Saravanan666/pypi-org huggingface dataset:
Package: appeau-client
# DescriptionUn client Python pour l’API appeau, généré à partir du fichier de description suivant la spec OpenAPI 3.0.
Il nécessite une version de python >= 3.8, pour le typage des dictionnaires.# Build & InstallPour générer le module, suivre ce lien:https://docs.python.org/fr/3.8/distutils/introduction.html#distutils-simple-exampleEn synthèse:`shell python setup.py sdist # à la racine, voirhttps://docs.python.org/fr/3/distutils/sourcedist.htmlpour les formats d'archive possible `puis, par défaut dans /dist, et après extraction de l’archive, à la racine:`shell python setup.py install `# Exemple`python import sample.login_check_post import sample.api_parcelles_get_collection response = sample.login_check_post.login_check_post(host ='http://appeau.api.vignevin-epicure.com',body_parameters = {"username":'vitisexplorer',"password":'Ajfkmdkp34'})token = response.json()print(token['token'])parcelles =sample.api_parcelles_get_collection.api_parcelles_get_collection('http://appeau.api.vignevin-epicure.com',headers = {"Authorization": "Bearer " +token['token']})print(parcelles.json())`
Package: appeears
appeears: Simple CLI for NASA AppEEARS APIThe Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) offers a simple and efficient way to access and transform geospatial data from a variety of federal data archives. AppEEARS enables users to subset geospatial datasets using spatial, temporal, and band/layer parameters. Two types of sample requests are available: point samples for geographic coordinates and area samples for spatial areas via vector polygons. Sample requests submitted to AppEEARS provide users not only with data values but also associated quality data values.NASA appears APIprovides endpoints to automate and use this tool in a programmatic environment. This command line tool attempts at creating an implementation of the overall API design.Disclaimer: Whole or part of the description is provided by the original owners of the product. This is an unofficial tool. Is not licensed or endorsed by NASA or any other orgs providing the NASA Appeears service. It is created and maintained by Samapriya Roy.Readme Docsavailable online
Package: appel
appelAppel contains tools to process Google Spreadsheets for attendance records and store results on Canvas.Free software: MIT licenseDocumentation:https://appel.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2019-01-11)First release on PyPI.
Package: appel-crises
# appel-crises-web## for developersOn first time,Installpython3.7if neededInstallpre-commitif needed (pip install –user pre-commit)Install a python virtualenv manager if needed (pip install –user vex,pip install –user pew, …)Create a virtualenv (vex –make appel-crises,pew new appel-crises)Install project dependencies:make bootsrap(orpip install -e .[dev]if make isn’t available)cp local_settings.ini.template local_settings.iniand editlocal_settings.iniif you needif you chose postgresql DB, create user and database if neededrunmake buildto build static filesrun./manage.py migrateto create DB tablesrun./manage.py createsuperuserto create a local user## Dependencies managementDependencies are stored insetup.cfg:Runtime dependencies are listed underinstall_requiresin the[options]section;Additional development dependencies are listed underdev=in the[options.extras_require],
and installed alongside required dependencies by specifying the[dev]extra marker -
as seen inpip install -e .[dev].## BuildingThe project is not composed only of pure Python code (it contains templates, images, …).
Some of those files must go through some processing before running in production:
- Static files should be consolidated into a single tree, with hashed names and a manifest;
- Message catalogs might need to be compiled to their final.moform;
- Some static data might be converted to some other formats for faster / easier loading.Those steps are controlled through the project wideMakefile, and should be called
through themake build(or simplymake) command.That step is also executed when building a release.## ReleasingA release consists of a built project archive, under thewheelformat; that package MUST include the result of a full compilation.
Package: appel-geocode
Project TitleAPPEL: A faster spatial join/reverse geocoding threaded algorithmGetting StartedSpatial joins are like common relational database joins, just for geographic data.
In general, we have a set of coordinates and we want to know which point is in which polygon, this operation is described as reverse geocoding.
The algorithm relies on standard Point-In-Polygon operations but tends to minimize then.APPEL proposes a new way to spatial joins that promises to be faster than than trivial brute force and R-Tree implementation of PostGIS and GeoPandas.
For a million points it takes about 14 seconds to finish locating, while PostGIS takes about 7 minutes and GeoPandas takes 1 minutes and 7 seconds.
All on the same machine.To do so, the polygons to be searched are organized through a tree. The tree levels are predefined based on states, mesoregions, microregions and municipalities.
In addition, it is considered that the geographic points provided by users are more likely to be located in more populated regions.
Therefore, these areas are sorted to be the first to be found at each level of the tree.Currently, the systems works only for Brazil territory and locates the cities of each point.
But it's principle is extensible for any geographical region.
You'll need just a shapefile (or equivalent) with each region and subregions population to build the data structure.These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.PrerequisitesPython 3.6
GeoPandas
Numpy
ShapelyInstallingA step by step series of examples that tell you how to get a development env running
Just use pip.pip install appelBy default, it comes with a tree for Brazil's regions.To use, you must input the longitude and latitudes in the query function:from numpy import array

from appel.searchtree import SearchTree

search = SearchTree()

longitudes = array([2.748047, -20.890625], dtype='float32')
latitudes = array([-63.03125, -49.53125], dtype='float32')
results = search.query(longitudes, latitudes)
print(results)It will return a dataframe with latitudes longitudes and the city id.Running the testsJust run methods on the classes of test package.Built WithGeoPandas- Essential for reading shapely files and build the search data structure.Shapely- vectorized contains function is the core of the search algorithm.ContributingCurrently I don't have a fixed system. Use issues for critics, help or any question in general.AuthorsGabriel Coimbra-gcoimbraLicenseThis project is licensed under the GNU Affero General Public License - see theLICENSE.mdfile for detailsAcknowledgmentsThanksPurpleBoothfor thisREADME.mdtemplate.
Package: appendfilename
Intelligent appending text to file names, considering file extensions and file tagsUsage::: ./appendfilename.py [<options>] <list of files>This tool inserts text between the old file name and optional tags or file extension.Text within file names is placed between the actual file name and
the file extension or (if found) between the actual file namd and
a set of tags separated with “ – “.:: Update for the Boss  <NEW TEXT HERE>.pptx
:: 2013-05-16T15.31.42 Error message <NEW TEXT HERE> – screenshot projectB.pngExample usages:
::  ./appendfilename.py –text=”of projectA” “the presentation.pptx”
::      … results in “the presentation of projectA.pptx”
::  ./appendfilename.py “2013-05-09T16.17_img_00042 – fun.jpeg”
::      … with interactive input of “Peter” results in:
::          “2013-05-09T16.17_img_00042 Peter – fun.jpeg”
Package: append-hygiene-sdk
Append Hygiene SDKAppend Hygiene SDK provides a library of classes for working with On-Demand API in your Python code.RequirementsPython 3.6+Must be logged into the private VPN.Installationpipinstallappend-hygiene-sdkEnvironment VariablesONDEMAND_URL: On-Demand Base URL.ExamplesHygieneimporttimefromdotenvimportload_dotenvfromappend_hygiene_sdkimportHygieneload_dotenv()# Step 1: Create the Hygiene objectmy_hygiene=Hygiene()# Step 2: Add your custom payload to the Hygiene object and execute the hygiene pushmy_hygiene.push_hygiene(payload={"filepath":"s3://bucket-name/folder1/folder2/file1.csv","result_path":"s3://bucket-name/folder1/folder2/","verification":False,"has_header":True,"email_column_number":1,"omit_suppressions":False,"ignore_duplicates":False,"suppression_types":["trap","high_complainer","low_complainer"],"on_success_uri":"mailto:[EMAIL]?subject=[SUCCESS SUBJECT LINE]","on_error_uri":"mailto:[EMAIL]?subject=[FAILED SUBJECT LINE]","callback_context":"{\"clientID\":\"123\"}"})# Step 3: Wait for the hygiene to completewhilemy_hygiene.hygiene_status(my_hygiene.hygiene_id):time.sleep(10)print("Waiting for Hygiene to complete...")Appendimporttimefromdotenvimportload_dotenvfromappend_hygiene_sdkimportAppendload_dotenv()# Step 1: Create the Append objectmy_append=Append()# Step 2: Add your custom payload to the Append object and execute the Append pushmy_append.push_append(payload={"filepath":"s3://bucket-name/folder1/folder2/file1.csv","has_header":True,"identifier_columns":{"first_name":1,"last_name":2,"address":4,"zip5":8},"individual_match":True,"household_match":False,"append_fields":["email"],"hygiene_and_verification":False,"verification":False,"results_per_row":1,"prioritize_individual_email":True,"additional_append_fields":{},"hide_results":False,"unique_emails":True,"suppression_types":["bad_domain","bad_extension","bad_word","catch_all","unsub","trap","high_complainer","low_complainer","bad_format","invalid","unknown","unpreferred_domain"],"apply_address_correction":False,"ac_with_history":False,"append_ac_columns":False,"raw_email":False,"result_path":"s3://bucket-name/folder1/folder2/","on_success_uri":"mailto:[EMAIL]?subject=[SUCCESS SUBJECT LINE]","on_error_uri":"mailto:[EMAIL]?subject=[FAILED SUBJECT LINE]","callback_context":"{\"clientID\":\"123\"}"})# Step 3: Wait for the Append to completewhilemy_append.append_status(my_append.append_id):time.sleep(10)print("Waiting for Hygiene to complete...")CHANGELOG[0.2.1] - 2020-06-01Updated package to include Python 3.6+[0.2.0] - 2020-06-01AddedAppendobject to the SDK.Addedpush_appendmethod to the Append class.Addedappend_statusmethod to the Append class.UpdatedREADME.mdto include the Append SDK.[0.1.1] - 2020-06-01Updated pypi description[0.1.0] - 2020-05-31AddedHygieneobject to the SDK.Addedpush_hygienemethod to Hygiene class.Addedhygiene_statusmethod to Hygiene class.UpdatedREADME.md
Package: appendonly
appendonlyREADMEThis package provides a set of data structures for use in ZODB applications
where standard BTrees are poor fits for an application’s requirements.In particular, these data structures are designed to minimize conflict
errors when doing frequent “append” operations to queues and stacks.appendonly.AppendStackThis class provides a LIFO stack of separately-persisted objects:The stack manages a set of “layer” objects, with a configurable limit
on the number of layers.  Each layer has a configurable maximum length,
and a sequential generation number.The stack appends items to most recent layer until the layer is filled;
it then adds a new layer.If the number of layers then exceeds the configured maximum, the stack
pruneds the oldest layer(s) to conform to that limit.When pruning, the stack calls an application-supplied callback for
archiving / cleanup of the pruned layer.Iteration over the stack yields (generation, index, object) tuples.
in reverse order to that in which the objects were appended.The stack is implemented as a single persistent record, with custom
ZODB conflict resolution code.appendonly.ArchiveThis class provides a linked list of separately-persisted copies of layer
data pruned from anAppendStack.  The intended use would be something
like:from appendonly import AppendStack
from appendonly import Archive

class RecentItems(object):
    def __init__(self):
        self._recent = AppendStack()
        self._archive = Archive()

    def pushItem(object):
        self._stack.push(object, self._archive.addLayer)

    def __iter__(self):
        for generation, index, item in self._stack:
            yield item
        for generation, index, item in self._archive:
            yield itemsappendonly.AccumulatorThis class provides a list-like data structure, where the only mutations
allowed are to append to or clear the list.  Intended uses are for a
set of pending operations / changes / notifications, which get processed
as a unit (at which point the accumulator is cleared).appendonlyChangelog1.2 (2014-12-28)Add support for Python 3.4.MakeZODBdependency unconditional, now that it fully supports Py3k.Add support for testing on Travis.1.1 (2013-11-28)AddAccumulator.extendmethod to enhance list-ness.Add support for PyPy.Add support for Python 3.2 / 3.3.1.0.1 (2013-02-25)Fix brown-bag in 1.0 release (Accumulator.appendchanges were not
persisted).1.0 (2013-02-25)Add a conflict-free ‘Accumulator’ class: manages a queue of items which
can be iterated, appended to, or conumed entirely (no partial / pop).Automate tests for supported Python versions via ‘tox’.Drop support for Python 2.4 / 2.5.0.10 (2012-02-21)Add an ‘Archive’ class, intended to support long-term storage of the
layer data pruned from an ‘AppendStack’.0.9 (2010-08-09)Initial public release.
Package: appendzip
append-zipAppends a file to a zip file, overwriting the existing file there if necessaryPerformanceNot efficient; extracts all the files in the zip, copies over the new file, and compresses a brand new zip replacing the original one. You will need enough disk space to duplicate the zip file.Caveatsfor some reason, windows has a different file length after unzipping (by 10-20 bytes). So beware how this works on windowsGetting startedinstall (on Mac)$ python3 -m pip install appendzipfromappendzip.appendzipimportappendzip# before appendzip calendar.txt in the zip archive test.zip contains 2021-01-02# before appendzip calendar.txt outside the zip contains 2022-02-03appendzip(pathlib.Path('test.zip'),pathlib.Path('calendar.txt'),'calendar.txt')# after appendzip calendar.txt inside the zip contains 2022-02-03# after, there is still only one file in the zip archive test.zip
Package: appengine-clean
appengine_cleanClean up old versions of AppEngine instances to avoid the dreaded "Your app may not have more than 210 versions. Please delete one of the existing versions before trying to create a new version" errorUsage:First, let's do a dry-run. Run the following to keep 15 versions of each module around:appengine-clean my-project-id 15 --dry-runIf you're happy with the result of the dry-run, let's delete:appengine-clean my-project-id 15 --force
Package: appengine-python-standard
Google App Engine bundled services SDK for Python 3This is a release of the App Engine services SDK for Python 3.  It provides access to various services and API endpoints that were previously only available on the Python 2.7 runtime.See thedocumentationto learn more about using this SDK, and learn more about it inthis product announcement(Fall 2021).Additional examples (Datastore [NDB], Task Queues [push tasks], Memcache) can be found in theApp Engine migration repo. (Specifically look for samples whose folders have abbut where the Python 2 equivalent folder doesnothave ana, meaning this SDK is required, e.g., Modules 1 [mod1andmod1b], 7, 12, etc.)Using the SDKIn yourrequirements.txtfile, add the following:appengine-python-standard>=1.0.0To use a pre-release version (Eg.1.0.1-rc1), modify the above line toappengine-python-standard>=[insert_version](Eg.appengine-python-standard>=1.0.1-rc1).In your app'sapp.yaml, add the following:app_engine_apis: trueIn yourmain.py, importgoogle.appengine.api.wrap_wsgi_app()and call it on your
WSGI app object.Example for a standard WSGI app:import google.appengine.api

def app(environ, start_response):
    start_response('200 OK', [('Content-Type', 'text/plain')])
    yield b'Hello world!\n'

app = google.appengine.api.wrap_wsgi_app(app)Example for a Flask app:import google.appengine.api
from flask import Flask, request

app = Flask(__name__)
app.wsgi_app = google.appengine.api.wrap_wsgi_app(app.wsgi_app)Then deploy your app as usual, withgcloud app deploy. The following modules are available:google.appengine.api.app_identitygoogle.appengine.api.background_threadgoogle.appengine.api.blobstoregoogle.appengine.api.capabilitiesgoogle.appengine.api.croninfogoogle.appengine.api.dispatchinfogoogle.appengine.api.imagesgoogle.appengine.api.mailgoogle.appengine.api.memcachegoogle.appengine.api.modulesgoogle.appengine.api.oauthgoogle.appengine.api.runtimegoogle.appengine.api.searchgoogle.appengine.api.taskqueuegoogle.appengine.api.urlfetchgoogle.appengine.api.usersgoogle.appengine.ext.blobstoregoogle.appengine.ext.dbgoogle.appengine.ext.gqlgoogle.appengine.ext.key_rangegoogle.appengine.ext.ndbgoogle.appengine.ext.testbedUsing the development version of the SDKTo install the code from themainbranch on GitHub rather than the latest
version published to PyPI, put this in yourrequirements.txtfile instead ofappengine-python-standard:https://github.com/GoogleCloudPlatform/appengine-python-standard/archive/main.tar.gz
Package: appengine-python-standard-tbafork
Google App Engine bundled services SDK for Python 3This is a release of the App Engine services SDK for Python 3.  It provides access to various services and API endpoints that were previously only available on the Python 2.7 runtime.See thedocumentationto learn more about using this SDK, and learn more about it inthis product announcement(Fall 2021).Additional examples (Datastore [NDB], Task Queues [push tasks], Memcache) can be found in theApp Engine migration repo. (Specifically look for samples whose folders have abbut where the Python 2 equivalent folder doesnothave ana, meaning this SDK is required, e.g., Modules 1 [mod1andmod1b], 7, 12, etc.)Using the SDKIn yourrequirements.txtfile, add the following:appengine-python-standard>=1.0.0To use a pre-release version (Eg.1.0.1-rc1), modify the above line toappengine-python-standard>=[insert_version](Eg.appengine-python-standard>=1.0.1-rc1).In your app'sapp.yaml, add the following:app_engine_apis: trueIn yourmain.py, importgoogle.appengine.api.wrap_wsgi_app()and call it on your
WSGI app object.Example for a standard WSGI app:import google.appengine.api

def app(environ, start_response):
    start_response('200 OK', [('Content-Type', 'text/plain')])
    yield b'Hello world!\n'

app = google.appengine.api.wrap_wsgi_app(app)Example for a Flask app:import google.appengine.api
from flask import Flask, request

app = Flask(__name__)
app.wsgi_app = google.appengine.api.wrap_wsgi_app(app.wsgi_app)Then deploy your app as usual, withgcloud app deploy. The following modules are available:google.appengine.api.app_identitygoogle.appengine.api.background_threadgoogle.appengine.api.blobstoregoogle.appengine.api.capabilitiesgoogle.appengine.api.croninfogoogle.appengine.api.dispatchinfogoogle.appengine.api.imagesgoogle.appengine.api.mailgoogle.appengine.api.memcachegoogle.appengine.api.modulesgoogle.appengine.api.oauthgoogle.appengine.api.runtimegoogle.appengine.api.searchgoogle.appengine.api.taskqueuegoogle.appengine.api.urlfetchgoogle.appengine.api.usersgoogle.appengine.ext.blobstoregoogle.appengine.ext.dbgoogle.appengine.ext.gqlgoogle.appengine.ext.key_rangegoogle.appengine.ext.ndbgoogle.appengine.ext.testbedUsing the development version of the SDKTo install the code from themainbranch on GitHub rather than the latest
version published to PyPI, put this in yourrequirements.txtfile instead ofappengine-python-standard:https://github.com/GoogleCloudPlatform/appengine-python-standard/archive/main.tar.gz
Package: appengine-toolkit
Appengine Toolkit pimps Django with some utilities which help deploying
projects on Google App Engine with Google Cloud SQL as data backend.Featurescollects project dependencies symlinking needed modules and packages and configuring App Engine environmentconfigures DATABASE setting parsing connection strings similar to those on HerokuDocumentationThe full documentation is athttp://django-appengine-toolkit.rtfd.org.QuickstartInstall appengine-toolkit:pip install django-appengine-toolkitAdd it to the installed apps:INSTALLED_APPS = (
    # ...
    'appengine_toolkit',
)To automatically configure database settings reading connection string
from the DATABASE_URL enviroment var:import appengine_toolkit
DATABASES = {
    'default': appengine_toolkit.config(),
}You can set DATABASE_URL directly in yourapp.yamlfile:env_variables:
  DJANGO_SETTINGS_MODULE: 'myapp.settings'
  DATABASE_URL: 'mysql://root@project_id:instance_id/database_name'To collect project dependencies, first configure Appengine Toolkit in your settings
file, specifying the full path to your app.yaml file:APPENGINE_TOOLKIT = {
    'APP_YAML': os.path.join(BASE_DIR, '../../', 'app.yaml'),
}…then run the commandcollectdepsspecifying the requirement file containing
the list of packages needed by your project to run:python manage.py collectdeps -r my_requirements.txta folder namedlibswill be created on your application root (i.e. the same folder
where the YAML file resides) containing symlinks needed by App Engine to include
dependencies in the production runtime enviroment.A fileappengine_config.pywill be created in the same folder and will contain
code needed to configure the environment. If you need to customize the moduleappengine_configtell the command to not overwrite it - the command will then
output the code you need to paste inside the module to complete the configuration
processHistory0.1.0 (2013-11-30)First release on PyPI.
Package: appenlight
AppEnlightPerformance, exception, and uptime monitoring for the WebAutomatic InstallationUse the ansible scripts in theautomationrepository to build complete instance of application
You can also usepackerfiles inautomation/packerto create whole VM's for KVM and VMWare.Manual InstallationTo run the app you need to have meet prerequsites:python 3.5+ (currently 3.6 tested)running elasticsearch (6.6.2 tested)running postgresql (9.5+ required, tested 9.6 and 10.6)running redisInstall the app by performingpip install -r requirements.txt

python setup.py developInstall the appenlight uptime plugin (ae_uptime_cepackage fromappenlight-uptime-cerepository).For production usage you can do:pip install appenlight
pip install ae_uptime_ceAfter installing the application you need to perform following steps:(optional) generate production.ini (or use a copy of development.ini)appenlight-make-config production.iniSetup database structure:appenlight-migratedb -c FILENAME.iniTo configure elasticsearch:appenlight-reindex-elasticsearch -t all -c FILENAME.iniCreate base database objects(run this command with help flag to see how to create administrator user)appenlight-initializedb -c FILENAME.iniGenerate static assetsappenlight-static -c FILENAME.iniRunning applicationTo run the main app:pserve development.iniTo run celery workers:celery worker -A appenlight.celery -Q "reports,logs,metrics,default" --ini FILENAME.iniTo run celery beat:celery beat -A appenlight.celery --ini FILENAME.iniTo run appenlight's uptime plugin:appenlight-uptime-monitor -c FILENAME.iniReal-time NotificationsYou should also run the `channelstream websocket server for real-time notificationschannelstream -i filename.iniAdditional documentationVisithttps://getappenlight.comfor additional server and client documentation.TestingTo run test suite:py.test appenlight/tests/tests.py --cov appenlight (this looks for testing.ini in repo root)DevelopmentTo develop appenlight frontend:cd frontend
npm install
grunt watch