PR summary

Add a fast path for np.insert with empty integer insertion indices. The result is still a copy, and the path keeps the existing empty-assignment step so values validation behavior is preserved.

ASV quick comparison against main:

bench_function_base.Insert.time_empty_indices((100, 100), 0, list):     50.8 us -> 39.9 us
bench_function_base.Insert.time_empty_indices((100, 100), None, array): 45.4 us -> 24.7 us
bench_function_base.Insert.time_empty_indices((1000,), 0, list):        39.7 us -> 19.3 us
bench_function_base.Insert.time_empty_indices((1000,), 0, array):       37.2 us -> 17.4 us
bench_function_base.Insert.time_empty_indices((1000,), None, array):    37.5 us -> 17.0 us
bench_function_base.Insert.time_empty_indices((100, 100), None, list):  52.5 us -> 22.0 us
bench_function_base.Insert.time_empty_indices((100, 100), 0, array):    64.3 us -> 22.7 us
bench_function_base.Insert.time_empty_indices((1000,), None, list):     92.4 us -> 30.4 us

First time committer introduction

I am a NumPy user/contributor looking at small, focused performance improvements in common array operations. I will handle review discussion and follow-up changes directly.

AI Disclosure

LLM / Harness: hybrid.

AI assistance was used to inspect the codebase, run local commands and benchmarks, draft PR text, and help prepare candidate patches. I reviewed the generated suggestions, selected the final changes, and am responsible for the code, submission, and follow-up discussion. Some PR text and candidate code edits were drafted with AI assistance; the final patch and text were reviewed and edited by me.