Initial upload with CI/CD workflow

src/utils/examples.py

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+from typing import Any, Dict, List, Optional
+import random
+
+
+FAKE_DATA = {
+    'names': ['John', 'Jane', 'Bob', 'Alice', 'Charlie', 'Diana', 'Eve', 'Frank'],
+    'domains': ['example.com', 'test.org', 'sample.net', 'demo.io'],
+    'cities': ['New York', 'Los Angeles', 'Chicago', 'Houston', 'Phoenix'],
+    'streets': ['Main St', 'Oak Ave', 'Maple Dr', 'Cedar Ln', 'Pine Rd'],
+    'countries': ['USA', 'Canada', 'UK', 'Germany', 'France'],
+    'companies': ['Acme Corp', 'TechStart', 'Global Inc', 'Local LLC', 'Digital Co'],
+    'job_titles': ['Engineer', 'Manager', 'Designer', 'Developer', 'Analyst'],
+    'departments': ['Engineering', 'Marketing', 'Sales', 'HR', 'Finance'],
+    'products': ['Widget', 'Gadget', 'Tool', 'Device', 'Component'],
+    'adjectives': ['Premium', 'Essential', 'Professional', 'Standard', 'Deluxe'],
+    'lorem_words': ['lorem', 'ipsum', 'dolor', 'sit', 'amet', 'consectetur', 'adipiscing', 'elit'],
+    'statuses': ['active', 'pending', 'completed', 'cancelled', 'archived'],
+    'id_prefixes': ['usr_', 'ord_', 'prd_', 'inv_', 'txn_']
+}
+
+
+def generate_id(prefix: str = None) -> str:
+    prefix = prefix or random.choice(FAKE_DATA['id_prefixes'])
+    return f"{prefix}{random.randint(10000, 99999)}"
+
+
+def generate_name() -> str:
+    first = random.choice(FAKE_DATA['names'])
+    last = random.choice(FAKE_DATA['names'])
+    return f"{first} {last}"
+
+
+def generate_email(name: str = None) -> str:
+    name = (name or generate_name()).lower().replace(' ', '.')
+    domain = random.choice(FAKE_DATA['domains'])
+    return f"{name}@{domain}"
+
+
+def generate_phone() -> str:
+    return f"+1-{random.randint(200, 999)}-{random.randint(100, 999)}-{random.randint(1000, 9999)}"
+
+
+def generate_address() -> Dict[str, Any]:
+    return {
+        'street': f"{random.randint(100, 9999)} {random.choice(FAKE_DATA['streets'])}",
+        'city': random.choice(FAKE_DATA['cities']),
+        'state': f"{random.choice(['CA', 'NY', 'TX', 'FL', 'IL'])}",
+        'zip': f"{random.randint(10000, 99999)}",
+        'country': random.choice(FAKE_DATA['countries'])
+    }
+
+
+def generate_company() -> Dict[str, Any]:
+    adj = random.choice(FAKE_DATA['adjectives'])
+    product = random.choice(FAKE_DATA['products'])
+    return {
+        'name': f"{adj} {product} {random.choice(FAKE_DATA['companies'])}",
+        'industry': random.choice(['Technology', 'Healthcare', 'Finance', 'Retail', 'Manufacturing']),
+        'employees': random.randint(10, 10000),
+        'founded': random.randint(1950, 2023)
+    }
+
+
+def generate_user() -> Dict[str, Any]:
+    return {
+        'id': generate_id('usr_'),
+        'name': generate_name(),
+        'email': generate_email(),
+        'phone': generate_phone(),
+        'address': generate_address(),
+        'created_at': '2024-01-15T10:30:00Z',
+        'status': random.choice(FAKE_DATA['statuses'])
+    }
+
+
+def generate_product() -> Dict[str, Any]:
+    adj = random.choice(FAKE_DATA['adjectives'])
+    product = random.choice(FAKE_DATA['products'])
+    return {
+        'id': generate_id('prd_'),
+        'name': f"{adj} {product}",
+        'description': ' '.join(random.choices(FAKE_DATA['lorem_words'], k=10)),
+        'price': round(random.uniform(9.99, 999.99), 2),
+        'sku': f"SKU-{random.randint(10000, 99999)}",
+        'in_stock': random.choice([True, False]),
+        'category': random.choice(['Electronics', 'Clothing', 'Home', 'Sports', 'Books'])
+    }
+
+
+def generate_order() -> Dict[str, Any]:
+    return {
+        'id': generate_id('ord_'),
+        'customer_id': generate_id('usr_'),
+        'items': [generate_product() for _ in range(random.randint(1, 5))],
+        'total': round(random.uniform(50, 2000), 2),
+        'status': random.choice(FAKE_DATA['statuses']),
+        'created_at': '2024-01-15T14:30:00Z'
+    }
+
+
+def generate(schema: Dict[str, Any], depth: int = 0) -> Any:
+    if depth > 3:
+        return None
+
+    if not schema:
+        return None
+
+    schema_type = schema.get('type', 'object')
+
+    if schema_type == 'object' and 'properties' in schema:
+        result = {}
+        for prop_name, prop_schema in schema['properties'].items():
+            required = schema.get('required', [])
+            if prop_name in required or random.choice([True, False]):
+                result[prop_name] = generate(prop_schema, depth + 1)
+        return result
+
+    elif schema_type == 'array':
+        item_schema = schema.get('items', {})
+        return [generate(item_schema, depth + 1) for _ in range(random.randint(1, 3))]
+
+    elif schema_type == 'string':
+        string_format = schema.get('format')
+        if string_format == 'date-time':
+            return '2024-01-15T10:30:00Z'
+        elif string_format == 'date':
+            return '2024-01-15'
+        elif string_format == 'email':
+            return generate_email()
+        elif string_format == 'uri':
+            return 'https://example.com/api'
+        elif string_format == 'uuid':
+            return '550e8400-e29b-41d4-a716-446655440000'
+        else:
+            return random.choice(['sample', 'example', 'test', 'demo'])
+
+    elif schema_type == 'integer' or schema_type == 'number':
+        return random.randint(1, 1000)
+
+    elif schema_type == 'boolean':
+        return random.choice([True, False])
+
+    elif schema_type == 'null':
+        return None
+
+    return None