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Documentation and in-progress work of NumFOCUS's sustainability program.

Website

http://www.pytables.org/

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Description

PyTables is a package for managing hierarchical datasets designed to efficiently cope with extremely large amounts of data.

It is built on top of the HDF5 [1] library, the Python language [2] and the NumPy [3] package. It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code, makes it a fast yet extremely easy-to-use tool for interactively storing and retrieving very large amounts of data.

Languages

Python

Team

PyTables Governance Team — PyTables 3.3.0 documentation

Governance Team:

Top Contributors:

Contributors: https://github.com/PyTables/PyTables/graphs/contributors

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Issues · PyTables/PyTables

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License

BSD-3-Clause: PyTables/LICENSE.txt at develop · PyTables/PyTables

Citing

FAQ — Citing

The recommended way to cite PyTables in a paper or a presentation is as following:

Author: Francesc Alted, Ivan Vilata and others

Title: PyTables: Hierarchical Datasets in Python

Year: 2002 -

URL: http://www.pytables.org

Here’s an example of a BibTeX entry:

@Misc{,

author = {Francesc Alted and Ivan Vilata and others},

title = {{PyTables}: Hierarchical Datasets in {Python}},

year = {2002--},

url = "http://www.pytables.org/"

}

History

“Since August 2015, PyTables is a NumFOCUS project, which means that your donations are fiscally sponsored under the NumFOCUS umbrella. Please consider donating to NumFOCUS.”

“Because, back in August 2002, one of its authors (Francesc Alted [10]) had a need to save lots of hierarchical data in an efficient way for later post-processing it. After trying out several approaches, he found that they presented distinct inconveniences. For example, working with file sizes larger than, say, 100 MB, was rather painful with ZODB (it took lots of memory with the version available by that time).

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