The difference between RPA and Python in data crawling is mainly reflected in the following aspects: Purpose and application scope: The main purpose of RPA is to complete repetitive and regular work, such as data input, file transfer, etc; RPA is suitable for these simple and repetitive automated tasks, and has a wide range of applications in enterprises in various industries, which can reduce manual repetitive operations; Python crawling data is mainly used to capture information from the Internet, such as commodity prices, news, etc; This scraping is usually a technique based on the structure of the web page, with Python analyzing the HTML code to extract the required information.

Technical implementation: RPA usually uses a graphical interface to record scripts, which are pre-defined, and then runs these scripts to get the job done; This makes the implementation of RPA relatively intuitive and simple, and does not require much programming knowledge; Python, on the other hand, is a programming language, and using Python to crawl data usually requires some programming knowledge, including how to send HTTP requests, how to process HTML, and how to parse data.

Python crawling data is more flexible and extensible, and new data can be crawled by writing new scripts.

Automation and flexibility: RPA is a rule-based technology that requires rules to be defined in advance to perform tasks, which means that RPA has a relatively high degree of automation, but it may need to update or adjust the rules frequently when dealing with some irregular or changing tasks; Python crawling data is more flexible, can be programmed to adapt to changes in the structure of the web page or changes in the data format, but this also requires developers to have enough programming knowledge and experience.

Legal and compliance: It should be noted that improper use of Python for web crawlers may pose legal risks to the company, such as violating the privacy or copyright of others; RPA, on the other hand, deals with relatively few of these issues because it mainly simulates human operations to automate tasks.

In summary, the differences between RPA and Python in data crawling are their purpose and scope of application, technical implementation, automation and flexibility, and legal and regulatory compliance.

The specific choice of which way to crawl data should be based on the actual needs and application scenarios to decide.