Following the improvements made to tables in Google Sheets in March and April, we’re excited to introduce API support for tables. Now, users will be able to take basic actions to create and modify tables via the Sheets API.
Following enhancements to Google Sheets tables last year, Google recently highlighted an update for developers: the Sheets API now supports tables. This is great news for the Google Workspace developer community, as it allows for direct programmatic creation and modification of tables, moving beyond previous reliance on workarounds.
For a while, developers have found clever ways to interact with table-like structures, such as Kanshi Tanaike’s notable 2024 solution using a mix of Apps Script and Sheet formulas. While these methods were very clever, the new, direct API support offers a more robust and straightforward way for interacting with tables in Google Sheets. For Google Apps Script users, for now this will require using the Google Sheets Advanced Service to call these new table methods, as direct integration into the SpreadsheetApp service hasn’t been announced at this time.
Key API Capabilities for Tables:
The Sheets API now lets developers:
Add Tables: Create tables with defined names, ranges, and specific column properties (like ‘PERCENT‘ or ‘DROPDOWN‘ with validation).
Update Tables: Modify table size (add/remove rows/columns), and toggle table footers. The API also provides methods like InsertRangeRequest and DeleteRangeRequest for more granular control.
Append Values: Easily add new rows to the end of a table using AppendCellsRequest, which intelligently handles existing data and footers.
Delete Tables: Remove entire tables and their content (DeleteTableRequest) or just the formatting while retaining data (DeleteBandingRequest).
Utilise Column Types: Work with various column types including numeric, date, dropdown, smart chip, and checkbox.
This is a sample Google Apps Script designed to replace all instances of specific text within a Google Slides presentation, while simultaneously applying a desired text style. The built-in Presentation.replaceAllText() method within the Google Slides service is limited; it efficiently replaces text strings but lacks the functionality to modify text formatting during the replacement process. This limitation poses a challenge when aiming for styled text replacements. This report presents a detailed script solution that overcomes this constraint.
Have you ever needed to replace text across your Google Slides presentation but also wanted to apply specific formatting to the new text at the same time? The standard replaceAllText() method in Apps Script is handy for bulk text replacement, but it falls short when you need to control the styling – like font, size, or colour – during the replacement process.
Community contributor Kanshi Tanaike has developed a clever solution to overcome this limitation. Tanaike has shared a Google Apps Script function that not only finds and replaces text throughout all elements in your slides (including shapes, tables, and grouped objects) but also applies your desired text styles simultaneously.
The script works by iterating through the elements on each slide. When it finds the text you want to replace, it uses TextRange methods to perform the replacement and apply the specified formatting attributes, such as font family, size, colour, bold, italics, underline, and more.
This approach provides significantly more control than the built-in method, allowing you to ensure that automatically replaced text matches the exact styling you need for visually consistent and polished presentations. Tanaike’s post includes the full script, configuration details for specifying the text and styles, and sample slides showing the results.
Gemini API now generates images via Flash Experimental and Imagen 3. This report introduces image evolution within conversations using Gemini API with Google Apps Script.
The Gemini API recently gained the ability to generate images. Taking this a step further, Kanshi Tanaike has explored how to create evolving images within a conversation using Google Apps Script.
Often, you might want to generate an image and then iteratively add or modify elements in subsequent steps. Kanshi’s approach cleverly uses the chat functionality of the Gemini API (gemini-2.0-flash-exp model). By sending prompts sequentially within a chat, the API uses the conversation history, allowing each new image to build upon the previous one. This enables the generation of images that evolve step-by-step based on your prompts, as demonstrated in the original post with examples like drawing successive items on a whiteboard.
This technique is particularly useful because, as noted in the post, using chat history provides better results for this kind of sequential image generation compared to generating images from isolated prompts.
Kanshi Tanaike’s original post includes a detailed explanation, setup instructions (including API key usage and library installation ), and complete sample code snippets that you can adapt for your own Google Workspace projects.
I’ve created a small (pseudo) class that more easily clears and creates conditional formatting rules in a Google Sheet tab with Google Apps Script. Why? Well in Google Apps Script, conditional formatting rules are all or nothing. You can only ever set, get or clear ALL rules in a specified Google Sheet tab.
Conditional formatting in Google Sheets can be a powerful tool. However, Google Apps Script’s native setConditionalFormatRules() method replaces the entire set of rules, requiring the retrieval and reconstruction of the complete rule array to add, modify, or remove a single rule. This can be cumbersome and inefficient.
Fortunately Scott Donald has developed Range_ConditionalFormatting(), a valuable utility that simplifies conditional formatting management. This includes a SetRule method that allows you to add new rules without overwriting existing ones, and the position parameter provides precise control over rule order, which is crucial as conditional formatting rules are applied sequentially.
Scott’s post includes all the code you need to get this working in your own project along with a number of example snippets. This makes managing conditional formatting much more efficient and manageable.
Today I had the task of implementing a newsletter for internal updates and decided to use Google Apps Script since I was already using it for managing the project data. Based upon past experiences with emails using HTML I need this area was full of landmines and I didn’t want to navigate through it. 💣
So I decided to use MJML with Google Apps Script.
Sending emails using Google Apps Script is a common task, however, creating HTML emails that render consistently across different email clients and that look visually appealing can be challenging.
Justin Poehnelt’s post on DEV Community, “Using MJML in Google Apps Script to Send Beautiful Emails,” offers a solution to this problem. MJML is a markup language that makes it easy to create responsive HTML emails. It removes some of the complexities of HTML email development, allowing users to focus on the content of their emails.
In the post, Justin explains how to use MJML with Google Apps Script to send beautiful, responsive emails. He also mentions that he has published a library, MJMLApp, that “hides the gnarly bits” of using MJML with Google Apps Script. This library is available on GitHub in the mjml-apps-script repo where you can find the library ID and basic usage information.
Imagine that you write in plain English what you want to do in Google Workspace (eg. workflows) and it happens just like magic. Insert text prompt, Gemini will generate the code for you and run it immediately. A dream? No, reality, thanks to my conceptual and practical idea of how to implement AI Agents in Google Apps Scripts to leverage the V8 runtime.
Ivan Kutil has explored the concept of AI Agents in Google Apps Script, enabling Google Workspace automation via plain English descriptions. Users describe their automation needs in natural language, which is then processed by Gemini API to generate the necessary code. The generated code is then executed in your Google Apps Script project.
Ivan’s solution uses the gemini-2.0-flash-thinking-exp-01-21 model, an experimental model within Vertex AI specifically designed to reveal its ‘thinking process’, resulting in more reliable code generation. The enhanced reasoning capabilities of this model are particularly beneficial for complex automation tasks, making it a powerful tool for Google Workspace customisation.
To ensure that the agent is doing the right thing, the clever bit is you can test the execution via a dry-run, where the code created with Gemini Flash Thinking is sent to an internal ‘Tester’ agent, which uses Gemini to comment on the code and summarises it in a log. It’s important to review the script before running it, as Ivan accepts no responsibility for the results of the script. Another nice feature is the generated code is stored in the Cache, so after running a dry-run and then a run, the same version will be executed within the Cache limit (currently set to 5 minutes).
This solution, which mirrors Gemini for Workspace’s ability to generate and execute basic Python code, suggests a future where Gemini for Workspace could write and execute Apps Script code for basic tasks. This has the potential to transform how users interact with and automate their Google Workspace environments.
If you are interested in a version of Ivan’s solution that incorporates my GeminiApp library, follow this link. For additional information on Ivan’s solution including setup instructions follow the source link.
If you have domain-specific knowledge that you want an LLM to leverage, you probably have a use case for fine-tuning. Fine-tuning can significantly improve how well the model understands and responds to your queries, whether it’s legal documents, medical texts, financial reports, or niche industry data.
The most crucial step in this process is structuring your data correctly. If your dataset is well-organized and formatted properly, the rest of the workflow becomes much more manageable. From there, it’s just a matter of setting up a few configurations and automating parts of the process with Apps Script. That’s where things get interesting and surprisingly efficient.
Archive Google Sheet Data with Google Sheets API Advanced Service in Google Apps Script
Keeping your Google Sheets organised can be a chore. A recent tutorial by Scott Donald shows you how to automatically archive old rows based on multi-column parameters using Google Apps Script and the Advanced Sheets API, making data management easier and more efficient. This post highlights Scott’s approach to scripting a solution, including how to set up the Sheets API, the main components of the script, and potential applications.
As always Scott packs in a lot of useful tips and guidance; in particular, the tutorial highlights how to archive data using just five API calls, potentially making it faster than the standard SpreadsheetApp approach. Scott also details how to modify the script to suit different processes and includes details on his SsReq class. It provides a structured way to perform common operations like retrieving data, finding rows based on criteria, copying rows, appending rows, and removing rows, making it a great addition to your personal Apps Script toolbox.
For detailed explanations, code examples, and helpful tips, consult the complete tutorial.
Discover how to combine Imagen 3 and Google Sheets for rapid image creation. Automate your workflow and generate visuals in bulk.
Have you ever wished you could create a bunch of images without the hassle of typing in each prompt one by one? Well, Stéphane Giron has shared a clever solution using Google’s Imagen 3, Google Sheets, and Apps Script to streamline this process. While Gemini for Workspace is rolling out to more users and includes Imagen 3 for image creation in apps like Slides and the Gemini side panel, it doesn’t offer an easy way to create images in bulk. That’s where this method comes in. Instead of making images one at a time, this approach allows you to generate multiple images at once, saving you time and effort.
To get started with this method, you’ll need a Google Cloud Project and creating a service account (see the Build an AI slides reviewer with Gemini tutorial for instructions on setting this up). Once that’s set up, you create a Google Sheet with a column for your text prompts, and another for the links to the generated images. The images are automatically saved into a specific folder in your Google Drive.
The real magic happens with Apps Script. It uses Vertex AI to connect with the Imagen 3 model. The script reads each prompt from your sheet, sends it to Imagen 3 to create an image, and then stores the image in Google Drive. It also helpfully adds the image’s link back into the Google Sheet.
Check out the source post for the required code and instructions.
4 Approaches to extracting the body text of a Google Doc with Google Apps Script. Full Code and tutorial
Scott Donald must be one of the most comprehensive Google Apps Script writers I know. All of his tutorials are packed with information and useful tips. This recent post is no exception, as Scott dives in and shares this detailed guide on retrieving a Google Docs body text using Google Apps Script.
The tutorial explores four approaches to extracting text from a Google Doc:
DocumentApp: This approach is straightforward for basic text extraction but may not capture all elements, especially “Smart Chips.”
DocumentApp with Element Iteration: This method allows for extracting text and URLs from standard text and supports some “Smart Chips” like Date, Rich Link, and Person.
OCR Approach: This involves converting the document to a PDF, applying OCR, and reading the extracted text. It captures most displayed text but may not recognise emojis or some formula symbols.
Docs API Advanced Service: This approach utilises the Docs REST API to access text, links, and specific “Smart Chip” data. It offers more control over data extraction but may require navigating complex JSON responses.
Scott’s tutorial provides a comprehensive and practical guide to retrieving Google Docs body text using Google Apps Script. Be sure to check out the full tutorial for detailed explanations, code examples, and helpful tips. And don’t forget to share your preferred approach and any challenges you’ve encountered on Scott’s post.
