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CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

Development Environment Setup

Poetry Environment Activation:

source $(poetry env info --path)/bin/activate

Install Dependencies:

poetry install

Common Development Commands

Code Quality:

# Format code with black
source $(poetry env info --path)/bin/activate && black .

# Run linter
source $(poetry env info --path)/bin/activate && flake8 .

# Run all pre-commit hooks
pre-commit run --all-files

Testing:

# Run all tests
source $(poetry env info --path)/bin/activate && python -m pytest

# Run specific test file
source $(poetry env info --path)/bin/activate && python -m pytest tests/path/to/test_file.py

# Run tests with specific pattern
source $(poetry env info --path)/bin/activate && python -m pytest -k "test_pattern"

Dependency Management:

# Check for unused dependencies
source $(poetry env info --path)/bin/activate && deptry .

Code Architecture

Core Components:

  1. Models Package (pypsdm/models/):

    • input/: Input data models for grid components and participants
    • result/: Result data models for simulation outputs
    • ts/: Time series data types and utilities
    • gwr.py: Main GridWithResults class combining input and result data

  2. Key Classes:

    • GridWithResults: Main facade combining grid model and simulation results
    • GridContainer: Contains raw grid elements and system participants
    • GridResultContainer: Contains simulation results for grid and participants
    • SystemParticipantsContainer: Manages participants (loads, PVs, storage, etc.)

  3. Data Flow:

    • CSV files → Container classes → Analysis/Plotting
    • Input models define grid structure and participant parameters
    • Result models contain time series simulation outputs
    • GridWithResults provides unified interface for analysis

Supported Grid Elements:

  • Nodes, lines, transformers, switches
  • Participants: loads, PVs, storage, EVs, heat pumps, biomass plants, wind energy converters
  • Time series data with complex power values

Key Features:

  • CSV-based data I/O with configurable delimiters
  • Plotting utilities for grid visualization and result analysis
  • Pandapower conversion capabilities
  • Database integration for weather and geographic data
  • Numba-optimized processing for performance

Code Style Configuration

  • Black: Line length 88 characters
  • Flake8: Configured in setup.cfg with ignore rules for E203, E501, W503
  • isort: Black-compatible profile
  • Pre-commit hooks: black, flake8, isort

Testing Structure

  • Test resources located in tests/resources/
  • Fixtures defined in tests/conftest.py for common test data paths
  • Test data includes SimBench grids and VN_SIMONA results
  • Tests organized by module structure matching pypsdm/

Development Notes

  • Uses Poetry for dependency management
  • Python 3.11+ required
  • Dataclasses with frozen=True for immutable data structures
  • Type hints throughout codebase
  • Loguru for logging
  • Supports both input-only and input+results workflows