Calculate total viewership count per game category using Twitch's current API in React

[JackHero77]

I’m working on a React project and need to get the total number of viewers watching each game category on Twitch. With the current Twitch API, I can’t find a direct endpoint that gives me total viewers per game category. The API only provides viewer counts for individual streams.

I can access the top games endpoint and the streams endpoint, but neither gives me what I need directly. My thinking is that I should fetch all active streams, group them by their game category, and then add up all the viewer counts for each group.

Has anyone implemented something similar? I’m looking for suggestions on the best approach to aggregate this data in React. Should I be making multiple API calls or is there a more efficient way to handle this?

[ameliat]

You’re on the right track. I built this exact thing last year and had to fetch streams in batches since Twitch caps you at 20 per request. Just keep hitting the streams endpoint with different “after” cursors until you’ve got enough data. Watch out for rate limits though - they’ll nail you if you’re not careful. I’d add exponential backoff and cache results for 5-10 minutes. Viewer counts don’t need to be real-time anyway. For aggregation, I used a Map grouped by game_id and just summed up the viewer_count values. The annoying part is figuring out how many streams to fetch since there’s no total count. I went with 500-1000 active streams - covers most popular categories pretty well.

[OwenNebula55]

Been there. React Query or SWR handles the data fetching and caching automatically - that’s your best bet. Batch your requests: grab top games first, then run parallel requests for stream data using Promise.all() with chunked game IDs. Here’s the thing - you don’t need every stream for decent totals. I fetch around 100 streams per popular category and get 90% accuracy on viewer counts. Use a reducer to aggregate data as it comes in instead of waiting for everything to finish. Keeps the UI snappy. Watch out though - viewer counts change constantly, so debounce your state updates or you’ll get crazy re-renders. If you’re processing thousands of streams, throw the heavy aggregation into Web Workers.

[Stella_Dreamer]

The Problem: You’re trying to get the total number of viewers for each game category on Twitch using the Twitch API, but the API only provides viewer counts for individual streams. You want an efficient way to aggregate this data in your React project.

Understanding the “Why” (The Root Cause):

The Twitch API doesn’t offer a direct endpoint for total viewers per game category. This means you need to fetch data from multiple endpoints and perform the aggregation yourself. Fetching all streams is inefficient and costly (in terms of API calls and processing power). The solution involves strategically limiting the number of streams fetched to reduce the load.

Step-by-Step Guide:

1. Fetch Top Games and their IDs: First, use the Twitch API’s “Top Games” endpoint to retrieve a list of the most popular games. This endpoint provides you with a list of game_ids for the top games. Limit the number of games fetched to a reasonable number (e.g., 50) to make the subsequent requests manageable. This significantly reduces the number of API calls needed compared to fetching all streams.

2. Batch Stream Data Requests: The Twitch Helix API allows you to specify multiple game_ids in a single request. Group the game_ids from Step 1 into batches (respecting API request limits) and make parallel requests using Promise.all() (or a similar method) to the Twitch “Streams” endpoint. Each request should include a game_id parameter filtering streams to specific game categories. You’ll likely need to use pagination (after cursor) to fetch all streams for each batch, handling rate limits carefully (exponential backoff is recommended).

3. Aggregate Viewer Counts: As you receive the stream data, use a reducer (or a similar aggregation technique) to group streams by game_id and sum their viewer_count properties. This step can be done incrementally as data arrives from the API, allowing for a snappier UI if needed. Consider using a Map for efficient grouping, particularly with a large amount of data.

4. Handle Rate Limits and Caching: Implement exponential backoff to handle Twitch API rate limits. Cache the results (for example, using React Query or SWR) for a period of 5-10 minutes, as viewer counts don’t require real-time accuracy. This significantly reduces the number of API calls and improves performance.

5. Optimize for Large Datasets: If you’re dealing with thousands of streams, offload the heavy aggregation task to Web Workers to prevent blocking the main thread and maintain UI responsiveness.

Common Pitfalls & What to Check Next:

• API Rate Limits: Carefully monitor and handle Twitch API rate limits. Implement exponential backoff to avoid getting your requests throttled.
• Pagination: The Streams endpoint uses pagination. Make sure to properly handle the cursor parameter in your requests to retrieve all streams for each game category.
• Error Handling: Implement robust error handling to gracefully manage potential issues with API requests, network connectivity, and data processing.
• Data Accuracy: Remember that viewer counts are constantly changing, so the aggregated totals will represent an approximate value at a specific point in time.

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