Reporting Module

Pipeline reporting, error aggregation, and executive dashboard generation.

Pipeline Reports (pipeline_report_model.py, pipeline_io.py)

python
from infrastructure.reporting import (
    generate_pipeline_report, save_pipeline_report,
    save_validation_report, save_test_results,
    save_performance_report, save_error_summary,
)
from infrastructure.reporting.report_generator import generate_test_report

# Generate comprehensive pipeline report
report = generate_pipeline_report(
    stage_results=stage_results,
    total_duration=total_duration,
    repo_root=Path("."),
    test_results=test_data,
    validation_results=validation_data,
    performance_metrics=perf_data,
    error_summary=error_summary,
)

# Save report to file
save_pipeline_report(report, output_dir)

# Individual report sections
test_report = generate_test_report(test_data)
saved_files = save_validation_report(validation_data, output_dir)

Error Aggregation (error_aggregator.py)

python
from infrastructure.reporting import (
    ErrorAggregator, ErrorEntry,
    get_error_aggregator, reset_error_aggregator,
)

# Singleton aggregator
aggregator = get_error_aggregator()
aggregator.add_error(error_type="rendering", message="Missing figure", stage="rendering")
aggregator.add_error(error_type="validation", message="Broken link", stage="validation")

# Construct ErrorEntry directly (type and message are required)
entry = ErrorEntry(type="rendering", message="Missing figure", stage="rendering")

# Get summary and save report
summary = aggregator.get_summary()
saved = aggregator.save_report(output_dir)
reset_error_aggregator()

Executive Summaries (executive_reporter.py)

python
from infrastructure.reporting import (
    generate_executive_summary, save_executive_summary,
    collect_project_metrics, ProjectMetrics, ExecutiveSummary,
)

# Generate cross-project executive summary
summary = generate_executive_summary(repo_root, project_names)
files = save_executive_summary(summary, output_dir)

# Collect metrics for a single project
metrics = collect_project_metrics(repo_root, project_name)

Dashboard Generation (_dashboard_matplotlib.py)

python
from infrastructure.reporting import (
    generate_all_dashboards,
    generate_matplotlib_dashboard,
    generate_plotly_dashboard,
)

# Generate all dashboard formats (PNG, PDF, HTML)
files = generate_all_dashboards(executive_summary, output_dir)

# Individual dashboard types
generate_matplotlib_dashboard(summary, output_dir)
generate_plotly_dashboard(summary, output_dir)

Test Reporting (pytest_output_parser.py, report_generator.py)

python
from infrastructure.reporting.pytest_output_parser import parse_pytest_output
from infrastructure.reporting.report_generator import save_test_report_to_files

# Parse pytest output into structured data (stdout, stderr, exit_code all required)
results = parse_pytest_output(stdout_text, stderr_text, exit_code)
save_test_report_to_files(results, output_path)

Output Reporting (output_statistics.py)

python
from infrastructure.reporting import (
    collect_output_statistics,
    log_output_summary,
    write_output_statistics_reports,
)

stats = collect_output_statistics(output_dir)
log_output_summary(stats)
write_output_statistics_reports(output_dir, stats)

Multi-Project Reports

python
from infrastructure.reporting import generate_multi_project_report

# Full workflow: executive summary + dashboards + CSV exports
files = generate_multi_project_report(
    repo_root=Path("."),
    project_names=["project_a", "project_b"],
    output_dir=Path("output/executive_summary"),
)

Test Summary Generation (markdown_formatter.py)

python
from infrastructure.reporting.markdown_formatter import run_test_summary_generation
run_test_summary_generation()

Manuscript Overview (manuscript_overview.py)

python
from infrastructure.reporting.manuscript_overview import generate_manuscript_overview
overview = generate_manuscript_overview(pdf_path, output_dir, project_name)

Coverage Parsing (coverage_parser.py)

python
from infrastructure.reporting.coverage_parser import extract_coverage_percentage
passed, pct = extract_coverage_percentage(stdout_text, coverage_json_paths)