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How would you use line_profiler (a third-party tool) to get LINE-BY-LINE timing information within a specific function, more granular than cProfile's function-level data?

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Answer

Decorate the target function with @profile (line_profiler's marker decorator) and run the script with `kernprof -l -v script.py` — this produces a report showing the exact TIME SPENT on EACH INDIVIDUAL LINE within that function, pinpointing precisely which line (not just which function) is the actual bottleneck.
@profile  # requires running via kernprof, not a normal Python run
def process_data(data):
    cleaned = [x.strip() for x in data]      # line-level timing shown for THIS line
    filtered = [x for x in cleaned if x]      # and separately for THIS line
    return sorted(filtered)

# Run with: kernprof -l -v script.py
Real-world example Pinpointing the EXACT line inside a slow function responsible for most of its execution time, beyond what function-level profiling shows.

Common follow-ups: Why can't you simply 'import' the @profile decorator normally, and what does kernprof do to make it available?

Debugging & Profiling
All 15 Debugging & Profiling questions