Front-end and rear-end automatic deployment tool forming method based on data analysis

Abstract

The invention provides a front-end and rear-end automatic deployment tool forming method based on data analysis. The method comprises the following steps of: configuring codes of a front-end project environment, a configuration file address corresponding to the environment, corresponding server information and a directory to be packaged into a static file; and deploying the static file on the static server corresponding to the target project environment, so that the problems of high manual error and high online risk caused by manual code modification of interface addresses of different environments in the prior art are avoided. Meanwhile, the problem of online failure caused by manual errors due to the fact that codes of the code server are not directly read in the online process is avoided. According to the method, manual operation is time-consuming and labor-consuming when traditional front-end projects are online, and after the method is adopted, the investment of labor cost is reduced, and the working efficiency is improved. The traditional online flows of the front end and the rear end of a project are different and cannot be managed in a unified manner, and the packaging deployment tool based on the invention enables the flows to be unified and is convenient to manage.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of data analysis, and in particular to a method for forming a front-end and back-end automatic deployment tool based on data analysis. Background technique [0002] At present, only the back-end java project integrates the deployment function among the existing tools. Front-end projects need to manually modify the code to distinguish environments for different environments. [0003] Find in the process of realizing the present invention, adopt prior art to have following shortcoming: [0004] Interface addresses in different environments are realized by manually modifying the code, and manual errors are high. After manually modifying the code and then manually uploading the code to the server for online deployment, the risk of online deployment is high; manually uploading the code to the server is inefficient; , the error rate is high, and the online risk is high; the front-end projec...

AI Technical Summary

Problems solved by technology

[0004] Interface addresses in different environments are realized by manually modifying the code, and manual errors are high. After manually modifying the code and then manually uploading the code to the server for online deployment, the risk of online deployment is high; manually uploading the code to the server is inefficient; , the error rate is high, and the risk of going online is high; the front-end project deployment process is inconsistent with the back-end, the online process cannot be managed uniformly, and the operation and maintenance complexity coefficient is high

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