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What's the Best Python Memory Profiler for Detailed Line-by-Line Reports?

Linda Hamilton
Release: 2024-12-10 11:02:09
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What's the Best Python Memory Profiler for Detailed Line-by-Line Reports?

Recommended Python Memory Profiler

Python developers often seek to optimize memory usage in their applications to enhance performance. To evaluate memory consumption and identify memory-intensive sections in code, several memory profilers are available. Among these, three notable options are Python Memory Validator, PySizer, and Heapy.

Considering the desired features of providing detailed information with minimal code modifications, memory_profiler emerges as a highly recommended option. Developed by the author of the question, this module offers a comprehensive line-by-line report of memory usage.

Benefits of using memory_profiler:

  • Generates detailed reports highlighting memory consumption at the line level.
  • User-friendly setup, requiring only a decorator (@profile) and running with the -m memory_profiler flag.
  • Cross-platform compatibility, working on both Unix and Windows (with psutil installed for Windows).

Example Output:

Line #    Mem usage  Increment   Line Contents
==============================================
     3                           @profile
     4      5.97 MB    0.00 MB   def my_func():
     5     13.61 MB    7.64 MB       a = [1] * (10 ** 6)
     6    166.20 MB  152.59 MB       b = [2] * (2 * 10 ** 7)
     7     13.61 MB -152.59 MB       del b
     8     13.61 MB    0.00 MB       return a
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This report provides a clear breakdown of memory consumption throughout the function, allowing developers to pinpoint memory bottlenecks efficiently.

For detailed memory analysis and compatibility with various platforms, memory_profiler offers an excellent solution.

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