Pandas - MongoDB - Decouple - Flask (For the Docker)

1. Install python

2. Install pip lib to install dependencies using: python3 -m pip install --user --upgrade pip

3. Install virtual env using: python3 -m pip install --user virtualenv

4. Create a virtualenv for the project: python3 -m venv env

5. To activate it use: source env/bin/activate

6. Install the Python imports using pip install -r requirements.txt

7. Set code variables on a .env file as .env.example shows

8. Run createIndexes.py for creating the indexes and constraints, this file needs to be run only once.

9. Run the code files to activate the pipelines, example : python tradedVolume.py, having the env activated within the libs of last step

• List of python pipelines files: tradedVolume.py, dailyTradedVolumeSENA.py, floorPriceSENA.py, NFTTradedVolume.py, senaNFTRoyalties.py, totalTransactions.py, tradedVolumeSENA.py

** If having problems upolading data to mongodb, try running python sslLoad.py before pipeline file.

** Pipelines are online and scheduled to run daily on heroku.com, so the docker build is only for demonstration

** Pipelines connected to devnet sometimes return no data, the code will print where no data stops the pipeline process and finish running normally

1. docker build -t sena-analytics:latest .

2. docker run -d sena-analytics