A robust data-pipeline that can run various backtests and store various useful artefacts in a robust data warehouse system.
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The main objective of this project is to design and build a reliable, large-scale ,robust data-pipeline that can run various backtests and store various useful artifacts in a robust data warehouse system for Mela who wants to enter the world of cryptocurrencies to make simple trade for everyone.
There are a number of data points that yahoo finance and binance provides and you can use, but for the purpose of testing the backend development, you can start of with the candlestick data. You can read a brief description of what a K-line or candlestick data is here. The data used for the EDA of this project is Algorand USD financial dataset, from Algorand USD (ALGO-USD) Price History & Historical Data - Yahoo Finance dates; from October 11, 2021 to October 11, 2022. The data shows the historical prices on a daily basis.
git clone https://github.com/Hu-10xB6W7G5/Mela-Crypto-Trading-Engineering.git
cd Mela-Crypto-Trading-Engineering
pip install -r requirements.txt
cd Mela-Crypto-Trading-Engineering/frontend
npm install
npm start
cd Mela-Crypto-Trading-Engineering/backend
npm install
touch .env #and write the environmental viriables there
npm start
MIT