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-2.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (707.8 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

asyncdb-2.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (664.4 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

asyncdb-2.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (670.9 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

File details

Details for the file asyncdb-2.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for asyncdb-2.5.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 09f0cbc4c6b489a943969918bcf0263d0cc6853f567c416894cf4f4c648a5fff
MD5 de6063dac99fd7b4b79018f3ae25536d
BLAKE2b-256 764949107b9fa84091e52460b587f37c270dd19e86d5eb798c7c999af6822d35

See more details on using hashes here.

File details

Details for the file asyncdb-2.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for asyncdb-2.5.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 86974d9775f1785c4ed8830f3abd260c0db45549e5f5afd8e4c70b8396ce7a73
MD5 8c16a0712492912f2ea0a04dac176fb2
BLAKE2b-256 3929e426773cd0529b8591d2049c97ad5382ae6dacc0c2681cabf53aa590c9cf

See more details on using hashes here.

File details

Details for the file asyncdb-2.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for asyncdb-2.5.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0b0cdf014c52c6ec45afb573fb5e1e7b2a3eae383dc9ffd89597d89a0eb8ce38
MD5 ad82337865a0163ad380ed57f07d8a4a
BLAKE2b-256 ea7f7ac9cce416f21342199d817eca4ed3f2cbb7066e45438dfefe982b8f4017

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