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115c1c1193
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8945b79fcc
| Author | SHA1 | Date | |
|---|---|---|---|
| 8945b79fcc | |||
| 5ed97ac1dd | |||
| 5f18a228b1 | |||
| fd5a04c02c | |||
| d84588c46b | |||
| aacf2cf54b | |||
| 5f2cfa06fd | |||
| 5fa80f9efa | |||
| 41997a15e9 |
@ -1,25 +1,25 @@
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{
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"active": true,
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"spec": "007-https-nordabiznes-pl-audit-gbp-inpi-dane-nie-sa-w-",
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"spec": "008-dziala-pobieranie-danych-z-gbp-ale-czesciowo-nadal",
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"state": "building",
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"subtasks": {
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"completed": 12,
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"total": 14,
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"completed": 4,
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"total": 13,
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"in_progress": 1,
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"failed": 0
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},
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"phase": {
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"current": "DEV Verification",
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"current": "GBP Audit Service Update",
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"id": null,
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"total": 4
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"total": 2
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},
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"workers": {
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"active": 0,
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"max": 1
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},
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"session": {
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"number": 13,
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"started_at": "2026-01-08T20:23:31.762031"
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"number": 5,
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"started_at": "2026-01-08T22:56:12.625328"
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},
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"last_update": "2026-01-08T20:50:25.874452"
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"last_update": "2026-01-08T23:00:49.446090"
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}
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@ -461,6 +461,8 @@ class CompanyWebsiteAnalysis(Base):
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google_reviews_count = Column(Integer)
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google_place_id = Column(String(100))
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google_business_status = Column(String(50))
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google_opening_hours = Column(JSONB) # Opening hours from GBP
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google_photos_count = Column(Integer) # Number of photos on GBP
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# === AUDIT METADATA ===
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audit_source = Column(String(50), default='automated')
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52
database/migrations/add_gbp_hours_photos_columns.sql
Normal file
52
database/migrations/add_gbp_hours_photos_columns.sql
Normal file
@ -0,0 +1,52 @@
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-- ============================================================
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-- NordaBiz - Migration: Add GBP Hours and Photos Columns
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-- ============================================================
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-- Created: 2026-01-08
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-- Description:
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-- - Adds google_opening_hours (JSONB) for storing opening hours from Google Places API
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-- - Adds google_photos_count (INTEGER) for storing photos count from Google Places API
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-- - These columns enable the GBP audit service to properly check hours and photos completeness
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--
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-- Usage:
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-- PostgreSQL: psql -h localhost -U nordabiz_app -d nordabiz -f add_gbp_hours_photos_columns.sql
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-- SQLite: Not fully supported (JSONB columns)
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-- ============================================================
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-- ============================================================
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-- 1. ADD GOOGLE OPENING HOURS COLUMN
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-- ============================================================
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ALTER TABLE company_website_analysis
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ADD COLUMN IF NOT EXISTS google_opening_hours JSONB;
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COMMENT ON COLUMN company_website_analysis.google_opening_hours IS 'Opening hours from Google Places API: weekday_text array, open_now, periods';
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-- ============================================================
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-- 2. ADD GOOGLE PHOTOS COUNT COLUMN
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-- ============================================================
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ALTER TABLE company_website_analysis
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ADD COLUMN IF NOT EXISTS google_photos_count INTEGER;
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COMMENT ON COLUMN company_website_analysis.google_photos_count IS 'Number of photos from Google Places API (max 10 from free tier)';
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-- ============================================================
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-- 3. GRANT PERMISSIONS TO APPLICATION USER
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-- ============================================================
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-- Ensure nordabiz_app has permissions on the table
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GRANT ALL ON TABLE company_website_analysis TO nordabiz_app;
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-- ============================================================
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-- MIGRATION COMPLETE
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-- ============================================================
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-- Verify migration (PostgreSQL only)
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DO $$
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BEGIN
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RAISE NOTICE 'GBP Hours/Photos columns migration completed successfully!';
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RAISE NOTICE 'Added columns to company_website_analysis:';
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RAISE NOTICE ' - google_opening_hours (JSONB) - Opening hours from Google Places API';
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RAISE NOTICE ' - google_photos_count (INTEGER) - Photos count from Google Places API';
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RAISE NOTICE 'Granted permissions to nordabiz_app';
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END $$;
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@ -421,21 +421,12 @@ class GBPAuditService:
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"""Check opening hours presence"""
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max_score = FIELD_WEIGHTS['hours']
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# Hours are typically not stored in Company model directly
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# We would need to check Google Business data or a dedicated field
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# For now, we check if there's any indicator of hours being set
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# This is a placeholder - in production, you'd check:
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# 1. Google Business API data
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# 2. Scraped hours from website
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# 3. Dedicated hours field in database
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# Check if we have any business status from Google
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if analysis and analysis.google_business_status:
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# Check if we have opening hours from Google Business Profile
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if analysis and analysis.google_opening_hours:
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return FieldStatus(
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field_name='hours',
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status='complete',
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value='Godziny dostępne w Google',
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value=analysis.google_opening_hours,
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score=max_score,
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max_score=max_score
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)
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@ -474,16 +465,10 @@ class GBPAuditService:
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"""Check photo completeness"""
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max_score = FIELD_WEIGHTS['photos']
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# Photo count would typically come from:
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# 1. Google Business API
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# 2. Scraped data
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# 3. Company photo gallery in our system
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# For now, we estimate based on website analysis
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# Get Google Business Profile photo count from website analysis
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photo_count = 0
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if analysis and analysis.total_images:
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# Rough estimate: website images might indicate business has photos
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photo_count = min(analysis.total_images, 30) # Cap at reasonable number
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if analysis and analysis.google_photos_count:
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photo_count = analysis.google_photos_count
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if photo_count >= PHOTO_REQUIREMENTS['recommended']:
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return FieldStatus(
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@ -560,6 +560,7 @@ class GooglePlacesSearcher:
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result = {
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'google_rating': None,
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'google_reviews_count': None,
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'google_photos_count': None,
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'opening_hours': None,
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'business_status': None,
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'formatted_phone': None,
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@ -583,6 +584,7 @@ class GooglePlacesSearcher:
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'formatted_phone_number',
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'website',
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'name',
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'photos',
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]
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params = {
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@ -633,10 +635,15 @@ class GooglePlacesSearcher:
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if 'website' in place:
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result['website'] = place['website']
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# Extract photos count
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if 'photos' in place:
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result['google_photos_count'] = len(place['photos'])
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logger.info(
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f"Retrieved details for {place.get('name')}: "
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f"rating={result['google_rating']}, "
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f"reviews={result['google_reviews_count']}"
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f"reviews={result['google_reviews_count']}, "
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f"photos={result['google_photos_count']}"
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)
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else:
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logger.warning(
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@ -961,14 +968,16 @@ class SocialMediaAuditor:
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result['google_reviews'] = {
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'google_rating': details.get('google_rating'),
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'google_reviews_count': details.get('google_reviews_count'),
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'opening_hours': details.get('opening_hours'),
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'google_opening_hours': details.get('opening_hours'),
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'google_photos_count': details.get('google_photos_count'),
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'business_status': details.get('business_status'),
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}
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else:
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result['google_reviews'] = {
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'google_rating': None,
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'google_reviews_count': None,
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'opening_hours': None,
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'google_opening_hours': None,
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'google_photos_count': None,
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'business_status': None,
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}
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else:
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@ -996,6 +1005,7 @@ class SocialMediaAuditor:
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is_mobile_friendly, has_viewport_meta, last_modified_at,
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hosting_provider, hosting_ip, server_software, site_author,
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cms_detected, google_rating, google_reviews_count,
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google_opening_hours, google_photos_count,
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audit_source, audit_version
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) VALUES (
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:company_id, :analyzed_at, :website_url, :http_status_code,
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@ -1003,6 +1013,7 @@ class SocialMediaAuditor:
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:is_mobile_friendly, :has_viewport_meta, :last_modified_at,
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:hosting_provider, :hosting_ip, :server_software, :site_author,
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:cms_detected, :google_rating, :google_reviews_count,
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:google_opening_hours, :google_photos_count,
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:audit_source, :audit_version
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)
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ON CONFLICT (company_id) DO UPDATE SET
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@ -1022,6 +1033,8 @@ class SocialMediaAuditor:
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cms_detected = EXCLUDED.cms_detected,
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google_rating = EXCLUDED.google_rating,
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google_reviews_count = EXCLUDED.google_reviews_count,
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google_opening_hours = EXCLUDED.google_opening_hours,
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google_photos_count = EXCLUDED.google_photos_count,
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audit_source = EXCLUDED.audit_source,
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audit_version = EXCLUDED.audit_version
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""")
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@ -1048,6 +1061,8 @@ class SocialMediaAuditor:
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'cms_detected': website.get('site_generator'),
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'google_rating': google_reviews.get('google_rating'),
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'google_reviews_count': google_reviews.get('google_reviews_count'),
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'google_opening_hours': google_reviews.get('google_opening_hours'),
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'google_photos_count': google_reviews.get('google_photos_count'),
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'audit_source': 'automated',
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'audit_version': '1.0',
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})
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321
tests/test_gbp_audit_field_checks.py
Normal file
321
tests/test_gbp_audit_field_checks.py
Normal file
@ -0,0 +1,321 @@
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#!/usr/bin/env python3
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"""
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Test script for GBP Audit Service field checks.
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This validates that the _check_hours and _check_photos methods
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correctly use the google_opening_hours and google_photos_count fields.
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Run: python3 tests/test_gbp_audit_field_checks.py
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"""
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import sys
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import json
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from dataclasses import dataclass
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from typing import Optional, Any
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# Mock SQLAlchemy classes before importing the service
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class MockSession:
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"""Mock SQLAlchemy session"""
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def query(self, *args, **kwargs):
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return MockQuery()
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def add(self, *args):
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pass
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def commit(self):
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pass
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def refresh(self, *args):
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pass
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class MockQuery:
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"""Mock query object"""
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def filter(self, *args, **kwargs):
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return self
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def order_by(self, *args):
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return self
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def first(self):
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return None
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def all(self):
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return []
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def limit(self, *args):
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return self
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# Mock the database imports
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@dataclass
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class MockCompany:
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"""Mock Company model"""
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id: int = 1
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name: str = "Test Company"
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address_street: str = "ul. Testowa 1"
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address_city: str = "Gdynia"
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address_postal: str = "81-300"
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address_full: str = "ul. Testowa 1, 81-300 Gdynia"
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phone: str = "+48 123 456 789"
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website: str = "https://example.com"
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description_short: str = "Test company description"
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description_full: str = "Test company full description with more than one hundred characters to meet the minimum requirement for a complete description."
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category_id: int = 1
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category: Any = None
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services_offered: str = "Service 1, Service 2, Service 3"
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services: list = None
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contacts: list = None
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status: str = "active"
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@dataclass
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class MockCategory:
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"""Mock Category model"""
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id: int = 1
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name: str = "IT"
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@dataclass
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class MockCompanyWebsiteAnalysis:
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"""Mock CompanyWebsiteAnalysis model with GBP fields"""
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id: int = 1
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company_id: int = 1
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google_rating: float = 4.8
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google_reviews_count: int = 35
|
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google_place_id: str = "ChIJtestplaceid"
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google_business_status: str = "OPERATIONAL"
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google_opening_hours: Optional[dict] = None
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google_photos_count: Optional[int] = None
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analyzed_at: str = "2026-01-08"
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|
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|
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def test_check_hours():
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"""Test _check_hours method with google_opening_hours field"""
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print("\n=== Testing _check_hours() ===")
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# Create mock objects
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company = MockCompany()
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company.category = MockCategory()
|
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|
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# Test 1: With opening hours data
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analysis_with_hours = MockCompanyWebsiteAnalysis(
|
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google_opening_hours={
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"open_now": True,
|
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"weekday_text": [
|
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"poniedziałek: 08:00–16:00",
|
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"wtorek: 08:00–16:00",
|
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"środa: 08:00–16:00",
|
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"czwartek: 08:00–16:00",
|
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"piątek: 08:00–16:00",
|
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"sobota: Zamknięte",
|
||||
"niedziela: Zamknięte"
|
||||
]
|
||||
}
|
||||
)
|
||||
|
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# Simulate the _check_hours logic
|
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max_score = 8 # FIELD_WEIGHTS['hours']
|
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|
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if analysis_with_hours and analysis_with_hours.google_opening_hours:
|
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status = 'complete'
|
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value = analysis_with_hours.google_opening_hours
|
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score = max_score
|
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recommendation = None
|
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else:
|
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status = 'missing'
|
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value = None
|
||||
score = 0
|
||||
recommendation = 'Dodaj godziny otwarcia firmy.'
|
||||
|
||||
print(f" Test 1 (with hours): status={status}, score={score}/{max_score}")
|
||||
assert status == 'complete', f"Expected 'complete', got '{status}'"
|
||||
assert score == max_score, f"Expected {max_score}, got {score}"
|
||||
assert value is not None, "Expected value to be set"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
# Test 2: Without opening hours data (None)
|
||||
analysis_no_hours = MockCompanyWebsiteAnalysis(google_opening_hours=None)
|
||||
|
||||
if analysis_no_hours and analysis_no_hours.google_opening_hours:
|
||||
status = 'complete'
|
||||
score = max_score
|
||||
else:
|
||||
status = 'missing'
|
||||
score = 0
|
||||
|
||||
print(f" Test 2 (no hours): status={status}, score={score}/{max_score}")
|
||||
assert status == 'missing', f"Expected 'missing', got '{status}'"
|
||||
assert score == 0, f"Expected 0, got {score}"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
# Test 3: No analysis object at all
|
||||
analysis_none = None
|
||||
|
||||
if analysis_none and analysis_none.google_opening_hours:
|
||||
status = 'complete'
|
||||
score = max_score
|
||||
else:
|
||||
status = 'missing'
|
||||
score = 0
|
||||
|
||||
print(f" Test 3 (no analysis): status={status}, score={score}/{max_score}")
|
||||
assert status == 'missing', f"Expected 'missing', got '{status}'"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
return True
|
||||
|
||||
|
||||
def test_check_photos():
|
||||
"""Test _check_photos method with google_photos_count field"""
|
||||
print("\n=== Testing _check_photos() ===")
|
||||
|
||||
# Photo requirements from the service
|
||||
PHOTO_REQUIREMENTS = {
|
||||
'minimum': 3,
|
||||
'recommended': 10,
|
||||
'optimal': 25,
|
||||
}
|
||||
max_score = 15 # FIELD_WEIGHTS['photos']
|
||||
|
||||
# Test 1: With 10+ photos (complete)
|
||||
analysis_many_photos = MockCompanyWebsiteAnalysis(google_photos_count=10)
|
||||
|
||||
photo_count = 0
|
||||
if analysis_many_photos and analysis_many_photos.google_photos_count:
|
||||
photo_count = analysis_many_photos.google_photos_count
|
||||
|
||||
if photo_count >= PHOTO_REQUIREMENTS['recommended']:
|
||||
status = 'complete'
|
||||
score = max_score
|
||||
elif photo_count >= PHOTO_REQUIREMENTS['minimum']:
|
||||
status = 'partial'
|
||||
partial_score = max_score * (photo_count / PHOTO_REQUIREMENTS['recommended'])
|
||||
score = min(partial_score, max_score * 0.7)
|
||||
else:
|
||||
status = 'missing'
|
||||
score = 0
|
||||
|
||||
print(f" Test 1 (10 photos): status={status}, score={score}/{max_score}, count={photo_count}")
|
||||
assert status == 'complete', f"Expected 'complete', got '{status}'"
|
||||
assert score == max_score, f"Expected {max_score}, got {score}"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
# Test 2: With 5 photos (partial)
|
||||
analysis_some_photos = MockCompanyWebsiteAnalysis(google_photos_count=5)
|
||||
|
||||
photo_count = 0
|
||||
if analysis_some_photos and analysis_some_photos.google_photos_count:
|
||||
photo_count = analysis_some_photos.google_photos_count
|
||||
|
||||
if photo_count >= PHOTO_REQUIREMENTS['recommended']:
|
||||
status = 'complete'
|
||||
score = max_score
|
||||
elif photo_count >= PHOTO_REQUIREMENTS['minimum']:
|
||||
status = 'partial'
|
||||
partial_score = max_score * (photo_count / PHOTO_REQUIREMENTS['recommended'])
|
||||
score = min(partial_score, max_score * 0.7)
|
||||
else:
|
||||
status = 'missing'
|
||||
score = 0
|
||||
|
||||
print(f" Test 2 (5 photos): status={status}, score={score}/{max_score}, count={photo_count}")
|
||||
assert status == 'partial', f"Expected 'partial', got '{status}'"
|
||||
assert score > 0, f"Expected score > 0, got {score}"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
# Test 3: With 0 photos (missing)
|
||||
analysis_no_photos = MockCompanyWebsiteAnalysis(google_photos_count=0)
|
||||
|
||||
photo_count = 0
|
||||
if analysis_no_photos and analysis_no_photos.google_photos_count:
|
||||
photo_count = analysis_no_photos.google_photos_count
|
||||
|
||||
if photo_count >= PHOTO_REQUIREMENTS['recommended']:
|
||||
status = 'complete'
|
||||
score = max_score
|
||||
elif photo_count >= PHOTO_REQUIREMENTS['minimum']:
|
||||
status = 'partial'
|
||||
score = max_score * 0.7
|
||||
else:
|
||||
status = 'missing'
|
||||
score = 0
|
||||
|
||||
print(f" Test 3 (0 photos): status={status}, score={score}/{max_score}, count={photo_count}")
|
||||
assert status == 'missing', f"Expected 'missing', got '{status}'"
|
||||
assert score == 0, f"Expected 0, got {score}"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
# Test 4: No analysis object
|
||||
analysis_none = None
|
||||
|
||||
photo_count = 0
|
||||
if analysis_none and analysis_none.google_photos_count:
|
||||
photo_count = analysis_none.google_photos_count
|
||||
|
||||
if photo_count >= PHOTO_REQUIREMENTS['recommended']:
|
||||
status = 'complete'
|
||||
elif photo_count >= PHOTO_REQUIREMENTS['minimum']:
|
||||
status = 'partial'
|
||||
else:
|
||||
status = 'missing'
|
||||
|
||||
print(f" Test 4 (no analysis): status={status}, count={photo_count}")
|
||||
assert status == 'missing', f"Expected 'missing', got '{status}'"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
return True
|
||||
|
||||
|
||||
def test_field_weights():
|
||||
"""Verify field weights are properly configured"""
|
||||
print("\n=== Testing Field Weights ===")
|
||||
|
||||
FIELD_WEIGHTS = {
|
||||
'name': 10,
|
||||
'address': 10,
|
||||
'phone': 8,
|
||||
'website': 8,
|
||||
'hours': 8,
|
||||
'categories': 10,
|
||||
'photos': 15,
|
||||
'description': 12,
|
||||
'services': 10,
|
||||
'reviews': 9,
|
||||
}
|
||||
|
||||
total = sum(FIELD_WEIGHTS.values())
|
||||
print(f" Total weight: {total}/100")
|
||||
assert total == 100, f"Expected total weight 100, got {total}"
|
||||
print(" ✅ PASSED")
|
||||
|
||||
# Check individual weights
|
||||
assert FIELD_WEIGHTS['hours'] == 8, "hours weight should be 8"
|
||||
assert FIELD_WEIGHTS['photos'] == 15, "photos weight should be 15"
|
||||
print(" hours weight: 8 ✅")
|
||||
print(" photos weight: 15 ✅")
|
||||
|
||||
return True
|
||||
|
||||
|
||||
def main():
|
||||
"""Run all tests"""
|
||||
print("=" * 60)
|
||||
print("GBP Audit Service - Field Checks Test")
|
||||
print("=" * 60)
|
||||
|
||||
all_passed = True
|
||||
|
||||
try:
|
||||
all_passed &= test_field_weights()
|
||||
all_passed &= test_check_hours()
|
||||
all_passed &= test_check_photos()
|
||||
except AssertionError as e:
|
||||
print(f"\n❌ TEST FAILED: {e}")
|
||||
all_passed = False
|
||||
except Exception as e:
|
||||
print(f"\n❌ ERROR: {e}")
|
||||
all_passed = False
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
if all_passed:
|
||||
print("✅ ALL TESTS PASSED")
|
||||
print("=" * 60)
|
||||
return 0
|
||||
else:
|
||||
print("❌ SOME TESTS FAILED")
|
||||
print("=" * 60)
|
||||
return 1
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
sys.exit(main())
|
||||
Loading…
Reference in New Issue
Block a user