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FabianHofmannpre-commit-ci[bot]
FabianHofmann
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Add Claude Code GitHub Workflow (#462)
* Claude PR Assistant workflow * Claude Code Review workflow * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * add CLAUDE.mc * add time limit and filtering conditions for claude code GH actions --------- Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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‎.github/workflows/claude-code-review.yml‎

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name: Claude Code Review
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on:
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pull_request:
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types: [opened]
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# Optional: Only run on specific file changes
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# paths:
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# - "src/**/*.ts"
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# - "src/**/*.tsx"
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# - "src/**/*.js"
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# - "src/**/*.jsx"
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jobs:
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claude-review:
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# Skip review for draft PRs, WIP, or explicitly skipped PRs
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if: |
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!contains(github.event.pull_request.title, '[skip-review]') &&
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!contains(github.event.pull_request.title, '[WIP]') &&
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!github.event.pull_request.draft
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runs-on: ubuntu-latest
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timeout-minutes: 30
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permissions:
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contents: read
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pull-requests: read
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issues: read
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id-token: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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fetch-depth: 1
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- name: Validate required secrets
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run: |
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if [ -z "${{ secrets.ANTHROPIC_API_KEY }}" ]; then
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echo "Error: Missing required secret ANTHROPIC_API_KEY"
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echo "Please add the ANTHROPIC_API_KEY secret to your repository settings"
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exit 1
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fi
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- name: Run Claude Code Review
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id: claude-review
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uses: anthropics/claude-code-action@beta
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with:
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anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
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# Optional: Specify model (defaults to Claude Sonnet 4, uncomment for Claude Opus 4)
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# model: "claude-opus-4-20250514"
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# Direct prompt for automated review (no @claude mention needed)
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direct_prompt: |
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Please review this pull request for the linopy optimization library. Focus on:
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- Python best practices and type safety (we use mypy for type checking)
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- Proper xarray integration patterns and dimension handling
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- Performance implications for large-scale optimization problems
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- Mathematical correctness in solver interfaces and constraint formulations
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- Memory efficiency considerations for handling large arrays
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- Test coverage and edge cases
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- Consistency with the existing codebase patterns, avoiding redundant code
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Linopy is built on xarray and provides N-dimensional labeled arrays for variables and constraints.
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Be constructive and specific in your feedback.
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# Optional: Customize review based on file types
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# direct_prompt: |
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# Review this PR focusing on:
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# - For TypeScript files: Type safety and proper interface usage
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# - For API endpoints: Security, input validation, and error handling
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# - For React components: Performance, accessibility, and best practices
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# - For tests: Coverage, edge cases, and test quality
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# Optional: Different prompts for different authors
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# direct_prompt: |
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# ${{ github.event.pull_request.author_association == 'FIRST_TIME_CONTRIBUTOR' &&
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# 'Welcome! Please review this PR from a first-time contributor. Be encouraging and provide detailed explanations for any suggestions.' ||
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# 'Please provide a thorough code review focusing on our coding standards and best practices.' }}
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# Project-specific tools for Python development
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allowed_tools: "Bash(pytest),Bash(ruff check .),Bash(ruff format .),Bash(mypy .),Bash(uv pip install -e .[dev,solvers])"
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# Optional: Skip review for certain conditions
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# if: |
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# !contains(github.event.pull_request.title, '[skip-review]') &&
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# !contains(github.event.pull_request.title, '[WIP]')

‎.github/workflows/claude.yml‎

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name: Claude Code
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on:
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issue_comment:
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types: [created]
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pull_request_review_comment:
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types: [created]
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issues:
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types: [opened, assigned]
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pull_request_review:
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types: [submitted]
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jobs:
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claude:
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# This workflow triggers when @claude is mentioned in:
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# - Issue comments (on issues or PRs)
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# - Pull request review comments (inline code comments)
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# - Pull request reviews (general review comments)
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# - New issues (in title or body)
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if: |
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(github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) ||
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(github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) ||
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(github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) ||
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(github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude')))
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runs-on: ubuntu-latest
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timeout-minutes: 30
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permissions:
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contents: read
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pull-requests: read
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issues: read
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id-token: write
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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fetch-depth: 1
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- name: Validate required secrets
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run: |
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if [ -z "${{ secrets.ANTHROPIC_API_KEY }}" ]; then
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echo "Error: Missing required secret ANTHROPIC_API_KEY"
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echo "Please add the ANTHROPIC_API_KEY secret to your repository settings"
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exit 1
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fi
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- name: Run Claude Code
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id: claude
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uses: anthropics/claude-code-action@beta
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with:
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anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
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# Optional: Specify model (defaults to Claude Sonnet 4, uncomment for Claude Opus 4)
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# model: "claude-opus-4-20250514"
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# Optional: Customize the trigger phrase (default: @claude)
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# trigger_phrase: "/claude"
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# Optional: Trigger when specific user is assigned to an issue
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# assignee_trigger: "claude-bot"
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# Project-specific tools for Python development
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allowed_tools: "Bash(pytest),Bash(ruff check .),Bash(ruff format .),Bash(mypy .),Bash(uv pip install -e .[dev,solvers])"
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# Custom instructions for linopy project
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custom_instructions: |
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You are working on linopy, a optimization library built on xarray.
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Follow these guidelines:
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- Use type hints and ensure mypy compliance
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- Follow xarray patterns for dimension handling
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- Write tests for new features or bug fixes
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- Use ruff for linting and formatting (run ruff check --fix .)
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- Place tests in the test directory with test_*.py naming
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- Maintain consistency with existing codebase patterns, avoiding redundant code
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- Consider memory efficiency for large-scale optimization problems
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# Optional: Custom environment variables for Claude
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# claude_env: |
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# NODE_ENV: test

‎.gitignore‎

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# IDE
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.idea/
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# Claude
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.claude/settings.local.json

‎CLAUDE.md‎

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# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Common Development Commands
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### Running Tests
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```bash
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# Run all tests
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pytest
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# Run tests with coverage
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pytest --cov=./ --cov-report=xml linopy --doctest-modules test
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# Run a specific test file
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pytest test/test_model.py
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# Run a specific test function
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pytest test/test_model.py::test_model_creation
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```
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### Linting and Type Checking
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```bash
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# Run linter (ruff)
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ruff check .
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ruff check --fix . # Auto-fix issues
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# Run formatter
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ruff format .
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# Run type checker
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mypy .
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# Run all pre-commit hooks
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pre-commit run --all-files
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```
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### Development Setup
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```bash
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# Create virtual environment and install development dependencies
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python -m venv venv
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source venv/bin/activate # On Windows: venv\Scripts\activate
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pip install uv
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uv pip install -e .[dev,solvers]
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```
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## High-Level Architecture
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linopy is a linear optimization library built on top of xarray, providing N-dimensional labeled arrays for variables and constraints. The architecture follows these key principles:
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### Core Components
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1. **Model** (`model.py`): Central container for optimization problems
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- Manages variables, constraints, and objective
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- Handles solver integration through abstract interfaces
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- Supports chunked operations for memory efficiency
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- Provides matrix representations for solver APIs
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2. **Variables** (`variables.py`): Multi-dimensional decision variables
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- Built on xarray.Dataset with labels, lower, and upper bounds
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- Arithmetic operations automatically create LinearExpressions
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- Support for continuous and binary variables
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- Container class (Variables) manages collections with dict-like access
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3. **Constraints** (`constraints.py`): Linear inequality/equality constraints
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- Store coefficients, variable references, signs, and RHS values
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- Support ≤, ≥, and = constraints
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- Container class (Constraints) provides organized access
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4. **Expressions** (`expressions.py`): Linear combinations of variables
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- LinearExpression: coeffs × vars + const
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- QuadraticExpression: for non-linear optimization
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- Support full arithmetic operations with automatic broadcasting
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- Special `_term` dimension for handling multiple terms
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5. **Solvers** (`solvers.py`): Abstract interface with multiple implementations
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- File-based solvers: Write LP/MPS files, call solver, parse results
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- Direct API solvers: Use Python bindings (e.g., gurobipy)
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- Automatic solver detection based on installed packages
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### Data Flow Pattern
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1. User creates Model and adds Variables with coordinates (dimensions)
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2. Variables combined into LinearExpressions through arithmetic
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3. Expressions used to create Constraints and Objective
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4. Model.solve() converts to solver format and retrieves solution
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5. Solution stored back in xarray format with original dimensions
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### Key Design Patterns
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- **xarray Integration**: All data structures use xarray for dimension handling
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- **Lazy Evaluation**: Expressions built symbolically before solving
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- **Broadcasting**: Operations automatically align dimensions
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- **Solver Abstraction**: Clean separation between model and solver specifics
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- **Memory Efficiency**: Support for dask arrays and chunked operations
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When modifying the codebase, maintain consistency with these patterns and ensure new features integrate naturally with the xarray-based architecture.
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## Working with the Github Repository
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* The main branch is `master`.
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* Always create a feature branch for new features or bug fixes.
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* Use the github cli (gh) to interact with the Github repository.
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### GitHub Claude Code Integration
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This repository includes Claude Code GitHub Actions for automated assistance:
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1. **Automated PR Reviews** (`claude-code-review.yml`):
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- Automatically reviews PRs only when first created (opened)
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- Subsequent reviews require manual `@claude` mention
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- Focuses on Python best practices, xarray patterns, and optimization correctness
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- Can run tests and linting as part of the review
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- **Skip initial review by**: Adding `[skip-review]` or `[WIP]` to PR title, or using draft PRs
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2. **Manual Claude Assistance** (`claude.yml`):
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- Trigger by mentioning `@claude` in any:
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- Issue comments
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- Pull request comments
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- Pull request reviews
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- New issue body or title
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- Claude can help with bug fixes, feature implementation, code explanations, etc.
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**Note**: Both workflows require the `ANTHROPIC_API_KEY` secret to be configured in the repository settings.
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## Development Guidelines
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1. Always write tests for new features or bug fixes.
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2. Always run the tests after making changes and ensure they pass.
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3. Always use ruff for linting and formatting, run `ruff check --fix .` to auto-fix issues.
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4. Use type hints and mypy for type checking.
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5. Always write tests into the `test` directory, following the naming convention `test_*.py`.
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6. Always write temporary and non git-tracked code in the `dev-scripts` directory.

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