Python Error Types

Python Error Types

Python is a familiar programming language for programmers. It will be quite complicated when a programmer encounters an error while working with Python. This tutorial will list error types in python and suggest solutions to deal with them.

Python programming language

Python is a programming language widely used in web applications, software development, and data science. Developers use Python because it’s efficient, easy to learn, and can run on a variety of platforms.

 In addition, Python can integrate well with all kinds of systems and speed up development. Python is user-friendly and gets along well with other programming languages ​​as it is an object-oriented language with a wide range of applications.

Not only famous for web programming, Python is also a widely used language in programming robots and embedded systems.

Error types in Python

A built-in exception in Python is the incident that occurs during running the program, which leads to the common course of commands being suspended. When the code runs into a circumstance, it might not solve, this will raise the exception. The object of Python, which represents the error, is known as an exception.

Here are types of errors in python and suggests solutions to fix them.

The exception of ArithmeticError class takes like the base class with these exceptions thrown because of different errors (ZeroDivisionError, and OverflowError). In brief, it is displayed when the error happens with numeric calculations. 
ZeroDivisionError: division by zero

It might be considered that dividing five by 0 leads to ZeroDivisionError. This is a child of a class of ArithmeticError.
This type of exception is thrown when the assert statement fails. Let’s go with this example below to know more about it. 
def length(List):
assert len(List)!=0, "There are no elements in the array"
return len(List)

list_len= length(obj_Array)
This type of exception will appear when the attribute reference fails. Take a look at the example and output below. 
firstname = "Tiff"
lastname = "Doan"

fullname = firstname.append(lastname)
This exception is thrown when the input() function meets the EOF (end of file) condition. In addition to that, it does not read the data. 
Here is the typical example and output that you should follow. 
str_1= input()

print("Press ctrl+D. This will raise an EOFError")
str_2= input()
This exception is displayed when the number owns big decimal digits. Let’s see the example below for further details. 
import numpy as np with np.errstate(invalid='raise'): np.sqrt(-1)
This exception is thrown when the generator is closed. Let’s have a look at the example below. 
The ImportError exception is thrown when your program can not load the module that a client imports.
import CodingNinjas
This type of exception will be displayed when you make a wrong indentation. Let’s check this example and output. 
This exception is popularly thrown when you attempt to use the invalid index. The index is out of the range of the list.
This type of exception is thrown when the key is unavailable in the dictionary.
The exception is thrown when you press the “Ctrl + C” or “Delete” key. 
The exception appears when errors are thrown might not be found. Let’s see the example below. 
In reality, this type of exception appears with double exceptions (IndexError, and KeyError). 
The MemoryError exception is thrown when the memory cannot run in the program. 
This exception will be displayed when the variable is not available. 
This type of exception will happen when the abstract method does not have enough of the requested derived class. 
The exception is thrown when the system involved in the operation leads to an error. Here is an example of this exception. 
An exception like OverFlowError will appear when the output of the numeric calculation is huge.
The exception can be hit when the iterator attempts to use the element which does not exist.
This type of exception is thrown when the parser comes across a syntax error. 
The TabError appears when the indentation includes the spaces or tabs. Let’s check the example below. 
This TypeError exception will be shown when various double types are mixed. Let’s have a look at the example below.
This exception is thrown when a value is wrong and defined as the data type. 
The exception of ZeroDivisionError is thrown when the second operator is 0. Let’s check this example below. 
This type of exception occurs when Jason’s data misses or gets a key which can not get a value.
The exception of UnicodeDecodeError is thrown when an issue of Unicode decoding executes.
The UnicodeEncodeError happens when encoding the Unicode string in a particular coding.

Python error tutorials


When trying to access methods or properties of a string object with no properties to be read, the system will tell you “AttributeError: ‘str’ object has no attribute ‘read’”. In addition, in case you confuse the two load() methods that are used for each object in the json library, it also causes this error.


The “ModuleNotFoundError: No module named ‘tensorflow’” error in Python indicates that Python cannot find the tensorflow module imported in your code or some package that your code imports.While Python runs the code, it will check check all packages or modules in your code and their dependencies Install pip to use it in your code as you want.

SciPy is a library built on top of the NumPy extension. When you use Scipy features without installing it, the system will notify you “ModuleNotFoundError: No module named ‘scipy’.” Checking the python version again will help you find the right Scipy package. In addition, if you name the variable with the same name as the Scipy package, it will also cause an error.

In python, request is considered an HTTP library, thanks to which users can conveniently send requests without having to manually set query strings via URL as before. However the request is not pre-installed. Therefore, when there is an error ModuleNotFoundError: no module named ‘requests’, it means that in your environment the request is not installed, you need to install it before using it.





In Python 3, print() is treated as a function that needs to be declared. Thus, if in the program you forget to declare it, the system will go to the error “SyntaxError: Missing parentheses in call to ‘print'”. Using ‘print()’ as a function when parentheses must be accompanied by invocation is the simplest way to get around this error.


The error “TypeError: string item 0: expected str instance, int found ” occurs when you try to concatenate some numbers of type int into a new string. In Python you can completely use the join() method to join all the strings in a list to a new string with commas separate. 

The TypeError: int() argument must be a string, a bytes-like object or a number, not ‘list’ error occurs when you intentionally pass the wrong type of the object’s value into the command’s syntax. To solve this error, you can completely use the join() function to convert the whole list to string and concatenate them together.

When you try to use a dictionary as a key in a dictionary, this will throw an error “TypeError: unhashable type: ‘dict’”. Only integer, string, float, boolean, unicode, tuple objects in python are hashable. Since the dictionary contains keys and values, it is not in hashable objects and cannot be used as keys.

The process you unpack the values has no return value or you fix to a nullable object for each variable in a function, this is not valid in python and it will return the error “Cannot Unpack Non-iterable NoneType Object”. To assign the “numeric” value of each variable to a separate variable you can pack the values for a variable.

A hash value is a key for a dictionary or an element of a set. Unhashable’ is a feature in Python used to determine if an object has a hash value. To add a key to the dictionary, you must specify a valid key, however only hash objects can be keys in the dictionary. So if the correct object is not specified, the error TypeError: unhashable type: ‘dict’ will occur.

The error “TypeError: list indices must be integers or slices, not str” occurs when using a string to index the list instead of the index or slice. Simply put, when you operate on an unsupported or incorrect object or object type, and in this situation you have passed the object as a string instead of an integer, there is an error.

In Python, the error TypeError: ‘<‘ not supported between instances of ‘str’ and ‘int’ occurs when comparing objects that are not of the same metric type using mathematical operators. For example, comparing strings to integers. Use the int() function to be able to convert numeric types. This allows the data to be encoded and converted.

Change the method name fullname (obj) to getFullName (obj) to resolve the error “TypeError: ‘nonetype’ object is not callable”. The error occurs when you name the function the same as the name of the property, Python will access the property first.As a result, you call the property as a function.

Lists are indexed using integers, called integers. If you try to slice a list using a non-integer value, the “Slice indices must be integers or None or have an__index__method” error will occur. Making sure you’re using integers while referring to slicing indices will help with the problem. In this tutorial we will talk more about the solution for converting objects to int.


In Python, when you convert a string to an integer using int (value) , you need to make sure the value is a valid string that can be converted. Suppose in the situation that if you pass in an invalid value for example 2.5, the system will return the error “ValueError: invalid literal for int() with base 10”


The .keys() function is a good solution to handle the error “RuntimeError: dictionary changed size during iteration”. The error occurs because you made a modification during the iteration, which caused the size of the dictionary to change. Using .keys(), we will create a list of keywords in the dictionary and after returning the result will be a new list unaffected.


The error message “JSONDecodeError: Expecting value: line 1 column 1 (char 0)” is displayed in some cases like you provided load() and loads() with empty JSON content. You can use a try-catch statement to prevent error messages in case strings and files are empty. Also need to convert json.decoder.JSONDecodeError to requests.exceptions.JSONDecodeError.


In some situations you can use the error parameter to solve the problem “UnicodeDecodeerror: ‘ASCII’ code can’t decode byte“. This error occurs when you try to decode some strings, but the codec “ASCII” ” does not match the codec used for encoding. If the keyword argument is passed to ‘ignore’ to ignore characters with errors and cannot be decoded via the error parameter, the returned result will be valid.


utf-8 encoding is a quick fix when the error “UnicodeEncodeError: ‘ascii’ codec can’t encode character in position” occurs. This is the error message returned when you use the ‘ascii’ codec to encode. characters in a string that contain characters that are not in the ‘ascii’ encoding, for example the character ‘βµ∞’  is not in the ‘ascii’  encoding.


What causes the error “DataFrame constructor not properly called!” because you called the wrong function at some step. To solve the error, you need to know the rules when calling the function like to save a string or numeric element into a DataFrame, you can put it in a list or dict instead.

The error “Series Objects Are Mutable and Cannot be Hashed” occurs when you use String as key to get value from a dictionary. Pandas Series is not hashable and cannot be used for such purposes. To fix it, convert the objects to a hashable object type via the a __hash__() function.

There are many reasons why you might get the “Max retries exceeded with URL” problem. It could be because there are too many open HTTP connections, Not enough RAM on the computer, or also because the request URL is incorrect. Turning off SSL verification is one way to fix this error.

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