import sys
from PySide6.QtWidgets import QApplication, QMainWindow, QVBoxLayout, QWidget
from datatable import DataTable, DataType

class MainWindow(QMainWindow):
    def __init__(self):
        super().__init__()
        self.setWindowTitle("DataTable Example")
        self.resize(800, 600)
        
        # Create central widget and layout
        central_widget = QWidget()
        self.setCentralWidget(central_widget)
        layout = QVBoxLayout(central_widget)
        
        # Create DataTable
        self.data_table = DataTable()
        layout.addWidget(self.data_table)
        
        # Set up columns (key, header, data_type)
        columns = [
            ("id", "ID", DataType.NUMERIC),
            ("name", "Name", DataType.STRING),
            ("age", "Age", DataType.NUMERIC),
            ("active", "Active", DataType.BOOLEAN)
        ]
        
        # Set up data
        data = [
            {"id": 1, "name": "John", "age": 30, "active": True},
            {"id": 2, "name": "Jane", "age": 25, "active": False},
            {"id": 3, "name": "Bob", "age": 40, "active": True}
        ]
        
        # Apply to table
        self.data_table.setColumns(columns)
        self.data_table.setData(data)
        
        # Connect signals
        self.data_table.rowSelected.connect(self.on_row_selected)
        
    def on_row_selected(self, row, row_data):
        print(f"Row {row} selected: {row_data}")

if __name__ == "__main__":
    app = QApplication(sys.argv)
    window = MainWindow()
    window.show()
    sys.exit(app.exec())

from datatable import DataTableModel

# Create model with custom formatting
model = DataTableModel()
model.setFormattingFunction("price", lambda value: f"${value:.2f}")
model.setFormattingFunction("percentage", lambda value: f"{value:.1f}%")

# Set model to table
data_table.setModel(model)

# Enable row collapsing
data_table.enableRowCollapsing(True, "subrows")

# Example data with subrows
data = [
    {
        "id": 1, 
        "name": "Category A", 
        "total": 1000,
        "subrows": [
            {"id": 101, "name": "Item A1", "total": 500},
            {"id": 102, "name": "Item A2", "total": 500}
        ]
    },
    {
        "id": 2, 
        "name": "Category B", 
        "total": 2000,
        "subrows": [
            {"id": 201, "name": "Item B1", "total": 1200},
            {"id": 202, "name": "Item B2", "total": 800}
        ]
    }
]

data_table.setData(data)

# Connect expansion signals
data_table.rowExpanded.connect(lambda row, data: print(f"Row {row} expanded"))
data_table.rowCollapsed.connect(lambda row, data: print(f"Row {row} collapsed"))

# Get aggregate values
total = data_table.getAggregateValue("amount", "sum")
average = data_table.getAggregateValue("amount", "avg")
count = data_table.getAggregateValue("id", "count")

# Calculate percentage of a row value relative to total
row_data = data_table.getSelectedRow()
if row_data:
    amount = row_data["amount"]
    total = data_table.getAggregateValue("amount", "sum")
    percentage = data_table.calculateRowPercentage(row_index, "amount")

# Set custom search function for a column
model.setSearchFunction("complex_data", lambda value, term: term in str(value["name"]))

# Search in table
data_table.search("search term")

# Search specific column
matching_rows = model.searchColumn("name", "John")