Generate realistic mock API responses with fake data. Use for testing, prototyping, or creating sample data for frontend development.
Resources
1Install
npx skillscat add dkyazzentwatwa/chatgpt-skills/api-response-mocker Install via the SkillsCat registry.
We need to produce a 2-3 sentence plain-text summary, objective, factual, no marketing language, no superlatives, no calls to action. Must be at most 60 words. No quotes, no bullet points, no headings, no markdown. Just plain text. Summarize: skill generates realistic mock API responses with fake data using Faker. Solves need for test data, prototyping, frontend development. Use when need sample data, testing APIs, prototyping. Let's craft maybe 2 sentences: "The API Response Mocker creates mock API responses with configurable schemas and Faker-generated fake data.
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 --previewSchema 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_nameemail,safe_emailphone_numberssn
Address
address,street_addresscity,state,state_abbrzipcode,postcodecountry,country_codelatitude,longitude
Internet
url,domain_nameipv4,ipv6user_name,passworduuid,uuid4mac_address
Business
company,company_suffixjob,job_titlebs,catch_phrase
Financial
credit_card_numberiban,bbancurrency_codeprice(custom: returns float)
Date/Time
date,timedate_time,date_time_this_yeardate_of_birthiso8601
Text
text,sentence,paragraphword,wordsslug
Numeric
random_int,random_numberrandom_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) -> FakerExample 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