Skip to main content

A Trio-Native PostgreSQL Interface Library

Project description

Unit Tests Coverage Badge

pgtrio

This is a Trio-native PostgreSQL interface library. It implements the PostgreSQL wire protocol (both text and binary) in pure Python. It automatically converts between common postgres/python types, and supports adding custom codecs for other types. Transactions, cursors, and prepared statements are also supported.

Minimum Python version supported is 3.8.

Usage

To use pgtrio, you either start by calling the connect function or the create_pool. The former returns a single Connection object while the latter returns a Pool object that can be used to acquire multiple Connection objects.

import trio
import pgtrio

async def main():
    async with pgtrio.connect('test') as conn:
        results = await conn.execute('select name, dob from users')
        for name, dob in results:
            print(name, dob)

trio.run(main)

A Connection object can be used to execute queries, or create transactions, cursors or prepared statements. One Connection object can only be used from a single Trio task. If you have multiple tasks, you can use a Pool object.

import trio
import pgtrio

async def insert_rows(pool, start, end):
    async with pool.acquire() as conn:
        for i in range(start, end):
            results = await conn.execute('insert into numbers (n) values ($1)', i)

async def main():
    async with pgtrio.create_pool('test') as pool:
        async with trio.open_nursery() as nursery:
            nursery.start_soon(insert_rows, pool, 0, 10)
            nursery.start_soon(insert_rows, pool, 10, 20)

trio.run(main)

As you can see, you can also use query parameters and pass your arguments to the execute method after the query. pgtrio automatically converts Python types to Postgres types. To see a list of supported types, see the relevant section further in this document.

Transactions

In order to create a transaction, you can use the Connection.transaction method:

import trio
import pgtrio

async def main():
    async with pgtrio.connect('test') as conn:
        async with conn.transaction() as tr:
            await conn.execute("insert into users (name) values ('John Smith')")
            await conn.execute("insert into users (name) values ('Jane Smith')")

trio.run(main)

The transaction will be committed automatically when execution reaches the end of the async with block. You can manually commit or rollback the transaction at any point by calling await tr.commit() or await tr.rollback at any point in the block. After any of those methods is called, execution of the block will stop.

Prepared Statements

If you need to execute a single query multiple times, perhaps with different arguments each time, you can use prepared statements.

import trio
import pgtrio

async def main():
    async with pgtrio.connect('test') as conn:
        stmt = await conn.prepare('insert into numbers (n) values ($1)')
        await stmt.execute(100)
        await stmt.execute(200)

        numbers = await conn.execute('select n from numbers order by n')
        assert numbers == [(100,), (200,)]

trio.run(main)

Cursors

pgtrio also supports cursors for fetching large numbers of rows without loading them all in memory.

import trio
import pgtrio

async def main():
    async with pgtrio.connect('test') as conn:
        async with conn.transaction():
            cur = await conn.cursor('select * from users')
            chunk1 = await cur.fetch(100)
            await cur.forward(50)
            chunk2 = await cur.fetch(100)

trio.run(main)

Notice that a cursor must be used in a transaction block.

The fetch method fetches the number of requested rows. The forward method skips the given number of rows.

You can also obtain a cursor from a prepared statement.

import trio
import pgtrio

async def main():
    async with pgtrio.connect('test') as conn:
        async with conn.transaction():
            stmt = await conn.prepare('select * from users')
            cur = await stmt.cursor()
            chunk1 = await cur.fetch(100)
            await cur.forward(50)
            chunk2 = await cur.fetch(100)

trio.run(main)

Instead of using the fetch method you can also use iteration to read from a cursor:

import trio
import pgtrio

async def main():
    async with pgtrio.connect('test') as conn:
        async with conn.transaction():
            cur = await conn.cursor('select name, dob from users')
            async for name, dob in cur:
                print(name, dob)

trio.run(main)

Supported Types

pgtrio can automatically convert between the following python/postgres types:

postgres type python type
bool bool
bytea bytes
char str
cidr IPv4Network/IPv6Network
date datetime.date
float4 float
float8 float
inet IPv4Address/IPv6Address
interval datetime.timedelta
json list/dict
jsonb list/dict
text str
time datetime.time
timetz datetime.time
timestamp datetime.datetime
timestamptz datetime.datetime
varchar str

Development

You can install development dependencies by setting up a virtualenv (for example by python3 -m venv venv && . venv/bin/activate) and running pip install -r requirements.txt.

You can run unit tests by running python -m pytest inside a properly setup virtualenv. Notice however that the tests currently only support Linux and need postgres executables at a well-known location (/usr/lib/postgresql).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pgtrio-0.1.3.tar.gz (26.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pgtrio-0.1.3-py3-none-any.whl (27.9 kB view details)

Uploaded Python 3

File details

Details for the file pgtrio-0.1.3.tar.gz.

File metadata

  • Download URL: pgtrio-0.1.3.tar.gz
  • Upload date:
  • Size: 26.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.8.10

File hashes

Hashes for pgtrio-0.1.3.tar.gz
Algorithm Hash digest
SHA256 1f6815657bef4c5c66798a379d6e6ffe8d4541ff3f8ef804d6a8e3b91ce1bdf9
MD5 d5d555d10bc2a812b79a45c6477e490e
BLAKE2b-256 c4d5ba95f6214e53fd83eebb2a214331e58b8552c1ee34dbdd11112981e4cce7

See more details on using hashes here.

File details

Details for the file pgtrio-0.1.3-py3-none-any.whl.

File metadata

  • Download URL: pgtrio-0.1.3-py3-none-any.whl
  • Upload date:
  • Size: 27.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.8.10

File hashes

Hashes for pgtrio-0.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 00422fb6b03651a56e0e405213d7b6e14da19345f943e6c1c655492119243a65
MD5 c5f8b89827796e6061274fef655b23a9
BLAKE2b-256 11dcf87aba0d98ede45925d9f231c78221f8ded851963e96150c6a3bad3d529e

See more details on using hashes here.

Supported by

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