asyncpg-🚀 -- A fast PostgreSQL Database Client Library for Python/asyncio that returns numpy arrays
====================================================================================================
.. image:: https://github.com/athenianco/asyncpg-rkt/workflows/Tests/badge.svg
:target: https://github.com/athenianco/asyncpg-rkt/actions?query=workflow%3ATests+branch%3Amaster
:alt: GitHub Actions status
.. image:: https://img.shields.io/pypi/v/asyncpg-rkt.svg
:target: https://pypi.python.org/pypi/asyncpg-rkt
**asyncpg-rkt** is a fork of **asyncpg**, a database interface library designed specifically for
PostgreSQL and Python/asyncio. asyncpg is an efficient, clean implementation
of PostgreSQL server binary protocol for use with Python's ``asyncio``
framework. You can read more about asyncpg in an introductory
`blog post <http://magic.io/blog/asyncpg-1m-rows-from-postgres-to-python/>`_.
**asyncpg-rkt** extends **asyncpg** as follows:
* Backward compatible with the origin.
* It is possible to set the numpy dtype for the fetched query.
* Such "typed" queries return numpy arrays instead of lists of Record objects.
* We construct numpy arrays directly from the low-level PostgreSQL protocol, without materializing any Python objects.
* Although, we support `object` fields, too.
* The time from receiving the response from PostgreSQL server until `Connection.fetch()` returns is ~20x less. This is because we avoid the overhead of dealing with Python objects in the result.
* We return `ravel()`-ed indexes of nulls while writing NaN-s/NaT-s at the corresponding places in the array.
* There is an option to return data by column vs. by row.
**asyncpg-rkt** provides the best performance when there are thousands of rows returned and the field types map to numpy.
Read the blog post with the introduction.
asyncpg-🚀 requires Python 3.8 or later and is supported for PostgreSQL
versions 9.5 to 14. Older PostgreSQL versions or other databases implementing
the PostgreSQL protocol *may* work, but are not being actively tested.
Documentation
-------------
The project documentation can be found
`here <https://magicstack.github.io/asyncpg/current/>`_.
See below about how to use the fork's special features.
Performance
-----------
In our testing asyncpg is, on average, **3x** faster than psycopg2
(and its asyncio variant -- aiopg).
.. image:: https://raw.githubusercontent.com/athenianco/asyncpg-rkt/master/performance.png
:target: https://gistpreview.github.io/?b8eac294ac85da177ff82f784ff2cb60
The above results are a geometric mean of benchmarks obtained with PostgreSQL
`client driver benchmarking toolbench <https://github.com/MagicStack/pgbench>`_
in November 2020 (click on the chart to see full details).
Further improvement from writing numpy arrays is ~20x:
.. image:: https://raw.githubusercontent.com/athenianco/asyncpg-rkt/master/benchmark_20220522_142813.svg
.. image:: https://raw.githubusercontent.com/athenianco/asyncpg-rkt/master/benchmark_20220522_143838.svg
Features
--------
asyncpg implements PostgreSQL server protocol natively and exposes its
features directly, as opposed to hiding them behind a generic facade
like DB-API.
This enables asyncpg to have easy-to-use support for:
* **prepared statements**
* **scrollable cursors**
* **partial iteration** on query results
* automatic encoding and decoding of composite types, arrays,
and any combination of those
* straightforward support for custom data types
Installation
------------
asyncpg-🚀 is available on PyPI and requires numpy 1.21+.
Use pip to install::
$ pip install asyncpg-rkt
Basic Usage
-----------
.. code-block:: python
import asyncio
import asyncpg
from asyncpg.rkt import set_query_dtype
import numpy as np
async def run():
conn = await asyncpg.connect(user='user', password='password',
database='database', host='127.0.0.1')
dtype = np.dtype([
("a", int),
("b", "datetime64[s]"),
])
array, nulls = await conn.fetch(
set_query_dtype('SELECT * FROM mytable WHERE id = $1', dtype),
10,
)
await conn.close()
loop = asyncio.get_event_loop()
loop.run_until_complete(run())
License
-------
asyncpg-🚀 is developed and distributed under the Apache 2.0 license, just like the original project.
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