File size: 10,482 Bytes
a74b879
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
"""
Schema Generator
Automatically generates JSON-LD schema markup for websites
"""

import json
from typing import Dict, List
from datetime import datetime

def generate_organization_schema(audit: Dict) -> Dict:
    """Generate Organization schema from audit data"""
    pages = audit.get('pages', [])
    org_name = audit.get('org_name', 'Company')
    url = audit.get('url', '')
    
    # Extract contact info from pages
    emails = []
    phones = []
    social_links = []
    
    for page in pages:
        text = page.get('text', '') + ' ' + str(page.get('paragraphs', ''))
        
        # Extract emails
        import re
        found_emails = re.findall(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b', text)
        emails.extend(found_emails)
        
        # Extract phones
        found_phones = re.findall(r'(\+?\d{1,3}[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}', text)
        phones.extend(found_phones)
        
        # Extract social links
        links = page.get('links', [])
        for link in links:
            href = link.get('href', '') if isinstance(link, dict) else str(link)
            if any(social in href.lower() for social in ['facebook', 'twitter', 'instagram', 'linkedin', 'youtube']):
                social_links.append(href)
    
    schema = {
        "@context": "https://schema.org",
        "@type": "Organization",
        "name": org_name,
        "url": url,
        "logo": f"{url}/logo.png",
        "description": f"{org_name} - خدمات متميزة"
    }
    
    if emails:
        schema["email"] = emails[0]
    
    if phones:
        schema["telephone"] = phones[0]
    
    if social_links:
        schema["sameAs"] = list(set(social_links))[:5]
    
    # Add contact point
    if emails or phones:
        schema["contactPoint"] = {
            "@type": "ContactPoint",
            "contactType": "customer service",
            "email": emails[0] if emails else None,
            "telephone": phones[0] if phones else None
        }
    
    return schema


def generate_faq_schema(faqs: List[Dict]) -> Dict:
    """Generate FAQPage schema from FAQ list"""
    if not faqs:
        return None
    
    schema = {
        "@context": "https://schema.org",
        "@type": "FAQPage",
        "mainEntity": []
    }
    
    for faq in faqs:
        question = faq.get('question', faq.get('q', ''))
        answer = faq.get('answer', faq.get('a', ''))
        
        if question and answer:
            schema["mainEntity"].append({
                "@type": "Question",
                "name": question,
                "acceptedAnswer": {
                    "@type": "Answer",
                    "text": answer
                }
            })
    
    return schema if schema["mainEntity"] else None


def generate_breadcrumb_schema(url: str) -> Dict:
    """Generate BreadcrumbList schema from URL structure"""
    from urllib.parse import urlparse
    
    parsed = urlparse(url)
    path_parts = [p for p in parsed.path.split('/') if p]
    
    schema = {
        "@context": "https://schema.org",
        "@type": "BreadcrumbList",
        "itemListElement": []
    }
    
    # Add home
    schema["itemListElement"].append({
        "@type": "ListItem",
        "position": 1,
        "name": "الرئيسية",
        "item": f"{parsed.scheme}://{parsed.netloc}"
    })
    
    # Add path parts
    current_url = f"{parsed.scheme}://{parsed.netloc}"
    for i, part in enumerate(path_parts, start=2):
        current_url += f"/{part}"
        schema["itemListElement"].append({
            "@type": "ListItem",
            "position": i,
            "name": part.replace('-', ' ').replace('_', ' ').title(),
            "item": current_url
        })
    
    return schema


def generate_website_schema(audit: Dict) -> Dict:
    """Generate WebSite schema with search action"""
    org_name = audit.get('org_name', 'Company')
    url = audit.get('url', '')
    
    schema = {
        "@context": "https://schema.org",
        "@type": "WebSite",
        "name": org_name,
        "url": url,
        "potentialAction": {
            "@type": "SearchAction",
            "target": {
                "@type": "EntryPoint",
                "urlTemplate": f"{url}/search?q={{search_term_string}}"
            },
            "query-input": "required name=search_term_string"
        }
    }
    
    return schema


def generate_article_schema(page: Dict, org_name: str) -> Dict:
    """Generate Article schema for blog posts"""
    title = page.get('title', '')
    url = page.get('url', '')
    
    # Try to extract publish date
    text = page.get('text', '')
    import re
    date_match = re.search(r'(\d{4}-\d{2}-\d{2})', text)
    publish_date = date_match.group(1) if date_match else datetime.now().strftime('%Y-%m-%d')
    
    schema = {
        "@context": "https://schema.org",
        "@type": "Article",
        "headline": title,
        "url": url,
        "datePublished": publish_date,
        "dateModified": publish_date,
        "author": {
            "@type": "Organization",
            "name": org_name
        },
        "publisher": {
            "@type": "Organization",
            "name": org_name
        }
    }
    
    # Extract image if available
    images = page.get('images', [])
    if images:
        first_image = images[0] if isinstance(images[0], str) else images[0].get('src', '')
        if first_image:
            schema["image"] = first_image
    
    return schema


def generate_product_schema(page: Dict, org_name: str) -> Dict:
    """Generate Product schema for product pages"""
    title = page.get('title', '')
    url = page.get('url', '')
    text = page.get('text', '')
    
    # Try to extract price
    import re
    price_match = re.search(r'(\$|SAR|ريال)\s*(\d+(?:\.\d{2})?)', text)
    price = price_match.group(2) if price_match else "0"
    currency = "SAR" if "ريال" in text or "SAR" in text else "USD"
    
    schema = {
        "@context": "https://schema.org",
        "@type": "Product",
        "name": title,
        "url": url,
        "description": text[:200] if text else title,
        "offers": {
            "@type": "Offer",
            "price": price,
            "priceCurrency": currency,
            "availability": "https://schema.org/InStock",
            "seller": {
                "@type": "Organization",
                "name": org_name
            }
        }
    }
    
    # Extract image
    images = page.get('images', [])
    if images:
        first_image = images[0] if isinstance(images[0], str) else images[0].get('src', '')
        if first_image:
            schema["image"] = first_image
    
    return schema


def generate_local_business_schema(audit: Dict) -> Dict:
    """Generate LocalBusiness schema"""
    pages = audit.get('pages', [])
    org_name = audit.get('org_name', 'Company')
    url = audit.get('url', '')
    
    # Extract location info
    addresses = []
    for page in pages:
        text = page.get('text', '')
        # Look for Saudi cities
        saudi_cities = ['الرياض', 'جدة', 'مكة', 'المدينة', 'الدمام', 'الخبر', 'تبوك', 'أبها']
        for city in saudi_cities:
            if city in text:
                addresses.append(city)
                break
    
    schema = {
        "@context": "https://schema.org",
        "@type": "LocalBusiness",
        "name": org_name,
        "url": url,
        "address": {
            "@type": "PostalAddress",
            "addressCountry": "SA",
            "addressLocality": addresses[0] if addresses else "الرياض"
        }
    }
    
    return schema


def generate_all_schemas(audit: Dict) -> List[Dict]:
    """Generate all applicable schemas for a website"""
    schemas = []
    
    # Always add Organization
    org_schema = generate_organization_schema(audit)
    schemas.append(org_schema)
    
    # Add WebSite with search
    website_schema = generate_website_schema(audit)
    schemas.append(website_schema)
    
    # Add LocalBusiness if applicable
    local_schema = generate_local_business_schema(audit)
    schemas.append(local_schema)
    
    # Add Breadcrumb for main page
    url = audit.get('url', '')
    if url:
        breadcrumb_schema = generate_breadcrumb_schema(url)
        schemas.append(breadcrumb_schema)
    
    return schemas


def format_schema_for_html(schemas: List[Dict]) -> str:
    """Format schemas as HTML script tags"""
    html_parts = []
    
    for schema in schemas:
        if schema:
            json_str = json.dumps(schema, ensure_ascii=False, indent=2)
            html_parts.append(f'<script type="application/ld+json">\n{json_str}\n</script>')
    
    return '\n\n'.join(html_parts)


def get_schema_recommendations(audit: Dict) -> List[Dict]:
    """Get recommendations for missing schemas"""
    recommendations = []
    
    pages = audit.get('pages', [])
    
    # Check if Organization schema exists
    has_org_schema = False
    for page in pages:
        html = page.get('html', '')
        if '"@type":"Organization"' in html or '"@type": "Organization"' in html:
            has_org_schema = True
            break
    
    if not has_org_schema:
        recommendations.append({
            'type': 'organization',
            'priority': 'high',
            'title': 'أضف Organization Schema',
            'description': 'يساعد محركات البحث على فهم معلومات شركتك',
            'code': json.dumps(generate_organization_schema(audit), ensure_ascii=False, indent=2)
        })
    
    # Check for FAQ schema
    has_faq = any('faq' in page.get('url', '').lower() for page in pages)
    if has_faq:
        recommendations.append({
            'type': 'faq',
            'priority': 'medium',
            'title': 'أضف FAQPage Schema',
            'description': 'يظهر الأسئلة الشائعة مباشرة في نتائج البحث',
            'code': 'استخدم generate_faq_schema() مع قائمة الأسئلة'
        })
    
    # Check for BreadcrumbList
    recommendations.append({
        'type': 'breadcrumb',
        'priority': 'medium',
        'title': 'أضف BreadcrumbList Schema',
        'description': 'يحسن التنقل في نتائج البحث',
        'code': json.dumps(generate_breadcrumb_schema(audit.get('url', '')), ensure_ascii=False, indent=2)
    })
    
    return recommendations