Best Tools to Debug Python

With no way of detecting and addressing your code bugs, the debugging step can soon become frustrating. Thankfully, there are many tools out there to help you rigorously debug your python code.

With no way of detecting and addressing your code bugs, the debugging step can soon become frustrating. Python has a few basic functions that can help with debugging (see the print() process below). Still, you might require third-party tools to help you improve your debugging skills.

Here is our list of the best tools to Debug Python:

  1. Sentry EDITOR’S CHOICE A robust bug tracking and performance monitoring tool with excellent options for obtaining granular feedback on problem reports as well as actionable insights that are directly linked to your development environment.
  2. Pycharm One of the best Python debugging tools for the core development process because it is a Python-specific IDE with outstanding debugging facilities.
  3. Rollbar Another approach for bug reporting and error aggregation. Rollbar offers a variety of notification control and tracking options to help you increase your debugging productivity.
  4. Instabug A bug reporting solution with VCS connectors that focuses on mobile user testing and feedback aggregation.
  5. Visual Studio Microsoft offers one of the greatest debugging IDEs on the market, with a professional package that includes many bug diagnosis features.
  6. Raygun This solution contains a suite of mitigation tools for integrated issue diagnosis and treatment, and it was built for crash reporting and bug monitoring.
  7. Glitchtip An open-source bug-reporting option. Glitchtip offers all of the basic features of premium products while remaining completely free and adaptable.
  8. Komodo IDE An open-source IDE with great debugging features and VCS integration that supports numerous languages (including Python).

You’re probably already familiar with the print() function if you’re seeking tools to help you debug Python. If not, this function can help with debugging because it outputs a defined parameter. While many of the solutions on this list use third-party debugging technologies, the print() function may always be relied on to detect flaws during development.

This article covers several distinct tools for debugging Python, including both diagnosing and resolving errors. The functions of the tools differ, but they can be divided into two categories: IDEs and Bug Reporting Tools.

IDEs

Upgrading your IDE is one of the most effective ways to increase your debugging abilities. This is because your coding abilities are influenced by your development environment in a subtle but significant way. While most premium IDEs work similarly, we’ve included a handful on this list that are specifically designed for debugging.

Bug Reporting Tools

While debugging during development is vital, the majority of your faults will be discovered during testing and post-deployment. Furthermore, throughout their hands-on time with your product, your QA team, external testers, and end-users will find flaws.

Bug reporting and aggregation tools are available to help with this since they provide a platform for errors to be registered and your bug-handling developers to be notified. To make debugging easier, these tools interface directly with your development environment or workflow systems. On our list, we’ve included a few of these tools for you to check out.

Open Source

A number of the solutions in this article are open source. While open source presents a variety of benefits across the board, debugging it is particularly useful. This is because of technical issues that might arise as a result of incompatibility with newer or differing systems.

Browser updates, new industry standards, and other such issues might cause problems when debugging with 3rd party solutions since you are reliant on those solutions to update their parameters. Open source can circumvent many of those issues by putting the onus on updating those parameters on the public user base.

The Best Tools to Debug Python

Our methodology for selecting Python debug tools

We reviewed the market for debugging systems for Python code and assessed the options based on the following criteria:

  • Code checkers that are built into development editors
  • A code verification system that enables debug messaging to write status codes
  • A system to collect debug messages
  • Integration with issue trackers
  • Automated testing systems that integrate into the CI/CD pipeline
  • A free trial or a demo to enable a pre-purchase assessment
  • Value for money from a debugger that can be used for other languages as well as Python and so provide full development verification for one price

1. Sentry

Sentry

Sentry is an error-tracking and performance-monitoring tool that can diagnose and resolve python problems. A stack trace feature simulates your development environment, allowing you to break down reported problems and gain a better understanding of where bugs occur in the code.

The service compiles your issues into a searchable list and allows you to identify areas of your code to make it easier to reproduce errors. The performance monitoring tools can help you diagnose problems by allowing you to quickly spot unusual readouts in your development projects.

Key Features:

  • Error detection
  • Performance monitoring
  • Stack tracing for error insights
  • Event log reader
  • Free with limited capacity

Sentry’s basic functions are completely free to use, however it has a limited user capacity. Upgrade to the Team package for $26/month, which increases the error detection algorithms, or the Business package for $80/month, which expands on the error insights even more.

Pros:

  • Dedicated to monitoring various languages, good for companies that already have other app monitoring tools they’re happy with
  • 100+ alerts and templates customized around server health monitoring
  • Supports root cause analysis for faster resolution times
  • Includes workflows for better root cause analysis

Cons:

  • Better suited for smaller teams

A free trial is offered for both the Team and Business editions. If you need to secure a large-scale business and require features such as total platform error monitoring and cross-project insights, you can contact Sentry directly for Enterprise-scale services.

EDITOR'S CHOICE

Sentry is our top pick for a tool to debug Python because it is an ideal system for DevOps environments and also for support teams that buy in Python-coded applications from third-party suppliers. This is because this tool can be used on code that is under development and also on applications that are live. Most Python code is deployed in Web applications and particularly in procedures inserted into Web pages and microservices. You can use this system as a code profiler. The system also reports if it detects problems with underlying infrastructure that seem to be caused by the activity of the Python code. The tool can be integrated into bug trackers to let your development team know what needs to be fixed, or your technicians can send an error report to suppliers of faulty applications.

OS: Cloud based

2. Pycharm

Pycharm

Pycharm is a python-focused IDE featuring some of the greatest python debugging tools available. Furthermore, the intelligent help capabilities give intelligent auto-completion and error checking, resulting in a significant reduction in problems. Aside from debugging tools, the solution includes a number of other tools that are beneficial to overall development.

Key Features:

  • Python focussed IDE
  • Smart assistance features
  • Web development frameworks
  • VCS integration
  • Graphical debugger

Because the product is built on open-source principles, it provides a lot of support and flexibility. In addition to Python, premium versions support JavaScript, HTML/CSS, and SQL, greatly expanding the tool’s applicability to a wider range of tasks.

Pros:

  • FeaturesPython focused debugging tools
  • Supports auto-completion
  • Built on an open-source platform
  • Is highly flexible and can support other languages

Cons:

  • Lacks AI capabilities

Pycharm is available in two versions: a free Community version and a paid Professional version with more capabilities. There is a free trial available for the Professional edition, which offers greater support for both scientific and web python development.

3. Rollbar

Rollbar

Another error reporting and fault aggregation solution, Rollbar, is based on real-time issue identification. The solution includes a set of notifications for quick and accurate bug reporting, but it also groups bug notifications intelligently for easier reading.

Key Features:

  • Bug reporting and aggregation
  • Real-time bug notifications
  • Error management
  • Workflow integration
  • Free with limited capacity

Automated issue tracking and workflow triggers help you avoid accidentally shipping projects with known but untreated bugs. Furthermore, telemetry data obtained through the various connectors offered allows you to track where bugs appear, allowing you to expedite bug repair.

Pros:

  • Supports real-time bug discovery and analysis
  • Supports various integrations for practically any workflow
  • Free for up to 25,000 error events

Cons:

  • Better suited for larger environments

Rollbar is free for up to 25,000 error events and has enough essential features to get you started, especially if you’re working with a small development team. The Essentials plan, which costs $21 per month and covers up to 50,000 mistake incidents, is included in the premium plans. The Advanced plan allows for up to 100k error occurrences and a multi-project feed, which is ideal for CI/CD workflows.

4. Instabug

Instabug

Instabug is a bug-reporting application designed specifically for mobile testing. The system relies on human testers to find defects in a product, but it also provides a way to collect and handle bug-related feedback. Because it only serves as a feedback device, the product isn’t created expressly for Python or any other language.

Key Features:

  • Mobile bug reporting
  • Log data
  • Performance monitoring
  • A large number of integrations
  • Automatic notifications

Bug reports can be compared to log data to have a better understanding of the issues that have been reported. In addition, the solution features a large number of integrations, such as Github, Slack, and Trello, that help to streamline the development process.

Pros:

  • Excellent user interface
  • Offers a variety of communication options for teams and workflows
  • Offers automatic notifications and performance monitoring

Cons:

  • Designed primarily for mobile testing
  • Would like to see a longer trial

A 14-day free trial of Instabug is available. The Basic product bundle, which costs $149 per month, is designed for small organizations. The Pro version, which costs $249 a month, provides more diagnosis features and integration options.

The Premium solution is designed for large enterprises and significantly enhances diagnosis choices, including on-premises hosting. However, you must contact the company directly for a customized price quote.

5. Visual Studio

Visual Studio

Microsoft Visual Studio is an IDE with one of the most comprehensive debugging toolkits available. You can, for example, use the breakpoint to isolate certain lines of code that may be creating problems, and then utilize the built-in visual debugging tools to identify and resolve issues.

You can also use the debugging tool in step sequences to figure out which line of code is creating issues. In terms of fault fixing, Visual Studio’s arsenal of debugging features means it can compete with any other IDE. Furthermore, because Visual Studio supports a wide range of languages, the usability extends beyond just Python.

Key Features:

  • Professional IDE
  • Expanded debugging features
  • Visual debugger
  • Lots of available integrations
  • Multi-language

Visual Studio is available in a variety of forms, including the Community version, which is a free, open-source version targeted for individual small-scale developers.

Pros:

  • Supports Python and other languages
  • Is one of the most popular IDEs on the market
  • Features a visual debugger

Cons:

  • Not ideal for those looking to leave Visual Studio for alternatives

If you work in a group, you might want to look into the Business options, which are available as part of a $45 monthly subscription. For $250 per month, enterprise services are available for large-scale commercial needs.

6. Raygun

Raygun

Raygun aggregates user data to enable accurate crash reporting and bug feedback. In addition, the solution includes issue-tracking tools and debugging mitigation measures. These features, combined with the user data monitoring, make this solution ideal for debugging an existing operational service.

The solution additionally splits its major functions among three different items. This means you can opt into the services you need without paying more, but it also means that if you require a fully-featured solution, you may end up paying more than other solutions.

Key Features:

  • Bug feedback
  • Crash reporting
  • Diagnostics and mitigation tools
  • User monitoring platform
  • Modular pricing model

The solution is divided into three main services, each of which can be tried for free on the website. Your monitoring needs will benefit from the Application Performance Monitoring and Real User Monitoring packages, which start at $8 per month.

Pros:

  • Simple visual debugger
  • Offers crash reporting and bug feedback
  • Supports user monitoring

Cons:

  • Better suited for real user monitoring use cases

The right Javascript debugging tools can be found in the Error Monitoring & Crash Reporting application, which costs $4 per month. Similarly, the price for each product is scalable based on the required capacity, with 10,000-unit increments being the typical.

7. Glitchtip

Glitchtip

Glitchtip is an open-source bug reporting application that collects and organizes problem reports into a legible, fixable format. It outperforms other alternatives because it is open-source, which means it has a larger community of users than some other products.

Key Features:

  • Open-source
  • Error reporting and aggregation
  • Performance monitoring
  • Sentry integration
  • Hosted or self-hosted options

The solution appears to have been developed in response to Sentry’s decision to abandon open-source, but it still works with Sentry’s open SDK. You can host the solution locally because it is open-source, but the company also provides hosting choices. Glitchtip is still in its infancy, but it could be the ideal answer for tiny enterprises or low-budget projects that require open-source.

Pros:

  • Completely open-source project
  • Offers both hosted and self-hosted options
  • Is extremely lightweight

Cons:

  • The interface could use improvement

When self-hosted, Glitchtip is open-source and fully free. You can also use their hosted platform for up to 1000 events, which is also free.

They offer services for small, medium, and large businesses in addition to the free hosted alternative. The Small package is $15 per month and supports up to 100k events. The Medium package costs $50 per month and supports up to 500k events. Finally, the Large package costs $250 per month and supports up to 3 million events.

8. Komodo IDE

Komodo IDE

Komodo is another IDE, but this one supports a wide range of languages, including Python. Komodo is open-source, and the product’s base version is also available for free. The visual debugger and code inspection capabilities in the IDE excel at debugging, improving error identification, and preventing problems.

Key Features:

  • Open-source IDE
  • Inbuilt VCS integration
  • Visual debugger
  • Workflow management
  • Multi-language (including Python)

You can avoid defective builds from being distributed thanks to built-in support for VCS like Git and workflow management solutions. The true allure of Komodo is its open-source nature, which means it has a lot of support and extension options. This solution will provide numerous features to boost your debugging capabilities if you require a new IDE for Python development.

Pros:

  • Includes Python tools as well as support for multiple languages
  • Open source-based tool
  • Supports visual debugging

Cons:

  • Not ideal for those looking to avoid open source solutions

The product may be downloaded and installed from the company’s website, but to use it, even the free version, you’ll need an ActiveState account. Regrettably, it appears like ActiveState is gradually phasing out the IDE in favor of incorporating it into the ActiveState platform.

The IDE still has a following, and because it’s free and open-source, it’s worth considering if you’re on a budget and need a solution. However, keep in mind that, while the product is still supported, it appears to be fading in popularity in comparison to more modern alternatives.

Python debugging FAQs

What is Python debugging?

Debugging involves detecting coding errors in Python script. There are a number of ways to implement debugging and the first of these is manual. You can simply insert print statements and write out lines to a file that include status output at each stage of the script. Automated tools effectively perform the same task, either by inserting lines into the code or by tracking the execution of the code, noting each line number as it runs, and then recording the outcome of that line’s execution.

Is it possible to debug Python?

Python has a library of functions that enable debugging. This is called the python debugger, or pbd. This is a structure that creates a class and provides functions and storage variables. The pbd system will provide output that can facilitate error correction by identifying the line in the code that needs attention.

Is Python difficult to debug?

Python is not particularly difficult to debug. In fact, as it is a script rather than a compiled program, it is easy to watch code execute line by line in a code profiler. For Web-based applications, developers can use the debugging features that are included for free in the major Web browsers to watch each line of code execute because those systems will pause the code after each line runs. Other strategies for Python debugging include writing debug messages into the code or using a code profiling debugging tool.