Add comprehensive code quality reporting script and CI workflow#73
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Ports the code-quality CI pipeline from Expert_op4grid_recommender to ExpertOp4Grid. The workflow installs radon, vulture, interrogate and ruff (no heavy grid2op install needed) then runs scripts/code_quality_report.py in two passes: a non-strict pass that always uploads a markdown artifact and populates the GitHub step summary, and a strict pass that fails the job on critical regressions (bare TODOs, hardcoded /home/… paths, duplicate config definitions). https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
Two issues caused the CI strict gate to fail on the existing codebase:
1. XXX was included in _TODO_RE but is used throughout alphaDeesp as a
sentinel string value ("XXX" comparisons and assignments), not as a
TODO marker. Drop it from the pattern to eliminate ~6 false positives.
2. bare_todos was treated as a critical/blocking regression gate, but
the codebase already has pre-existing TODO comments not yet linked to
issues. Demote it to informational so it appears in the report without
blocking PRs. The two remaining strict gates (hardcoded /home/... paths
and duplicate config definitions) are real portability/config issues
worth enforcing.
https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
alphaDeesp/core/alphadeesp.py
- Remove 7 dead/stub methods (load2, simulate_network_change,
get_loop_paths, isAntenna, write_g, read_g, compute_meaningful_structures)
and the trivial get_adjacency_matrix logger helper.
- Strip ~25 commented-out print-debug lines from the hot paths
(compute_best_topologies, compute_all_combinations, rank_topologies,
sort_hubs, identify_routing_buses, rank_red_loops).
- Split rank_loop_buses into three focused helpers (_bus_loop_strength,
_local_production_at_bus, _initial_inflow_between) so the outer loop
becomes a readable "for each loop, for each intermediate bus" iteration
instead of 50 lines of quadruple-nested logic.
- Tighten to_DiGraph and rank_red_loops; all 35 functions now grade A in
cyclomatic complexity (was: several B).
alphaDeesp/core/graphs/overflow_graph.py
- Drop ~120 lines of commented-out dead code inside
consolidate_constrained_path (old reasoning-flawed alternatives left
behind from a prior iteration).
- Extract build_edges_from_df into a color-dispatch helper (_edge_color)
and a single add-edge helper (_add_overflow_edge); module-level
_TARGET_MAX_PENWIDTH / _MIN_PENWIDTH constants replace the inline magic
numbers.
- Extract _recolor_ambiguous_as_blue so consolidate_constrained_path
reads as two symmetric amont/aval passes.
- Condense highlight_swapped_flows, plot, and _setup_null_flow_styles.
Tests
- Split the 1390-line test_graphs_and_paths_unit.py (C 0.00) into 5
focused A-grade modules + a shared graphs_test_helpers.py:
test_graph_utils.py (delete_color_edges, nodepath_to_edgepath,
incident_edges, from_edges_get_nodes,
find_multidigraph_edges_by_name,
all_simple_edge_paths_multi)
test_shortest_paths.py (shortest_path_with_promoted_edges,
shortest_path_min_weight_then_hops)
test_constrained_path.py (ConstrainedPath)
test_null_flow.py (add/remove_double_edges_null_redispatch,
_setup_null_flow_styles, null-flow helpers)
test_overflow_graph.py (keep_overloads_components,
collapse_red_loops, scaling,
detect_edges_to_keep + helpers)
- Add new unit tests for the extracted helpers: _bus_loop_strength,
_local_production_at_bus, _initial_inflow_between, to_DiGraph,
_edge_color, _recolor_ambiguous_as_blue.
Tests: 184 passing (was 165; +19). No module is C-grade anymore;
only alphadeesp.py and overflow_graph.py remain B, every other module
is A.
https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
Extract four mixin modules to bring every file to MI grade A (was B): - core/topology_scorer.py — scoring helpers for AlphaDeesp - core/topo_applicator.py — busbar-split graph-mutation helpers - core/graphs/null_flow_graph.py — null-flow redispatch logic (refactored _prepare_detect_edges_inputs into _preprocess_gc_edges + _preprocess_gc_nodes; _detect_edges_for_target_path split into four static strategy helpers) - core/graphs/graph_consolidation.py — consolidation/disambiguation methods (_run_consolidation_loop, _is_ambiguous_component extracted) All 76 modules now grade A (was: 2×B, 0 A for the two target files). 233 tests pass (+49 over previous 184). New test files: - tests/test_topology_scorer.py (get_prod_conso_sum, get_bus_id_from_edge, is_connected_to_cpath, _collect_flows_on_bus, _score_not_connected_to_cpath) - tests/test_topo_applicator.py (_compute_prod_load_per_bus, _classify_bus) Extended tests/test_alphadeesp_unit.py with: - TestLegalComb, TestComputeAllCombinations, TestFilterConstrainedPath, TestCleanAndSortBestTopologies https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
Drop Tuple, ExtremityLine, OriginLine — all moved to the mixin modules. https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
…e Pypownet - Extract D-grade monolith into four focused helpers: _compute_overload_counts (A/5), _compute_line_flags (B/10), _compute_cut_load_percent (A/1), _resolve_score (C/15). Main function drops to A(1); module MI improves to A (24.69). - Reorder main.py so Grid2OP is the first (default) branch. - Add DeprecationWarning + logger.warning when Pypownet is selected. - Update config.ini comment to mark Pypownet as deprecated/unmaintained. https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
Move the four pure-numpy helpers (_compute_overload_counts, _compute_line_flags, _compute_cut_load_percent, _resolve_score) from Grid2opSimulation.py into a new grid2op/scoring.py module that has no grid2op dependency, making them unit-testable without the full grid2op package installed. Add alphaDeesp/tests/test_score_helpers.py with 42 tests covering every branch of all four helpers (8 overload-count cases, 15 flag-logic cases, 6 cut-load cases, 13 resolve-score cases including every scoring branch). https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi
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Summary
Introduces an automated code quality reporting system that aggregates multiple static analysis tools into a single markdown report, along with a GitHub Actions workflow to run it on every push and pull request.
Key Changes
New Script:
scripts/code_quality_report.pyA comprehensive code quality analysis tool that:
Aggregates 10 different metrics into a single markdown report:
Implements critical regression gates (strict mode):
/home/<user>/...absolute pathsconfig*.pyfilesProvides flexible output options:
--output--github-summary--strictmode when critical issues are foundNew Workflow:
.github/workflows/code-quality.ymlA GitHub Actions workflow that:
Notable Implementation Details
https://claude.ai/code/session_01Mjev1wwsV1drJ219tGThWi