617 lines
16 KiB
Python
617 lines
16 KiB
Python
import typing
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from typing import Dict, List, Set, Tuple
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import cloudpickle
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import pytest
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from pandas import DataFrame
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from reflex.base import Base
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from reflex.state import State
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from reflex.vars import (
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BaseVar,
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ComputedVar,
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ImportVar,
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ReflexDict,
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ReflexList,
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ReflexSet,
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Var,
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get_local_storage,
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)
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test_vars = [
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BaseVar(name="prop1", type_=int),
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BaseVar(name="key", type_=str),
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BaseVar(name="value", type_=str, state="state"),
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BaseVar(name="local", type_=str, state="state", is_local=True),
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BaseVar(name="local2", type_=str, is_local=True),
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]
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test_import_vars = [ImportVar(tag="DataGrid"), ImportVar(tag="DataGrid", alias="Grid")]
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class BaseState(State):
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"""A Test State."""
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val: str = "key"
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@pytest.fixture
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def TestObj():
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class TestObj(Base):
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foo: int
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bar: str
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return TestObj
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@pytest.fixture
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def ParentState(TestObj):
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class ParentState(State):
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foo: int
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bar: int
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@ComputedVar
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def var_without_annotation(self):
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return TestObj
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return ParentState
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@pytest.fixture
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def ChildState(ParentState, TestObj):
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class ChildState(ParentState):
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@ComputedVar
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def var_without_annotation(self):
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return TestObj
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return ChildState
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@pytest.fixture
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def GrandChildState(ChildState, TestObj):
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class GrandChildState(ChildState):
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@ComputedVar
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def var_without_annotation(self):
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return TestObj
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return GrandChildState
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@pytest.fixture
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def StateWithAnyVar(TestObj):
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class StateWithAnyVar(State):
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@ComputedVar
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def var_without_annotation(self) -> typing.Any:
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return TestObj
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return StateWithAnyVar
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@pytest.fixture
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def StateWithCorrectVarAnnotation():
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class StateWithCorrectVarAnnotation(State):
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@ComputedVar
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def var_with_annotation(self) -> str:
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return "Correct annotation"
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return StateWithCorrectVarAnnotation
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@pytest.fixture
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def StateWithWrongVarAnnotation(TestObj):
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class StateWithWrongVarAnnotation(State):
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@ComputedVar
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def var_with_annotation(self) -> str:
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return TestObj
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return StateWithWrongVarAnnotation
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@pytest.mark.parametrize(
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"prop,expected",
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zip(
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test_vars,
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[
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"prop1",
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"key",
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"state.value",
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"state.local",
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"local2",
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],
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),
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)
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def test_full_name(prop, expected):
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"""Test that the full name of a var is correct.
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Args:
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prop: The var to test.
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expected: The expected full name.
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"""
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assert prop.full_name == expected
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@pytest.mark.parametrize(
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"prop,expected",
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zip(
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test_vars,
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["{prop1}", "{key}", "{state.value}", "state.local", "local2"],
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),
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)
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def test_str(prop, expected):
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"""Test that the string representation of a var is correct.
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Args:
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prop: The var to test.
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expected: The expected string representation.
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"""
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assert str(prop) == expected
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@pytest.mark.parametrize(
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"prop,expected",
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[
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(BaseVar(name="p", type_=int), 0),
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(BaseVar(name="p", type_=float), 0.0),
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(BaseVar(name="p", type_=str), ""),
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(BaseVar(name="p", type_=bool), False),
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(BaseVar(name="p", type_=list), []),
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(BaseVar(name="p", type_=dict), {}),
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(BaseVar(name="p", type_=tuple), ()),
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(BaseVar(name="p", type_=set), set()),
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],
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)
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def test_default_value(prop, expected):
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"""Test that the default value of a var is correct.
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Args:
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prop: The var to test.
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expected: The expected default value.
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"""
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assert prop.get_default_value() == expected
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@pytest.mark.parametrize(
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"prop,expected",
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zip(
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test_vars,
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[
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"set_prop1",
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"set_key",
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"state.set_value",
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"state.set_local",
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"set_local2",
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],
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),
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)
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def test_get_setter(prop, expected):
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"""Test that the name of the setter function of a var is correct.
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Args:
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prop: The var to test.
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expected: The expected name of the setter function.
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"""
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assert prop.get_setter_name() == expected
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@pytest.mark.parametrize(
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"value,expected",
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[
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(None, None),
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(1, BaseVar(name="1", type_=int, is_local=True)),
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("key", BaseVar(name="key", type_=str, is_local=True)),
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(3.14, BaseVar(name="3.14", type_=float, is_local=True)),
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([1, 2, 3], BaseVar(name="[1, 2, 3]", type_=list, is_local=True)),
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(
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{"a": 1, "b": 2},
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BaseVar(name='{"a": 1, "b": 2}', type_=dict, is_local=True),
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),
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],
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)
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def test_create(value, expected):
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"""Test the var create function.
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Args:
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value: The value to create a var from.
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expected: The expected name of the setter function.
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"""
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prop = Var.create(value)
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if value is None:
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assert prop == expected
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else:
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assert prop.equals(expected) # type: ignore
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def test_create_type_error():
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"""Test the var create function when inputs type error."""
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class ErrorType:
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pass
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value = ErrorType()
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with pytest.raises(TypeError) as exception:
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Var.create(value)
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assert (
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exception.value.args[0]
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== f"To create a Var must be Var or JSON-serializable. Got {value} of type {type(value)}."
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)
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def v(value) -> Var:
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val = Var.create(value)
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assert val is not None
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return val
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def test_basic_operations(TestObj):
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"""Test the var operations.
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Args:
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TestObj: The test object.
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"""
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assert str(v(1) == v(2)) == "{(1 === 2)}"
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assert str(v(1) != v(2)) == "{(1 !== 2)}"
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assert str(v(1) < v(2)) == "{(1 < 2)}"
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assert str(v(1) <= v(2)) == "{(1 <= 2)}"
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assert str(v(1) > v(2)) == "{(1 > 2)}"
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assert str(v(1) >= v(2)) == "{(1 >= 2)}"
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assert str(v(1) + v(2)) == "{(1 + 2)}"
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assert str(v(1) - v(2)) == "{(1 - 2)}"
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assert str(v(1) * v(2)) == "{(1 * 2)}"
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assert str(v(1) / v(2)) == "{(1 / 2)}"
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assert str(v(1) // v(2)) == "{Math.floor(1 / 2)}"
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assert str(v(1) % v(2)) == "{(1 % 2)}"
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assert str(v(1) ** v(2)) == "{Math.pow(1 , 2)}"
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assert str(v(1) & v(2)) == "{(1 && 2)}"
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assert str(v(1) | v(2)) == "{(1 || 2)}"
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assert str(v([1, 2, 3])[v(0)]) == "{[1, 2, 3].at(0)}"
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assert str(v({"a": 1, "b": 2})["a"]) == '{{"a": 1, "b": 2}["a"]}'
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assert (
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str(BaseVar(name="foo", state="state", type_=TestObj).bar) == "{state.foo.bar}"
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)
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assert str(abs(v(1))) == "{Math.abs(1)}"
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assert str(v([1, 2, 3]).length()) == "{[1, 2, 3].length}"
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@pytest.mark.parametrize(
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"var",
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[
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BaseVar(name="list", type_=List[int]),
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BaseVar(name="tuple", type_=Tuple[int, int]),
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BaseVar(name="str", type_=str),
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],
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)
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def test_var_indexing_lists(var):
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"""Test that we can index into str, list or tuple vars.
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Args:
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var : The str, list or tuple base var.
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"""
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# Test basic indexing.
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assert str(var[0]) == f"{{{var.name}.at(0)}}"
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assert str(var[1]) == f"{{{var.name}.at(1)}}"
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# Test negative indexing.
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assert str(var[-1]) == f"{{{var.name}.at(-1)}}"
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@pytest.mark.parametrize(
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"var, index",
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[
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(BaseVar(name="lst", type_=List[int]), [1, 2]),
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(BaseVar(name="lst", type_=List[int]), {"name": "dict"}),
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(BaseVar(name="lst", type_=List[int]), {"set"}),
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(
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BaseVar(name="lst", type_=List[int]),
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(
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1,
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2,
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),
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),
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(BaseVar(name="lst", type_=List[int]), 1.5),
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(BaseVar(name="lst", type_=List[int]), "str"),
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(BaseVar(name="lst", type_=List[int]), BaseVar(name="string_var", type_=str)),
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(BaseVar(name="lst", type_=List[int]), BaseVar(name="float_var", type_=float)),
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(
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BaseVar(name="lst", type_=List[int]),
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BaseVar(name="list_var", type_=List[int]),
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),
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(BaseVar(name="lst", type_=List[int]), BaseVar(name="set_var", type_=Set[str])),
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(
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BaseVar(name="lst", type_=List[int]),
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BaseVar(name="dict_var", type_=Dict[str, str]),
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),
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(BaseVar(name="str", type_=str), [1, 2]),
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(BaseVar(name="lst", type_=str), {"name": "dict"}),
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(BaseVar(name="lst", type_=str), {"set"}),
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(BaseVar(name="lst", type_=str), BaseVar(name="string_var", type_=str)),
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(BaseVar(name="lst", type_=str), BaseVar(name="float_var", type_=float)),
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(BaseVar(name="str", type_=Tuple[str]), [1, 2]),
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(BaseVar(name="lst", type_=Tuple[str]), {"name": "dict"}),
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(BaseVar(name="lst", type_=Tuple[str]), {"set"}),
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(BaseVar(name="lst", type_=Tuple[str]), BaseVar(name="string_var", type_=str)),
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(BaseVar(name="lst", type_=Tuple[str]), BaseVar(name="float_var", type_=float)),
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],
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)
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def test_var_unsupported_indexing_lists(var, index):
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"""Test unsupported indexing throws a type error.
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Args:
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var: The base var.
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index: The base var index.
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"""
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with pytest.raises(TypeError):
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var[index]
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@pytest.mark.parametrize(
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"var",
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[
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BaseVar(name="lst", type_=List[int]),
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BaseVar(name="tuple", type_=Tuple[int, int]),
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BaseVar(name="str", type_=str),
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],
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)
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def test_var_list_slicing(var):
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"""Test that we can slice into str, list or tuple vars.
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Args:
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var : The str, list or tuple base var.
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"""
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assert str(var[:1]) == f"{{{var.name}.slice(0, 1)}}"
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assert str(var[:1]) == f"{{{var.name}.slice(0, 1)}}"
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assert str(var[:]) == f"{{{var.name}.slice(0, undefined)}}"
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def test_dict_indexing():
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"""Test that we can index into dict vars."""
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dct = BaseVar(name="dct", type_=Dict[str, int])
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# Check correct indexing.
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assert str(dct["a"]) == '{dct["a"]}'
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assert str(dct["asdf"]) == '{dct["asdf"]}'
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@pytest.mark.parametrize(
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"var, index",
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[
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(
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BaseVar(name="dict", type_=Dict[str, str]),
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[1, 2],
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),
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(
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BaseVar(name="dict", type_=Dict[str, str]),
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{"name": "dict"},
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),
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(
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BaseVar(name="dict", type_=Dict[str, str]),
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{"set"},
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),
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(
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BaseVar(name="dict", type_=Dict[str, str]),
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(
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1,
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2,
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),
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),
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(
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BaseVar(name="lst", type_=Dict[str, str]),
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BaseVar(name="list_var", type_=List[int]),
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),
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(
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BaseVar(name="lst", type_=Dict[str, str]),
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BaseVar(name="set_var", type_=Set[str]),
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),
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(
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BaseVar(name="lst", type_=Dict[str, str]),
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BaseVar(name="dict_var", type_=Dict[str, str]),
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),
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(
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BaseVar(name="df", type_=DataFrame),
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[1, 2],
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),
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(
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BaseVar(name="df", type_=DataFrame),
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{"name": "dict"},
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),
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(
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BaseVar(name="df", type_=DataFrame),
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{"set"},
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),
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(
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BaseVar(name="df", type_=DataFrame),
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(
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1,
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2,
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),
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),
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(
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BaseVar(name="df", type_=DataFrame),
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BaseVar(name="list_var", type_=List[int]),
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),
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(
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BaseVar(name="df", type_=DataFrame),
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BaseVar(name="set_var", type_=Set[str]),
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),
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(
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BaseVar(name="df", type_=DataFrame),
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BaseVar(name="dict_var", type_=Dict[str, str]),
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),
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],
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)
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def test_var_unsupported_indexing_dicts(var, index):
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"""Test unsupported indexing throws a type error.
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Args:
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var: The base var.
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index: The base var index.
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"""
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with pytest.raises(TypeError):
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var[index]
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@pytest.mark.parametrize(
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"fixture,full_name",
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[
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("ParentState", "parent_state.var_without_annotation"),
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("ChildState", "parent_state.child_state.var_without_annotation"),
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(
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"GrandChildState",
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"parent_state.child_state.grand_child_state.var_without_annotation",
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),
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("StateWithAnyVar", "state_with_any_var.var_without_annotation"),
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],
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)
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def test_computed_var_without_annotation_error(request, fixture, full_name):
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"""Test that a type error is thrown when an attribute of a computed var is
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accessed without annotating the computed var.
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Args:
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request: Fixture Request.
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fixture: The state fixture.
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full_name: The full name of the state var.
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"""
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with pytest.raises(TypeError) as err:
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state = request.getfixturevalue(fixture)
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state.var_without_annotation.foo
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assert (
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err.value.args[0]
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== f"You must provide an annotation for the state var `{full_name}`. Annotation cannot be `typing.Any`"
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)
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|
|
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@pytest.mark.parametrize(
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"fixture,full_name",
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[
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(
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"StateWithCorrectVarAnnotation",
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"state_with_correct_var_annotation.var_with_annotation",
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),
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(
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"StateWithWrongVarAnnotation",
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"state_with_wrong_var_annotation.var_with_annotation",
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),
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],
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)
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def test_computed_var_with_annotation_error(request, fixture, full_name):
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"""Test that an Attribute error is thrown when a non-existent attribute of an annotated computed var is
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accessed or when the wrong annotation is provided to a computed var.
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Args:
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request: Fixture Request.
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fixture: The state fixture.
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full_name: The full name of the state var.
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"""
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with pytest.raises(AttributeError) as err:
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state = request.getfixturevalue(fixture)
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state.var_with_annotation.foo
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assert (
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err.value.args[0]
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== f"The State var `{full_name}` has no attribute 'foo' or may have been annotated wrongly.\n"
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f"original message: 'ComputedVar' object has no attribute 'foo'"
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)
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def test_pickleable_rx_list():
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"""Test that ReflexList is pickleable."""
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rx_list = ReflexList(
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original_list=[1, 2, 3], reassign_field=lambda x: x, field_name="random"
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)
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pickled_list = cloudpickle.dumps(rx_list)
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assert cloudpickle.loads(pickled_list) == rx_list
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|
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def test_pickleable_rx_dict():
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"""Test that ReflexDict is pickleable."""
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rx_dict = ReflexDict(
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original_dict={1: 2, 3: 4}, reassign_field=lambda x: x, field_name="random"
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)
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pickled_dict = cloudpickle.dumps(rx_dict)
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assert cloudpickle.loads(pickled_dict) == rx_dict
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|
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def test_pickleable_rx_set():
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"""Test that ReflexSet is pickleable."""
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|
rx_set = ReflexSet(
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original_set={1, 2, 3}, reassign_field=lambda x: x, field_name="random"
|
|
)
|
|
|
|
pickled_set = cloudpickle.dumps(rx_set)
|
|
assert cloudpickle.loads(pickled_set) == rx_set
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"import_var,expected",
|
|
zip(
|
|
test_import_vars,
|
|
[
|
|
"DataGrid",
|
|
"DataGrid as Grid",
|
|
],
|
|
),
|
|
)
|
|
def test_import_var(import_var, expected):
|
|
"""Test that the import var name is computed correctly.
|
|
|
|
Args:
|
|
import_var: The import var.
|
|
expected: expected name
|
|
"""
|
|
assert import_var.name == expected
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"key, expected",
|
|
[
|
|
("test_key", BaseVar(name="localStorage.getItem('test_key')", type_=str)),
|
|
(
|
|
BaseVar(name="key_var", type_=str),
|
|
BaseVar(name="localStorage.getItem(key_var)", type_=str),
|
|
),
|
|
(
|
|
BaseState.val,
|
|
BaseVar(name="localStorage.getItem(base_state.val)", type_=str),
|
|
),
|
|
(None, BaseVar(name="getAllLocalStorageItems()", type_=Dict)),
|
|
],
|
|
)
|
|
def test_get_local_storage(key, expected):
|
|
"""Test that the right BaseVar is return when get_local_storage is called.
|
|
|
|
Args:
|
|
key: Local storage key.
|
|
expected: expected BaseVar.
|
|
|
|
"""
|
|
local_storage = get_local_storage(key)
|
|
assert local_storage.name == expected.name
|
|
assert local_storage.type_ == expected.type_
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"key",
|
|
[
|
|
["list", "values"],
|
|
{"name": "dict"},
|
|
10,
|
|
BaseVar(name="key_var", type_=List),
|
|
BaseVar(name="key_var", type_=Dict[str, str]),
|
|
],
|
|
)
|
|
def test_get_local_storage_raise_error(key):
|
|
"""Test that a type error is thrown when the wrong key type is provided.
|
|
|
|
Args:
|
|
key: Local storage key.
|
|
"""
|
|
with pytest.raises(TypeError) as err:
|
|
get_local_storage(key)
|
|
type_ = type(key) if not isinstance(key, Var) else key.type_
|
|
assert (
|
|
err.value.args[0]
|
|
== f"Local storage keys can only be of type `str` or `var` of type `str`. Got `{type_}` instead."
|
|
)
|