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CLAUDE.md

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

Project Overview

Predbat is a Home Assistant App (addon) that predicts and optimizes home battery charging/discharging based on electricity rates, solar forecasts, and historical load data. It supports inverters from GivEnergy, Solis, Huawei, SolarEdge, and Sofar, and integrates with energy providers like Octopus Energy, Kraken (EDF/E.ON), and Axle Energy VPP.

It also supports Predbat.com which is a cloud based product that does not use Home Assistant and can run in a Docker environment.

Running Tests

Tests take time to run, always save the test output to a file and then grep the file afterwards. Never just pipe the output to grep as if you search for the wrong thing you will have to re-run it again.

Tests live in apps/predbat/tests/ and are run from the coverage/ directory:

# First-time setup (creates venv and installs deps):
cd coverage
source setup.csh

# Run all tests:
./run_all

# Skip slow tests (used by CI):
./run_all --quick

# Run a specific test by name:
./run_all --test basic_rates

# Run multiple specific tests:
./run_all --test basic_rates --test units

# Run tests matching a keyword:
./run_all -k octopus_

# List all available test names:
./run_all --list

# Coverage analysis:
./run_cov --quick
# Then open htmlcov/index.html

The run_all script is a thin wrapper; you can run unit_test.py directly from the coverage/ directory (it needs to be the working directory so relative paths resolve).

Replaying a debug dump

predbat_debug_*.yaml is a full state dump, written to debug/ when switch.predbat_debug_enable is on and normally what users attach to bug reports. Replay one against the current tree with:

cd coverage
./run_all --debug_file <path-to-predbat_debug.yaml>

It lists every config item that differs from its default, recalculates the plan, and writes plan_orig.html / plan_final.json into coverage/. Add --redo to recompute rates, load model and Octopus slots instead of reusing the ones in the dump. Committed examples live in coverage/cases/*.yaml and run as golden regressions under ./run_all --test debug_cases.

Finding test order dependencies

All tests share one PredBat/HA fixture, so a test that mutates shared state without fully restoring it can make an unrelated later test fail depending on run order (see issue #5079). ./run_shuffle --hunt --quick (from coverage/) fuzzes the test order, bisects any failure down to the minimal (culprit, victim) pair, and records it so the next run looks for a different one. See "Finding test order dependencies" in docs/developing.md for the full set of modes (--bisect, --campaign).

Debugging notes

tools/debug-journal.md records what past investigations found: per-integration API quirks, symptom-to-module pointers, and traps such as stale kernel binaries and test-order pollution. Read it before debugging an integration or a "the plan is wrong" report, and add to it when you learn something a future session would want.

Code Quality

All checks are enforced via pre-commit and must pass before merging:

./run_pre_commit

Key constraints:

  • Line length: 256 chars (Black), 250 chars (Flake8)
  • Docstrings: 100% coverage required (interrogate) for all functions and classes
  • Spell checking: British English (en-gb) via CSpell; add valid unknown words to .cspell/custom-dictionary-workspace.txt (file is auto-sorted alphabetically on commit, so re-stage after running pre-commit)
  • Variable naming: lower_case_with_underscores
  • pre-commit.ci will auto-commit fixable issues (trailing whitespace, etc.) back to your PR branch — run git pull after pushing to avoid divergence

Architecture

Orchestrator Pattern

PredBat in predbat.py is the main class and uses multiple inheritance to compose its behaviour:

class PredBat(hass.Hass, Octopus, Energidataservice, Fetch, Plan, Execute, Output, UserInterface):

The main loop (update_pred()) runs every 5 minutes: fetch data → run optimization → execute plan → publish results.

Core Modules

Module Role
plan.py Optimization engine — multi-threaded search across thousands of charge/discharge window scenarios
predict.py / prediction.py Battery SOC prediction models, PV generation, load forecasting
fetch.py Pulls PV forecasts, historical load, rate data, and inverter state
execute.py Sends charge/discharge/reserve commands to inverters
output.py Creates and updates Home Assistant sensors, switches, selects
inverter.py Multi-inverter abstraction layer (GivEnergy, Solis, Huawei, SolarEdge, Sofar)
config.py Defines CONFIG_ITEMS (all user settings) and APPS_SCHEMA (YAML validation)
ha.py WebSocket + REST communication with Home Assistant
userinterface.py Manages HA input entities (switches, selects, input_numbers)
components.py Plugin registry and component lifecycle management
component_base.py Abstract base class for all pluggable components

Component/Plugin System

components.py defines a registry of 31 pluggable components (DB, HA, Web, MCP, GECloud, Octopus, Fox, Solax, Solis, Axle, Ohme, Wallbox, Kraken, etc.). Each component:

  • Inherits from ComponentBase
  • Has api_start() / api_stop() lifecycle methods
  • Can be independently enabled/disabled
  • Has health monitoring with exponential backoff
  • Routes HA events via entity prefix filtering
  • Is registered in COMPONENT_LIST by its "module.ClassName" path and imported only when enabled (load_component_class()), so startup no longer compiles every component - the components test in the quick suite imports them all instead

Key Data Flow

  1. Fetch retrieves rates (Octopus/Kraken API), solar forecasts (Solcast), historical load (HA history), and live inverter state
  2. Plan runs a search algorithm to find the optimal set of charge/discharge windows over a 48-hour horizon
  3. Execute sends the resulting commands to the inverter
  4. Output publishes the plan and metrics as HA sensor states

Storage

The Storage component provides an abstraction of saving/loading from a cache and must be used instead of direct file access.

Testing Infrastructure

unit_test.py uses TestHAInterface (from tests/test_infra.py) to mock the Home Assistant connection. Tests call create_predbat() which builds a full PredBat instance against the mock. Individual test modules in tests/ follow the naming convention test_<feature>.py with an exported run_<feature>_tests() or test_<feature>() function registered in TEST_REGISTRY in unit_test.py.

IMPORTANT Unit tests must be added for all new code.

Documentation

Documentation source lives in docs/ and is built with MkDocs:

mkdocs serve   # Live preview at http://localhost:8000

When adding a new doc page, add it to mkdocs.yml. The published site at https://springfall2008.github.io/batpred/ is built automatically from main via GitHub Actions.

GitNexus — Code Intelligence

This project is indexed by GitNexus as batpred (13494 symbols, 38059 relationships, 279 execution flows). Use the GitNexus MCP tools to understand code, assess impact, and navigate safely.

Index stale? Run node .gitnexus/run.cjs analyze from the project root — it auto-selects an available runner. No .gitnexus/run.cjs yet? npx gitnexus analyze (npm 11 crash → npm i -g gitnexus; #1939).

Always Do

  • MUST run impact analysis before editing any symbol. Before modifying a function, class, or method, run impact({target: "symbolName", direction: "upstream"}) and report the blast radius (direct callers, affected processes, risk level) to the user.
  • MUST run detect_changes() before committing to verify your changes only affect expected symbols and execution flows. For regression review, compare against the default branch: detect_changes({scope: "compare", base_ref: "main"}).
  • MUST warn the user if impact analysis returns HIGH or CRITICAL risk before proceeding with edits.
  • When exploring unfamiliar code, use query({search_query: "concept"}) to find execution flows instead of grepping. It returns process-grouped results ranked by relevance.
  • When you need full context on a specific symbol — callers, callees, which execution flows it participates in — use context({name: "symbolName"}).
  • For security review, explain({target: "fileOrSymbol"}) lists taint findings (source→sink flows; needs analyze --pdg).

Never Do

  • NEVER edit a function, class, or method without first running impact on it.
  • NEVER ignore HIGH or CRITICAL risk warnings from impact analysis.
  • NEVER rename symbols with find-and-replace — use rename which understands the call graph.
  • NEVER commit changes without running detect_changes() to check affected scope.

Resources

Resource Use for
gitnexus://repo/batpred/context Codebase overview, check index freshness
gitnexus://repo/batpred/clusters All functional areas
gitnexus://repo/batpred/processes All execution flows
gitnexus://repo/batpred/process/{name} Step-by-step execution trace

CLI

Task Read this skill file
Understand architecture / "How does X work?" .claude/skills/gitnexus/gitnexus-exploring/SKILL.md
Blast radius / "What breaks if I change X?" .claude/skills/gitnexus/gitnexus-impact-analysis/SKILL.md
Trace bugs / "Why is X failing?" .claude/skills/gitnexus/gitnexus-debugging/SKILL.md
Rename / extract / split / refactor .claude/skills/gitnexus/gitnexus-refactoring/SKILL.md
Tools, resources, schema reference .claude/skills/gitnexus/gitnexus-guide/SKILL.md
Index, status, clean, wiki CLI commands .claude/skills/gitnexus/gitnexus-cli/SKILL.md