Saravanan666/pypi-org huggingface dataset:
Package: ansys-api-geometry
ansys-api-geometry gRPC Interface PackageThis repository provides the auto-generated gRPC Python interface files for
the Ansys Geometry Service.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-geometryBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-api-mapdl
ansys-api-mapdl gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
mapdl.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-mapdlOtherwise, see theBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.17was
Python 3.7, so to improve your build time, use Python 3.7 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-api-mechanical
ansys-api-mechanical gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
Mechanical.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-mechanicalOtherwise, see theBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.30was
Python 3.7, so to improve your build time, use Python 3.7 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-api-meshing-prime
Ansys Prime Server gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
Ansys Prime Server.  Contributions for this API will not be accepted.  Please
create an issue or discussion for questions or enhancements relating to this
project.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pipinstallansys-api-meshing-primeBuildTo build the gRPC packages, run:pipinstallbuild
python-mbuild.This will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.46was
Python 3.10, so to improve your build time, use Python 3.10 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with:pipinstalltwine
twineuploaddist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.1.2.gittagv0.1.2
gitpush--tags
Package: ansys-api-modelcenter
ansys-api-modelcentergRPC Interface Package.This repository provides the auto-generated gRPC Python interface files for the Ansys ModelCenter.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-modelcenterBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags.gitcheckoutrelease/{new_version}gitmergemain
-->Bumptheversion
gitpushorigin
gittagv{new_version}gitpushoriginv{{new_version}
Package: ansys-api-platform-instancemanagement
ansys-api-platform-instancemanagement gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
the Product Instance Management (PIM) API.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with this command:pip install ansys-api-platform-instancemanagementBuildTo build the gRPC packages, run this command:python -m buildThe preceding command creates both the source distribution containing only the PROTO files
and the wheel containing the PROTO files and build Python interface files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.17was
Python 3.7. To improve your build time, use Python 3.7 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with these commands:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. These commands provides an example for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-api-pyensight
ansys-api-pyensight gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
PyEnSight. It also contains the xml stubs for the automated generation of the
ensight module in PyEnSight.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-pyensightOtherwise, see theBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.17was
Python 3.8, so to improve your build time, use Python 3.8 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-api-sherlock
ansys-api-sherlock gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
Sherlock.InstallationProvided that wheels have been published to public PyPI, you can install the latest package
with this command:pip install ansys-api-sherlockOtherwise, in the PySherlock documentation, see the instructions for downloading and installing
this package inInstall packages <https://sherlock.docs.pyansys.com/version/dev/getting_started/installation.html>_.Build packagesTo build the gRPC packages, run these commands:pip install build
python -m buildThe preceding commands create both the source distribution containing only the PROTO files
and the wheel containing the PROTO files and build Python interface files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.17was
Python 3.7. To improve your build time, use Python 3.7 when building the
wheel.Manual deploymentAfter building the packages, manually deploy them with these commands:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic deploymentThis repository contains a.githubdirectory with theci.ymlworkflow
file. This file uses GitHub Actions to automatically build the
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure that your branch is up to date and then
push tags. For example, to push tags for versionv0.5.0, you would use these commands:gittagv0.5.0
gitpush--tags
Package: ansys-api-systemcoupling
ansys-api-systemcoupling gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
System Coupling.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-systemcouplingBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.30was
Python 3.7, so to improve your build time, use Python 3.7 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-api-tools-filetransfer
ansys-api-tools-filetransfer gRPC Interface PackageThis Python package contains the auto-generated gRPC Python interface files for
the filetransfer tool.InstallationProvided that these wheels have been published to public PyPI, they can be
installed with:pip install ansys-api-tools-filetransferBuildTo build the gRPC packages, run:pip install build
python -m buildThis will create both the source distribution containing just the protofiles
along with the wheel containing the protofiles and build Python interface
files.Note that the interface files are identical regardless of the version of Python
used to generate them, but the last pre-built wheel forgrpcio~=1.17was
Python 3.7, so to improve your build time, use Python 3.7 when building the
wheel.Manual DeploymentAfter building the packages, manually deploy them with:pip install twine
twine upload dist/*Note that this is automatically done through CI/CD.Automatic DeploymentThis repository contains GitHub CI/CD that enables the automatic building of
source and wheel packages for these gRPC Python interface files. By default,
these are built on PRs, the main branch, and on tags when pushing. Artifacts
are uploaded for each PR.To publicly release wheels to PyPI, ensure your branch is up-to-date and then
push tags. For example, for the versionv0.5.0.gittagv0.5.0
gitpush--tags
Package: ansys-dpf-composites
PyDPF Composites enables the post-processing of composite structures based onAnsys DPFand the DPF Composites plugin. So it is a Python wrapper which
implements classes on top of DPF Composites operators and data accessors for
short fiber and layered composites (layered shell and solid elements). This
module can be used to postprocess fiber reinforced plastics and layered
composites, and to implement custom failure criteria and computation. For
information demonstrating the behavior and usage of PyDPF Composites,
seeExamplesin the DPF Composite documentation.ContributeInstall in development modeInstalling PyDPF Composites in development mode allows
you to modify the source and enhance it.Before attempting to contribute to PyDPF Composites, ensure that you are thoroughly
familiar with thePyAnsys Developer’s Guide.Clone the repository:gitclonehttps://github.com/ansys/pydpf-compositescdpydpf-compositesInstall dependencies:python-mpipinstallpipxpipxensurepath# Minimum required poetry version is 1.2.0pipxinstallpoetrypipxinstallpippipxinstalltoxPyDPF Composites usesPoetryto manage the development environment.Create a virtual environment and install the package with the
development dependencies:poetryinstall--all-extrasActivate the virtual environment:poetryshellTestThere are different ways to run the PyDPF Composites tests, depending on how the DPF
server is started.Run tests with a Docker container:Follow the steps inGetting the DPF server Docker imageto get
and run the DPF docker image. Run the tests with the following commandpytest.--port50052Run tests with a DPF server started from the Ansys installer. The Ansys version must
be 2023 R2 or later.pytest.--ansys-path"C:\Program Files\Ansys Inc\v232"Run tests with a Docker container from Github (Ansys Internal only):dockerpullghcr.io/ansys/pydpf-composites:latestpytest.Build documentationFollow the description inGetting the DPF server Docker imageimage to get
and run the dpf docker image.On Windows, build the documentation with:tox-edoc-windowsOn Linux, build the documentation with:tox-edoc-linuxAnsys internal only: Build the docs with the latest container from Github:dockerpullghcr.io/ansys/pydpf-composites:latestdockerrun-d-p50052:50052-eANSYSLMD_LICENSE_FILE=1055@mylicserver-eANSYS_DPF_ACCEPT_LA=Yghcr.io/ansys/pydpf-composites:latesttox-edoc-windowsRun style checksThe style checks usepre-commitand can be run throughtox:tox-estyleThe style checks can also be configured to run automatically before eachgit commit:pre-commitinstallView documentationDocumentation for the latest stable release of PyDPF Composites is hosted atPyDPF Composites Documentation.In the upper right corner of the documentation’s title bar, there is an option
for switching from viewing the documentation for the latest stable release
to viewing the documentation for the development version or previously
released versions.
Package: ansys-dpf-gate
ansys-dpf-gate: DPF (Ansys Data Processing Framework) python helpers to call DPF C and gRPC APIsThis module is designed to provide helper APIs to call C functions from DPFClientAPI (.dll or .so)
from python.
DPFClientAPI is a dynamic library providing C APIs to create, access and modify DPF's objects "in process"
(sharing memory) and/or in "client/server" mode through gRPC. DPFClientAPI wraps and makes easier the switch
between the 2 modes of communication.To allow for backward compatibility with old DPF Servers (strictly older than Ansys 2022 R2), which didn't have a DPFClientAPI,
an implementation of ansys-dpf-capi functions is done with direct calls to ansys-grpc-dpf (dpf grpc python module which
directly communicates with DPF server).
Package: ansys-dpf-gatebin
ansys-dpf-gatebin: DPF (Ansys Data Processing Framework) C++ APIs librariesThis module is providing runtime OS dependent binaries dependencies for ansys-dpf-gate. The DPF APIs DPFClientAPI (.dll or .so) and Ans.Dpf.GrpcClient (.dll or .so) are packaged.DPFClientAPI is a dynamic library providing C APIs to create, access and modify DPF's objects "in process" (sharing memory) and/or in "client/server" mode through gRPC, using Ans.Dpf.GrpcClient.
Package: ansys-dyna-core
PyDYNAOverviewPyDYNA is a Pythonic package for providing a more convenient and complete way to
build an Ansys DYNA input deck, submit it to the Ansys LS-DYNA solver, and
finally postprocess the results.PyDYNA contains two submodules,ansys.dyna.core.preandansys.dyna.core.solverpre: This module provides highly abstracted APIs for creating and
setting up DYNA input decks. There are many classes supported, namely,
DynaMech, DynaIGA, DynaICFD, DynaSALE, DynaEM,DynaNVH, DynaMaterial,
DynaISPH, DynaICFD and DynaAirbag. Each of these classes can be used to generate
LS-DYNA keywords. Since these classes have high-level abstraction, each function call
generates groups of keywords needed to define an input in LS-DYNA.solver: This API provides features to interact directly with the Ansys LS-DYNA solver.
LS-DYNA is primarily a batch solver with very limited interactive capabilities, thesolverservice provides a way to push input files to the LS-DYNA solver, monitor the state
of the running job, change the value of a load curve and finally retrieve result files back from
the serverOnce you have results, you can use the Ansys Data Processing Framework (DPF),
which is designed to provide numerical simulation users and engineers
with a toolbox for accessing and transforming simulation data. DPF
can access data from Ansys solver files and from several files with neutral formats,
including CSV, HDF5, and VTK. Using DPF’s various operators,
you can manipulate and transform this data.Theansys-dpf-post packageprovides
a simplified Python interface to DPF, thus enabling rapid postprocessing
without ever leaving a Python environment. For more information on DPF-Post,
see theDPF-Post documentation.Documentation and issuesDocumentation for the latest stable release of PyDyna is hosted atPyDYNA documentation.For examples on how to use PyDYNA, seeExamplesin the PyDYNA documentation.In the upper right corner of the documentation’s title bar, there is an option for switching from
viewing the documentation for the latest stable release to viewing the documentation for the
development version or previously released versions.On thePyDYNA Issuespage, you can create issues to
report bugs and request new features. On thePyDYNA Discussionspage or theDiscussionspage on the Ansys Developer portal,
you can post questions, share ideas, and get community feedback.To reach the project support team, emailpyansys.core@ansys.com.LicensePyDYNA is licensed under the MIT license.PyDYNA makes no commercial claim over Ansys whatsoever. This library extends the functionality of
Ansys LS-DYNA by adding a Python interface to LS-DYNA without changing the core behavior or
license of the original software. The use of the interactive control of PyDYNA requires a legally
licensed local copy of LS-DYNA.For more information on LS-DYNA, see theAnsys LS-DYNApage on the Ansys website.
Package: ansys-edb-core
PyEDB-Core is a Python client for the Electronics Database (EDB), a format for storing
information describing designs for Ansys Electronic Desktop (AEDT). Using the PyEDB-Core API,
you can make calls to an EDB server that is running either locally or remotely.The EDB server can create, edit, read, and write EDB files to disk. These files can then be
read into AEDT and their designs simulated.Documentation and issuesDocumentation for the latest stable release of PyEDB-Core is hosted atPyEDB-Core documentation.
The documentation has five sections:Getting started: Describes
how to install PyEDB-Core in user mode.User guide: Describes how to
use PyEDB-Core.API reference: Provides API member descriptions
and usage examples.Examples: Provides examples showing
end-to-end workflows for using PyEDB-Core.Contribute: Describes how to install
PyEDB-Core in developer mode and how to contribute to this PyAnsys library.In the upper right corner of the documentation’s title bar, there is an option for switching from
viewing the documentation for the latest stable release to viewing the documentation for the
development version or previously released versions.On thePyEDB-Core Issuespage, you can create
issues to report bugs and request new features. When possible, use these issue templates:Bug report templateFeature request templateDocumentation issue templateExample request templateIf your issue does not fit into one of these categories, create your own issue.On theDiscussionspage on the Ansys Developer portal, you can post questions,
share ideas, and get community feedback.To reach the PyAnsys support team, emailpyansys.core@ansys.com.LicensePyEDB-Core is licensed under the MIT license.PyEDB-Core makes no commercial claim over Ansys whatsoever. The use of this Python client requires
a legally licensed copy of AEDT. For more information, see theAnsys Electronicspage on the Ansys website.