Tag: Pipelines

Rent and return arrays from a shared pool to avoid repeated allocations in buffer-heavy code.

Eliminate heap allocations when parsing strings by using Span for memory-efficient operations.

Handle rate limits and transient failures gracefully with exponential backoff.

Enterprise data integration has evolved from simple ETL batch jobs […]

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

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