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from fastapi import APIRouter, Depends, HTTPException, Query
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import text, inspect
from typing import List, Dict, Any, Optional
import logging
from core.database import get_db, engine, Base
# Import all models to ensure they are registered with Base.metadata
from core.models import User, ClientUser, AuditLog, GeminiJob, PaymentTransaction, Contact, RateLimit, ApiKeyUsage
router = APIRouter(prefix="/api/schema", tags=["schema"])
logger = logging.getLogger(__name__)
@router.get("/tables")
async def get_tables():
"""
Get a list of all tables in the database.
"""
# We can inspect the metadata from the Base class since all models inherit from it
# and are imported above.
return sorted(list(Base.metadata.tables.keys()))
@router.get("/table/{table_name}")
async def get_table_data(
table_name: str,
page: int = Query(1, ge=1),
per_page: int = Query(50, ge=1, le=1000),
db: AsyncSession = Depends(get_db)
):
"""
Get data for a specific table with pagination.
"""
if table_name not in Base.metadata.tables:
raise HTTPException(status_code=404, detail=f"Table {table_name} not found")
table = Base.metadata.tables[table_name]
# Get columns
columns = [c.name for c in table.columns]
# Calculate offset
offset = (page - 1) * per_page
# Construct query safely using SQLAlchemy Core
# We use text() for dynamic table names but validate against metadata first
try:
# Get total count
count_query = text(f"SELECT COUNT(*) FROM {table_name}")
result = await db.execute(count_query)
total = result.scalar()
# Get data
data_query = text(f"SELECT * FROM {table_name} LIMIT :limit OFFSET :offset")
result = await db.execute(data_query, {"limit": per_page, "offset": offset})
# Convert rows to dicts
# result.keys() gives column names, result.all() gives rows
# We need to serialize datetime objects and others to JSON-friendly format
rows = []
for row in result:
row_dict = {}
for idx, col in enumerate(result.keys()):
val = row[idx]
# Simple string conversion for non-JSON serializable types might be needed
# FastAPI/Pydantic handles datetime usually, but let's be safe if needed.
# For now, let's rely on FastAPI's default encoder.
row_dict[col] = val
rows.append(row_dict)
return {
"table": table_name,
"columns": columns,
"total": total,
"page": page,
"per_page": per_page,
"data": rows
}
except Exception as e:
logger.error(f"Error fetching data for table {table_name}: {e}")
raise HTTPException(status_code=500, detail=str(e))
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