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PyArrow

data-science

Python bindings for Apache Arrow with efficient columnar format

15M/week ↑ Growing

Features

columnarapache-arrowinteroperabilityparquetperformance

Pros and Cons

Ventajas

  • + Ultra-efficient columnar format
  • + Cross-language interoperability
  • + Native Parquet read/write
  • + Zero-copy reads between systems
  • + De facto standard for data exchange
  • + Foundation for Polars and many modern tools

Desventajas

  • - Low-level API
  • - Steep learning curve
  • - Complex technical documentation
  • - Overhead for small datasets
  • - Doesn't replace pandas for analysis

Use Cases

  • Data exchange between systems
  • Parquet file read/write
  • High-performance ETL
  • Modern data lakes
  • Columnar database integration
  • In-memory data transfer

Tecnologías Relacionadas

Compatible with

Alternatives