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Squashed commit at 2025-05-09 21:54
Add config pydantic model
Add detect.py
Add group-node-mapping
Add dump logger
Add dump engine
Add dump managers
Add facades
Add utils
Add changes to CLI
Add changes to init, disable mypy for feature for now
Add changes to docs
Add changes to and additional tests
[pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
Fix bug in explicitly-groupd sub-workflows being filtered out for profile/group dumping
Fix group validation exception on `verdi profile dump -G` and creation of empty dirs for deselected groups.
.. - ``-f/--flat``: Dump files in a flat directory structure
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.. - ``--dump-unsealed/--no-dump-unsealed``: Allow/disallow dumping of unsealed process nodes
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.. For group and profile dumping, additional options include:
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.. - ``--filter-by-last-dump-time/--no-filter-by-last-dump-time``: Only dump nodes modified since last dump
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.. - ``--dump-processes/--no-dump-processes``: Control process dumping
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.. - ``--only-top-level-calcs/--no-only-top-level-calcs``: Control calculation directory creation
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.. - ``--only-top-level-workflows/--no-only-top-level-workflows``: Control workflow directory creation
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.. - ``--symlink-calcs/--no-symlink-calcs``: Use symlinks for duplicate calculations to avoid data duplication
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.. For a full list of available options, call ``verdi process dump --help``, ``verdi group dump --help``, or ``verdi profile dump --help``.
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.. Incremental Dumping
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.. ---------------~~
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.. By default, all dump commands operate in incremental mode, which means they only process nodes that are new or have been modified since the last dump operation. This makes the feature efficient when run repeatedly:
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.. .. code-block:: shell
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.. $ verdi group dump my-calculations
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.. Report: No (new) calculations to dump in group `my-calculations`.
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.. Report: No (new) workflows to dump in group `my-calculations`.
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.. Success: Raw files for group `my-calculations` dumped into folder `my-calculations-dump`.
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Python API
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----------
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The dump functionality is also available through a Python API:
The data dumping functionality was designed to bridge the gap between research conducted with AiiDA and scientists not familiar with AiiDA. Some common use cases include:
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1. Sharing simulation results with collaborators who don't use AiiDA
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2. Periodically running the dump command to reflect changes while working on a project
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3. Analyzing data using traditional shell tools outside of AiiDA's programmatic approach
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