Saravanan666/pypi-org huggingface dataset:
Package: connectomics
ConnectomicsNote: Under heavy developmentThis repository is currently under significant development, and should not be considered stable. Semantic versioning is not guaranteed for now; APIs may - and likely will - change often and without notice.About this repositoryCommon code for analyzing volumetric datasets for connectomic reconstruction, including geometric primitives likeBoundingBoxandBoxGenerator, and dealing with segmentation ID ranges, including relabeling, making ranges contiguous, and testing whether two volumes contain equivalent sequences.Coming soon: pipeline primitives to process subvolumes.Projects using ConnectomicsSOFIMA- SOFIMA (Scalable Optical Flow-based Image Montaging and Alignment) is a tool for stitching, aligning and warping large 2d, 3d and 4d microscopy datasets.This is not an officially supported Google product.
Package: connect-openapi-client
Connect Python OpenAPI ClientIntroductionConnect Python OpenAPI Clientis the simple, concise, powerful and REPL-friendly CloudBlue Connect API client.It has been designed following thefluent interface design pattern.Due to its REPL-friendly nature, using the CloudBlue Connect OpenAPI specifications it allows developers to learn and
play with the CloudBlue Connect API using a python REPL likejupyteroripython.InstallConnect Python OpenAPI Clientrequires python 3.8 or later.Connect Python OpenAPI Clientcan be installed frompypi.orgusing pip:$ pip install connect-openapi-clientDevelopmentWe useisortlibrary to order and format our imports, andblack- to format the code.
We check it usingflake8-isortandflake8-blacklibraries (automatically onflake8run).For convenience you may runisort . && black .to format the code.DocumentationConnect Python OpenAPI Clientdocumentationis hosted on theRead the Docsservice.LicenseConnect Python OpenAPI Clientis released under theApache License Version 2.0.
Package: connector-calendars
Connector calendars is a Django application for tracking third-party calendars
via iCalendar feed and syncing events based on that feed. It relies onconnector-eventsfor managing
individual events themselves.It was designed as a component for a ‘connector’ project, tracking events for a
community from multiple sources.DocumentationThe full documentation is athttps://connector-calendars.readthedocs.org.QuickstartInstall connector-calendars:pip install connector-calendarsThen add events and calendars to your project’s INSTALLED_APPS:INSTALLED_APPS = (
    'events',
    'calendars',
)After adding calendar feeds in the admin you can update them right from there,
or use theread_calendarsmanagement command to begin syncing them.History0.1.0 (2014-09-01)First release on PyPI.
Package: connectorcomet
Comet ConnectorA Python package to connect and retrieve data from the Comet API.Usagefromconnectorcomet.connectorimportConnector# Crear una instancia de la clase Connectorconnector_instance=Connector()# Lista de tokenslist_token_api=['your tokens']# Llamar al método getResultsdf_results=connector_instance.getResults(list_token_api)
Package: connector-db-tools
connector_db_toolsconnector_db_tools is a Python library that implements for connection databasesInstallationThe code is packaged for PyPI, so that the installation consists in running:pipinstallspark-datax-schema-toolsUsagewrapper take connection database using pandas and modinexample1:(generatedummy_data)================================importray
importos
fromconnector_db_toolsimportCore

ray.shutdown()ray.init(local_mode=True)""""config.json{"ORACLE":{"oracle":{"host":"XXXXXX","port":1521,"db":"XXXXXX","username":"XXXXX","password":"XXXXX","driver":"{Microsoft ODBC for Oracle}"}}""""path=os.getcwd()path_file_config=os.path.join(path,"config.json")df=Core.database_query(file_config=path_file_config,server="oracle",database="oracle",query=query,is_sql_direct=False)df.head(10)LicenseApache License 2.0.New features v1.0BugFixchoco install visualcpp-build-toolsReferenceJonathan Quizagithub.Jonathan QuizaRumiMLSpark.Jonathan Quizalinkedin.
Package: connector-events
================connector-events================.. image:: https://badge.fury.io/py/connector-events.png:target: https://badge.fury.io/py/connector-events.. image:: https://travis-ci.org/rva-data/connector-events.png?branch=master:target: https://travis-ci.org/rva-data/connector-events.. image:: https://coveralls.io/repos/rva-data/connector-events/badge.png?branch=master:target: https://coveralls.io/r/rva-data/connector-events?branch=masterConnector events is a Django application for tracking events. It hasthe typical list and detail views you expect and an iCal feed foreasily sharing event data.It was designed as a component for a 'connector' project, trackingevents for a community from multiple sources. However it can also beused on it's own... Documentation.. -------------.. The full documentation is at https://connector-events.readthedocs.org.Quickstart----------Install connector-events::pip install connector-eventsThen add events to your project's `INSTALLED_APPS`::INSTALLED_APPS = ('events',)And into your URL configuration::urlpatterns = patterns('',url(r'^events/', include('events.urls')),)Overview--------You can store and display information about events, including start and endtimes, descriptions written in Markdown, and location. Locations can be storedin both plain form, e.g.100 Main St, Richmond, VA, USAand in basic geocoded format. The *current* format for storing geographiclocation uses two separate decimal database fields for latitude and longituderespectively. This is suboptimal compared to using a `single point field<https://docs.djangoproject.com/en/1.6/ref/contrib/gis/model-api/#pointfield>`_but does not entail any special database requirements.The feed is available via the URL `/ical/`, relative to the root URL where youhave configured the event URLs.Settings--------Three settings are worth calling out.`TIME_ZONE`~~~~~~~~~~~This is a `default Django setting<https://docs.djangoproject.com/en/1.6/ref/settings/#time-zone>`_ thatyou should pay attention to, as the ics feed makes uses of this.`EVENTS_UID_STRING`~~~~~~~~~~~~~~~~~~~This is a string that will be formatted with a keyword argument named `pk`. Itused to provide a default `UID` value for an event if none is otherwiseprovided (e.g. through a calendar import, which is beyond the scope of thisapplication itself).The default value is::"event_{pk}"A replacement might be::"event_{pk}@mydomain.com"The `iCalendar specification <http://www.kanzaki.com/docs/ical/uid.html>`_requires that this be a *globally unique* identifier which is why it's a goodidea to use your site name/domain in conjunction with the event primary key(unique on your site).`EVENTS_PRODUCT_ID`~~~~~~~~~~~~~~~~~~~This is a string that identifies the product generating the iCalendar feed. Itpopulates the `PRODID` field in the feed.The default is::"-//django-connector//connector-events//EN"See the `iCalendar specification<http://www.kanzaki.com/docs/ical/prodid.html>`_ for more information aboutthis field.History-------0.1.0 (2014-09-01)++++++++++++++++++* First release on PyPI.
Package: connectors
TheConnectorspackage facilitates the writing of block-diagram-like processing networks.
For this it provides decorators for the methods of processing classes, so they can be connected to each other.
When a parameter in such a processing network is changed, the result values will also be updated automatically.
This is similar to a pipes and filters architecture, the observer pattern or streams.This short example demonstrates the core functionality of theConnectorspackage by implementing a processing network of two sequential blocks, which double their input value:>>> import connectors
>>>
>>> class TimesTwo:
...     def __init__(self, value=0):
...         self.__value = value
...
...     @connectors.Input("get_double")
...     def set_value(self, value):
...         self.__value = value
...
...     @connectors.Output()
...     def get_double(self):
...          return 2 * self.__value
>>>
>>> d1 = TimesTwo()                                     # create an instance that doubles its input value
>>> d2 = TimesTwo().set_value.connect(d1.get_double)    # create a second instance and connect it to the first
>>> d2.get_double()
0
>>> d1.set_value(2)
>>> d2.get_double()                                     # causes the new input value 2 to be processed by d1 and d2
8InstallationTheConnectorspackage requires Python version 3.6 or later.
Python 3.5 might work, but this is not tested.pip3 install connectorsDocumentationThe documentation for theConnectorslibrariy can be found onRead the Docs.LicenseTheConnectorspackage is published under the terms and conditions of the GNU lesser general public license version 3 or later (LGPLv3+).
Package: connectors-to-databases
Connector to databasesConnector to databases– easy package for connect with database:PostgreSQLClickHouseInstallationInstall the current version withPyPI:pipinstallconnectors-to-databasesOr from GitHub:pipinstallhttps://github.com/k0rsakov/connectors_to_databases/archive/refs/heads/main.zipUsageHow to use connections:ClickHouse.mdPostgreSQL.mdContributingBug reports and/or pull requests are welcomeLicenseThe module is available as open source under the terms of theApache License, Version 2.0
Package: connect.py
connect.py is an API wrapper forMonstercat Connectwritten in Python.If you want to report errors, bugs or typos you can join the discord guild listed next to the build shield.InstallingTo install the library, you can just run the following command:python3-mpipinstall-Uconnect.pyTo install the development version, do the following:python3-mpipinstall-Uhttps://github.com/GiovanniMCMXCIX/connect.py/archive/master.zip#egg=connect.py[performance]RequirementsPython 3.6+requestslibraryExtra RequirementsThis library contains an extra requirement that is nameperformancein other the library to work faster.You can install it using the following command:python3-mpipinstall-Uconnect.py[performance]Exampleimportconnectclient=connect.Client()defget_release():releases=client.search_release('friends')print('Found the following:')forreleaseinreleases:print('{0.title}by{0.artists}[{0.catalog_id}] was released on{0.release_date}''and has{1}track(s)'.format(release,len(release.tracks)))if__name__=="__main__":get_release()
Package: connect-reports-core
Connect Reports CoreIntroductionConnect Reports Coreis the kernel package for handling reports on CloudBlue Connect Ecosystem.
This library is reponsible for validation of reports definition, choosing of renderer for parsing process and writing results of reports execution.InstallConnect Reports Corerequires python 3.8 or later and has the following dependencies:openpyxl>=2.5.14WeasyPrint>=53.4Jinja2>=2.11.3jsonschema<=3.2.0pytz>=2021.1lxml>=4.7.1Connect Reports Corecan be installed frompypi.orgusing pip:$ pip install connect-reports-coreTestingOn MacOs:Install system dependenciesbrew install py3cairo pangoCreate virtualenvInstall project dependenciespip install poetry
poetry updateRun testspoetry run pytestLicenseConnect Reports Coreis released under theApache License Version 2.0.
Package: connectrum
Stratum (electrum-server) Client Protocol libraryUses python3 to be a client to the Electrum server network. It makes heavy use ofasynciomodule and newer Python 3 keywords such asawaitandasync.For non-server applications, you can probably find all you need
already in the standard Electrum code and command line.Featurescan connect via Tor, SSL, proxied or directlyfilter lists of peers by protocol,.onionnamemanage lists of Electrum servers in simple JSON files.fully asynchronous design, so can connect to multiple at oncea number of nearly-useful examples providedExamplesInexamplesyou will find a number little example programs.cli.pysend single commands, plan is to make this an interactive REPLsubscribe.pystream changes/events for an address or blocks.explorer.pyimplements a simplistic block explorer websitespider.pyfind all Electrum servers recursively, read/write results to JSONVersion History0.8.0Support for ElectrumX protocol 1.4 with some helpers to restore useful functions.0.7.4Addactual_connectionatrribute onStratumClientwith some key details0.7.3Not sure0.7.2Bugfix: port numbers vs. protocols0.7.1Python 2.6 compat fix0.7.0Reconnect broken server connections automatically (after first connect).0.6.0Various pull requests from other devs integrated. Thanks to @devrandom, @ysangkok!0.5.3Documents the build/release process (no functional changes).0.5.2Make aiosocks and bottom modules optional at runtime (thanks to @BioMike)0.5.1Minor bug fixes0.5.0First public release.TODO Listbe more robust about failed servers, reconnect and handle it.connect to a few (3?) servers and compare top block and response times; pick bestsome sort of persistant server list that can be updated as we runtype checking of parameters sent to server (maybe)?lots of test codean example that finds servers that do SSL with self-signed certificatean example that fingerprints servers to learn what codebase they usesome bitcoin-specific code that all clients would need; like block header to hash
Package: connect-sdk
Connect Python  SDKConnect Python SDK allows an easy and fast integration with Connect fulfillment API. Thanks to it you can automate the fulfillment of orders generated by your products.Please check the documentation availablehere, which contains information on how to install and use the library, and a complete API reference guide.Main FeaturesThis library may be consumed in your project in order to automate the fulfillment of requests, this class once imported into your project will allow you to:Communicate with Connect using your API credentials.List all requests, and even filter them:For a specific product.For a specific status.For a specific asset.Etc.Process each request and obtain full details of the request.Modify the activation parameters of each request in order to:Inquiry for changesStore information into the fulfillment requestChange the status of the requests from its initial pending state to either inquiring, failed or approved.Generate and upload usage files to report usage for active contracts and listings.Process usage file status changes.Work with Notes for requests.Generate logs.Collect debug logs in case of failure.Your code may use any scheduler to execute, from a simple cron to a cloud scheduler like the ones available in Azure, Google, Amazon or other cloud platforms.Installation$pipinstallconnect-sdkRequirementsPython 2.7+ or Python 3.4+Requests (https://pypi.org/project/requests/)Marshmallow (https://pypi.org/project/marshmallow/)ContributeIf you want to contribute to the connect-python-sdk development feel free to open issues or fork the github repository and submit your pull request.DevelopmentGetting startedAssuming that you have python and virtualenv installed, and forked the connect-python-sdk repository, set up your environment and install the required dependencies like this:$gitclonehttps://github.com/{your_github_account}/connect-python-sdk.git
$cdconnect-python-sdk
$virtualenvvenv
$.venv/bin/activate
$pipinstall-rrequirements/test.txtRunning testsThe connect-python-sdk usespytestfor unit testing.To run the entire tests suite execute:$pytestLicenseThe connect-python-sdk is released under theApache License, Version 2.0.
Package: connect-sdk-python2
IntroductionThe Python SDK helps you to communicate with theIngenico ConnectServer API. Its primary features are:convenient Python library for the API calls and responsesmarshalls Python request objects to HTTP requestsunmarshalls HTTP responses to Python response objects or Python exceptionshandling of all the details concerning authenticationhandling of required meta dataIts use is demonstrated by an example for each possible call. The examples execute a call using the provided API keys.See theIngenico Connect Developer Hubfor more information on how to use the SDK.Structure of this repositoryThis repository consists out of four main components:The source code of the SDK itself:/ingenico/connect/sdk/The source code of the SDK unit tests:/tests/unit/The source code of the SDK integration tests:/tests/integration/Usage examples:/examples/Note that the source code of the unit tests and integration tests and the examples can only be found on GitHub.RequirementsPython 2.7 is required. In addition, the following packages are required:requests2.25.0 or higherrequests-toolbelt0.8.0 or higherThese packages will be installed automatically if the SDK is installed manually or using pip following the below instructions.InstallationTo install the SDK using pip, execute the following command:pipinstallconnect-sdk-python2Alternatively, you can install the SDK from a source distribution file:Download the latest version of the Python SDK from GitHub. Choose theconnect-sdk-python2-x.y.z.zipfile from thereleasespage, wherex.y.zis the version number.Execute the following command in the folder where the SDK was downloaded to:pipinstallconnect-sdk-python2-x.y.z.zipUninstallingAfter the Python SDK has been installed, it can be uninstalled using the following command:pipuninstallconnect-sdk-python2The required packages can be uninstalled in the same way.Running testsThere are two types of tests: unit tests and integration tests. The unit tests will work out-of-the-box; for the integration tests some configuration is required.
First, some environment variables need to be set:connect.api.apiKeyIdfor the API key id to use. This can be retrieved from the Configuration Center.connect.api.secretApiKeyfor the secret API key to use. This can be retrieved from the Configuration Center.connect.api.merchantIdfor your merchant ID.In addition, to run the proxy integration tests, the proxy URI, username and password should be set in thetests/resources/configuration.proxy.inifile.In order to run the unit and integration tests, themockbackport andmockitoare required. These can be installed using the following command:pipinstallmock'mockito<1.3.1'The following commands can now be executed from thetestsdirectory to execute the tests:Unit tests:pythonrun_unit_tests.pyIntegration tests:pythonrun_integration_tests.pyBoth unit and integration tests:pythonrun_all_tests.pyNote: in the current version of the unit tests, two errors will pop up ([Errno 10053] for Windows and [Errno 32] for Linux), indicating that there was a client disconnect. These errors occur during cleanup of the tests and do not hinder the tests in any way, and should therefore be ignored.
Package: connect-sdk-python3
IntroductionThe Python SDK helps you to communicate with theIngenico ConnectServer API. Its primary features are:convenient Python library for the API calls and responsesmarshalls Python request objects to HTTP requestsunmarshalls HTTP responses to Python response objects or Python exceptionshandling of all the details concerning authenticationhandling of required meta dataIts use is demonstrated by an example for each possible call. The examples execute a call using the provided API keys.See theIngenico Connect Developer Hubfor more information on how to use the SDK.Structure of this repositoryThis repository consists out of four main components:The source code of the SDK itself:/ingenico/connect/sdk/The source code of the SDK unit tests:/tests/unit/The source code of the SDK integration tests:/tests/integration/Usage examples:/examples/Note that the source code of the unit tests and integration tests and the examples can only be found on GitHub.RequirementsPython 3.5 or higher is required. In addition, the following packages are required:requests2.25.0 or higherrequests-toolbelt0.8.0 or higherThese packages will be installed automatically if the SDK is installed manually or using pip following the below instructions.InstallationTo install the SDK using pip, execute the following command:pipinstallconnect-sdk-python3Alternatively, you can install the SDK from a source distribution file:Download the latest version of the Python SDK from GitHub. Choose theconnect-sdk-python3-x.y.z.zipfile from thereleasespage, wherex.y.zis the version number.Execute the following command in the folder where the SDK was downloaded to:pipinstallconnect-sdk-python3-x.y.z.zipUninstallingAfter the Python SDK has been installed, it can be uninstalled using the following command:pipuninstallconnect-sdk-python3The required packages can be uninstalled in the same way.Running testsThere are two types of tests: unit tests and integration tests. The unit tests will work out-of-the-box; for the integration tests some configuration is required.
First, some environment variables need to be set:connect.api.apiKeyIdfor the API key id to use. This can be retrieved from the Configuration Center.connect.api.secretApiKeyfor the secret API key to use. This can be retrieved from the Configuration Center.connect.api.merchantIdfor your merchant ID.In addition, to run the proxy integration tests, the proxy URI, username and password should be set in thetests/resources/configuration.proxy.inifile.In order to run the unit and integration tests, themockbackport andmockitoare required. These can be installed using the following command:pipinstallmockmockitoThe following commands can now be executed from thetestsdirectory to execute the tests:Unit tests:pythonrun_unit_tests.pyIntegration tests:pythonrun_integration_tests.pyBoth unit and integration tests:pythonrun_all_tests.py
Package: connect-spotify
How to use the PackageRunpip install connect_spotifyfrom connect_spotify import ConnectionAPI
conn = ApiConnection(
    token=SPOTIFY_API_TOKEN
)
conn._connect()
conn.get_artist_name('the strokes')
#returns artist dataDescriptionOriginal RepoThis application was created to join Streamlit Hackathon. It data visualizes music artist popularities by bar and line plots. Streamlit connection was used to interact with Spotify API.How to RunRunpip intallCreate secrets.toml according to the sample.secrets.toml. You need to get your client secret from SpotifyRunstreamlit run app.pyLive pageLive PageStreamlit kindly provides the community cloud server for streamlit app.
Follow the instructions of thelinkif you want to deploy it on your own.