Yes, in Python, you can explicitly define the datatype of function parameters and return values using type hints or type annotations. Even if you specify the data types using type hints, Python will still run the code even when the wrong types are passed. The execution of the program will not be interrupted, and an error will not be raised.To find these type-related mistakes, you can use tools like mypy or pyright that check your code before it runs. Using Type Hints in Python Functions To add type hints to a parameter of a function, you need to specify the ... Read More

Any object, such as a dictionary, can be the return value of a Python function. To do so, create the dictionary object in the function body, assign it to any variable, and return the dictionary to the function's caller. Data values are stored as key-value pairs in dictionaries. A Python dictionary is a collection that is ordered, changeable, and forbids duplicates. In this article, we will discuss various methods to return a dictionary from a Python function. Using Dictionary Comprehension One line of Python code can create and initialize dictionaries using the simple and memory-efficient way known as Dictionary Comprehension. ... Read More

Camel case and snake case are ways of writing words together when we are programming. In camel case, we write words together without spaces and we start each new word with a capital letter except for the first word. For example, if we want to write a variable name for someone's date of birth, we can write it like this: dateOfBirth. In snake case, we write words together with an underscore symbol between them, and all the letters are lowercase. For example, if we want to write a variable name for someone's home address, we can write it like this: ... Read More

In Python, documenting your functions is an important step that helps others understand what your code does, what inputs it expects, and what it returns. Python provides a built-in way to write documentation using docstrings. By producing good documentation, you can make your code more readable and usable in larger projects or by external users. Using Docstrings A docstring is a string that appears just after the definition of a function. It describes what the function does, its parameters, and its return value. You write it using triple quotes (""" or '''). Syntax Following is the syntax for writing a ... Read More

In this article, we will discuss how to delete multiple lines that are repeated in a Python Function. If the file containing the program is small and only has a few lines, we can remove repeated lines manually. However, when dealing with huge files, we need a Python program to do so. Using the File Handling Methods Python has built-in methods for creating, opening, and closing files, which makes handling files easier. Using the methods, we can also perform several file actions, such as reading, writing, and appending data (while files are open). To remove duplicate lines from a text ... Read More

In Python, everything is an object. And every object has attributes and methods, or functions. Attributes are described by data variables, for example like name, age, height, etc.Properties  Properties are a special kind of attributes that have getter, setter, and delete methods like __get__, __set__, and __delete__ methods. A property decorator in Python provides getter/setter access to an attribute. You can define getters, setters, and delete methods with the property function. If you just want the read property, there is also a @property decorator you can add above your method. Example This example shows how to use the @property decorator ... Read More

Functions accept arguments that can contain data. The function name is followed by parenthesis that list the arguments. Simply separate each argument with a comma to add as many as you like. As the name implies, mandatory arguments are those that must be given to the function at the time of the function call. Failure to do so will lead to a mistake. Simply put, default function parameters are the exact opposite of required arguments. As we previously saw, while declaring the function, we give the function parameters a default value in the case of default arguments. The function automatically ... Read More

In Python, function names follow specific rules. A valid function name can only contain certain characters, and it must follow the naming conventions defined in the Python language syntax. Using the correct characters ensures that your code runs without syntax errors and stays readable. Allowed Characters in Function Names Python function names can consist of the following characters - Letters (A–Z, a–z) Digits (0–9) — but not at the beginning Underscores (_) — often used to separate words Function names must follow these rules - Must start with a letter or underscore Cannot start with a digit ... Read More

When you write tests in Python, it is important to make sure that your function raises the correct exception for invalid input or unexpected conditions. This helps to confirm that your code handles errors properly. You can test exceptions using the following ways in python − Using the try-except blocks manually Using the unittest module Using the pytest module Using try-except Block One of the basic ways to test for exceptions is by manually using a try-except block. This allows you to execute code and catch any exceptions that occur. If the function doesn't raise the ... Read More

In Python, you may notice that code runs faster when it is placed inside a function rather than running directly in the top-level script (global scope). This is due to how Python manages variable lookups and optimizes execution inside functions. Functions have their own local scope, which is much faster to access compared to the global scope. Also, Python internally applies several optimizations when it detects function boundaries. Reasons for Faster Execution in Functions Here are the main reasons why Python code executes faster inside a function - Local Variable Access: Local variables are stored in a fixed-size array, ... Read More