Common Python Programming Mistakes

10 Common Python Programming Mistakes
10 Common Python Programming Mistakes

In addition to being a general purpose programming language, Python also has easy to understand and use syntax rules. The syntax of Python enables programmers to build custom software applications without writing lengthy and complex code. The developers can even use specific Python libraries and frameworks to accelerate development custom software applications according to varying business requirements. Many beginners find it easier to learn Python as first programming language, whereas other switch from other programming languages to Python.

But Python programmers often commit a number of programming and coding errors that affect the software application’s performance and user experience. They also have to put extra time and effort to fix the Python programming mistakes during testing. The programmers can easily make the software deliver richer user experience by avoiding common Python programming mistakes. However, they must remember that the common programming and coding mistakes vary from Python 2.x to Python 3.x.

Common Python Programming Mistakes

1) Ignoring Python Scoping Rules

Python, unlike other programming languages, uses scoping variables based on local, enclosing, global, and built-ins (LEGB) approach. Local refers to the local variables/identifiers specified within a function, whereas enclosed stands for enclosing function locals and global refers to global entities. At the same time, built-ins refer to built-in names like input and print. While writing Python code, the programmers often ignore the significance of ordering namespaces based on LEGB approach. They can easily improve the code quality by following Python scoping rules.

2) Defining Get/Set Functions in Java Style

It is common for Java programmers to access members of a class using get and set functions. But Python does not require programmers to use get/set functions for accessing class members. A Python programmer even has to write additional code to use get/set functions. Instead of using get/set functions, a programmer must access and manipulate class members directly. Otherwise, he can achieve the get/set functions in Python code by using property decorators.

3) Using Tabs and Spaces Interchangeably

While writing Python code, programmers need to use tab for indentation and spaces for alignment. But Python coding best practices emphasize on using spaces instead of tabs. Often programmers use tabs and spaces interchangeably. PEP 8 recommends Python programmers to use four spaces instead of a single tab for indentation. The developers can easily enhance the quality of Python code by replacing tabs with spaces. They can even avoid the Python programming mistakes by changing the default text editor setting to insert four spaces instead of a tab.

4) Not Taking Advantage of Exception Blocks

Python makes it easier for programmers to handle errors and catch exceptions using exception blocks. The programmers can even create exception blocks by using try and except keywords. But many Python programmers do not take advantage of exceptions blocks. Many programmers even do not use exception blocks appropriately. But they can easily identify various coding mistakes through error messages by embedding code within try-except blocks.

5) Specifying Wrong Parameters for Exception Blocks

In addition to ignoring significance of exception blocks, many Python programmers even do not specify parameters for exception blocks accurately. It is always important for the programmer to define exception blocks according to syntax of Python 2.x or Python 3.x. At the same time, they must specify the parameters accurately to make the statement catch multiple exceptions.

6) Not Performing Type Checking Accurately

While writing Python code, a programmer can compare data types in a number of ways. It is a common practice among programmers to compare data types by calling <type()> in the code. But option leads to weak data-typing. The developers can easily implement strong data-typing by using <isinstance> instead of calling <type()> in the code. In addition to comparing data types more effectively, the <isinstance> method can even identify a derived class object.

7) Not Distinguishing Custom Modules for Standard Library Modules

While writing a software application in Python, programmers have option to choose from a wide range of standard library modules according to their precise needs. At the same time, they can also write custom modules to meet specific business requirements. But programmers often name custom modules after the standard Python modules. The name clashing leads to a number of Python coding mistakes. The programmers must differentiate the names of custom modules from standard Python modules to execute the code smoothly.

8) Making the __init__ Method Return a Value Explicitly

Python used _init_ method as a constructor. The method is used by default to set values of instance members of a class object. Each time Python allocates memory to a new class object, the _init_ method is invoked automatically. But programmers sometimes make the _init_ method return a value explicitly. When the _init_ method returns a value explicitly its original purpose and usage alters. Hence, developers must not make the _init_ method returns a value explicitly.

9) Importing Modules Recursively

Python treats import clause as an executable statement. A programmer can use import clause to execute specific modules. But once the module is executed, the class and functions in the module will also be executed while executing the related code. If the programmers call one module inside another module recursively, the performance of the application will be affected due to circular dependency. The developers can easily rectify the Python programming mistake by eliminating recursive imports.

10) Forgetting Syntactical Differences between Python 2.x and Python 3.x

A programmer has option to choose from two current editions of Python – version 2.x and version 3.x. Python 3 is the futuristic version of the programming language. But many programmers still write code in Python 2.x. The two versions of Python are incompatible with each other. Also, they differ from each others in the category of syntax. Often programmers find it difficult to understand the differences between syntax of Python 2.x and Python 3.x. Hence, they commit a number of Python coding mistakes which could be avoided easily.

On the whole, the Python programmers must identify and avoid a number of programming mistakes to build outstanding software applications. They can easily avoid these common programming and coding mistakes by implementing commonly used Python programming best practices. Also, they can review the code consistently to identify and rectify the coding mistakes before testing process commences. Also, Python programmers should understand the advantages and disadvantages of Python to improve the quality of coding

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