Saravanan666/pypi-org huggingface dataset:
Package: f3d
F3D - Fast and minimalist 3D viewerBy Michael Migliore and Mathieu Westphal.F3D (pronounced `/fɛd/`) is a fast and minimalist 3D viewer desktop application. It supports many file formats, from digital content to scientific datasets (including glTF, USD, STL, STEP, PLY, OBJ, FBX, Alembic), can show animations and support thumbnails and many rendering and texturing options including real time physically based rendering and raytracing.It is fully controllable from the command line and support configuration files. It can provide thumbnails, support interactive hotkeys, drag&drop and integration into file managers.F3D also contains the libf3d, a simple library to render meshes, with C++ and Python Bindings, as well as experimental Java and Javascript bindings.A typical render by F3DAnimation of a glTF file within F3DA direct scalars render by F3DSee thegalleryfor more images, take a look at thechangelogor go to theinstall guideto download and install F3D!If you need any help or want to discuss with other F3D users and developers, head over to ourdiscord.QuickstartOpen a file and visualize it interactively:f3d /path/to/file.extOpen a file and save the rendering into an image file:f3d /path/to/file.ext --output=/path/to/img.pngGet help:f3d --help
man f3d # Linux onlyDocumentationTo get started, please take a look at theuser documentation.If you need any help, are looking for a feature or found a bug, please open anissue.If you want to use the libf3d, please take a look at itsdocumentation.If you want to build F3D, please take a look at thedeveloper documentation.SupportF3D is developed by a team of passionate devs. Please use F3D, star it on github or even become asponsorto support us!ContributingWe envision F3D as a community-driven project, we love to see how the project is growing thanks to the contributions from the community. We would love to see your face in the list below! If you want to contribute to F3D, you are very welcome to! Take a look at ourcontribution documentation.AcknowledgmentsF3D was initially created byKitware SASand is relying on many awesome open source projects, includingVTK,OCCT,Assimp,Alembic,Draco,OpenUSD,OpenVDBandOSPRay.LicenseF3D can be used and distributed under the 3-Clause BSD License, see thelicense.
F3D integrate the sources of other libraries and tools, all under permissive licenses, see thethird party licenses.
F3D packages relies on other libraries and tools, all under permissive licenses, all listed in the respective packages.
Package: f3dasm
f3dasmFramework for data-driven design & analysis of structures and materialsDocs|Installation|GitHub|PyPI|Practical sessionsSummaryWelcome tof3dasm, a Python package for data-driven design and analysis of structures and materials.AuthorshipCurrent created and developer:M.P. van der Schelling(M.P.vanderSchelling@tudelft.nl)The Bessa research group at TU Delft is small... At the moment, we have limited availability to help future users/developers adapting the code to new problems, but we will do our best to help!Getting startedThe best way to get started is to follow theinstallation instructions.ReferencingIf you use or edit our work, please cite at least one of the appropriate references:[1] Bessa, M. A., Bostanabad, R., Liu, Z., Hu, A., Apley, D. W., Brinson, C., Chen, W., & Liu, W. K. (2017). A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality. Computer Methods in Applied Mechanics and Engineering, 320, 633-667.[2] Bessa, M. A., & Pellegrino, S. (2018). Design of ultra-thin shell structures in the stochastic post-buckling range using Bayesian machine learning and optimization. International Journal of Solids and Structures, 139, 174-188.[3] Bessa, M. A., Glowacki, P., & Houlder, M. (2019). Bayesian machine learning in metamaterial design: fragile becomes super-compressible. Advanced Materials, 31(48), 1904845.[4] Mojtaba, M., Bostanabad, R., Chen, W., Ehmann, K., Cao, J., & Bessa, M. A. (2019). Deep learning predicts path-dependent plasticity. Proceedings of the National Academy of Sciences, 116(52), 26414-26420.Community SupportIf you find anyissues, bugs or problemswith this template, please use theGitHub issue trackerto report them.LicenseCopyright 2023, Martin van der SchellingAll rights reserved.This project is licensed under the BSD 3-Clause License. SeeLICENSEfor the full license text.
Package: f3dasm-optimize
f3dasm_optimizeOptimization extension package for the framework for data-driven design & analysis of structures and materialsDocs|Installation|GitHub|PyPI|Practical sessionsSummaryWelcome tof3dasm_optimize, an optimization extension Python package for data-driven design and analysis of structures and materials.AuthorshipCurrent created and developer:M.P. van der Schelling(M.P.vanderSchelling@tudelft.nl)The Bessa research group at TU Delft is small... At the moment, we have limited availability to help future users/developers adapting the code to new problems, but we will do our best to help!Getting startedThe best way to get started is to follow theinstallation instructionsof thef3dasmpackage.ReferencingIf you use or edit our work, please cite at least one of the appropriate references:[1] Bessa, M. A., Bostanabad, R., Liu, Z., Hu, A., Apley, D. W., Brinson, C., Chen, W., & Liu, W. K. (2017). A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality. Computer Methods in Applied Mechanics and Engineering, 320, 633-667.[2] Bessa, M. A., & Pellegrino, S. (2018). Design of ultra-thin shell structures in the stochastic post-buckling range using Bayesian machine learning and optimization. International Journal of Solids and Structures, 139, 174-188.[3] Bessa, M. A., Glowacki, P., & Houlder, M. (2019). Bayesian machine learning in metamaterial design: fragile becomes super-compressible. Advanced Materials, 31(48), 1904845.[4] Mojtaba, M., Bostanabad, R., Chen, W., Ehmann, K., Cao, J., & Bessa, M. A. (2019). Deep learning predicts path-dependent plasticity. Proceedings of the National Academy of Sciences, 116(52), 26414-26420.Community SupportIf you find anyissues, bugs or problemswith this template, please use theGitHub issue trackerto report them.LicenseCopyright 2023, Martin van der SchellingAll rights reserved.This project is licensed under the BSD 3-Clause License. SeeLICENSEfor the full license text.
Package: f3dasm-simulate
f3dasm_simulateAuthors:Martin van der Schelling (M.P.vanderSchelling@tudelft.nl)Authors afilliation:Bessa Research Group @ Delft University of TechnologyMaintainers:Martin van der Schelling (M.P.vanderSchelling@tudelft.nl)Jiaxiang Yi (J.Yi@tudelft.nl)Maintainer afilliation:Bessa Research Group @ Delft University of TechnologyFirst publication:June 19, 2023SummaryThis repository is an extension tof3dasm: Framework for data-driven design & analysis of structures and materials.
Package: f3wikidatabot
F3 Wikidata Botf3wikidatabot is a python module and command-line tool for thewikidata Forges project.Setupgitclone--recursivehttps://lab.forgefriends.org/friendlyforgeformat/f3-wikidata-bot.gitcdf3-wikidata-botecholayoutpython3>.envrc
direnvallow
pipinstallpoetry
poetryinstallUsageFrom the source tree:PYTHONPATH=$(pwd)pythonbin/f3wikidatabot--helpUsing the modulefrom PyPI:fromf3wikidatabotimportbotb=bot.Bot.factory(["--verbose","--show","--plugin","Features"])forforgeinb.run_query():print(forge)Publish$poetryconfigpypi-token.pypi{pypitoken}$poetryversionpatch
$poetrybuild
$poetrypublishLicenseThis project is licensed under the GPLv3+ License.FundingThis project is funded through theNGI Assure Fund, a fund established byNLnetwith financial support from the European Commission'sNext Generation Internetprogram. Learn more on theNLnet project page.
Package: f4enix
F4EnixParser for Monte Carlo simulations input and output filesPyhton >3.10!Both Windows and Linux supported.Go toF4Enix official documentationto get
more information on the library capabilities, examples and much more.InstallThe easiest way to install F4Enix is using pip:pip install f4enixTroubleshooting and developer modeIf any unexpected issue is encountered during installation, the first step for
its resolution would be to create a new fresh virtual environment.
In conda this would be done with:conda create -n <env_name> python=3.10Please remeber that python versions lower than 3.10 are not supported.Developer mode installationThere are many situations (especially while being an active developer) where it may be useful to install f4enix in developer mode. In order to do so, navigate to the
F4Eparser folder and type the following to be sure that your pip is
up to date (optional):python -m pip install --upgrade pip setuptools wheeland then to install the package:python3 -m pip install -e .This installation will only save the package info in your local environment
while it will point to your local folder to get the actual package code.
This means that when you have the package installed (i.e. that you can
use in whatever directory) you will still be able to modify the package
source code without the need for re-installing the package.This also means though that if you move the F4Eparser folder, the link will
be broken and you will need to reinstall the package. Anyhow, if you are
working on your local GitHub repo to modify the code (as it should be) this
should never be moved anyway.
Package: f4ratk
f4ratkA Fama/French Finance Factor Regression Analysis Toolkit.The deployed project is provided athttps://f4ratk.web.app.Here be dragonsThis project is experimental: it does not provide any guarantees and its
results are not rigorously tested. It should not be used by itself as a
basis for decision‐making.If you would like to join, please seeCONTRIBUTINGfor guidelines.FeaturesThe following lists some main use cases, this software can assist you.Analyze stock quotes of a ticker symbol.Analyze arbitrary performance data from file.Display historic factor returns.Estimate excess returns based on regression results.QuickstartInstallationObtain the latest released version of f4ratk using pip:pip install -U f4ratkUsageRun the program to see an interactive help. Note that each listed
command also provides an individual help.f4ratk --helpUsage: f4ratk [OPTIONS] COMMAND [ARGS]...

Options:
  -v, --verbose  Increase output verbosity.
  --about        Display program information and exit.
  --help         Show this message and exit.

Commands:
  convert    Convert files to the 'file' command format.
  file       Analyze a CSV file.
  history    Display historic factor returns.
  portfolio  Analyze a portfolio file.
  ticker     Analyze a ticker symbol.Adjust the program arguments according to your problem.
Then run your regression analysis similar to the following.Examplesf4ratk ticker USSC.L US USD
f4ratk file ./input.csv DEVELOPED EUR PRICE --frequency=MONTHLYLicenseThis project is licensed under the GNU Affero General Public License
version 3 (only). SeeLICENSEfor more information andCOPYINGfor the full license text.
Package: f5abtesting
A python package for region based abtesting.Installation Guide1. Install Python (if not has python installed)Download python 2.7: https://www.python.org/downloads/release/python-2712/Install Python 2.72. Install pipTo install pip, follow the link https://pip.pypa.io/en/latest/installing/Download get-pip.py, https://bootstrap.pypa.io/get-pip.pypython get-pip.py3. Install f5-sdkpip install f5-sdk4. Install f5abtestingpip install f5abtesting5. Patch f5-sdkCopy f5sdk_pool_patch.py to pool.py in f5-sdk package------------------------------------------------------------------2 configure files need for the initialization.ip2region.conf, input IP address to region mapping, here is an example:region1 10.0.0.0/24region1 10.10.2.0/24region2 10.20.2.0/24region2 10.30.0.0/24region3 10.40.2.0/24region3 10.50.2.0/24irules_tmp.conf, an irules for F5 BIG-IP to distribute traffic to B pool:# Replace ab_demo with the actual name of the virtual serverwhen CLIENT_ACCEPTED {set debug 1set vs_name_dg_ip2region ab_demo_dg_ip2regionset vs_name_dg_region2b ab_demo_dg_region2bset vs_name_pool_b ab_demo_pool_bset region_name [class lookup [IP::client_addr] $vs_name_dg_ip2region ]if {$debug} {log local0. "Client [IP::client_addr] accepted from $region_name, will be assigned to $vs_name_pool_b"}if { [class match $region_name equals $vs_name_dg_region2b]} {pool $vs_name_pool_bif {$debug} {log local0. "region $region_name is assigned to $vs_name_pool_b"}}}
Package: f5-admin
What is it?Release NotesHow Does It Work?Running Requirement?Working Examples?API DocumentsUnit TestingInstallationInstall from Python Package RepositoryBuild from SourceInstall from Build PackageVerify the InstallationTo DoWho is this guyLicenseWhat is it?I call it DIY F5 Security Administrators's Swiss Army knife. This is a simple python API built for F5 security administrators.I implemented the Python package in order to better understand and help manage my employer F5 infrastructure. Which has a whopping 32 nodes in total, and over half million running configuration lines when combined together as of this writing.Release NotesCheck outReleasesdocument for complete information.How Does It Work?The package provides a direct hook to theF5 TMOScommand line interface from your local workstation, by establishing a TTY connection via SSH as the privileged user. Once hooked, the security admin will be able to
manipulate F5 running configuration by using the standard TMOS commands.Furthermore, the security admin can go to the next level of the playing field, by custom buildout the  automation procedures in the full-stack capable, object-oriented Python programming language from there.Running Requirement?As of November 11 2019, you'll need Python 3 environment to run the package.The package is originally developed in Python 2.7 environment of my Macbooks Pro. Since Python 2 is depreciated end of 2019, the package is converted intoPython 3from version 1.1.16 onward. Note I have no plan to backward supporting 2.7.Checking your Python version with the command below:$python-VWorking Examples?Please refer to theutility examplesdocuments for the working examples.API DocumentsPlease refer toAPI, for complete information on how to use this API.Unit TestingUnit testsare written to ensure the quality of the code. It provides the assurance and sustainability of the project. Use the following command to run the tests:$cdf5-admin/
$python-munittestdiscovertests/InstallationsThere are several ways you can install the Python package in your favorite system.Install from Python Package Repository$pipinstallf5-adminBuild the Python Package from SourceOnce youdownload and unzipthe source code, find and run the rebuild.sh script under the source root directory:$pythonsetup.pysdistbdist_wheelInstall from Build PackageAfter the successful build, you'll also have the .gz package under 'dist' sub-folder.  You have the option to distribute it to other systems. And you can then install the software by using the Python standard package management toolpip.For example:$sudopipinstalldist/f5_admin-1.1.2.tar.gz
Password:
...
Successfullyinstalledf5-admin-1.1.2Verify the InstallationOnce installed, you'll be able to list it under your Python environment:$piplist|grepf5
f5-admin1.2.0To DoRefer toTODOdocument for complete list of expectations / project roadmap.Who is this guy?Sam (Yang) Li serves as the IT Security Architect in the infrastructure team. He is an information security veteran with 20 years hand-on experiences in the fields. You can connect him inLinkedIn.License
Package: f5-openstack-heat-plugins
IntroductionThis repository houses all of F5®’s OpenStack Heat resource plugins. F5’s Heat plugins can be used to orchestrate BIG-IP® services in your OpenStack environment.Releases and VersionsThis branch supports the OpenStack Kilo release.Please seeF5 OpenStack Releases, Versioning, and Support Matrixfor additional information about F5’s OpenStack plugins and BIG-IP compatibility.DocumentationProject documentation, which includes installation and usage instructions, can be found onRead The Docs.For DevelopersFiling IssuesIf you find an issue we would love to hear about it. Please let us know by filing an issue in this repository and tell us as much as you can about what you found and how you found it.ContributingSeeContributing.BuildTo make a PyPI package…pythonsetup.pysdistTestBefore you open a pull request, your code must have passingpytestunit tests. In addition, you should include a set of functional tests written to use a real BIG-IP device for testing. Information on how to run our set of tests is included below.Unit TestsWe use pytest for our unit tests.If you haven’t already, install the project requirements in your virtual environment.pipinstallhackingpytestpytest-covpipinstall-rrequirements.txtpipinstall-rrequirements.unit.test.txtRun the tests and produce a coverage report. The--cov-report=htmlwill create ahtmlcov/directory that you can view in your browser to see the missing lines of code.py.test--covf5_heat/resources/test--cov-report=htmlopenhtmlcov/index.htmlFunctional TestsPytest is also used for functional testsIf you haven’t already, install requirements.func.test.txt in your virtual environment.pipinstall-rrequirements.func.test.txtCurrently, you must modifytest/functional/test_variables.pyfile to provide the proper credentials to Openstack. See that file for more info on what is needed. Also remember not to include this file in your pull request, since it may contiain sensitive information.Run the functional tests and pass in arguments to connect to the F5 device.py.testtest/functional/--bigip=<bigip_ip>--bigip-username=<web_login_username>--bigip-passwword=<web_login_password>Style ChecksWe use the hacking module for our style checks (installed as part of step 1 in the Unit Test section).flake8./CopyrightCopyright 2015-2016 F5 Networks, Inc.SupportSeeSupport.LicenseApache V2.0Licensed 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, 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.Contributor License AgreementIndividuals or business entities who contribute to this project must
have completed and submitted theF5® Contributor License
AgreementtoOpenstack_CLA@f5.comprior to their code submission being included in this
project.
Package: f5project
F5 ProjectFinlab Fugle for financial freedom.QuickstartPipx (recommended)Usepipxto create your F5 project with a template and install all dependencies.cd~/repos
pipxrun--no-cachef5projectcreate-projectmy_f5projectcdmy_f5project
pipinstall-rrequirements.txtThen, follow these instructions to make it work:Put all your secrets in.secrets/index.jsonfileRunpython main.pyto see if it worksRunscripts/setup_github_secrets.pyto sync your secrets with Github secrets[Optional] Follow the instructions inscripts/setup_github_secrets.pyto make it a pre-push Git hookgit pushto deploy your code according to.github/workflows/main.ymlTraditional wayIf you don't feel like using pipx, you can also run this with traditional pip.cd~/repos
mkdirmy_f5projectcdmy_f5project
python3-mvenv.venvsource.venv/bin/activate
pipinstallf5project
f5projectf5projectcreate-project.
pipinstall-rrequirements.txtThen, follow these instructions to make it work:Put all your secrets in.secrets/index.jsonfileRunpython main.pyto see if it worksRunscripts/setup_github_secrets.pyto sync your secrets with Github secrets[Optional] Follow the instructions inscripts/setup_github_secrets.pyto make it a pre-push Git hookgit pushto deploy your code according to.github/workflows/main.ymlWhy?This library makes it easier to use Finlab/Fugle with GCF and CD/CD.When deploying your code on Cloud. Many troubles come up. This library helps you to solve them. Including:Read config from a simle JSON file or environment variables, depending on your environment.Extract Fugle config and certificate from config, dynamically generate them as needed, by-passing Fugle's restriction that only accepts files as input.Provide a decorator to make your function a GCF endpoint, without worrying about the request/response format.Simulate GCF request locally.Sync Github secrets with local config, make CI/CD easier.With all of these, you can focus on your trading strategy and iterate faster, letting this library handle the rest.
Package: f5tarea4primos
Este es un ejemplo simple de un paquete Python. Este  paquete implementa una funciÃ³n en Python para calcular los nÃºmeros primos entre 1 y n, donde n es un parÃ¡metro de la funciÃ³n.This program is free software: You can redistribute it and/or modify it under the terms of license by the Free Software Foundation, either version 3 of the License(at your option) any other version.
Package: f5-teem
IntroductionPython library providing an interface for F5's TEEM infrastructure to provide usage analytics to F5.Usage (Anonymous API)fromf5teemimportAnonymousDeviceClientclient_info={'name':'f5-example-product','version':'1.0.0','id':'<asset UUID>'}telemetry_client=AnonymousDeviceClient(client_info,api_key='<API KEY>')telemetry_client.report({'foo':'bar'},telemetry_type='Installation Usage',telemetry_type_version='1')By default, this library will include in the report telemetry client properties including:The type of Operating System where telemetry is sent from (for example, 'Linux')Example Telemetry Record{"digitalAssetName":"f5-example-product","digitalAssetVersion":"1.0.0","digitalAssetId":"<asset UUID>","documentType":"Installation Usage","documentVersion":"1","observationStartTime":"","observationEndTime":"","epochTime":"","telemetryId":"","telemetryRecords":[{"foo":"bar","telemetryClientProperties":{"os":"linux"}}]}Use TEEM staging environmentSet environment variableexportTEEM_API_ENVIRONMENT='staging'Additional NotesThis library is similar to the node-based f5-teem library (https://www.npmjs.com/package/@f5devcentral/f5-teem).Future Improvementsf5-teem-python should support Reg Key API when running on BIG-IP (similar to node based f5-teem library)f5-teem-python should honor the phone home setting when running on BIG-IP.tmsh modify sys software update auto-phonehome disabled
Package: f61d
📦 setup.py (for humans)This repo exists to providean example setup.pyfile, that can be used
to bootstrap your next Python project. It includes some advanced
patterns and best practices forsetup.py, as well as some
commented–out nice–to–haves.For example, thissetup.pyprovides a$ python setup.py uploadcommand, which creates auniversal wheel(andsdist) and uploads
your package toPyPiusingTwine, without the need for an annoyingsetup.cfgfile. It also creates/uploads a new git tag, automatically.In short,setup.pyfiles can be daunting to approach, when first
starting out — even Guido has been heard saying, "everyone cargo cults
thems". It's true — so, I want this repo to be the best place to
copy–paste from :)Check out the example!Installationcdyour_project# Download the setup.py file:#  download with wgetwgethttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.py-Osetup.py#  download with curlcurl-Ohttps://raw.githubusercontent.com/navdeep-G/setup.py/master/setup.pyTo DoTests via$ setup.py test(if it's concise).Pull requests are encouraged!More ResourcesWhat is setup.py?on Stack OverflowOfficial Python Packaging User GuideThe Hitchhiker's Guide to PackagingCookiecutter template for a Python packageLicenseThis is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any means.