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Tabular Data - 19.5 KB - 20 Variables, 71 Observations - UNF:6:4aW5YYtNsiGfEn3vIOgYwQ==
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Tabular Data - 32.4 KB - 20 Variables, 150 Observations - UNF:6:7mhAUXkcp8mepCX68X6aoQ==
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Tabular Data - 24.8 KB - 20 Variables, 89 Observations - UNF:6:TqNdoTYK82lhOhxcATp7eA==
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Tabular Data - 32.6 KB - 20 Variables, 150 Observations - UNF:6:HHQ8P/NKfR4RJZy0Yb9fQA==
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Tabular Data - 102.9 KB - 32 Variables, 240 Observations - UNF:6:vulLddFxKuZx5MP/f3/uOQ==
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Tabular Data - 495.9 KB - 44 Variables, 627 Observations - UNF:6:0SJFoESklDHpNQVN45MgpA==
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Tabular Data - 1.3 MB - 44 Variables, 1643 Observations - UNF:6:QbiXDl2lE/+qYzoqudwqvA==
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Python Source Code - 29.0 KB -
MD5: 9a19cf68dc30173ece57c5f04afd85d9
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Tabular Data - 1.0 MB - 32 Variables, 2576 Observations - UNF:6:F2GH0cuqnNr0JMqNnlWEQg==
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Jan 24, 2022 - PN 6-6
Tkachev, Gleb, 2022, "PyPlant: A Python Framework for Cached Function Pipelines", https://doi.org/10.18419/DARUS-2249, DaRUS, V1
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. |