Hey everyone! I’m working on a project where I need to pick a random entry from a big Notion database. The problem is the API only lets me grab 100 items at a time. I can’t just get the total number of entries upfront either.
Right now I’m going through all the pages one by one until I hit the end, then picking a random entry. It works okay for small databases, but I’ve got this automated task that needs to pick random entries from a database with thousands of items. Plus, I’m worried about hitting API rate limits if I make too many requests at once.
Does anyone know a smarter way to grab a random entry from a big database like this? I’m looking for something that’s faster and won’t get me in trouble with rate limits. Any ideas would be super helpful! Thanks in advance!
hey, i had a similar issue. what worked for me was using a weighted random selection. basically, estimate the total items based on your first few API calls, then pick a random page number. grab that page and choose randomly from those 100 items. it’s not perfect, but way faster and less API intensive. hope this helps!
I’ve faced a similar challenge with large Notion databases. One approach that worked well for me was implementing a reservoir sampling algorithm. Here’s how it works:
Set a sample size (e.g., 100 items).
Fill your reservoir with the first batch of items.
For each subsequent batch, randomly replace items in the reservoir with a decreasing probability.
This method allows you to maintain a representative sample without processing the entire database. It’s efficient and respects API limits. You’ll need to tweak the implementation based on your specific use case, but it should significantly reduce API calls while still providing a random selection across the entire dataset.
Remember to implement proper error handling and backoff strategies to avoid hitting rate limits. Good luck with your project!
I’ve dealt with similar API limitations before, and one strategy that’s worked well for me is implementing a caching system. Basically, you can store the IDs of all the items in your database locally, updating it periodically (maybe once a day or week, depending on how often your database changes). Then, when you need a random item, you just pick a random ID from your local cache and fetch only that specific item from the API.
This approach significantly reduces API calls and speeds up the process. It does require some initial setup and maintenance, but it’s been a game-changer for my projects dealing with large datasets. Just make sure to handle edge cases, like when an item in your cache no longer exists in the actual database. It’s not perfect, but it’s a good balance between randomness, efficiency, and API friendliness.