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Zhongwei Li
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skills/analyze-regressions/generate_html_report.py
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315
skills/analyze-regressions/generate_html_report.py
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#!/usr/bin/env python3
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"""
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Generate HTML component health report from JSON data.
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This script reads regression data and generates an interactive HTML report
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using the template. It handles all the data processing and HTML generation.
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Usage:
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python3 generate_html_report.py --release 4.20 --data data.json --output report.html
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Or pipe JSON data directly:
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cat data.json | python3 generate_html_report.py --release 4.20 --output report.html
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"""
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import json
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import sys
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import argparse
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from pathlib import Path
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from datetime import datetime
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def format_hours_to_days(hours):
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"""Convert hours to days with one decimal place."""
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if hours is None:
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return "N/A"
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return f"{hours / 24:.1f}"
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def get_grade_class(value, thresholds, reverse=False):
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"""
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Get CSS class based on value and thresholds.
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Args:
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value: The value to grade
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thresholds: Dict with 'excellent', 'good', 'warning' keys
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reverse: If True, lower is better (for time metrics)
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"""
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if value is None:
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return "poor"
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if reverse:
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if value < thresholds['excellent']:
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return "good"
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elif value < thresholds['good']:
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return "good"
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elif value < thresholds['warning']:
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return "warning"
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else:
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return "poor"
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else:
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if value >= thresholds['excellent']:
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return "good"
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elif value >= thresholds['good']:
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return "good"
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elif value >= thresholds['warning']:
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return "warning"
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else:
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return "poor"
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def get_grade_text(value, thresholds, reverse=False):
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"""Get grade text (emoji + text) based on value."""
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grade_class = get_grade_class(value, thresholds, reverse)
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grade_map = {
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'good': '✅ EXCELLENT',
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'warning': '⚠️ NEEDS IMPROVEMENT',
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'poor': '❌ POOR'
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}
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# Special handling for coverage and timeliness
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if not reverse: # Coverage
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if value is None:
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return '❌ POOR'
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elif value >= 90:
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return '✅ EXCELLENT'
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elif value >= 70:
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return '✅ GOOD'
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elif value >= 50:
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return '⚠️ NEEDS IMPROVEMENT'
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else:
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return '❌ POOR'
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else: # Timeliness
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if value is None:
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return 'N/A'
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elif value < 24:
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return '✅ EXCELLENT'
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elif value < 72:
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return '⚠️ GOOD'
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elif value < 168:
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return '⚠️ NEEDS IMPROVEMENT'
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else:
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return '❌ POOR'
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def get_component_grade(component_data):
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"""Calculate overall grade for a component."""
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triage_pct = component_data['summary']['triage_percentage']
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if triage_pct >= 70:
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return 'good', '✅ GOOD'
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elif triage_pct >= 50:
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return 'good', '⚠️ GOOD'
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elif triage_pct >= 25:
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return 'warning', '⚠️ NEEDS IMPROVEMENT'
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else:
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return 'poor', '❌ POOR'
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def format_time_value(value):
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"""Format time value, handling None."""
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if value is None:
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return '-'
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return f"{int(value)} hrs"
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def format_percentage_value(value):
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"""Format percentage value with grade class."""
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if value is None or value == 0:
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return '<span class="grade-poor">0.0%</span>'
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elif value >= 90:
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return f'<span class="grade-excellent">{value:.1f}%</span>'
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elif value >= 70:
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return f'<span class="grade-good">{value:.1f}%</span>'
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elif value >= 50:
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return f'<span class="grade-warning">{value:.1f}%</span>'
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else:
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return f'<span class="grade-poor">{value:.1f}%</span>'
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def generate_component_row(name, data):
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"""Generate a table row for a component."""
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summary = data['summary']
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grade_class, grade_text = get_component_grade(data)
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return f'''<tr data-grade="{grade_class}">
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<td class="component-name">{name}</td>
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<td>{summary['total']}</td>
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<td>{format_percentage_value(summary['triage_percentage'])}</td>
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<td>{format_time_value(summary['time_to_triage_hrs_avg'])}</td>
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<td>{format_time_value(summary['time_to_close_hrs_avg'])}</td>
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<td>{summary['open']['total']}</td>
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<td class="grade-{grade_class}">{grade_text}</td>
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</tr>'''
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def generate_html_report(release, data, release_dates, output_path):
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"""Generate HTML report from data."""
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template_path = Path(__file__).parent / "report_template.html"
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with open(template_path, 'r') as f:
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template = f.read()
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# Extract summary data
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summary = data['summary']
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# Calculate derived values
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triage_coverage = summary['triage_percentage']
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triage_time_avg = summary['time_to_triage_hrs_avg'] or 0
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resolution_time_avg = summary['time_to_close_hrs_avg'] or 0
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# Determine release period
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dev_start = release_dates.get('development_start', 'Unknown')
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ga_date = release_dates.get('ga')
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if dev_start != 'Unknown':
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dev_start = dev_start.split('T')[0]
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if ga_date:
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ga_date = ga_date.split('T')[0]
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release_period = f"Development Period: {dev_start} - {ga_date} (GA)"
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date_range = f"{dev_start} (Development Start) to {ga_date} (GA)"
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else:
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release_period = f"Development Period: {dev_start} - Present (In Development)"
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date_range = f"{dev_start} (Development Start) - Present"
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# Calculate grades
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triage_coverage_class = get_grade_class(triage_coverage,
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{'excellent': 90, 'good': 70, 'warning': 50})
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triage_time_class = get_grade_class(triage_time_avg,
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{'excellent': 24, 'good': 72, 'warning': 168},
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reverse=True)
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resolution_time_class = get_grade_class(resolution_time_avg,
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{'excellent': 168, 'good': 336, 'warning': 720},
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reverse=True)
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# Build component rows (sorted by health)
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components = data.get('components', {})
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component_rows = []
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for name, comp_data in sorted(components.items(),
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key=lambda x: x[1]['summary']['triage_percentage'],
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reverse=True):
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component_rows.append(generate_component_row(name, comp_data))
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# Generate attention sections
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attention_sections = []
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# Zero triage components
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zero_triage = [name for name, comp in components.items()
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if comp['summary']['triage_percentage'] == 0]
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if zero_triage:
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items = '\n'.join([f'<li><strong>{name}</strong> - {components[name]["summary"]["total"]} regressions</li>'
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for name in zero_triage])
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attention_sections.append(f'''<div class="alert-box">
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<h3>🚨 Zero Triage Coverage (0% triaged)</h3>
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<ul>
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{items}
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</ul>
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</div>''')
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# Low triage components
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low_triage = [(name, comp) for name, comp in components.items()
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if 0 < comp['summary']['triage_percentage'] < 25]
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if low_triage:
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items = '\n'.join([f'<li><strong>{name}</strong> - {comp["summary"]["total"]} regressions, only {comp["summary"]["triage_percentage"]:.1f}% triaged</li>'
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for name, comp in low_triage])
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attention_sections.append(f'''<div class="alert-box">
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<h3>⚠️ Low Triage Coverage (<25%)</h3>
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<ul>
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{items}
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</ul>
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</div>''')
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# High volume components
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high_volume = [(name, comp) for name, comp in components.items()
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if comp['summary']['total'] >= 20]
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if high_volume:
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high_volume.sort(key=lambda x: x[1]['summary']['total'], reverse=True)
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items = '\n'.join([f'<li><strong>{name}</strong> - {comp["summary"]["total"]} regressions ({comp["summary"]["triage_percentage"]:.1f}% triaged)</li>'
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for name, comp in high_volume[:5]])
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attention_sections.append(f'''<div class="alert-box">
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<h3>📊 High Regression Volume (Top 5)</h3>
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<ul>
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{items}
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</ul>
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</div>''')
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# Substitutions
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substitutions = {
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'RELEASE': release,
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'RELEASE_PERIOD': release_period,
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'DATE_RANGE': date_range,
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'TRIAGE_COVERAGE': f"{triage_coverage:.1f}",
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'TRIAGE_COVERAGE_CLASS': triage_coverage_class,
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'TRIAGE_COVERAGE_GRADE': get_grade_text(triage_coverage, {}, False),
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'TRIAGE_COVERAGE_GRADE_CLASS': f"grade-{triage_coverage_class}",
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'TOTAL_REGRESSIONS': str(summary['total']),
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'TRIAGED_REGRESSIONS': str(summary['triaged']),
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'UNTRIAGED_REGRESSIONS': str(summary['total'] - summary['triaged']),
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'TRIAGE_TIME_AVG': str(int(triage_time_avg)) if triage_time_avg else 'N/A',
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'TRIAGE_TIME_AVG_DAYS': format_hours_to_days(triage_time_avg),
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'TRIAGE_TIME_MAX': str(int(summary['time_to_triage_hrs_max'])) if summary['time_to_triage_hrs_max'] else 'N/A',
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'TRIAGE_TIME_MAX_DAYS': format_hours_to_days(summary['time_to_triage_hrs_max']),
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'TRIAGE_TIME_CLASS': triage_time_class,
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'TRIAGE_TIME_GRADE': get_grade_text(triage_time_avg, {}, True),
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'TRIAGE_TIME_GRADE_CLASS': f"grade-{triage_time_class}",
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'RESOLUTION_TIME_AVG': str(int(resolution_time_avg)) if resolution_time_avg else 'N/A',
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'RESOLUTION_TIME_AVG_DAYS': format_hours_to_days(resolution_time_avg),
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'RESOLUTION_TIME_MAX': str(int(summary['time_to_close_hrs_max'])) if summary['time_to_close_hrs_max'] else 'N/A',
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'RESOLUTION_TIME_MAX_DAYS': format_hours_to_days(summary['time_to_close_hrs_max']),
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'RESOLUTION_TIME_CLASS': resolution_time_class,
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'RESOLUTION_TIME_GRADE': get_grade_text(resolution_time_avg, {}, True),
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'RESOLUTION_TIME_GRADE_CLASS': f"grade-{resolution_time_class}",
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'OPEN_REGRESSIONS': str(summary['open']['total']),
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'OPEN_TRIAGE_PERCENTAGE': f"{summary['open']['triage_percentage']:.1f}",
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'CLOSED_REGRESSIONS': str(summary['closed']['total']),
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'CLOSED_TRIAGE_PERCENTAGE': f"{summary['closed']['triage_percentage']:.1f}",
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'OPEN_AGE_AVG': str(int(summary['open']['open_hrs_avg'])) if summary['open']['open_hrs_avg'] else 'N/A',
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'OPEN_AGE_AVG_DAYS': format_hours_to_days(summary['open']['open_hrs_avg']),
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'COMPONENT_ROWS': '\n'.join(component_rows),
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'ATTENTION_SECTIONS': '\n'.join(attention_sections),
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'INSIGHTS': '<li>Report generated automatically from regression data</li>',
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'RECOMMENDATIONS': '<li>Review components with zero triage coverage</li><li>Address high-volume components</li>',
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'GENERATED_DATE': datetime.now().strftime("%B %d, %Y"),
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}
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# Apply substitutions
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for key, value in substitutions.items():
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template = template.replace(f'{{{{{key}}}}}', value)
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# Write output
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with open(output_path, 'w') as f:
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f.write(template)
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print(f"HTML report generated: {output_path}", file=sys.stderr)
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def main():
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parser = argparse.ArgumentParser(description='Generate HTML component health report')
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parser.add_argument('--release', required=True, help='Release version (e.g., 4.20)')
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parser.add_argument('--data', help='Path to JSON data file (or read from stdin)')
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parser.add_argument('--dates', help='Path to release dates JSON file')
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parser.add_argument('--output', required=True, help='Output HTML file path')
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args = parser.parse_args()
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# Read regression data
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if args.data:
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with open(args.data, 'r') as f:
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data = json.load(f)
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else:
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data = json.load(sys.stdin)
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# Read release dates
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release_dates = {}
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if args.dates:
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with open(args.dates, 'r') as f:
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release_dates = json.load(f)
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generate_html_report(args.release, data, release_dates, args.output)
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if __name__ == '__main__':
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main()
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