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Two fixes from the previous round were incomplete: - The scheduled-message chunk budget used the schedule's explicit scope, but send_channel_message resolves an unset scope from flood_scope.<channel> and then outgoing_flood_scope_override. A schedule with an implicit regional scope was therefore sized for a global send and every chunk could overshoot once the sender added the regional header. The budget now resolves the effective scope, and assumes regional if that resolution fails, since guessing regional only ever makes chunks smaller. - Resetting _last_path_distance_km per request fixed sequential reuse but not concurrency: the decode awaits a database lookup, and the dispatcher runs handlers as independent tasks, so two path commands can interleave and render each other's distance. The distance now rides on the request's own message, with the instance attribute kept only as a fallback for direct calls. Two new findings: - rf_data_is_correlated() treated pubkey and partial-prefix matches as packet-unique, but a sender prefix identifies a sender, not one transmission. With several cached packets from the same sender, the first (usually oldest) was returned and allowed to supply a route. Those strategies now take the newest match and are authoritative only when the match is unambiguous; otherwise the entry is marked fallback, so it still provides SNR/RSSI but never a route. - The flood_scopes allowlist accepted a scope resolved from an uncorrelated fallback packet. The HMAC proves the cached packet is in an allowed scope, not that this message is, so a recent allowed-scope packet could admit an unrelated message. Scope authorisation now requires packet-bound correlation and logs plainly when it does not have it. That last one is a deliberate fail-closed change to an authorisation path that predates tonight. Channel messages normally carry raw_hex and correlate exactly, so the fallback is the exception rather than the rule, but a deployment using flood_scopes will now stay quiet in cases where it previously replied on an assumed scope.
MeshCore Bot Test Suite
This directory contains the test suite for the MeshCore Bot, focusing on graph-based path guessing functionality.
Structure
tests/
├── README.md # This file
├── conftest.py # Pytest fixtures and configuration
├── helpers.py # Test data factories and helper functions
├── unit/ # Unit tests (isolated, with mocks)
│ ├── test_mesh_graph_edges.py
│ ├── test_mesh_graph_validation.py
│ ├── test_mesh_graph_scoring.py
│ ├── test_mesh_graph_multihop.py
│ └── test_path_command_graph_selection.py
└── integration/ # Integration tests (with real database)
└── test_path_resolution.py
Running Tests
Run all tests
pytest
Run only unit tests
pytest tests/unit/
Run only integration tests
pytest tests/integration/
Run specific test file
pytest tests/unit/test_mesh_graph_edges.py
Run specific test
pytest tests/unit/test_mesh_graph_edges.py::TestMeshGraphEdges::test_add_new_edge
Run with coverage
pytest --cov=modules --cov-report=html --cov-report=term-missing
Run with verbose output
pytest -v
Run with markers
pytest -m unit # Run only unit tests
pytest -m integration # Run only integration tests
pytest -m slow # Run slow tests
Test Coverage
Unit Tests
test_mesh_graph_edges.py (15 tests)
Tests for MeshGraph edge management:
- Adding new edges
- Updating existing edges
- Public key handling
- Hop position tracking
- Geographic distance
- Edge queries (get, has, outgoing, incoming)
- Prefix normalization
test_mesh_graph_validation.py (12 tests)
Tests for path validation:
- Path segment validation
- Confidence calculation
- Recency checks
- Bidirectional edge validation
- Full path validation
- Minimum observations filtering
test_mesh_graph_scoring.py (11 tests)
Tests for candidate scoring:
- Score calculation with various edge combinations
- Bidirectional bonuses
- Hop position matching
- Geographic distance bonuses
- Minimum observations filtering
test_mesh_graph_multihop.py (12 tests)
Tests for multi-hop path inference:
- 2-hop and 3-hop path finding
- Intermediate node discovery
- Minimum observations filtering
- Bidirectional path bonuses
- Score reduction for longer paths
test_path_command_graph_selection.py (8 tests)
Tests for PathCommand._select_repeater_by_graph:
- Direct edge selection
- Stored public key bonus
- Star bias multiplier
- Multi-hop inference
- Confidence conversion
Integration Tests
test_path_resolution.py (5 tests)
End-to-end tests for full path resolution:
- Path resolution with graph edges from database
- Prefix collision resolution using graph data
- Edge persistence across graph restarts
- Graph vs geographic selection
- Real-world multi-hop scenarios
Test Fixtures
Fixtures are defined in conftest.py:
mock_logger: Mock logger for testingtest_config: Test configuration with Path_Command settingstest_db: In-memory SQLite database for testingmock_bot: Mock bot instance with all necessary attributesmesh_graph: CleanMeshGraphinstance for testingpopulated_mesh_graph:MeshGraphinstance with sample edges
Test Helpers
Helper functions in helpers.py:
create_test_repeater(): Factory for creating test repeater datacreate_test_edge(): Factory for creating test edge datacreate_test_path(): Factory for creating test path datapopulate_test_graph(): Helper to populate a graph with test edges
Writing New Tests
Unit Test Example
import pytest
from tests.helpers import create_test_edge
@pytest.mark.unit
class TestMyFeature:
def test_my_feature(self, mesh_graph):
"""Test description."""
mesh_graph.add_edge('01', '7e')
assert mesh_graph.has_edge('01', '7e')
Integration Test Example
import pytest
@pytest.mark.integration
class TestMyIntegration:
def test_my_integration(self, mock_bot, test_db):
"""Test description."""
# Use real database and bot components
pass
Test Markers
Tests are marked with:
@pytest.mark.unit: Unit tests (isolated, with mocks)@pytest.mark.integration: Integration tests (with real database)@pytest.mark.slow: Slow-running tests
Dependencies
Test dependencies are in requirements.txt:
pytest>=7.0.0pytest-asyncio>=0.21.0pytest-mock>=3.10.0pytest-cov>=4.0.0
Configuration
Pytest configuration is in pytest.ini:
- Test discovery patterns
- Async test support
- Output options
- Test markers
Notes
- Unit tests use in-memory SQLite databases for speed
- Integration tests may use real database connections
- All tests should be deterministic and not depend on external services
- Tests should clean up after themselves (fixtures handle this automatically)