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Debugging and Profiling¶

These libraries help you with Python development: the debugger enables you to step through code, analyze stack frames and set breakpoints etc., and the profilers run code and give you a detailed breakdown of execution times, allowing you to identify bottlenecks in your programs. Auditing events provide visibility into runtime behaviors that would otherwise require intrusive debugging or patching.

  • Audit events table
  • bdb — Debugger framework
  • faulthandler — Dump the Python traceback
    • Dumping the traceback
    • Fault handler state
    • Dumping the tracebacks after a timeout
    • Dumping the traceback on a user signal
    • Issue with file descriptors
    • Example
  • pdb — The Python Debugger
    • Debugger Commands
  • The Python Profilers
    • Introduction to the profilers
    • Instant User’s Manual
    • profile and cProfile Module Reference
    • The Stats Class
    • What Is Deterministic Profiling?
    • Limitations
    • Calibration
    • Using a custom timer
  • timeit — Measure execution time of small code snippets
    • Basic Examples
    • Python Interface
    • Command-Line Interface
    • Examples
  • trace — Trace or track Python statement execution
    • Command-Line Usage
      • Main options
      • Modifiers
      • Filters
    • Programmatic Interface
  • tracemalloc — Trace memory allocations
    • Examples
      • Display the top 10
      • Compute differences
      • Get the traceback of a memory block
      • Pretty top
        • Record the current and peak size of all traced memory blocks
    • API
      • Functions
      • DomainFilter
      • Filter
      • Frame
      • Snapshot
      • Statistic
      • StatisticDiff
      • Trace
      • Traceback

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test — Regression tests package for Python

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Audit events table

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Last updated on Nov 14, 2023. Found a bug?
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