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Merge pull request #245 from djarecka/satra-enh-dask
adding comments on Dask worker [skip ci]
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README.md

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2. Composable dataflows with simple node semantics. A dataflow can be a node of another dataflow.
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3. `splitter` and `combiner` provides many ways of compressing complex loop semantics
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4. Cached execution with support for a global cache across dataflows and users
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5. Distributed execution (presently via ConcurrentFutures and SLURM, more on their way)
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5. Distributed execution, presently via ConcurrentFutures, SLURM,
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and Dask (this is an experimental implementation with limited testing)
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[[API Documentation](https://nipype.github.io/pydra/)]
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pip install -e .[dev]
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```
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If you want to test execution with Dask:
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```
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git clone [email protected]:nipype/pydra.git
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cd pydra
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pip install -e .[dask]
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```
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It is also useful to install pre-commit:
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```

pydra/engine/workers.py

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class DaskWorker(Worker):
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"""A worker to execute in parallel using Python's concurrent futures."""
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""" A worker to execute in parallel using Dask.distributed.
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This is an experimental implementation with limited testing.
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"""
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def __init__(self, **kwargs):
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"""Initialize Worker."""

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