直播技术>> Grou-Cha-Darby>> 返回
项目作者： Kitsuya0828

项目描述 ：
This website enables you to make a Bar Chart Race with your LINE chat history.
高级语言： Python
项目地址: git://github.com/Kitsuya0828/Grou-Cha-Darby.git
创建时间： 2021-02-08T05:02:16Z
项目社区：https://github.com/Kitsuya0828/Grou-Cha-Darby
开源协议：
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Grou-Cha-Darby

This website enables you to make a Bar Chart Race with your LINE chat history.

URL : https://grouchadarby0210.herokuapp.com/

DEMO

Below are the website overview






Features

Requirement

  • Python 3.8.5
  • bar-chart-race 0.1.0
  • ffmpeg 1.4
  • ffmpeg-python 0.2.0
  • japanize-matplotlib 1.1.3
  • matplotlib 3.3.2
  • numpy 1.18.5
  • pandas 1.1.2
  • Pillow 7.2.0
  • plotly 4.14.3
  • streamlit 0.76.0

Installation

  1. pip install bar-chart-race
  2. pip install ffmpeg
  3. pip install ffmpeg-python
  4. pip install japanize-matplotlib
  5. pip install matplotlib
  6. pip install numpy
  7. pip install pandas
  8. pip install Pillow
  9. pip install plotly
  10. pip install streamlit

Usage

  1. git clone https://github.com/Kitsuya0828/Grou-Cha-Darby.git
  2. cd Grou-Cha-Darby

You can run it locally from the command prompt just using the command:

  1. streamlit run app.py

This will spin up a webserver on your local machine and display the application in your browser. You can do your testing here to make sure everything works fine.

The next step is deploying the application on Heroku.
Heroku requires you to create a new GitHub repository for your application and link it with Heroku. This repository should contain all the artifacts needed for your projects.

Below are the main components:

  1. app.py : This is my python code file.
  2. requirements.txt : This file contains all the environmental requirements.
  3. setup.sh : This file is required to run Streamlit in Heroku.
  4. Procfile : This is a file required by Heroku to run the application. It basically tells Heroku what command to execute.
  5. logo.png : This is an image for the logo of the website.
  6. mainimg.png : This is an image for the key visual of the website.

For more details, please refer to the link below:

NLP and Streamlit on Heroku. How I deployed my Streamlit based NLP… | by Rahul Bhattacharya | Towards Data Science

Note

FFmpeg is a collection of libraries and tools to process multimedia content such as audio, video, subtitles and related metadata.

To add Heroku buildpack for ffmpeg, run the following from the heroku command line:

  1. heroku buildpacks:add --index 1 https://github.com/jonathanong/heroku-buildpack-ffmpeg-latest.git

See also:

jonathanong/heroku-buildpack-ffmpeg-latest - Buildpacks - Heroku Elements

Author

License

“Grou-Cha-Darby” is under MIT license.

Thank you!