$ pip install asyncdb ---> 100% Successfully installed asyncdb

Can also install only drivers required like:

$ pip install asyncdb[pg] # this install only asyncpg

Or 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.