AsyncDB is a collection of different Database Drivers using asyncio-based connections and binary connectors (as asyncpg) but providing an abstraction layer to easily connect to different data sources, a high-level abstraction layer for various non-blocking database connectors, on other blocking connectors (like MS SQL Server) we are using ThreadPoolExecutors to run in a non-blocking manner.
The finality of AsyncDB is to provide us with a subset of drivers (connectors) for accessing different databases and data sources for data interaction. The main goal of AsyncDB is to use asyncio-based technologies.
Python 3.9+
$ pip install asyncdb
---> 100%
Successfully installed asyncdbCan also install only drivers required like:
$ pip install asyncdb[pg] # this install only asyncpgOr install all supported drivers as:
$ pip install asyncdb[all]- Python >= 3.8
- asyncio (https://pypi.python.org/pypi/asyncio/)
Currently AsyncDB supports the following databases:
- PostgreSQL (supporting two different connectors: asyncpg or aiopg)
- SQLite (requires aiosqlite)
- mySQL/MariaDB (requires aiomysql and mysqlclient)
- ODBC (using aioodbc)
- JDBC(using JayDeBeApi and JPype)
- RethinkDB (requires rethinkdb)
- Redis (requires aioredis)
- Memcache (requires aiomcache)
- MS SQL Server (non-asyncio using freeTDS and pymssql)
- Apache Cassandra (requires official cassandra driver)
- InfluxDB (using influxdb)
- CouchBase (using aiocouch)
- MongoDB (using motor and pymongo)
- SQLAlchemy (requires sqlalchemy async (+3.14))
- Oracle (requires oracledb)
from asyncdb import AsyncDB
db = AsyncDB('pg', dsn='postgres://user:password@localhost:5432/database')
# Or you can also passing a dictionary with parameters like:
params = {
"user": "user",
"password": "password",
"host": "localhost",
"port": "5432",
"database": "database",
"DEBUG": True,
}
db = AsyncDB('pg', params=params)
async with await db.connection() as conn:
result, error = await conn.query('SELECT * FROM test')And that's it!, we are using the same methods on all drivers, maintaining a consistent interface between all of them, facilitating the re-use of the same code for different databases.
Every Driver has a simple name to call it:
- pg: AsyncPG (PostgreSQL)
- postgres: aiopg (PostgreSQL)
- mysql: aiomysql (mySQL)
- influx: influxdb (InfluxDB)
- redis: redis-py (Redis)
- mcache: aiomcache (Memcache)
- odbc: aiodbc (ODBC)
- oracle: oracle (oracledb)
With Output Support results can be returned into a wide-range of variants:
from datamodel import BaseModel
class Point(BaseModel):
col1: list
col2: list
col3: list
db = AsyncDB('pg', dsn='postgres://user:password@localhost:5432/database')
async with await d.connection() as conn:
# changing output format to Pandas:
conn.output_format('pandas') # change output format to pandas
result, error = await conn.query('SELECT * FROM test')
conn.output_format('csv') # change output format to CSV
result, _ = await conn.query('SELECT TEST')
conn.output_format('dataclass', model=Point) # change output format to Dataclass Model
result, _ = await conn.query('SELECT * FROM test')Currently AsyncDB supports the following Output Formats:
- CSV (comma-separated or parametrized)
- JSON (using orjson)
- iterable (returns a generator)
- Recordset (Internal meta-Object for list of Records)
- Pandas (a pandas Dataframe)
- Datatable (Dt Dataframe)
- Dataclass (exporting data to a dataclass with -optionally- passing Dataclass instance)
- PySpark Dataframe
And others to come:
- Apache Arrow (using pyarrow)
- Polars (Using Python polars)
- Dask Dataframe
Please have a look at the Contribution Guide
- Writing tests
- Code review
- Repo owner or admin
- Other community or team contact
AsyncDB is copyright of Jesus Lara (https://phenobarbital.info) and is licensed under BSD. I am providing code in this repository under an open source licenses, remember, this is my personal repository; the license that you receive is from me and not from my employeer.