If you've ever tried to pull Google Trends data in Python, you know the drill. Install pytrends, run it on a few keywords, feel great. Run it on a few hundred, get a wall of 429 errors.

Then pytrends got archived in April 2025. Google announced an official Trends API, but it's invite-only. So for most of us, the old way is just... gone.

I spent a long time on this problem, so here's what I learned, and what I use now.

First, the part most people miss: related topics

Everyone knows the Google Trends line chart. Fewer people use the bit underneath it: related topics .

Related queries show you what people typed . Related topics show you what they meant . "air fryer recipes", "best air fryer" and "ninja air fryer" are three queries, but Google groups them under topics like Air fryer (Cooking appliance) or Ninja (Brand) . That's gold for content planning, because you see the real themes, not 50 variations of the same search.

The catch? It's the hardest part of Trends to get at scale.…