Saravanan666/pypi-org huggingface dataset:
Package: whylabs-client
whylabs-clientWhyLabs API that enables end-to-end AI observabilityThis Python package is automatically generated by theOpenAPI Generatorproject:API version: 0.1Build package: org.openapitools.codegen.languages.PythonClientCodegen
For more information, please visithttps://whylabs.aiRequirements.Python >= 3.6Installation & Usagepip installYou can install directly using:pipinstallwhylabs-clientThen import the package:importwhylabs_clientSetuptoolsInstall viaSetuptools.pythonsetup.pyinstall--user(orsudo python setup.py installto install the package for all users)Then import the package:importwhylabs_clientGetting StartedPlease follow theinstallation procedureand then run the following:importtimeimportwhylabs_clientfrompprintimportpprintfromwhylabs_client.apiimportdataset_profile_apifromwhylabs_client.model.delete_analyzer_results_responseimportDeleteAnalyzerResultsResponsefromwhylabs_client.model.delete_dataset_profiles_responseimportDeleteDatasetProfilesResponsefromwhylabs_client.model.reference_profile_item_responseimportReferenceProfileItemResponse# Defining the host is optional and defaults to http://localhost# See configuration.py for a list of all supported configuration parameters.configuration=whylabs_client.Configuration(host="https://api.whylabsapp.com")# The client must configure the authentication and authorization parameters# in accordance with the API server security policy.# Examples for each auth method are provided below, use the example that# satisfies your auth use case.# Configure API key authorization: ApiKeyAuthconfiguration.api_key['ApiKeyAuth']='YOUR_API_KEY'configuration.discard_unknown_keys=True# Uncomment below to setup prefix (e.g. Bearer) for API key, if needed# configuration.api_key_prefix['ApiKeyAuth'] = 'Bearer'# Enter a context with an instance of the API clientwithwhylabs_client.ApiClient(configuration)asapi_client:# Create an instance of the API classapi_instance=dataset_profile_api.DatasetProfileApi(api_client)org_id="org-123"# str | Your company's unique organization IDdataset_id="model-123"# str | The unique dataset ID in your company.start_timestamp=1577836800000# int, none_type | Optional, scope deleting analyzer results more recent than the timestamp (optional)end_timestamp=1893456000000# int, none_type | Optional, scope deleting analyzer results older than the timestamp (optional)try:# Deletes a set of analyzer resultsapi_response=api_instance.delete_analyzer_results(org_id,dataset_id,start_timestamp=start_timestamp,end_timestamp=end_timestamp)pprint(api_response)exceptwhylabs_client.ApiExceptionase:print("Exception when calling DatasetProfileApi->delete_analyzer_results:%s\n"%e)
Package: whylabs-datasketches
# Python Wrapper for Datasketches## InstallationThe release files do not include the needed python binding library ([pybind11](https://github.com/pybind/pybind11)). If building
from a relase package, you must ensure that the pybind11 directory points to a local copy of pybind11.An official pypi build is eventually planned but not yet available.If you instead want to take a (possibly ill-advised) gamble on the current state of the master branch being useable, you can run:`pip installgit+https://github.com/apache/datasketches-cpp.git`## Developer Instructions### BuildingWhen cloning the source repository, you should include the pybind11 submodule with the–recursiveoption to the clone command:` git clone--recursivehttps://github.com/apache/datasketches-cpp.gitcddatasketches-cpppython-mpip install--upgradepip setuptools wheel numpy python setup.py build `If you cloned without–recursive, you can add the submodule post-checkout usinggit submodule update –init –recursive.### InstallingAssuming you have already checked out the library and any dependent submodules, install by simply replacing the lsat
line of the build command withpython setup.py install.### Unit testsThe python tests are run withtox. To ensure you have all the needed packages, from the package base directory run:` python-mpip install--upgradepip setuptools wheel numpy tox tox `## UsageHaving installed the library, loading the Datasketches library in Python is simple:import datasketches.## Available Sketch ClassesKLLkll_ints_sketchkll_floats_sketchFrequent Itemsfrequent_strings_sketchError types arefrequent_items_error_type.{NO_FALSE_NEGATIVES | NO_FALSE_POSITIVES}Thetaupdate_theta_sketchcompact_theta_sketch(cannot be instantiated directly)theta_uniontheta_intersectiontheta_a_not_bHLLhll_sketchhll_unionTarget HLL types aretgt_hll_type.{HLL_4 | HLL_6 | HLL_8}CPCcpc_sketchcpc_unionVarOpt Samplingvar_opt_sketchvar_opt_unionVector of KLLvector_of_kll_ints_sketchesvector_of_kll_floats_sketches## Known Differences from C++The Python API largely mirrors the C++ API, with a few minor exceptions: The primary known differences are that Python on modern platforms does not support unsigned integer values or numeric values with fewer than 64 bits. As a result, you may not be able to produce identical sketches from within Python as you can with Java and C++. Loading those sketches after they have been serialized from another language will work as expected.The Vector of KLL object is currently exclusive to python, and holds an array of independent KLL sketches. This is useful for creating a set of KLL sketches over a vector and has been designed to allow input as either a vector or a matrix of multiple vectors.We have also removed reliance on a builder class for theta sketches as Python allows named arguments to the constructor, not strictly positional arguments.
Package: whylabs-toolkit
WhyLabs ToolkitThe WhyLabs Toolkit package contains helper methods to help users interact with our internal APIs. Users will benefit from using it if they want to abstract some of WhyLabs' internal logic and also automate recurring API calls.Basic usageTo start using thewhylabs_toolkitpackage, install it from PyPI with:pipinstallwhylabs_toolkitPackagesThe available packages that we have enable different use-cases for thewhylabs_toolkit. To get started, navigate to one of the following sections and find useful tutorials there.PackageUsageMonitor ManagerAuthor and modify existing WhyLabs monitor with PythonWhyLabs HelpersInteract with and modify your Datasets and ML Models specs in WhyLabs.DevelopmentTo start contributing, you will manage dependencies withPoetryand also a handful ofMakefilecommands. To install all necessary dependencies and activate the virtual environment, run:makesetup&&poetryshellGet in touchIf you want to learn more how you can benefit from this package or if there is anything missing, pleasecontact our support, we'll be more than happy to help you!
Package: whylog
whylogThis is an library to print color-coded log messages to the terminal. It prints in the following format.TIME [LOG TYPE] (file names) > (path of the call|line no): Message.Log LevelsPrint or Save to a log file.Log LevelLog TypePrint ColorBackground Color0EmergencyBlackRed1AlertBlackYellow2CriticalBlackMagenta3ErrorRedNo Color4WarningYellowNo Color5NoticeWhiteBlue6InformationalWhiteNo Color7DebugCyanNo Color8NoneNANAUsageCodefromwhylogimportLogdefmain():test()deftest():log=Log(loglevel=8)log.emergency('Test emergency Print by importing')log.alert('Test alert Print by importing')log.critical('Test crtical Print by importing')log.error('Test error Print by importing')log.warning('Test warning Print by importing')log.notice('Test notice Print by importing')log.debug('Test Debug Print by importing')log.info('Test info Print by importing')if__name__=='__main__':main()Output
Package: whylogs
The open standard for data loggingDocumentation•Slack Community•Python Quickstart•WhyLabs QuickstartWhat is whylogswhylogs is an open source library for logging any kind of data. With whylogs, users are able to generate summaries of their datasets (calledwhylogs profiles) which they can use to:Track changes in their datasetCreatedata constraintsto know whether their data looks the way it shouldQuickly visualize key summary statistics about their datasetsThese three functionalities enable a variety of use cases for data scientists, machine learning engineers, and data engineers:Detect data drift in model input featuresDetect training-serving skew, concept drift, and model performance degradationValidate data quality in model inputs or in a data pipelinePerform exploratory data analysis of massive datasetsTrack data distributions & data quality for ML experimentsEnable data auditing and governance across the organizationStandardize data documentation practices across the organizationAnd moreQuickstartInstall whylogs using the pip package manager in a terminal by running:pip install whylogsThen you can log data in python as simply as this:importwhylogsaswhyimportpandasaspddf=pd.read_csv("path/to/file.csv")results=why.log(df)And voilà, you now have a whylogs profile. To learn more about what a whylogs profile is and what you can do with it, check out ourdocsand ourexamples.
Package: whyshift
WhyShift: A Benchmark with Specified Distribution Shift PatternsJiashuo Liu*,Tianyu Wang*,Peng Cui,Hongseok NamkoongTsinghua University, Columbia UniversityWhyShiftis a python package that provides a benchmark with various specified distribution shift patterns on real-world tabular data. And tools to diagnose performance degradation are integrated in it, including performance degradation decomposition and risky region identification. Our testbed highlights the importance of future research that builds an understanding of how distributions differ. For more details, please refer to ourpaper.If you find this repository useful in your research, please cite the following paper:@inproceedings{liu2023need,
  title={On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets},
  author={Jiashuo Liu and Tianyu Wang and Peng Cui and Hongseok Namkoong},
  booktitle={Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
  year={2023}
}For settings utilizing ACS Income, Public Coverage, Mobility datasetsget_data(task, state, year, need_preprocess, root_dir)functiontaskvalues: 'income', 'pubcov', 'mobility'examples:fromwhyshiftimportget_data# for ACS IncomeX,y,feature_names=get_data("income","CA",True,'./datasets/acs/',2018)# for ACS Public CoverageX,y,feature_names=get_data("pubcov","CA",True,'./datasets/acs/',2018)# for ACS MobilityX,y,feature_names=get_data("mobility","CA",True,'./datasets/acs/',2018)supportstatevalues:['AL', 'AK', 'AZ', 'AR', 'CA', 'CO', 'CT', 'DE', 'FL', 'GA', 'HI', 'ID', 'IL', 'IN', 'IA', 'KS', 'KY', 'LA', 'ME', 'MD', 'MA', 'MI', 'MN', 'MS', 'MO', 'MT', 'NE', 'NV', 'NH', 'NJ', 'NM', 'NY', 'NC', 'ND', 'OH', 'OK', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'UT', 'VT', 'VA', 'WA', 'WV', 'WI', 'WY', 'PR']For settings utilizing US Accident, Taxi datasetsdownload data files:# US Accident:https://www.kaggle.com/datasets/sobhanmoosavi/us-accidents# Taxihttps://www.kaggle.com/competitions/nyc-taxi-trip-durationput data files in dir./datasets/accident:./datasets/Accident/US_Accidents_Dec21_updated.csvtaxi:./datasets/Taxi/{city}_clean.csvpass thepath to the data fileofget_datafunctionexample:fromwhyshiftimportget_data# for US AccidentX,y,_=get_data("accident","CA",True,'./datasets/Accident/US_Accidents_Dec21_updated.csv')# for TaxiX,y,_=get_data("taxi","nyc",True,'./datasets/Taxi/train.csv')supportstatevalues:for US Accident:  ['CA', 'TX', 'FL', 'OR', 'MN', 'VA', 'SC', 'NY', 'PA', 'NC', 'TN', 'MI', 'MO']for Taxi: ['nyc', 'bog', 'uio', 'mex']
Package: whyslow
WhySlow 🐌Developer-friendly performance profiling utility for PythonWhySlowsimplifies the usage ofcProfileandsnakeviz. It offers the fastest way to get from slow code to flame chart and start the performance optimization investigations.Installationpip install whyslowUsageThere are three ways to use this profiler.As decorator to profile a function callfromwhyslowimportprofile@profile()defmy_slow_function():# do expensive operationsAs context manager to profile any codefromwhyslowimportprofilewithprofile():# some expensive operationsAs module to profile a script$python-mwhyslowmy-slow-script.pyLicenseMIT License
Package: whyylog
whylogThis is an library to print color-coded log messages to the terminal. It prints in the following format.TIME [LOG TYPE] (file names) > (path of the call|line no): Message.Log LevelsPrint or Save to a log file.Log LevelLog TypePrint ColorBackground Color0EmergencyBlackRed1AlertBlackYellow2CriticalBlackMagenta3ErrorRedNo Color4WarningYellowNo Color5NoticeWhiteBlue6InformationalWhiteNo Color7DebugCyanNo Color8NoneNANAUsageCodefromwhylogimportLogdefmain():test()deftest():log=Log(loglevel=8)log.emergency('Test emergency Print by importing')log.alert('Test alert Print by importing')log.critical('Test crtical Print by importing')log.error('Test error Print by importing')log.warning('Test warning Print by importing')log.notice('Test notice Print by importing')log.debug('Test Debug Print by importing')log.info('Test info Print by importing')if__name__=='__main__':main()Output
Package: wi1-bot
wi1-botA Discord bot to integrateRadarr&Sonarr, allowing commands like !addmovie and !downloads.UsageCopyconfig.yaml.templateto$XDG_CONFIG_HOME/wi1-bot/config.yamland set the necessary values.pip install wi1-bot(or from source:pip install git+https://github.com/wthueb/wi1-bot.git)wi1-botDevelopmentgit clone https://github.com/wthueb/wi1-bot.gitcd wi1-bot/pip install -e .[dev]pre-commit installRequires Python >=3.10.TODOhave config.discord.users be a dict with 'quotas' and 'name' for *arr tagsBetter pushover notificationsFailures for pretty much everythingNotifications for grabs/downloads of personal watchlistTag user who added movie when it's downloadedWould replace Radarr/Sonarr's Discord webhooks!notify <query> to also be tagged when a movie/show someone else added is downloadedreact to "added movie/show" instead of having to !notifyreact to notification to stop notificationsif user tries to add movie that's already present, add them to list to notifyWould require a DB; don't use tags as those are to strictly track quotasDB is useful for caching other information as wellUse Discord slash commands instead of normal text commandsThis is difficult/impossible currently, can't have "conversation" with slash commandsEnforce quotasTestingdocker(-compose) for spinning up Sonarr and Radarr instances to test API interactionsWeb dashboard for seeing transcode queue, transcode progress, quotas!linktmdb!rate / !ratings (https://developers.themoviedb.org/3/movies/rate-movie)!movierec based off of ratings and similar-to-user ratings?https://towardsdatascience.com/the-4-recommendation-engines-that-can-predict-your-movie-tastes-109dc4e10c52or just use TMDB's API to get recommendations (if that's possible?)!movieinfo showing user/public ratings and other general info (runtime, cast, director)use TMDB API to get movie metadataif movie isn't on Radarr, react to message to add it?Tautulli API (get_history) to show who has already seen the movieUser leaderboardmovies/shows added, Tautulli watch counts
Package: wialon
Wialon SDK for PythonInstallationUse the package managerpipto install wialon-python.pip3installwialonUsage"""WialonSDK example usage"""fromwialon.sdkimportWialonSdk,WialonError,SdkException# Initialize Wialon instancesdk=WialonSdk(is_development=True,scheme='https',host='hst-api.wialon.com',port=0,session_id='',extra_params={})try:token=''# If you haven't a token, you should use our token generator# https://goldenm.com/#/Resources/token-generatorresponse=sdk.login(token)print(response)parameters={'spec':{'itemsType':str,'propName':str,'propValueMask':str,'sortType':str,'propType':str,'or_logic':bool},'force':int,'flags':int,'from':int,'to':int}units=sdk.core_search_items(parameters)sdk.logout()exceptSdkExceptionase:print(f'Sdk related error:{e}')exceptWialonErrorase:print(f'Wialon related error:{e}')exceptExceptionase:print(f'Python error:{e}')Methods availableFor more information, please go toWialon Remote API documentationWork with us!Golden M is a software/hardware development company what is working on a new, innovative and disruptive technologies.
Fore more information, contact us atsales@goldenm.comContributingMerge requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.
Package: wialon-ips
DescriptionSimpleWialon IPsprotocol emulator.
Allows you to send Wialon IPs messages (with TCP or UDP) to any available network endpoint that accepts Wialon IPs protocol.After installing this package,wialon_ipsconsole script becomes available in OS-specific user directory.
Run this script to repeatedly send Wialon IPs messages to configurable endpoint with any interval.This tool supposed to provide facility for quick debugging and not intended to be advanced Wialon IPs emulation tool.
As soon as this tool just for debugging purposes, it is fully interactive, and does not support passing configuration as arguments.
All settings related to communication interactively asked when script runs.PresetsYou can choose to persist communication configuration for future uses: just save current configuration as preset when you will be prompted. All saved presets stored in tojson-filewialon_ips_presets.confliving in OS-specific user directory (/home/$USER/.local/share/wialon_ips/wialon_ips_presets.conffor Ubuntu Linux). It's not recommended to edit this file manually, but also not forbidden(format is quite intuitive) :)
To drop all your presets:wialon_ipsclearOS compatibility notesIt tested and works well under Ubuntu 18.04.
It wasn't tested under Windows or other Linux distributions, but unlikely any problems expected there: project structure follows recommendations fromofficial Python documentation about project packaging and distribution, and no platform-specific feautures used. Let me know if you will have issues.
Package: wi-analyzer
GKE Workload Identity AnalyzerThis script takes a Pod name (running in the current context) and performs checks to ensure thatWorkload Identityis properly configured.Performed checksWorkload Identity enabled on the GKE clusterPod has.spec.serviceAccountNameconfiguredKSA (configured in previous step) existsKSA is annotated correctly with a GSAGSA (configured in previous step) exists in the projectKSA hasroles/iam.workloadIdentityUseron the GSAGSA IAM roles in the projectPrerequisitesgcloudcliinstalled and configuredApplication Default Credentials generatedusing gcloudkubectlinstalled and configured with cluster accesscurrent kubectl contextpointing to the relevant clusterpython 3 andpipinstalledif running from source, python requirements installed:pip install -r requirements.txtInstallationThis package is published toPyPIand can be installed usingpip:pipinstallwi-analyzerNecessary project accessThe script can be run by a user with theViewerrole in the project.Alternatively, the user will need enough GKE cluster access to read Pods and ServiceAccounts, plus the following IAM permissions:container.clusters.getiam.serviceAccounts.getiam.serviceAccounts.getIamPolicyresourcemanager.projects.getIamPolicyIf the GSA is in a different GCP project than the GKE cluster, you'll need the last 3 permissions on that project instead.Using the tool$wi-analyzer--help
usage:wi-analyzer[-h][-nNAMESPACE][-d]pod

GKEWorkloadIdentityAnalyzer

positionalarguments:podKubernetesPodnametocheck

options:-h,--helpshowthishelpmessageandexit-nNAMESPACE,--namespaceNAMESPACEKubernetesNamespacetorunin-pPROJECT,--projectPROJECTGCPProjectholdingthecluster-lLOCATION,--locationLOCATIONTheGCPlocationofthecluster-cCLUSTER,--clusterCLUSTERThenameofthecluster-d,--debugEnabledebugloggingConfigure your current context to point at the cluster where the workload is running.
Either configure the relevantnamespace for the current contextor pass the namespace name using the-nflag.Pass a pod name to check - it can be part of a Deployment, Job, StatefulSet, etc, but it has to be running already.TODOSupportFleet Workload Identity(GKE WI for Anthos)
Package: wibble
Wibble - a template for simple python packagesA minimalist template for a python package.Provides the bl and the blarg commands,
and does basic continuous integraton testing on github.Make a copy of the project, and fix the replacements below.Things to replacegrep -ri word .will find thewordin all the filesfind . | grep wordwill find thewordin any filenamesretospect- changed to your github user namewibble- change to the name of your projectwobble- change to the internal package name you want to usefafa- change to whatever your commandline command should be if you are providing a scriptupdate the pyproject.py file to have your name and the right description.
Package: wibblywobbly
WibblyWobblyPython library to create equivalence dictionaries between a set of texts and a catalog using FuzzyWuzzy.It is a common nightmare for data scientist, your human users captured the data according to a "catalog" but it is full of mistakes. WibblyWobbly automates the task of automatically matching the data to a catalog while allowing for manual review of suspicious cases and rejecting bad matches.RequirementsPython 3 or higherthe fuzzpython-Levenshtein (optional)unidecodepandas#InstalationUsing PIP via PyPIpip install wibblywobblyWibblyWobbly extends hefuzz, it is recomended to install python-Levenshtein toopip install thefuzz pip install python-LevenshteinUsageMatch data to a catalogImport wibblywobbly and load your data and catalog as list. If you are using pandas use.to_list().import wibblywobbly as ww catalog = ["Mouse", "Cat", "Dog", "Human"] data = ["mice",  "CAT ", "doggo", "PERSON", 999]WibblyWobbly compares the data to the catalog and returns the most likely options and a similarity score. If it cannot find a good match it will return the original data.It automaticaly accepts the catalog options that have a higher similarity score thanthr_acceptand rejects those that have a lower score thanthr_reject. This treshold values can be adjusted depending in the data quality. It ignores non-string values.By default it returns a pandas dataframe that can be saved as a csv or excel file.to_excel().ww.map_list_to_catalog(data, catalog, thr_accept=95, thr_reject=40)DataOption1Score1Option2Score2Option3Score30CATCat100NoneNaNNoneNaN1doggoDog90Mouse20.0Human0.02miceMouse44Cat29.0Human22.03PERSONPERSON0NoneNaNNoneNaN49999990NoneNaNNoneNaNWibblyWobbly can also return a dictionary with the best options. This dictionary can be used to clean a pandas dataframe with.replace()and.map().ww.map_list_to_catalog(data, catalog, output_format="dictionary"){'mice': 'mice', 999: 999, 'doggo': 'Dog', 'PERSON': 'PERSON', 'CAT ': 'Cat'}It is possible set areject_value.ww.map_list_to_catalog(data, catalog, output_format="dictionary", reject_value='Other'){'mice': 'Other', 999: 999, 'doggo': 'Dog', 'PERSON': 'Other', 'CAT ': 'Cat'}WibblyWobbly can also raise warnings of the suspicious values to facilitate visual inspection.ww.map_list_to_catalog(data, catalog, output_format="dictionary",  thr_accept=95, thr_reject=40,  warnings=True)WOBBLY: mice
Options: Mouse (44), Cat (29), Human (22)
WOBBLY: doggo
Options: Dog (90), Mouse (20), Human (0){'mice': 'Mouse', 999: 999, 'doggo': 'Dog', 'PERSON': 'PERSON', 'CAT ': 'Cat'}Versions0.2.0Now uses thefuzzRough clustering algorithmHierarchical dictionariesHappy New Year!0.1.0We are online!Basic operations to match list to catalogsThanksThethefuzzteam, you are amazing!Syatsfor helping with the hierarchical code.You see, most people think that time is a strict progression of cause to effect, but actually, from a non-linear, non-subjective point of view, it’s more like a big ball of... Wibbly-Wobbly... Timey-Wimey... stuff.The Doctor
Package: wibor-simulation
wibor-simulationSimulates the loan installments at different interest ratesFree software: MITDocumentation:https://wibor-simulation.readthedocs.ioFeaturessimulations of loan installment based on changing interest rate (WIBOR6M)wibor-simulationsimulation100000.000.05600.0025,0.0175,0.0270,0.0500,0.069CreditsThis package was created withCookiecutterand thezillionare/cookiecutter-pypackageproject template.