redshift-connector 2.0.711

Redshift interface library

redshift_connector is the Amazon Redshift connector for Python. Easy integration with pandas and numpy, as well as support for numerous Amazon Redshift specific features help you get the most out of your data

Supported Amazon Redshift features include:

• IAM authentication

• Identity provider (IdP) authentication

• Redshift specific data types

This pure Python connector implements Python Database API Specification 2.0.

Getting Started

The easiest way to get started with redshift_connector is via pip

pip install redshift_connector

For pandas and numpy support, install as shown below:

pip install 'redshift_connector[full]'

Note: redshift_connector requires Python >= 3.5

You can install from source by cloning this repository.

$ git clone https://github.com/aws/amazon-redshift-python-driver.git
$ cd redshift_connector
$ pip install .

Basic Example

import redshift_connector

# Connects to Redshift cluster using AWS credentials
conn = redshift_connector.connect(
    host='examplecluster.abc123xyz789.us-west-1.redshift.amazonaws.com',
    database='dev',
    user='awsuser',
    password='my_password'
 )

cursor: redshift_connector.Cursor = conn.cursor()
cursor.execute("create Temp table book(bookname varchar,author‎ varchar)")
cursor.executemany("insert into book (bookname, author‎) values (%s, %s)",
                    [
                        ('One Hundred Years of Solitude', 'Gabriel García Márquez'),
                        ('A Brief History of Time', 'Stephen Hawking')
                    ]
                  )
cursor.execute("select * from book")

result: tuple = cursor.fetchall()
print(result)
>> (['One Hundred Years of Solitude', 'Gabriel García Márquez'], ['A Brief History of Time', 'Stephen Hawking'])

Integration with pandas

import pandas
cursor.execute("create Temp table book(bookname varchar,author‎ varchar)")
cursor.executemany("insert into book (bookname, author‎) values (%s, %s)",
                   [
                       ('One Hundred Years of Solitude', 'Gabriel García Márquez'),
                       ('A Brief History of Time', 'Stephen Hawking')

                   ])
cursor.execute("select * from book")
result: pandas.DataFrame = cursor.fetch_dataframe()
print(result)
>>                         bookname                 author‎
>> 0  One Hundred Years of Solitude  Gabriel García Márquez
>> 1        A Brief History of Time         Stephen Hawking

Integration with numpy

import numpy
cursor.execute("select * from book")

result: numpy.ndarray = cursor.fetch_numpy_array()
print(result)
>> [['One Hundred Years of Solitude' 'Gabriel García Márquez']
>>  ['A Brief History of Time' 'Stephen Hawking']]

Query using functions

cursor.execute("SELECT CURRENT_TIMESTAMP")
print(cursor.fetchone())
>> [datetime.datetime(2020, 10, 26, 23, 3, 54, 756497, tzinfo=datetime.timezone.utc)]

Connection Parameters

Name	Description	Default Value	Required
database	String. The name of the database to connect to		Yes
user	String. The username to use for authentication		Yes
password	String. The password to use for authentication		Yes
host	String. The hostname of Amazon Redshift cluster		Yes
port	Int. The port number of the Amazon Redshift cluster	5439	No
ssl	Bool. If SSL is enabled	True	No
iam	Bool. If IAM Authentication is enabled	False	No
sslmode	String. The security of the connection to Amazon Redshift. ‘verify-ca’ and ‘verify-full’ are supported.	‘verify-ca’	No
idp_response_timeout	Int. The timeout for retrieving SAML assertion from IdP	120	No
listen_port | Int. The listen port IdP will send the SAML assertion to		7890	No
log_level	Int. The level of logging enabled, increasing in granularity (values [0,4] are valid)	0	No
log_path	String. The file path to the log file	‘driver.log’	No
max_prepared_statements	Int. The maximum number of prepared statements that can be open at once	1000	No
idp_tenant	String. The IdP tenant	None	No
credentials_provider	String. The IdP that will be used for authenticating with Amazon Redshift. ‘OktaCredentialsProvider’, ‘AzureCredentialsProvider’, ‘BrowserAzureCredentialsProvider’, ‘PingCredentialsProvider’, ‘BrowserSamlCredentialsProvider’, and ‘AdfsCredentialsProvider’ are supported	None	No
cluster_identifier	String. The cluster identifier of the Amazon Redshift Cluster	None	No
db_user	String. The user ID to use with Amazon Redshift	None	No
db_groups	String. A comma-separated list of existing database group names that the DbUser joins for the current session	None	No
auto_create	Bool. Indicates whether the user should be created if they do not exist	False	No
allow_db_user_override	Bool. True specifies the driver uses the DbUser value from the SAML assertion while False indicates the value in the DbUser connection parameter is used	False	No
login_url	String. The SSO Url for the IdP	None	No
preferred_role	String. The IAM role preferred for the current connection	None	No
client_secret	String. The client secret from Azure IdP	None	No
client_id	String. The client id from Azure IdP	None	No
region	String. The AWS region where the cluster is located	None	No
app_name	String. The name of the IdP application used for authentication	None	No

Getting Help

• Ask a question on Stack Overflow and tag it with redshift_connector

• Open a support ticket with AWS Support

• If you may have found a bug, please open an issue

Contributing

We look forward to collaborating with you! Please read through CONTRIBUTING before submitting any issues or pull requests.

Running Tests

You can run tests by using pytest test/unit. This will run all unit tests. Integration tests require providing credentials for an Amazon Redshift cluster as well as IdP attributes in test/config.ini.

Additional Resources

• LICENSE