Projects / pysqlite / Releases / Major bugfixes

RSS All releases tagged Major bugfixes

  •  01 Feb 2006 18:34

Release Notes: More checks have been added to make executescript() and the transparent statement caching more robust. An API misuse has been fixed so that pysqlite can be used with SQLite 3.3.3 and later. The function enable_shared_cache() has been added to use the shared cache available with SQLite 3.3.

  •  23 Oct 2005 13:44

Release Notes: A problem that could lead to crashes with long timeouts has been fixed. Leaks that occurred when a BEGIN, COMMIT, or ROLLBACK failed have been fixed. A function that checks whether a string is a complete SQL statement has been added.

  •  11 Sep 2005 20:37

Release Notes: This release takes care that sqlite3_finalize is not called twice. This seems to have led to the crashes in multithreaded applications that users saw. Concurrency has been improved. pysqlite now wakes up more often in case of a busy database. Calling the constructor of the (undocumented) Cache class with insufficient parameters no longer crashes Python. Other minor fixes and clarifications in the documentation.

  •  28 May 2005 07:14

Release Notes: The changes for prefetching in 2.0.2 were incomplete. A check that made sense before had to be removed, otherwise fetchone()/fetchmany()/fetchall() could raise ProgrammingErrors instead of returning None or an empty list if no more rows were available. Users of pysqlite 2.0.2 should definitely upgrade.

  •  07 May 2005 20:40

Release Notes: This release adds documentation, fixes lots of reference count bugs and memory leaks, and features better compliance with DB-API 2.0.

  •  26 Apr 2005 07:57

Release Notes: Two memory leaks in the fetchmany() and fetchall() methods were fixed.

  •  05 Jul 2004 11:14

Release Notes: This release fixes several bugs, including three that would lead to crashes of the Python interpreter.

  •  06 Sep 2002 14:42

Release Notes: This release includes several new features, such as the ability to create new SQL functions and aggregates in Python. It also benefits from more extensive testing and debugging, Python style LaTeX documentation, and one more example which illustrates importing data from an XML document.

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