBGE
e exporta os dados como um arquivo .csv.path: caminho para o arquivo .zipano: ano da PNAD.header:  boolean, Default True - acrescenta o cÃ³digo da variÃ¡vel como nome de cada coluna.ler_PNS(path, header=True):Realiza a leitura dos microdados da PNS 2013 diretamente do arquivo .zip baixado do site do IBGE e exporta os dados como um arquivo .csv.FunÃ§Ã£o  sugerida porBruna Schultz.path: caminho para o arquivo .zipheader: boolean, Default True - acrescenta o cÃ³digo da variÃ¡vel como nome de cada coluna.ler_PNADcontinua(anos: list):Faz a leitura de arquivos da PNAD ContÃ­nua trimestral, diretamente do site do IBGE. Retorna um dataframe com os dados agrupados para todos os anos informados.anos: Lista com os anos desejados da pesquisa.Exemplo:pnad = ler_PNADcontinua(anos=['2017','2018'])FuncionamentoLeia mais sobre o pacoteneste artigo.
Package: lernsax
This project is in no way associated with LernSax, WebWeaver, DigiOnline GmbH or Freistaat SachsenWhat is this?This is an API Wrapper for the LernSax API using aiohttp. Please note that we do not encourage taking any harmful actions against anyone using this wrapper.InstallationLernSax is available on pip!pip install lernsaxYou can also install directly from the repo viapython -m pip install git+https://github.com/okok7711/lernsax.gitDocumentation?Basic Documentation, generated with pdoc, for this module is availablehereFor Documentation of the actual LernSax jsonrpc API you should probably still stick tothis repoExample Usageimport lernsax
import asyncio

async def main():
    client = await lernsax.Client(
    email="",
    password=""
    )
    await client.login(client.email, client.password)
    print(await client.get_emails("494e424f58"))

asyncio.get_event_loop().run_until_complete(main())Accessing Files via WebDavThis module has built-in support for WebDav via aiodavjust use the lernsax.Client() class the same as if it was the aiodav.Client().visitthis repofor more info and examples for aiodavExample (as inthe examples dir):import lernsax
import asyncio

async def main():
    client = await lernsax.Client(
        email="",
        password=""
    )
    await client.login(client.email, client.password)
    dirs = await client.list()
    print(dirs)

asyncio.get_event_loop().run_until_complete(main())
Package: lesana
lesana is a python3 library to organize collections of various kinds.
It is designed to have a data storage / serialization format that is
friendly to git and other VCSs, but decent performances.To reach this aim it usesyamlas its serialization format, which is
easy to store in a VCS, share between people and syncronize between
different computers, but it also keeps an index of this data in a localxapiandatabase in order to allow for fast searches.lesana supports collections of any kind, as long as their entries can be
described with a mostly flat dictionary of fields of the types described
in the documentation filefield_types.Some example collection schemas are provided, but one big strenght of
lesana is the ability to customize your collection with custom fields
by simply writing a personalizedsettings.yaml.InstallationThe recommended way to install lesana is to use the packages available
for your distribution; see e.g. thelist of distributions that provide
lesana on repology.Alternatively, the source code for lesana can be downloaded from the git
repository athttps://git.sr.ht/~valhalla/lesana; and releases are made
onpypi.lesana expects to run on a POSIX-like system and requires the following
dependencies:python3xapianruamel.yamljinja2dateutilGitPythonoptional, to add git support.Under debian (and derivatives), the packages to install are:apt install python3-jinja2 python3-ruamel.yaml python3-xapian \
            python3-dateutil python3-gitlesana can be run in place from the git checkout / extracted tarball; to
usesetup.pyyou will also need setuptools (e.g. from thepython3-setuptoolspackage under debian and derivatives).ContributingLesana ishosted on sourcehut:bug trackermailing listsgit repositoryCILicenseCopyright (C) 2016-2021 Elena GrandiThis program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.This program 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 General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, see <http://www.gnu.org/licenses/>.
Package: les-assets-generator
Lyon e-Sport assets generatorThis website help you to generate assets from an image and GET parametersRequirementsPython (check version in pyproject.toml)Installpip install les-assets-generatorDevInstallPoetrywith version >= 1.2.0a1Install and setup dependenciespoetry install
poetry shell
pre-commit installRun pre-commitpre-commit run --all-filesConfigurationProduction onlySet the environnement for production (.env file or env vars)Dev: les_assets_generator.assets_generator.settings.devProd: les_assets_generator.assets_generator.settings.productionDJANGO_SETTINGS_MODULE="les_assets_generator.assets_generator.settings.production"

# Database URL following https://github.com/jazzband/dj-database-url#url-schema
DATABASE_URL="sqlite:////opt//assets-generator//db.sqlite3"

# Folder that store static files
DJANGO_STATIC_ROOT="/var/www/assets-generator/static"

# Folder that store media files
DJANGO_MEDIA_ROOT="/var/www/assets-generator/media"

# Django allowed host like .lyon-esport.fr
DJANGO_ALLOWED_HOST=""

# Django log level
DJANGO_LOG_LEVEL=""

# Set the secret key for session and other thinks
SECRET_KEY=""

# Used to generate example URL in django admin like https://assets.lyon-esport.fr
DEFAULT_DOMAIN=""

# Set allowed google email domain like lyon-esport.fr
GOOGLE_DOMAIN=""Run$ export DJANGO_SETTINGS_MODULE="les_assets_generator.assets_generator.settings.production"
$ python -m les_assets_generator.manage makemigrations
$ python -m les_assets_generator.manage migrate
$ python -m les_assets_generator.manage compilemessagesDev$ cd les_assets_generator
$ python -m les_assets_generator.manage runserverProduction$ python -m les_assets_generator.manage collectstatic --noinput
$ gunicorn les_assets_generator.assets_generator.wsgi:application --bind localhost:8000 --workers 3i18nhttps://docs.djangoproject.com/en/4.1/topics/i18n/translation/#message-filesLicenceThe code is under CeCILL license.You can find all details here:https://cecill.info/licences/Licence_CeCILL_V2.1-en.htmlCreditsCopyright © Lyon e-Sport, 2022Contributor(s):-Ortega Ludovic -ludovic.ortega@lyon-esport.fr
Package: lesaviezvous
LesaviezvousUn package Python pour obtenir des informations intéressantes à partir de l'API Lesaviezvous.Quoi de neuf dans la dernière version (0.2.6) :Ajout d'une fonctionnalité pour obtenir des faits aléatoires sans répétition (Avec cette version, vous pouvez maintenant obtenir des faits aléatoires sans répétition en appelant simplement la fonction obtenir_fait() à plusieurs reprises. Chaque appel renverra un fait différent jusqu'à ce que tous les faits aient été utilisés une fois. Vous pouvez également réinitialiser la liste des faits utilisés avec reinitialiser_faits_utilises() pour recommencer à obtenir de nouveaux faits sans répétition. Profitez de la découverte de faits passionnants et divertissants avec la version 0.2.6 !)InstallationInstallez le package à l'aide depip:pipinstalllesaviezvousMettre à jour le packagepipinstall--upgradelesaviezvousUtilisationImportez le package dans votre script Python et appelez la fonction obtenir_fait() pour obtenir des informations intéressantes :  :fromlesaviezvous.lesaviezvousimportobtenir_fait,reinitialiser_faits_utilises# Obtenir un fait aléatoireprint(obtenir_fait())# Obtenir un autre fait aléatoire (différent du premier)print(obtenir_fait())# Réinitialiser les faits utilisés pour pouvoir en obtenir de nouveaux sans répétitionreinitialiser_faits_utilises()# Obtenir un nouveau fait après la réinitialisationprint(obtenir_fait())# Obtenir un autre fait aléatoire (différent du précédent)print(obtenir_fait())ExigencesPython3
Package: leselys
I’m Leselys, your very elegant RSS reader. Try meright now(password: demo)!Nobullshit appsfor Android, iPhone, etc. Just a responsive design and for every device.Leselys is Heroku ready.InstallationUbuntuTwo requirements:MongodbandPython.In order to install leselys you’ll need some dependencies:sudo apt-get install build-essential python-dev python-setuptools
sudo apt-get install libxslt1-dev libxml2-dev
sudo easy_install pip
sudo easy_install virtualenvAnd install yourMongoDB.This is the right way, withvirtualenv:mkdir leselys && cd leselys
virtualenv .
source bin/activate
pip install leselys
leselys init leselys.ini
leselys serve leselys.ini
# In another terminal (in leselys directory)
source bin/activate
leselys worker leselys.iniOpen your browser athttp://localhost:5000.DockerSetting up withDockeris easy. There is no
published images on theDocker Hubyet but
here’s how to build a set of images easily and quickly usingDocker Compose:git clone https://github.com/prologic/leselys
cd leselys
git checkout dockerize
docker-compose up -dWith the configuration indocker-compose.ymlyou can then visit:http://localhost:5000/if you’re on a native Linux Docker host orhttp://$(docker-machineip dev):5000/ if you’re on OS X via boot2docker
or similar.HerokuAdvanced setup with MongoDB for storage and Redis for session on Heroku.
You will also need the Heroku Scheduler add-on to refresh your feeds.All Heroku dependencies likePymongo,gunicornandredisare inrequirements.txtfile, so everything will be installed automagically.git clone git@github.com:socketubs/leselys.git
cd leselys
heroku create
heroku addons:add mongohq:sandbox
heroku addons:add redistogo:nano
heroku addons:add scheduler:standard
heroku addons:open scheduler
# Add "sh heroku.sh && leselys refresh heroku.ini" job every 10 minutes
# And "sh heroku.sh && leselys retention heroku.ini" job every day
git push heroku masterImport your Google Reader OPML file right now!UpdateThis is how to update your Leselys (on Heroku):git pull
git push heroku master
heroku restartAnd for thepipway, you just have to go to yourvirtualenvand runpip install leselys-Uand restart Leselys processes.MiscStorage and session backends are Python modules, you can easily write your own. Take a look at theMongoDB storage backend.Leselys automagically fetch new stories with it’s refresher worker, and automagically (again), purge our stories database with it’s retention task.Python 3 support is available, there is justworkerwith celery which doesn’t work correctly. You can schedule the task with refresh and retention commands.
Python 3 is automatically used on Heroku.LicenseLicense isAGPL3. SeeLICENSE.
Package: lesion-metrics
lesion-metricsVarious metrics for evaluating lesion segmentations [1]Free software: Apache Software License 2.0Documentation:https://lesion-metrics.readthedocs.io.InstallThe easiest way to install the package is with:pip install lesion-metricsTo install the dependencies of the CLI, install with:pip install "lesion-metrics[cli]"You can also download the source and run:python setup.py installBasic UsageYou can generate a report of lesion metrics for a directory of predicted labels and truth labels
with the CLI:lesion-metrics -p predictions/ -t truth/ -o output.csvOr you can import the metrics and run them on label images:importnibabelasnibfromlesion_metrics.metricsimportdicepred=nib.load('pred_label.nii.gz').get_fdata()truth=nib.load('truth_label.nii.gz').get_fdata()dice_score=dice(pred,truth)References[1] Carass, Aaron, et al. “Longitudinal multiple sclerosis lesion segmentation: resource and challenge.” NeuroImage 148 (2017): 77-102.History0.1.12 (2022-01-21)Reduce pymedio dependency in volume calculation0.1.11 (2022-01-13)Use pymedio to open files instead of torchioRefactor for consistency with other projects and code quality0.1.10 (2021-12-09)Add lesion count to reportAdd helper metric calculator class0.1.9 (2021-12-07)Add per lesion metric report CLI for a prediction/truth segmentation pair0.1.8 (2021-10-28)Add more summary statistics to report0.1.7 (2021-10-27)Add segmentation volume to report and fix minor bugs0.1.6 (2021-08-16)Fix minor bug in IoU per lesion computation0.1.5 (2021-08-16)Make package compliant with mypyAdd lesion volume calculationAdd support for IoU threshold for LTPR and LFPR0.1.4 (2021-07-14)Fix type hints in volume correlationCorrect name of LFPR (lesion false positive rate) to LFDR (lesion false discovery rate)0.1.3 (2021-06-07)Fix correlation computation in CLI and other minor typos.0.1.2 (2021-05-26)Update code style to black and improve docs.0.1.1 (2021-05-14)Fix repo name.0.1.0 (2021-05-14)First release on PyPI.
Package: lesionprocessor
Lesion Processor crops, labels, and/or isolates lesions in a given image
or a set of images.InstallationpipinstalllesionprocessorUsageimportlesionprocessoraslpimg_path='data/raw/lesion1.jpg'crop_dir='data/cropped'label_dir='data/labeled'isolate_dir='data/isolated'unprocessed_dir='data/unprocessed'# optional, will default to 'unprocessed' directory# Croplp.crop(img_path,crop_dir,unprocessed_dir)# option 1lp.process(img_path,unprocessed_dir,crop_dir=crop_dir)# option 2# Labellp.label(img_path,label_dir,unprocessed_dir)# option 1lp.process(img_path,unprocessed_dir,label_dir=label_dir)# option 2# Isolatelp.isolate(img_path,isolate_dir,unprocessed_dir)# option 1lp.process(img_path,unprocessed_dir,isolate_dir=isolate_dir)# option 2# Crop + label + isolate (partiton into given out directories)lp.process(img_path,unprocessed_dir,crop_dir=crop_dir,label_dir=label_dir,isolate_dir=isolate_dir)How It WorksSample ResultsUsing the crop technique for standardization:Additional FeaturesConcurrently process multiple imagesAdjustable crop padding sizeAdjustable label colorAdjustable label line thicknessAdjustable number of contours to targetAdjustable size of kernels for morphological transformationsIn ProgressAdditional thresholding methodsAdjustable padding for isolation processLicenseApache License 2.0
Package: les-iterables
Installation$ pip install les_iterablesExamplesA collection of utility functions for processing iterable series which
aren't initertoolsormore-itertools. Some are little more than simple aliases with less confusing names.>>> from les_iterables import *
>>> is_odd = lambda x: x%2 != 0
>>>
>>> list(retain_if(is_odd, range(10))
[1, 3, 5, 7, 9]
>>>
>>> list(reject_if(is_odd, range(10))
[0, 2, 4, 6, 8]
>>>
>>> list(retain_truthy(reject_if(is_odd, range(10)))
[2, 4, 6, 8]CI/CD$ bumpversion patch
$ git push --follow-tagsMIT LicenseCopyright (c) 2020 Sixty North ASPermission 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.
Package: leslie
LeslieAn MIT NLP research library, built on TensorFlow, for developing state-of-the-art deep learning models on a wide variety of linguistic tasks.Models Supporttext classifier：average_pooling_text_classifierbert_text_classifiercnn_text_classifierintent slot multitask:sf_idPaper With CodeA Novel Bi-directional Interrelated Model for Joint Intent Detection and
Slot Filling
Package: les-louisdelatech
LouisDeLaTech is a discord bot manager for Lyon e-SportRequirementsPython (check version in setup.py)SetupDiscordCreate adiscord botand get the tokenGoogleCreate agoogle projectCreate agoogle service accountEnable Google workspace delegationGenerate keys and download the file (used by the bot-g)Add required scopesfor the service account (see config.example for the list of scopes)You must createuser custom attribute"custom":{"pseudo":"","discordId":"","teeShirt":"","birthdate":""}Hello assoDocumentationCustom fields{"name":"Pseudonyme","type":"TextInput",},{"name":"Date de naissance","type":"Date",},{"name":"Adresse postale","type":"TextInput",},{"name":"Numéro de téléphone","type":"TextInput",},{"name":"Nom d'utilisateur Discord","type":"TextInput",},{"name":"Taille du tee-shirt","type":"ChoiceList",},{"name":"Je m'engage à signer l'engagement de confidentialité : https://example.fr","type":"YesNo",}Installpipinstallles_louisdelatechConfigureGenerate a secret_key to encrypt database secrets>>>fromcryptography.fernetimportFernet>>>Fernet.generate_key()Fillconfig.tomlwithconfig.exampleRunpython3-mles_louisdelatech.main-cconfig.toml-ggoogle.jsonDevInstallPoetrypoetryinstall
poetryshell
pre-commitinstallRun pre-commitpre-commit run --all-filesLicenceThe code is under CeCILL license.You can find all details here:https://cecill.info/licences/Licence_CeCILL_V2.1-en.htmlCreditsCopyright © Lyon e-Sport, 2021Contributor(s):Ortega Ludovic -ludovic.ortega@lyon-esport.frEtienne "PoPs" G. -etienne.guilluy@lyon-esport.frPierre "DrumSlayer" Sarret -pierre.sarret@lyon-esport.fr
Package: lesma
lesma(c) 2017-2023 Óscar García AmorRedistribution, modifications and pull requests are welcomed under the terms
of GPLv3 license.lesma is a simple paste app, friendly with browser and command line, with
files as storage backend. You can see in action inhttps://lesma.eu.InstallTo install lesma follow this steps.From sourcegitclonehttps://github.com/ogarcia/lesma.git
virtualenv3./lesma-venvsource./lesma-venv/bin/activatecdlesma
pythonsetup.pyinstallFrom PyPIvirtualenv3./lesma-venvsource./lesma-venv/bin/activate
pipinstalllesmaRunIn your virtualenv runlesma server.source./lesma-venv/bin/activate
lesmaserverOr without activate virtualenv../lesma-venv/bin/lesma serverRunlesmawithout parameters to see help.
Package: lesp
LESP - Lightweight Efficient Spelling ProofreaderWelcome to LESP - Lightweight Efficient Spelling Proofreader!LESP is a lightweight, efficient spelling proofreader for Python, designed to be easy to use and resource-friendly.FeaturesLightweight and efficientEasy to useCross-platform (Linux, Windows, macOS)No external dependenciesInstallationpipinstalllespUsagefromlesp.autocorrectimportProofreaderproofreader=Proofreader()is_correct=proofreader.is_correct("apgle")# Falseifnotis_correct:similar_word=proofreader.get_similar("apgle")print("Did you mean:",similar_word)# Did you mean: appleFor detailed usage and configuration options, check thedocumentation.ContributingContributions are welcome! Check out theGitHub repositoryand feel free to open issues or pull requests.LicenseThis project is licensed under the BSD 3-Clause License. See theLICENSEfile for details.AcknowledgementsThanks toGoogle 10000 EnglishandEnglish Word Listfor contributing to the wordlist.ContactFor discussions or support, join theDiscord Serveror DM @lyubomirt.