beauty_trend_dash_flask_app
repo for trend engine web application. work in progress
1. Install requirements
Run pip install --upgrade -r requirements.txt in the desired virtual environment before executing python file.
2. Set environment variable
You have to set AWS credentials environment variables before you can get your application up and running.
To start with, create a file (if it is not exists) .env and set your AWS credentials inside the file.
The content of the .env file should be as follows:
AWS_ACCESS_KEY_ID=your_access_key_id
AWS_SECRET_ACCESS_KEY=your_secret_access_key
The .env file should be in the same folder as settings.py.
3. (Optional) Make necessary changes on the settings.py file
Default value inside settings.py should be fine. Feel free to make any changes
4. Start the dash server on your local computer
To run the app on local machine run
cd meiyume_bte_dash_flask_app
python main.py
in the command line.
Default data is stored and read from S3
bucket = meiyume-datawarehouse-prod
dash_data_path = 'Feeds/BeautyTrendEngine/WebAppData'
Navigate to the correct folder containing the python file before running it.
To deploy the application, please follow how to deploy flask app on aws. Dash app and Flask app deployment procedures are identical.
Make sure assets, images folders are present in correct path when deploying.
Project Folder Structure
meiyume_bte_dash_flask_app
│ README.md
│ License
| Manifest
│ requirements.txt
| setup.py
└───meiyume_trend_engine
│ │ __init__.py
│ │ .env
│ │ settings.py
│ │ main.py
| | bte_category_page_data_and_plots.py
│ │ bte_ingredient_page_data_and_plots.py
| | bte_market_trend_page_data_and_plots.py
| | bte_product_page_data_and_plots.py
| | bte_utils.py
│ └───images
│ | │ not_avlbl.jpg
│ | │ temp_product_image.png
│ | │ ...
| └───assets
│ | │ bte_logo.png
│ | │ resizing_script.js
│ | | responsive-sidebar.css
| | | styles.css
| | | landing_page_bg.jpg