Created
August 10, 2017 15:54
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asyncpgsa benchmark against aiopg.sa
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| import asyncio | |
| import aiopg | |
| import aiopg.sa | |
| import asyncpg | |
| import asyncpgsa | |
| import sqlalchemy as sa | |
| pg_tables = sa.Table( | |
| 'pg_tables', sa.MetaData(), | |
| sa.Column('schemaname'), | |
| sa.Column('tablename'), | |
| sa.Column('tableowner'), | |
| sa.Column('tablespace'), | |
| sa.Column('hasindexes') | |
| ) | |
| query = pg_tables.select().where(pg_tables.c.schemaname == 'pg_catalog') | |
| loop = asyncio.get_event_loop() | |
| async def aio_coro(): | |
| await connection.execute(query) | |
| async def apg_coro(): | |
| await pgconn.execute(query) | |
| run_aiopg = lambda: loop.run_until_complete(aio_coro()) | |
| run_asyncpgsa = lambda: loop.run_until_complete(apg_coro()) | |
| pgconn = asyncpg.connect(user='postgres', host='127.0.0.1', password='password', database='postgres', connection_class=asyncpgsa.connection.SAConnection) | |
| pgconn = loop.run_until_complete(pgconn) | |
| engine = loop.run_until_complete(aiopg.sa.create_engine(user='postgres', password='password', host='127.0.0.1', database='postgres')) | |
| connection = loop.run_until_complete(engine.acquire()) | |
| run_asyncpgsa() | |
| run_aiopg() | |
| from timeit import timeit | |
| print('aiopg.sa:', timeit(run_aiopg, number=10000)) | |
| print('asyncpgsa', timeit(run_asyncpgsa, number=10000)) |
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Hi!
I've added also raw-query performance over
asyncpgfor comparing it with raw queries performance, still pretty impressive: