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| Started by | Tom Kooij <tom.kooij@gmail.com> |
|---|---|
| First post | 2016-09-12 10:01 +0200 |
| Last post | 2016-09-12 10:01 +0200 |
| Articles | 1 — 1 participant |
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ANN: PyTables 3.3.0 Tom Kooij <tom.kooij@gmail.com> - 2016-09-12 10:01 +0200
| From | Tom Kooij <tom.kooij@gmail.com> |
|---|---|
| Date | 2016-09-12 10:01 +0200 |
| Subject | ANN: PyTables 3.3.0 |
| Message-ID | <mailman.142.1473681756.2411.python-announce-list@python.org> |
=========================== Announcing PyTables 3.3.0 =========================== We are happy to announce PyTables 3.3.0. What's new ========== - Single codebase Python 2 and 3 support (PR #493). - Internal Blosc version updated to 1.11.1 (closes :issue:`541`) - Full BitShuffle support for new Blosc versions (>= 1.8). - It is now possible to remove all rows from a table. - It is now possible to read reference types by dereferencing them as numpy array of objects (closes :issue:`518` and :issue:`519`). Thanks to Ehsan Azar - Fixed Windows 32 and 64-bit builds. In case you want to know more in detail what has changed in this version, please refer to: http://www.pytables.org/release_notes.html You can install it via pip or download a source package with generated PDF and HTML docs from: https://github.com/PyTables/PyTables/releases/tag/v3.3.0 For an online version of the manual, visit: http://www.pytables.org/usersguide/index.html What it is? =========== PyTables is a library for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data with support for full 64-bit file addressing. PyTables runs on top of the HDF5 library and NumPy package for achieving maximum throughput and convenient use. PyTables includes OPSI, a new indexing technology, allowing to perform data lookups in tables exceeding 10 gigarows (10**10 rows) in less than a tenth of a second. Resources ========= About PyTables: http://www.pytables.org About the HDF5 library: http://hdfgroup.org/HDF5/ About NumPy: http://numpy.scipy.org/ Acknowledgments =============== Thanks to many users who provided feature improvements, patches, bug reports, support and suggestions. See the ``THANKS`` file in the distribution package for a (incomplete) list of contributors. Most specially, a lot of kudos go to the HDF5 and NumPy makers. Without them, PyTables simply would not exist. Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. ---- **Enjoy data!** -- The PyTables Developers .. Local Variables: .. mode: rst .. coding: utf-8 .. fill-column: 72 .. End:
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