gbanyan
c10d59548f
- Create test_report_cmd.py with 9 comprehensive tests - Test fixtures: test_config (minimal YAML), populated_db (synthetic scored_genes data) - Test coverage: help output, file generation, tier counts, visualizations, skip flags, custom thresholds, error handling, custom output directory - Synthetic data design: 3 HIGH, 5 MEDIUM, 5 LOW, 4 EXCLUDED, 3 NULL composite_score - All tests pass with isolated tmp_path DuckDB instances - Fixed report_cmd.py tier threshold format (uppercase keys: HIGH/MEDIUM/LOW, composite_score field) - Fixed write_candidate_output parameter name (filename_base not base_filename)
309 lines
9.9 KiB
Python
309 lines
9.9 KiB
Python
"""Integration tests for report CLI command using CliRunner.
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Tests:
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- report --help
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- Full report generation with tiered candidates
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- Tier counts in CLI output
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- Visualization generation
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- --skip-viz flag
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- --skip-report flag
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- Custom tier thresholds
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- Missing scored_genes error handling
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- Custom output directory
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"""
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import tempfile
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from pathlib import Path
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import polars as pl
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import pytest
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import duckdb
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from click.testing import CliRunner
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from usher_pipeline.cli.main import cli
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@pytest.fixture
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def test_config(tmp_path):
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"""Create minimal config YAML for testing."""
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config_path = tmp_path / "test_config.yaml"
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config_content = f"""
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versions:
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ensembl_release: "111"
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gnomad_version: "v4.1"
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gtex_version: "v8"
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hpa_version: "v23"
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data_dir: {tmp_path}/data
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cache_dir: {tmp_path}/cache
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duckdb_path: {tmp_path}/test.duckdb
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api:
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rate_limit_per_second: 3
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max_retries: 3
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cache_ttl_seconds: 3600
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timeout_seconds: 30
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scoring:
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gnomad: 0.20
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expression: 0.15
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annotation: 0.15
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localization: 0.15
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animal_model: 0.15
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literature: 0.20
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"""
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config_path.write_text(config_content)
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return config_path
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@pytest.fixture
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def populated_db(tmp_path):
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"""Create DuckDB with gene_universe and scored_genes tables."""
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db_path = tmp_path / "test.duckdb"
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conn = duckdb.connect(str(db_path))
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# Create gene_universe table (20 synthetic genes)
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gene_universe_df = pl.DataFrame({
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"gene_id": [f"ENSG{i:011d}" for i in range(1, 21)],
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"gene_symbol": [f"GENE{i}" for i in range(1, 21)],
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})
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conn.execute("CREATE TABLE gene_universe AS SELECT * FROM gene_universe_df")
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# Create scored_genes table
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# Design: 3 HIGH (score 0.7-0.95, evidence 3-5), 5 MEDIUM, 5 LOW, 4 EXCLUDED (score < 0.2), 3 NULL composite_score
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scored_genes_df = pl.DataFrame({
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"gene_id": [f"ENSG{i:011d}" for i in range(1, 21)],
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"gene_symbol": [f"GENE{i}" for i in range(1, 21)],
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# HIGH tier: genes 1-3
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"composite_score": [0.95, 0.85, 0.75] +
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# MEDIUM tier: genes 4-8
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[0.65, 0.55, 0.45, 0.42, 0.40] +
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# LOW tier: genes 9-13
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[0.35, 0.30, 0.25, 0.22, 0.20] +
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# EXCLUDED: genes 14-17
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[0.15, 0.10, 0.05, 0.02] +
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# NULL: genes 18-20
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[None, None, None],
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"evidence_count": [5, 4, 3] + # HIGH
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[3, 2, 2, 2, 2] + # MEDIUM
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[1, 1, 1, 1, 1] + # LOW
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[1, 1, 0, 0] + # EXCLUDED
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[0, 0, 0], # NULL
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"quality_flag": ["sufficient_evidence"] * 3 +
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["sufficient_evidence", "moderate_evidence", "moderate_evidence", "moderate_evidence", "moderate_evidence"] +
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["sparse_evidence"] * 5 +
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["sparse_evidence", "sparse_evidence", "no_evidence", "no_evidence"] +
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["no_evidence"] * 3,
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# Layer scores (simplified)
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"gnomad_score": [0.9] * 20,
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"expression_score": [0.8] * 20,
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"annotation_score": [0.7] * 20,
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"localization_score": [0.6] * 20,
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"animal_model_score": [0.5] * 20,
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"literature_score": [0.4] * 20,
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# Contribution columns
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"gnomad_contribution": [0.18] * 20,
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"expression_contribution": [0.12] * 20,
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"annotation_contribution": [0.105] * 20,
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"localization_contribution": [0.09] * 20,
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"animal_model_contribution": [0.075] * 20,
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"literature_contribution": [0.08] * 20,
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# Weighted average metadata
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"available_weight": [1.0] * 20,
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"weighted_sum": [0.65] * 20,
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})
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conn.execute("CREATE TABLE scored_genes AS SELECT * FROM scored_genes_df")
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# Register checkpoint
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conn.execute("""
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CREATE TABLE IF NOT EXISTS _checkpoints (
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table_name VARCHAR PRIMARY KEY,
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created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
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)
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""")
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conn.execute("INSERT INTO _checkpoints (table_name) VALUES ('scored_genes')")
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conn.close()
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return db_path
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def test_report_help(test_config):
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"""Test report --help shows all options."""
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runner = CliRunner()
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result = runner.invoke(cli, ['--config', str(test_config), 'report', '--help'])
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assert result.exit_code == 0
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assert '--output-dir' in result.output
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assert '--force' in result.output
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assert '--skip-viz' in result.output
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assert '--skip-report' in result.output
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assert '--high-threshold' in result.output
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assert '--medium-threshold' in result.output
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assert '--low-threshold' in result.output
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assert '--min-evidence-high' in result.output
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assert '--min-evidence-medium' in result.output
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def test_report_generates_files(test_config, populated_db):
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"""Test report generates candidates.tsv, candidates.parquet, and provenance."""
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runner = CliRunner()
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report'
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])
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assert result.exit_code == 0
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# Check output files exist
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output_dir = test_config.parent / "data" / "report"
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assert (output_dir / "candidates.tsv").exists()
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assert (output_dir / "candidates.parquet").exists()
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assert (output_dir / "candidates.provenance.yaml").exists()
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def test_report_tier_counts_in_output(test_config, populated_db):
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"""Test report CLI output shows tier counts."""
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runner = CliRunner()
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report'
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])
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assert result.exit_code == 0
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# Expected: 3 HIGH, 5 MEDIUM, 5 LOW (from synthetic data design)
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assert 'HIGH' in result.output
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assert 'MEDIUM' in result.output
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assert 'LOW' in result.output
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# Check for counts (flexible regex since exact format may vary)
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assert '3' in result.output # HIGH count
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assert '5' in result.output # MEDIUM and LOW counts
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def test_report_with_viz(test_config, populated_db):
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"""Test report generates plots by default."""
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runner = CliRunner()
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report'
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])
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assert result.exit_code == 0
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# Check plots directory and files exist
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plots_dir = test_config.parent / "data" / "report" / "plots"
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assert plots_dir.exists()
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assert (plots_dir / "score_distribution.png").exists()
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assert (plots_dir / "layer_contributions.png").exists()
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assert (plots_dir / "tier_breakdown.png").exists()
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def test_report_skip_viz(test_config, populated_db, tmp_path):
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"""Test --skip-viz flag skips visualization generation."""
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runner = CliRunner()
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# Use different output dir to avoid conflict with previous test
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custom_output = tmp_path / "output_no_viz"
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report',
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'--output-dir', str(custom_output),
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'--skip-viz'
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])
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assert result.exit_code == 0
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assert 'Skipping visualizations' in result.output
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# Plots directory should not exist
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plots_dir = custom_output / "plots"
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assert not plots_dir.exists() or not any(plots_dir.iterdir())
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def test_report_skip_report(test_config, populated_db, tmp_path):
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"""Test --skip-report flag skips reproducibility report generation."""
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runner = CliRunner()
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custom_output = tmp_path / "output_no_report"
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report',
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'--output-dir', str(custom_output),
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'--skip-report'
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])
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assert result.exit_code == 0
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assert 'Skipping reproducibility report' in result.output
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# Reproducibility files should not exist
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assert not (custom_output / "reproducibility.json").exists()
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assert not (custom_output / "reproducibility.md").exists()
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def test_report_custom_thresholds(test_config, populated_db, tmp_path):
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"""Test custom tier thresholds produce different tier counts."""
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runner = CliRunner()
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custom_output = tmp_path / "output_custom_thresholds"
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# Use higher thresholds: HIGH >= 0.8, MEDIUM >= 0.5, LOW >= 0.2
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report',
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'--output-dir', str(custom_output),
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'--high-threshold', '0.8',
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'--medium-threshold', '0.5',
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'--low-threshold', '0.2'
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])
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assert result.exit_code == 0
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# With these thresholds:
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# HIGH: genes 1-2 (scores 0.95, 0.85)
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# MEDIUM: genes 3-6 (scores 0.75, 0.65, 0.55, 0.45 - but need evidence >= 2)
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# LOW: remaining above 0.2
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# Should see different counts than default
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# Load the output and verify tier distribution changed
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candidates_df = pl.read_parquet(custom_output / "candidates.parquet")
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high_count = candidates_df.filter(candidates_df['confidence_tier'] == 'HIGH').height
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assert high_count == 2 # Only genes with score >= 0.8 and evidence >= 3
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def test_report_no_scored_genes_error(test_config, tmp_path):
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"""Test report with missing scored_genes table produces clear error."""
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# Create empty DuckDB (no scored_genes table)
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empty_db_path = tmp_path / "empty.duckdb"
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conn = duckdb.connect(str(empty_db_path))
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conn.close()
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runner = CliRunner()
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report'
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])
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assert result.exit_code != 0
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assert "Run 'usher-pipeline score' first" in result.output
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def test_report_output_dir_option(test_config, populated_db, tmp_path):
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"""Test --output-dir option creates files in custom location."""
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runner = CliRunner()
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custom_output = tmp_path / "custom_report_dir"
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result = runner.invoke(cli, [
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'--config', str(test_config),
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'report',
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'--output-dir', str(custom_output)
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])
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assert result.exit_code == 0
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# Files should be in custom directory
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assert (custom_output / "candidates.tsv").exists()
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assert (custom_output / "candidates.parquet").exists()
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assert (custom_output / "candidates.provenance.yaml").exists()
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