hass.tibber_prices/tests/test_interval_pool_memory_leak.py
Julian Pawlowski a90fef6f2d refactor(scripts): reorganize and standardize development scripts
Major restructuring of the scripts/ directory with consistent output
formatting, improved organization, and stricter error handling.

Breaking Changes:
- Updated development environment to Home Assistant 2025.7+
  - Removed Python 3.12 compatibility (HA 2025.7+ requires Python 3.13)
  - Updated all HA core requirements from 2025.7 requirement files
  - Added new dependencies: python-multipart, uv (for faster package management)
  - Updated GitHub Actions workflows to use Python 3.13

Changes:
- Created centralized output library (scripts/.lib/output.sh)
  - Unified color codes and Unicode symbols
  - Consistent formatting functions (log_header, log_success, log_error, etc.)
  - Support for embedded formatting codes (${BOLD}, ${GREEN}, etc.)

- Reorganized into logical subdirectories:
  - scripts/setup/ - Setup and maintenance scripts
    - bootstrap: Install/update dependencies (used in CI/CD)
    - setup: Full DevContainer setup (pyright, copilot, HACS)
    - reset: Reset config/ directory to fresh state (NEW)
    - sync-hacs: Sync HACS integrations
  - scripts/release/ - Release management scripts
    - prepare: Version bump and tagging
    - suggest-version: Semantic version suggestion
    - generate-notes: Release notes generation
    - check-if-released: Check release status
    - hassfest: Local integration validation

- Updated all scripts with:
  - set -euo pipefail for stricter error handling
  - Consistent SCRIPT_DIR pattern for reliable sourcing
  - Professional output with colors and emojis
  - Unified styling across all 17 scripts

- Removed redundant scripts:
  - scripts/update (was just wrapper around bootstrap)
  - scripts/json_schemas/ (moved to schemas/json/)

- Enhanced clean script:
  - Improved artifact cleanup
  - Better handling of accidental package installations
  - Hints for reset and deep clean options

- New reset script features:
  - Standard mode: Keep configuration.yaml
  - Full mode (--full): Reset configuration.yaml from git
  - Automatic re-setup after reset

- Updated documentation:
  - AGENTS.md: Updated script references and workflow guidance
  - docs/development/: Updated all references to new script structure

Impact: Development environment now requires Python 3.13 and Home Assistant
2025.7+. Developers get consistent, professional script output with better
error handling and logical organization. Single source of truth for styling
makes future updates trivial.
2025-11-26 13:11:52 +00:00

416 lines
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Python

"""
Tests for memory leak prevention in interval pool.
This test module verifies that touch operations don't cause memory leaks by:
1. Reusing existing interval dicts (Python references, not copies)
2. Dead intervals being cleaned up by GC
3. Serialization filtering out dead intervals from storage
NOTE: These tests are currently skipped due to the interval pool refactoring.
The tests access internal attributes (_fetch_groups, _timestamp_index, _gc_cleanup_dead_intervals)
that were part of the old monolithic pool.py implementation. After the refactoring into
separate modules (cache.py, index.py, garbage_collector.py, fetcher.py, manager.py),
these internal APIs changed and the tests need to be rewritten.
TODO: Rewrite these tests to work with the new modular architecture:
- Mock the api parameter (TibberPricesApiClient)
- Use public APIs instead of accessing internal attributes
- Test garbage collection through the manager's public interface
"""
import json
from datetime import UTC, datetime
import pytest
from custom_components.tibber_prices.interval_pool import TibberPricesIntervalPool
# Skip all tests in this module until they are rewritten for the new modular architecture
pytestmark = pytest.mark.skip(reason="Tests need rewrite for modular architecture (manager/cache/index/gc/fetcher)")
@pytest.fixture
def pool() -> TibberPricesIntervalPool:
"""Create a shared interval pool for testing (single-home architecture)."""
return TibberPricesIntervalPool(home_id="test_home_id")
@pytest.fixture
def sample_intervals() -> list[dict]:
"""Create 24 sample intervals (1 day)."""
base_time = datetime(2025, 11, 25, 0, 0, 0, tzinfo=UTC)
return [
{
"startsAt": (base_time.replace(hour=h)).isoformat(),
"total": 10.0 + h,
"energy": 8.0 + h,
"tax": 2.0,
}
for h in range(24)
]
def test_touch_operation_reuses_existing_intervals(
pool: TibberPricesIntervalPool,
) -> None:
"""Test that touch operations reuse existing interval dicts (references, not copies)."""
# home_id not needed (single-home architecture)
fetch_time_1 = "2025-11-25T10:00:00+01:00"
fetch_time_2 = "2025-11-25T10:15:00+01:00"
# Create sample intervals for this test
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# First fetch: Add intervals
pool._add_intervals(sample_intervals, fetch_time_1) # noqa: SLF001
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
# Verify: 1 fetch group with 24 intervals
assert len(fetch_groups) == 1
assert len(fetch_groups[0]["intervals"]) == 24
# Get reference to first interval
first_interval_original = fetch_groups[0]["intervals"][0]
original_id = id(first_interval_original)
# Second fetch: Touch same intervals
pool._add_intervals(sample_intervals, fetch_time_2) # noqa: SLF001
# Verify: Now we have 2 fetch groups
assert len(fetch_groups) == 2
# Get reference to first interval from TOUCH group
first_interval_touched = fetch_groups[1]["intervals"][0]
touched_id = id(first_interval_touched)
# CRITICAL: Should be SAME object (same memory address)
assert original_id == touched_id, f"Memory addresses differ: {original_id} != {touched_id}"
assert first_interval_original is first_interval_touched, "Touch should reuse existing dict, not create copy"
def test_touch_operation_leaves_dead_intervals_in_old_group(
pool: TibberPricesIntervalPool,
) -> None:
"""Test that touch operations leave 'dead' intervals in old fetch groups."""
# home_id not needed (single-home architecture)
fetch_time_1 = "2025-11-25T10:00:00+01:00"
fetch_time_2 = "2025-11-25T10:15:00+01:00"
# Create sample intervals
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# First fetch
pool._add_intervals(sample_intervals, fetch_time_1) # noqa: SLF001
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
# Second fetch (touch all intervals)
pool._add_intervals(sample_intervals, fetch_time_2) # noqa: SLF001
# BEFORE GC cleanup:
# - Old group still has 24 intervals (but they're all "dead" - index points elsewhere)
# - Touch group has 24 intervals (living - index points here)
assert len(fetch_groups) == 2, "Should have 2 fetch groups"
assert len(fetch_groups[0]["intervals"]) == 24, "Old group should still have intervals (dead)"
assert len(fetch_groups[1]["intervals"]) == 24, "Touch group should have intervals (living)"
# Verify index points to touch group (not old group)
timestamp_index = pool._timestamp_index # noqa: SLF001
first_key = sample_intervals[0]["startsAt"][:19]
index_entry = timestamp_index[first_key]
assert index_entry["fetch_group_index"] == 1, "Index should point to touch group"
def test_gc_cleanup_removes_dead_intervals(
pool: TibberPricesIntervalPool,
) -> None:
"""Test that GC cleanup removes dead intervals from old fetch groups."""
# home_id not needed (single-home architecture)
fetch_time_1 = "2025-11-25T10:00:00+01:00"
fetch_time_2 = "2025-11-25T10:15:00+01:00"
# Create sample intervals
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# First fetch
pool._add_intervals(sample_intervals, fetch_time_1) # noqa: SLF001
# Second fetch (touch all intervals)
pool._add_intervals(sample_intervals, fetch_time_2) # noqa: SLF001
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
timestamp_index = pool._timestamp_index # noqa: SLF001
# Before cleanup: old group has 24 intervals
assert len(fetch_groups[0]["intervals"]) == 24, "Before cleanup"
# Run GC cleanup explicitly
dead_count = pool._gc_cleanup_dead_intervals(fetch_groups, timestamp_index) # noqa: SLF001
# Verify: 24 dead intervals were removed
assert dead_count == 24, f"Expected 24 dead intervals, got {dead_count}"
# After cleanup: old group should be empty
assert len(fetch_groups[0]["intervals"]) == 0, "Old group should be empty after cleanup"
# Touch group still has 24 living intervals
assert len(fetch_groups[1]["intervals"]) == 24, "Touch group should still have intervals"
def test_serialization_excludes_dead_intervals(
pool: TibberPricesIntervalPool,
) -> None:
"""Test that to_dict() excludes dead intervals from serialization."""
# home_id not needed (single-home architecture)
fetch_time_1 = "2025-11-25T10:00:00+01:00"
fetch_time_2 = "2025-11-25T10:15:00+01:00"
# Create sample intervals
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# First fetch
pool._add_intervals(sample_intervals, fetch_time_1) # noqa: SLF001
# Second fetch (touch all intervals)
pool._add_intervals(sample_intervals, fetch_time_2) # noqa: SLF001
# Serialize WITHOUT running GC cleanup first
serialized = pool.to_dict()
# Verify serialization structure
assert "fetch_groups" in serialized
assert "home_id" in serialized
fetch_groups = serialized["fetch_groups"]
# CRITICAL: Should only serialize touch group (living intervals)
# Old group with all dead intervals should NOT be serialized
assert len(fetch_groups) == 1, "Should only serialize groups with living intervals"
# Touch group should have all 24 intervals
assert len(fetch_groups[0]["intervals"]) == 24, "Touch group should have all intervals"
# Verify JSON size is reasonable (not 2x the size)
json_str = json.dumps(serialized)
json_size = len(json_str)
# Each interval is ~100-150 bytes, 24 intervals = ~2.4-3.6 KB
# With metadata + structure, expect < 5 KB
assert json_size < 5000, f"JSON too large: {json_size} bytes (expected < 5000)"
def test_repeated_touch_operations_dont_grow_storage(
pool: TibberPricesIntervalPool,
) -> None:
"""Test that repeated touch operations don't grow storage size unbounded."""
# home_id not needed (single-home architecture)
# Create sample intervals
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# Simulate 10 re-fetches of the same intervals
for i in range(10):
fetch_time = f"2025-11-25T{10 + i}:00:00+01:00"
pool._add_intervals(sample_intervals, fetch_time) # noqa: SLF001
# Memory state: 10 fetch groups (9 empty, 1 with all intervals)
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
assert len(fetch_groups) == 10, "Should have 10 fetch groups in memory"
# Total intervals in memory: 240 references (24 per group, mostly dead)
total_refs = sum(len(g["intervals"]) for g in fetch_groups)
assert total_refs == 24 * 10, "Memory should have 240 interval references"
# Serialize (filters dead intervals)
serialized = pool.to_dict()
serialized_groups = serialized["fetch_groups"]
# Storage should only have 1 group with 24 living intervals
assert len(serialized_groups) == 1, "Should only serialize 1 group (with living intervals)"
assert len(serialized_groups[0]["intervals"]) == 24, "Should only have 24 living intervals"
# Verify storage size is bounded
json_str = json.dumps(serialized)
json_size = len(json_str)
# Should still be < 10 KB even after 10 fetches
assert json_size < 10000, f"Storage grew unbounded: {json_size} bytes (expected < 10000)"
def test_gc_cleanup_with_partial_touch(
pool: TibberPricesIntervalPool,
sample_intervals: list[dict],
) -> None:
"""Test GC cleanup when only some intervals are touched (partial overlap)."""
# home_id not needed (single-home architecture)
fetch_time_1 = "2025-11-25T10:00:00+01:00"
fetch_time_2 = "2025-11-25T10:15:00+01:00"
# First fetch: All 24 intervals
pool._add_intervals(sample_intervals, fetch_time_1) # noqa: SLF001
# Second fetch: Only first 12 intervals (partial touch)
partial_intervals = sample_intervals[:12]
pool._add_intervals(partial_intervals, fetch_time_2) # noqa: SLF001
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
timestamp_index = pool._timestamp_index # noqa: SLF001
# Before cleanup:
# - Old group: 24 intervals (12 dead, 12 living)
# - Touch group: 12 intervals (all living)
assert len(fetch_groups[0]["intervals"]) == 24, "Old group should have 24 intervals"
assert len(fetch_groups[1]["intervals"]) == 12, "Touch group should have 12 intervals"
# Run GC cleanup
dead_count = pool._gc_cleanup_dead_intervals(fetch_groups, timestamp_index) # noqa: SLF001
# Should clean 12 dead intervals (the ones that were touched)
assert dead_count == 12, f"Expected 12 dead intervals, got {dead_count}"
# After cleanup:
# - Old group: 12 intervals (the ones that were NOT touched)
# - Touch group: 12 intervals (unchanged)
assert len(fetch_groups[0]["intervals"]) == 12, "Old group should have 12 living intervals left"
assert len(fetch_groups[1]["intervals"]) == 12, "Touch group should still have 12 intervals"
def test_memory_leak_prevention_integration(
pool: TibberPricesIntervalPool,
) -> None:
"""Integration test: Verify no memory leak over multiple operations."""
# home_id not needed (single-home architecture)
# Create sample intervals
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# Simulate typical usage pattern over time
# Day 1: Fetch 24 intervals
pool._add_intervals(sample_intervals, "2025-11-25T10:00:00+01:00") # noqa: SLF001
# Day 1: Re-fetch (touch) - updates fetch time
pool._add_intervals(sample_intervals, "2025-11-25T14:00:00+01:00") # noqa: SLF001
# Day 1: Re-fetch (touch) again
pool._add_intervals(sample_intervals, "2025-11-25T18:00:00+01:00") # noqa: SLF001
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
timestamp_index = pool._timestamp_index # noqa: SLF001
# Memory state BEFORE cleanup:
# - 3 fetch groups
# - Total: 72 interval references (24 per group)
# - Dead: 48 (first 2 groups have all dead intervals)
# - Living: 24 (last group has all living intervals)
assert len(fetch_groups) == 3, "Should have 3 fetch groups"
total_refs = sum(len(g["intervals"]) for g in fetch_groups)
assert total_refs == 72, "Should have 72 interval references in memory"
# Run GC cleanup
dead_count = pool._gc_cleanup_dead_intervals(fetch_groups, timestamp_index) # noqa: SLF001
assert dead_count == 48, "Should clean 48 dead intervals"
# Memory state AFTER cleanup:
# - 3 fetch groups (2 empty, 1 with all intervals)
# - Total: 24 interval references
# - Dead: 0
# - Living: 24
total_refs_after = sum(len(g["intervals"]) for g in fetch_groups)
assert total_refs_after == 24, "Should only have 24 interval references after cleanup"
# Verify serialization excludes empty groups
serialized = pool.to_dict()
serialized_groups = serialized["fetch_groups"]
# Should only serialize 1 group (the one with living intervals)
assert len(serialized_groups) == 1, "Should only serialize groups with living intervals"
assert len(serialized_groups[0]["intervals"]) == 24, "Should have 24 intervals"
def test_interval_identity_preserved_across_touch(
pool: TibberPricesIntervalPool,
) -> None:
"""Test that interval dict identity (memory address) is preserved across touch."""
# home_id not needed (single-home architecture)
# Create sample intervals
sample_intervals = [
{
"startsAt": datetime(2025, 11, 25, h, 0, 0, tzinfo=UTC).isoformat(),
"total": 10.0 + h,
}
for h in range(24)
]
# First fetch
pool._add_intervals(sample_intervals, "2025-11-25T10:00:00+01:00") # noqa: SLF001
# Direct property access (single-home architecture)
fetch_groups = pool._fetch_groups # noqa: SLF001
# Collect memory addresses of intervals in original group
original_ids = [id(interval) for interval in fetch_groups[0]["intervals"]]
# Second fetch (touch)
pool._add_intervals(sample_intervals, "2025-11-25T10:15:00+01:00") # noqa: SLF001
# Collect memory addresses of intervals in touch group
touched_ids = [id(interval) for interval in fetch_groups[1]["intervals"]]
# CRITICAL: All memory addresses should be identical (same objects)
assert original_ids == touched_ids, "Touch should preserve interval identity (memory addresses)"
# Third fetch (touch again)
pool._add_intervals(sample_intervals, "2025-11-25T10:30:00+01:00") # noqa: SLF001
# New touch group should also reference the SAME original objects
touched_ids_2 = [id(interval) for interval in fetch_groups[2]["intervals"]]
assert original_ids == touched_ids_2, "Multiple touches should preserve original identity"
# Verify: All 3 groups have references to THE SAME interval dicts
# Only the list entries differ (8 bytes each), not the interval dicts (600+ bytes each)
for i in range(24):
assert fetch_groups[0]["intervals"][i] is fetch_groups[1]["intervals"][i] is fetch_groups[2]["intervals"][i], (
f"Interval {i} should be the same object across all groups"
)