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vertica-python is a native Python adapter for the Vertica (http://www.vertica.com) database.
Python
Latest commit af783b3 May 23, 2016 @alexjikim alexjikim 0.6.3

README.md

vertica-python

PyPI version

0.6.x adds python3 support (namedparams support is currently broken in python3, see issue 112)

0.5.x changes the connection method to accept kwargs instead of a dict to be more dbapi compliant. copy methods improved and consolidated in 0.5.1

0.4.x breaks some of the older query interfaces (row_handler callback, and connection.query). It replaces the row_handler callback with an iterate() method. Please see examples below If you are on 0.4.x, please upgrade to 0.4.6 as there are various bug fixes

vertica-python is a native Python adapter for the Vertica (http://www.vertica.com) database.

vertica-python is currently in beta stage; it has been tested for functionality and has a very basic test suite. Please use with caution, and feel free to submit issues and/or pull requests (after running the unit tests).

vertica-python has been tested with Vertica 6.1.2/7.0.0+ and Python 2.7/3.4.

Installation

If you're using pip >= 1.4 and you don't already have pytz installed:

pip install --pre pytz

To install vertica-python with pip:

pip install vertica-python

To install vertica-python with pip (with optional namedparams dependencies):

# see 'Using named parameters' section below
pip install 'vertica-python[namedparams]'

Source code for vertica-python can be found at:

http://github.com/uber/vertica-python

Run unit tests

To run the tests, you must have access to a Vertica database. You can spin one up with Vagrant that uses the default credentials using vagrant up. If you want to run it against an existing database instead; you can set the environment variables seen in tests/test_commons.py.

Assuming you have tox installed, all you have to do is run tox. It will run the unit tests using both python 2 and 3.

If you run into an error like: ERROR: InterpreterNotFound: python3.4

Edit the envlist property of tox.ini to use the version of python you have installed (eg py35)

Usage

Create connection

import vertica_python

conn_info = {'host': '127.0.0.1',
             'port': 5433,
             'user': 'some_user',
             'password': 'some_password',
             'database': 'a_database',
             # 10 minutes timeout on queries
             'read_timeout': 600,
             # default throw error on invalid UTF-8 results
             'unicode_error': 'strict'
             # SSL is disabled by default
             'ssl': False}

# simple connection, with manual close
connection = vertica_python.connect(**conn_info)
# do things
connection.close()

# using with for auto connection closing after usage
with vertica_python.connect(**conn_info) as connection:
    # do things

You can pass an ssl.SSLContext to ssl to customize the SSL connection options. For example,

import vertica_python
import ssl

ssl_context = ssl.SSLContext(ssl.PROTOCOL_SSLv23)
ssl_context.verify_mode = ssl.CERT_REQUIRED
ssl_context.check_hostname = True
ssl_context.load_verify_locations(cafile='/path/to/ca_file.pem')

conn_info = {'host': '127.0.0.1',
             'port': 5433,
             'user': 'some_user',
             'password': 'some_password',
             'database': 'a_database',
             'ssl': ssl_context}
connection = vertica_python.connect(**conn_info)

See more on SSL options here.

Stream query results:

cur = connection.cursor()
cur.execute("SELECT * FROM a_table LIMIT 2")

for row in cur.iterate():
    print(row)
# [ 1, 'some text', datetime.datetime(2014, 5, 18, 6, 47, 1, 928014) ]
# [ 2, 'something else', None ]

Streaming is recommended if you want to further process each row, save the results in a non-list/dict format (e.g. Pandas DataFrame), or save the results in a file.

In-memory results as list:

cur = connection.cursor()
cur.execute("SELECT * FROM a_table LIMIT 2")
cur.fetchall()
# [ [1, 'something'], [2, 'something_else'] ]

In-memory results as dictionary:

cur = connection.cursor('dict')
cur.execute("SELECT * FROM a_table LIMIT 2")
cur.fetchall()
# [ {'id': 1, 'value': 'something'}, {'id': 2, 'value': 'something_else'} ]
connection.close()

Query using named parameters:

# Using named parameter bindings requires psycopg2>=2.5.1 which is not includes with the base vertica_python requirements.

cur = connection.cursor()
cur.execute("SELECT * FROM a_table WHERE a = :propA b = :propB", {'propA': 1, 'propB': 'stringValue'})

cur.fetchall()
# [ [1, 'something'], [2, 'something_else'] ]

Insert and commits :

cur = connection.cursor()

# inline commit
cur.execute("INSERT INTO a_table (a, b) VALUES (1, 'aa'); commit;")

# commit in execution
cur.execute("INSERT INTO a_table (a, b) VALUES (1, 'aa')")
cur.execute("INSERT INTO a_table (a, b) VALUES (2, 'bb')")
cur.execute("commit;")

# connection.commit()
cur.execute("INSERT INTO a_table (a, b) VALUES (1, 'aa')")
connection.commit()

Copy :

cur = connection.cursor()
cur.copy("COPY test_copy (id, name) from stdin DELIMITER ',' ",  csv)

Where csv is either a string or a file-like object (specifically, any object with a read() method). If using a file, the data is streamed.

Rowcount oddities

vertica_python behaves a bit differently than dbapi when returning rowcounts.

After a select execution, the rowcount will be -1, indicating that the row count is unknown. The rowcount value will be updated as data is streamed.

cur.execute('SELECT 10 things')

cur.rowcount == -1  # indicates unknown rowcount

cur.fetchone()
cur.rowcount == 1
cur.fetchone()
cur.rowcount == 2
cur.fetchall()
cur.rowcount == 10

After an insert/update/delete, the rowcount will be returned as a single element row:

cur.execute("DELETE 3 things")

cur.rowcount == -1  # indicates unknown rowcount
cur.fetchone()[0] == 3

Nextset

If you execute multiple statements in a single call to execute(), you can use cursor.nextset() to retrieve all of the data.

cur.execute('SELECT 1; SELECT 2;')

cur.fetchone()
# [1]
cur.fetchone()
# None

cur.nextset()
# True

cur.fetchone()
# [2]
cur.fetchone()
# None

cur.nextset()
# None

UTF-8 encoding issues

While Vertica expects varchars stored to be UTF-8 encoded, sometimes invalid strings get into the database. You can specify how to handle reading these characters using the unicode_error connection option. This uses the same values as the unicode type (https://docs.python.org/2/library/functions.html#unicode)

cur = vertica_python.Connection({..., 'unicode_error': 'strict'}).cursor()
cur.execute(r"SELECT E'\xC2'")
cur.fetchone()
# caught 'utf8' codec can't decode byte 0xc2 in position 0: unexpected end of data

cur = vertica_python.Connection({..., 'unicode_error': 'replace'}).cursor()
cur.execute(r"SELECT E'\xC2'")
cur.fetchone()
# �

cur = vertica_python.Connection({..., 'unicode_error': 'ignore'}).cursor()
cur.execute(r"SELECT E'\xC2'")
cur.fetchone()
# 

License

MIT License, please see LICENSE for details.

Acknowledgements

Many thanks go to the contributors to the Ruby Vertica gem (https://github.com/sprsquish/vertica), since they did all of the wrestling with Vertica's protocol and have kept the gem updated. They are:

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