Python使用pyforms实现轻松构建GUI

from pyforms.basewidget import BaseWidget
from pyforms.controls import ControlButton, ControlList
import matplotlib.pyplot as plt
import numpy as np

class DataVisualization(BaseWidget):
    def __init__(self):
        super().__init__('Data Visualization')

        self._data = ControlList('Data')
        self._plot_button = ControlButton('Plot')

        self._plot_button.value = self.__plot_data

    def __plot_data(self):
        data = np.array(self._data.value)
        plt.plot(data)
        plt.show()

if __name__ == '__main__':
    app = DataVisualization()
    app.run()

from pyforms.basewidget import BaseWidget
from pyforms.controls import ControlButton, ControlText
import numpy as np

class ScientificCalculator(BaseWidget):
    def __init__(self):
        super().__init__('Scientific Calculator')

        self._input = ControlText('Input')
        self._calculate_button = ControlButton('Calculate')
        self._result = ControlText('Result')

        self._calculate_button.value = self.__calculate

    def __calculate(self):
        expression = self._input.value
        result = eval(expression)
        self._result.value = str(result)

if __name__ == '__main__':
    app = ScientificCalculator()
    app.run()

from pyforms.basewidget import BaseWidget
from pyforms.controls import ControlButton, ControlFile
from sklearn.linear_model import LinearRegression
import pandas as pd

class MachineLearning(BaseWidget):
    def __init__(self):
        super().__init__('Machine Learning')

        self._data_file = ControlFile('Data File')
        self._train_button = ControlButton('Train')
        self._predict_button = ControlButton('Predict')

        self._train_button.value = self.__train_model
        self._predict_button.value = self.__predict

        self._model = LinearRegression()
        self._data = None

    def __train_model(self):
        data_file = self._data_file.value
        self._data = pd.read_csv(data_file)
        X = self._data[['x']]
        y = self._data['y']
        self._model.fit(X, y)

    def __predict(self):
        x = float(input('Enter x: '))
        y = self._model.predict([[x]])
        print('Predicted y:', y)

if __name__ == '__main__':
    app = MachineLearning()
    app.run()