API Response Mocker

Generate realistic mock API responses with fake data using Faker.

Features Schema-Based Generation: Define response structure Faker Integration: Realistic fake data Nested Objects: Complex nested structures Arrays: Generate lists of objects Relationships: Reference other mock data Multiple Formats: JSON, XML output Quick Start from api_mocker import APIMocker

mocker = APIMocker()

Generate user response

user = mocker.generate({ "id": "uuid", "name": "name", "email": "email", "created_at": "datetime" })

Generate list of users

users = mocker.generate_list({ "id": "uuid", "name": "name", "email": "email" }, count=10)

CLI Usage

Generate from schema file

python api_mocker.py --schema user_schema.json --output user.json

Generate list

python api_mocker.py --schema product.json --count 50 --output products.json

Generate with seed (reproducible)

python api_mocker.py --schema order.json --seed 42 --output order.json

Preview without saving

python api_mocker.py --schema customer.json --preview

Schema Format

Define fields using Faker provider names:

{ "id": "uuid", "first_name": "first_name", "last_name": "last_name", "email": "email", "phone": "phone_number", "company": "company", "address": { "street": "street_address", "city": "city", "state": "state", "zip": "zipcode", "country": "country" }, "created_at": "date_time_this_year", "is_active": "boolean" }

Available Data Types Personal name, first_name, last_name email, safe_email phone_number ssn Address address, street_address city, state, state_abbr zipcode, postcode country, country_code latitude, longitude Internet url, domain_name ipv4, ipv6 user_name, password uuid, uuid4 mac_address Business company, company_suffix job, job_title bs, catch_phrase Financial credit_card_number iban, bban currency_code price (custom: returns float) Date/Time date, time date_time, date_time_this_year date_of_birth iso8601 Text text, sentence, paragraph word, words slug Numeric random_int, random_number random_float (use {"type": "float", "min": 0, "max": 100}) boolean Advanced Schemas Arrays { "id": "uuid", "name": "name", "tags": { "_array": true, "_count": 3, "_item": "word" }, "orders": { "_array": true, "_count": 5, "_item": { "order_id": "uuid", "amount": "random_int", "date": "date" } } }

Custom Values { "id": "uuid", "status": { "_choice": ["pending", "active", "completed"] }, "priority": { "_range": [1, 5] }, "score": { "_float": {"min": 0.0, "max": 100.0, "decimals": 2} } }

Nested Objects { "user": { "id": "uuid", "profile": { "bio": "paragraph", "avatar_url": "image_url", "social": { "twitter": "user_name", "linkedin": "url" } } } }

API Reference APIMocker Class class APIMocker: def init(self, locale: str = "en_US", seed: int = None)

# Generation
def generate(self, schema: dict) -> dict
def generate_list(self, schema: dict, count: int = 10) -> list

# File operations
def from_schema_file(self, filepath: str) -> dict
def save(self, data: any, filepath: str, format: str = "json")

# Utilities
def set_seed(self, seed: int)
def get_faker(self) -> Faker

Example Schemas User Response { "id": "uuid", "username": "user_name", "email": "email", "profile": { "first_name": "first_name", "last_name": "last_name", "avatar": "image_url", "bio": "sentence" }, "created_at": "iso8601", "last_login": "date_time_this_month" }

E-commerce Product { "sku": "uuid", "name": "catch_phrase", "description": "paragraph", "price": {"_float": {"min": 9.99, "max": 999.99}}, "currency": "currency_code", "category": {"_choice": ["Electronics", "Clothing", "Home", "Sports"]}, "in_stock": "boolean", "rating": {"_float": {"min": 1, "max": 5, "decimals": 1}}, "reviews_count": {"_range": [0, 500]} }

API Error Response { "error": { "code": {"_choice": ["NOT_FOUND", "UNAUTHORIZED", "BAD_REQUEST"]}, "message": "sentence", "request_id": "uuid", "timestamp": "iso8601" } }

Dependencies faker>=22.0.0