Python Built-in Functions vs Libraries

In this article we want to learn about Python Built-in Functions vs Libraries, so as you know that Python is one of the most popular programming language, and there are two types of resources, we have built-in functions and also libraries.

 

 

Python Built-in Functions

Built-in functions are pre defined functions that are included in Python. they can be used to perform different tasks such as mathematical operations, string manipulation and file handling.

 

These are some examples of built-in functions:

abs() returns the absolute value of a number
len() returns the length of an object
range() generates a sequence of numbers
type() returns the type of an object
print() prints an object to the console

 

 

On the other hand, libraries are pre written code that can be imported into your Python code. they are collections of modules that can be used to perform specific tasks. libraries can be installed using pip package manager or can be included with Python distribution.

 

These are some examples of Python libraries:

NumPy library for numerical computations and array processing
Pandas library for data manipulation and analysis
Matplotlib library for data visualization
Scikit-learn library for machine learning algorithms
Flask library for building web applications

 

 

Now, let’s compare built-in functions and libraries.

 

Python Built-in Functions vs Libraries

  1. Functionality: Builtin functions are designed to perform basic operations and libraries offer specialized functionality. libraries provides different tools and functions that you can use it for particular task. but builtin functions can be used in different types of applications, they may not be sufficient for more complex tasks. on the other hand libraries provides developers with different functions and tools to handle complex tasks.
  2. Usability: Builtin functions are easy to use and require no installation or setup. they are always available in Python environment. but libraries require installation and setup before they can be used.
  3. Efficiency: Builtin functions are optimized for speed and are usually faster than libraries. this is because they are built into the Python interpreter and are executed directly. but libraries may be slower as they are external modules that need to be loaded into the interpreter.

 

 

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