Google Sheets Python Connector

Read, Write, and Update Google Sheets with Python

Easily connect Python-based Data Access, Visualization, ORM, ETL, AI/ML, and Custom Apps with Google Sheets!


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

Features

  • Access Google Spreadsheet data as an entire worksheet or from discrete ranges of data within a worksheet
  • Represent discrete blocks of data as tables through automatic detection or by manually specifying ranges of data
  • Optionally specify if the first row of data should be used for field names
  • Read tables that are oriented horizontally or vertically
  • Powerful metadata querying enables SQL-like access to non-database sources
  • Push down query optimization pushes SQL operations down to the server whenever possible, increasing performance
  • Client-side query execution engine, supports SQL-92 operations that are not available server-side
  • Connect to live Google Sheets 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 Google Sheets with bi-directional access.
  • Write SQL, get Google Sheets data. Access Google Sheets through standard Python Database Connectivity.
  • Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
  • Simple command-line based data exploration of Google Sheets GoogleSpreadsheet, and more!
  • Full Unicode support for data, parameter, & metadata.


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.

WATCH THE PYTHON CONNECTOR VIDEO OVERVIEW

Python Connectivity with Google Sheets

Full-featured and consistent SQL access to any supported data source through Python


  • Universal Python Google Sheets Connectivity

    Easily connect to Google Sheets data from common Python-based frameworks, including:


    • Data Analysis/Visualization: Jupyter Notebook, pandas, Matplotlib
    • ORM: SQLAlchemy, SQLObject, Storm
    • Web Applications: Dash, Django
    • ETL: Apache Airflow, Luigi, Bonobo, Bubbles, petl
  • Popular Tooling Integration

    The Google Sheets Connector integrates seamlessly with popular data science and developer tooling like Anaconda, Visual Studio Python IDE, PyCharm, and more. Real Python,

  • Replication and Caching

    Our replication and caching commands make it easy to copy data to local and cloud data stores such as Oracle, SQL Server, Google Cloud SQL, etc. The replication commands include many features that allow for intelligent incremental updates to cached data.

  • String, Date, Numeric SQL Functions

    The Google Sheets Connector includes a library of 50 plus functions that can manipulate column values into the desired result. Popular examples include Regex, JSON, and XML processing functions.

  • Collaborative Query Processing

    Our Python Connector enhances the capabilities of Google Sheets with additional client-side processing, when needed, to enable analytic summaries of data such as SUM, AVG, MAX, MIN, etc.

  • Easily Customizable and Configurable

    The data model exposed by our Google Sheets Connector can easily be customized to add or remove tables/columns, change data types, etc. without requiring a new build. These customizations are supported at runtime using human-readable schema files that are easy to edit.

  • Enterprise-class Secure Connectivity

    Includes standard Enterprise-class security features such as TLS/ SSL data encryption for all client-server communications.

Connecting to Google Sheets with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Google Sheets 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 Google Sheets
  • Query Google Sheets to retrieve or update data
  • Connect your Google Sheets data with Python data tools.


Connecting to Google Sheets in Python

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

import cdata.google sheets as mod
conn = mod.connect("User=user@domain.com; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM GoogleSpreadsheet")
 
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 Google Sheets Data with pandas

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

engine = create_engine("google sheets///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM GoogleSpreadsheet", engine)

df.plot()
plt.show()

More Than Read-Only: Full Update/CRUD Support

Google Sheets 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 Google Sheets Connector as easily as interacting with a database table.