Saravanan666/pypi-org huggingface dataset:
Package: python-keystoneclient-rackspace
# python-keystoneclient-rackspacePlugin for API key authentication in the Rackspace CloudExample usage:from keystoneclient_rackspace.v2_0 import RackspaceAuthfrom keystoneclient.session import Sessionfrom novaclient.client import Clientauth = RackspaceAuth(auth_url="https://identity.api.rackspacecloud.com/v2.0",username="demoauthor",api_key="aaaaa-bbbbb-ccccc-12345678",tenant_id=1100111)session = Session(auth=auth)client = Client(2, session=session, region_name="DFW")client.servers.list()
Package: python-keystoneclient-saml2
Federation plugins and helpers for the OpenStack clients.Free software: Apache licenseDocumentation:http://docs.openstack.org/developer/python-keystoneclient-saml2Source:http://git.openstack.org/cgit/openstack/python-keystoneclient-saml2Bugs:http://bugs.launchpad.net/python-keystoneclientFeaturesTODO
Package: python-keystone-voms
# Keystone VOMS auth module [![Build Status](https://travis-ci.org/IFCA/keystone-voms.png?branch=stable/icehouse)](https://travis-ci.org/IFCA/keystone-voms)This module is intended to provide VOMS authentication to a Grizzly
OpenStack Keystone. It is designed to be integrated as an external
authentication plugin, so that Keystone will preserve its original
features and users will still be able to authenticate using any of the
Keystone native mechanisms.The documentation (the source is indoc/source/) is online at
[Keystone VOMS documentation](https://keystone-voms.readthedocs.org/en/latest/).If you are using it, it would be nice that you add your site to the
[Sites Using It](https://github.com/IFCA/keystone-voms/wiki/SitesUsingIt) wiki page.## TestingIf you are interested in running the unit tests, check theTESTING.mdfile for instructions.[Build Status]:https://travis-ci.org/IFCA/keystone-voms[BS img]:https://travis-ci.org/IFCA/keystone-voms.png
Package: python-kitsune
KitsuneA prettier way to tail multiple files.Installationpip install python-kitsuneCommand Line Interfaceusage: kitsune [--color <when>] [-h] [-V] pattern [pattern ...]

A prettier way to tail multiple files.

positional arguments:
  pattern         Files to tail.

optional arguments:
  --color <when>  Specify when to use colored output. The automatic mode only
                  enables colors if an interactive terminal is detected.
                  [default: auto] [possible values: auto, never, always]
  -h, --help      Print this help message.
  -V, --version   Show version information.Screenshot
Package: python-kkmeans
kkmeansRepository:https://git01lab.cs.univie.ac.at/osterj97/oster-bachelor-thesisImplementation of the Kernel k-means clustering algorithm for multiple dimensions (including as well one-dimensional data) in Python. The results are visualized in plots and measured with quality metrics (e.g. Silhouette Coefficient). The algorithm can be used as a framework.https://sites.google.com/site/dataclusteringalgorithms/kernel-k-means-clustering-algorithmThe related bachelor thesis can be found here:https://www.overleaf.com/read/shnzrthjgqtw(read only) or as an exported .pdf hereBachelor_Thesis____Kernel_k_means_clustering_framework_in_Python.pdfInstallationpip install python-kkmeansThe package can also be installed directly from this repository usingpip install git+ssh://git@git01lab.cs.univie.ac.at/osterj97/oster-bachelor-thesis.git.Quickstartfrom sklearn.datasets import make_blobs
from sklearn.preprocessing import StandardScaler
import matplotlib.pyplot as plt

from kkmeans import kkmeans

n_clusters = 3
X, _ = make_blobs(n_samples=100, n_features=3, centers=n_clusters)
X_scaled = StandardScaler().fit_transform(X)

cluster_assignments = kkmeans(X, n_clusters=n_clusters)
plt.scatter(X_scaled[:,0], X_scaled[:,1], c=cluster_assignments)ExamplesTake a look at theexamples folderto see benchmarking and plotted examples of the algorithm in action. The playground notebook should give you a comprehensive overview of the evaluation of the algorithm. It can be run afterinstalling jupyterand runningjupyter notebookfrom this folder.Local DevelopmentThe following commands assume you run on a Linux or Mac, for Windows instructions take a look at the officialdocumentations.(optional) Create a venvpython3 -m venv .venv(optional) Active venvsource .venv/bin/activate(optional) Update pippip install --upgrade pipInstall all required packagespip install -r requirements.txtTestTesting is set up usingpytest. Run all tests running the commandpytestin the root directory. For detailed description on pytest see:Full pytest documentation
Package: python-klabclient
# python-klabclient## InstallationDeveloper installation:```bashgit clone https://github.com/kuberlab/python-klabclientcd python-klabclientpip install -e .```* for MacOS add --ignore-installed six at the end of the command lineUser installation:```bashpip install python-klabclient```* for MacOS add --ignore-installed six at the end of the command lineInstall in virtual environment:```bashvirtualenv venvcd venvbin/pip install python-klabclient```* `klab` console command will be accessed from `venv/bin/klab` path.## Uninstall:```bashpip uninstall python-klabclient```* Also, if it is required, delete file `~/.kuberlab/config`.## Usage#### Use config for auth (default location is *~/.kuberlab/config*)```bashtouch ~/.kuberlab/configcat << EOF >> ~/.kuberlab/configbase_url: https://go.kuberlab.com/api/v0.2token: <user-token>EOF```**Note**: Refer to [Config example](config.yaml.example) to see all possible values.#### Use environment variables```bash# Set tokenexport KUBERLAB_TOKEN=token# Or, use your login/passwordexport KUBERLAB_USERNAME=my@example.comexport KUBERLAB_PASSWORD=mypassword```#### Call CLI or see help to take a look on a command list:```bashklab workspace-list# See helpklab --help```## App installation exampleSee how to install a simple app - [App installation](App_installation.md)**Note**: Priority for auth parameters: CLI parameters, Env variables, config values.## Usage as a python library```pythonfrom klabclient.api import client# Init sessionses = client.create_session(token='token') # Pick up default base_url# Or, use username and password# ses = client.create_session(username='username', password='password') # Pick up default base_urlklab = client.Client(session=ses) # Pick up default klab_urlworkspaces = klab.workspaces.list()# Print all workspace namesprint([w.Name for w in workspaces])```
Package: python-kodaksmarthome
Python Kodak Smart HomePython Kodak Smart Home is a library written in Python 3 (>=3.7) that works as API forKodak Smart Home Portal.This API uses the credentials from Kodak Smart Home Portal to fetch devices
registered and its events to be used as Python Projects.This project is not part of Kodak.Installationpip install python-kodaksmarthomeUsageInitializing the connection>>>fromkodaksmarthomeimportKodakSmartHome>>>my_home=KodakSmartHome('my@email.com','my-pass')>>>my_home.connect()>>>my_home.is_connectedTrueListing devices, state, model and device id>>>fordeviceinmy_home.list_devices:...print(f"Device:{device['name']}")...print(f"Device ID:{device['device_id']})...print(f"Model:{device['model_name']})...print(f"Online:{device['is_online']}\n")...Device: PlaygroundDevice ID: '000009999999999999999999'Model: Cherish 525Online: FalseDevice: BedroomDevice ID: '00000222222222222222222'Model: Cherish 525Online: TrueListing last device motion events>>>motion_events=my_home.get_motion_events(device_id="00000222222222222222222")>>>foreventinmotion_events[:2]:...print(f"snapshot:{event['snapshot']}")...print(f"video_recorded:{event['data'][0]['file']}")...print(f"data:{event['created_date']}\n")snapshot: http://video_url/00000222222222222222222/SNAPSHOT.jpgvideo_recorded: http://video_url/00000222222222222222222/VIDEO000001.flvdate: 2020-01-04T16:11:48.000Zsnapshot: http://video_url/00000222222222222222222/SNAPSHOTvideo_recorded: http://video_url/00000222222222222222222/VIDEO000002.flvdate: 2020-01-04T16:08:52.000ZDocumentationhttps://python-kodaksmarthome.readthedocs.io
Package: python-kong
docstestspackagecompatibilityA Python client for the Kong API (https://getkong.org/)Free software: BSD licenseInstallationpip install python-kongDocumentationhttps://python-kong.readthedocs.org/DevelopmentTo run the all tests run:toxChangelog0.4.0 (2015-10-09)Changed ‘add’ to ‘create’ and ‘add_or_update’ to ‘create_or_update’ (WARNING: Not backwards compatible!)Code cleanup0.3.2 (2015-10-07)Updated contract docstrings to explicitly support ‘six.text_type’ instead of ‘str’0.3.1 (2015-09-23)Now supporting ‘preserve_host’ and ‘strip_request_path’ options0.3.0 (2015-09-22)Updated library again to be compatible with Kong 0.5.x (WARNING: Not backwards compatible!)0.2.0 (2015-09-09)Updated library to be compatible with Kong 0.5.x (WARNING: Not backwards compatible!)0.1.14 (2015-08-26)Added some error checks0.1.13 (2015-08-26)Small bugfix0.1.12 (2015-08-20)Implemented retrieve api for APIPluginConfigurationAdminContract0.1.11 (2015-08-19)Implemented close method for KongAdminContract0.1.10 (2015-08-18)Implemented Basic Auth credentials API’sImplemented Key authentication API’sImplemented OAuth2 API’s0.1.9 (2015-08-06)Improved error handling in client0.1.8 (2015-08-06)Bugfixes0.1.7 (2015-07-30)Implemented APIAdminContract.add_or_update APIImplemented APIPluginConfigurationAdminContract.create_or_update APIImplemented ConsumerAdminContract.create_or_update API0.1.6 (2015-07-28)Updated KongAdminSimulator constructor to accept api_url0.1.5 (2015-07-28)Added CollectionMixin to contract (abstract base classes)0.1.4 (2015-07-28)Bugfix related to checking for API conflicts0.1.3 (2015-07-28)Added more tests and ‘CollectionMixin’ that exposes an ‘iterate’ api0.1.2 (2015-07-27)Implemented ‘plugin configuration’ update API0.1.1 (2015-07-24)Package structure updated0.1.0 (2015-07-23)First release on PyPI.
Package: python-kongclient
Python - Kong ClientThis is a Python library for the Kong admin API.It was build aroundkong 1.14.x specificationsInstallationPypIpipinstallpython-kongclientManualClone the repositorygit clone git@github.com:haintd/python-kongclient.gitEnter itcd python-kongclientInstall itpython setup.py installInstructionsImport into your projectfromkongclientimportKongClientCreate a kong clientkong_client=KongClient(kong_url='https://localhost:8444',verify_ssl=True)kong_client.services.create(name='httpbin',url='https://httpbin.org')kong_client.services.add_route(service_id='httpbin',name='route',hosts=['httpbin.org'])kong_client.routes.list()...For Python-FlaskfromflaskimportFlask
fromkongclient.flaskimportKongClientapp=Flask(__name__)app.config['KONG_ADMIN_URL']='https://localhost:8444'app.config['KONG_ADMIN_VERIFY_SSL']=Truekong_client=KongClient(app)@app.route('/services',methods=['GET])defget_services():returnkong_client.services.list()For more details, checkoutkong documentation
Package: python-kong-management
Python Kong ManagementPython api wrapper for Kong API GatwayFree software: MIT licenseDocumentation:https://python-kong-management.readthedocs.io.FeaturesTODOTesting`bash cp .env.example .env python3-mvenv venv source venv eval $(cat .env | sed's/^/export/') setup.py pytest `History0.1.0 (2017-10-25)First release on PyPI.
Package: python-kubernetes
Python KubernetesA Python wrapper around the Kubernetes API.By the Python-Kubernetes Developers <pjs7678@cosmos.io>IntroductionThis library provides a pure Python interface for theKubernetes API http://cdn.rawgit.com/GoogleCloudPlatform/kubernetes/31a0daae3627c91bc96e1f02a6344cd76e294791/api/kubernetes.html.InstallingGetting the codehttps://github.com/cosmos-io/python-kubernetesDocumentationUsingThe library provides a Python wrapper around the Kubernetes API and the Kubernetes data model.ModelAPITododoc
testsMore InformationLicenseCopyright 2014 Cosmos.ioLicensed 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 athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed 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 andlimitations under the License.
Package: python-kubernetes-wrapper
============Python Kubernetes============A Python wrapper around the Kubernetes API.By the Python-Kubernetes Developers <pjs7678@gmail.com>============Introduction============This library provides a pure Python interface for the `Kubernetes API http://cdn.rawgit.com/GoogleCloudPlatform/kubernetes/31a0daae3627c91bc96e1f02a6344cd76e294791/api/kubernetes.html`.==========Installing==========================Getting the code================https://github.com/cosmos-io/python-kubernetes=============Documentation==================Using=====The library provides a Python wrapper around the Kubernetes API and the Kubernetes data model.-----Model--------API-------Todo----doctests----------------More Information-----------------------License-------| Copyright 2014 Cosmos.io|| 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.pjs76782014-10-25Released 0.1Initial checkin of python-kubernetes
Package: python-kuro
A simple Python API for controlling Pioneer Kuro TV’s using an rs232 serial port.Supported hardware:  PDP-LX5090/5090H/6090/6090H and KRP-500A/600A seriesTV ConfigurationTo configure the serial port in the Kuro TV the following steps must be done:1.1 Baud rate selection
a) Entering integrator menu:
Push Menu key and Power key within 3sec. Following default Integrator menu will appear.
RS232C baud rate settingb) Exit from integrator menu:
Push Home Menu key then close Integrator menu and return to normal operation.c) RS232C baud rate setting
UART SELECT: 1200bps/2400bps/4800bps/9600bps/19200bps/38400bpsExample of useCreate a new instance of the gateway:gat=Gateway(portname,baudrate)portname is the name of the serial port where the serial is listed on the os.
It can be also be defined as an rfr2217 url.
baudrate value on which the TV has been set (see TV configuration section)
Please refer to the serial library documentation.To send a command to the tv:gat.executeCmd(command,parameter)this will send any command if it is properly configured.On the protocol.py file several commands are already configured and can be
send directly to the gateway. For example to mute the TV:gat.executeCommand(MutedCommand(MutedState.ON))Please review the protocol.py file for a complete list of implemented commands.
Package: python-kyototycoon
ABOUTPython client library for Kyoto Tycoon. For more information on
Kyoto Tycoon please refer to the official project website.http://fallabs.com/kyototycoon/python-kyototycoon’s interface follows the preferred interface
provided by Kyoto Tycoon’s original author(s).http://fallabs.com/kyototycoon/kyototycoon.idlThere is currently no documentation for this software but for
the meantime please see kyototycoon.py for the interface.This fork is backwards compatible, and includes cursor support
and significant performance improvements over the original
library.INSTALLATIONUsing pip:pip install python-kyototycoonOr, from source:python setup.py build
sudo python setup.py installAUTHORSToru Maesaka <dev@torum.net>Stephen Hamer <stephen.hamer@upverter.com>
Package: python-kyototycoon-binary
A lightweight Python client for accessingKyoto Tycoonvia its binary protocol.The specification of the binary protocol is explainedhere.Installation$pipinstallCython$pipinstallpython-kyototycoon-binaryBasic Usage>>>frombkyototycoonimportKyotoTycoonConnection>>>client=KyotoTycoonConnection()>>>client.set_bulk({'key1':'value1','key2':'value2'})2>>>client.get_bulk(['key1','key2','key3']){'key2':'value2','key1':'value1'}>>>client.remove_bulk(['key1','key2'])1>>>client.get_bulk(['key1','key2','key3']){'key1':'value1'}PerformanceIn our benchmark tests,python-kyototycoon-binarywas about6-8 fasterthanpython-kyototycoon.$pipinstallpython-kyototycoon$ktserver-dmn$pythonbenchmarks/benchmark.pypython-kyototycoon-binaryget_bulkqps:30961python-kyototycoon-binaryset_bulkqps:40320python-kyototycoon-binaryget_bulk_with_poolqps:31722python-kyototycoon-binaryset_bulk_with_poolqps:42961python-kyototycoonget_bulkqps:4394python-kyototycoonset_bulkqps:4534DocumentationDocumentation is available athttp://python-kyototycoon-binary.readthedocs.org.
Package: python-la
python-la : Python linear algebra v=0.97.0introductionThe aim of this project is to implement programatically all of the mathematical operations you can in linear algebra, and more so - to implement themt in such a way that it will be written programmatically as close to mathematically as possibleHow to installpip install python-laExamples>>frompython_laimportMatrix,Span,Vector,PolynomialSimple,LinearMap,RealField,VectorSpace>>Matrix([[1,2],[3,4]]).gaussian_elimination()---------|1|0|---------|0|1|--------->>Matrix([[1,2,3],[4,5,6],[7,8,9]]).characteristic_polynomialX^3-15X^2-18X>>Matrix([[1,0,1],[0,1,1]]).kernel[-1,-1,1]>>v1,v2=Vector([3,4]),Vector([4,5])>>Span([v1,v2]).to_orthonormal()[0.6,0.8][0.8,-0.6]>>R2=RealField(2)>>V=VectorSpace(R2)>>lm=LinearMap(V,V,lambdavector:Vector([0,vector[0]],R2))>>x_squared=PolynomialSimple.from_string("x^2")>>plus_1=PolynomialSimple.from_string("x+1")>>v=V.random()>>P=plus_1(x_squared)>>PX^2+1>>P(lm)(v)==vTrue
Package: python-lala
Lala is a Python library for access log analysis. It provides a set of methods to retrieve, parse and analyze access logs (only from NGINX for now), and makes it easy to plot geo-localization or time-series data. Think of it as a simpler, Python-automatable version of Google Analytics, to make reports like this:UsagefromlalaimportWebLogsweblogs,errored_lines=WebLogs.from_nginx_weblogs('access_logs.txt')Similarly, to fetch logs on a distant server (for which you have access keys)
you would write:fromlalaimportget_remote_file_content,WebLogslogs=lala.get_remote_file_content(host="cuba.genomefoundry.org",user='root',filename='/var/log/nginx_cuba/access.log')weblogs,errors=WebLogs.from_nginx_weblogs(logs.split('\n'))Nowweblogsis a scpecial kind ofPandasdataframe where each row is one server access, with fields such asIP,date,referrer,country_name, etc.The web logs can therefore be analyzed using any of Pandas’ built-in filtering and plotting functions. TheWebLogsclass also provides additional methods which are particularly useful to analyse web logs, for instance to plot pie-charts:ax,country_values=weblogs.plot_piechart('country_name')Next we plot the location (cities) providing the most connexions:ax=weblogs.plot_geo_positions()We can also restrict the entries to the UK, and plot a timeline of connexions:uk_entries=weblogs[weblogs.country_name=='United Kingdom']ax=uk_entries.plot_timeline(bins_per_day=2)Here is how to get the visitors a list of visitors and visits, sort out the most frequent visitors, find their locations, and plot it all:visitors=weblogs.visitors_and_visits()visitors_locations=weblogs.visitors_locations()frequent_visitors=weblogs.most_frequent_visitors(n_visitors=5)ax=weblogs.plot_most_frequent_visitors(n_visitors=5)Lala can do more, such as identifying the domain name of the visitors, which can be used to filter out the robots of search engines:weblogs.identify_ips_domains()filtered_entries=weblogs.filter_by_text_search(terms=['googlebot','spider.yandex','baidu','msnbot'],not_in='domain')Lala also plays nicely with thePDF Reportslibrary to let you define report templates such asthis one(written in Pug), and then generatethis PDF reportwith the following code:weblogs.write_report(template_path="path/to/template.pug",target="report_example.pdf")InstallationYou can install lala through PIPsudopipinstallpython-lalaAlternatively, you can unzip the sources in a folder and typesudopythonsetup.pyinstallFor plotting maps you will need Cartopy which is not always easy to install - it may depend on your system. If you are on Ubuntu 16+, first install the dependencies with:sudoapt-getinstalllibproj-devproj-binproj-datalibgeos-devsudopipinstallcythonLicense = MITlala is an open-source software originally written at theEdinburgh Genome FoundrybyZulkoandreleased on Githubunder the MIT licence (Copyright 2018 Edinburgh Genome Foundry).Everyone is welcome to contribute!
Package: python-lambda-4dn
Python-lambda is a toolset for developing and deployingserverlessPython code in AWS Lambda.ImportantThis is a FORK of the original Python-lambda package by Nick Ficano.
It will NOT be updated regularly and is frozen per our projects needs.DescriptionAWS Lambda is a service that allows you to write Python, Java, or Node.js code that gets executed in response to events like http requests or files uploaded to S3.Working with Lambda is relatively easy, but the process of bundling and deploying your code is not as simple as it could be.ThePython-Lambdalibrary takes away the guess work of developing your Python-Lambda services by providing you a toolset to streamline the annoying parts.RequirementsPython 3.6Pip (Any should work)Virtualenv (>=15.0.0)Virtualenvwrapper (>=4.7.1)Getting StartedUsing this library is intended to be as straightforward as possible. Code for a very simple lambda used in the tests is reproduced below.config={'function_name':'my_test_function','function_module':'service','function_handler':'handler','handler':'service.handler','region':'us-east-1','runtime':'python3.6','role':'helloworld','description':'Test lambda'}defhandler(event,context):return'Hello! My input event is%s'%eventThis code illustrates the two things required to create a lambda. The first isconfig, which specifies metadata for AWS. One important thing to note in here is therolefield. This must be a IAM role with Lambda permissions - the one in this example is ours. The second is thehandlerfunction. This is the actual code that is executed.Given this code inexample_function.pyyou would deploy this function like so:fromaws_lambdaimportdeploy_functionimportexample_functiondeploy_function(example_function,function_name_suffix='<suffix>',package_objects=['list','of','local','modules'],requirements_fpath='path/to/requirements',extra_config={'optional_arguments_for':'boto3'})And that’s it! You’ve deployed a simple lambda function. You can navigate to the AWS console to create a test event to trigger it or you can invoke it directly using Boto3.Advanced UsageMany of the options specified in the above code block when it came to actually deploying the function are not used. These become more useful as you want to make more complicated lambda functions. The ideal way to incorporate dependencies into lambda functions is by providing arequirements.txtfile. We rely onpipto install these packages and have found it to be very reliable. While it is also possible to specify local modules as well throughpackage_objects, doing so is not recommended because those modules must be specified at the top level of the repository in order to work out of the box. There is a comment on this topic inexample_function_package.pywith code on how to handle it.TestsTests can be found in thetest_aws_lambda.py. Using the tests as a guide to develop your lambdas is probably a good idea. You can also see how to invoke the lambdas directly from Python (and interpret the response).