pyiron_base.maintenance.generic.LocalMaintenance

pyiron_base.maintenance.generic.LocalMaintenance#

class pyiron_base.maintenance.generic.LocalMaintenance(project)[source]#

Bases: object

__init__(project)[source]#

Methods

__init__(project)

defragment_storage([recursive, progress])

Rewrite the hdf5 files of jobs.

update_hdf_types([recursive, progress])

Rewrite TYPE fields in hdf5 files for renamed modules.

update_pyiron_tables([recursive, progress])

defragment_storage(recursive: bool = True, progress: bool = True, **kwargs: dict)[source]#

Rewrite the hdf5 files of jobs. This can free up unused space.

By default iterate recursively over the jobs within the current project. This can be controlled with recursive and kwargs.

Parameters:

  • recursive (bool) – search subprojects [True/False] - True by default

  • progress (bool) – if True (default), add an interactive progress bar to the iteration

  • **kwargs (dict) – Optional arguments for filtering with keys matching the project database column name (eg. status=”finished”). Asterisk can be used to denote a wildcard, for zero or more instances of any character

update_hdf_types(recursive: bool = True, progress: bool = True, **kwargs: dict)[source]#

Rewrite TYPE fields in hdf5 files for renamed modules.

New module conversions can be added with add_module_conversion(old, new)(). This method will then consider all objects previously imported from old to be imported from new.

Parameters:

  • recursive (bool) – search subprojects [True/False] - True by default

  • progress (bool) – if True (default), add an interactive progress bar to the iteration

  • **kwargs (dict) – Optional arguments for filtering with keys matching the project database column name (eg. status=”finished”). Asterisk can be used to denote a wildcard, for zero or more instances of any character

Contents