Retrieving Access Token for Google APIs

Gists

This sample is for retrieving access token for Google APIs. I created this for studying newStateToken().

Preparation

In order to use this sample, please do as follows.

  1. Deploy and launch Web Apps for retrieving redirect uri
    • On the Script Editor
      • File
      • -> Manage Versions
      • -> Save New Version
      • Publish
      • -> Deploy as Web App
      • -> At Execute the app as, select “your account”
      • -> At Who has access to the app, select “Only myself”
      • -> Click “Deploy”
      • -> Click “latest code” (By this click, it launches the authorization process.)
      • -> Please copy URL shown in the top of your browser as the redirect URI. And please modify the redirect URI like https://script.google.com/macros/s/#####/usercallback.
  2. Open console project
    • On the Script Editor
      • -> Resources
      • -> Cloud Platform Project
      • -> Click “Projects currently associated with this script”
      • -> Click API in start guide
  3. Retrieve client id and client secret
    • On the Console Project
      • Click authentication information at left side
      • -> Create a valid Client ID as OAyth client ID
      • -> Choose Web Application
      • -> Input Name (This is a name you want.)
      • -> Input redirect URI that you have already copied.
      • -> done
      • -> Please copy client ID and client Secret in a pop-up window.

Here, you have client ID, client Secret and redirect URI to retrieving refresh token and access token. These can be used for following sample script.

Updated: GAS Library - SOUWA

SOUWA means summing in Japanese. SOUWA can sum string elements in an array at the high speed. The speed of SOUWA with the pyramid algorithm is about 380 times faster than that of the standard method. New algorithm for summing array elements was developed for SOUWA. You can see the detailed report of this library at here. If you are interested in this, I’m glad.

It was updated to v1.0.2. Please check it out. https://github.com/tanaikech/SOUWA_GAS

Benchmark: Retrieving Values from Deep Nested JSON at Golang

This sample script is for retrieving values from a deep nested JSON. There are 2 patterns. So for these, the benchmark were measured.

Script :

package main

import (
    "encoding/json"
    "testing"
)

const (
    data = `{
      "A_key1": {
        "B_key1": {
          "C_key": "value"
        }
      }
    }`
)

func BenchmarkB1(b *testing.B) {
    b.ResetTimer()
    for i := 0; i < b.N; i++ {
        var p map[string]interface{}
        json.Unmarshal([]byte(data), &p)
        a1 := p["A_key1"]
        a2 := p["A_key1"].(map[string]interface{})["B_key1"]
        a3 := p["A_key1"].(map[string]interface{})["B_key1"].(map[string]interface{})["C_key"]
        _ = a1 // --> map[B_key1:map[C_key:value]]
        _ = a2 // --> map[C_key:value]
        _ = a3 // --> value
    }
}

func BenchmarkB2(b *testing.B) {
    b.ResetTimer()
    for i := 0; i < b.N; i++ {
        var p map[string]interface{}
        json.Unmarshal([]byte(data), &p)
        b1 := p["A_key1"]
        temp, _ := json.Marshal(b1)
        json.Unmarshal(temp, &p)
        b2 := p["B_key1"]
        temp, _ = json.Marshal(b2)
        json.Unmarshal(temp, &p)
        b3 := p["C_key"]
        _ = b1 // --> map[B_key1:map[C_key:value]]
        _ = b2 // --> map[C_key:value]
        _ = b3 // --> value
    }
}

Result :

$ go test -bench .
BenchmarkB1-4             300000              4177 ns/op
BenchmarkB2-4             100000             13619 ns/op
PASS

It was found that the process cost of json.Unmarshal() was high. json.Unmarshal() for test 2 is 3 times larger than that for test 1.

Reopening Current File as a File with New Name at Sublime

This is for Sublime Text. This sample is for reopening current file as a file with new file name. The current file is closed when reopening a new file.

newfilename = "new file name"
contents = self.view.substr(sublime.Region(0, self.view.size()))
window = self.view.window()
window.run_command('close_file')
view = window.new_file()
view.set_name(newfilename)
view.settings().set("auto_indent", False)
view.run_command("insert", {"characters": contents})
view.set_scratch(True)
view.run_command("prompt_save_as")

Flow of this sample

  1. Copy all text on current file to memory (contents).
  2. Close current file.
  3. Create new file with new file name.
  4. Paste contents to new file.
  5. Open dialog box for saving new file.

Search Route and Embedding Map using Custom Function on Spreadsheet

This sample script is for searching route between place A and B and embedding a map by custom function on Spreadsheet.

I think that this method is one of various ideas.

Problem

When the map is embedded to a cell on spreadsheet as an image, the function =IMAGE() is suitable for this situation. However, Class Maps, setFormula() for importing =IMAGE() and DriveApp.createFile() for creating images from maps also cannot be used for custom functions.

Updated: CLI Tool - goris

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

Today, it was updated to v1.1.0. Please check it out. https://github.com/tanaikech/goris

When images are matched to a searched image, web pages with matching images are retrieved. These are web pages displayed on Google top page. When this is not used, images are retrieved. This was added as a boolean option. (This was added by a request.)

Giving and Retrieving Parameters for Chart at GAS

This sample script is for retrieving parameters from a chart. The chart created by both Google Apps Script and manually operation can be used.

Creates Chart

When a chart is created, it supposes following parameters.

var parameters = {
  "title": "x axis",
  "fontName": "Arial",
  "minValue": 0,
  "maxValue": 100,
  "titleTextStyle": {
    "color": "#c0c0c0",
    "fontSize": 10,
    "fontName": "Roboto",
    "italic": true,
    "bold": false
  }
};

.setOption('hAxis', parameters)

Retrieve Parameters From Chart

For the chart created by above parameters, in order to retrieve the parameters, it uses following script.

Error Handling for Subprocess at Python

This sample is for error handling for subprocess.Popen. It confirms whether the execution file is existing. If the execution file is also not in the path, the error message is shown.

import subprocess

res = subprocess.Popen(
    "application",  #  <- Execution file
    stdout=subprocess.PIPE,
    stderr=subprocess.PIPE,
    shell=True
).communicate()

if len(res[1]) == 0:
    print("ok: Application is existing.")
else:
    print("Error: Application is not found.")

Using Constructor Between Classes at Python

This sample is for using constructor between classes at Python.

Sample :

class test1:

    def __init__(self):
        self.msg = "sample text"


class test2:

    def __init__(self):
        self.msg = test1().msg


print(test2().msg)

>>> sample text

Slice Created by Split at Golang

When a string without no strings is split by strings.Split(), the created slice is the same to the slice created by make(). The length of the slice doesn’t become zero.

Sample script :

package main

import (
    "fmt"
    "strings"
)

func main() {
    sample1a := strings.Split("", " ")
    fmt.Printf("%v, %v, '%v', %v, %+q\n", sample1a, len(sample1a), sample1a[0], len(sample1a[0]), sample1a[0])

    sample1b := make([]string, 1)
    fmt.Printf("%v, %v, '%v', %v, %+q\n", sample1b, len(sample1b), sample1b[0], len(sample1b[0]), sample1b[0])

    var sample2a []string
    fmt.Printf("%v, %v\n", sample2a, len(sample2a))

    sample2b := []string{}
    fmt.Printf("%v, %v\n", sample2b, len(sample2b))
}

Result :

strings.Split() : [], 1, '', 0, ""
make()          : [], 1, '', 0, ""
var                : [], 0
[]string{}      : [], 0

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).