Author | Rizel Scarlett
Translator | Bian An Editor | Wang Ziyu
Produced by | csdn (ID: csdnnews)
What programming language can continue to be popular 30 years after its birth?
If you can think of Python, congratulations, that’s right. In the October 2022 report, we found that Python is still the second most commonly used programming language on GitHub. Interestingly, the usage of Python increased by more than 22% year-on-year. In 2022, more than 4 million developers on GitHub were using it.
In this paper, we will introduce the history, characteristics and usage of Python in depth, and try to answer why the programming language conceived in the 1980s can continue to dominate the development. In addition, we will provide some useful tips and techniques for experienced Python developers.
What is Python?
Python is a high-level interpretable programming language, and its syntax is very simple, which makes it easy to read and very friendly to users and beginners. Python was originally built to satisfy the author Guido Van Rossum’s desire to design a simple and beautiful programming language. It was first released to the world in 1991.
Interestingly, this programming language, which originally wanted to express "beauty", chose the word Python as its name, which was related to a TV comedy "Monty Python’s Flying Circus in monty python" which was first broadcast in the 1970s in Britain.
Python language has been widely used in developers, data scientists, researchers and other fields since its birth. You may ask, where do you see that Python is simple and beautiful? Let’s make a comparison:
Usually, as an introductory example, every little white who studies programming will write this case:
Python
And if you use Java, you will have to write many more lines:
Java
Because Python is a universal language, it can be used in various applications, and its simplicity makes it an excellent language for automating tasks, building websites or software and analyzing data. Python has several other features that make it very popular among developers and engineers. These include:
Easy to read:
Python code uses English keywords instead of punctuation, and its line breaks help define code blocks. This means that you can easily understand the design purpose of the code by looking at the code;
Open source code:
You can download the source code, modify it, and use it at will;
Cross platform:
Some languages require you to modify the code to adapt to different platforms, but Python, as a cross-platform language, can run the same code on any operating system as long as it has a Python interpreter installed.
It is extensible:
Python code can be written in other languages (such as C++), and users can add low-level modules in Python interpreters to customize and optimize their tools.
Has a powerful standard library:
This library can be accessed by anyone, which means that users don’t have to write code for each function, but access the built-in modules to help solve problems in daily programming.
What is Python usually used for?
Python can be used for almost anything, from network and software development to machine learning and artificial intelligence (AI). Let’s look at one of the most common use cases.
If you run it, you will see some jokes, which Python engineers usually use to laugh when they are bored.
Anyway, let’s introduce the current situation of Python from some fields:
1.Web and software development field
Python is a popular language for Web and software development, because you can create complex multi-protocol applications on the basis of ensuring concise and readable code. In fact, some of the most popular applications are built in Python. In addition, Python’s open source community provides developers with a lot of reusable code, frameworks and support. Django, for example, is one of the most commonly used Python frameworks designed by a group of experienced developers, aiming to help others develop applications efficiently and solve some common problems that may hinder them from advancing the project.
2. Task automation
An important advantage of using Python is that it can automatically perform some streamlined or repetitive tasks. With Python, you can learn how to automate anything by using built-in modules or pre-written code from its robust library. Or you can write your own custom scripts to perform specific operations. For example, you can easily send an email automatically using the "smtplib" module or copy a file using the "shutil" module. Python also has a set of robust test frameworks, which makes it an excellent language for test automation. Frameworks like Pytest, Behave and Robot allow developers to write simple and effective tests to ensure the quality of their construction.
3. Machine learning and big data
Here is an interesting fact: Python is the preferred language for data science and research. Because its syntax is easy to understand and adaptable, people with little development experience can easily learn Python and use it to manipulate data for research, reporting, prediction or regression analysis. Collecting and analyzing data is a time-consuming task for data scientists. Python, as one of the main languages for training machine learning (ML) models, can analyze and identify the features in these model data through specific algorithms, so as to make predictions or decisions based on these data. It can also be continuously optimized and adjusted based on previous data sets to cope with new variables. Data scientists and developers who train ML models often use some libraries, such as NumPy, Pandas and Matplotlib, to complete automatic data cleaning, transformation and visualization.
4. Financial or financial analysis
Similar to how Python helps data scientists deal with large data sets, Python is widely used in the financial industry to quickly perform complex calculations. The stock market will produce a lot of data, Python can be used to import data about stock prices, and identify trading opportunities through algorithm generation strategies. The language can also be used for portfolio optimization, risk management, financial modeling and visualization, cryptocurrency analysis and even fraud detection.
5. Artificial intelligence
Python can also be used in some of the most complex artificial intelligence (AI) technologies, and it is actually one of the preferred languages for AI. Python’s concise and readable code allows developers to create consistent and reliable systems. Its huge library provides many frameworks like PyBrain, which provides developers with powerful algorithms for machine learning tasks. In addition, the visualization function of Python can help transform these large data sets of AI or ML into understandable graphs or reports. Interestingly, OpenAI, an artificial intelligence research laboratory, uses Python framework Pytorch as their standard framework for deep learning and is used to train its artificial intelligence system.
Why is Python so popular?
Apart from relatively simple learning, there are other reasons why Python continues to be popular. Including:
High production efficiency:
Compared with other more complex programming languages such as C++, Python’s syntax allows users to do more things in less time and reduces the time and effort to write the same line of code.
It has a broad and supportive user community:
Even the best developers will encounter problems, and the user community has become a valuable resource gathering place. Python has a huge community that provides documentation, tutorials, tips and tricks to master the language. For example, the Python community on GitHub provides everything from the latest version of the language to Bug reports and update instructions.
Education recognized:
Python has become the preferred programming language in education, and some students even met Python in primary school. Believe it or not, there are some children’s picture books specially written for Python. Although students majoring in computer science are often taught Python, its use has already gone beyond a single discipline and extended to other fields of STEM and academic research. For example, Python can be used to solve differential equations, perform statistical analysis, simulate and track particle diffusion, and so on.
It has a high enterprise demand:
Because of its wide applicability in development and data analysis, learning and understanding Python is generally considered as a necessary skill for job seekers. According to the situation of well-known recruitment agencies, Python language is the third programming language for global recruiters in 2022.
Python is everywhere, and it has been widely used to build a large number of technologies, websites and even systems that most people encounter every day. The technology it provides, from your favorite video streaming service to machine learning algorithms, even helps you to conduct cryptocurrency transactions. To give a broader example, NASA is also using Python to analyze the data of the complex James Webb space telescope, which makes it one of the few programming languages used in projects outside the world.
