Write a script to collect data from Binance API for provided interval (can be 1d, 4h, 1h) and for provided symbol (BTCUSDT, ETHUSDT, etc.). Suggest a method of deploying such a script to collect relevant data in the interval of your choice (every 1D, 4H, 1H). Save data in csv format. Suggest format of saving data in a relational database.
Write a simple Flask UI, which will display a page with candlestick data from task 1, using plotly as a module for output (since it works dynamically using js), and a piechart of market caps for 10 symbols of your choice.
To run both scripts, you need to have Docker and Docker Compose installed on your machine. You can check if you have them installed by running the following commands:
docker -v
docker-compose -vIf you don't have them installed, please follow the instructions on the official Docker website: https://docs.docker.com/get-docker/
To run the solution, please follow the steps below:
- Clone the repository to your machine:
git clone https://github.com/LexGlu/binance-api.git- Go to the project directory:
cd binance-api- Create a config.py file in the app directory and add the API key from CoinMarketCap to it. You can get the API key from the official CoinMarketCap website: https://coinmarketcap.com/api/ (free plan is enough for this task). The file should look like this:
api_key='your_API_key'- Run the following command:
docker-compose up -d- Wait for the containers to be built and started. Please note that Python script get_kline_data.py will run on startup (to collect sample data from Binance API). You can check the status of the containers with the following command:
docker-compose ps-
When the containers are up and running, you can check Flask UI, which will display a page with candlesticks data and a piechart of market caps for top 10 tokens. It is available at http://localhost:8000. Pie chart is updated in a mock real-time mode (every 30 seconds for demonstration purposes). It is implemented using websockets (Flask-SocketIO library).
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You can check the data in the database using GUI for the database. It is available at http://localhost:8080. You can use credentials from the file .env to login to the database and check the data.
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To stop the containers, run the following command:
docker-compose down -v # -v flag is used to remove volumes as well (database data)The script get_kline_data.py uses Binance API endpoint (https://api.binance.com/api/v3/klines) to collect data for provided interval and symbol. It saves the data in csv format and also saves it in the database (PostgreSQL). The database credentials are stored in the .env file and it runs in a separate container (see docker-compose.yml).
The script will run every hour using cron job. The cron job is defined in the crontab file.
Detailed logs are stored in the logs.txt file. Also logs of cron jobs are stored in the cron.log file.
The database schema is as follows:
- 'open_time' - timestamp of the start of the candlestick (timestamp)
- 'open_price' - price at the start of the candlestick (float)
- 'high_price' - highest price during the candlestick (float)
- 'low_price' - lowest price during the candlestick (float)
- 'close_price' - price at the end of the candlestick (float)
- 'volume' - volume during the candlestick (float)
- 'close_time' - timestamp of the end of the candlestick (timestamp)
- 'quote_asset_volume' - volume of the quote asset during the candlestick (float)
- 'number_of_trades' - number of trades during the candlestick (int)
- 'taker_buy_base_asset_volume' - volume of the base asset bought by taker during the candlestick (float)
- 'taker_buy_quote_asset_volume' - volume of the quote asset bought by taker during the candlestick (float)
The Flask UI is implemented in app.py. It uses the data from the database to display candlesticks. The candlesticks and piechart are implemented using plotly library. The UI is available at http://localhost:8000 (several charts are available, you can switch between them using the list in the top left corner). Gunicorn is used as a WSGI HTTP Server.
