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pydantic/monty

A minimal, secure Python interpreter written in Rust for use by AI

Healthy

Healthy across all four use cases

HealthyDependency

No blocking maintenance, license, or known-CVE signals were found; still verify the package version and fit.

HealthyFork & modify

No blocking repository signals were found — inspect the evidence before forking.

HealthyLearn from

Documented and popular — useful reference codebase to read through.

HealthyDeploy as-is

No blocking repository-level signals were found; deployment review is still required.

  • ⚠Scorecard: default branch unprotected (0/10)
  • ✓Last commit 3d ago
  • ✓12 active contributors
  • ✓Distributed ownership (top contributor 41% of recent commits)
  • ✓MIT licensed
  • ✓CI configured
  • ✓Tests present

Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

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Repository brief

Repo brief: pydantic/monty

Generated by RepoPilot · document generated 2026-09-16 · concise human review Evidence snapshot · analyzed 2026-09-16T15:47:30.505Z · commit 4303db4f1c2c

Verdict

Healthy — Healthy across all four use cases

  • Last commit 3d ago
  • 12 active contributors
  • Distributed ownership (top contributor 41% of recent commits)
  • MIT licensed
  • 2 more receipts on the live page

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

What it is

Monty is a minimal, secure Python 3.14 interpreter written in Rust that runs untrusted Python code generated by LLMs with microsecond startup times and complete sandboxing of filesystem, network, and environment access. It replaces container-based sandboxes for AI agent code execution, offering snapshotable state, fast startup (<1μs), and the ability to expose only whitelisted host functions to the interpreter. Monorepo with 15+ crates under crates/: core interpreter in crates/monty, runtime in crates/monty-runtime, filesystem sandbox in crates/monty-fs, Python bindings in crates/monty-python, JavaScript bindings in crates/monty-js, type checking in…

Start here

Read these in order:

  • crates/monty-fs/src/common.rs — Foundation: doesn't import anything internally and is imported by 1 other file. Read first to learn the vocabulary.
  • crates/monty-fs/src/direct.rs — Foundation: imported by 1, no internal dependencies of its own.
  • crates/monty-proto/src/convert/mod.rs — Built on the foundation; imported by 2 downstream files.
  • crates/monty/src/builtins/mod.rs — Built on the foundation; imported by 1 downstream file.
  • crates/monty/src/types/mod.rs — Layer 2 — application-level code that wires the lower layers together.

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

Clone with git clone https://github.com/pydantic/monty.git && cd monty. Build the workspace with cargo build --release (Rust project, Cargo.toml present with workspace resolver). Verify Rust 1.95+ is installed. Run…

Daily commands:

For the Rust codebase: cargo build to compile (debug), cargo build --release for optimized binary. Default workspace member is crates/monty-runtime. Run tests with cargo test --workspace. Run benchmarks with `ca…

…shortened for this brief.

Key cautions & unknowns

  • Scorecard: default branch unprotected (0/10)
  • Rust version constraint: workspace requires rust-version 1.95, which is very recent and may not be in stable channel—verify your rustc --version before building. Lockstep release coupling: all internal crate versions…
  • Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.

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