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Python quickly realizes large screen data display, which is very cool

編輯:Python

Hello , I'm brother Zheng , A large data screen will be built recently , To show the overall progress of the project to the leaders , So I opened it VSCode, plan Python、flask、echarts Open the door . however , Time is limited , must 1 In a day , So I searched GitHub, It really takes no effort , Modification data , Fine tuning down echarts Just like the .

I feel that friends who do data analysis may need , Let's share .

Project address TurboWay/big_screen[1]

1、 Look at the renderings first

The background is dynamic , It's cool .

2、 Installation and operation

Clone project first , install flask rely on

git clone https://github.com/xiaokai1996/big_screen.git 
pip install flask

Enter the directory , function app.py:

cd big_screen
python app.py

And then you can see :

  • General template for big data visualization display board http://127.0.0.1:5000/

  • 4600 Large screen visualization of enterprise data http://127.0.0.1:5000/corp

  • (2020-09) Xiamen 10 Large screen visualization of recruitment data http://127.0.0.1:5000/job

modify

The data of the project is written in data.py Medium , You need to change it to automatic acquisition .

If you want to adjust echarts The histogram of 、 Broken line diagram 、 The pie chart , You can modify templates/index.html file , Need to adjust data , Please cooperate with the modification data.py The data format inside .

Other large screen templates

You can refer to the large screen templates of various industries [2], All are echarts It's done , Bring it to me if you need it , use Python Of Web Frame to render , You can make a large data screen ,Django and Flask Fine . Small projects Flask Well , Very fast .

Last words

This article shares Python Template of large data screen , You can modify it for your own use , This is a very fast development method . If it helps , Please like it 、 Looking at diffusion . If there are questions , You can send a message directly below , New friends can pay attention to .

Reference material

[1]

TurboWay/big_screen: https://github.com/TurboWay/big_screen

[2]

Large screen templates for data of various industries : https://gitee.com/lvyeyou/DaShuJuZhiDaPingZhanShi


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