7 Common Mistakes of Python Programmers

Before moving on to discussing why exception handling is so important and looking at Python’s built-in exceptions, or 7 Common Mistakes of Python Programmers. It’s important to understand that there is a fine line between the concepts of error and exception.

The error cannot be handled, and Python exceptions are handled during program execution. The error may be syntactical, but there are many types of exceptions that occur during execution and do not stop the program immediately. An error can indicate critical problems that the application should not intercept, and exceptions – states that are worth trying to intercept. Errors are a type of unverifiable and irrecoverable errors, such as OutOfMemoryError, which you should not try to handle.

Exception handling makes the code more fault-tolerant and helps prevent potential problems that could lead to a premature stop of execution. Imagine code that is ready for deployment but still crashes due to an exception. The client will not accept this, so it’s worthwhile to process specific exceptions in advance to avoid confusion.

In case, you have some errors that you can’t handle by yourself, find a Python assignment help service like AssignmentCore whose experts are committed to do Python coding projects with excellence.

Errors can be of different types:

  • Syntactic;
  • Not enough memory;
  • Recursion errors;
  • Exceptions,

We will analyze them in turn.

Syntax Errors 

Syntax errors are often referred to as parsing errors. They occur when the interpreter detects a syntax problem in the code.

Out of Memory (OutofMemoryError)

Memory errors are most often associated with the computer’s main memory and are related to a data structure called the “heap” (heap). If there are large objects (or) links to similar ones, then OutofMemory error will most likely occur. It may appear for several reasons:

  • Using the 32-bit Python architecture (the maximum amount of allocated memory is low, between 2 and 4 GB);
  • Large file upload;
  • Launching a machine learning / deep learning model and much more.

You can handle a memory error using exception handling — a backup exception. It is used when the interpreter runs out of memory and should immediately stop the current execution. In rare cases, Python raises an OutofMemoryError, allowing the script to somehow intercept itself, stop a memory error, and recover.

But since Python uses the C memory architecture (the malloc () function), it is not a fact that all processes will be restored – in some cases, a MemoryError will cause it to stop. Therefore, handling such errors is not recommended, and this is not considered good practice.

Recursion Error (RecursionError)

This error is associated with the stack and occurs when calling functions. As the name suggests, a recursion error occurs when many methods are executed inside each other (one of which is with infinite recursion), but this is limited by the size of the stack.

All local variables and methods are placed on the stack. For each method call, a stack frame (frame) is created, inside of which the variable data or the result of the method call is placed. When the method completes, its element is deleted.

To reproduce this error, we define a recursion function that will be recursive – call itself in an infinite loop. As a result, a StackOverflow error or a recursion error will appear, because the stack frame will be filled with method data from each call, but they will not be freed.

Standard Errors (StandardError)

Consider some basic programming errors.

Arithmetic Errors (ArithmeticError)

  • Error division by zero (Zero Division);
  • Overflow error (OverFlow);
  • Floating Point Error;

All of the above exceptions belong to the Arithmetic class and are thrown when errors occur in arithmetic operations.

Division by zero (ZeroDivisionError)

When the divisor (the second argument of the division operation) or the denominator is equal to zero, then the result is a division error by zero.

Error “NotImplementedError”

A runtime error serves as the base class for a NotImplemented error. The abstract methods of a user-defined class raise this exception when derived methods overwrite the original.

Type error (TypeError)

A type error is caused when trying to combine two incompatible operands or objects.

In the example below, they try to add an integer to the string, which leads to a type error.

Value Error (ValueError)

A value error is raised when an inline operation or function receives an argument with a valid type but an invalid value.

The built-in float operation will receive an argument representing a sequence of characters (value), which is an invalid value for the type: floating-point number.

Exception handling helps to interrupt a typical program flow using a special mechanism that makes the code more fault-tolerant.

Exception handling is one of the main factors that make your code ready for deployment. This is a simple concept, built on just 4 blocks: try “looks” for exceptions, and except “handles” them.

It is very important to practice using them to make your code more fault-tolerant.

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Programming is the best field overall though it is somehow difficult but very interesting. As you have several programming courses and one of the best programming is Python. So, I hope you will avoid the 7 common mistakes of python programmers do.

Moreover, if you have any question regarding to common mistakes of python programmers. Then, leave a comment in the comment section.

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