Common Beginner Mistakes in Python


Python is a simple, minimalistic, and easy to comprehend programming language. With its pseudo-code ability, students who enroll in a coding school can easily learn and start coding. This explains why this language is widely used in rapid application development and as a scripting language or glue that connects several pre-existing components and services. Python also supports packages and modules, thus encourages program modularity and reuse of codes.

However, despite novice-friendly, beginner coders can make several mistakes when using Python. Outlined below are some common mistakes of using Python.

Choosing the Right Version

What adds to the confusion that beginners already have when venturing into programming is the availability of two versions of Python. Python has two functional versions that can be downloaded and used. These include version 2.7.x and version 3.6.x.; the 3.6.x version is the latest and best for beginners. However, note that version 3.6.x codes don’t work with 2.7.x codes and vice versa.

Coping from the Internet

This is something that every programmer has done at one point in their coding journey. Beginners may find it easier going to the internet, copying an already written code or lines, and insert them into their routine. While using another person’s mistake isn’t a bad idea, you should know how the code works before using it. Otherwise, you will be running an unknown code blindly on your computer.

Error Handling

Unlike other coding languages, errors in Python are distinct and often called tracebacks. Similarly, you shouldn’t necessarily understand all the possible Python mistakes to code with Python perfectly. For example, error handling or syntax error occurs if you miss a colon at the end of the line, accidentally add an extra space to an “if” statement, or place a parenthesis wrongly. This typically means that the system couldn’t understand your code.

Incorrect Indentation

All blocks of codes in Python are betokened depending on their corresponding volume. However, unlike other programming languages, an indentation in Python goes beyond making the code appear neat. Indentation also helps in symbolizing blocks of codes that the statement belongs to. Several code characteristics depend on indentation.

Just to mention, Python makes use of precise indentations for its codes. Each indent signifies that the following code is part of the previous statement. Avoid using tab key when creating indents. Instead, use four spaces to avoid these errors.  Unfortunately, it is difficult to spot indentation errors in Python, especially by beginners. This might be as simple as tangling tabs and spaces that are no easy to locate.

Low Test Coverage

This is another common problem, especially for beginners who don’t understand the benefits of unit testing. Seasoned programmers understand the dangers of working with untested codes. Improving your test coverage starts right at the beginning of your coding project.

You should create test cases immediately you add a feature or function to your codes to validate its implementation. Fortunately, several libraries are available. You can use Unittest or the popular Pytest. As a beginner, you should spend enough time testing your codes. While it may take some time, it is a long-term investment that will save you a lot of time when debugging.

Misusing Expressions

One of the Python programing language hallmarks is its ability to give default values to arbitrary function arguments. While this is a lifesaver, the problem arises when the default value isn’t the same in the entire code. That said, you shouldn’t use mutable values as default arguments.

Name Clashing in Python’s Standard Library

One of the advantages of coding with Python is the wide array of insightful library modules. However, even if you try to avoid using the library, you can easily name clash one of your modules with another module in the languages’ standard library.

For instance, you can simply name your module in your code “” This name can clash with a standard library module with the same name, leading to gnarly issues. For instance, it becomes impossible to import the version from the public library since you already have one with the same name.

That said, you should be cautious when naming packages to avoid the confusion that comes with using the same names. Similarly, it is easier for you to change the name instead of filing a Python Enhancement Proposal requesting a change in the name of the module in the standard library.

Bottom Line

Python is among the few powerful and flexible coding languages with several paradigms and mechanisms that can improve every coder’s productivity. However, like any other tool or coding language, having a limited understanding of its capabilities impedes enjoying its benefits. That said, beginners should familiarize themselves with some of the common nuances of coding with Python, including, but not limited to, programing problems highlighted above.