Avoid unnecessary function calls, I/O operations, and redundant checks that can significantly impact performance. Look for opportunities to consolidate operations, remove duplicate work, and streamline execution paths.
Avoid unnecessary function calls, I/O operations, and redundant checks that can significantly impact performance. Look for opportunities to consolidate operations, remove duplicate work, and streamline execution paths.
Common patterns to watch for:
Example improvements:
# Instead of repeated append() calls and redundant checks:
if location not in key_mapping:
key_mapping[location] = [key]
start_mapping[location] = [start]
end_mapping[location] = [end]
continue
key_mapping[location].append(key)
start_mapping[location].append(start)
end_mapping[location].append(end)
# Use efficient unpacking to avoid repeated operations:
if reordered_blocks:
_, memory_objs, starts, ends = zip(*reordered_blocks)
self.gpu_connector.batched_to_gpu(list(memory_objs), list(starts), list(ends), **kwargs)
# Remove unnecessary I/O operations:
# Instead of: if self.exists_in_put_tasks(key) or self.contains(key):
# Just use: if self.exists_in_put_tasks(key):
# The contains() call adds unnecessary RPC or I/O overhead
Always question whether each operation is truly necessary and look for opportunities to batch, cache, or eliminate redundant work entirely.
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