refresh(config={'temporary-directory': None, 'tokenize': {'ensure-deterministic': False}, 'dataframe': {'shuffle-compression': None, 'parquet': {'metadata-task-size-local': 512, 'metadata-task-size-remote': 16}}, 'array': {'svg': {'size': 120}, 'slicing': {'split-large-chunks': None}, 'chunk-size': '128MiB', 'rechunk-threshold': 4}, 'optimization': {'fuse': {'active': None, 'ave-width': 1, 'max-width': None, 'max-height': inf, 'max-depth-new-edges': None, 'subgraphs': None, 'rename-keys': True}}}, defaults=[{'temporary-directory': None, 'tokenize': {'ensure-deterministic': False}, 'dataframe': {'shuffle-compression': None, 'parquet': {'metadata-task-size-local': 512, 'metadata-task-size-remote': 16}}, 'array': {'svg': {'size': 120}, 'slicing': {'split-large-chunks': None}}, 'optimization': {'fuse': {'active': None, 'ave-width': 1, 'max-width': None, 'max-height': inf, 'max-depth-new-edges': None, 'subgraphs': None, 'rename-keys': True}}}, {'array': {'chunk-size': '128MiB', 'rechunk-threshold': 4}}], **kwargs)
This mutates the global dask.config.config, or the config parameter if passed in.
This goes through the following stages:
Clearing out all old configuration
Updating from the stored defaults from downstream libraries (see update_defaults)
Updating from yaml files and environment variables
Note that some functionality only checks configuration once at startup and may not change behavior, even if configuration changes. It is recommended to restart your python process if convenient to ensure that new configuration changes take place.
Update configuration by re-reading yaml files and env variables
dask.config.collect
for parameters
The following pages refer to to this document either explicitly or contain code examples using this.
dask.config.collect
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