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If you are building a social media dashboard, you will eventually hit the N+1 problem. You fetch a team. Then you loop through their accounts. Then you loop through their posts. Then you loop through the analytics for each post. 
# The Bad Way
for post in posts:
    analyze(post) # Slow. Painful. API limits will eat you.

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Vectorization & Batching

When dealing with data-heavy APIs like bundle.social (or underlying platforms), you need to think in batches.
  1. Batch Requests: Don’t ask for one post’s analytics. Ask for 50.
  2. Vectorized Processing: If you are calculating engagement rates in Python (pandas) or JS, process the whole array at once.

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Why it matters for Social APIs

Social data is “bursty”. A user connects an account and wants to see 3 years of history now. If you loop, your UI hangs. If you batch and vectorize, you look like a wizard. See also: Rate Limits to understand why batching saves your wallet.