Saravanan666/pypi-org huggingface dataset:
Package: chaosmagpy
OverviewChaosMagPy is a simple Python package for evaluating the CHAOS geomagnetic
field model and other models of Earth’s magnetic field. The latest CHAOS model
is available athttp://www.spacecenter.dk/files/magnetic-models/CHAOS-7/. To
quickly get started, download the complete working example including the latest
model under the “Forward code” section.DocumentationThe documentation of the current release is available on Read the Docs
(https://chaosmagpy.readthedocs.io/en/)CitationTo reference ChaosMagPy in publications, please cite the package itselfhttps://doi.org/10.5281/zenodo.3352398and some of the following:Finlay, C.C., Kloss, C., Olsen, N., Hammer, M. Toeffner-Clausen, L.,
Grayver, A and Kuvshinov, A. (2020), The CHAOS-7 geomagnetic field model and
observed changes in the South Atlantic Anomaly, Earth Planets and Space 72,
doi:10.1186/s40623-020-01252-9Finlay, C.C., Olsen, N., Kotsiaros, S., Gillet, N. and Toeffner-Clausen, L. (2016),
Recent geomagnetic secular variation from Swarm and ground observatories
as estimated in the CHAOS-6 geomagnetic field model Earth Planets Space,
Vol 68, 112. doi: 10.1186/s40623-016-0486-1Olsen, N., Luehr, H., Finlay, C.C., Sabaka, T. J., Michaelis, I., Rauberg, J. and Toeffner-Clausen, L. (2014),
The CHAOS-4 geomagnetic field model, Geophys. J. Int., Vol 197, 815-827,
doi: 10.1093/gji/ggu033.Olsen, N., Luehr, H., Sabaka, T.J., Mandea, M. ,Rother, M., Toeffner-Clausen, L. and Choi, S. (2006),
CHAOS — a model of Earth’s magnetic field derived from CHAMP, Ørsted, and SAC-C magnetic satellite data,
Geophys. J. Int., vol. 166 67-75InstallationChaosMagPy relies on the following (some are optional):python>=3.6numpyscipypandascythonh5pyhdf5storage>0.1.17matplotlib>=3pyshp>=2.3.1cdflib (optional)lxml (optional)Specific installation steps using the conda/pip package managers are as follows:Install packages with conda:>>> conda install python numpy scipy pandas cython pyshp matplotlib h5py lxmlInstall remaining packages with pip:>>> pip install cdflib hdf5storageFinally install ChaosMagPy either with pip from PyPI:>>> pip install chaosmagpyOr, if you have downloaded the distribution archives from the Python Package
Index (PyPI) athttps://pypi.org/project/chaosmagpy/#files, install
ChaosMagPy using the built distribution:>>> pip install chaosmagpy-x.x-py3-none-any.whlreplacingx.xwith the relevant version, or using the source
distribution:>>> pip install chaosmagpy-x.x.tar.gz
Package: chaosmeter
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              ▀ChaosMeterJava Metrics Calculator
(Currently supporting Mutant Density, Cyclomatic Complexity, and SLOC)Copyright (C) 2020 Ali ParsaiHow to Use:On your selected python platform use:pip3 install chaosmeterYou can use the program by executing it as a module:python3 -m chaosmeter [options]For a java project, all you need to do is to pass the required arguments to ChaosMeter:python3 -m chaosmeter  -p [path to source code] -t [path to target results]LicenseThis program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.You should have received a copy of the GNU General Public License
along with this program.  If not, seehttps://www.gnu.org/licenses/.Find me at:parsai.net
Package: chaosmonkey
Chaos Monkey EngineTheChaos Monkey Engine(CME) is a tool to orchestrate attacks to your cloud infrastructure in order to implement the principles ofChaos Engineering). It is inspired in the Netflix’sSimianArmybut built with these principles in mind:Multi-cloud (not only AWS) support through standards asApache Libcloudand SSHEase of extensibility to add your new attacks and plannersHALAPI interfaceThe CME is completely API-driven, so that it can be easily integrated with external and third-party systems.To try aquickstartor read more, please refer to thedocumentation).You can also find the last docker image build in thedockerhub.TODO:Improve testing quality & coverageExecutors and Plans trackingRight now we are only tracking if the plan or executor has been executed or not.
We need to track the state (executed, failed, pending…), possible logs and results.Load planners & attacks dynamically from APIPlanners and Attacks are dynamically loaded from the modules directories.
We need endpoints to upload attacks and planners modules to the modules directories.Historic of executionsKeep and historic and provide a way to query it.Contributing to Chaos Monkey EngineYou can contribute to Chaos Monkey Engine in a few different ways:Submit issues throughissue trackeron GitHub.If you wish to make code changes, or contribute something new, please follow theGitHub Forks / Pull requests model): Fork the chaos-monkey-engine repo, make the change and propose it back by submitting a pull request.Changelog1.1.0Add CHANGELOG
Package: chaosplatform
Chaos Platform - Chaos Engineering Platform for EveryoneThis is theChaos Platformmain project.ContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-account
Chaos Platform Account ServiceThis is the account service of theChaos Platform.PurposeProvide a REST api to manage users, organizations and workspacesProvide a gRPC api to manage registrations of new usersContentInstallConfigureRunContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-auth
Chaos Platform Authentication ServiceThis is the authentication service of theChaos Platform.PurposeProvide a REST api to manage access tokensProvide a gRPC api to manage access tokensProvide a web entrypoint to register a new user using an OAuth2 providerContentInstallConfigureRunContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-experiment
Chaos Platform Experiment and Execution ServiceThis is the experiment/execution service of theChaos Platform.PurposeProvide a REST api to manage experiment and their executionsContentInstallConfigureRunContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-grpc
Chaos Platform gRPC LibraryThis is the authentication service of theChaos Platform.PurposeProvide gRPC client stubs for the Chaos Platform servicesProvide gRPC server stubs for the Chaos Platform servicesContentInstallGeneratefrom the protobug definitionsContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-relational-storage
Chaos Platform Relational Database UtilityThis is the relational database utility for theChaos Platform.PurposeProvide a simple library to work with relational database throughSQLAlchemy. It's unlikely usable in any other context.ContentInstallConfigureUseContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-scheduler
Chaos Platform Authentication ServiceThis is the default scheduler service of theChaos Platform.PurposeProvide a gRPC api to schedule/cancel experiment executionsContentInstallConfigureRunContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaosplatform-scheduling
Chaos Platform Authentication ServiceThis is the scheduling service of theChaos Platform.PurposeProvide a REST api to schedule experiment executionsContentInstallConfigureRunContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined inPEP8. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.The Chaos Platform projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaospy
DocumentationInteractive tutorials with BinderCode of conductContribution guidelineChangelogLicenseChaospy is a numerical toolbox for performing uncertainty quantification using
polynomial chaos expansions, advanced Monte Carlo methods implemented in
Python. It also include a full suite of tools for doing low-discrepancy
sampling, quadrature creation, polynomial manipulations, and a lot more.The philosophy behindchaospyis not to be a single tool that solves every
uncertainty quantification problem, but instead be a specific tools to aid to
let the user solve problems themselves. This includes both well established
problems, but also to be a foundry for experimenting with new problems, that
are not so well established. To do this, emphasis is put on the following:Focus on an easy to use interface that embraces thepythonic code style.Make sure the code is “composable”, such a way that changing one part of the
code with something user defined should be easy and encouraged.Try to support a broad width of the various methods for doing uncertainty
quantification where that makes sense to involvechaospy.Make sure thatchaospyplays nice with a large set of of other other
similar projects. This includesnumpy,scipy,scikit-learn,statsmodels,openturns, andgstoolsto mention a few.Contribute all code to the community open source.InstallationInstallation should be straight forward frompip:pipinstallchaospyOr ifCondais more to your liking:condainstall-cconda-forgechaospyThen go over to thedocumentationto see how to use the toolbox.DevelopmentInstallingchaospyand its dependencies in developer mode is done as
follows:pipinstall-rrequirements-dev.txtpipinstall-e.TestingTo ensure that the code run on your local system, run the following:pytest--doctest-moduleschaospy/tests/README.rstDocumentationThe documentation build assumes thatpandocis installed on your
system and available in your path.To build documentation locally on your system, usemakefrom thedocs/folder:cddocs/makehtmlRunmakewithout argument to get a list of build targets.
The HTML target stores output to the folderdoc/.build/html.
Package: chaosrouter
Route path based requests to JSON endpoints.  Designed for web APIsUsage examplesfrom chaosrouter                  import ChaosRouter

router                            = ChaosRouter({
    "404": {
        "error": "Not Found",
        "message": "The page you are looking for does not exist",
        "code": 404
    }
})

Draft                             = router.route("/404")
data                              = Draft.proceed()

print(data)

# Output:
# {
#     "error": "Not Found",
#     "message": "The page you are looking for does not exist",
#     "code": 404
# }
Package: chaostoolkit
Chaos Toolkit - Chaos Engineering for All EngineersCommunity•Installation•Tutorials•Reference•ChangeLogChaos Toolkit - Chaos Engineering for All EngineersThe Chaos Toolkit, or as we love to call it “ctk”, is a simple
CLI-driven tool who helps you write and run Chaos Engineering experiment. It
supports any target platform you can think of throughexisting extensionsor
the ones you write as you need.Chaos Toolkit is versatile and works really well in settings where other Chaos
Engineering tools may not fit: cloud environments, datacenters, CI/CD, etc.Install or UpgradeProvided you have Python 3.8+ installed, you can install it as follows:$pipinstall-UchaostoolkitGetting StartedOnce you have installed the Chaos Toolkit you can use it through its simple command line tool.Running an experiment is as simple as:$chaosrunexperiment.jsonGet involved!Chaos Toolkit's mission is to provide an open API to chaos engineering in all its forms. As such, we encourage and welcome you  tojoinour open community Slack team to discuss and share your experiments and needs with the community.
You can also useStackOverflowto ask any questions regarding using the
Chaos Toolkit or Chaos Engineering.If you'd prefer not to use Slack then we welcome the raising of GitHub issues on this repo for any questions, requests, or discussions around the Chaos Toolkit.Finally you can always emailcontact@chaostoolkit.orgwith any questions as well.ContributeContributors to this project are welcome as this is an open-source effort that
seeksdiscussionsand continuous improvement.From a code perspective, if you wish to contribute, you will need to run a
Python 3.8+ environment. Please, fork this project, write unit tests to cover
the proposed changes, implement the changes, ensure they meet the formatting
standards set out byruff, add an entry intoCHANGELOG.md, and then raise a PR to the repository for reviewThe project is driven byPDM, so install it and you can run the
following commands:$pdminstall$pdmruntest$pdmrunformat$pdmrunlintThe Chaos Toolkit projects require all contributors must sign aDeveloper Certificate of Originon each commit they would like to merge
into the master branch of the repository. Please, make sure you can abide by
the rules of the DCO before submitting a PR.
Package: chaostoolkit-addons
Chaos Toolkit AddonsThis project provides a set of commnly requested actions, probes, tolerances
or controls that can benefit the community.InstallThis package requires Python 3.7+To be used from your experiment, this package must be installed in the Python
environment wherechaostoolkitalready lives.$ pip install chaostoolkit-addonsDevelopTestTo run the tests for the project execute the following:$ pytestContributeIf you wish to contribute more functions to this package, you are more than
welcome to do so. Please, fork this project, make your changes following the
usualPEP 8code style, sprinkling with tests and submit a PR for
review.
Package: chaostoolkit-chaoshub
# chaostoolkit-chaoshub[![Build Status](https://travis-ci.org/chaostoolkit-incubator/chaostoolkit-chaoshub.svg?branch=master)](https://travis-ci.org/chaostoolkit-incubator/chaostoolkit-chaoshub)The Chaos Hub plugin library.## PurposeThe purpose of this library is to provide [Chaos Hub][] collaboration and sharingsupport to the [Chaos Toolkit][chaostoolkit].[chaostoolkit]:http://chaostoolkit.org[chaoshub]:http://chaoshub.com## FeaturesThe library adds the ability to login to a Chaos Hub, by default [ChaosHub.com][chaoshub],
and then to be able to publish experiment’s and experimental findings into the hub.## InstallInstall this package as any other Python packages:` $ pip install-Uchaostoolkit-chaoshub`Notice that this draws a few [dependencies][deps]:[deps]:https://github.com/chaostoolkit-incubator/chaostoolkit-chaoshub/blob/master/requirements.txt## UsageOnce installed, newloginandpublishsubcommands will be made available to thechaoscommand. You can use them as follows:` $ chaos login `` $ chaos publish journal.json `Thelogincommand sets up your chaos toolkit installation to target a particular
Chaos Hub. Thechaos publishcommand enables you to manually push your experimental
findings, typically recorded in thejournal.json, to your Chaos Hub account.By default, once you have logged into your Chaos Hub you will automatically publish
your experiment’s findings to your own organization and workspace when you executechaos run. You can turn this behaviour off by specifying–no-publishas shown here:` $ chaos run experiment.json--no-publish`## ContributeContributors to this project are welcome as this is an open-source effort that
seeks [discussions][join] and continuous improvement.[join]:https://join.chaostoolkit.org/From a code perspective, if you wish to contribute, you will need to run a
Python 3.5+ environment. Then, fork this repository and submit a PR. The
project cares for code readability and checks the code style to match best
practices defined in [PEP8][pep8]. Please also make sure you provide tests
whenever you submit a PR so we keep the code reliable.[pep8]:https://pycodestyle.readthedocs.io/en/latest/### DevelopIf you wish to develop on this project, make sure to install the development
dependencies. But first, [create a virtual environment][venv] and then install
those dependencies.[venv]:http://chaostoolkit.org/reference/usage/install/#create-a-virtual-environment`console $ pip install-rrequirements-dev.txt-rrequirements.txt `Then, point your environment to this directory:`console $ python setup.py develop `Now, you can edit the files and they will be automatically be seen by your
environment, even when running from thechaoscommand locally.### TestTo run the tests for the project execute the following:` $ pytest `
Package: chaostoolkit-datadog
Chaos Toolkit Extension TemplateThis project contains Chaos Toolkit activities and tolerances to work
with DataDog.InstallThis package requires Python 3.7+To be used from your experiment, this package must be installed in the Python
environment wherechaostoolkitalready lives.$ pip install chaostoolkit-datadogUsageA typical experiment using this extension would look like this:{"version":"1.0.0","title":"Run a, experiment using a DataDog SLO to verify our system","description":"n/a","configuration":{"datadog_host":"https://datadoghq.eu"},"steady-state-hypothesis":{"title":"n/a","probes":[{"type":"probe","name":"read-slo","tolerance":{"type":"probe","name":"check-slo","provider":{"type":"python","module":"chaosdatadog.slo.tolerances","func":"slo_must_be_met","arguments":{"threshold":"7d"}}},"provider":{"type":"python","module":"chaosdatadog.slo.probes","func":"get_slo","arguments":{"slo_id":"..."}}}]},"method":[]}That's it!Please explore the code to see existing probes and actions.ConfigurationIn theconfigurationblock you may want to specify the DataDog host you are
targetting:"configuration":{"datadog_host":"https://datadoghq.eu"},The authentication can be set using the typical DataDog environment variables,
notably:DD_API_KEY: the API keyDD_APP_KEY: the application keyTestTo run the tests for the project execute the following:$ pytestFormatting and LintingWe use a combination ofblack,flake8, andisortto both lint and format this repositories code.Before raising a Pull Request, we recommend you run formatting against your
code with:$makeformatThis will automatically format any code that doesn't adhere to the formatting
standards.As some things are not picked up by the formatting, we also recommend you run:$makelintTo ensure that any unused import statements/strings that are too long, etc.
are also picked up.ContributeIf you wish to contribute more functions to this package, you are more than
welcome to do so. Please, fork this project, make your changes following the
usualPEP 8code style, sprinkling with tests and submit a PR for
review.