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Documentation: add troubleshooting section related to the model (#139)
* add troubleshooting section related to the model * fix * Add set_dynamic_available_results_capability in doc * Update the PR looking at the review that have been made on a similar PR on pydpf-post
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docs/source/user_guide/troubleshooting.rst

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===============
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Troubleshooting
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===============
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This section explains how to resolve the most common issues encountered with ``pydpf-core``.
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This section explains how to resolve the most common issues encountered with PyDPF-Core.
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It also includes suggestions for improving scripts.
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Using the Server
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Connecting to DPF Server
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~~~~~~~~~~~~~~~~~~~~~~~~
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If an issue appears while using the pydpf-core API to connect to an initialized server with :py:meth:`connect_to_server()
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If an issue appears while using the ``pydpf-core`` API to connect to an initialized server with :py:meth:`connect_to_server()
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<ansys.dpf.core.server.connect_to_server>`, ensure that the IP address and port number that are set as parameters
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are applicable for a DPF server started on the network.
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Importing pydpf-core module
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Assume that you are importing the pydpf-core module:
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Assume that you are importing the ``pydpf-core`` module:
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.. code-block:: default
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The module `ansys.grpc.dpf <https://pypi.org/project/ansys-grpc-dpf/>`_ should always be synchronized with its server
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version.
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Using the Model
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---------------
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Invalid UTF-8 Error
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~~~~~~~~~~~~~~~~~~~
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Assume that you are trying to access the py:class:`Model<ansys.dpf.core.model.Model>`.
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The following error can be raised:
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.. code-block:: default
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[libprotobuf ERROR C:\.conan\897de8\1\protobuf\src\google\protobuf\wire_format_lite.cc:578]
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String field 'ansys.api.dpf.result_info.v0.ResultInfoResponse.user_name' contains invalid UTF-8
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data when serializing a protocol buffer. Use the 'bytes' type if you intend to send raw bytes.
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This will prevent the model from being accessed. To avoid a this error, ensure that you are using
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a PyDPF-Core version higher than 0.3.2. In this case, a warning will still be raised, but it should not
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prevent the use of the Model.
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Then, with result files reproducing this issue, to avoid the warning to pop up, you can use:
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.. code-block:: default
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from ansys.dpf import core as dpf
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dpf.settings.set_dynamic_available_results_capability(False)
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However, this will disable the reading and generation of the available results of the model: static prewritten
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available results will be used instead.
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Performance Issues
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------------------
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Getting and Setting a Field's Data
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Accessing or modifying field data :py:class:`Field<ansys.dpf.core.field.Field>` entity by entity can
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be slow if the field's size is large or if the server is far from the Python client. To improve performance,
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use :py:meth:`as_local_field()<ansys.dpf.core.field.Field.as_local_field>` in a context manager.

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