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Redshift Python Connector. It supports Python Database API Specification v2.0.

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redshift_connector

Python Version PyPi

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

Install from Binary

Package Manager Downloads Installation Command
PyPi PyPi Downloads pip install redshift_connector
Conda Conda Downloads conda install -c conda-forge redshift_connector

Install from Source

You may install from source by cloning this repository.

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

Tutorials

We are working to add more documentation and would love your feedback. Please reach out to the team by opening an issue or starting a discussion to help us fill in the gaps in our documentation.

Integrations

redshift_connector integrates with various open source projects to provide an interface to Amazon Redshift. Please open an issue with our project to request new integrations or get support for a redshift_connector issue seen in an existing integration.

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'])

Enabling autocommit

Following the DB-API specification, autocommit is off by default. It can be turned on by using the autocommit property of the connection.

# Make sure we're not in a transaction
con.rollback()
con.autocommit = True
con.run("VACUUM")
con.autocommit = False

Configuring cursor paramstyle

The paramstyle for a cursor can be modified via cursor.paramstyle. The default paramstyle used is format. Valid values for paramstyle include qmark, numeric, named, format, pyformat.

# qmark
redshift_connector.paramstyle = 'qmark'
sql = 'insert into foo(bar, jar) VALUES(?, ?)'
cursor.execute(sql, (1, "hello world"))

# numeric
redshift_connector.paramstyle = 'numeric'
sql = 'insert into foo(bar, jar) VALUES(:1, :2)'
cursor.execute(sql, (1, "hello world"))

# named
redshift_connector.paramstyle = 'named'
sql = 'insert into foo(bar, jar) VALUES(:p1, :p2)'
cursor.execute(sql, {"p1":1, "p2":"hello world"})

# format
redshift_connector.paramstyle = 'format'
sql = 'insert into foo(bar, jar) VALUES(%s, %s)'
cursor.execute(sql, (1, "hello world"))

# pyformat
redshift_connector.paramstyle = 'pyformat'
sql = 'insert into foo(bar, jar) VALUES(%(bar)s, %(jar)s)'
cursor.execute(sql, {"bar": 1, "jar": "hello world"})

Exception Handling

redshift_connector uses the guideline for exception handling specified in the Python DB-API. For exception definitions, please see redshift_connector/error.py

Example using IAM Credentials

IAM Credentials can be supplied directly to connect(...) using an AWS profile as shown below:

import redshift_connector

# Connects to Redshift cluster using IAM credentials from default profile defined in ~/.aws/credentials
conn = redshift_connector.connect(
    iam=True,
    database='dev',
    db_user='awsuser',
    password='',
    user='',
    cluster_identifier='examplecluster',
    profile='default'
 )
# ~/.aws/credentials
[default]
aws_access_key_id="my_aws_access_key_id"
aws_secret_access_key="my_aws_secret_access_key"
aws_session_token="my_aws_session_token"

# ~/.aws/config
[default]
region=us-west-2

If a region is not provided in ~/.aws/config or you would like to override its value, region may be passed to connect(...).

Alternatively, IAM credentials can be supplied directly to connect(...) using AWS credentials as shown below:

import redshift_connector

# Connects to Redshift cluster using IAM credentials from default profile defined in ~/.aws/credentials
conn = redshift_connector.connect(
    iam=True,
    database='dev',
    db_user='awsuser',
    password='',
    user='',
    cluster_identifier='examplecluster',
    access_key_id="my_aws_access_key_id",
    secret_access_key="my_aws_secret_access_key",
    session_token="my_aws_session_token",
    region="us-east-2"
 )

Integration with pandas

Retrieving query results as a pandas.DataFrame

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

Insert data stored in a pandas.DataFrame into an Amazon Redshift table

import numpy as np
import pandas as pd

df = pd.DataFrame(
    np.array(
        [
            ["One Hundred Years of Solitude", "Gabriel García Márquez"],
            ["A Brief History of Time", "Stephen Hawking"],
        ]
    ),
    columns=["bookname", "author‎"],
)
with con.cursor() as cursor:
    cursor.write_dataframe(df, "book")
    cursor.execute("select * from book; ")
    result = cursor.fetchall()

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 Type Description Default Value Required
access_key_id str The access key for the IAM role or IAM user configured for IAM database authentication None 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
app_name str The name of the IdP application used for authentication None No
auth_profile str The name of an Amazon Redshift Authentication profile having connection properties as JSON. See the RedshiftProperty class to learn how connection parameters should be named. None No
auto_create bool Indicates whether the user should be created if they do not exist FALSE No
client_id str The client id from Azure IdP None No
client_secret str The client secret from Azure IdP None No
cluster_identifier str The cluster identifier of the Amazon Redshift Cluster None No
credentials_provider str The IdP that will be used for authenticating with Amazon Redshift. None No
database str The name of the database to connect to None No
database_metadata_current_db_only bool Indicates if application supports multi-database datashare catalogs. Default value of True indicates application does not support multi-database datashare catalogs for backwards compatibility TRUE No
db_groups str A comma-separated list of existing database group names that the DbUser joins for the current session None No
db_user str The user ID to use with Amazon Redshift None No
endpoint_url str The Amazon Redshift endpoint url. This option is only used by AWS internal teams. None No
host str The hostname of Amazon Redshift cluster None No
iam bool If IAM Authentication is enabled FALSE No
iam_disable_cache bool This option specifies whether the IAM credentials are cached. By default the IAM credentials are cached. This improves performance when requests to the API gateway are throttled. False No
idp_response_timeout int The timeout for retrieving SAML assertion from IdP 120 No
idp_tenant str The IdP tenant None No
listen_port int The listen port IdP will send the SAML assertion to 7890 No
login_url str The SSO Url for the IdP None No
max_prepared_statements int The maximum number of prepared statements that can be open at once 1000 No
partner_sp_id str The Partner SP Id used for authentication with Ping None No
password str The password to use for authentication None No
port Int The port number of the Amazon Redshift cluster 5439 No
preferred_role str The IAM role preferred for the current connection None No
principal_arn str The ARN of the IAM entity (user or role) for which you are generating a policy None No
profile str The name of a profile in a AWS credentials file that contains AWS credentials. None No
region str The AWS region where the cluster is located None No
role_arn str The Amazon Resource Name (ARN) of the role that the caller is assuming. This parameter is used by JwtCredentialsProvider. For this provider, this is a mandatory parameter. None No
role_session_name str An identifier for the assumed role session. Typically, you pass the name or identifier that is associated with the user who is using your application. That way, the temporary security credentials that your application will use are associated with that user. This parameter is used by JwtCredentialsProvider. For this provider, this is an optional parameter. jwt_redshift_session No
secret_access_key_id str The secret access key for the IAM role or IAM user configured for IAM database authentication None No
session_token str The access key for the IAM role or IAM user configured for IAM database authentication. Not required unless temporary AWS credentials are being used. None No
ssl bool If SSL is enabled TRUE No
ssl_insecure bool Specifies if IDP hosts server certificate will be verified TRUE No
sslmode str The security of the connection to Amazon Redshift. verify-ca and verify-full are supported. verify_ca No
user str The username to use for authentication None No
web_identity_token str The OAuth 2.0 access token or OpenID Connect ID token that is provided by the identity provider. Your application must get this token by authenticating the user who is using your application with a web identity provider. This parameter is used by JwtCredentialsProvider. For this provider, this is a mandatory parameter. None No

Supported Datatypes

redshift_connector supports the following Amazon Redshift datatypes. redshift_connector will attempt to treat unsupported datatypes as strings. Incoming data from Amazon Redshift is treated as follows:

Amazon Redshift Datatype Python Datatype
ACLITEM str
BOOLEAN bool
INT8 int
INT4 int
INT2 int
VARCHAR str
OID int
REGPROC int
XID int
JSON dict
FLOAT4 float
FLOAT8 float
TEXT str
CHAR str
DATE datetime.date
TIME datetime.time
TIMETZ datetime.time
TIMESTAMP datetime.datetime
TIMESTAMPTZ datetime.datetime
NUMERIC decimal.Decimal
GEOMETRY str
SUPER str
VARBYTE bytes
GEOGRAPHY str

Logging

redshift_connector uses logging for providing detailed error messages regarding IdP authentication. A do-nothing handler is enabled by default as to prevent logs from being output to sys.stderr.

Enable logging in your application to view logs output by redshift_connector as described in the documentation for Python logging module.

Client Transfer Protocol

redshift_connector requests the Amazon Redshift server use the highest transfer protocol version supported. As of v2.0.879 binary transfer protocol is requested by default. If necessary, the requested transfer protocol can be modified via the client_protocol_version parameter of redshift_connector.connect(...). Please see the Connection Parameters table for more details.

Getting Help

Contributing

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

Changelog Generation

An entry in the changelog is generated upon release using gitchangelog. Please use the configuration file, .gitchangelog.rc when generating the changelog.

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

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