The `settings.py` module#

Summary#

Functions

`disable_off_screen_rendering`	No pop up windows appears to plot data with `matplotlib` or `pyvista`.
`set_default_pyvista_config`	Set default pyvista configuration.
`bypass_pv_opengl_osmesa_crash`	Bypass pyvista opengl osmesa crash.
`disable_interpreter_properties_evaluation`	Disable property evaluation on tab key press if the jedi module is installed.
`set_upload_chunk_size`	Set upload chunk size.
`set_dynamic_available_results_capability`	Disable evaluation and dynamic creation of result properties when creating a “Model.
`get_runtime_client_config`	Get the runtime configuration information of Ans.Dpf.GrpcClient binary.
`get_runtime_core_config`	Get the runtime configuration information of Ans.Dpf.GrpcClient binary.

Description#

settings.

Customize the behavior of the module.

Module detail#

settings.disable_off_screen_rendering() → None#: No pop up windows appears to plot data with matplotlib or pyvista.

settings.set_default_pyvista_config()#: Set default pyvista configuration.

settings.bypass_pv_opengl_osmesa_crash()#: Bypass pyvista opengl osmesa crash.

settings.disable_interpreter_properties_evaluation() → bool#

Disable property evaluation on tab key press if the jedi module is installed.

If jedi module is installed (autocompletion module for most of IDEs), disables the property evaluation when tab key is pressed.

To use in Jupyter Notebook if autocompletion becomes slow.

Returns:: Whether disabling the capability has been possible.
Return type:: bool

settings.set_upload_chunk_size(num_bytes=misc.DEFAULT_FILE_CHUNK_SIZE) → None#: Set upload chunk size.

settings.set_dynamic_available_results_capability(value) → None#

Disable evaluation and dynamic creation of result properties when creating a “Model.

Disables the evaluation of the available results and the dynamic creation of the results properties when a ‘’Model’’ is created.

Parameters:: value (bool) – With ‘’True’’, models will dynamically generate results properties

Examples

>>> from ansys.dpf import core as dpf
>>> dpf.settings.set_dynamic_available_results_capability(False)
>>> dpf.settings.set_dynamic_available_results_capability(True)

settings.get_runtime_client_config(server=None)#

Get the runtime configuration information of Ans.Dpf.GrpcClient binary.

Parameters:: server (server.DPFServer, optional) – Server with channel connected to the remote or local instance. When None, attempts to use the global server.

Notes

Available from 4.0 server version. Can only be used for a gRPC communication protocol using DPF CLayer.

Returns:: runtime_config – RuntimeClientConfig object that can be used to interact with Ans.Dpf.GrpcClient configuration.
Return type:: RuntimeClientConfig

settings.get_runtime_core_config(server=None)#