This package provides a client interface to query Presto a distributed SQL engine. It supports Python 2.7, 3.5, 3.6, and pypy.
$ pip install presto-python-client
Use the DBAPI interface to query Presto:
import prestodb
conn=prestodb.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 Presto cluster.
The DBAPI implementation in prestodb.dbapi
provides methods to retrieve fewer
rows for example Cursorfetchone()
or Cursor.fetchmany()
. By default
Cursor.fetchmany()
fetches one row. Please set
prestodb.dbapi.Cursor.arraysize
accordingly.
The BasicAuthentication
class can be used to connect to a LDAP-configured Presto
cluster:
import prestodb
conn=prestodb.dbapi.connect(
host='coordinator url',
port=8443,
user='the-user',
catalog='the-catalog',
schema='the-schema',
http_scheme='https',
auth=prestodb.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 prestodb
from prestodb import transaction
with prestodb.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.execute('INSERT INTO sometable VALUES (4, 5, 6)')
The transaction is created when the first SQL statement is executed.
prestodb.dbapi.Connection.commit()
will be automatically called when the code
exits the with context and the queries succeed, otherwise
`prestodb.dbapi.Connection.rollback()' will be called.
There is a helper scripts, run
, that provides commands to run tests.
Type ./run tests
to run both unit and integration tests.
presto-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 build a Docker
image and then run a container with a Presto server:
- the image is named
presto-server:${PRESTO_VERSION}
- the container is named
presto-python-client-tests-{uuid4()[:7]}
The container is expected to be removed after the tests are finished.
Please refer to the Dockerfile
for details. You will find the configuration
in etc/
.
You can use ./run
to manipulate the containers:
./run presto_server
: build and run Presto in a container./run presto_cli CONTAINER_ID
: connect the Java Presto CLI to a container./run list
: list the running containers./run clean
: kill the containers
Start by forking the repository and then modify the code in your fork.
Please refer to CONTRIBUTING.md
before submitting your contributions.
Clone the repository and go inside the code directory. Then you can get the
version with python setup.py --version
.
We recommend that you use virtualenv
to develop on presto-python-client
:
$ virtualenv /path/to/env
$ /path/to/env/bin/active
$ pip install -r requirements.txt
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.
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 Presto Python client, you can join us on the #presto-python-client channel on Slack.