MockForge
#python#automation#microsaas
Accelera i cicli di sviluppo con MockForge, il motore per API mock e dati sintetici di livello enterprise. Elimina le dipendenze dal backend, ottimizza il QA e dai piena autonomia ai team frontend con endpoint dinamici e iper-realistici in pochi secondi. Riduci drasticamente il time-to-market e crea architetture resilienti senza attriti. Potenzia il tuo workflow: crea software migliore più velocemente con MockForge.
Leggi l'approfondimento tecnicoDisaccoppiare Frontend e Backend con MockForge: Mocking Dinamico e Dati Sinteticimain.pymain.py — estratto d'esempio nello stile del tool
#!/usr/bin/env python3
"""
MockForge - Enterprise Mock API & Synthetic Data Engine
Accelerates development cycles by generating hyper-realistic, dynamic mock API
endpoints and synthetic datasets with zero backend dependencies.
Features:
- Dynamic route matching with regex and path parameter extraction
- Context-aware synthetic data generation using type heuristics
- Custom response latency simulation and fault injection rules
- OpenAPI/Swagger schema ingestion for instant mock creation
Usage:
$ python main.py serve --config=routes.json --port=8080
$ python main.py generate --schema=user_schema.json --count=500
"""
from __future__ import annotations
from dataclasses import dataclass, field
from enum import Enum
from typing import Any, Dict, List, Optional, Tuple
import json
import re
import time
# --- Domain Models ---
class HTTPMethod(str, Enum):
"""Supported HTTP request methods for route matching."""
GET = "GET"
POST = "POST"
PUT = "PUT"
DELETE = "DELETE"
PATCH = "PATCH"
OPTIONS = "OPTIONS"
@dataclass(frozen=True)
class RouteEndpoint:
"""Defines a target mock endpoint definition and response signature."""
path_pattern: str
method: HTTPMethod
status_code: int = 200
latency_ms: float = 0.0
template_body: Dict[str, Any] = field(default_factory=dict)
class MockForgeEngine:
"""Core orchestration engine for dynamic API mock handling."""
# ... the full file ships with your download