What are Python Libraries? 15 Types of Python Libraries

What are python libraries

Table of Contents

Created by Guido van Possum in the 1980s, Python is an object-oriented and dynamic High-Level programming Language (HLL) with easy syntax, understandable semantics, and reusable modules and packages across the programs. 

It is the most extensively used language for a wide range of applications by developers due to its modularity feature, which gives the programmer high flexibility, productivity, and a fast edit-test-debug cycle. 

And this modularity is a feature offered by the Python libraries. 

Must be curious to know “what are Python libraries?” 

Let us delve right into answering this question and learn more about the types of Python libraries.

Key Takeaways

  • Learn What Python Libraries Are.
  • Know the Working of Python Library.
  • Understand What Python Standard Library is.
  • Know the Types of Python Libraries.

What are Python Libraries?

It is a digital space where the collection of priorly used codes, their modules and packages are stored for reuse in another program for a pre-defined specific function. 

Important Terms:

  • Module: A file consisting of Python code.
  • Package: It is a directory consisting of sub-packages and modules.

Example of a Python Libraries

The ON button in electronic gadgets. 

If a programmer has already programmed the functionality of the ON button for a TV remote in a way that when a user presses this button once, it turns on the TV. 

Now, he stores this code in the Python library as a module to be reused later if needed.

Suppose the programmer needs to develop the same program for the ON button of a washing machine, AC remote, or gaming console. In that case, he can just recall the same functional code from the Python library using syntax without the need to rewrite the whole algorithm again.

Entities Stored in a Python Libraries Are

  • Modules of codes
  • Program Documents
  • Configuration data
  • Message templates
  • Classes
  • Values

Features of Python Libraries 

  • These are the list of object-oriented class definitions.
  • These coding modules can be reused in and across the programs repeatedly. 
  • It saves time from writing the same code multiple times from scratch.
  • The scope of Python libraries is very narrow, like strings, I/O, and sockets.
  • Their APIs are smaller and least dependent on other programs.

How do Python Libraries work?

Once the developer saves the code with a specific functioning in the OS environment, it gets stored as a DLL extension (Dynamic Load Libraries). The very collection of these codes is called Python Libraries.

Now, while writing a program, if the programmer needs the same function again, he imports this code from the python library by linking this code from the library to the program.

The linker searches and run that code from the library to execute the program accordingly.

What is Python Standard Library?

A Python Standard Library (PSL) is a compilation of pre-defined exact syntax, semantics, and tokens of Python language that are used to launch the core functionalities of the Python program.

It holds more than 200 such modules of Python codes, and most of its codes are written in C language. 

The feature of PSL is that it allows access to a compilation of 1000s of components from the Python Package Index (PyPI).

Let us see some of the most important modules in Python Standard Library as follows:

  • time: Get local time and other time-related functions.
  • sys: Functions and variables related to Python runtime environment.
  • os: For the user and OS interaction.
  • math: Provides C standard-defined mathematical functions.
  • random: To generate random float numbers between 0 and 1.
  • pickle: To serialise and deserialise a Python object structure and pickle them, which can be stored on a disk.
  • urllib.request: To define classes and functions for opening URLs in a complex environment.
  • re: This regular expression (RE) syntax specifies a set of strings to match it.
  • cgi: Common gateway interface, establishes the way data is transferred between the routine scripts and web server.
  • socket: Offers objects and functions with exceptions to building network applications for both client and server ends.

15 Types of Python Libraries

Other than Python Standard libraries, other types of libraries are also imported by programmers to make the program easy and fast. 

Some of them are:

1. TensorFlow: Developed by a collaboration of Google and Brain Team.

  • An open-source library.
  • For high-level and complex maths or physics computations. 
  • Used in Machine Learning and Deep Learning. 
  • It contains a large number of tensor operations.

2. Matplotlib

  • An open-source library.
  • Used in Data Analysis.
  • To plot numerical data and high-definition 2D plotting, like histograms, pie charts, scatterplots, graphs, etc.
  • Plots graphs for various hard-copy formats.

3. Pandas: licensed by Berkeley Software Distribution (BSD)

  • Open source library with HLL code structures.
  • Used in Machine Learning and Data Analysis. 
  • Helps in data manipulation, cleaning, sorting, re-indexing, iteration, concatenation, data visualisations, data aggregation, etc.
  • If using it, then, no need to switch to another language, such as R. 
  • Used in datasets and time series for organised and unorganised data.

4. NumPy: i.e. Numerical Python

  • It has in-built basic mathematical functions, a computing package, n-dimensional array function interfaces, broadcasting functions, etc.
  • Used in Machine Learning and Data Analysis.
  • For handling large complex matrices and multi-dimensional data. 
  • Used by other libraries for tensor operations.
  • Has tools to integrate C, C++, and Fortran codes as well.

5. SciPy: i.e. Scientific Python

  • An open-source library, which is an extension of NumPy.
  • An HLL library with user-friendly and efficient numerical computations. 
  • SciPy stores the numerical data codes, while NumPy sorts and indexes the array data.

6. Scrapy

  • Open source library.
  • Extracts data from websites.
  • Enables fast web crawling and high-level screen scraping in data mining and automated testing.

7. Scikit-learn

  • Open source library
  • Used in Machine Learning along with NumPy and Scipy.
  • Handles complex mathematical algorithms like linear regression, classification, clustering, etc.

8. PyGame

  • Helps in easy interlinking of Standard Directmedia Library (SDL) with graphics, audio and input libraries.
  • For creating high-definition games and audio libraries.

9. PyTorch

  • Largest ML library, rich APIs and GPU acceleration.
  • Used in tensor computations, solving neural network issues in the program.

10. PyBrain: i.e. Python Based Reinforcement Learning

  • Open source library.
  • Used for coding in AI/ML and Neural Networks.
  • Its syntax and semantics are flexible and easy to understand.

11. Requests: licensed by Apache 2

  • It is an HTTP library that gives HTTP requests capabilities
  • Allows the addition of headers and multi-part parameters with simple Python dictionaries.

12. BeautifulSoup

  • A library for XML and HTML parsing.

13. Pyglet: licensed by Berkeley Software Distribution (BSD).

  • Used in object-oriented programming.
  • Offers cross-platform windowing and multimedia functions.
  • For high-level interface in game design.
  • Used widely in applications of Operating Systems like Mac OS X, Windows, and Linux.

14. Pillow: i.e. Python Imaging Library

  • A user-friendly library.
  • Best to work with images.

15. iPython

  • For parallel and distributed applications computing.

Conclusion

Although it was a general overview of Python libraries, I hope you got the gist of them to know which libraries to opt for. 

You must have also got the idea to create modules of codes and store them in the PyPI library if you need any specific function in Python.

Also Read: 15 Best Python Books For Beginners

Frequently Asked Questions (FAQs)

Is Pandas a module or a library in Python?

Pandas is a Python library used in Machine Learning and Data Analysis for data manipulation.

Why the library is important in Python?

As the Python language is widely used in Machine Learning and Data Science, the modules of Python libraries can be recalled as and when needed for their specific functions multiple times with simple syntax.

How many Python libraries are there?

Python contains more than 137000 libraries available for reuse in programs to develop applications.

What are the 4 data types in Python?

There are both standard and built-in data types in Python; they are numeric, sequence, boolean, set, and dictionary.

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