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

Source: Dev.to

Why Google Autocomplete?

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

• Every suggestion comes from real searches
• It reflects user intent
• It 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.

The goal was simplicity and hackability.

The Scraping Logic

Each base keyword goes through a configurable expansion pipeline:

1. Base keyword input
2. Optional prepend/append words
3. Character expansion: a–z and a–z + 0–9
4. Google Autocomplete request
5. Deduplication
6. Live UI update

Example request

params = {
    "client": "firefox",
    "q": query,
    "hl": language,
    "gl": country
}
response = requests.get(
    "https://suggestqueries.google.com/complete/search",
    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 via app.after()

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

These measures keep 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)

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

Three options are offered:

👉 Get KeySage here:

Why Release the Source Code?

Developers learn best from real tools — not toy examples. With the source you can:

• Add async requests
• Improve clustering
• Add new export formats
• Integrate other suggestion sources
• Turn it into a CLI or API

The project 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: