mirror of
https://github.com/pacnpal/thrillwiki_django_no_react.git
synced 2025-12-22 10:31:09 -05:00
chore: fix pghistory migration deps and improve htmx utilities
- Update pghistory dependency from 0007 to 0006 in account migrations - Add docstrings and remove unused imports in htmx_forms.py - Add DJANGO_SETTINGS_MODULE bash commands to Claude settings - Add state transition definitions for ride statuses
This commit is contained in:
pacnpal
@@ -0,0 +1,276 @@
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"""
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Management command for analyzing state transition patterns.
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This command provides insights into transition usage, patterns, and statistics
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across all models using django-fsm-log.
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"""
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from django.core.management.base import BaseCommand
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from django.db.models import Count, Avg, F
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from django.utils import timezone
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from datetime import timedelta
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from django_fsm_log.models import StateLog
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from django.contrib.contenttypes.models import ContentType
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class Command(BaseCommand):
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help = 'Analyze state transition patterns and generate statistics'
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def add_arguments(self, parser):
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parser.add_argument(
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'--days',
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type=int,
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default=30,
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help='Number of days to analyze (default: 30)'
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)
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parser.add_argument(
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'--model',
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type=str,
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help='Specific model to analyze (e.g., editsubmission)'
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)
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parser.add_argument(
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'--output',
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type=str,
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choices=['console', 'json', 'csv'],
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default='console',
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help='Output format (default: console)'
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)
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def handle(self, *args, **options):
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days = options['days']
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model_filter = options['model']
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output_format = options['output']
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self.stdout.write(
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self.style.SUCCESS(f'\n=== State Transition Analysis (Last {days} days) ===\n')
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)
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# Filter by date range
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start_date = timezone.now() - timedelta(days=days)
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queryset = StateLog.objects.filter(timestamp__gte=start_date)
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# Filter by specific model if provided
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if model_filter:
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try:
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content_type = ContentType.objects.get(model=model_filter.lower())
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queryset = queryset.filter(content_type=content_type)
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self.stdout.write(f'Filtering for model: {model_filter}\n')
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except ContentType.DoesNotExist:
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self.stdout.write(
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self.style.ERROR(f'Model "{model_filter}" not found')
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)
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return
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# Total transitions
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total_transitions = queryset.count()
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self.stdout.write(
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self.style.SUCCESS(f'Total Transitions: {total_transitions}\n')
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)
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if total_transitions == 0:
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self.stdout.write(
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self.style.WARNING('No transitions found in the specified period.')
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)
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return
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# Most common transitions
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self.stdout.write(self.style.SUCCESS('\n--- Most Common Transitions ---'))
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common_transitions = (
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queryset.values('transition', 'content_type__model')
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.annotate(count=Count('id'))
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.order_by('-count')[:10]
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)
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for t in common_transitions:
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model_name = t['content_type__model']
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transition_name = t['transition'] or 'N/A'
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count = t['count']
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percentage = (count / total_transitions) * 100
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self.stdout.write(
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f" {model_name}.{transition_name}: {count} ({percentage:.1f}%)"
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)
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# Transitions by model
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self.stdout.write(self.style.SUCCESS('\n--- Transitions by Model ---'))
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by_model = (
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queryset.values('content_type__model')
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.annotate(count=Count('id'))
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.order_by('-count')
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)
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for m in by_model:
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model_name = m['content_type__model']
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count = m['count']
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percentage = (count / total_transitions) * 100
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self.stdout.write(
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f" {model_name}: {count} ({percentage:.1f}%)"
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)
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# Transitions by state
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self.stdout.write(self.style.SUCCESS('\n--- Final States Distribution ---'))
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by_state = (
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queryset.values('state')
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.annotate(count=Count('id'))
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.order_by('-count')
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)
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for s in by_state:
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state_name = s['state']
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count = s['count']
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percentage = (count / total_transitions) * 100
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self.stdout.write(
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f" {state_name}: {count} ({percentage:.1f}%)"
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)
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# Most active users
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self.stdout.write(self.style.SUCCESS('\n--- Most Active Users ---'))
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active_users = (
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queryset.exclude(by__isnull=True)
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.values('by__username', 'by__id')
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.annotate(count=Count('id'))
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.order_by('-count')[:10]
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)
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for u in active_users:
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username = u['by__username']
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user_id = u['by__id']
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count = u['count']
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self.stdout.write(
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f" {username} (ID: {user_id}): {count} transitions"
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)
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# System vs User transitions
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system_count = queryset.filter(by__isnull=True).count()
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user_count = queryset.exclude(by__isnull=True).count()
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self.stdout.write(self.style.SUCCESS('\n--- Transition Attribution ---'))
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self.stdout.write(f" User-initiated: {user_count} ({(user_count/total_transitions)*100:.1f}%)")
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self.stdout.write(f" System-initiated: {system_count} ({(system_count/total_transitions)*100:.1f}%)")
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# Daily transition volume
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self.stdout.write(self.style.SUCCESS('\n--- Daily Transition Volume ---'))
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daily_stats = (
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queryset.extra(select={'day': 'date(timestamp)'})
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.values('day')
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.annotate(count=Count('id'))
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.order_by('-day')[:7]
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)
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for day in daily_stats:
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date = day['day']
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count = day['count']
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self.stdout.write(f" {date}: {count} transitions")
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# Busiest hours
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self.stdout.write(self.style.SUCCESS('\n--- Busiest Hours (UTC) ---'))
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hourly_stats = (
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queryset.extra(select={'hour': 'extract(hour from timestamp)'})
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.values('hour')
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.annotate(count=Count('id'))
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.order_by('-count')[:5]
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)
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for hour in hourly_stats:
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hour_val = int(hour['hour'])
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count = hour['count']
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self.stdout.write(f" Hour {hour_val:02d}:00: {count} transitions")
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# Transition patterns (common sequences)
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self.stdout.write(self.style.SUCCESS('\n--- Common Transition Patterns ---'))
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self.stdout.write(' Analyzing transition sequences...')
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# Get recent objects and their transition sequences
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recent_objects = (
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queryset.values('content_type', 'object_id')
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.distinct()[:100]
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)
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pattern_counts = {}
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for obj in recent_objects:
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transitions = list(
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StateLog.objects.filter(
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content_type=obj['content_type'],
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object_id=obj['object_id']
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)
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.order_by('timestamp')
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.values_list('transition', flat=True)
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)
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# Create pattern from consecutive transitions
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if len(transitions) >= 2:
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pattern = ' → '.join([t or 'N/A' for t in transitions[:3]])
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pattern_counts[pattern] = pattern_counts.get(pattern, 0) + 1
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# Display top patterns
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sorted_patterns = sorted(
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pattern_counts.items(),
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key=lambda x: x[1],
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reverse=True
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)[:5]
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for pattern, count in sorted_patterns:
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self.stdout.write(f" {pattern}: {count} occurrences")
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self.stdout.write(
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self.style.SUCCESS(f'\n=== Analysis Complete ===\n')
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)
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# Export options
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if output_format == 'json':
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self._export_json(queryset, days)
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elif output_format == 'csv':
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self._export_csv(queryset, days)
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def _export_json(self, queryset, days):
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"""Export analysis results as JSON."""
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import json
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from datetime import datetime
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data = {
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'analysis_date': datetime.now().isoformat(),
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'period_days': days,
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'total_transitions': queryset.count(),
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'transitions': list(
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queryset.values(
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'id', 'timestamp', 'state', 'transition',
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'content_type__model', 'object_id', 'by__username'
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)
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)
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}
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filename = f'transition_analysis_{datetime.now().strftime("%Y%m%d_%H%M%S")}.json'
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with open(filename, 'w') as f:
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json.dump(data, f, indent=2, default=str)
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self.stdout.write(
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self.style.SUCCESS(f'Exported to {filename}')
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)
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def _export_csv(self, queryset, days):
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"""Export analysis results as CSV."""
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import csv
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from datetime import datetime
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filename = f'transition_analysis_{datetime.now().strftime("%Y%m%d_%H%M%S")}.csv'
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with open(filename, 'w', newline='') as f:
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writer = csv.writer(f)
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writer.writerow([
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'ID', 'Timestamp', 'Model', 'Object ID',
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'State', 'Transition', 'User'
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])
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for log in queryset.select_related('content_type', 'by'):
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writer.writerow([
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log.id,
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log.timestamp,
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log.content_type.model,
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log.object_id,
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log.state,
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log.transition or 'N/A',
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log.by.username if log.by else 'System'
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])
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self.stdout.write(
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self.style.SUCCESS(f'Exported to {filename}')
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)
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@@ -0,0 +1,191 @@
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"""Management command to validate state machine configurations for moderation models."""
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from django.core.management.base import BaseCommand
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from django.core.management import CommandError
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from apps.core.state_machine import MetadataValidator
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from apps.moderation.models import (
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EditSubmission,
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ModerationReport,
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ModerationQueue,
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BulkOperation,
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PhotoSubmission,
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)
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class Command(BaseCommand):
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"""Validate state machine configurations for all moderation models."""
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help = (
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"Validates state machine configurations for all moderation models. "
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"Checks metadata, transitions, and FSM field setup."
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)
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def add_arguments(self, parser):
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"""Add command arguments."""
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parser.add_argument(
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"--model",
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type=str,
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help=(
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"Validate only specific model "
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"(editsubmission, moderationreport, moderationqueue, "
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"bulkoperation, photosubmission)"
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),
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)
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parser.add_argument(
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"--verbose",
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action="store_true",
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help="Show detailed validation information",
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)
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def handle(self, *args, **options):
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"""Execute the command."""
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model_name = options.get("model")
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verbose = options.get("verbose", False)
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# Define models to validate
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models_to_validate = {
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"editsubmission": (
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EditSubmission,
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"edit_submission_statuses",
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"moderation",
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),
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"moderationreport": (
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ModerationReport,
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"moderation_report_statuses",
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"moderation",
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),
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"moderationqueue": (
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ModerationQueue,
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"moderation_queue_statuses",
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"moderation",
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),
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"bulkoperation": (
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BulkOperation,
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"bulk_operation_statuses",
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"moderation",
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),
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"photosubmission": (
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PhotoSubmission,
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"photo_submission_statuses",
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"moderation",
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),
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}
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# Filter by model name if specified
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if model_name:
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model_key = model_name.lower()
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if model_key not in models_to_validate:
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raise CommandError(
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f"Unknown model: {model_name}. "
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f"Valid options: {', '.join(models_to_validate.keys())}"
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)
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models_to_validate = {model_key: models_to_validate[model_key]}
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self.stdout.write(
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self.style.SUCCESS("\nValidating State Machine Configurations\n")
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)
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self.stdout.write("=" * 60 + "\n")
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all_valid = True
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for model_key, (
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model_class,
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choice_group,
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domain,
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) in models_to_validate.items():
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self.stdout.write(f"\nValidating {model_class.__name__}...")
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self.stdout.write(f" Choice Group: {choice_group}")
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self.stdout.write(f" Domain: {domain}\n")
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# Validate metadata
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validator = MetadataValidator(choice_group, domain)
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result = validator.validate_choice_group()
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if result.is_valid:
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self.stdout.write(
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self.style.SUCCESS(
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f" ✓ {model_class.__name__} validation passed"
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)
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)
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if verbose:
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self._show_transition_graph(choice_group, domain)
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else:
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all_valid = False
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self.stdout.write(
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self.style.ERROR(
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f" ✗ {model_class.__name__} validation failed"
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)
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)
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for error in result.errors:
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self.stdout.write(
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self.style.ERROR(f" - {error.message}")
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)
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# Check FSM field
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if not self._check_fsm_field(model_class):
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all_valid = False
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self.stdout.write(
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self.style.ERROR(
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f" - FSM field 'status' not found on "
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f"{model_class.__name__}"
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)
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)
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# Check mixin
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if not self._check_state_machine_mixin(model_class):
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all_valid = False
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self.stdout.write(
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self.style.WARNING(
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f" - StateMachineMixin not found on "
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f"{model_class.__name__}"
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)
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)
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self.stdout.write("\n" + "=" * 60)
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if all_valid:
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self.stdout.write(
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self.style.SUCCESS(
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"\n✓ All validations passed successfully!\n"
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)
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)
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else:
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self.stdout.write(
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self.style.ERROR(
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"\n✗ Some validations failed. "
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"Please review the errors above.\n"
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)
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)
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raise CommandError("State machine validation failed")
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def _check_fsm_field(self, model_class):
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"""Check if model has FSM field."""
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from apps.core.state_machine import RichFSMField
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status_field = model_class._meta.get_field("status")
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return isinstance(status_field, RichFSMField)
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def _check_state_machine_mixin(self, model_class):
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"""Check if model uses StateMachineMixin."""
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from apps.core.state_machine import StateMachineMixin
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return issubclass(model_class, StateMachineMixin)
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def _show_transition_graph(self, choice_group, domain):
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"""Show transition graph for choice group."""
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from apps.core.state_machine import registry_instance
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self.stdout.write("\n Transition Graph:")
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graph = registry_instance.export_transition_graph(
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choice_group, domain
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)
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for source, targets in sorted(graph.items()):
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if targets:
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for target in sorted(targets):
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self.stdout.write(f" {source} -> {target}")
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else:
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self.stdout.write(f" {source} (no transitions)")
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self.stdout.write("")
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