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# Byte-compiled / optimized / DLL files | ||
__pycache__/ | ||
*.py[cod] | ||
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# PyInstaller: | ||
# Usually these files are written by a python script from a template | ||
# before PyInstaller builds the exe, so as to inject date/other infos into it. | ||
*.manifest | ||
*.spec | ||
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# Unit test / coverage reports: | ||
cover/ | ||
.tox/ | ||
.coverage | ||
.cache | ||
nosetests.xml | ||
coverage.xml | ||
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.DS_Store | ||
frontend/node_modules | ||
/dist | ||
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# Log files | ||
npm-debug.log* | ||
yarn-debug.log* | ||
yarn-error.log* | ||
pnpm-debug.log* | ||
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# Editor directories and files | ||
.idea | ||
.vscode | ||
*.suo | ||
*.ntvs* | ||
*.njsproj | ||
*.sln | ||
*.sw? | ||
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# Pip: | ||
*.lock | ||
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*lock.json |
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# Data Visualization With Python + Vue | ||
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This project aims to explore ``plotly`` library to build and serve a dashboard throughout a flask api. | ||
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On the other side, to present these plots for users, vue is being used with a bootstrap template. | ||
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 | ||
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## Running | ||
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This project was configured to be easy to use, just follow the bellow steps: | ||
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1. Install and configure ``docker`` and ``docker-compose`` in your computer. | ||
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2. After that just start docker compose with the following command: | ||
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```bash | ||
$ docker-compose up --build backend frontend | ||
``` | ||
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3. Now it's time to access the [Dashboard](http://localhost:8080/). | ||
## Conclusion | ||
This project was only a prof of concept to try the ``flask`` framework with a web interface written with ``vue`` using ``plotly`` library. | ||
It was very easy to configure this project, build the charts and configure the interface. I believe that it can be used for commercial proposals and be very acceptable. | ||
## Contributors | ||
**Priscilla Trindade** [Github](#) | ||
**Rafael Souza da Silva** [Github](https://github.com/arkanister) |