
When Parallel Processing in Python Actually Helps (And When It Makes Things Worse)
Stop processing data one row at a time - but know when parallelization is worth the complexity
Parallel processing can turn a 10-minute data job into a 30-second one. But only if you use it correctly. Here is when to parallelize, when to stick with loops, and how to avoid the mistakes that make your code slower, not faster.
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