There is a newer version of PyTablesPyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data. PyTables is built on top of the HDF5 library, using the Python language and the NumPy package. It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code (generated using Cython), makes it a fast, yet extremely easy to use tool for interactively browse, process and search very large amounts of data. One important feature of PyTables is that it optimizes memory and disk resources so that data takes much less space (specially if on-flight compression is used) than other solutions such as relational or object oriented databases.
Accessing PyTables 3.6.1-foss-2019b-Python-3.7.4
To load the module for PyTables 3.6.1-foss-2019b-Python-3.7.4 please use this command on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs):
module load PyTables/3.6.1-foss-2019b-Python-3.7.4
There is a GPU enabled version of this module: PyTables 3.6.1-fosscuda-2019b-Python-3.7.4
BEAR Apps Version
For more information visit the PyTables website.
This version of PyTables has a direct dependency on: Blosc/1.17.1-GCCcore-8.3.0 foss/2019b HDF5/1.10.5-gompi-2019b LZO/2.10-GCCcore-8.3.0 numexpr/2.7.1-foss-2019b-Python-3.7.4 Python/3.7.4-GCCcore-8.3.0
This version of PyTables is a direct dependent of: BEAR-Python-DataScience/2019b-foss-2019b-Python-3.7.4 scVelo/0.1.24-foss-2019b-Python-3.7.4 scVelo/0.1.25-foss-2019b-Python-3.7.4 variant_tools/3.1.3-foss-2019b-Python-3.7.4
These versions of PyTables are available on the BEAR systems (BlueBEAR, BEARCloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.
Last modified on 27th January 2020