Mock Predicate Pushdown in Python for Big Data Queries

class Query:
    def __init__(self, table, rows):
        self.table = table
        self.rows = rows

    def filter(self, predicate):
        return Query(
            self.table,
            [row for row in self.rows if all(predicate(row) for predicate in predicate)]
        )

    def filter_pushdown(self, predicate, column):
        """
        Mock predicate pushdown: apply predicate at the 'storage' level
        before reading full rows. Simulates pushing filter into scan.
        """
        # Simulate storage-level scan returning only matching rows
        # (as if the predicate was applied in the storage engine)
        storage_rows = [row for row in self.rows if predicate(row)]

        # This is where real pushdown would avoid materializing full data
        return Query(self.table, storage_rows)

    def execute(self):
        return self.rows


if __name__ == "__main__":
    # Simulate a table with 5 rows
    rows = [
        {"id": 1, "name": "Alice", "age": 30},
        {"id": 2, "name": "Bob", "age": 25},
        {"id": 3, "name": "Charlie", "age": 35},
        {"id": 4, "name": "Diana", "age": 28},
        {"id": 5, "name": "Eve", "age": 32},
    ]

    q = Query("users", rows)

    # Push predicate into "storage" (simulated)
    pushed = q.filter_pushdown(lambda r: r["age"] > 30, "age")

    print("Rows after predicate pushdown (filter age > 30):")
    for row in pushed.execute():
        print(row)