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AGENTS.md — mkl_random

Entry point for agent context in this repo.

What this project is

mkl_random is a NumPy-compatible random module backed by Intel® oneMKL RNG. It provides accelerated random sampling with API compatibility goals relative to numpy.random.

Key components

  • Python package: mkl_random/
  • Cython layer: mkl_random/mklrand.pyx
  • C backend/templates: mkl_random/src/
  • Tests: mkl_random/tests/
  • Packaging: conda-recipe/, conda-recipe-cf/
  • Examples: examples/

Build/runtime basics

  • Build system: pyproject.toml + setup.py
  • Build deps: cython, numpy, mkl-devel
  • Runtime deps: numpy, mkl

Development guardrails

  • Preserve numpy.random API compatibility unless change is explicitly requested.
  • RNG changes must preserve statistical correctness and reproducibility expectations.
  • Keep diffs minimal and pair behavior changes with tests.
  • Avoid hardcoding mutable versions/matrices/channels in docs.

Where truth lives

  • Build/config: pyproject.toml, setup.py
  • Dependencies: pyproject.toml, conda-recipe*/meta.yaml
  • CI matrices/workflows: .github/workflows/*.{yml,yaml}
  • Public API: mkl_random/__init__.py
  • Tests: mkl_random/tests/

For behavior policy, see .github/copilot-instructions.md.

Directory map

Use nearest local AGENTS.md when present:

  • .github/AGENTS.md — CI workflows and automation policy
  • mkl_random/AGENTS.md — package-level implementation context
  • mkl_random/tests/AGENTS.md — testing scope and conventions
  • conda-recipe/AGENTS.md — Intel-channel conda packaging
  • conda-recipe-cf/AGENTS.md — conda-forge recipe context
  • examples/AGENTS.md — runnable examples and expected behavior