PyTables 0.7.1 is out!¶
This is a mainly a bug-fixing release, where the next problems has been addressed:
- Fixed several memory leaks. After that, the memory consumption when using large object trees has dropped sensibly. However, there remains some small leaks, but hopefully they are not very important unless you use huge object trees.
- Fixed a bug that make the __getitem__ special method in table to fail when the stop parameter in a extended slice was not specified. That is, table[10:] now correctly returns table[10:table.nrows+1], and not table[10:11].
- The removeRows() method in Table did not update the NROWS attribute in Table objects, giving place to errors after doing further updating operations (removing or adding more rows) in the same table. This has been fixed now.
Apart of these fixes, a new lazy reading algorithm for attributes has been activated by default. With that, the opening of objects with large hierarchies has been improved by 60% (you can obtain another additional 10% if using python 2.3 instead of python 2.2). The documentation has been updated as well, specially a more detailed instructions on the compression (zlib) libraries installation.
Also, a stress test has been conducted in order to see if PyTables can really work not only with large data tables, but also with large object trees. In it, it has been generated and checked a file with more than 1 TB of size and more than 100 thousand tables on it!. See http://www.pytables.org/moin/StressTestsBck for details.