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A trading robot built for Python that uses the TD Ameritrade API.

Project description

Python Trading Robot

Table of Contents


Current Version: 0.1.1

A trading robot written in Python that can run automated strategies using a technical analysis. The robot is designed to mimic a few common scenarios:

  1. Maintaining a portfolio of multiple instruments. The Portfolio object will be able to calculate common risk metrics related to a portfolio and give real-time feedback as you trade.

  2. Define an order that can be used to trade a financial instrument. With the Trade object, you can define simple or even complex orders using Python. These orders will also help similify common scenarios like defining both a take profit and stop loss at the same time.

  3. A real-time data table that includes both historical and real-time prices as they change. The StockFrame will make the process of storing your data easy and quick. Additionally, it will be setup so that way you can easily select your financial data as it comes in and do further analysis if needed.

  4. Define and calculate indicators using both historical and real-time prices. The Indicator object will help you easily define the input of your indicators, calculate them, and then update their values as new prices come.


Setup - Local Install:

If you are planning to make modifications to this project or you would like to access it before it has been indexed on PyPi. I would recommend you either install this project in editable mode or do a local install. For those of you, who want to make modifications to this project. I would recommend you install the library in editable mode.

If you want to install the library in editable mode, make sure to run the file, so you can install any dependencies you may need. To run the file, run the following command in your terminal.

pip install -e .

If you don't plan to make any modifications to the project but still want to use it across your different projects, then do a local install.

pip install .

This will install all the dependencies listed in the file. Once done you can use the library wherever you want.

Setup - PyPi Install:

The project can be found at PyPI, if you'd like to view the project please use this link. To install the library, run the following command from the terminal.

pip install python-trading-robot

Setup - PyPi Upgrade:

To upgrade the library, run the following command from the terminal.

pip install --upgrade python-trading-robot


To run the robot, you will need to provide a few pieces of information from your TD Ameritrade Developer account. The following items are need for authentication:

  • Client ID: Also, called your consumer key, this was provided when you registered an app with the TD Ameritrade Developer platform. An example of a client ID could look like the following MMMMYYYYYA6444VXXXXBBJC3DOOOO.

  • Redirect URI: Also called the callbakc URL or redirect URL, this was specified by you when you regiestered your app with the TD Ameritrade Developer platform. Here is an example of a redirect URI https://localhost/mycallback

  • Credentials Path: This is a file path that will point to a JSON file where your state info will be saved. Keep in mind that it is okay if it points to a non-existing file as once you run the script the file will be auto generated. For example, if I want my state info to be saved to my desktop, then it would look like the following: C:\Users\Desktop\ts_state.json

Once you've identfied those pieces of info, you can run the robot. Here is a simple example that will create a new instance of it:

from pyrobot.robot import PyRobot

# Initialize the robot
trading_robot = PyRobot(

For more detailed examples, go to the file to see an example of how to use the library along with all the different objects inside.

Support these Projects

Patreon: Help support this project and future projects by donating to my Patreon Page. I'm always looking to add more content for individuals like yourself, unfortuantely some of the APIs I would require me to pay monthly fees.

YouTube: If you'd like to watch more of my content, feel free to visit my YouTube channel Sigma Coding.

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