Abstract
Since the outbreak of COVID-19 in 2020, it has had a great impact on the health
of the people and the economic development of all regions of the country, and the
impact of COVID-19 on various fields has not been completely eliminated. In the past
three years, new epidemics have broken out many times in various regions of the
country, resulting in many people being quarantined, and also leading to the need
for students at all stages of the country to have online classes at home, which has
also brought inconvenience to students' learning. Although the epidemic has been
well controlled, if the virus mutates again, no one can guarantee that the epidemic
will return. At the beginning of the epidemic, people learned about the daily
epidemic data through television news or newspapers, but this form is laborious,
because the number of information transmission channels in a region is limited,
people can not freely understand the epidemic data, and the number of prevention
and control staff in each region is certainly limited, The accuracy and timeliness of
epidemic data can not be guaranteed by traditional methods.
The frontend interface of the system uses the latest HTML5 technology and
uses DIV+CSS for layout, which makes the whole frontend page more beautiful and
greatly improves the user experience. In addition, the system can ensure the correct
layout of the website whether it is accessed using a computer browser or using a
mobile device. The back-end code technology is PYTHON. PYTHON language is one of
the most commonly used programming languages at present, which can ensure the
stability and smoothness of the system. PYTHON can flexibly connect with the
database. The data of this system uses the MYSQL database, which can improve the
query speed and enhance the stability and security of the system data storage. The
core algorithm of this system is the big data algorithm. Using data crawler to analyze
data is a very popular mode at present and also the development trend of many
industries in the future. This method can accurately display and analyze epidemic
data.
Key words:Campus; Epidemic monitoring;PYTHON； MySQL
