Poll multiple data sources in a single thread using Python generators with itertools.cycle to alternate between infinite data streams efficiently.

Use Django query expressions like Replace, Upper, Lower, Concat, and Substr for efficient database-level text manipulation without fetching data.

Accelerate Django bulk_update operations by 4x using multiprocessing to parallelize database writes across chunked record batches.

Practical SQLite recipes for Python: execute statements, batch operations, transactions, row factories, and context managers with sqlite3.

Emulate Python's random.choice in SQLite using JSON arrays and the random() function. Populate tables with realistic test data efficiently.

Speed up Django bulk operations with ProcessPoolExecutor while preserving signals and hooks that bulk_create/bulk_update bypass.

We used hibernate to set up our initial database schema. Hibernate generates constraint names like: fk_jwy3ip299dvht6bhrf7kxnmap and fk_bc7w4arbgsiasoufirt1ec0na. While these are unique and of a length that works on all databases, they are not very descrip...