diff --git a/doc/source/concepts/waysofusing.rst b/doc/source/concepts/waysofusing.rst index 1debf55aa0..25077c38da 100644 --- a/doc/source/concepts/waysofusing.rst +++ b/doc/source/concepts/waysofusing.rst @@ -32,7 +32,7 @@ These capabilities can be accessed through client APIs, as shown here: .. image:: ../images/drawings/apis_2.png -1. DPF server application can be accessed using Ansys Inc product, or DPF Server package (see :ref:`ref_getting_started_with_dpf_server`) available on the Customer portal. +1. DPF server application can be accessed using Ansys Inc product, or DPF Server package (see :ref:`ref_dpf_server`) available on the Customer portal. 2. Several client APIs are available (CPython, IronPython, C++, and so on). diff --git a/doc/source/conf.py b/doc/source/conf.py index 2c18f594bf..ab5f92c489 100644 --- a/doc/source/conf.py +++ b/doc/source/conf.py @@ -319,7 +319,8 @@ def verify_meilisearch_is_active(app): MEILISEARCH_PUBLIC_API_KEY = os.getenv("MEILISEARCH_PUBLIC_API_KEY", None) if not MEILISEARCH_PUBLIC_API_KEY: sys.stderr.write("Could not find MEILISEARCH_PUBLIC_API_KEY") - sys.exit(1) + # sys.exit(1) + def setup(app): app.connect("builder-inited", verify_meilisearch_is_active) diff --git a/doc/source/getting_started/compatibility.rst b/doc/source/getting_started/compatibility.rst index e1a92b945d..5b3d7e1dc1 100644 --- a/doc/source/getting_started/compatibility.rst +++ b/doc/source/getting_started/compatibility.rst @@ -13,7 +13,7 @@ more information, see `Ansys Platform Support `_ of the Ansys Customer Portal. +The first standalone version of DPF Server available is 6.0 (2023 R2). + +The sections on this page describe how to install and use a standalone DPF Server. + +* For a quick start on using PyDPF, see :ref:`ref_getting_started`. +* For more information on DPF and its use, see :ref:`ref_user_guide`. + + +Install DPF Server +------------------ + +.. _target_installing_server: + +#. Download the ``ansys_dpf_server_win_v2024.2.pre0.zip`` or ``ansys_dpf_server_lin_v2024.2.pre0.zip`` file as appropriate. +#. Unzip the package. +#. Optional: download any other plugin ZIP file as appropriate and unzip the package. For example, to access the ``composites`` plugin for Linux, + download ``ansys_dpf_composites_lin_v2024.2.pre0.zip`` and unzip the package in the same location as ``ansys_dpf_server_lin_v2024.2.pre0.zip``. +#. Change to the root folder (``ansys_dpf_server_win_v2024.2.pre0``) of the unzipped package. +#. In a Python environment, run this command: + +.. code:: + + pip install -e . + + +As detailed in :ref:`licensing`, a standalone DPF Server is protected using the license terms specified in the +`DPFPreviewLicenseAgreement `_ +file, which is available on the `DPF Pre-Release page `_ +of the Ansys Customer Portal. +To accept these terms, you must set this environment variable: + +.. code:: + + ANSYS_DPF_ACCEPT_LA=Y + +To use :ref:`licensed DPF capabilities ` you must set the +``ANSYSLMD_LICENSE_FILE`` environment variable to point to a valid local or remote license +following indications in :ref:`configure_licensing`. + + +Use DPF Server +-------------- + +DPF Server is protected using the license terms specified in the +`DPFPreviewLicenseAgreement `_ +file, which is available on the `DPF Pre-Release page `_ +of the Ansys Customer Portal. + +Run DPF Server with PyDPF +~~~~~~~~~~~~~~~~~~~~~~~~~ + +PyDPF-Core is a Python client API communicating with a **DPF Server**, either +through the network using gRPC or directly in the same process. PyDPF-Post is a Python +module for postprocessing based on PyDPF-Core. + +Both PyDPF-Core and PyDPF-Post can be used with DPF Server. Installation instructions +for PyDPF-Core are available in the PyDPF-Core `Getting started `_. +Installation instructions for PyDPF-Post are available in the PyDPF-Post `Getting started `_. + +With PyDPF-Core and PyDPF-Post, the first creation of most DPF entities starts a DPF Server with the current default configuration and context. +For example, the following code automatically starts a DPF Server behind the scenes: + +.. code:: + + from ansys.dpf import core as dpf + data_sources = dpf.DataSources() + +With PyDPF-Core, you can also explicitly start a DPF Server using this code: + +.. code:: + + from ansys.dpf import core as dpf + server = dpf.start_local_server() + +To start a DPF Server from outside a Python environment, you can also use the execution script provided with your DPF Server package. +On Windows, start the DPF Server by running the ``Ans.Dpf.Grpc.bat`` file in the unzipped package. +On Linux, start the DPF Server by running the ``Ans.Dpf.Grpc.sh`` file in the unzipped package. + +Manage multiple DPF Server installations +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +PyDPF automatically starts a local instance of a DPF Server when you run a method requiring a +connection to a server, or when you use the ``start_local_server()`` method. +The ``start_local_server()`` method allows to choose, if necessary, which DPF Server installation +to use thanks to its ``ansys_path`` argument. +PyDPF otherwise follows the logic below to automatically detect and choose which locally installed +version of DPF Server to run: + +- it uses the ``ANSYS_DPF_PATH`` environment variable in priority if set and targeting a valid path to a DPF Server installation. +- it then checks the currently active Python environment for any installed standalone DPF Server, and uses the latest version available. +- it then checks for ``AWP_ROOTXXX`` environment variables, which are set by the **Ansys installer**, and uses the latest version available. +- if then raises an error if all of the steps above failed to return a valid path to a DPF Server installation. + +Run DPF Server in a Docker container +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +DPF Server can be run in a Docker container. + +#. Along with the ``ansys_dpf_server_lin_v2024.2.pre0.zip`` file mentioned earlier + in :ref:`Install DPF Server `, download the ``Dockerfile`` file. +#. Optional: download any other plugin ZIP file as appropriate. For example, to access the ``composites`` plugin for Linux, + download ``ansys_dpf_composites_lin_v2024.2.pre0.zip``. +#. Copy all the ZIP files and ``Dockerfile`` file in a folder and navigate into that folder. +#. To build the DPF Docker container, run the following command: + +.. code:: + + docker build . -t dpf-core:v2024.2.pre0 --build-arg DPF_VERSION=242 + +5. To run the DPF Docker container, license it. For more information, see :ref:`DPF Preview License Agreement`. diff --git a/doc/source/getting_started/index.rst b/doc/source/getting_started/index.rst index 326243c2c6..3cbc115a45 100644 --- a/doc/source/getting_started/index.rst +++ b/doc/source/getting_started/index.rst @@ -15,66 +15,38 @@ PyDPF-Core is a Python client API communicating with a **DPF Server**, either through the network using gRPC or directly in the same process. -Install PyDPF-Core ------------------- - -To install PyDPF-Core, in a Python environment, run this command: - -.. code:: - - pip install ansys-dpf-core - -For more installation options, see :ref:`Installation section `. - - Install DPF Server ------------------ +To use PyDPF-Core, you need access to a DPF Server. + * DPF Server is packaged within the **Ansys installer** in Ansys 2021 R1 and later. - To use it, download the standard installation using your preferred distribution channel, - and install Ansys following the installer instructions. If you experience problems, - see :ref:`Environment variable `. For information on getting - a licensed copy of Ansys, visit the `Ansys website `_. + To use it, download the standard installation using your preferred distribution channel, + and install Ansys following the installer instructions. + For information on getting a licensed copy of Ansys, visit the `Ansys website `_. -* DPF Server is available as a **standalone** package (independent of the Ansys installer) on the +* DPF Server pre-releases are also available as **standalone** packages (independent of the Ansys installer) on the `DPF Pre-Release page `_ of the Ansys Customer Portal. - As explained in :ref:`Ansys licensing `, - DPF Server is protected by an Ansys license mechanism. Once you have access to an - Ansys license, install DPF Server: - -.. card:: + As explained in :ref:`ref_licensing`, the standalone DPF Server is still protected by an Ansys license mechanism + and requires accepting the :ref:`DPF Preview License Agreement`. + Once you have access to an Ansys license, follow the guidelines to :ref:`install a standalone DPF Server `. - * Download the ``ansys_dpf_server_win_v2023.2.pre1.zip`` or ``ansys_dpf_server_lin_v2023.2.pre1.zip`` - file as appropriate. - * Unzip the package and go to its root folder (``ansys_dpf_server_win_v2023.2.pre1`` or - ``ansys_dpf_server_lin_v2023.2.pre1``). - * In a Python environment, run this command: +For more information regarding installing, managing and running DPF servers, see :ref:`ref_dpf_server`. - .. code:: - - pip install -e . - - * DPF Server is protected using the license terms specified in the - `DPFPreviewLicenseAgreement `_ - file, which is available on the `DPF Pre-Release page `_ - of the Ansys Customer Portal. To accept these terms, you must set this - environment variable: - - .. code:: +Install PyDPF-Core +------------------ - ANSYS_DPF_ACCEPT_LA=Y +To install PyDPF-Core, in a Python environment, run this command: -For more information about the license terms, see :ref:`DPF Preview License Agreement`. +.. code:: -To use a remote license, set the ``ANSYSLMD_LICENSE_FILE`` environment -variable to point to the Ansys license server ````: + pip install ansys-dpf-core -.. code:: +Be sure to check the :ref:`compatibility guidelines ` to know if your +DPF Server version is compatible with the latest version of PyDPF-Core. - ANSYSLMD_LICENSE_FILE=1055@ +For more installation options, see :ref:`Installation section `. -For installation methods that do not use `pip `_, -such as using **Docker containers**, see :ref:`ref_getting_started_with_dpf_server`. Use PyDPF-Core -------------- @@ -140,8 +112,10 @@ To use PyDPF-Core, in the same Python environment, run this command: .. toctree:: :hidden: - - compatibility + install + dpf_server + compatibility + licensing dependencies diff --git a/doc/source/getting_started/licensing.rst b/doc/source/getting_started/licensing.rst new file mode 100644 index 0000000000..d30c448326 --- /dev/null +++ b/doc/source/getting_started/licensing.rst @@ -0,0 +1,190 @@ +.. _ref_licensing: + +========= +Licensing +========= + +This section details how to properly set-up licensing, as well as what the user should expect in +terms of limitations or license usage when running PyDPF scripts. + +DPF follows a client-server architecture, which means that the PyDPF client library must interact with a running DPF Server. +It thus either starts a DPF Server via a local installation of DPF Server, or it connects to an already running local or remote DPF Server. + +DPF Server is packaged within the **Ansys installer** in Ansys 2021 R1 and later. +It is also available as a standalone application. +For more information on installing DPF Server, see :ref:`ref_dpf_server`. + + +.. _target_to_license_terms: +License terms +------------- + +When using the DPF Server from an ANSYS installation, the user has already agreed to the licensing +terms when installing ANSYS. + +When using a standalone DPF Server, the user needs to accept the ``DPF Preview License Agreement`` +by following the indications below. +Starting a DPF Server without agreeing to the ``DPF Preview License Agreement`` throws an exception. + +DPF Preview License Agreement +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +The standalone versions of DPF Server are protected using license terms specified in the `DPFPreviewLicenseAgreement `_ +file that can be found on the `DPF Pre-Release page `_ +of the Ansys Customer Portal. +The ``DPFPreviewLicenseAgreement`` file is a text file, which means that you can open it with a text editor, such as ``Notepad``. + +To accept the terms of this license agreement, you must set the following environment variable: + +.. code:: + + ANSYS_DPF_ACCEPT_LA=Y + +The ``ANSYS_DPF_ACCEPT_LA`` environment variable confirms your acceptance of the DPF License Agreement. +By passing the value ``Y`` to this environment variable, you are indicating that you have a valid and +existing license for the edition and version of DPF Server that you intend to use. + + +.. _configure_licensing: +Configure licensing +------------------- + +If your machine does not have a local ANSYS installation, you need to define where DPF should look for a valid license. + +To use a local license file, set the ``ANSYSLMD_LICENSE_FILE`` environment +variable to point to an Ansys license file ````: + +.. code:: + + ANSYSLMD_LICENSE_FILE= + +To use a remote license, set the ``ANSYSLMD_LICENSE_FILE`` environment +variable to point to an Ansys license server ````: + +.. code:: + + ANSYSLMD_LICENSE_FILE=1055@ + +For DPF Docker container usage only, you can use the following code to set both the ``ANSYS_DPF_ACCEPT_LA`` +and ``ANSYSLMD_LICENSE_FILE`` environment variables. For the ``ANSYSLMD_LICENSE_FILE`` environment variable, +ensure that you replace ```` to point to the Ansys license server. + +.. code:: + + docker run -e "ANSYS_DPF_ACCEPT_LA=Y" -e ANSYSLMD_LICENSE_FILE=1055@ -p 50052:50052 -e DOCKER_SERVER_PORT=50052 --expose=50052 dpf-core:v2024_2_pre0 + +The next section provides information on +the Ansys license mechanism that is used with DPF Server. + + +.. _target_to_ansys_license_mechanism: +License checks and usage +------------------------ + +Some DPF operators require DPF to check for an existing license +and some require DPF to check-out a compatible license increment. + +DPF is by default allowed to check-out license increments as needed. +To change this behavior, see :ref:`here `. + +To know if operators require a license increment check-out to run, check their ``license`` +attribute in :ref:`ref_dpf_operators_reference` or directly in Python by checking the operator's +properties for a ``license`` key: + +.. code-block:: python + + import ansys.dpf.core as dpf + + operator = dpf.operators.averaging.elemental_difference() + print(operator.specification.properties) + +.. rst-class:: sphx-glr-script-out + + .. code-block:: none + + {'category': 'averaging', 'exposure': 'public', 'license': 'any_dpf_supported_increments', 'plugin': 'core', 'scripting_name': 'elemental_difference', 'user_name': 'elemental difference (field)'} + + +To check which ANSYS licensing increments correspond to ``any_dpf_supported_increments``, +see :ref:`here`. + +Even if an operator does not require a license check-out to run, most DPF operators still require +DPF to check for a reachable license server or license file. + +Operators which do not perform any kind of license check are source operators (data extraction +operators) which do not perform any data transformation. + +For example, when considering result operators, they perform data transformation if the requested +location is not the native result location. In that case, averaging occurs which is considered +as data transformation (for example, elemental to nodal, nodal to elemental...). + +.. _licensing_server_context: +Server context +~~~~~~~~~~~~~~ + +You can allow or prevent licensed operators from running and using a license with a +:ref:`server context `: + +- **Premium:** This default context allows DPF to perform license checkouts, + making licensed DPF operators available. +- **Entry:** This context does not allow DPF to perform any license checkout, + meaning that licensed DPF operators fail. + +To update the context, apply a new server context: + +.. code:: + + server.apply_context(dpf.AvailableServerContexts.premium) + +.. _licensing_errors: +Licensing errors +~~~~~~~~~~~~~~~~ + +The following user actions may fail due to licensing: + +- Starting a standalone DPF Server may fail due to the + ``DPF Preview License Agreement`` (see :ref:`target_to_license_terms`). +- Creating an operator may fail if the operator performs data transformation and no license server + or license file is found (see :ref:`target_to_ansys_license_mechanism`). +- Running an operator requiring a license checkout may fail if no + :ref:`compatible license increment ` + is available or if the DPF Server context is **Entry**, preventing any license check-out + (see :ref:`licensing_server_context`). + + +.. _target_to_ansys_license_increments_list: +Compatible Ansys license increments +----------------------------------- + +The following Ansys licensing increments provide rights to use the licensed DPF capabilities: + +- ``preppost`` available in the ``Ansys Mechanical Enterprise PrepPost`` product +- ``meba`` available in the ``ANSYS Mechanical Enterprise Solver`` product +- ``mech_2`` available in the ``ANSYS Mechanical Premium`` product +- ``mech_1`` available in the ``ANSYS Mechanical Pro`` product +- ``ansys`` available in the ``ANSYS Mechanical Enterprise`` product +- ``dynapp`` available in the ``ANSYS LS-DYNA PrepPost`` product +- ``dyna`` available in the ``ANSYS LS-DYNA`` product +- ``vmotion`` available in the ``Ansys Motion`` product +- ``acpreppost`` available in the ``Ansys Mechanical Enterprise`` product +- ``acdi_adprepost`` available in the ``Ansys AUTODYN`` and ``Ansys AUTODYN PrepPost`` products +- ``cfd_preppost`` available in the ``Ansys CFD Enterprise`` product +- ``cfd_preppost_pro`` available in the ``Ansys CFD Enterprise`` product +- ``vmotion_post`` available in the ``Ansys Motion Post`` product +- ``vmotion_pre`` available in the ``Ansys Motion Pre`` product +- ``advanced_meshing`` available in the ``Ansys CFD Enterprise`` product +- ``fluent_meshing_pro`` available in the ``Ansys CFD Enterprise`` product +- ``fluent_setup_post`` available in the ``Ansys CFD Enterprise`` product +- ``fluent_setup_post_pro`` available in the ``Ansys CFD Enterprise`` product +- ``acfx_pre`` available in the ``Ansys CFD Enterprise`` product +- ``cfd_base`` available in the ``Ansys CFD Enterprise`` product +- ``cfd_solve_level1`` available in the ``Ansys CFD Enterprise`` product +- ``cfd_solve_level2`` available in the ``Ansys CFD Enterprise`` product +- ``cfd_solve_level3`` available in the ``Ansys CFD Enterprise`` product +- ``fluent_meshing`` available in the ``Ansys CFD Enterprise`` product +- ``avrxp_snd_level1`` available in the ``Ansys Sound Enterprise`` product +- ``sherlock`` available in the ``Ansys Sherlock`` product + +Each increment may be available in other products. On the Ansys Customer Portal, +the `Licensing section `_ +provides product/increment mapping. diff --git a/doc/source/index.rst b/doc/source/index.rst index ed5533f7af..67d1d94468 100644 --- a/doc/source/index.rst +++ b/doc/source/index.rst @@ -112,7 +112,9 @@ Accessing and enriching DPF capabilities ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Most of the DPF capabilities can be accessed using the operators. -For more information, see :ref:`_ref_dpf_operators_reference`. +For more information, see :ref:`ref_dpf_operators_reference`. + +DPF also follows a licensing strategy detailed in :ref:`ref_licensing`. The following sections are summaries. For more information, see :ref:`user_guide_waysofusing`. @@ -126,13 +128,13 @@ the **Ansys installer** and **DPF Server**. on getting a licensed copy of Ansys, visit the `Ansys website `_. - The DPF Server package is independent of the Ansys installer. For more information, see - :ref:`ref_getting_started_with_dpf_server`. + :ref:`ref_dpf_server`. **Accessing capabilities with scripting** - C++ documentation: - - On the `Developer Documentation `_page of the Ansys Developer portal, + - On the `Developer Documentation `_ page of the Ansys Developer portal, see **Data Processing Framework (DPF)**. - PyDPF documentation: diff --git a/doc/source/user_guide/getting_started_with_dpf_server.rst b/doc/source/user_guide/getting_started_with_dpf_server.rst deleted file mode 100644 index a2ad328901..0000000000 --- a/doc/source/user_guide/getting_started_with_dpf_server.rst +++ /dev/null @@ -1,183 +0,0 @@ -.. _ref_getting_started_with_dpf_server: - -=============================== -Getting started with DPF Server -=============================== - -What is DPF Server ------------------- - -DPF provides numerical simulation users and engineers with a toolbox for accessing and transforming -simulation data. With DPF, you can perform complex preprocessing or postprocessing of large amounts of simulation data within a -simulation workflow. - -DPF Server is a package that contains all the necessary files to run the DPF Server, enabling DPF capabilities. It is available -on the `DPF Pre-Release page `_ of the Ansys Customer Portal. -The first version of DPF Server is 6.0 (2023 R2). - -The sections on this page describe how to use DPF Server. - -* For a quick start on DPF Server, see :ref:`ref_getting_started`. -* For more information on DPF and its use, see :ref:`ref_user_guide`. - - -Install DPF Server ------------------- - -.. _target_installing_server: - -#. Download the ``ansys_dpf_server_win_v2024.1.pre0.zip`` or ``ansys_dpf_server_lin_v2024.1.pre0.zip`` file as appropriate. -#. Unzip the package. -#. Optional: download any other plugin ZIP file as appropriate and unzip the package. For example, to access the ``composites`` plugin for Linux, - download ``ansys_dpf_composites_lin_v2024.1.pre0.zip`` and unzip the package in the same location as ``ansys_dpf_server_lin_v2024.1.pre0.zip``. -#. Change to the root folder (``ansys_dpf_server_win_v2024.1.pre0``) of the unzipped package. -#. In a Python environment, run this command: - -.. code:: - - pip install -e . - -Use DPF Server --------------- - -DPF Server is protected using the license terms specified in the -`DPFPreviewLicenseAgreement `_ -file, which is available on the `DPF Pre-Release page `_ -of the Ansys Customer Portal. - -Run DPF Server with PyDPF -~~~~~~~~~~~~~~~~~~~~~~~~~ - -PyDPF-Core is a Python client API communicating with a **DPF Server**, either -through the network using gRPC or directly in the same process. PyDPF-Post is a Python -module for postprocessing based on PyDPF-Core. - -Both PyDPF-Core and PyDPF-Post can be used with DPF Server. Installation instructions -for PyDPF-Core are available in the PyDPF-Core `Getting started `_. -Installation instructions for PyDPF-Post are available in the PyDPF-Post `Getting started `_. - -With PyDPF-Core and PyDPF-Post, the first creation of most DPF entities starts a DPF Server with the current default configuration and context. -For example, the following code automatically starts a DPF Server behind the scenes: - -.. code:: - - from ansys.dpf import core as dpf - data_sources = dpf.DataSources() - -With PyDPF-Core, you can also explicitly start a DPF Server using this code: - -.. code:: - - from ansys.dpf import core as dpf - server = dpf.start_local_server() - -To start a DPF Server from outside a Python environment, you can also use the execution script provided with your DPF Server package. -On Windows, start the DPF Server by running the ``Ans.Dpf.Grpc.bat`` file in the unzipped package. -On Linux, start the DPF Server by running the ``Ans.Dpf.Grpc.sh`` file in the unzipped package. - -Run DPF Server in a Docker container -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -DPF server can be run in a Docker container. - -#. Along with the ``ansys_dpf_server_lin_v2024.1.pre0.zip`` file mentioned earlier - in :ref:`Install DPF Server `, download the ``Dockerfile`` file. -#. Optional: download any other plugin ZIP file as appropriate. For example, to access the ``composites`` plugin for Linux, - download ``ansys_dpf_composites_lin_v2024.1.pre0.zip``. -#. Copy all the ZIP files and ``Dockerfile`` file in a folder and navigate into that folder. -#. To build the DPF Docker container, run the following command: - -.. code:: - - docker build . -t dpf-core:v2024.1.pre0 --build-arg DPF_VERSION=241 - -4. To run the DPF Docker container, license it. For more information, see' - :ref:`DPF Preview License Agreement`. - -License terms -------------- - -.. _target_to_license_terms: - -DPF Preview License Agreement -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -DPF Server is protected using license terms specified in the `DPFPreviewLicenseAgreement `_ -file that can be found on the `DPF Pre-Release page `_ -of the Ansys Customer Portal. The ``DPFPreviewLicenseAgreement`` file s a text file, which means that you can -open it with a text editor, such as notepad. - -To accept the terms of this license agreement, you must set the following environment variable: - -.. code:: - - ANSYS_DPF_ACCEPT_LA=Y - -The ``ANSYS_DPF_ACCEPT_LA`` environment variable confirms your acceptance of the DPF License Agreement. -By passing the value ``Y`` to this environment variable, you are indicating that you have a valid and -existing license for the edition and version of DPF Server that you intend to use. - -For DPF Docker container usage only, you can use the following code to set both the ``ANSYS_DPF_ACCEPT_LA`` -and ``ANSYSLMD_LICENSE_FILE`` environment variables. For the ``ANSYSLMD_LICENSE_FILE`` environment variable, -ensure that you replace ```` to point to the Ansys license server. - -.. code:: - - docker run -e "ANSYS_DPF_ACCEPT_LA=Y" -e ANSYSLMD_LICENSE_FILE=1055@ -p 50052:50052 -e DOCKER_SERVER_PORT=50052 --expose=50052 dpf-core:v2024_1_pre0 - -The next section, :ref:`Ansys licensing`, provides information on -the Ansys license mechanism that is used with DPF Server. - - -.. _target_to_ansys_license_mechanism: - -Ansys licensing -~~~~~~~~~~~~~~~ - -DPF Server is protected by an Ansys licensing mechanism. - -DPF capabilities are available through the following main contexts: - -- **Premium:** This default context allows DPF to perform license checkouts, - making licensed DPF operators available. -- **Entry:** This context does not allow DPF to perform any license checkout, - meaning that licensed DPF operators fail. - -To update the context, apply a new server context: - -.. code:: - - server.apply_context(dpf.AvailableServerContexts.premium) - -.. _target_to_ansys_license_increments_list: - -The following Ansys licensing increments provide rights to use DPF Server: - -- ``preppost`` available in the ``Ansys Mechanical Enterprise PrepPost`` product -- ``meba`` available in the ``ANSYS Mechanical Enterprise Solver`` product -- ``mech_2`` available in the ``ANSYS Mechanical Premium`` product -- ``mech_1`` available in the ``ANSYS Mechanical Pro`` product -- ``ansys`` available in the ``ANSYS Mechanical Enterprise`` product -- ``dynapp`` available in the ``ANSYS LS-DYNA PrepPost`` product -- ``vmotion`` available in the ``Ansys Motion`` product -- ``acpreppost`` available in the ``Ansys Mechanical Enterprise`` product -- ``acdi_adprepost`` available in the ``Ansys AUTODYN`` and ``Ansys AUTODYN PrepPost`` products -- ``cfd_preppost`` available in the ``Ansys CFD Enterprise`` product -- ``cfd_preppost_pro`` available in the ``Ansys CFD Enterprise`` product -- ``vmotion_post`` available in the ``Ansys Motion Post`` product -- ``vmotion_pre`` available in the ``Ansys Motion Pre`` product -- ``advanced_meshing`` available in the ``Ansys CFD Enterprise`` product -- ``fluent_meshing_pro`` available in the ``Ansys CFD Enterprise`` product -- ``fluent_setup_post`` available in the ``Ansys CFD Enterprise`` product -- ``fluent_setup_post_pro`` available in the ``Ansys CFD Enterprise`` product -- ``acfx_pre`` available in the ``Ansys CFD Enterprise`` product -- ``cfd_base`` available in the ``Ansys CFD Enterprise`` product -- ``cfd_solve_level1`` available in the ``Ansys CFD Enterprise`` product -- ``cfd_solve_level2`` available in the ``Ansys CFD Enterprise`` product -- ``cfd_solve_level3`` available in the ``Ansys CFD Enterprise`` product -- ``fluent_meshing`` available in the ``Ansys CFD Enterprise`` product -- ``avrxp_snd_level1`` available in the ``Ansys Sound Enterprise`` product -- ``sherlock`` available in the ``Ansys Sherlock`` product - -Each increment may be available in other products. On the Ansys Customer Portal, -the `Licensing section `_ -provides product/increment mapping. diff --git a/doc/source/user_guide/how_to.rst b/doc/source/user_guide/how_to.rst index c121b8bafe..bc28573411 100644 --- a/doc/source/user_guide/how_to.rst +++ b/doc/source/user_guide/how_to.rst @@ -37,7 +37,7 @@ How-tos .. card:: Use DPF Server package - :link: ref_getting_started_with_dpf_server + :link: ref_dpf_server :link-type: ref :width: 25% :text-align: center