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Part 1: Document Description
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Citation |
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Title: |
PyPlant: A Python Framework for Cached Function Pipelines |
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Identification Number: |
doi:10.18419/darus-2249 |
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Distributor: |
DaRUS |
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Date of Distribution: |
2022-01-24 |
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Version: |
1 |
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Bibliographic Citation: |
Tkachev, Gleb, 2022, "PyPlant: A Python Framework for Cached Function Pipelines", https://doi.org/10.18419/darus-2249, DaRUS, V1 |
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Citation |
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Title: |
PyPlant: A Python Framework for Cached Function Pipelines |
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Identification Number: |
doi:10.18419/darus-2249 |
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Authoring Entity: |
Tkachev, Gleb (Universität Stuttgart) |
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Grant Number: |
EXC 2075 - 390740016 |
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Distributor: |
DaRUS |
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Access Authority: |
Tkachev, Gleb |
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Access Authority: |
Tkachev, Gleb |
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Depositor: |
Tkachev, Gleb |
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Date of Deposit: |
2021-11-26 |
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Holdings Information: |
https://doi.org/10.18419/darus-2249 |
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Study Scope |
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Keywords: |
Computer and Information Science |
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Topic Classification: |
Development frameworks and environments |
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Abstract: |
PyPlant is a simple coroutine-based framework for writing data processing pipelines. PyPlant's goal is to simplify caching of intermediate results in the pipeline and avoid re-running expensive early stages of the pipeline, when only the later stages have changed. |
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Notes: |
<p>PyPlant is a simple coroutine-based framework for writing data processing pipelines. <br/> Given a set of Python functions that consume and produce data, it automatically runs them in a correct order and caches intermediate results. When the pipeline is executed again, only the necessary parts are re-run.</p> <p>Importantly, PyPlant was designed with the following design consideration in mind: <ul> <li>Simple: Quick to learn, no custom language and workflow design programs. Start prototyping right away.</li> <li>DRY: Function code is metadata. No need to write execution graphs or external metadata. It just works (tm).</li> <li>Automatic: No need to manually re-run outdated parts.</li> <li>Large data: Handle data that doesn't fit into memory. Persist between runs.</li> </ul> <p>PyPlant can be installed from PyPI: `pip install pyplant`<br> For documentation, see <a href="https://darus.uni-stuttgart.de/file.xhtml?fileId=70090&version=DRAFT">README.md</a>.</p> |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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.gitignore |
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application/octet-stream |
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.travis.yml |
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application/octet-stream |
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LICENSE.txt |
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text/plain |
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README.md |
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text/markdown |
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requirements.txt |
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text/plain |
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roadmap.txt |
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text/plain |
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setup.cfg |
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application/octet-stream |
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setup.py |
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text/x-python |
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pyplant.py |
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text/x-python |
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specs.py |
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text/x-python |
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utils.py |
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text/x-python |
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__init__.py |
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text/x-python |
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PipeworkMock.py |
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text/x-python |
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test_utils.py |
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text/x-python |
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__init__.py |
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text/x-python |
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pyplant_test.py |
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text/x-python |
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utils_test.py |
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text/x-python |