This package provides a client interface to query Trino a distributed SQL engine. It supports Python 2.7, 3.5, 3.6, and pypy.
$ pip install trino
Use the DBAPI interface to query Trino:
import trino
conn = trino.dbapi.connect(
host='localhost',
port=8080,
user='the-user',
catalog='the-catalog',
schema='the-schema',
)
cur = conn.cursor()
cur.execute('SELECT * FROM system.runtime.nodes')
rows = cur.fetchall()
This will query the system.runtime.nodes
system tables that shows the nodes
in the Trino cluster.
The DBAPI implementation in trino.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.
The BasicAuthentication
class can be used to connect to a LDAP-configured Trino
cluster:
import trino
conn = trino.dbapi.connect(
host='coordinator url',
port=8443,
user='the-user',
catalog='the-catalog',
schema='the-schema',
http_scheme='https',
auth=trino.auth.BasicAuthentication("principal id", "password"),
)
cur = conn.cursor()
cur.execute('SELECT * FROM system.runtime.nodes')
rows = cur.fetchall()
The client runs by default in autocommit mode. To enable transactions, set
isolation_level to a value different than IsolationLevel.AUTOCOMMIT
:
import trino
from trino import transaction
with trino.dbapi.connect(
host='localhost',
port=8080,
user='the-user',
catalog='the-catalog',
schema='the-schema',
isolation_level=transaction.IsolationLevel.REPEATABLE_READ,
) as conn:
cur = conn.cursor()
cur.execute('INSERT INTO sometable VALUES (1, 2, 3)')
cur.fetchone()
cur.execute('INSERT INTO sometable VALUES (4, 5, 6)')
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.
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.
- 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.
There is a helper scripts, run
, that provides commands to run tests.
Type ./run tests
to run both unit and integration tests.
trino-python-client
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
trino-python-client-tests-{uuid4()[:7]}
- Set up your development environment.
- Check the local workspace is up to date and has no uncommitted changes
git fetch -a && git status
- Change version in
trino/__init__.py
to a new version, e.g.0.123.0
. - Commit
git commit -a -m "Bump version to 0.123.0"
- Create an annotated tag
git tag -m "" 0.123.0
- Create release package and upload it to PyPI
. .venv/bin/activate && pip install twine && rm -rf dist/ && ./setup.py sdist bdist_wheel && twine upload dist/* && open https://pypi.org/project/trino/ && echo "Released!"
- Push the branch and the tag
git push upstream master 0.123.0
- Send release announcement.
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.