Retrieving User Information with Shared Spreadsheet

This sample script retrieves the user information which is editing the shared spreadsheet.

It was found as follows.

  • User information retrieving by Class Session is the owner and users which installed triggers by themselves.
  • When each user installs a trigger, user information retrieving by Class Session losts the accuracy. So user information has to be retrieved using a temporally installed trigger.
  • Using onOpen(), it cannot directly install triggers and authorize.
  • Using menu bar, it can install triggers and authorize Google Services using API.

Here, I thought 2 problems.

CLI Tool - goris

Overview

This is a CLI tool to search for images with Google Reverse Image Search.

Motivation

Because I had wanted to search for images with an image URL and file on my terminal, I created this. This can download images from searched image URLs.

The detail information and how to get this are https://github.com/tanaikech/goris.

CLI Tool - ggsrun

Overview

This is a CLI tool to execute Google Apps Script (GAS) on a terminal.

Motivation

Will you want to develop GAS using CoffeeScript on your local PC? Generally, when we develop GAS, we have to login to Google using own browser and develop it using Javascript on the Script Editor. Recently, I have wanted to have more convenient local-environment for developing GAS. So I created this “ggsrun”.

CLI Tool - ggsrun

Overwriting Spreadsheet to Existing Excel File

This sample script converts a spreadsheet to excel file, and overwrites the excel file to the existing excel file. When you use this script, at first, please confirm whether Drive API is enabled at Google API console. Because the existing excel file is overwritten, the file name and file ID are not changed.

function overWrite(src_spreadsheetId, dst_excelfileId) {
  var accesstoken = ScriptApp.getOAuthToken();
  return UrlFetchApp.fetch(
    "https://www.googleapis.com/upload/drive/v3/files/" +
    dst_excelfileId +
    "?uploadType=multipart",
    {
      method: "PATCH",
      headers: {Authorization: "Bearer " + accesstoken},
      contentType: "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
      payload: function(a, s) {
        return UrlFetchApp.fetch(
          "https://www.googleapis.com/drive/v3/files/" +
          s +
          "/export?mimeType=application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
          {
            method: "GET",
            headers: {Authorization: "Bearer " + a},
            muteHttpExceptions: true
          }
        ).getBlob().getBytes();
      }(accesstoken, src_spreadsheetId)
    }
  ).getContentText();
}

Converting Spreadsheet to PDF

Converting Spreadsheet to PDF

This sample script converts from a spreadsheet to a PDF file which has all sheets in the spreadsheet. When you use this, please enable Drive API at Google API console.

var spreadsheetId = "#####";
var folderId = "#####";
var outputFilename = "#####";

DriveApp.getFolderById(folderId)
    .createFile(UrlFetchApp.fetch(
      "https://www.googleapis.com/drive/v3/files/" +
        spreadsheetId +
        "/export?mimeType=application/pdf",
      {
        method: "GET",
        headers: {Authorization: "Bearer " + ScriptApp.getOAuthToken()},
        muteHttpExceptions: true
      })
    .getBlob())
    .setName(outputFilename);

GAS Library - CreateImg

Recently, I had been looking for creating an image from coordinate data. Unfortunately I have never found them. So I made this. This Google Apps Script (GAS) library creates an image file from coordinate data.

You can see the detail information at https://github.com/tanaikech/CreateImg.

There is a part where I would like to improve in this library. That’s convByteSlice(). I think that there is the method to be faster about the part. If you know much about the logical operation using GAS, if you teach me about the improvements. I’m so glad.

Comprehension of GAS

Here, I would like to introduce a comprehension of GAS.

Input :

var data = [[[0], [1], [2], [3]], [[4], [5], [6], [7]]];

Output :

[[0.0, 2.0], [0.0, 2.0]]

Pattern 1

var a = [];
for (var i=0; i<data.length; i++) {
  var temp = [];
  for (var j=0; j<data[i].length; j++) {
    if (data[i][j][0] % 2 == 0) temp.push(j);
  }
  a.push(temp);
}
Logger.log(a)

Pattern 2

var b = [];
data.forEach(function(e1){
  var temp = [];
  e1.forEach(function(e2, i2){
    if (e2[0] % 2 == 0) temp.push(parseInt(i2, 10));
  });
  b.push(temp);
});
Logger.log(b)

Pattern 3

var c = [[parseInt(i, 10) for (i in e) if (e[i][0] % 2 == 0)] for each (e in data)];
Logger.log(c)

GAS can use JavaScript 1.7. So it can write as above.

Creating Spreadsheet from Excel file

These scripts can be executed on Script Editor. But, in order to use these, you have to enable Drive API of Advanced Google services and of Google API Console. “Drive API v2” can be used at Google Apps Script by enabling Drive API of Advanced Google services and of Google API Console.

How to use it is as follows.

  1. In the script editor, select Resources > Advanced Google services

  2. In the dialog that appears, click the on/off switch for Drive API v2.

Creating Downloaded Excel file as Spreadsheet

This is a sample GAS script to create an Excel file, which was downloaded from web, as Spreadsheet. By using Drive API, it can be achieved without access token.

Script :

function downloadFile(fileURL, folder) {
  var filename = fileURL.match(".+/(.+?)([\?#;].*)?$")[1];
  var response = UrlFetchApp.fetch(fileURL);
  var rc = response.getResponseCode();
  var blob = response.getBlob();
  var resource = {
    "mimeType": "application/vnd.google-apps.spreadsheet",
    "parents": [{id: folder}],
    "title": filename
  };
  var res = Drive.Files.insert(resource, blob);
  var fileInfo = [rc, res.title, blob.getBytes().length, res.id];
  return fileInfo;
}

Result :

[
    200,
    sample.xlsx,
    10000.0,
    ## file id ##
]

Google OAuth Verification & Application Privacy Policy

Registered Application Name: Workspace & Gemini AI Orchestration Engine

Application Purpose & Core Functionality:

This web page serves as the official homepage and privacy compliance interface for the application "Workspace & Gemini AI Orchestration Engine". This specialized developer utility is designed to research, benchmark, and optimize advanced integrations between Google Workspace services, the Google Apps Script API, and Gemini AI models (via Google Vertex AI / Gemini API endpoints).

The application facilitates automated multi-agent scaffolding, programmatic script deployment, project resource management, and structural analysis of Google Apps Script projects. It allows developers and autonomous AI agents (operating via Model Context Protocol / MCP) to securely evaluate execution performance, implement high-performance batch requests, and test agent-to-agent (A2A) workflows within a controlled and structured environment.

Google User Data Policy Compliance Statements:

1. Data Access & Specific Usage

Our application explicitly requests access to specific Google user accounts through OAuth scopes required strictly for interacting with the Google Apps Script API and Google Workspace endpoints. This access is utilized solely to execute user-initiated or agent-orchestrated programmatic operations—such as creating, modifying, deploying, or benchmarking script projects and executing automated workflows. No background automated extraction occurs without explicit session initiation.

2. Data Storage & Zero-Retention Policy

Adhering to a strict Zero-Retention Model, this application does not store, log, or persist any personal data, OAuth tokens, script source codes, or Google account configurations on any external server, database, or persistent storage medium. All data processing and API responses are handled entirely in-memory or securely on the client side within the active session context, ensuring complete cryptographic transient isolation.

3. Data Sharing & Third-Party Non-Disclosure

We maintain absolute data privacy. No data accessed via Google OAuth scopes is shared, sold, rented, or transferred to third-party entities, advertising networks, or data brokers. All data transmissions are strictly point-to-point, encrypted in transit using industry-standard protocols, and limited entirely to the direct channel between the execution environment and Google's official API gateways.

For inquiries regarding this developer application, technical benchmarks, or verification compliance, please refer to the official documentation and repositories linked on this homepage (tanaikech.github.io).