Python

Python is a common programming language. It competes with Perl, Tcl, Scheme, Ruby and Java.

Key Features

• Clean and understandable code structure
• Modular structure and flexibility
• Ability to debug
• Standard and third party libraries

Python has evolved quite a bit in its developer’s ecosystem. Today, it is one of the most powerful languages ​​used when building a wide variety of applications. There are various reasons to use Python, but the main reason to use Python is because it is one of the most flexible, powerful and simplest languages ​​available on the market, and also has large code libraries and frameworks.

Where you can use Python?

1. Web Development

Python’s most popular use case is web development. You can use Python to create web applications of many difficulties. It includes some pretty good web frameworks like Django, Pyramid, and Flask. These frameworks provide the necessary features to illuminate the tasks related to content management, backend database access, management of network protocols such as HTTP, SMTP, XML-RPC, FTP, POP. Some of the most popular Python web apps: YouTube, Instagram, Google, Spotify, Dropbox…

2. Artificial Intelligence and Machine Learning

Python is a popular programming language for artificial intelligence and machine learning. These areas involve the collection, analysis and processing of large amounts of data every day. Most people who specialize in these areas look for a language that is easy to learn and understand, as any complex programming language will increase the learning curve and therefore delay project development. For this reason, they generally prefer Python. Python syntax is similar to everyday English, so artificial intelligence and machine learning scientists can easily work with complex systems. Also, Python’s flexibility, great community support, and platform-independent operation (it can run on any platform such as Windows, Linux, macOS, Unix) make it an excellent choice for AI and machine learning projects.

3. Data Analysis

It is said that people perceive better by looking at visual data. Data scientists collect large volumes of unstructured data to analyze and synthesize structured visual content. This helps companies gain actionable insights into their own business. Visualizing their data is easy for data scientists with Python. It includes powerful libraries for visualization such as Python, Seaborn, and Matplotlib. It also includes Panda, the most powerful and popular library for Python data manipulation and analysis. Panda’s source code is highly optimized and provides precise results even when the data scientist is performing data manipulation and analysis.

4. Game Development

With Python, you can create adventure, arcade, and puzzle games. You can also develop classic games such as table tennis, three stone games -Tic-Tac-Toe, hangman. Pygame is the most popular Python library for game development. Pygame includes several modules with several functions for playing sound, drawing graphics, handling mouse input. It is an open source library for creating games in Python for free. It is highly portable and can run on any operating system. It contains a wide variety of modules that you can use to add interactive features or functions to your existing application.

5. Robotics Applications

According to the report of Global Market Insights, “The size of the industrial robotics market worldwide is set to exceed $80 billion by 2024.”. And, artificial intelligence contributed much to the development of robotics. Artificial intelligence is a field of robotics used to control robots. We previously covered why Python is the most popular programming language in the field of artificial intelligence. Now, let’s understand why Python is the most suitable language for robotics. First of all, robotic operating systems are compatible with Python. Python includes many computational libraries required for robotics. It is also an easy language that non-programmers (with extensive knowledge in robotics technologies) can learn and understand and use effectively when building robotic applications.