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How to Use the Google Sheets API with Pythonby@pictureinthenoise
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8,230 reads

How to Use the Google Sheets API with Python

by Picture in the NoiseOctober 6th, 2022
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Google Sheets was released over 16 years ago in March 2006 and is one of the core applications comprising Google Workspace today. The Google Sheet API provides a programmatic way to interact with a Google spreadsheet and supports a wide variety of languages including Python, Java, and Node.js. In this tutorial, you will learn how to set up the underlying dependencies needed to use the Google. Sheets API provides developers with a set of methods that can be used to manipulate a given spreadsheet in a nearly unlimited way.

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16 Years of Sheets!

Google Sheets was released over 16 years ago in March 2006 and is one of the core applications comprising Google Workspace today. While Google Sheets does not offer all the bells-and-whistles available with Microsoft Excel, it is still a very powerful spreadsheet application. With Google Workspace enjoying greater adoption as a result of the pandemic-fueled work-at-home trend, it is likely that more and more people are using or will be using Google Sheets.


Like any spreadsheet application, Google Sheets allows users to organize, edit, analyze, and visualize data. Given that Google Sheets has been a web-based application from its inception, its collaborative features are arguably its greatest strength where multiple users can view and edit a given spreadsheet simultaneously. Additional strengths and weaknesses (as compared to Microsoft Excel) include:


Strengths

  • User-friendly.
  • Integration with Google Forms and other Google Workspace products.
  • Collaboration features, including revision history.


Weaknesses

  • Cannot work with very large datasets.
  • Limited graphing/charting features.
  • Limited macro/scripting capabilities.


The Google Sheets API provides a programmatic way to interact with a Google Sheets spreadsheet and supports a wide variety of languages including Python, Java, and Node.js. An application developer can read data from and write data to a Google Sheets spreadsheet via the API, as well as complete more complex interactions such as creating new worksheets, formatting data, and creating charts. To a certain extent, the Google Sheets API provides developers with a set of methods that can be used to manipulate a given Google Sheets spreadsheet in a nearly unlimited way.


In this tutorial you will learn how to set up the underlying dependencies needed to use the Google Sheets API with a Python application. In particular, you will create a new Google Cloud Platform project, enable the Google Sheets API, create credentials to securely access the API, install the required Python libraries to interact with the API from a Python application, and build a simple test application.


Prerequisites

To complete this tutorial, you will need:


  • To have a Google Account.
  • Python 2.6 or higher installed on your development system.
  • To have pip installed.


Step 1 - Create a New Google Cloud Platform Project

Google Cloud Platform projects allow developers to work with Google Workspace APIs, including the Google Sheets API. Keep in mind that Google sets a quota on the number of projects a given user can create. If you are using the Google Cloud Platform for the first time, then this obviously shouldn't be a problem. However, if you need a higher project quota in the future, you can always request one from Google.


  • To begin, open the Google Cloud Console. Enter your Google account credentials to login.
  • Once you are logged in, you will land at the Dashboard page where you will be able to view a summary of your existing projects. Of course, if this is your first time using the Google Cloud Console, you will not have any existing projects.
  • Click on the main menu (hamburger) icon in the upper-left corner of the screen and select IAM & Admin > Create a Project from the drop-down menu.
  • Enter a name for the new project . You will also see a Project ID in a small font directly underneath the project Name input field. The Project ID is created automatically based on the project name that you select. You can click on Edit to change the Project ID. However, keep in mind that once the new project is created, the Project ID cannot be changed.
  • Optionally, enter a location for the project. The location specifies the organization or folder to which the project will belong. As a new user, the default value of this field may display No organization and does not need to be changed. If you used a Google account that is managed, by your employer for example, when logging in, the Location field may display a different value.
  • Click on Create to create the project.
  • You will be re-directed back to the Dashboard page. In a few minutes, you should see the newly created project listed under the Project Info window.


Step 2 - Enable the Google Sheets API

Now that you have created a new Google Cloud Platform project, you need to enable the Google Sheets API for the project.


  • From the Dashboard page, click on the main menu icon in the upper-left corner again and select APIs & Services > Library.
  • From the Library page, scroll down to the Google Workspace section and click on Google Sheets API.
  • Once on the Google Sheets API page, click on Enable.
  • The Google Sheets API is now enabled for the new Google Cloud Platform project created in Step 1.


Step 3 - Create a Service Account

A Python application that wants to interact with the Google Sheets API must be authenticated and authorized to access the resources that the API supports. Google provides different options for the authentication and authorization mechanisms depending on the needs of the developer. In this step, we will choose to configure a new Service Account for authentication and authorization purposes.


Step 3a - Create a New Service Account


  • From the Dashboard page, click on the main menu icon in the upper-left corner again and select APIs & Services > Credentials.
  • On the Credentials page, click on Manage Service Accounts under Service Accounts.
  • You will be directed to the Service Accounts page where you need to click on Create Service Account.
  • Enter a new name for the service account. You can choose any name that you would like. Notice that as you enter your chosen service account name, an associated Service account ID will be automatically generated in the Service account ID field. Additionally, an e-mail address matching the service account ID will also be automatically generated. For example, if you entered some new service account in the name field, you might see a strange looking e-mail address ending in .iam.gserviceaccount.com like some-new-service-account@young-home-460928.iam.gserviceaccount.com as the service account e-mail. Copy this e-mail address since you will use it later when connecting a Python application to a Google Sheets spreadsheet via the Google Sheets API.
  • Once you have entered a name for the service account, click on Create And Continue.
  • Click on the Select a role dropdown menu from the Grant this service account access to project section. Look for the Basic option on the left side of the menu and hover over it. Then, click on Editor from the right-side of the menu. The Editor role will allow a Python application using this service account to read and write to a Google Sheets spreadsheet that it is interacting with via the Google Sheets API.
  • Click on Done to create the new service account.
  • You will be redirected back to the Service Accounts page.


Step 3b - Create a New Key for the Service Account

  • From the Service Accounts page, click on the options menu icon (i.e. the icon with three vertical dots) under the Actions label for the new service account. When the menu opens, click on Manage Keys.
  • On the Keys page, click on Add Key and then select Create new key.
  • The key format should already be set to JSON when the Create private key modal opens. Click on Create. A new private key will be generated and a JSON file download with the new key should automatically start. Note the location of the JSON file with the private key value as it will be needed later when connecting to the Google Sheets API from a Python application.


Step 4 - Install Required Google Libraries for Python

A Python application needs to import certain Google libraries for Python to successfully authenticate with and interact with the Google Sheets API.


Step 4a - Install the Google API Python Client Library

The Google Client Libraries provide access to Google Cloud APIs for a variety of languages. In this tutorial, we will install the Google API Python Client Library.


  • You can install the Google API Python Client Library using the following command:


pip install google-cloud


Step 4b - Install the Google Authentication Libraries

The Google Authentication libraries are used for authentication with Google Workspace APIs, and in this particular case, the Google Sheets API.


  • First, install the Google Authentication Library for Python using the following command:


pip install google-auth


  • Second, install the Google Authentication OAuth Library for Python using the following command:


pip install google-auth-oauthlib


The required Python libraries have now been installed.


Step 5 - Configuring a Test Application in Python

With everything setup in Steps 1 - 4, you can now start programmatically interacting with Google Sheets spreadsheets via the Google Sheets API. This steps builds a simple test application to retrieve the title of a Google Sheets spreadsheet.


Step 5a - Create a New Google Sheets Spreadsheet

  • In Google Sheets, create a new spreadsheet and give it a title such as My New Google Sheets Spreadsheet.
  • For this simple test, the new spreadsheet does not need to have any data in it.

Step 5b - Share the New Google Sheets Spreadsheet With Your Service Account

  • Click on the green Share button in the upper right corner of the new Google Sheets spreadsheet.
  • When the dialog opens, copy the Google Cloud Service Account e-mail address from Step 3a into the Add people and groups field.
  • Uncheck the Notify people option and click Send.

Step 5c - Record the URL Identifier for the New Google Sheets Spreadsheet

  • Your new Google Sheets spreadsheet will have a URL like:


https://docs.google.com/spreadsheets/d/8VaaiCuZ2q09IVndzU54s1RtxQreAxgFNaUPf9su5hK0/edit#gid=0


  • Record the portion of the URL string starting after d/ and ending before /edit.
  • In other words, you would write down 8VaaiCuZ2q09IVndzU54s1RtxQreAxgFNaUPf9su5hK0 using this example.

Step 5d - Configure the Test Application in Python

  • To keep things simple, put the key.json file generated in Step 3b in the same directory where you will create the test application in Python.
  • Build the test application as follows:


from google.oauth2 import service_account
from googleapiclient.discovery import build

spreadsheet_id = ENTER_YOUR_SPREADSHEET_ID FROM_STEP_5c_HERE_WITH_QUOTES
# For example:
# spreadsheet_id = "8VaaiCuZ2q09IVndzU54s1RtxQreAxgFNaUPf9su5hK0"

credentials = service_account.Credentials.from_service_account_file("key.json", scopes=["https://www.googleapis.com/auth/spreadsheets"])
service = build("sheets", "v4", credentials=credentials)

request = service.spreadsheets().get(spreadsheetId=spreadsheet_id, ranges=[], includeGridData=False)
sheet_props = request.execute()

print(sheet_props["properties"]["title"])

# Output:
# My New Google Sheets Spreadsheet


Conclusion

In this tutorial, you created a new Google Cloud Platform project, enabled the Google Sheets API for that project, created a new service account to authenticate with the Google Sheets API, installed all required Google libraries for Python, and built a simple test application. As mentioned in the introduction, the possibilities are almost endless when programmatically interfacing with Google Sheets. See Google Sheets for Developers documentation for more information.