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Best Python Debugging Tools in 2023 

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Debugging is an important aspect of any software development lifecycle. It enables developers to identify and fix problems in their code, in order to make sure that their applications function properly, Effective debugging tools are becoming more and more necessary as Python keeps holding onto its position as one of the most popular programming languages. In this blog, we will cover some of the popular debugging tools Python has to offer. But before that let’s start with little overview of Python Debugging.

Introduction to Python Debugging

The act of debugging involves locating and fixing flaws, or “bugs,” in computer programs. In order to guarantee that programs work as intended, it is a crucial component of software development. Python is a well-liked option among developers because of its clarity and readability. In order to speed up their debugging procedures, Python developers have access to a wide variety of potent debugging tools. For understanding and leveraging these tools, hire dedicated developers who can help you develop robust Python applications.

# Built-in pdb

Python’s built-in debugger, pdb is a versatile tool that provides a basic yet effective console-based debugging environment. It can be raised in multiple ways, making it highly accessible for debugging python programs. Pdb allows developers to set breakpoints, set through code, inspect variables, evaluate expressions, and even allows to attach the running process.

Key features of pdb:

  • Set breakpoints and step through code
  • Inspect variables, stacks, and threads
  • Evaluate expressions in context
  • Attach to running processes
  • Issue console commands for control flow

pdb provides a simple yet powerful interface for debugging Python code. 

Some key commands include:

  • l (list) – show code fragment 
  • n (next) – execute next line
  • s (step) – step into functions
  • b (breakpoint) – set breakpoint
  • c (continue) – resume execution

Though basic, pdb is quite flexible. It allows fine-grained control when stepping through code. pdb is ideal for inspecting what is happening locally in a function or method. Due to its simplicity, pdb is usually the quickest way to start debugging.

# IPython 

IPython is an enhanced Python shell with powerful introspection capabilities. The IPython shell allows inspecting and debugging Python code interactively. 

Some useful features of IPython for debugging:

  • Tab completion on object attributes and methods
  • Dynamic object information with ? operator
  • %pdb magic command enables pdb during execution
  • %debug magic enters post-mortem debugging
  • Debugger API integration with Pdb, PyCharm, etc

IPython makes it easy to inspect large nested data structures. The shell keeps variables available across sessions. IPython is ideal for interactively developing and testing code fragments. Using IPython can speed up debugging cycles by enabling quick introspection of objects and state.

# PyCharm Debugger

PyCharm is a popular Python integrated development environment (IDE), it is a graphical debugger that significantly improves  the  debugging experience. It has a rich visual interface that helps set breakpoints, steeping through code, inspect variables and much more. Everything is comparatively easy to use because of it being a graphical debugger.

It supports:

  • Breakpoints, stepping, and variable inspection
  • Debugging multi-threaded apps 
  • Remote debugging over SSH
  • Integration with pdb

PyCharm provides a rich visual interface for debugging. The variable values are displayed inline which reduces context switching. Complex bugs can be examined by evaluating nested expressions. 

PyCharm offers productive debugging features like:

  • Conditional breakpoints
  • Data breakpoints on variable modification
  • Debugging specific tests in pytest 
  • Viewing call stacks, threads, and console

PyCharm’s visual debugger improves efficiency for large Python projects by making debugging faster and easier.

# django-debug-toolbar

 

django-debug-toolbar is a handy debugger for developers working with Django a popular Python framework. As it offers detailed debugging information as an overlay in browser, it is easier for developers to inspect and optimize the Django web applications.

Key features:

  • Displays SQL queries including execution time
  • Shows request headers, cookies, and parameters
  • Views full environment settings and context variables
  • Profiling time taken by CPU and SQL queries 

The toolbar is configured via a single middleware, providing insights into the application’s runtime behavior. It enables examining the proxied request and response data. For optimizing web apps, django-debug-toolbar is invaluable.

# Werkzeug Debugger

 

Werkzeug is a versatile WSGI (Web server gateway interface) utility library with a built-in browser-based debugger called Werkzeug. debug. Designed for debugging web applications, it provides a straightforward way to inspect the application’s stark traces and variable values. 

Key features:

  • Inspect stack traces and variable values
  • Filter traceback by module to locate errors
  • Interactive console within debugger UI
  • Light-weight and framework-independent

Werkzeug debugger works with any Python framework based on WSGI. Though not as full-featured as django-debug-toolbar, the werkzeug debugger is simple and portable. For debugging specific errors in deployed web apps, it can be useful.

# Python Debugpy

Debugpy implements the Python Debug Adapter Protocol for supporting debuggers like VSCode, PyCharm, etc. It provides a set of hooks to control execution and inspect state.

Some capabilities enabled by debugpy:

  • Remote debugging over network
  • Debugging multi-threaded apps
  • Launching apps for debugging using debugpy
  • Stepping through Django web apps

Debugpy makes it easy to debug Python code remotely over an SSH connection. The debugger frontend can be attached and detached as needed. For debugging remote Python processes, debugpy is very handy.

# PuDB 

PuDB is a full-screen console-based visual debugger for Python. It is intended to provide a better alternative to pdb. PuDB allows debugging code with visual variable inspection and stack traces.

Some of the useful capabilities of PuDB:

  • Syntax highlighted source
  • Global and local variable explorer
  • Multi-line code entry for expressions
  • Post-mortem debugging
  • Program step through
  • Stack and breakpoint management

PuDB makes it easy to analyze code in the terminal visually. With pdb style controls and visual interactions, it can speed up debugging.

# Python Logging Module

While its not a dedicated debugger, Python has its in-built logging module, which is a valuable tool for diagnostic purposes. This module allows developers to log messages, errors and information at various severity levels. This structured approach for diagnostic is important for understanding code behavior & troubleshooting issues. 

The key features are:

  • Flexible logging configuration using .ini or dictConfig()
  • Multiple log targets – files, streams, HTTP, sockets etc
  • Hierarchical loggers with recursion depth control
  • Rich info logging with levels like debug, info, error etc  
  • Thread-safety and module level context

The logging module enables adding print style diagnostics to applications in a structured manner. Verbose logging with timestamps allows reconstructing the application flow. The logs provide insight during testing and debugging phases.

Conclusion

In conclusion, there are various debugging tools available in Python, to leverage these tools you can hire python developers who has variety of tools in their arsenal. In this blog we have covered Python’s built-in pdb module offers a basic but adequate debugging environment. IDEs like PyCharm provide full graphical debugging capabilities. Tools like django-debug-toolbar and PuDB enable debugging visually right in the browser or terminal. For debugging remotely over the network, Python Debugpy can be very useful. The wide range of debugging tools available makes debugging Python applications easier. From plain console debugging using pdb, to visual debuggers like PyCharm and PuDB, there are options suitable for various workflows. With the right tools, bugs can be quickly identified and fixed to build robust Python applications.