Saravanan666/pypi-org huggingface dataset:
Package: ansys-fluent-parametric
OverviewPyFluent-Parametric provides Pythonic access to Ansys Fluent’s parametric
workflows.Documentation and issuesFor comprehensive information on PyFluent-Parametric, see the latest
releasedocumentation.On thePyFluent-Parametric Issues,
you can create issues to submit questions, report bugs, and request new features. To reach
the project support team, emailpyansys.core@ansys.com.InstallationTheansys-fluent-parametricpackage currently supports Python 3.9 through Python
3.11 on Windows and Linux.Install the latest release fromPyPIwith:pip install ansys-fluent-parametricAlternatively, install the latest fromGitHubwith:pip install git+https://github.com/ansys/pyfluent-parametric.gitIf you plan on doing localdevelopmentof PyFluent with Git, install
with:git clone https://github.com/ansys/pyfluent-parametric.git
cd pyfluent-parametric
pip install pip -U
pip install -e .DependenciesYou must have a locally-installed, licensed copy of Ansys to run Fluent. The
first supported version is 2022 R2.Getting startedBasic usageThe following code assumes that a PyFluent session has already been created and a Fluent case
with input parameters has been set up. For a full example, seeDefining Parametric Workflowsin
the PyFluent-Parametric documentation.importansys.fluent.coreaspyfluentfromansys.fluent.parametricimportParametricStudysolver_session=pyfluent.launch_fluent(mode="solver")study=ParametricStudy(solver_session.parametric_studies)input_parameters_update=study.design_points["Base DP"].input_parametersinput_parameters_update["inlet1_vel"]=0.5study.design_points["Base DP"].input_parameters=input_parameters_updatestudy.update_current_design_point()print(study.design_points["Base DP"].output_parameters)License and acknowledgmentsPyFluent-Parametric is licensed under the MIT license.PyFluent-Parametric makes no commercial claim over Ansys whatsoever. This library
extends the functionality of Fluent by adding a Python interface to Fluent without
changing the core behavior or license of the original software. The use of the
interactive Fluent control of PyFluent-Parametric requires a legally licensed
local copy of Fluent.For more information, see theAnsys Fluent <https://www.ansys.com/products/fluids/ansys-fluent>page on the Ansys website.
Package: ansys-fluent-visualization
OverviewPyFluent-Visualization provides postprocessing and visualization
capabilities forPyFluentusingPyVistaandMatplotlib.Documentation and issuesFor comprehensive information on PyFluent-Visualization, see the latest releasedocumentation.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 thePyFluent Visualization Issuespage, you can create
issues to submit questions, reports burgs, and request new features. To reach
the project support team, emailpyansys.core@ansys.com.InstallationTheansys-fluent-visualizationpackage supports Python 3.9 through Python
3.11 on Windows and Linux.If you are using Python 3.10, download and install the wheel file for thevtkpackage fromhere for Windowsor fromhere for Linux.Install the latest release fromPyPIwith:pip install ansys-fluent-visualizationAlternatively, install the latest release fromGitHubwith:pip install git+https://github.com/ansys/pyfluent-visualization.gitIf you plan on doing localdevelopmentof PyFluent-Visualization with Git,
install with:git clone https://github.com/ansys/pyfluent-visualization.git
cd pyfluent-visualization
pip install pip -U
pip install -e .DependenciesYou must have a licensed copy of Ansys Fluent installed locally.
PyFluent-Visualization supports Ansys Fluent 2022 R2 and
later.Getting startedBasic usageThe following code assumes that a PyFluent session has already been created
and a Fluent case with input parameters has been set up. For a complete
example, seeAnalyzing your resultsin
the PyFluent-Visualization documentation.fromansys.fluent.visualization.pyvistaimportGraphicsgraphics=Graphics(session=session)temperature_contour=graphics.Contours["contour-temperature"]temperature_contour.field="temperature"temperature_contour.surfaces_list=["in1","in2","out1"]temperature_contour.display("window-1")Usage in a JupyterLab environmentPyFluent-Visualization uses PyVista, which has the ability to display fully
featured plots within a JupyterLab environment using ipyvtklink. Find out
about using ipyvtklink with PyVistahere <https://docs.pyvista.org/user-guide/jupyter/ipyvtk_plotting.html>License and acknowledgmentsPyFluent-Visualization is licensed under the MIT license.PyFluent-Visualization makes no commercial claim over Ansys
whatsoever. This tool extends the functionality of Ansys Fluent
by adding a Python interface to Fluent without changing the
core behavior or license of the original software. The use of the
interactive Fluent control of PyFluent-Visualization requires
a legally licensed local copy of Fluent.For more information on Fluent, visit theFluentpage on the Ansys website.
Package: ansys-geometry-core
ContentsOverviewInstallationBasic usageDocumentation and issuesOverviewPyAnsys Geometry is a Python client library for the Ansys Geometry service, as well as other CAD Ansys products
such as Ansys Discovery and Ansys SpaceClaim.InstallationYou can usepipto install PyAnsys Geometry.pipinstallansys-geometry-coreTo install the latest development version, run these commands:gitclonehttps://github.com/ansys/pyansys-geometrycdpyansys-geometrypipinstall-e.For more information, seeGetting Started.Basic usageThis code shows how to import PyAnsys Geometry and use some basic capabilities:fromansys.geometry.coreimportlaunch_modelerfromansys.geometry.core.designerimportDesignFileFormatfromansys.geometry.core.mathimportPlane,Point3D,Point2Dfromansys.geometry.core.miscimportUNITS,Distancefromansys.geometry.core.sketchimportSketch# Define a sketchorigin=Point3D([0,0,10])plane=Plane(origin,direction_x=[1,0,0],direction_y=[0,1,0])# Create a sketchsketch=Sketch(plane)sketch.circle(Point2D([1,1]),30*UNITS.m)sketch.plot()# Start a modeler sessionmodeler=launch_modeler()# Create a designdesign=modeler.create_design("ModelingDemo")# Create a body directly on the design by extruding the sketchbody=design.extrude_sketch(name="CylinderBody",sketch=sketch,distance=Distance(80,unit=UNITS.m))# Plot the bodydesign.plot()# Download the modeldesign.download(file_location="file.scdocx",format=DesignFileFormat.SCDOCX)For comprehensive usage information, seeExamplesin thePyAnsys Geometry documentation.Documentation and issuesDocumentation for the latest stable release of PyAnsys Geometry is hosted atPyAnsys Geometry 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 thePyAnsys Geometry Issuespage,
you can create issues to report bugs and request new features. On thePyAnsys Geometry 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.
Package: ansys-grantami-bomanalytics
ansys-grantami-bomanalyticsProject OverviewPyGranta BoM Analytics is part of the largerPyAnsyseffort to facilitate the use of Ansys technologies directly from Python.The MI Restricted Substances and MI Sustainability solutions for Granta MI include REST APIs for:Evaluating compliance of products, assemblies, specifications, and
materials against legislations.Evaluating the environmental performance of products, assemblies, materials and processes.This package abstracts automatically-generated code into an easy-to-use client library.InstallationInstall theansys-grantami-bomanalyticspackage with this code:pip install ansys-grantami-bomanalyticsTo install a release compatible with a specific version of Granta MI, use thePyGrantameta-package with a requirement specifier:pip install pygranta==2023.2.0Alternatively, clone and install this package with this code:git clone https://github.com/ansys/grantami-bomanalytics
cd grantami-bomanalytics
pip install .DocumentationThePyGranta BoM Analytics Documentationprovides comprehensive installation and usage information.UsageHere’s a brief example of how to use PyGranta BoM Analytics:# Connect and query the Granta service.>>>frompprintimportpprint>>>fromansys.grantami.bomanalyticsimportConnection,queries>>>cxn=Connection("http://my_grantami_server/mi_servicelayer").with_autologon().connect()>>>query=(...queries.MaterialImpactedSubstancesQuery()....with_material_ids(['plastic-abs-pvc-flame'])....with_legislation_ids(['Candidate_AnnexXV'])...)# Print out the result from the query.>>>result=cxn.run(query)>>>pprint(result.impacted_substances)[<ImpactedSubstance:{"cas_number":10108-64-2,"percent_amount":1.9}>,<ImpactedSubstance:{"cas_number":107-06-2,"percent_amount":None}>,<ImpactedSubstance:{"cas_number":115-96-8,"percent_amount":15.0}>,...TestingFor information on testing, see theContributingsection of the documentation.LicensePyGranta BoM Analytics is provided under the terms of the MIT license. You can find
this license in the LICENSE file at the root of the repository.
Package: ansys-grantami-bomanalytics-openapi
Project OverviewAutogenerated client library for the Granta MI BoM Analytics Services.Direct use of this package is unsupported, please useansys-grantami-bomanalyticsinstead.This Python package is automatically generated by theSwagger Codegenproject.LicenseThe library is provided under the terms of the MIT license. You can find
the license text in the LICENSE file at the root of the repository.
Package: ansys-grantami-recordlists
PyGranta RecordListsA Python wrapper for the Granta MI Lists API.To avoid ambiguity with the Python objectlist, lists available via the Granta MI Lists API are referred to asrecord lists. Granta MI users might also know the feature asFavorites Lists.Using the Granta MI Lists API requires the user to have necessary permissions on the Granta MI Server. Some
operations on record lists require additional permissions, specific to record lists. For more information,
see the Help for the Favorites app in Granta MI.DependenciesTo use theansys.grantami.recordlistspackage you must have access to a Granta MI 2023 R2 deployment.Theansys.grantami.recordlistspackage currently supports Python from version 3.9 to version 3.12.InstallationTo install the latest release fromPyPI, use
this code:pip install ansys-grantami-recordlistsTo install a release compatible with a specific version of Granta MI, use thePyGrantameta-package with a requirement specifier:pip install pygranta==2023.2.0Alternatively, to install the latest fromansys-grantami-recordlistsGitHub,
use this code:pip install git:https://github.com/ansys/grantami-recordlists.gitTo install a localdevelopmentversion with Git and Poetry, use this code:git clone https://github.com/ansys/grantami-recordlists
cd grantami-recordlists
poetry installThe preceding code installs the package and allows you to modify it locally,
with your changes reflected in your Python setup after restarting the Python kernel.
Package: ansys-grantami-serverapi-openapi
Project OverviewAutogenerated client library for the Granta MI Server API.Direct use of this package is unsupported, please useansys-grantami-recordlistsinstead.This Python package is automatically generated by theSwagger Codegenproject.LicenseThe library is provided under the terms of the MIT license. You can find
the license text in the LICENSE file at the root of the repository.
Package: ansys-hps-client
PyHPS is a Python client library for Ansys HPC Platform Services (HPS), which is
a set of technology components designed to help you manage the execution of simulations
while making use of your full range of computing assets.PyHPS brings Ansys HPS to your Python app. Wrapping around Ansys HPS REST APIs, PyHPS
allows you to:Create projects and modify existing ones.Monitor and manage jobs.Run your own design exploration algorithms.Retrieve simulation results.Documentation and issuesDocumentation for the latest stable release of PyHPS is hosted atPyHPS 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.The PyHPS documentation contains these sections:Getting started: Explains
how to install PyHPS in user mode.User guide: Describes the basics
of how to use PyHPS to interact with Ansys HPS.Examples: Provides examples of how
to interact with Ansys HPS in Python using PyHPS.API reference: Describes PyHPS functions,
classes, methods, and their parameters and return values so that you can understand how to
interact with them programmaticallyContribute: Provides information on
how to install PyHPS in developer mode and make contributions to the codebase and documentation.On thePyHPS Issuespage, you can
create issues to report bugs and request new features. On thePyHPS 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.LicensePyHPS is licensed under the MIT license.PyHPS makes no commercial claim over Ansys whatsoever. This library extends the
functionality of Ansys HPC Platform Services by adding a Python interface to it
without changing the core behavior or license of the original software. The use
of PyHPS requires a legally licensed local copy of Ansys HPC Platform Services.To get a copy of Ansys HPC Platform Services, see theAnsys HPC Platform Services Guidein the Ansys Help.
Package: ansys-magnet-segmentation-toolkit
The Magnet Segmentation Toolkit is a Python wrapper for automating the segmentation
and skew of interior permanent magnet (IPM) and surface permanent magnet (SPM)
motors using Ansys Electronics Desktop (AEDT). You can launch this toolkit
from the AEDT UI or launch it directly from a Python console.RequirementsIn addition to the runtime dependencies listed inGetting started,
the Magnet Segmentation Toolkit requires AEDT 2023 R1 or later. This toolkit also supports the AEDT
Student Version for 2023 R1 or later.Documentation and issuesDocumentation for the latest stable release of the Magnet Segmentation Toolkit is hosted atMagnet Segmentation Toolkit 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 theMagnet Segmentation Toolkit Issuespage, you can create issues to report bugs and request new features. On theDiscussionspage on the Ansys Developer portal, you can post questions, share ideas, and get community feedback.LicenseThe Magnet Segmentation Toolkit is licensed under the MIT license.This toolkit makes no commercial claim over Ansys whatsoever. The use of this toolkit
requires a legally licensed copy of AEDT. For more information, see theAnsys Electronicspage on the Ansys website.
Package: ansys-math-core
PyAnsys Math is a Python repository holding Ansys mathematical libraries.
To use them, you must have a local installation of Ansys Mechanical APDL.For information on getting a licensed copy of Ansys Mechanical APDL, visit
theAnsys web site.InstallationFor usersTheansys.math.corepackage currently supports Python 3.8 through
Python 3.11 on Windows, Mac OS, and Linux.Install the latest package for use with this command:pip install ansys-math-coreAlternatively, install the latestPyAnsys Math GitHubpackage
with this command:pip install git+https://github.com/ansys/pyansys-math.gitFor developersFor a localdevelopmentversion, install the latest package with:git clone https://github.com/ansys/pyansys-math.git
cd pyansys-math
pip install -e .Installing the development version allows you to edit theansys-math-corepackage locally. The changes that you make are reflected in your setup
after restarting the Python kernel.Verify your installationCheck that you can start PyAnsys Math from Python by running this code:importansys.math.core.mathaspymath# Start PyAnsys Math.mm=pymath.AnsMath()print(mm)If you see a response from the server, you can start using PyAnsys Math
as a service.Ansys software requirementsYou must have a copy of Ansys 2021 R1 or later installed locally.NoteThe latest versions of Ansys provide significantly better support
and features. PyAnsys Math is not supported on Ansys versions earlier than 2021 R1.
Package: ansys-meshing-prime
PyPrimeMeshOverviewPyPrimeMesh is a Python client to Ansys Prime Server, which
delivers core Ansys meshing technology.Documentation and issuesDocumentation for the latest stable release of PyPrimeMesh is hosted atPyPrimeMesh 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.You can alsoviewordownloadthe
PyPrimeMesh cheat sheet. This one-page reference provides syntax rules and commands
for using PyPrimeMesh.On thePyPrimeMesh Issuespage,
you can create issues to report bugs and request new features. On thePyPrimeMesh 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.InstallationTheansys-meshing-primepackage supports Python 3.8 to Python 3.11 on the Windows and Linux
operating systems.PyPrimeMesh can be installed with all dependencies directly from PyPi by running
this command:pipinstallansys-meshing-prime[all]Alternatively, you can clone this repository and install the client using
these commands:gitclonehttps://github.com/ansys/pyprimemeshcdpyprimemesh
pipinstall-e.[all]The preceding commands install all functionality that is important to development.
To install a basic version of the client, use this command instead:pipinstall-e.DependenciesYou must have Ansys 2023 R1 or later installed for access to Ansys Prime Server.
Optionally, CAD readers can be configured. Ansys Prime Server requires
an Ansys Mechanical PrepPost or Fluids PrepPost (CFD) license to run.Get startedLaunch PyPrimeMeshTo launch PyPrimeMesh, use this code:importansys.meshing.primeasprimewithprime.launch_prime()asprime_client:model=prime_client.modelLicense and aknowledgmentsPyPrimeMesh is licensed under the MIT license.PyPrimeMesh makes no commercial claim over Ansys whatsoever. This library extends the functionality of
Ansys Prime Server by adding a Python interface without changing the core behavior or license
of the original software. The use of Ansys Prime Server requires a legally licensed copy of Ansys
2023 R1 or later.
Package: ansys-platform-instancemanagement
PyPIMexposes a Pythonic interface to
communicate with the Product Instance Management (PIM) API.What is the PIM API?The PIM API is a gRPC API, enabling both library and app developers to
start a product in a remote environment and communicate with its API.The PIM API is intended to be as simple as possible to be adaptable in a variety of
network and software infrastructures. Using this API does not require any
knowledge of its infrastructure. You need only know which product to
start and which API the product exposes. The PIM API itself exposes very few
features and assumes that all the configuration is set on a server.The PIM API is not intended to manage stateless services, to be a job management
system, or a fully featured service orchestration API. Its purpose is to expose
a minimum feature set for managing service-oriented apps.Getting startedTo use PyPIM, you must have access to the PIM API.NoteThe PIM API is a work in progress. Even though the API definition and the
PyPIM client are published, the service itself is not publicly exposed.PyPIM itself is pure Python and relies ongRPC.InstallationTheansys-platform-instancemanagementpackage is tested for Python 3.7 through
Python 3.10 on Windows and Linux.pip install ansys-platform-instancemanagementConfigurationBy default, PyPIM is configured externally instead of via code. Anywhere in the
local storage, create a configuration file with this format:{"version":1,"pim":{"uri":"dns:pim.svc.com:80","headers":{"metadata-info":"value"},"tls":false}}Then, define the environment variableANSYS_PLATFORM_INSTANCEMANAGEMENT_CONFIGto point to this configuration file.UsagePyPIM is a single module calledansys.platform.instancemanagement, shortened
topypim.To start MAPDL and communicate with PyPIM, use this code:importansys.platform.instancemanagementaspypimfromansys.mapdl.coreimportMapdlifpypim.is_configured():withpypim.connect()aspim:withpim.create_instance(product_name="mapdl",product_version="221")asinstance:instance.wait_for_ready()channel=instance.build_grpc_channel(options=[("grpc.max_receive_message_length",8*1024**2)])mapdl=Mapdl(channel=channel)mapdl.prep7()...You can also use PyPIM without thewithstatement, as shown in this code:importansys.platform.instancemanagementaspypimfromansys.mapdl.coreimportMapdlifpypim.is_configured():pim=pypim.connect()instance=pim.create_instance(product_name="mapdl",product_version="221")channel=instance.build_grpc_channel(options=[("grpc.max_receive_message_length",8*1024**2)])mapdl=Mapdl(channel=channel)mapdl.prep7()...instance.delete()pim.close()IntegrationPyPIM can be integrated in PyAnsys libraries to transparently switch to a remote
instance in a suitable environment. This process is described inIntegrationin the PyPIM documentation.For example, starting MAPDL with PyPIM is as simple as using this code:fromansys.mapdl.coreimportlaunch_mapdlmapdl=launch_mapdl()
Package: ansys-rocky-core
PyRocky is a Python client library for remotely controllingAnsys Rocky,
which is the most powerful software in the market for performing
DEM (discrete element method) simulations.Documentation and issuesDocumentation for the latest stable release of PyRocky is hosted atPyRocky documentation.The documentation has five sections:Getting started: Learn
how to install PyRocky in user mode and then launch it.User guide: Understand how to
use the Rocky PrePost API with PyRocky.API reference: Understand PyRocky API
endpoints, their capabilities, and how to interact with them programmatically.Examples: Explore end-to-end
examples that show how to use PyRocky.Contribute: Learn how to contribute
to the PyRocky codebase or 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 thePyRocky Issuespage, you can
create issues to report bugs and request new features. On theDiscussionspage on the Ansys Developer portal,
you can post questions, share ideas, and get community feedback.To reach the PyAnsys project support team, emailPyAnsys Core team.LicensePyRocky is licensed under theMIT License.PyRocky makes no commercial claim over Ansys whatsoever. This library extends the
functionality of Ansys Rocky by adding a Python interface without changing the
core behavior or license of the original software. The use of PyRocky requires a
legally licensed copy of Ansys Rocky.To get a copy of Ansys Rocky, see theAnsys Rockypage on the Ansys website.