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ASyncIO Client for the Trino distributed SQL Engine

Project description

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Introduction

This package provides a asyncio client interface to query Trino a distributed SQL engine. It supports Python 3.7, 3.8, 3.9, 3.10, 3.11, 3.12.

Installation

$ pip install aiotrino

Quick Start

Use the DBAPI interface to query Trino:

import aiotrino
conn = aiotrino.dbapi.connect(
    host='localhost',
    port=8080,
    user='the-user',
    catalog='the-catalog',
    schema='the-schema',
)
cur = await conn.cursor()
await cur.execute('SELECT * FROM system.runtime.nodes')
rows = await cur.fetchall()
await conn.close()

Or with context manager

import aiotrino
async with aiotrino.dbapi.connect(
    host='localhost',
    port=8080,
    user='the-user',
    catalog='the-catalog',
    schema='the-schema',
) as conn:
    cur = await conn.cursor()
    await cur.execute('SELECT * FROM system.runtime.nodes')
    rows = await cur.fetchall()

This will query the system.runtime.nodes system tables that shows the nodes in the Trino cluster.

The DBAPI implementation in aiotrino.dbapi provides methods to retrieve fewer rows for example Cursorfetchone() or Cursor.fetchmany(). By default Cursor.fetchmany() fetches one row. Please set trino.dbapi.Cursor.arraysize accordingly.

For backwards compatibility with PrestoSQL, override the headers at the start of your application

import aiotrino
aiotrino.constants.HEADERS = aiotrino.constants.PrestoHeaders

Basic Authentication

The BasicAuthentication class can be used to connect to a LDAP-configured Trino cluster:

import aiotrino
conn = aiotrino.dbapi.connect(
    host='coordinator url',
    port=8443,
    user='the-user',
    catalog='the-catalog',
    schema='the-schema',
    http_scheme='https',
    auth=aiotrino.auth.BasicAuthentication("principal id", "password"),
)
cur = await conn.cursor()
await cur.execute('SELECT * FROM system.runtime.nodes')
rows = await cur.fetchall()
await conn.close()

JWT Token Authentication

The JWTAuthentication class can be used to connect to a configured Trino cluster:

import aiotrino
conn = aiotrino.dbapi.connect(
    host='coordinator url',
    port=8443,
    catalog='the-catalog',
    schema='the-schema',
    http_scheme='https',
    auth=aiotrino.auth.JWTAuthentication(token="jwt-token"),
)
cur = await conn.cursor()
await cur.execute('SELECT * FROM system.runtime.nodes')
rows = await cur.fetchall()
await conn.close()

Transactions

The client runs by default in autocommit mode. To enable transactions, set isolation_level to a value different than IsolationLevel.AUTOCOMMIT:

import aiotrino
from aiotrino import transaction
async with aiotrino.dbapi.connect(
    host='localhost',
    port=8080,
    user='the-user',
    catalog='the-catalog',
    schema='the-schema',
    isolation_level=transaction.IsolationLevel.REPEATABLE_READ,
) as conn:
  cur = await conn.cursor()
  await cur.execute('INSERT INTO sometable VALUES (1, 2, 3)')
  await cur.fetchone()
  await cur.execute('INSERT INTO sometable VALUES (4, 5, 6)')
  await cur.fetchone()

The transaction is created when the first SQL statement is executed. trino.dbapi.Connection.commit() will be automatically called when the code exits the with context and the queries succeed, otherwise `trino.dbapi.Connection.rollback()' will be called.

Development

Getting Started With Development

Start by forking the repository and then modify the code in your fork.

Clone the repository and go inside the code directory. Then you can get the version with ./setup.py --version.

We recommend that you use virtualenv for development:

$ virtualenv .venv
$ . .venv/bin/activate
# TODO add requirements.txt: pip install -r requirements.txt
$ pip install .

For development purpose, pip can reference the code you are modifying in a virtualenv:

$ pip install -e .[tests]

That way, you do not need to run pip install again to make your changes applied to the virtualenv.

When the code is ready, submit a Pull Request.

Code Style

  • For Python code, adhere to PEP 8.
  • Prefer code that is readable over one that is "clever".
  • When writing a Git commit message, follow these guidelines.

Running Tests

There is a helper scripts, run, that provides commands to run tests. Type ./run tests to run both unit and integration tests.

aiotrino uses pytest for its tests. To run only unit tests, type:

$ pytest tests

Then you can pass options like --pdb or anything supported by pytest --help.

To run the tests with different versions of Python in managed virtualenvs, use tox (see the configuration in tox.ini):

$ tox

To run integration tests:

$ pytest integration_tests

They pull a Docker image and then run a container with a Trino server:

  • the image is named trinodb/trino:${TRINO_VERSION}
  • the container is named aiotrino-python-client-tests-{uuid4()[:7]}

Test setup

Supported OS Ubuntu 22.04

  1. Install pyenv

    curl https://pyenv.run | bash
    
  2. Install required python versions

    # Install the latest of all supported versions
    pyenv install 3.7, 3.8, 3.9, 3.10, 3.11, 3.12
    
  3. Set the installed versions as default for the shell. This allows tox to find them.

    List installed versions and update the following command as needed.

    pyenv versions
    
    pyenv shell 3.12.1 3.11.3 3.10.11 3.9.16 3.8.16 3.7.16
    
  4. Install tox

    pip install tox
    
  5. Run tox

    tox
    

Releasing

  • Set up your development environment.
  • Change version in aiotrino/__init__.py.
  • Commit and create an annotated tag (git tag -m '' current_version)
  • Run the following:
    . .venv/bin/activate &&
    pip install twine wheel setuptools &&
    rm -rf dist/ &&
    ./setup.py sdist bdist_wheel &&
    twine upload dist/* &&
    open https://pypi.org/project/aiotrino/ &&
    echo "Released!"
    
  • Push the branch and the tag (git push upstream master current_version)
  • Send release announcement.

Need Help?

Feel free to create an issue as it make your request visible to other users and contributors.

If an interactive discussion would be better or if you just want to hangout and chat about the Trino Python client, you can join us on the #python-client channel on Trino Slack.

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