I Built a Google Autocomplete Keyword Tool in Python (Source Code Included)

Most keyword tools are just thin wrappers around Google Autocomplete — but they hide the implementation behind subscriptions, APIs, and dashboards you don’t control.

I wanted something different:

A local desktop app

Written in plain Python

No API keys

No accounts

Full access to the source code

So I built KeySage, a Google Autocomplete keyword research tool using Tkinter, ttkbootstrap, threading, and requests — and I’m releasing both the EXE and the full source code.

Why Google Autocomplete?

Google Autocomplete is one of the most honest keyword datasets available.

Every suggestion:

Comes from real searches

Reflects user intent

Surfaces long-tail queries early

Under the hood, most SEO tools call the same endpoint:

https://suggestqueries.google.com/complete/search

KeySage connects to it directly — no API, no authentication.

High-Level Architecture

KeySage is a single-process desktop app with a background scraping thread.

Main components:

UI layer → Tkinter + ttkbootstrap

Networking → requests

Concurrency → threading + Event flags

Data model → sets + defaultdict

Exports → txt / csv / json

The goal was simplicity and hackability.

The Scraping Logic

Each base keyword goes through a configurable expansion pipeline:

Base keyword input

Optional prepend/append words

Character expansion:

a–z

a–z + 0–9

Google Autocomplete request

Deduplication

Live UI update

Example request:

params = {
    "client": "firefox",
    "q": query,
    "hl": language,
    "gl": country
}
requests.get(GOOGLE_SUGGEST_URL, params=params)

Results are streamed back to the UI using app.after() to keep Tkinter thread-safe.

Threading Without Freezing the UI

Tkinter is single-threaded, so scraping runs in a background thread.

Key patterns used:

threading.Thread(..., daemon=True)

threading.Event() for safe cancellation

UI updates marshaled back to the main loop

This allows:

Real-time keyword output

Instant cancellation

No UI hangs

Rate Limiting & Stability

Google doesn’t love aggressive scraping.

KeySage includes:

Built-in delays between requests

Optional proxy support

Stop-safe execution at every loop

This keeps the app usable without being reckless.

Automatic Keyword Clustering

After scraping, keywords are grouped by root word:

root = keyword.split()[0].lower()
clusters[root].append(keyword)

Simple? Yes.
Effective for content planning? Also yes.

Clusters are preserved across all export formats.

Exporting Data (Developer-Friendly)

Supported formats:

TXT → human-readable clusters

CSV → SEO tools & spreadsheets

JSON → automation & pipelines

Everything stays open and editable.

UI: Tkinter, But Not Ugly

The interface uses ttkbootstrap to avoid the “default Tkinter look”.

Features:

Responsive layout

Themed widgets

Collapsible advanced settings

Live scrolling output

Built-in help window

It’s intentionally minimal — no Electron, no web stack.

EXE vs Source Code

I’m offering three options:

Windows EXE ($7) — run instantly, no Python required

Full Source Code ($10) — learn, modify, extend

EXE + Source ($12) — best of both

👉 Get KeySage here:
https://gum.new/gum/cmk5ca5og002f04lbfga113vy

Why Release the Source Code?

Because developers learn best from real tools — not toy examples.

You can:

Add async requests

Improve clustering

Add new export formats

Integrate other suggestion sources

Turn it into a CLI or API

This is meant to be a foundation.

Final Thoughts

KeySage isn’t trying to replace enterprise SEO platforms.

It’s a transparent, hackable keyword tool built with:

Python

Common libraries

Simple architecture

No vendor lock-in

If you want a practical example of a real-world scraping + desktop app — or a tool you can actually use — this is for you.

👉 Buy / Download KeySage:
https://gum.new/gum/cmk5ca5og002f04lbfga113vy