Async database support for Python.
Project description
Databases
Databases gives you simple asyncio support for a range of databases.
It allows you to make queries using the powerful SQLAlchemy Core expression language, and provides support for PostgreSQL, MySQL, and SQLite.
Databases is suitable for integrating against any async Web framework, such as Starlette, Sanic, Responder, Quart, aiohttp, FastAPI, or Bocadillo.
Requirements: Python 3.6+
Installation
$ pip install databases
You can install the required database drivers with:
$ pip install databases[postgresql]
$ pip install databases[mysql]
$ pip install databases[sqlite]
Driver support is providing using one of asyncpg, aiomysql, or aiosqlite.
Getting started
Declare your tables using SQLAlchemy:
import sqlalchemy
metadata = sqlalchemy.MetaData()
notes = sqlalchemy.Table(
"notes",
metadata,
sqlalchemy.Column("id", sqlalchemy.Integer, primary_key=True),
sqlalchemy.Column("text", sqlalchemy.String(length=100)),
sqlalchemy.Column("completed", sqlalchemy.Boolean),
)
You can use any of the sqlalchemy column types such as sqlalchemy.JSON
, or
custom column types.
Queries
You can now use any SQLAlchemy core queries (official tutorial):
from databases import Database
database = Database('postgresql://localhost/example')
# Establish the connection pool
await database.connect()
# Execute
query = notes.insert()
values = {"text": "example1", "completed": True}
await database.execute(query, values)
# Execute many
query = notes.insert()
values = [
{"text": "example2", "completed": False},
{"text": "example3", "completed": True},
]
await database.execute_many(query, values)
# Fetch multiple rows
query = notes.select()
rows = await database.fetch_all(query)
# Fetch single row
query = notes.select()
row = await database.fetch_one(query)
# Fetch multiple rows without loading them all into memory at once
query = notes.select()
async for row in database.iterate(query):
...
# Close all connection in the connection pool
await database.disconnect()
Connections are managed as task-local state, with driver implementations transparently using connection pooling behind the scenes.
Transactions
Transactions are managed by async context blocks:
async with database.transaction():
...
For a lower-level transaction API:
transaction = await database.transaction()
try:
...
except:
transaction.rollback()
else:
transaction.commit()
You can also use .transaction()
as a function decorator on any async function:
@database.transaction()
async def create_users(request):
...
Transaction blocks are managed as task-local state. Nested transactions are fully supported, and are implemented using database savepoints.
Connecting and disconnecting
You can control the database connect/disconnect, by using it as a async context manager.
async with Database(DATABASE_URL) as database:
...
Or by using explicit connection and disconnection:
database = Database(DATABASE_URL)
await database.connect()
...
await database.disconnect()
If you're integrating against a web framework, then you'll probably want to hook into framework startup or shutdown events. For example, with Starlette you would use the following:
@app.on_event("startup")
async def startup():
await database.connect()
@app.on_event("shutdown")
async def shutdown():
await database.disconnect()
Connection options
The PostgreSQL and MySQL backends provide a few connection options for SSL and for configuring the connection pool.
# Use an SSL connection.
database = Database('postgresql://localhost/example?ssl=true')
# Use a connection pool of between 5-20 connections.
database = Database('mysql://localhost/example?min_size=5&max_size=20')
Test isolation
For strict test isolation you will always want to rollback the test database to a clean state between each test case:
database = Database(DATABASE_URL, force_rollback=True)
This will ensure that all database connections are run within a transaction that rollbacks once the database is disconnected.
If you're integrating against a web framework you'll typically want to use something like the following pattern:
if TESTING:
database = Database(TEST_DATABASE_URL, force_rollback=True)
else:
database = Database(DATABASE_URL)
This will give you test cases that run against a different database to the development database, with strict test isolation so long as you make sure to connect and disconnect to the database between test cases.
For a lower level API you can explicitly create force-rollback transactions:
async with database.transaction(force_rollback=True):
...
Migrations
Because databases
uses SQLAlchemy core, you can integrate with Alembic
for database migration support.
$ pip install alembic
$ alembic init migrations
You'll want to set things up so that Alembic references the configured
DATABASE_URL
, and uses your table metadata.
In alembic.ini
remove the following line:
sqlalchemy.url = driver://user:pass@localhost/dbname
In migrations/env.py
, you need to set the 'sqlalchemy.url'
configuration key,
and the target_metadata
variable. You'll want something like this:
# The Alembic Config object.
config = context.config
# Configure Alembic to use our DATABASE_URL and our table definitions.
# These are just examples - the exact setup will depend on whatever
# framework you're integrating against.
from myapp.settings import DATABASE_URL
from myapp.tables import metadata
config.set_main_option('sqlalchemy.url', str(DATABASE_URL))
target_metadata = metadata
...
Note that migrations will use a standard synchronous database driver,
rather than using the async drivers that databases
provides support for.
This will also be the case if you're using SQLAlchemy's standard tooling, such
as using metadata.create_all(engine)
to setup the database tables.
Note for MySQL:
For MySQL you'll probably need to explicitly specify the pymysql
dialect when
using Alembic since the default MySQL dialect does not support Python 3.
If you're using the databases.DatabaseURL
datatype, you can obtain this using
DATABASE_URL.replace(dialect="pymysql")
— ⭐️ —
Databases is BSD licensed code. Designed & built in Brighton, England.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
File details
Details for the file databases-0.1.11.tar.gz
.
File metadata
- Download URL: databases-0.1.11.tar.gz
- Upload date:
- Size: 15.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/39.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.1
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c47ea5b6fb942067b5632fd78960f45ae654f194c2bd7a3e781d1df5e5849f46 |
|
MD5 | 8087b0378a68b0915d19ef3c6c8fdc12 |
|
BLAKE2b-256 | 100ba774ce80d5c0c9e5b58811096c85909f985361d43055061ab5e1ef380ca8 |