Hello! In this article, we will take a closer look at developing an automated trading system using Python and the layout of PyQt. Through this blog, I will explain the process of building a system that can automatically trade financial assets like stocks or cryptocurrencies, and in that process, we will learn how to configure the user interface (UI) using PyQt.
1. What is an Automated Trading System?
An automated trading system is a system where a computer program automatically trades financial assets according to a pre-set algorithm. It makes buying and selling decisions according to a strategy that has been set beforehand, without human intervention. This allows exclusion of emotional judgment and facilitates a more systematic and consistent trading approach.
2. Powerful Tools in Python
Python is a widely used programming language for developing automated trading systems. The reasons are as follows:
- Simple and intuitive syntax
- Powerful data analysis libraries (e.g., Pandas, NumPy)
- Various packages for algorithmic trading (e.g., ccxt, backtrader)
- Libraries for user interface configuration (e.g., PyQt, Tkinter)
3. What is PyQt?
PyQt is a binding of the Qt framework for Python, which helps in easily developing GUI programs. PyQt provides various widgets and layouts that are useful for designing user interfaces, and can also be designed separately through Qt Designer.
4. Understanding PyQt Layouts
Layouts determine how UI elements are arranged on the screen. PyQt provides several layout managers. The main layout managers are as follows:
- QHBoxLayout: Arranges widgets horizontally
- QVBoxLayout: Arranges widgets vertically
- QGridLayout: Arranges widgets in a grid form
- QFormLayout: Arranges labels and input fields in pairs
4.1 QVBoxLayout Example
Here is an example of configuring a simple automated trading UI using QVBoxLayout.
import sys
from PyQt5.QtWidgets import QApplication, QWidget, QVBoxLayout, QLabel, QPushButton, QLineEdit
class TradeApp(QWidget):
def __init__(self):
super().__init__()
self.initUI()
def initUI(self):
layout = QVBoxLayout()
self.label = QLabel('Automated Trading System', self)
layout.addWidget(self.label)
self.stock_input = QLineEdit(self)
self.stock_input.setPlaceholderText('Enter the stock to buy')
layout.addWidget(self.stock_input)
self.start_button = QPushButton('Start Trading', self)
layout.addWidget(self.start_button)
self.setLayout(layout)
self.setWindowTitle('Automated Trading System')
self.show()
if __name__ == '__main__':
app = QApplication(sys.argv)
ex = TradeApp()
sys.exit(app.exec_())When you run the above code, a simple GUI window will open, featuring a text field for entering the name of the stock and a button to start trading.
4.2 QHBoxLayout and QGridLayout
If you want to make the UI more complex, you can use QHBoxLayout and QGridLayout. For example, here is code that includes input fields for buy and sell prices along with a button to execute the trade.
class AdvancedTradeApp(QWidget):
def __init__(self):
super().__init__()
self.initUI()
def initUI(self):
grid_layout = QGridLayout()
grid_layout.addWidget(QLabel('Asset:'), 0, 0)
self.stock_input = QLineEdit(self)
grid_layout.addWidget(self.stock_input, 0, 1)
grid_layout.addWidget(QLabel('Buy Price:'), 1, 0)
self.buy_price_input = QLineEdit(self)
grid_layout.addWidget(self.buy_price_input, 1, 1)
grid_layout.addWidget(QLabel('Sell Price:'), 2, 0)
self.sell_price_input = QLineEdit(self)
grid_layout.addWidget(self.sell_price_input, 2, 1)
self.start_button = QPushButton('Start Trading', self)
grid_layout.addWidget(self.start_button, 3, 0, 1, 2)
self.setLayout(grid_layout)
self.setWindowTitle('Advanced Automated Trading System')
self.show()
if __name__ == '__main__':
app = QApplication(sys.argv)
ex = AdvancedTradeApp()
sys.exit(app.exec_())Using the above code, you can create a UI that allows users to input the asset, buy price, and sell price. QGridLayout can be used to further organize the spacing between widgets.
5. Implementing the Trading Logic
After configuring the UI, the process of implementing the actual automated trading algorithm begins. I will show you a simple example of an automated trading logic. In this example, a strategy will be applied to buy when the price is below a specified buy price and to sell when the price is above a sell price.
class TradingAlgorithm:
def __init__(self):
self.current_price = 0
self.buy_price = 0
self.sell_price = 0
def update_price(self, price):
self.current_price = price
self.trade_logic()
def trade_logic(self):
if self.current_price <= self.buy_price:
print(f'Buy: Current price {self.current_price}')
elif self.current_price >= self.sell_price:
print(f'Sell: Current price {self.current_price}')
if __name__ == "__main__":
algorithm = TradingAlgorithm()
algorithm.buy_price = 50000
algorithm.sell_price = 55000
# Example of virtual price updates
for price in [48000, 51000, 53000, 55000, 57000]:
algorithm.update_price(price)This code executes buying or selling logic based on the current price being below or above the set buy and sell prices, respectively. In a real environment, prices can be fetched in real-time through an external API.
6. Integration
This is the process of integrating the UI and the algorithm. You can connect the algorithm to execute based on the conditions received from the UI.
class TradeApp(QWidget):
def __init__(self):
super().__init__()
self.initUI()
self.algorithm = TradingAlgorithm()
def initUI(self):
# ... Reuse previous UI code ...
self.start_button.clicked.connect(self.start_trading)
def start_trading(self):
self.algorithm.buy_price = float(self.buy_price_input.text())
self.algorithm.sell_price = float(self.sell_price_input.text())
# Example of continuously updating with actual external prices
for price in [48000, 51000, 53000, 55000, 57000]:
self.algorithm.update_price(price)
if __name__ == '__main__':
app = QApplication(sys.argv)
ex = TradeApp()
sys.exit(app.exec_())The above code applies the buy and sell prices inputted by the user to the automated trading algorithm for execution. In reality, external APIs would continuously receive the prices, but here we used simple examples with virtual prices.
7. Conclusion
In this article, we explored the fundamentals of developing an automated trading system using Python and how to configure the GUI using PyQt. You can create a user-friendly UI through various layout managers in PyQt and build a complete system by integrating the automated trading algorithm.
Now you have laid the foundation for building an automated trading system with Python. Based on this, try developing your unique automated trading system!