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DataClaw/backend/app/services/mdl.py
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2026-03-16 22:18:23 +08:00
import json
import os
from pathlib import Path
from typing import Optional, Dict, Any, List
from app.models.datasource import DataSource
from app.schemas.mdl import MDLManifest, Model, Column, TableReference
from app.connectors.factory import get_connector
from app.database import SessionLocal
# Assuming running from backend/ directory
MDL_STORAGE_PATH = Path("data/mdl")
class MDLService:
@staticmethod
def _get_mdl_path(datasource_id: int) -> Path:
MDL_STORAGE_PATH.mkdir(parents=True, exist_ok=True)
return MDL_STORAGE_PATH / f"{datasource_id}.json"
@staticmethod
def get_raw_schema(datasource: DataSource) -> Dict[str, List[Dict[str, str]]]:
connector = get_connector(datasource)
try:
return connector.get_schema()
except Exception as e:
print(f"Error fetching schema for DS {datasource.id}: {e}")
return {}
@staticmethod
def generate_default_mdl(
datasource: DataSource,
selected_tables: Optional[List[str]] = None,
selected_columns: Optional[Dict[str, List[str]]] = None,
) -> MDLManifest:
raw_schema = MDLService.get_raw_schema(datasource)
models = []
for table_name, columns in raw_schema.items():
if selected_tables is not None and table_name not in selected_tables:
continue
model_cols = []
for col_info in columns:
if isinstance(col_info, dict):
name = col_info.get("name", "UNKNOWN")
type_ = col_info.get("type", "UNKNOWN")
elif isinstance(col_info, str):
# Fallback for old string format "name (type)"
if "(" in col_info and col_info.endswith(")"):
parts = col_info.rsplit(" (", 1)
if len(parts) == 2:
name = parts[0]
type_ = parts[1][:-1]
else:
name = col_info
type_ = "UNKNOWN"
else:
name = col_info
type_ = "UNKNOWN"
else:
name = str(col_info)
type_ = "UNKNOWN"
if selected_columns is not None:
allowed = selected_columns.get(table_name, [])
if allowed and name not in allowed:
continue
model_cols.append(Column(name=name, type=type_))
if not model_cols:
continue
models.append(Model(
name=table_name,
tableReference=TableReference(table=table_name),
columns=model_cols
))
return MDLManifest(
catalog="default",
schema="public", # Default schema, might need adjustment based on datasource config
dataSource=datasource.type.upper(),
models=models
)
@staticmethod
def get_mdl(datasource_id: int) -> Optional[MDLManifest]:
path = MDLService._get_mdl_path(datasource_id)
if path.exists():
try:
with open(path, "r") as f:
data = json.load(f)
# Pydantic v2 compatible
return MDLManifest.model_validate(data)
except Exception as e:
print(f"Error loading MDL for {datasource_id}: {e}")
return None
return None
@staticmethod
def save_mdl(datasource_id: int, mdl: MDLManifest):
path = MDLService._get_mdl_path(datasource_id)
with open(path, "w") as f:
f.write(mdl.model_dump_json(indent=2, by_alias=True))
@staticmethod
def get_or_create_mdl(datasource_id: int) -> MDLManifest:
mdl = MDLService.get_mdl(datasource_id)
if mdl:
return mdl
# Generate new
db = SessionLocal()
try:
ds = db.query(DataSource).filter(DataSource.id == datasource_id).first()
if not ds:
raise ValueError(f"DataSource {datasource_id} not found")
mdl = MDLService.generate_default_mdl(ds)
MDLService.save_mdl(datasource_id, mdl)
return mdl
finally:
db.close()