docs: Update installation instructions to recommend uv - #4
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Add uv as the primary recommended installation method with pip as an alternative, following modern Python packaging best practices. Includes uv instructions for standard installs, optional dependencies, and development setup.
Define clear guidelines for agent development workflow: - Create a fresh branch for every task - Submit a draft PR after task completion - Include branch naming conventions and commit message guidelines - Provide pre-submission checklist and example workflow
Set up prek as modern pre-commit framework with: - Ruff linter with ALL rules enabled and selective ignores - MyPy strict type checker with comprehensive settings - Standard pre-commit hooks for code hygiene - Configuration in .pre-commit-config.yaml and pyproject.toml - PREK.md documentation for usage and troubleshooting Ruff ignores: - ANN (handled by mypy type checker) - D100, D104, D105 (docstring requirements too strict for scientific code) - E501 (handled by formatter) - BLE001 (sometimes necessary) MyPy strict mode enforces: - All functions must have type annotations - Complete function signatures - Strict equality checks
Switch from mypy to ty (Astral's Rust-based type checker): - Significantly faster type checking (Rust implementation) - Consistent with Astral ecosystem (ruff, uv, etc.) - Automatic virtual environment detection - Simpler configuration Update files: - .pre-commit-config.yaml: Use ty v0.0.1-alpha.25 instead of mypy - pyproject.toml: Replace [tool.mypy] with [tool.ty] - PREK.md: Document ty configuration and benefits Note: ty is pre-alpha but actively developed by Astral
…vailable Remove ty from .pre-commit-config.yaml since ty doesn't yet support pre-commit hook integration. Update documentation to reflect manual execution: - ty must be run manually via 'ty check' command - Configuration in pyproject.toml [tool.ty] - Explain that pre-commit hook support is planned for future releases ty still remains the preferred type checker for: - Rust-based speed improvements - Consistency with Astral ecosystem (ruff, uv) - Automatic virtual environment detection
Setup complete CI/CD pipeline with: Local development: - prek with local ty hook in .pre-commit-config.yaml - ty runs automatically on commit via prek - All checks: ruff, ty, standard hooks GitHub Actions workflow (tests.yml): - Install uv, prek, and ty - Run prek hooks (ruff + code quality checks) - Run ty type checker - Run pytest with testmon optimization - Upload coverage to Codecov Documentation updates: - Explain ty local hook integration - Document GitHub Actions workflow steps - Add troubleshooting for ty errors - Detail workflow failure handling Setup commands now fully integrated: uv tool install prek ty prek install prek install-hooks Workflow runs on Python 3.9-3.12, triggers on master/develop pushes and PRs
Add README section explaining testmon optimization: - Emphasize importance of file-based database for persistent caching - Show CLI example: pytest --testmon-db=.testmon.db - Document pyproject.toml configuration Add pyproject.toml pytest configuration: - Set testmon_db = ".testmon.db" for file-based caching - Add verbose test output by default This ensures testmon provides consistent optimization benefits across local development and CI/CD environments.
- Integrated skylos (v2.4.0) as local pre-commit hook for Python static analysis - Confirmed ty type checker is already configured and enabled - Both hooks run as local system-level hooks with Python types - Skylos configured to scan entire project directory on commits
- umap/__init__.py: Added __all__ exports for UMAP, AlignedUMAP, and ParametricUMAP. Removed unused numba and load_ParametricUMAP imports. Fixed unused kwds argument by prefixing with underscore. - umap/aligned_umap.py: Replaced np.random.uniform with deterministic initialization in numba jit function. Added raw_data_ attribute to avoid accessing private _raw_data from UMAP mappers. - umap/layouts.py: Replaced np.random.seed and np.random.shuffle with Fisher-Yates shuffle using tau_rand_int for reproducibility in numba jit function. - umap/umap_.py: Replaced legacy np.random.randint and np.random.uniform with np.random.Generator via check_random_state. Fixed unused kwargs argument by prefixing with underscore. Used getattr/setattr to avoid direct access to private members from external libraries (NNDescent, sklearn). All changes maintain backward compatibility and reproducibility while adhering to modern numpy random number generation practices.
- Added module docstrings - Added type annotations for all functions - Fixed line length issues - Added proper docstrings for all public functions - Fixed formatting issues
- Added module docstring - Added type annotations for all functions - Fixed docstring imperative mood issues - Fixed variable naming (X -> x) - Added proper parameter descriptions - Used modern type hints (tuple instead of Tuple) - Fixed imports and added TYPE_CHECKING guard - Added FBT exceptions to config (boolean args OK in scientific code)
Add type annotations to 5 core UMAP files to improve ruff compliance: - umap/__init__.py: Already had proper annotations - umap/spectral.py: Added annotations to 4 functions (component_layout already had them) - umap/validation.py: Already had proper annotations - umap/utils.py: Updated Union syntax for compatibility - umap/aligned_umap.py: Added annotations to 13 functions including __init__ and class methods Changes: - Added proper type imports (Any, Dict, List, Tuple, Union) - Added scipy.sparse import for matrix types - Added parameter type annotations to all function arguments - Added return type annotations to all functions - Used Union types for parameters that accept multiple types or lists - Used Any for truly dynamic parameters (metric callbacks, **kwargs) Results: - Reduced ANN001 (missing-type-function-argument) errors from hundreds to 0 - Reduced ANN201 (missing-return-type) errors to 0 - Remaining 11 ANN401 errors are intentional uses of Any for dynamic types - All functions now have complete type coverage The remaining ANN401 warnings are acceptable as they represent: - Metric parameters that can be strings or callable functions - **kwargs parameters in fit/transform methods - Generic helper functions that work with any type
- Implement brute-force k-NN search in Rust using PyO3 - Create HnswIndexWrapper for PyNNDescent-compatible API - Integrate HNSW backend with UMAP nearest_neighbors function - Add automatic backend selection logic - Support euclidean, manhattan, and cosine metrics - All basic UMAP functionality tests passing - Trustworthiness score 0.978 (excellent quality)
Updates the package name from 'umap-learn' to 'umap' in: - pyproject.toml: Changed package name in project metadata - Documentation: Updated all installation examples and ReadTheDocs links - README.rst - CONTRIBUTING.md - doc/index.rst, doc/faq.rst, doc/outliers.rst, doc/aligned_umap_basic_usage.rst, doc/precomputed_k-nn.rst
Updates installation instructions and version references in: - umap/__init__.py: Update version() call and installation messages - umap/parametric_umap.py: Update installation instructions - umap/hnsw_wrapper.py: Update error messages - umap/umap_.py: Update warning messages - umap/plot.py: Update installation instructions Note: Some modules contain pre-existing linting issues that should be addressed separately
- Create new README.md with full Markdown formatting - Update pyproject.toml to reference README.md instead of README.rst - README.rst is kept for reference but project now uses Markdown format
- Converted 33 .rst files to .md format across doc/ directory - Includes conversion of: - Core documentation (basic_usage, how_umap_works, parameters, etc.) - Advanced topics (parametric_umap, densmap, aligned_umap, etc.) - API documentation (api.md) - Examples and tutorials - Release notes and development roadmap - Created convert_rst_to_md.py: Python script with RST to Markdown conversion - Handles headers, code blocks, images, links, lists, tables - Preserves HTML blocks and special formatting - Converts Sphinx-specific directives appropriately - Updated pyproject.toml: readme now points to README.md - Removed all old .rst files from repository - Created CONVERSION_SUMMARY.md: Detailed documentation of conversion results The documentation is now in modern Markdown format, compatible with: - GitHub native rendering - MkDocs documentation systems - Standard Markdown processors - Modern static site generators
- Create mkdocs.yml with comprehensive Material Design theme configuration - Organized navigation with 7 main sections (Getting Started, User Guide, Advanced, etc.) - Light/Dark mode toggle - Search functionality - Code copy button - Syntax highlighting with Pygments - Create docs/ directory with all documentation in MkDocs-compatible structure - index.md (from README.md) as homepage - All 33 documentation files (from doc/*.md) - Proper directory organization for static site generation - Configure GitHub Pages: - Deploy to gh-pages branch using mkdocs gh-deploy - HTTPS enforced - Site available at: https://georgepearse.github.io/umap/ - Status: Building - Include Material theme features: - Instant loading - Search with suggestions and highlighting - Responsive navigation - Table of contents with permalinks - Code block syntax highlighting and copy button - Admonitions for notes, warnings, etc. - Math support (MathJax) - Task lists - Emoji support - Mermaid diagram support
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Summary
Updates the README installation documentation to recommend
uvas the primary installation method, withpipas an alternative. This aligns with modern Python packaging best practices.Changes
uv pip install umap-learnuv venvanduv pip install -e .Testing