microsoft / microsoft/mssql-python
True async query execution
@sumitmsft y travaille déjà.
Depuis le 3/3/2025.
- Langage dominant
- Python
- Étoiles
- 473
- Forks
- 60
- Merge moyen
- 2 j 11 h
- PR mergées (30 j)
- 36
Description
Is your feature request related to a problem? Please describe.
Currently, mssql-python does not support true async execution, forcing developers to use thread-based workarounds (asyncio.to_thread() or aioodbc). This leads to performance limitations, increased memory usage, and suboptimal scalability in high-throughput applications, such as web servers and data processing pipelines.
For applications using FastAPI, Django Async, or AI/ML workloads, true async support is critical for handling multiple concurrent database operations efficiently. Without it, developers face blocking I/O that slows down event-driven applications.
Describe the solution you'd like
- Truly non-blocking I/O using
asyncio(asyncio.StreamReader/asyncio.StreamWriter). - Async query execution with
await conn.execute("SELECT ..."). - Streaming large result sets asynchronously using
async for row in cursor. - Better scalability for FastAPI, Django Async, and other async frameworks.
Example API:
async def stream_users():
conn = await asyncpg.connect(...)
async with conn.transaction(): # Ensures rollback on failure
async for row in conn.cursor("SELECT * FROM users"):
print(row) # Process each row asynchronously
await conn.close()
asyncio.run(stream_users())
### Describe alternatives you've considered
- asyncio.to_thread() → Still uses blocking I/O and threads, increasing overhead.
- aioodbc → Uses a thread pool, not true async, leading to performance bottlenecks.
- Custom Thread Management → Adds complexity and does not scale well under high concurrency.
### Additional context
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