I ended up switching to df.query(), but keeping this dummy code here for reference

typed_queries_in_python.py

# Create class for handling filters with logical operations
class Filter(Generic[T]):
    def __init__(self, name: str, value: T, op: str = "=="):
        self.name = name
        self.value = value
        self.op = op

        if type(value) == str:
            if op == "==":
                self.op = "eq"
            elif op == "!=":
                self.op = "neq"
            elif op == ">":
                self.op = "gt"
            elif op == ">=":
                self.op = "gte"
            elif op == "<":
                self.op = "lt"
            elif op == "<=":
                self.op = "lte"
            elif op == "contains":
                self.op = "contains"
            elif op == "not contains":
                self.op = "notContains"
            elif op == "unknown":
                self.op = "unknown"

    def __and__(self, other: Filter):
        return Filter(self.name, self.value & other.value)

    def __or__(self, other: Filter):
        return Filter(self.name, self.value | other.value)

    def __invert__(self):
        return Filter(self.name, ~self.value)

    def __repr__(self):
        return f"Filter({self.name}, {self.value})"