1. Introduction

In recent years, Python has become so popular that many students have no idea what Python can do, so they blindly learn Python. Today, I will give a brief overview of the application fields of Python, so that students who want to learn Python can find the right direction.

2. Python features

First of all, Python is a cross-platform language. The syntax is very simple, and you can do more with very short code. In addition, it is a scripting language, whenever and wherever you write a script can process data, very convenient. It is also an object-oriented language, which is very friendly for beginners. Python also has a rich library of classes in various fields. Crawlers, machine learning, data processing, image processing, and so on meet the needs of most fields. More importantly, Python is a “glue language” that can easily call the mainstream C, C++, and Java libraries. But is that why Python gets blown up? Of course not! No matter how good a language is, it doesn’t matter and can’t be good if it has no practical application.

3. Use areas of Python

Let’s take a look at some areas where Python is actually used.

3.1 Data crawler

Nowadays, Internet data has become the core asset of any company, but there is a huge amount of information on the Internet. In the future, crawlers will come into use to quickly obtain useful public information. The Python language is very good at writing crawlers that crawl web pages through the Requests library, and that use BeautifulSoup to parse web pages and clearly and organize data to get data quickly and accurately. Watching Tiktok with the crawler allows you to see exactly what little video you want to watch. I spent a lot of boring time during the epidemic.

But be careful to do data crawling legally, otherwise it’s jail-oriented programming!

3.2 Web development

Java is not the only Web developer. Python can also be used for fast Web development. Django, Flask, etc., are well-known Python Web frameworks. The ability to take advantage of Python’s features for efficient Web development.

3.3 Software Testing

Python writes test scripts to make testers lose less hair. Python scripts are supported by all the major automated test frameworks. And one of the languages that testers need to know on job boards is Python.

3.4 operations

For large-scale platform operation and maintenance management, even automatic operation and maintenance. Python also has powerful tools such as Fabric, SaltStack, and Ansible.

3.5 Artificial intelligence

At the heart of ai are algorithms and models. You need to focus quickly on the problem itself, and you need to be able to model it interactively. Only Python can fulfill these requirements. The two leading deep learning frameworks, TensorFlow and Pytorch, are both written in Python, and the small but beautiful Darknet was also developed in Python. At present, I am also using Python for the development of deep learning, which will be very complicated if I use Java, because the neural network calculation is a large number of high-dimensional matrices for complex multiplication operations.

The syntax features of Python handle this kind of high-dimensional data manipulation well. Then we can train the weight model to recognize the number, position, and so on of objects in the image.

Deep learning has a high threshold of learning.

3.6 Data Analysis Data mining

Handling large amounts of data is Python’s strength. So Python is also a must-have skill for data engineers. Data cleaning is very convenient. Data analysis Library Pandas provides a convenient Api for analyzing, structuring, and graphically displaying data. Python also provides fast visualization tools such as Matplotlib and HoloViews, which allow data to be visualized quickly.

4. Programmers are not the only ones using Python

Python isn’t just for developers; many people in finance use Python for financial quantification. Office workers who know how to use Python can easily batch Excel, Word, and PDF files, making you a true time management guru. Unfortunately, Python can’t be used for cooking just yet.

5. Getting started with Python is easy

In fact, people with basic programming background can learn the basic syntax of Python in half a day at the earliest. I personally recommend Python as a second language for developers as well. However, to become proficient in Python, you need to learn it systematically. Some of Python’s common libraries, such as Numpy and Pandas, are much harder to learn than Python itself.

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