Python Connector Libraries for Snowflake Enterprise Data Warehouse Data Connectivity. Integrate Snowflake Enterprise Data Warehouse with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Snowflake data with Python and any Python-based applications.

Features

• SQL-92 access to Snowflake data warehouses
• Connect to live Snowflake data, for real-time data access
• Full support for data aggregation and complex JOINs in SQL queries
• Secure connectivity through modern cryptography, including TLS 1.2, SHA-256, ECC, etc.
• Seamless integration with leading BI, reporting, and ETL tools and with custom applications

Specifications

• Python Database API (DB-API) Modules for Snowflake with bi-directional access.
• Write SQL, get Snowflake data. Access Snowflake through standard Python Database Connectivity.
• Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
• An easy-to-use interface for working with data from Snowflake data warehouse.
• Full Unicode support for data, parameter, & metadata.

Connecting to Snowflake with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Snowflake from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

• Configure the connection properties to Snowflake
• Query Snowflake to retrieve or update data
• Connect your Snowflake data with Python data tools.

Connecting to Snowflake in Python

To connect to your data from Python, import the extension and create a connection:

import cdata.snowflake as mod
conn = mod.connect("User=user@domain.com; Password=password;")
 
#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM Leads")
 
rs = cur.fetchall()
 
for row in rs:
print(row)

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

Visualize Snowflake Data with pandas

The data-centric interfaces of the Snowflake Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

engine = create_engine("salesforce///Password=password&User=user")
 
df = pandas.read_sql("SELECT * FROM Leads", engine)
 
df.plot()
plt.show()

More Than Read-Only: Full Update/CRUD Support

Snowflake Connector goes beyond read-only functionality to deliver full support for Create, Read Update, and Delete operations (CRUD). Your end-users can interact with the data presented by the Snowflake Connector as easily as interacting with a database table.

CData Python Connectors in Action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

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