In the current technological environment, learning programming languages has become a necessary skill, whether for self-improvement or employment needs. As technology continues to develop, various programming languages are also emerging.
Therefore, when choosing a programming language to learn, you need to consider multiple factors, such as the popularity of the language, ease of use, development efficiency, applicable scenarios, etc. In the environment of 2023, the most worth learning programming language is Python.
1. Popularity of Python
Python has been one of the most popular programming languages since its release in 1991. It is a high-level programming language with clear and concise syntax and easy to learn. Python is an interpreted language, so it does not require a compiler to run the program. With the rise of data science and artificial intelligence, Python has become one of the most popular data science and machine learning languages. Python is open source, which means developers can freely use and modify its code, which is one of the reasons why Python is popular.
According to statistics, in 2023, Python will still be one of the most popular programming languages. According to the TIOBE rankings, Python ranked third in April 2023, second only to Java and C language. Meanwhile, in the latest Stack Overflow developer survey, Python was considered one of the most popular programming languages, especially in the fields of data science and machine learning.
2. Ease of use of Python
Python is a high-level programming language with a very clear and easy-to-understand syntax. Compared with other programming languages, Python is easier to get started. Python does not require complex syntax, so you can learn basic programming knowledge in a short time.
In addition, Python has rich libraries and frameworks that help developers build applications quickly. For example, NumPy and Pandas libraries are used for data science, Django and Flask frameworks are used for web development, and PyTorch and TensorFlow frameworks are used for machine learning.
3. Python development efficiency
Python is a high-level programming language, so development efficiency is very high. Compared to other programming languages, Python requires less code to achieve the same functionality.
Python has many built-in libraries and frameworks that help developers build applications quickly. Python has a large number of libraries and frameworks that can meet different development needs. Therefore, Python has great advantages in development efficiency.
4. Applicable Scenarios of Python
Python has a wide range of application scenarios and can be used in various fields and industries, especially in the fields of data science, artificial intelligence and machine learning. The following are the application scenarios of Python in different fields:
- Data Science and Machine Learning: Python is widely used in the field of data science and machine learning. It has many data science libraries and machine learning frameworks, such as NumPy, Pandas, Matplotlib, Scikit-learn, PyTorch and TensorFlow, etc. These libraries and frameworks help data scientists and machine learning engineers perform tasks such as data analysis, modeling, and prediction.
- Web Development: Python also has many applications in the field of web development. Django and Flask are one of the most commonly used Python web frameworks that help developers quickly build web applications.
- Automated testing: Python can be used for automated testing. For example, Selenium WebDriver can use Python for automated browser testing, PyAutoGUI can be used for automated GUI testing, and testing frameworks such as pytest and unittest can help developers write test scripts and test cases.
- Game Development: Python can be used for game development. For example, the Pygame library is a Python library for making 2D games, providing many features such as audio, animation, collision detection, and physics simulation.
- Scientific computing: Python is also widely used in the field of scientific computing. NumPy and SciPy are two major Python scientific computing libraries that can perform various mathematical, statistical and scientific computing tasks.
To sum up, Python is widely used in various fields, especially in the fields of data science, artificial intelligence and machine learning. Therefore, learning Python is very valuable for people who want to pursue a career in these fields.
5. Difficulty of learning Python
Python is a very easy-to-learn programming language, and even people with no programming experience can learn it quickly. Python's syntax is very simple and similar to natural language, making it easier to understand.
In addition, Python has rich documentation and tutorials to help novices get started faster. Python also has a smoother learning curve than other programming languages, meaning newbies can implement their ideas faster.