How we rebuilt Pydantic’s Rust Python interpreter as a Bazel remote build
The article describes how Pydantic rebuilt its Rust-based Python interpreter as a Bazel remote build system, enabling faster and more efficient compilation and testing of Python projects by leveraging Bazel's distributed caching and remote execution capabilities.
Background
- **Pydantic** is a popular Python library for data validation and type safety; its core is written in **Rust** (via the PyO3 framework) for performance. The "Rust Python interpreter" referenced is **pydantic-core**, the Rust-powered engine underpinning Pydantic.
- **Bazel** is a build and test system (open-sourced by Google) designed for large, multi-language monorepos. It uses a **remote execution** model: build actions can be farmed out to a cluster of machines, enabling caching, parallelism, and reproducible builds.
- The article describes how Pydantic's team moved from compiling pydantic-core locally (slow, fragile across platforms) to treating it as a **remote Bazel build action** — so any developer or CI pipeline can trigger a build without installing Rust or a full toolchain locally.
- This matters because it solves a common pain point: Python libraries with native Rust extensions are hard to distribute and develop on. By wrapping the build in Bazel's remote execution, Pydantic gains faster, hermetic, and cross-platform builds without requiring each contributor to set up a Rust environment.