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Originally written for bulldo.gs — republished here with the canonical link pointing home. I want to pull live JSON data from an API endpoint directly into a Google Sheet without installing an add-on. // Fetch JSON from an API and write it to the active sheet // Adjust API_URL and the field list to match your endpoint function importJsonFromApi () { var API_URL = ' https://jsonplaceholder.typicode.com/users ' ; var sheet = SpreadsheetApp . getActiveSpreadsheet (). getActiveSheet (); var response = UrlFetchApp . fetch ( API_URL ); var raw = response . getContentText (); var data = JSON . parse ( raw ); var headers = [ ' id ' , ' name ' , ' username ' , ' email ' , ' phone ' ]; var rows = data . map ( function ( obj ) { return headers . map ( function ( key ) { return obj [ key ] || '' ; }); }); sheet . clearContents (); sheet . getRange ( 1 , 1 , 1 , headers . length ). setValues ([ headers ]); sheet . getRange ( 2 , 1 , rows . length , headers . length ). setValues ( rows ); } Why getContentText() comes before JSON.parse UrlFetchApp.fetch() returns an HTTPResponse object, not a string. The first time I skipped getContentText() and passed the response object directly to JSON.parse(), it silently parsed to null and the sheet wrote nothing. You need raw = response.getContentText() to get the actual body as a string, then JSON.parse(raw) turns it into a JavaScript object or array. The URL must be publicly accessible or accept an API key via a query parameter or Authorization header. Add headers like this: UrlFetchApp.fetch(url, { headers: { Authorization: 'Bearer ' + token } }). Apps Script's UrlFetchApp quota is 20,000 calls per day on a free Google account, 100,000 on Workspace. The rectangular array constraint — why setValues fails without mapping setValues() is strict: it requires a 2D array where every row has the same number of columns. If you hand it an array of plain JSON objects, it throws 'The number of rows or columns in the range does not match the number of

Originally written for bulldo.gs — republished here with the canonical link pointing home. I have a spreadsheet of names and email addresses and I want to send each person a personalized message from my Gmail account without copy-pasting or using a paid tool. // Mail merge: Sheet cols A=Name, B=Email, C=Sent // Run from Apps Script; authorize Gmail + Sheets scopes function sendMerge () { var sheet = SpreadsheetApp . getActiveSheet (); var rows = sheet . getDataRange (). getValues (); var quota = MailApp . getRemainingDailyQuota (); var sent = 0 ; for ( var i = 1 ; i < rows . length ; i ++ ) { if ( rows [ i ][ 2 ] === ' Sent ' ) continue ; if ( sent >= quota ) { Logger . log ( ' Quota reached at row ' + ( i + 1 )); break ; } var name = rows [ i ][ 0 ]; var email = rows [ i ][ 1 ]; var subject = ' Hey ' + name + ' , here is your update ' ; var body = ' Hi ' + name + ' , \n\n Your personalized content goes here. \n\n Thanks ' ; MailApp . sendEmail ( email , subject , body ); sheet . getRange ( i + 1 , 3 ). setValue ( ' Sent ' ); sent ++ ; } } Set up your sheet and open the script editor Put names in column A, email addresses in column B, and leave column C blank — the script writes 'Sent' there as it goes. Header row in row 1 is assumed; the loop starts at index 1 (row 2) to skip it. Open the script editor from Extensions > Apps Script, paste the function, and save. The first time you run sendMerge() Google will ask you to authorize two scopes: Sheets (read/write the active spreadsheet) and Gmail (send mail on your behalf). Both are required. If you only see a Sheets prompt, delete the file and re-paste — a cached partial authorization sometimes skips the Gmail scope on older script files. Why the Sent column is the whole point Consumer Google accounts cap at roughly 100 outgoing recipients per 24-hour rolling window via MailApp. If your list has 200 rows and you run the script at 11 pm, it will send 100 and log 'Quota reached at row 101'. Without the Sent check, a sec

Originally written for bulldo.gs — republished here with the canonical link pointing home. I have a Google Sheet with duplicate rows and I want to remove them programmatically, either on demand or on a schedule, without destroying the rest of my data. // removeDuplicates.gs — dedup active sheet, keep first occurrence // Run from Extensions > Apps Script, or bind to a trigger. function removeDuplicateRows () { var sheet = SpreadsheetApp . getActiveSheet (); var data = sheet . getDataRange (). getValues (); var seen = new Set (); var unique = []; for ( var i = 0 ; i < data . length ; i ++ ) { var key = data [ i ]. join ( ' | ' ); if ( ! seen . has ( key )) { seen . add ( key ); unique . push ( data [ i ]); } } sheet . clearContents (); sheet . getRange ( 1 , 1 , unique . length , unique [ 0 ]. length ). setValues ( unique ); } Why rewrite instead of delete The instinct when deduplicating is to loop through the sheet and call deleteRow on each duplicate. That works, but it has a sharp edge: every call to deleteRow shifts all rows below it up by one. If you delete row 3, what was row 4 is now row 3, and your loop index is already pointing at the new row 4. The safe workaround people reach for is iterating bottom-to-top, which works but means holding the full duplicate set in memory anyway, making one API call per deleted row. The approach here sidesteps the problem entirely. Read everything once with getDataRange().getValues() — a single API call that returns a 2D array. Build the deduplicated array in JavaScript using a Set to track which row fingerprints you have already seen. Then clear the sheet and write the result back with one setValues call. Two API calls total, regardless of how many duplicates you had. For a 10,000-row sheet, this is the difference between a script that finishes in two seconds and one that times out at the six-minute Apps Script execution limit. The row key is built with data[i].join('|'). The pipe character works as a separator in practice; i

Google has announced the Google Colab CLI, a command-line tool that allows developers and AI agents to interact with remote Colab runtimes directly from a local terminal. By Daniel Dominguez

Even moderately sized data centers can have an outsized local impact.

The fraudsters allegedly targeted hundreds of thousands of people with Gemini-coded scams sites.

We are so excited to announce the winners of the Google I/O 2026 Writing Challenge ! We asked you to explore the announcements from Google I/O 2026 and share your thoughts and firsthand takes. Wow, you delivered. The quality and depth of submissions genuinely impressed our team. From hands-on walkthroughs to bold opinions on what the announcements really mean for developers, the entries were thoughtful, original, and packed with insight. Thank you to everyone who participated. Your writing helps make this community one of the best places on the internet to learn what's actually happening in tech. Now, let's celebrate our five winners! 🎉 🏆 Congratulations To… The Sleeper Announcement from Google I/O 2026 That Will Change How We Think About Apps Google I/O Writing Challenge Submission Vrushali Vrushali Vrushali Follow May 24 The Sleeper Announcement from Google I/O 2026 That Will Change How We Think About Apps # devchallenge # googleiochallenge # android # kotlin 7 reactions 2 comments 7 min read @vrushali_dev_15 wrote a standout deep-dive into AppFunctions — Android's new API for exposing app capabilities directly to AI agents. With 10 years of Android experience behind the lens, this post goes far beyond the surface announcement to map out the full architectural shift this signals and what developers should be thinking about right now, even before shipping a single AppFunction. I gave Gemini 3.5 Flash a CVE-fix PR to review. It found another bug in the same file. Google I/O Writing Challenge Submission Vicente Junior Vicente Junior Vicente Junior Follow May 22 I gave Gemini 3.5 Flash a CVE-fix PR to review. It found another bug in the same file. # googleiochallenge # devchallenge # ai # gemini 9 reactions 1 comment 7 min read @vicente_junior_dev did something rare: actually tested the thing. Running Gemini 3.5 Flash across 3 real production PRs, including a CVE fix, the post documents what the model caught. Grounded, honest, and exactly the kind of first-person expe

New research suggests that dozens of monetized YouTube channels are run by people and organizations that the US government has sanctioned for their ties to Tehran.

YouTube is testing DMs in its mobile app, and US is now part of the experiment.

Diffusion AI is most common in image generation, but it can make text outputs much faster.

Originally published on clintech.me If you've integrated Google Maps into a React app and seen Autocomplete randomly stop working, Directions silently fail, or the API throw google is not defined on second render — you've hit the duplicate loading bug. Here's exactly what caused it in my case and how I fixed it. The setup that broke things While building delivery address flows at POLOM — a production e-commerce platform — I integrated Google Places Autocomplete across 20+ screens. I had the Maps JavaScript API loading in two places: A provider.tsx for global script loading across the app A useLoadGoogleMaps hook inside a shared component This caused race conditions. The Autocomplete and Directions APIs were initialising before the script fully resolved in some renders, silently failing in others. The failure wasn't consistent, which made it harder to catch. The fix Step 1 — Remove the global load Delete the script tag or next/script call in provider.tsx . There should be exactly one place the Maps API loads. Step 2 — Centralise in a hook Move all loading logic into a single useLoadGoogleMaps hook using dynamic loading. If you're on Next.js, next/script with strategy="afterInteractive" inside the hook is the right approach. Step 3 — Guard before initialising if ( ! window . google ?. maps ) return ; Check that the API is fully available before attempting to attach Autocomplete or Directions . Don't assume the script load event means every namespace is ready. Step 4 — Scope your ref correctly Bind the autocomplete instance to inputRef.current explicitly. If the component remounts, re-initialise the binding — don't assume the previous instance is still attached. The result One load, one source of truth, no race conditions. Autocomplete and Directions worked consistently across all 20+ screens without reinitialising on every render. Security — the step most developers skip Restrict your API key at the Google Cloud Console level: HTTP referrers: whitelist your domain onl

I got tired of paying for form services or spinning up a backend just to handle contact form submissions. So I built RG Forms — a contact form endpoint backed entirely by a Google Sheet you own. No server, no monthly fee, no third-party storing your data. The idea Most form tools store your submissions on their servers. You pay monthly, you depend on their uptime, and your data lives in their database. RG Forms does the opposite: every submission goes straight into a Google Sheet in your own Google Drive, sent by an Apps Script that you own and control. RG Forms provisions that sheet and script for you in about 90 seconds. After that, your endpoint runs forever at no cost — completely independent of any RG Forms server. Built for static sites If you host on GitHub Pages, Netlify, Vercel, Cloudflare Pages, or just plain HTML on a CDN, you've hit this wall: there's no backend to receive a form POST. The usual workarounds are a paid form service, a serverless function you have to write and maintain, or standing up a whole backend just for a contact form. RG Forms is built exactly for this. Your endpoint is a plain HTTPS URL you POST to straight from client-side JavaScript — no build step, no serverless function, no server of any kind. Drop the fetch call into your page and you're done. It pairs naturally with any static-site generator (Hugo, Jekyll, Astro, Eleventy, Next export) and any no-code builder that lets you add a snippet of JS. Your static site stays static; the form just works. How it's built RG Forms is a fully static web app. There's no RG Forms server, no database, no backend. Every API call during setup goes directly from your browser to Google using your own OAuth token. Setup (one time, in your browser): Your Browser ├─── Google OAuth ──▶ Short-lived token (memory only) ├─── Google Drive API ──▶ Creates Sheet + Drive folder └─── Apps Script API ──▶ Creates & deploys form handler Live endpoint (after provisioning): Your Website / App └─── POST to script

🚀 What I Built I created a collaborative AI Multi-Agent system using Google's new Agent Development Kit (ADK). The system functions as an automated Hollywood Production Team designed to streamline creative brainstorming. The user submits a simple movie prompt (e.g., "A movie about a time-traveling chef"), and the specialized agents work sequentially to refine the idea into a viable film concept. 🧠 My Agent Architecture My multi-agent team uses a sequential workflow tracking architecture consisting of two specialized agents running on gemini-2.5-flash : movie_writer : Takes the raw user input concept and expands it into a high-stakes, descriptive three-sentence movie plot. movie_critic : Automatically intercepts the writer's completed story context to deliver constructive structural improvements. These agents are orchestrated via a SequentialAgent pipeline configuration that manages data handoffs automatically. 🛠️ Key Learnings & Challenges Framework Evolution: I learned how to structure project modules using ADK 2.0's directory scanning conventions ( __init__.py mapping definitions). Overcoming Roadblocks: I originally ran into layout separation issues on Windows where the backend command runner could not discover the python modules. Resolving this taught me how the google.adk.cli maps working directory environments ( ./app ). Handling API Constraints: Dealing with transient API capacity limits (like standard 503 backend service spikes) taught me how crucial error handling and session resets are when building live AI tools.

If you've uploaded a song to YouTube, Google almost certainly considers your video fair game for training its Lyria music AI, it just won't admit it right now. A group of independent musicians is suing Google, claiming that it illegally used songs they uploaded to YouTube to train its Lyria 3 model. Google has filed […]

Google is making some changes to how it saves your interactions with Search. In an email sent to users, Google says it will save the images, files, audio, and video you use to search under a new "Search Services History" setting. That includes the images you search for with Google Lens, recordings from its real-time […]

In 2025 Google Cloud added G4 , powered by NVIDIA's RTX PRO 6000 Blackwell Server Edition GPUs to their offering, allowing them to offer hardware not only for AI applications, but also for other applications, such as rendering, simulations or gaming. A single G4 instance with one accelerator ( g4-standard-48 ) comes equipped with 48 CPU cores, 180 gigabytes of RAM and 96 gigabytes of GPU memory. This is a lot of resources for a single cloud workstation, that only the most demanding workstreams would utilize. Most professionals who require a graphics accelerator to do their job, don't really need this much compute power for day to day tasks. It wasn't financially reasonable to pay for a G4 instance, when you weren't utilizing all the resources you paid for. If only there were smaller machine types… If only you could share that one very powerful GPU between multiple virtual machines… Introducing fractional VMs! During Google Cloud Next 2026, Google announced GA for fractional G4 VMs and was the first provider to bring vGPU functionality to RTX PRO 6000 accelerators. vGPU stands for virtual graphical processing unit . Just like VMs (virtual machines) are a way to split one physical computer into smaller, independent systems, vGPU allows for a single physical accelerator to be split into 2, 4 or 8 virtual accelerators! The new fractional machine types ( g4-standard-24 , g4-standard-12 , g4-standard-6 ) now allow you to perfectly match the compute capabilities to your needs! Who is it for? The existence of those new machine types makes it much more cost-efficient to move many GPU-dependent tasks to the cloud. Replacing physical workstations in offices with cloud infrastructure is not a new thing , but till now, Google Cloud didn't offer a good platform for those who needed workstations to process images, post-process videos, simulate physics or render 3D graphics. Those users now can get exactly the hardware they need, allowing their companies to move away from maintaini

You’ve spent weeks, maybe months, tracking down bugs, optimizing your user interface, and wrestling with backend security rules. You compile your native release build or run your final production compilations, thinking the hardest part of the journey is officially behind you. Then you open the Google Play Console, and you’re hit with the ultimate indie developer roadblock: the mandatory 12-tester and 14-day closed testing requirement . Many independent creators view this process as a simple download checklist. You might think, "I'll just find 12 people to download the app, leave it on their phones for two weeks, and wait it out." However, treating the testing phase as a static metric is the fastest way to get rejected during the final production access review. So, what is Google actually tracking in the background during these two weeks? Let’s take a deep dive into the core algorithmic requirement that determines your success: Continuous Engagement . 🔄 Decoding "Continuous Engagement" Google Play policies are not designed as a simple box-checking exercise. The underlying goal of the algorithm is to verify if your application is genuinely functional, stable, and being tested by an organic user base before it reaches millions of production users. To enforce this, Google's advanced systems actively monitor the devices connected to your closed test track over the 14-day timeline: Background Device Pings: Google Play Services regularly collects background automated signals (ping logs) from the devices where your test build is active. Real User Interaction: Leaving an app to rot in an application drawer without ever opening it is instantly flagged by the algorithm. Google measures whether the app is actively opened daily and tracks active interaction metrics within the build. Feedback Loops: The system monitors whether your test community is utilizing the internal testing channel on the Play Store to send private developer feedback and crash reports. 📉 The Illusion of "Ju

The Argentine national team will be Google’s test bench and technological showcase during the World Cup.

Google just made it significantly cheaper to enjoy its budget AI subscription tier.

Voice translations preserve speaker's tone, pacing, pitch—with SynthID watermarks for security.