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 instructions found on GitHub.
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.
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).
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:
- 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:
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.