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Why do most programmers choose Python as an entry-level language?

At this point, many developers would argue that they did not choose Python and cannot generalize. Below, we take a statistical look at the most popular programming languages today.

In March, HackerRank released its latest developer survey. According to the report, the most popular programming language for students at school is Python, followed by C++, Java, C and JavaScript.

For established developers, their favorite programming languages are Python, Java, JavaScript, C, and C++. Although the rankings vary, Python does rank first.

Additionally, according to Hacker News job trends, more and more companies are interested in developers with Python skills. Meanwhile, According to PYPL, which tracks the popularity of programming languages, Python overtook JavaScript in second place with 5.2% growth, faster than any other language, while Java’s overall learning trend declined slightly.

In summary, Python is not as widely used as Java, but it is undoubtedly the most dazzling among upstarts such as Go and Swift.

Introduction of Python

Python was designed by Guido Van Rossum at the Dutch National Institute for Mathematical and Computer Science in the late eighties and early nineties.

Python is a high-level scripting language that combines interpretation, compilation, interactivity, and object-oriented programming.

Python is designed to be highly readable and has a more distinctive syntax structure than other languages that use English keywords more often, and some punctuation marks in other languages.

  • Python is an interpreted language: this means there is no compilation part of the development process. Similar to PHP and Perl.
  • Python is an interactive language: this means that you can execute code directly after a Python prompt >>>.
  • Python is an object-oriented language: this means that Python supports an object-oriented style or programming technique in which code is wrapped in objects.
  • Python is a Beginner’s language: Python is a great language for beginning programmers, supporting a wide range of application development, from simple word processing to WWW browsers to games.
Pros and cons of Python

What is it about Python that makes it so popular? We have to start with Python features:

  • Its standard library provides a variety of features designed to simplify the implementation of complex applications;
  • Use high-level programming languages;
  • Perform basic tasks with less code;
  • If compared to Java, Python has 3-5 times less code; It has 5-10 times less code than C ++.
  • The Python language supports many types of programming, such as object-oriented, imperative, and functional.
  • Its memory management is done automatically.

For beginners, Python is more practical and easier to use than traditional static languages such as Java and C++. For developers with some programming background, learning Java, C++, C#, etc., and then learning Python in reverse is a piece of cake.

Is there a downside to Python? The answer must be yes. Its disadvantages are mainly the execution speed is not fast enough, single line statements, forced indentation and other small problems, and compared with its advantages, almost negligible.

Learning Python

Although Python is a programming language that is very easy to use, it only means that getting started is relatively easy, and there are some systematic ways to learn Python well. This paper has drawn up its own learning route, as shown in the mind map.

You should start with basic knowledge of data structures, what objects are, Python’s built-in functions, conditional controls and loop statements, functions and object-oriented, string regular handling, file handling, and exception handling.

Crawler is optional, requiring front-end and back-end basic knowledge and communication principles, and can be combined with requests and Bs4 library for simple web page crawling. Selenium and Applium respectively simulate web browsing and app browsing by machine, and scrapy library helps us to implement high-throughput distributed crawler. Pyquery and PyMongo help us access and query data;

Python is used to perform data analysis and visualization. Numpy and PANDAS are used to calculate arrays and data boxes, and Matplotlib and Pyecharts are used to draw geographic graphs.

With a deeper understanding of data, we can use Python to implement artificial intelligence algorithms very easily. For example, SkLearn can help us to implement text image classification, regression, clustering and dimensionality reduction. Keras, TensorFlow, PyTorch and others use neural networks (simulating the role of human brain neurons) to operate deep learning, which is a new research direction in the field of machine learning. It is introduced into machine learning to make it closer to the original goal and artificial intelligence.

The final piece is big data content, which requires a basic knowledge of Java (or Scala), SQL, and Linux. For example, MapReduce in Hadoop can be implemented through Pyton. Spark and Flink also support Python interfaces.

After following the Python learning roadmap above, you will be able to become a qualified Python development engineer, + 606 for the first three digits, 846 for the middle three digits, 127 for the last three digits, T123 for the secret code, and receive Python Web development, Python crawler, And Python data analysis. Artificial intelligence and other boutique learning courses. Learn Python from scratch!

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