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Create a Jupyter Notebook that, using `polars` to process the data, does a thorough exploratory data analysis of data saved in `youtube_videos.db`, for all columns.
The entire pipeline executes in a single call stack. No promises are created, no microtask queue scheduling occurs, and no GC pressure from short-lived async machinery. For CPU-bound workloads like parsing, compression, or transformation of in-memory data, this can be significantly faster than the equivalent Web streams code — which would force async boundaries even when every component is synchronous.。WPS下载最新地址对此有专业解读