Skip to main content

Library for Asynchronous data source connections Collection of asyncio drivers.

Project description

AsyncDB

AsyncDB is a collection of different Database Drivers using asyncio-based connections, 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.

Why AsyncDB?

The finality of AsyncDB is to provide us a subset of drivers (connectors) for accessing different databases and data sources for data interaction. The main goal of AsyncDB is using asyncio-based technologies.

Getting Started

Requirements

Python 3.8+

Installation

$ 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]

Requirements

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)
  • SQLAlchemy (requires sqlalchemy async (+3.14))

Quick Tutorial

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: aioredis (Redis)
  • mcache: aiomcache (Memcache)
  • odbc: aiodbc (ODBC)

Future work:

  • Prometheus

Output Support

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

Contribution guidelines

Please have a look at the Contribution Guide

  • Writing tests
  • Code review

Who do I talk to?

  • Repo owner or admin
  • Other community or team contact

License

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.

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 Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

asyncdb-2.5.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (707.9 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

asyncdb-2.5.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (664.5 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

asyncdb-2.5.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (671.0 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

File details

Details for the file asyncdb-2.5.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for asyncdb-2.5.12-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 698a4ef08e662606a59d81390de39c435c12ac813f823f1b96513c7be0622376
MD5 67546c01be493b50fcc534fb169acc61
BLAKE2b-256 c12e90e5842025bad8e76e0849d7a1e3f4de275db2c78305a5508cfe3711dba0

See more details on using hashes here.

File details

Details for the file asyncdb-2.5.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for asyncdb-2.5.12-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 812989a83b9225459a9b7e6954703ed898321921bee63fffad561aedaef7ed58
MD5 cde3b2b38b9c4320292c8b13af0bea30
BLAKE2b-256 efb5248a574c4eac36d0c23371ab51383969a18995bf3d5e1158ab81ea342764

See more details on using hashes here.

File details

Details for the file asyncdb-2.5.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for asyncdb-2.5.12-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4a328d670c0b272b5122b93800b855deb8d288d9848776fdcc5a22f4b5fc4b8e
MD5 9257756032bc4aca7b3bd06375f9716c
BLAKE2b-256 4c3783d6f818ee309cd04725a1a0ee747ee08aa10c76ecee220000c9aabe700f

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page