The Top Python Libraries for Junior and Senior Developers!

Python is an object-oriented and dynamic language, and it actually used to be so popular the last two years. Python has remained simple, easy, and readable, and due to all these characteristics, it was an excellent programming language for beginners as well as experts. Some of the most significant reasons due to which Python was so overwhelmingly popular are its huge libraries and frameworks offered to offer quick development, easy development, and productive development.

Introduction

Here, in this blog, we will inform you about the most appropriate Python libraries for beginners and for a professional programmer. We will inform you about some libraries on the basis of their purpose, i.e., data science, machine learning, web development, etc. You are a new programmer or a professional programmer, then here in this blog you will get appropriate knowledge about the most appropriate Python libraries.

Data Science and Machine Learning Libraries

NumPy: NumPy is Python's standard library for scientific computing and data science. It is a high-level library of functions and n-dimensional arrays of large size.
Pandas: Pandas is a data manipulation and analysis library. It provides data structures such as Series (labeled 1-dimensional array) and DataFrame (labeled 2-dimensional data structure with potentially mixed types in columns).
scikit-learn: scikit-learn is a popular Python machine learning library. scikit-learn offers an astronomically large number of classification, regression, clustering, etc., algorithms and other utility packages including model selection utilities, data pre-processing utilities, and feature selection utilities.
TensorFlow: TensorFlow is an open-source machine and deep learning library. TensorFlow contains a gigantic collection of APIs and tools that are used in the training and building of machine learning models, such as very popular deep learning libraries like Keras.
Keras: Keras is a high-level library and even a Python library for deep learning. Keras provides a simple interface to build and train deep learning models and even supports backends of deep learning frameworks TensorFlow and Theano.

Web Development Libraries

Flask: Flask is a light-weight web development library for Python. Flask provides some APIs and utilities to build web applications such as routing, templating, and database support.
Django: Django is a high-level web development Python library. Django offers several APIs and features to build web applications like routing support, template support, database support, and authentication support.
Pyramid: Pyramid is dynamic, extensible, and modular library to build Python web applications. Pyramid is constructed using various tools and APIs utilized to build web applications like routing, templates, and databases.
Bottle: Bottle is a small and lightweight extensible Python library for web application development. Bottle relies on various APIs and utilities employed to create web applications, routing, templates, and databases.

Data Visualization Libraries

Matplotlib: Matplotlib is the most popular data visualization library in Python. Matplotlib has very rich APIs and utilities to render high-quality 2D and 3D plots like line plots, scatter plots, bar plots, etc., etc.
Seaborn: Seaborn is a Matplotlib-based visualization library. Seaborn is a high-level plotting API to create beautiful and informative statistical graphics like heatmaps, scatterplots, etc.
Plotly: Plotly is one of the popular Python libraries used for interactive data visualization. Plotly offers a number of APIs and tools to create interactive plots like line plots, scatter plots, bar plots, etc.
Bokeh: Bokeh is a big Python data visualization library to plot interactive plots. It is a set of APIs and tools to plot interactive plots, i.e., line plot, scatter plot, bar plot, etc.

Game Development Libraries

Pygame: Pygame is a widely used library to develop games with the help of Python. Pygame provides different tools and APIs to develop games, i.e., provides graphics, sound, and input.
Pyglet: Pyglet is among the best Python libraries to use when creating games. Pyglet is a cross-platform library for Python containing the complete set of tools and APIs utilized when creating games including graphics, audio, and support for input.
Panda3D: Panda3D is an easy-to-use 3D game development library for Python. Panda3D is a complete 3D game development library with graphics, audio, and input handling APIs and tools.
Cocos2d: Cocos2d is a widely used Python library for 2D game development. It is full of sets of graph, sound, and input handling-based 2D game development APIs and utilities.

Networking Libraries

requests: requests is a widely used Python library to issue HTTP requests. It is highly light-weighted and it is easy to use its API to

issue an HTTP request and communicate with a web server.

urllib3: urllib3 is the most used Python HTTP request library. urllib3 contains an excellent set of functionality and HTTP request functionalities.
paramiko: paramiko is a Python library used to create secure remote connections. paramiko contains a good set of functionalities and remote connection functionalities.
socket: socket is the built-in Python library for network socket operations. socket contains a good set of functionalities and network socket optimizations.

Database Libraries

sqlite3: sqlite3 is the native Python library to work with SQLite databases. sqlite3 has the whole set of functions and database optimization.
psycopg2: psycopg2 is usually employed to work with PostgreSQL databases using Python. psycopg2 has an enormously wide set of flags and options to specify databases.
mysql-connector-python: mysql-connector-python is a sophisticated library with which primitive communication can be achieved between Python and MySQL databases. mysql-connector-python offers some facilities and channels of tailored interaction with databases.
SQLAlchemy: SQLAlchemy is another widely used library with which databases might have been interacted in Python. It also offers a phenomenal level of flexibility and range of features in interacting with databases.

Testing Libraries

unittest: unittest is Python's built-in unit test library. It also provides much in terms of features and flexibility while unit testing.
pytest: pytest is the most widely used unit test library of Python. It provides a ginormous long list of features and options through which the unit test can be customized.
nose: nose is another Python unit testing library and it is very popular. It has so many features and choices by which the unit test can be customized.
Behave: Behave is another popular BDD library for Python. It is one set of many features and functionalities by which the parameterization of tests in BDD can be achieved.

Conclusion

In general, Python boasts an enormous library storehouse of libraries and frameworks to aid in development, simplify, and speed up. New developer or veteran programmer, you've got a library to do it all. Your Python programming is elevated to another level by these libraries on this blog.

Tips

Learn from scratch: You need to have the basics of Python at your fingertips before you learn libraries.
Experiment with different libraries: Just go ahead and try out a collection of some different libraries so you will know clearly what will best fit your projects.
Learn from documentation: Learn step by step and everything about each of your libraries so you are best equipped to learn more about their options as well as features.
Practice, practice, practice: Learning is practice. Practice other libraries and frameworks in order to get better.

Through following the tips above and playing with libraries here in this entry, you will be an enhanced and good Python programmer.