软件界的尺码通用指南：欧洲尺码与日本尺码破解对比

Introduction

With the growth of technology and the internet, it has become increasingly convenient for people to access a wide range of services online. This has given rise to a number of websites and apps that offer entertainment, education, shopping, and much more. In this article, we will focus on the development of a Python web crawler that we can use to extract data from two websites: a European clothing size website and a short video app.

The European Clothing Size Website

There are several websites that offer a platform for online shopping, but the sizes of clothing can differ greatly depending on the country of origin. Hence, one of the major challenges of shopping online is finding the right size that best fits one's body type. The European Clothing Size Website provides a solution for this problem with its size converter that offers a comparison between European and Japanese sizes.

One of the difficulties of extracting data from this website is the fact that it requires a login before proceeding to the size conversion page. To address this, we will first use the Requests library to create a session, pass in the login credentials, and navigate to the size converter page. Once we get to the conversion page, we will use BeautifulSoup to parse the HTML and extract the necessary data for our size conversion table.

The Short Video App

Short video apps are becoming increasingly popular among younger audiences as they offer a quick and entertaining way to consume small amounts of information. In this section, we will focus on extracting data from a video app that offers free access to a short video library. The app is developed for both Android and iOS, and is available for download on their respective app stores.

We can use a similar approach as we did with the European Clothing Size website to extract data from this app. We will first use Requests to simulate the app login process and create a session. Once successfully logged in, we will use BeautifulSoup to parse the app's HTML and extract the links to the free videos. Finally, we will use the FFmpeg library to download the videos and save them locally on our computer.

Conclusion

In this article, we have outlined the steps required to use Python web crawling tools like Requests, BeautifulSoup, and FFmpeg to extract data from a European clothing size website and a short video app. Web crawlers are a valuable asset for data scientists and researchers as they allow for the extraction of vast amounts of data that can be analyzed for valuable insights. While web crawling comes with certain ethical concerns, with responsible use, it can be a powerful tool that benefits both individuals and organizations.

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