cProfile
cProfile is a Python standard-library deterministic profiler that records function-call counts and execution-time statistics.
Fast Python: High performance techniques for large datasets
- How it is used
- Locates function-level bottlenecks before code optimization, including costs hidden inside subcalls and I/O.
- How deep it goes
- Reports calls and cumulative, inclusive, and exclusive function timings, but stops short of line-level breakdowns.
- Examples
- Uses a NOAA data downloader, cumulative-time reports, socket reads, and IPython timeit comparisons.
- What you can do after
- Diagnose/debug with it by running a script under cProfile and prioritizing functions or I/O paths with high cumulative time.
Read how Fast Python: High performance techniques for large datasets explains cProfile →
Advanced Algorithms and Data Structures
cProfile is Python's deterministic profiler for recording execution-time statistics for function and method calls.
- How it is used
- Profiles Huffman encoding and heap operations to identify where execution time accumulates.
- How deep it goes
- Records per-call, total, and cumulative timings, then filters and exports results without detailing cProfile usage.
- Examples
- Uses repeated Huffman-encoding runs and selected heap-building and heap-operation functions as profiling targets.
- What you can do after
- Diagnose/debug with cProfile by collecting, filtering, interpreting, and saving function timing statistics.
Read how Advanced Algorithms and Data Structures explains cProfile →
Related concepts
- profilingused by · Profiling is the measurement and analysis of a program’s runtime behavior and resource use to characterize performance and identify bottlenecks.
- Pythonuses · Python is a high-level, general-purpose, dynamically typed programming language known for readable syntax and automatic memory management.
- throughputmeasures · The amount of work, data, or output a system processes or completes per unit of time.
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