Principle:Pola rs Polars Rust Crate Feature System
| Knowledge Sources | |
|---|---|
| Domains | Build_System, Feature_Flags |
| Last Updated | 2026-02-09 09:00 GMT |
Overview
Mechanism that uses Cargo's feature flag system to provide fine-grained compile-time selection of data types, operations, I/O formats, and optimizations in a modular library.
Description
A large library like Polars contains hundreds of features spanning data types, compute operations, I/O format support, and platform-specific optimizations. Making all of these unconditionally compiled would result in unacceptable binary sizes and compilation times. Cargo's feature system solves this by allowing features to be opt-in at compile time. Polars organizes features into a hierarchy: individual features (e.g., dtype-datetime, rolling_window, parquet), aggregate features (dtype-full, dtype-slim, performant), and meta features (default, full, docs-selection). Features propagate through the dependency graph, so enabling parquet on the top-level polars crate automatically enables it on polars-io, polars-lazy, etc. This conditional compilation pattern also applies to the Python bindings crate, where features map to Python-accessible functionality.
Usage
Use this principle when designing Rust libraries with optional functionality that users may not need. Organize features into logical groups (types, operations, I/O) with sensible defaults. Provide aggregate features for common use cases. Ensure feature propagation is correct across workspace crates. The Polars pattern of having a default feature for typical use and a full feature for maximum capability is a proven approach.
Theoretical Basis
Feature Hierarchy Pattern:
# Abstract feature organization
features:
# Individual features
dtype-date, dtype-datetime, csv, parquet, rolling_window, ...
# Aggregate features (groups of related features)
dtype-full = [dtype-date, dtype-datetime, dtype-duration, ...]
dtype-slim = [dtype-date, dtype-datetime, dtype-duration]
io = [csv, json, parquet, ipc, ...]
operations = [rank, pivot, rolling_window, ...]
# Meta features (combination of aggregates)
default = [csv, parquet, temporal, fmt, dtype-slim]
full = [docs-selection, performant, fmt]