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Here’s a highly optimized version of your code for both **runtime** and **memory**, based on the profile hot spots. - **Avoid repeated summing** for checking lengths in a growing list — we keep a running sum. - **Avoid repeatedly copying lists/dicts** by using lists of indices and marking to remove in one pass, and using set operations for fast membership checks. - **Avoid creating lots of small dicts** and list extensions inside loops. - **Combine related generator expressions** so costly operations are only done once. - **Group similar linear scans** into one to minimize number of loops over `queue`. - Use **pre-allocated lists and sets** where it saves time. Here's the rewritten function (all comments preserved except where the code logic was changed). **Key optimizations:** - Only a *single pass* over queue for setup. - No repeated `.append(dict)`; pass only indices around until the end. - Use `.clear()` for lists inside dict to avoid reallocations. - Use lists of lengths for O(1) access everywhere. - Maintain a running sum for batch size check, not repeated `sum`. This should **dramatically cut runtime**, especially at the hot spots from your line profiler output. If you need even more speed and the queue is huge/long-lived, consider reworking the data structure for the queue itself (`deque`, heap, etc.), but for code-level optimization this is near optimal for this algorithm! |
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