Tag: data

Bypass the GIL and utilize all CPU cores for compute-intensive tasks.

Cache expensive function results automatically with the built-in cache decorator.

Switch to PyArrow-backed DataFrames for faster operations and lower memory usage.

Process large datasets without loading everything into memory using Python generators.

Use table partitioning to dramatically speed up queries on large datasets.

Use MERGE (upsert) for safe, rerunnable data pipelines that handle duplicates gracefully.