Official SDK for MRC Data — China's apparel supply chain API
Project description
mrc-data
Official Python SDK for MRC Data -- China's apparel supply chain API.
Access 1,000+ verified suppliers, 350+ fabric specifications, and 170+ industrial clusters across China, each enriched with independent lab measurements (AATCC, ISO, GB).
Installation
pip install mrc-data
Quick start
from mrc_data import MRCData
client = MRCData(api_key="your-api-key")
# Search suppliers in Guangzhou
suppliers = client.search_suppliers(city="Guangzhou", certification="BSCI")
# Get supplier details
detail = client.get_supplier_detail("sup_abc123")
# Search fabrics by composition
fabrics = client.search_fabrics(composition="cotton", weight_min=150)
# Compare industrial clusters
comparison = client.compare_clusters(ids=["cls_humen", "cls_shaoxing"])
# Detect specification discrepancies
result = client.detect_discrepancy(supplier_id="sup_abc123", fabric_id="fab_xyz")
# Database statistics
stats = client.get_stats()
Async usage
import asyncio
from mrc_data import AsyncMRCData
async def main():
async with AsyncMRCData(api_key="your-api-key") as client:
suppliers = await client.search_suppliers(province="Guangdong")
fabrics = await client.search_fabrics(weave="twill")
print(suppliers)
asyncio.run(main())
API methods
| Method | Endpoint | Description |
|---|---|---|
search_suppliers(**kwargs) |
GET /v1/suppliers |
Search suppliers with filters |
get_supplier_detail(id) |
GET /v1/suppliers/{id} |
Get a single supplier |
get_supplier_fabrics(id) |
GET /v1/suppliers/{id}/fabrics |
List fabrics by supplier |
search_fabrics(**kwargs) |
GET /v1/fabrics |
Search fabrics with filters |
get_fabric_detail(id) |
GET /v1/fabrics/{id} |
Get a single fabric |
get_fabric_suppliers(id) |
GET /v1/fabrics/{id}/suppliers |
List suppliers for a fabric |
search_clusters(**kwargs) |
GET /v1/clusters |
Search industrial clusters |
compare_clusters(ids) |
POST /v1/clusters/compare |
Compare clusters side by side |
get_stats() |
GET /v1/stats |
Aggregate database statistics |
detect_discrepancy(**kwargs) |
POST /v1/discrepancy |
Detect spec discrepancies |
Error handling
from mrc_data import MRCData, AuthenticationError, NotFoundError, RateLimitError
client = MRCData(api_key="your-api-key")
try:
detail = client.get_supplier_detail("sup_invalid")
except AuthenticationError:
print("Check your API key")
except NotFoundError:
print("Supplier not found")
except RateLimitError:
print("Slow down -- rate limit exceeded")
Configuration
client = MRCData(
api_key="your-api-key",
base_url="https://api.meacheal.ai", # default
timeout=60.0, # seconds, default 30
)
Both MRCData and AsyncMRCData support context managers for automatic cleanup of the underlying HTTP connection pool.
License
MIT
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