Saravanan666/pypi-org huggingface dataset:
Package: pykolada
PyKoladaA Python wrapper for the statistical API Kolada.OverviewThis Python package provides a lightweight wrapper for the Kolada API, which allows users to access and interact with key performance indicators (KPIs) for Swedish municipalities and organizational units. The Kolada database, maintained by RKA (Rådet för kommunal analys), offers a rich set of data, and this wrapper simplifies the process of querying and retrieving this information.FeaturesAccess to various endpoints like KPI, KPI groups, municipalities, municipality groups, and organizational units.Support for querying data based on different parameters such as ID, title, description, operating area, year, etc.Handling of pagination to fetch all relevant data.Customizable queries with support for filtering and specifying primary keys.InstallationThis package requires Python 3.8 or higher.
You can install it using pip:pipinstallpykoladaUsageImporting the ModuleimportpykoladaMaking QueriesYou can make queries to different endpoints. For example, to query KPI data:kpi_data=pykolada.get_kpi(id='some_id',title='some_title')Endpointskpikpi_groupsmunicipalitymunicipality_groupsoudataoudataEach endpoint supports different parameters for querying. Please refer to the documentation for detailed information.Documentation and ExamplesPlanned FeaturesOptional caching of data.Support for outputting data in CSV format (currently only original JSON is supported).Usage of additional custom filters that can be applied after the data has been retrieved.Support for the from_date parameter (limiting results data published after a certain date).LicenseMIT License
Package: pykonal
Welcome to thepykonalrepository!This code implements the Fast Marching Method (FMM; Sethianet al., 1996) for solving the eikonal equation in Cartesian or spherical coordinates in 2 or 3 dimensions. The method implements mixed first- and second-order finite differences.PyKonal offers two features that are absent from the comparablescikit-fmmpackage: (a) an implementation in spherical coordinates, and (b) functionality to compute shortest-traveltime paths.DocumentationDocumentation is availablehere.CitationIf you make use of this code in published work, please cite Whiteet al.(2020).InstallationPIP—recommendedsh$>pipinstallpykonalFrom source codeDownload and unzip thelatest release.sh$>cdpath/to/pykonal
sh$>pipinstall.BugsPlease report bugs, feature requests, and questions through theIssuestracker.ReferencesSethian, J. A. (1996). A fast marching level set method for monotonically advancing fronts.Proceedings of the National Academy of Sciences, 93(4), 1591–1595.https://doi.org/10.1073/pnas.93.4.1591White, M. C. A., Fang, H., Nakata, N., & Ben-Zion, Y. (2020). PyKonal: A Python Package for Solving the Eikonal Equation in Spherical and Cartesian Coordinates Using the Fast Marching Method.Seismological Research Letters, 91(4), 2378-2389.https://doi.org/10.1785/0220190318
Package: pykonkeio
KonkeIOThis library (and its accompanying cli tool) is used to interface with
Konke remote-control devices.Supported DevicesSince some of Konke's device does not have a clear model, I used internal code to identify it.SocketSmart Plug Kk1K2 / K2 Prok2Mini K / Mini ProminikPower StripThe normal onemicmulThe Standing one with USB supportmulLightKLight (LED with RGB color)klightKBulbkbulbInstallpipinstallpykoneioAPI Referenceclasses and methodsK1(ip)is_onlinestatusupdate()turn_on()turn_off()K2(ip)is_onlinestatusupdate()turn_on()turn_off()turn_on_usb()turn_off_usb()turn_on_light()turn_off_light()is_support_ir()ir_learn()ir_quit()ir_emit()ir_remove()ir_remove_group()is_support_rf()rf_learn()rf_quit()rf_emit()rf_remove()rf_remove_group()MinK(ip)is_onlinestatusupdate()turn_on()turn_off()is_support_ir()ir_learn()ir_quit()ir_emit()ir_remove()ir_remove_group()Mul(ip)is_onlinestatus[]usb_status[]update()turn_on(index)turn_off(index)turn_on_all()turn_off_all()turn_on_usb(index)turn_off_usb(index)MicMul(ip)is_onlinestatus[]update()turn_on(index)turn_off(index)turn_on_all()turn_off_all()KLight(ip)is_onlinestatuscolorbrightnessupdate()turn_on()turn_off()set_color()set_brightness()KBulbis_onlinestatusctbrightnessupdate()turn_on()turn_off()set_ct()set_brightness()Demo:frompykonkeioimportK2k2=K2('192.168.0.222')ifnotk2.is_online:print('switch is off line')ifk2.status=='open':k2.turn_off()elifk2.status=='close':k2.turn_on()CLI Commandusage:konkeio[action][device][address][value][--verbose]Supporteddevicesandactionssupportedbyeachdevice:
global:search
k2:get_statusturn_[on/off]turn_[on/off]_usbturn_[on/off]_light
minik:get_statusturn_[on/off]micmul:get_countget_status_allget_status[1/2/3/4]turn_[on/off]_allturn_[on/off]_socket[1/2/3/4]mul:get_countget_status_allget_status[1/2/3]get_usb_countget_usb_status_allget_usb_status[1/2]turn_[on/off]_allturn_[on/off]_socket[1/2/3]turn_[on/off]_usb[1/2]klight:get_statusget_brightnessget_colorturn_[on/off]set_brightnessset_color
kbulb:get_statusget_brightnessget_ctturn_[on/off]set_brightnessset_ct

*eachactionstartswith'set_'mustprovideavalueparameter
valueformat:
color:r,g,b
ct:2700-6500
brightness:0-100

example:
konkeiosearch
konkeioturn_onminik192.168.0.64
konkeioget_statusminik192.168.0.64
konkeioturn_on_usbk2192.168.0.64
konkeioturn_off_lightk2192.168.0.64
konkeioget_countmicmul192.168.0.64
konkeioturn_on_socket3micmul192.168.0.64
konkeioget_status2mul192.168.0.64
konkeioturn_off_allmul192.168.0.64
konkeioget_brightnessklight192.168.0.64
konkeioset_colorklight192.168.0.64255,255,0
konkeioset_ctkbulb192.168.0.643400konkeioturn_offbulb192.168.0.64
Package: pykonker
ObjectiveThis library creates a python wrapper over Konker API to allow easier usage and integration
with Konker REST APISample Usagefrompykonker.main.apiimportClientkonker=Client()konker.login(username='',password='')applications=konker.get_applications()devices=konker.get_all_devices_for_application('default')data=konker.read_data(guid=devices[0]['guid'])Change and publish the library on PyPimakeshellmakepylintNOTE: solve problems identified by lint process .. after that it will generate the module to be publishedmakeuploadafter that, the module will be available on pippipinstallpykonkerorpipinstall--upgradepykonkerReferenceshttps://www.konkerlabs.com/developers/developers-en.htmlhttps://konker.atlassian.net/wiki/spaces/DEV/pages/28180518/Guia+de+Uso+da+Plataforma+Konkerhttps://api.demo.konkerlabs.net/v1/swagger-ui.htmlhttps://itnext.io/create-build-and-ship-a-python3-pip-module-in-5-minutes-31dd6d9d5c8f
Package: pykontagent
This is a very minimal API into Kontagent, written using purely modules from
the Python standard library.Here’s how you might use it:from kontagent import Kontagentk = Kontagent(‘MY_API_KEY’, ‘MY_SECRET_KEY’)
k.invite_sent(16904779, [542469672], tracking_tag=’testtag’)This is now being used in production forhttp://radiosox.com/A full list of all of the methods available is:invite_sentinvite_click_responsenotification_sentnotification_click_responsenotification_email_sentnotification_email_responsepostpost_responseapplication_addedapplication_removedundirected_communication_clickpage_requestuser_informationgoal_countsrevenue_trackingraw_requestYou should consult with the Kontagent REST Server API to see what each of these
functions does.  You can find that here:http://developers.kontagent.com/reference/api-documentation/facebook-rest-server-apiUnfortunately, for right now you’re going to have to UTSL to find out about the
parameters that each method takes.Hope you find this useful!
Package: pykooh
pykoohKonno Ohmachi filter implemented in Numba.This code implements Konno-Ohmachi spectral smoothing as defined in:Konno, K. and Ohmachi, T., 1998. Ground-motion characteristics estimated
from spectral ratio between horizontal and vertical components of
microtremor. Bulletin of the Seismological Society of America, 88(1),
pp.228-241.This code was originally written for smoothing sub-module ingmprocessby Bruce Worden. Dave Boore has providednoteson this topic, which also may be of interest. Notes regarding the
characteristics of the Konno-Ohmachi filter and the implementation are
provided in theimplementationJupyter Notebook.Installationpykoohis available viapipand can be installed with:pip install pykoohBy default,pykoohusesnumbafor the fast implementation of the filter.
Performance can be increased by usingcython, but this requires a C
complier. If a C compiler is available, installcythonrequired
dependencies with:pip install pykooh[cython]UsageSmooth a signal using a bandwith of 30.importpykoohsignal_smooth=pykooh.smooth(freqs,freqs_raw,signal_raw,30)Additional examples and comparison withobspyare provided inexample.CitationPlease cite this software using the followingDOI.Revision Historyv0.3.2Change setup.py to install numpy prior to import.v0.3.1Rename to pykoohv0.3.0Rename to pykoomAdd support for numbaMake cython an optonal dependencyv0.2.5Packaging is hard. MANIFEST is fixed now.v0.2.4Added History to MANIFEST.v0.2.3Updated badges.Added tests for example and implemenation notebooks.v0.2.2Moved Cython to a setup_requiresv0.2.1Fixed packaging issuev0.2Added calculation of effective amplitude spectrumv0.1.2Initial release
Package: pykor
포르투갈어로 명령을 받아들이도록 Python 구문을 수정하는 프로그래밍 언어입니다. 이 언어는
포르투갈어로 명령을 받아들이는 Python의 확장으로 개발되었습니다.PyKor의 유일한 목표는 프로그래밍 학습을 촉진하는 것입니다. 일단 기초가 잡히면 (Python의
경우) 실제 언어로의 전환이 점진적이고 자연스러워집니다.
Package: pykorm
pykorm - Python Kubernetes Object-relational mapping (ORM)pykormis a simple library that links your models to theirkubernetescounterpart.Each model and instance on your code is thus directly linked to your kubernetes
cluster and modifications are thus reflected both ways.ExamplesNamespaced Custom ResourceSetupFirst of all, you need to have Custom Resource Definitions on your cluster.This README will use the following Namespaced resource. You can apply it on your
cluster withkubectl.apiVersion:apiextensions.k8s.io/v1kind:CustomResourceDefinitionmetadata:name:peaches.pykorm.infomaniak.comspec:group:pykorm.infomaniak.comnames:kind:PeachlistKind:PeachListplural:peachessingular:peachscope:Namespacedversions:-name:v1served:truestorage:trueschema:openAPIV3Schema:type:objectproperties:spec:type:objectproperties:variety:type:stringrequired:-varietyadditionalPrinterColumns:-name:Varietytype:stringdescription:The variety of the peachjsonPath:.spec.varietyClass definitionIn order to link a python class to a kubernetes CustomResourceDefinition,
you need to inherit the class from pykorm'sNamespacedModelorClusterModeland annotate it with the kubernetes CRD information like so:importpykorm@pykorm.k8s_custom_object('pykorm.infomaniak.com','v1','peaches')classPeach(pykorm.NamespacedModel):variety:str=pykorm.fields.Spec('variety')Notice that a class inheriting frompykorm.NamespacedModelalready has thenameandnamespacefields setup.Create a CRIn order to create a kubernetes custom resource from python, you just
have to instantiate the class and save it withPykorm.save():importpykormpk=pykorm.Pykorm()cake_peach=Peach(namespace='default',name='cake-peach',variety='Frost')pk.save(cake_peach)# We save the resourceas you can see, the model is instantly ensured in kubernetes:$kubectlgetpeach-ndefault
NAMEVARIETY
cake-peachFrostList resourcesPykorm can also list resources from kubernetes>>>all_peaches=Peach.query.all()>>>forpeachinall_peaches:>>>print(peach)<Peachnamespace=default,name=cake-peach,variety=Frost># Filter by namespace>>>Peach.query.filter_by(namespace='default').filter_by(variety='Frost').all()You can even filter resources by some criterion:>>>Peach.query.filter_by(name='cake-peach').all()[<Peachnamespace=default,name=cake-peach,variety=Frost>]>>>Peach.query.filter_by(namespace='kube-system').all()[]Delete resourcesYou can delete a resource withpykormtoo:pk.delete(peach)$kubectlgetpeach
Noresourcesfoundindefaultnamespace.More examplesFor more examples, don't hesitate to look into theexamples/directoryCoreAPI WrapperMulti Layer Nested & Mixin FieldsLabel Filter & Field SelectorMulti ClusterIs pykorm stable ?pykorm is still very young and very naive. It's also missing quite a lot of
features (relationships, etc.).
It was originally created because a lot of boilerplate code was written each
time a kubernetes custom object had to be interfaced with python
code.Work onpykormis actually on the way. Don't hesitate to contribute to the
project if you have the energy for it !EquivalencesPythonKubernetesClassCustomResourceDefinitionInstanceCustomResource
Package: pykosmos
An easy to use reduction package for one-dimensional longslit spectroscopy.InstallationThe easiest way to install is via pip:pip install pykosmosGoalsThis toolshouldbe able to handle 90% of basic reduction needs from a longslit-style spectrograph.... there are many other smaller or more subtle goals for this project that will be outlined here.There needs to be many worked examples available.MotivationWe need simple to use, standalone reduction tools that can handle most tasks automatically.The predecessor wasPyDIS, a semi-complete standalone reduction suite in Python that has been used for many instruments andpublicationsso far! Since then, manyastropycomponents have advanced to better handle many of the tasks PyDIS attempted, butspecreduceis not complete yet (I share in this blame).Myoriginal blog poston the topic from 2015 still largely stands...LinksPyKOSMOSon GitHubKOSMOSinstrument page at APOPyDIS, the predecessor.dtw_identify, automatic wavelength calibration using Dynamic Time Warping, developed in PyKOSMOSkosmos-arc, a library of calibrated arc lamp templates for KOSMOS at APO
Package: pykosmos-jradavenport
PyKOSMOSAn easy to use reduction package for one-dimensional longslit spectroscopy.GoalsThis toolshouldbe able to handle 90% of basic reduction needs from a longslit-style spectrograph.... there are many other smaller or more subtle goals for this project that will be outlined here.There needs to be many worked examples available.MotivationWe need simple to use, standalone reduction tools that can handle most tasks automatically.The predecessor wasPyDIS, a semi-complete standalone reduction suite in Python that has been used for many instruments andpublicationsso far! Since then, manyastropycomponents have advanced to better handle many of the tasks PyDIS attempted, butspecreduceis not complete yet (I share in this blame).Myoriginal blog poston the topic from 2015 still largely stands...LinksPyDISdtw_identify, automatic wavelength calibration using Dynamic Time Warping, developed in PyKOSMOS
Package: pykostal
pykostal - a python based kostal bridgePython module forKostalpiko inverters supporting:current-valuesanalog-inputsbatterygridhomepv-generators0-inhomeinfo.versionsstatisticsdaylog-datatotalnot supported:all settingseventsongoing:response code mapping (e.g. status code)InstallationRun the following to install:pipinstallpykostalUsageimportkostal# create instanceinverter=kostal.Piko(aiohttp.ClientSession(),url)Developing pykostalInitially run the following in your virtualenv:pythonsetup.pybdist_wheelEverytime you update setup.py, run the following in your virtualenv:pipinstall-e.To install pykostal, along with the tools you need to develop and run tests, run the following in your virtualenv:pipinstall-e.[dev]publishingpythonsetup.pybdist_wheelsdist
twineuploaddist/*
Package: pykostalpiko
pykostalpikoA simple python library to interface with a Kostal Piko Solar inverterExplore the docs »Report Bug·Request FeatureTable of ContentsAbout The ProjectUsageContributingLicenseContactAcknowledgmentsAbout The ProjectThis project aims to support the same functionallity as the web interface of the Piko inverter and provide a friendly way to access it using python.(back to top)UsageInstallationpipinstallpykostalpikoExamplesPrint the current values of the inverterimportasynciofromaiohttpimportClientSessionfrompykostalpikoimportPikofrompykostalpiko.dxs.current_valuesimportLISTasyncdefasnyc_main():asyncwithClientSession()assession:asyncwithPiko(session,"<ip-address>")aspiko:print(awaitpiko.async_fetch_multiple(LIST))asyncio.run(asnyc_main())Change the name of the inverterimportasynciofromaiohttpimportClientSessionfrompykostalpikoimportPikofrompykostalpiko.dxs.inverterimportNAMEasyncdefasnyc_main():asyncwithClientSession()assession:asyncwithPiko(session,"<ip-address>","username","password")aspiko:awaitpiko.async_set_descriptors([(NAME,"<new-name>")])asyncio.run(asnyc_main())(back to top)ContributingContributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make aregreatly appreciated.If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
Don't forget to give the project a star! Thanks again!Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature')Push to the Branch (git push origin feature/AmazingFeature)Open a Pull Request(back to top)LicenseDistributed under the MIT License. SeeLICENSEfor more information.(back to top)ContactFlorian Schmidt -floriansch7843@gmail.comProject Link:https://github.com/Florian7843/pykostalpiko(back to top)Acknowledgmentspykostal(back to top)
Package: pykov-eft
Work In ProgressThis is an API, written in Python, for Escape From Tarkov based on dank's work:https://github.com/dank/tarkovThe main goal of this API is to provide simple and concise methods for retrieving various information from the Escape From Tarkov REST API in Python. Most methods will return a Python dictionary with requested information.LoginLogin with two-factor authentication is supported, but the user will need to manually enter the authentication code when prompted. Captcha bypass is possible thanks to Cosmos3904https://github.com/Cosmo3904/Recaptcha-Harvester-V2Notes For Captcha:To bypass the Captcha you will need to download ChromeDriver first and then add it to your system's pathhttps://sites.google.com/a/chromium.org/chromedriver/downloadsFeatures so far include:Automatic version updating upon launch, with functions to update as neededRetrieval of information like items, traders, and profilesEasy to use JSON in Python's dictionary formatPip PackageThere is currently a pip package available usingpip install pykov-eft. Please note that the package may not be as up-to-date as this repository.Requires Flask and selenium.ExampleA basic example is included under example.py, along with the example_get_all_items.txt file that it produces. More example usage will be provided in the future.UNOFFICIALThis project is not affiliated to BattleState Games or Escape From Tarkov in any way.
Package: pykqml
PyKQMLPyKQML is an implementation of KQML messaging in Python.InstallationPyKQML can be installed aspip install pykqmlNote that releases of PyKQML up to 0.5 work in Python 2 only, whereas
releases above and including 1.0 work in Python 3 only.To install for Python 2, use:pip install pykqml==0.5To install for Python 3 (or force an upgrade to a compatible version),
usepip install "pykqml>0.5"UsagePyKQML implements the following KQML classes, which allow constructing
and manipulating KQML messages programmatically:KQMLToken
KQMLString
KQMLQuotation
KQMLList
KQMLPerformative
KQMLReader
KQMLDispatcher
KQMLModuleYou can import KQML classes as, for instance,fromkqmlimportKQMLListYou can create a new KQML messaging agent in the context of the TRIPS
system asfromkqmlimportKQMLModuleclassMyAgent(KQMLModule):name="MyAgent"# This is the name of the agent to register withdef__init__(self,**kwargs):# Call the parent class' constructor which sends a registration# message, setting the agent's name to be recognized by the# Facilitator.super(MyAgent,self).__init__(name=self.name,**kwargs)# Subscribe to REQUESTs of interest. The list will change# depending on the role of the agentforreqin('what-next','commit','evaluate'):self.subscribe_request(req)# Subscribe to TELLs of interest if needed. This list will change# depending on the role of the agentfortellin('log-speechact',):self.subscribe_tell(tell)# Now signal that the agent is ready to receive messagesself.ready()# Finally, start the listener for incoming messagesself.start()defreceive_request(self,msg,content):# First, figure out what kind of request this istask=content.head().upper()# Here you typically decide what to do based on the# type of request.# Construct reply message's contentreply_content=KQMLList()# Set whatever needs to be set in the reply content# Finally, wrap the content in a message and replyreply_msg=KQMLPerformative('reply')reply_msg.set('content',reply_content)self.reply(msg,reply_msg)TestingYou can run all tests by runningnosetestsin the top level folder.
Package: pykrack
pyKrackInstallDue to the comparisons with the R packagesnawe recommend using conda
to manage your environment.First create the pykrack conda environment from the environment.yml
file:conda(ormamba)envcreate-fenvironment.ymlThen load the conda environment with:condaactivatepykrackAnd finally install the package from pip via the following command:pipinstallpyKrackAlternatively pyKrack can also be isntalled using pip via the following
commandpipinstallpyKrackThen install the R dependencies listed in the conda environmnet.yml
manually.How to usePlease see the core and hierarchy notebooks for more detailed
explanations.pyKrackconsists of one main function,compute_hierarchy.sourcecompute_hierarchycompute_hierarchy (G, metric='pykrack')Compute one of the possible hierarchy scoresTypeDefaultDetailsGDirected NetworkX graphmetricstrpykrackType of hierarchy metric to compute. Accepted types are:‘pykrack’ for this module’s implementation of the Krackhardt score.‘rsnakrack’ for the sna implementation in R.‘hierarchy_flow’ for the Luo and Magee 2011 as implemented in the NetworkX package.ReturnsfloatOne of the possible hierarchy scores
Package: pykraken
pykrakenpython implementation ofhttps://www.kraken.com/APIFree software: ISC licenseDocumentation:https://pykraken.readthedocs.org.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2016-05-28)First release on PyPI.
Package: py-kraken
py-krakenA python module to download files from KrakenFilesInstallpip install py-krakenCommand Line Usekraken-download https://krakenfiles.com/view/dbe8ee9c34/file.htmlModule UsefrompykrakenimportKrakenkraken_link="https://krakenfiles.com/view/dbe8ee9c34/file.html"# Download the file to local directoryk=Kraken()k.download_file(kraken_link)# Convert the kraken link to a download linkdownload_link=k.get_download_link(kraken_link)print(download_link)# 'https://krakenfiles.com/force-download/YXNkejUzNERTZmRzU0RGY3YzMmRiZThlZTljMzR8MTYxNTA3MDkyNA?fileHash=dbe8ee9c34'