Source code for examples.asyncio.basic
"""Illustrates the asyncio engine / connection interface.
In this example, we have an async engine created by
:func:`_engine.create_async_engine`. We then use it using await
within a coroutine.
"""
import asyncio
from sqlalchemy import Column
from sqlalchemy import Integer
from sqlalchemy import MetaData
from sqlalchemy import String
from sqlalchemy import Table
from sqlalchemy.ext.asyncio import create_async_engine
meta = MetaData()
t1 = Table(
"t1", meta, Column("id", Integer, primary_key=True), Column("name", String)
)
async def async_main():
# engine is an instance of AsyncEngine
engine = create_async_engine(
"postgresql+asyncpg://scott:tiger@localhost/test",
echo=True,
)
# conn is an instance of AsyncConnection
async with engine.begin() as conn:
# to support SQLAlchemy DDL methods as well as legacy functions, the
# AsyncConnection.run_sync() awaitable method will pass a "sync"
# version of the AsyncConnection object to any synchronous method,
# where synchronous IO calls will be transparently translated for
# await.
await conn.run_sync(meta.drop_all)
await conn.run_sync(meta.create_all)
# for normal statement execution, a traditional "await execute()"
# pattern is used.
await conn.execute(
t1.insert(), [{"name": "some name 1"}, {"name": "some name 2"}]
)
async with engine.connect() as conn:
# the default result object is the
# sqlalchemy.engine.Result object
result = await conn.execute(t1.select())
# the results are buffered so no await call is necessary
# for this case.
print(result.fetchall())
# for a streaming result that buffers only segments of the
# result at time, the AsyncConnection.stream() method is used.
# this returns a sqlalchemy.ext.asyncio.AsyncResult object.
async_result = await conn.stream(t1.select())
# this object supports async iteration and awaitable
# versions of methods like .all(), fetchmany(), etc.
async for row in async_result:
print(row)
asyncio.run(async_main())