Async Queries

Handle long-running queries with execute_query_async, which submits a query, polls until Snowflake finishes, and returns the same cursor with results ready to fetch.

When to use async

Use execute_query_async when:

Queries take seconds or minutes.
You want an async/await flow (for example alongside other asyncio code).

For fast queries, ordinary synchronous cursor.execute() is simpler.

Basic example

execute_query_async returns the cursor after the query completes (it does not return a query-id string). Call fetchall(), fetch_pandas_all(), etc. on that cursor.

import asyncio
from komodo import get_snowflake_connection, execute_query_async


async def run_async_query():
    conn = get_snowflake_connection()
    cursor = conn.cursor()
    cursor.execute("USE DATABASE DATA")

    query = "SELECT column_name, table_name FROM INFORMATION_SCHEMA.COLUMNS LIMIT 20"
    cursor = await execute_query_async(cursor=cursor, query=query)

    rows = cursor.fetchall()
    print(f"Query returned {len(rows)} rows")

    cursor.close()
    conn.close()


asyncio.run(run_async_query())

Blocking I/O

The underlying connector still performs blocking I/O while polling query status. The library docstring notes that in FastAPI, similar work is often run in a thread pool. In a plain asyncio app, using await execute_query_async(...) is still appropriate; if you mix in synchronous cursor.execute calls inside async handlers, consider asyncio.to_thread for those sync calls so the event loop stays responsive.

Concurrent queries

You can run multiple async query helpers concurrently — each needs its own connection and cursor (do not share a single cursor across concurrent tasks).

import asyncio
from komodo import get_snowflake_connection, execute_query_async


async def one_query(sql: str):
    conn = get_snowflake_connection()
    try:
        cur = conn.cursor()
        try:
            cur.execute("USE DATABASE DATA")
            cur = await execute_query_async(cursor=cur, query=sql)
            return cur.fetchall()
        finally:
            cur.close()
    finally:
        conn.close()


async def main():
    results = await asyncio.gather(
        one_query("SELECT CURRENT_TIMESTAMP()"),
        one_query("SELECT CURRENT_USER()"),
    )
    print(results)


asyncio.run(main())

SDK reference: execute_query_async
Pandas Integration — load results into DataFrames after the query finishes