BOTSLab on GitHub

We have integrations for a variety of programming languages. A bot creator may connect his bots to our platform by using the following integrations.: MetaTrader Integration, R, C Sharp, TradingView, and Python. If a bot creator wants to run the bot on his own server, he must contact his system or network administrator. The following firms provide appropriate virtual machines:

• DigitalOcean: https://www.digitalocean.com/products/droplets/
• Microsoft: https://azure.microsoft.com/en-us/services/virtual-machines/

To operate an existing bot or to develop your own, you'll need to prepare your PC so that this project can execute.

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Follow the steps in this part to accomplish it.

Create and run your own bot:

• This bot is located in bots/rsi.py. The bots folder contains the files ema.py and sma.py, which are two Ta-Lib library-using bots. To build your own bot, read the README instructions in this part of the document.

Writing your first bot: 

• Please refer to bots/bot_template.py for guidance on how to write your first bot. You will have to implement a function called get_buy_or_sellsignal and store it in a python file with the ".py" extension inside the "bots" folder.

Configuration Backtesting tool: 

• The Backtesting tool's simulation parameters and the data settings for the historical data can be found in config_test.py.

Run your bot against the backtesting engine: 

• Configure the bot_name parameter in config_test.py with the following value: bot_name = 'bots.[file_name_of_bot]'
• To test the bot, follow the instructions above and use the recommended Docker command: run_bot.sh test (or run_bot.cmd test on Windows).

Run your bot live: 

• Give the parameter bot_name the proper value in config_live.py: bot_name = 'bots.[file_name_of_bot]' .
• You can execute the bot in live mode by following the instructions above, for example with the recommended Docker command: run_bot.sh live (or run_bot.cmd live if you're using Windows).

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Running a bot using Docker: 

• Install Docker
• You won't have to install any platform-specific dependencies when you use Docker (for example, Python). Only Docker is needed.
• For Windows and macOS, install Docker Desktop from: https://www.docker.com/get-started.
• If you want to install Docker and Docker Compose on Ubuntu Linux, follow these instructions:

• https://www.digitalocean.com/community/tutorials/how-to-install-and-use-docker-on-ubuntu-18-04
• https://www.digitalocean.com/community/tutorials/how-to-install-docker-compose-on-ubuntu-18-04

• If you have not already done so, clone the Bot-Backtesting project onto your computer using Git.
• Use the following commands in a command prompt, after you navigate to the project directory:

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Alternative: running the bot without Docker

• Python 3 must be downloaded and installed.
• Install the TA-Lib library.
• To install the Python dependencies, run bash create_venv.sh from a terminal on Linux and macOS or run create_venv.cmd on Windows.

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