Debugging is an essential skill for any programmer. Mastering this skill can help you identify problems quickly and effectively in your Python code. Without knowing how to debug code, developers will face endless hours of frustration trying to solve problems.

Fortunately, Python’s built-in tools and debugging techniques make it easy for developers to identify and fix errors without wasting too much time. To help you get the most out of your Python coding experience, this article contains a list of the top debugging techniques for Python developers. But first, you must know the importance of debugging and its practical use cases in the developer community.

The Importance of Debugging

As mentioned, debugging is among the essential Python skills that all developers need to know. A common misconception of debugging is that it’s only necessary for complex projects. In reality, debugging should be part of the development cycle of any project, regardless of its size or complexity.

This process helps you identify and fix bugs in your code quickly and efficiently. It can also help you better understand the program’s flow of execution, which enables you to make more informed decisions about improvements or modifications to the code.

Debugging Use Cases

A common mistake of new developers is to assume that debugging is only done to correct errors in code. In reality, debugging is used for more than just fixing errors. Here are some of the most common use cases:

Handling Python code errors that occur during program execution. Errors can be caused by incorrect syntax, type errors, name errors, etc. Different types of errors can occur in each code, and good debugging skills can get you out of a jam.
Investigating problems with code logic or implementation. This could include issues such as unintended infinite loops or unexpected output from functions. Debugging can help programmers determine the root cause of these issues and identify solutions.
Testing code for desired behavior. Debugging can be used to test if the code is working as intended. This could include checking for outcomes from functions, or ensuring that calculations are performed correctly.
Locating and removing code that is no longer necessary. As a developer, you should know that code can become obsolete over time. Debugging allows you to identify and remove obsolete or redundant code from your project. This could include dead code, duplicate functions, or redundant variables.
Identifying potential performance issues in your program. Poorly written code can significantly slow the running time of a program. Thus, accurately tracking and diagnosing these problems is essential for efficiency. And yes, debugging can help with that.

Common Debugging Techniques For Python Developers

Now that you understand the importance of debugging and its various use cases, here are some of the most helpful techniques for Python developers:

The “print()” Function

The simplest way to debug a program is by using the print() function. This can be used to debug programs by displaying values in real time. But how, you may ask? This function allows you to print out variables and values to gain insight into what is going on with your program. It also helps you identify errors that appear during the execution of your code. Through this function, you can easily track the program’s flow of execution and identify any potential problems along the way.

Integrated Development Environment (IDE)

An IDE provides a suite of tools to help debug code more effectively. With features such as syntax highlighting, auto-completion, debugging consoles, and breakpoints, it allows you to quickly identify and fix errors without having to search through your code manually.

An IDE is present in almost every programming language, and Python is no exception. Popular IDEs include PyCharm and Visual Studio Code as the go-to choices for many developers. If you have the resources, you can try out different IDEs and find the one that works best for you.

Debugger

A debugger is a powerful tool used to step through code line by line. It can be used to inspect variables, set breakpoints, and trace functions as they execute in real-time. This helps you identify the exact source of an issue quickly and easily.

The Python debugger, known as pdb, comes installed with Python. It allows you to inspect the flow of control in your code. You can also set breakpoints with pdb which allows you to pause at specific points during program execution so that you can investigate what is going on at that time.

Logging

Logging can be used to keep track of errors and detect any unexpected behavior during the program’s runtime. This provides you with a record of events that can be used for further investigation into the cause of an issue. Many seasoned developers use logging as a reliable way to track errors and identify improvement points.

The logging module in Python allows you to create basic loggers that can be used for debugging purposes. This module also includes more advanced features such as custom levels, filtering, and formatting, making it even more powerful!

Conclusion

Debugging is one of the most critical aspects of development that every professional developer should learn. You can quickly identify and solve problems in Python code by learning and mastering the debugging techniques listed above. Remember, debugging is an essential part of the development process, so learning how to use these techniques efficiently will help you become a more productive and successful developer!

There’s an interesting trend in the second decade of this millennium. Things once declared “dead,” are experiencing a resurgence. For example, animated GIFs, once relegated to cheesy ads for home refinancing or losing belly fat in a month with acai berries, are back in Slack channels, social media and blogs everywhere. Email newsletters have returned after many corporations abandoned them as sales and marketing tools in 2008 or so. Podcasts were declared to have peaked sometime around 2010. Now, they’re back and there are almost too many to choose from. The consensus about the return of animated GIFs, email newsletters and podcasts is that they’ve improved in quality and offer more to people who use them.

Visual programming environments and platforms were also hot in the 1990s and the early 2000s. Then the noise they generated seemed to die down. And, now they’re back, very likely for good. Let’s look at why.

Too fast, too choppy, too inwardly focused and…it’s complicated

Visual programming has been around for much longer than we think. It started quietly enough in the 1960s with Bert Sutherland’s interactive programming language. The idea built up steam in the 1970s and 1980s (Smalltalk). The idea of moving away from text editing, compiling, writing down the errors, and debugging with the eyes was alluring. And, so it came of age in the 1990s with Visual Basic, Xelfi/Netbeans, Visual Studio and the height of the CASE tools hype.

Ah, the old Smalltalk days. Source: Basic Aspects of Squeak and the Smalltalk-80 Programming Language

So, there you have it. A whole slew of tools that could make programming so easy a child could do it. So, what happened? Why did visual programming virtually go gentle into that good night?

I think it’s because so much was still new in the 1990s and early 2000s. A whole lot of great digital and online stuff came out of that period very quickly. Take the World Wide Web, for example. It was going mainstream, but parts of it were more like the World Wild, Wild West. But I think that, in the rush to show the world the cool stuff the web and digital were bringing us, some steps were missed.

So, the visual programming tools of that period were really more about “look what we can do,” rather than “look at what you can do.” So, the end result of that philosophy is shaky extensibility (if there’s any at all), slow code generation and little to no cross-platform capability. In addition, in-depth programming skills and mindset were still the name of the game.

The only thing that’s constant is that nothing is constant

If there’s one thing I’ve learned since I started writing about programming languages and development trends in 1998, it’s that nothing is constant. When I invested in my first Mac in 1996, I had no idea I would replace it with a laptop just a few years later. And when I upgraded to one with an Intel Core i7 processor, I had no idea that it would end up gathering dust in my home office while I played with my smartphone and tablet in my living room.

In this mobile world, people want apps for almost everything. In addition, there are the other trends that are in the backlogs of today’s developers. These include solutions for cloud, machine learning, data science, artificial intelligence and IoT, as highlighted in “The State of the Developer Nation, Q1 2017,” the report compiled by Developer Economics. So, all of a sudden the already significant amount of knowledge you need to build software and applications in this brave new technological world has skyrocketed.

Most of you are developers, so I don’t need to tell you how difficult it is to be a full-stack unicorn in the age of “we need an AI and predictive analytics app for that on the cloud.” The Developer Economics surveys tell your story: your work can span multiple different areas, requiring mastery of several languages. Nor do I need to go on and on about the pressure to get these apps built and out in the marketplaces or stores ASAP or all the headaches that come with updates (new JavaScript libraries! Dependencies! Merges!). So, I’m going to skip all that and get to my point.

Now more than ever, we need to move away from the slow pace and nightmares of hand coding to something visual that makes development as easy as GUI interfaces make almost any computer task. But we don’t need the visual programming of the 1990s; we need something new and improved. And now we have it: it’s called “low-code.” An easy-to-understand name that Forrester coined in 2014.

Low-code is visual programming of the 1990s on steroids

Although low-code development includes visual programming, I want to be clear that this is not your father’s visual programming. Yes, it’s true that common code elements, workflows and business processes are turned into components so you can drag them around and drop them into a visual IDE. But there’s even more to it than that. Application deployment, updates and generation are automated. You’re doing more than building applications visually using things that have survived the tests of time and software battles.

More specifically, rather than starting a project by hand-coding, some basic routing or writing a set of failing tests, you draw the shape of your application. You define the precise workflow your application needs to address each possible scenario. You draw the UI. You specify the data your application will store and how the database will store it. And, you use your visual IDE to integrate REST APIs with your application or integrate your applications with other systems, such as an SAP ERP.

So, instead of worrying how you’re going find the time to learn the latest faddish JavaScript framework or play with a cutting edge NoSQL data store, you’re delivering something valuable to the world in what seems like no time flat. Even better, you’re not sweating over DevOps or crying in your beer over application monitoring. So, basically, you’ve got something that’s miles ahead of what visual programming used to offer.

What about low-code platforms gives visual programming staying power?

The ability to leave the choppy, inwardly focused, released-too-fast ways of 1990s visual programming is becoming easier all the time. That’s huge. In the Forrester Wave: Low-Code Platforms Q2 2016, they rated the top 14 vendors of low-code development platforms out of a much bigger number. The fact that Google has thrown its hat in the low-code arena is another sign, as is a recent article in InformationWeek about low-code.

Here are the reasons I think low-code has brought visual programming back to stay:

Flexibility: You work in an IDE for visually defining the UIs, workflows and data models of your application but you can still add your own hand-written code (code you already know) where necessary,
Automated database integration. Low-code platforms transparently convert your data models into relational tables and SQL queries. And, data from external APIs is automatically made available from your application. This is not your typical ORM. It includes change management from the database all the way up to the UI.
No more deployment, maintenance and change nightmares. Automated tools build, debug, deploy and maintain the application in test, staging and production—sometimes with just one click.

Basically, everything that anyone ever complained about in forums related to visual programming is gone, and the parts people loved are still here.

And, while low-code platforms do require a little training, I’m not talking months of schooling here. More like a few weeks. Plus, low-code makes it possible to avoid having to know more languages and technology than I can count, all of which are needed to meet the demands of web and mobile application development. What’s not to love about that? You get to take a concept and build it into a working app without going back to school to learn six more things that have popped up in the last few months.

Conclusion: Low-code keeps the heart of visual programming beating

So, Justin Timberlake might have brought sexy back, but low-code has brought the heart of visual programming back. It takes what was good about the early days of visual programming but adds a big advantage. You can jump right in and start describing your solution to a problem. You don’t need to learn a whole bunch of arcane details. Deployment, updates, integration, all are fast and easy, mostly because the majority of those things are done for you automatically.

As a result, when a request comes in for an app that uses fitness and heart rate data to propose a specific exercise program for a heart patient—in 2 weeks—you can get right on it. How cool is that?

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