27. 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.

• 27.1. bdb Debugger framework
• 27.2. faulthandler Dump the Python traceback
  • 27.2.1. Dumping the traceback
  • 27.2.2. Fault handler state
  • 27.2.3. Dumping the tracebacks after a timeout
  • 27.2.4. Dumping the traceback on a user signal
  • 27.2.5. Issue with file descriptors
  • 27.2.6. Example
• 27.3. pdb The Python Debugger
  • 27.3.1. Debugger Commands
• 27.4. The Python Profilers
  • 27.4.1. Introduction to the profilers
  • 27.4.2. Instant Users Manual
  • 27.4.3. profile and cProfile Module Reference
  • 27.4.4. The Stats Class
  • 27.4.5. What Is Deterministic Profiling?
  • 27.4.6. Limitations
  • 27.4.7. Calibration
  • 27.4.8. Using a custom timer
• 27.5. timeit Measure execution time of small code snippets
  • 27.5.1. Basic Examples
  • 27.5.2. Python Interface
  • 27.5.3. Command-Line Interface
  • 27.5.4. Examples
• 27.6. trace Trace or track Python statement execution
  • 27.6.1. Command-Line Usage
    • 27.6.1.1. Main options
    • 27.6.1.2. Modifiers
    • 27.6.1.3. Filters
  • 27.6.2. Programmatic Interface
• 27.7. tracemalloc Trace memory allocations
  • 27.7.1. Examples
    • 27.7.1.1. Display the top 10
    • 27.7.1.2. Compute differences
    • 27.7.1.3. Get the traceback of a memory block
    • 27.7.1.4. Pretty top
  • 27.7.2. API
    • 27.7.2.1. Functions
    • 27.7.2.2. DomainFilter
    • 27.7.2.3. Filter
    • 27.7.2.4. Frame
    • 27.7.2.5. Snapshot
    • 27.7.2.6. Statistic
    • 27.7.2.7. StatisticDiff
    • 27.7.2.8. Trace
    • 27.7.2.9. Traceback