What are the applications of python in ordinary work?

Application of Python in ordinary work: 1. Python development, including automated testing, automated operation and maintenance, and WEB development; 2. Python crawler, which obtains or processes a large amount of information; 3. Python big data analysis, from chaos to chaos Extract valuable information or patterns from the data.

Application of python in ordinary work:

From work Applications: Python development, Python crawlers, big data;

In terms of life, crawlers add a lot of fun to our lives and make our daily lives easier.

Python development

Automated testing, automated operation and maintenance, WEB development (website development), and artificial intelligence all belong to Python development.

Automated testing - use Python to write simple implementation scripts and use them in Selenium/lr to achieve automation.

Automated operation and maintenance - Python is very important for server operation and maintenance.

Currently, almost all Linux distributions come with a Python interpreter to use Python scripts for batch file deployment and operation adjustment~

And Python provides a full range of tools Collection, combined with the Web, it will become very simple to develop tools that facilitate operation and maintenance.

WEB development - Python's most popular WEB development framework Django is very popular in the industry, and its design philosophy is also commonly used in other programming language design frameworks~

If it is a website backend, use It is a single-room website and the backend service is relatively easy to maintain. As we often see: Gmail, Zhihu, Douban, etc.~

Artificial intelligence is a very popular direction now. Most of the several very influential AI frameworks released now are implemented in Python. of.

Python crawler

In the current era of information explosion, a large amount of information is displayed through the Web. In order to obtain this data, web crawler engineers came into being.

But this is not only our daily simple data capture and analysis, it can also break through the common anti-crawler mechanisms of ordinary websites, as well as write deeper crawler collection algorithms.

You can also go online to search for interesting things that others have done through crawlers. Let me pick a few to talk about:

"The first program written in Python was crawling embarrassing things. The pictures on the encyclopedia are automatically downloaded to the local area and automatically divided into folders to save. At that time, I thought, holy shit, it’s so NB~”

“12306 train ticket query tool, Ctrip ticket query; crawling Meituan movies , Douban movie user reviews; a simple Meituan restaurant crawler and making a simple heat map based on geographical coordinates...these are not difficult.” The obtained data were analyzed and visualized using Excel and Python (matplotlib) respectively..."

"I tried to crawl the product information of JD.com's hot sales and Taobao's rush sales (or Juhuasuan), but I didn't expect it to be quite good. Simple, mainly because there are no anti-crawler measures..."

Data is the core asset of a company, and useful information can be extracted from messy data. Value information or patterns have become the primary task of data analysts.

Python's tool chain provides extremely efficient support for this heavy work. Data analysis is based on crawlers. We can easily crawl down massive amounts of data to perform analysis.

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