test_graph.py

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import inspect
import pathlib
import sys
import uuid
from itertools import permutations
from types import ModuleType

import pandas as pd
import pytest

import hamilton.graph_utils
import hamilton.htypes
from hamilton import ad_hoc_utils, base, graph, node
from hamilton import function_modifiers as fm
from hamilton.execution import graph_functions
from hamilton.function_modifiers import schema
from hamilton.lifecycle import base as lifecycle_base
from hamilton.node import NodeType

import tests.resources.bad_functions
import tests.resources.compatible_input_types
import tests.resources.config_modifier
import tests.resources.cyclic_functions
import tests.resources.display_name_functions
import tests.resources.display_name_list_functions
import tests.resources.dummy_functions
import tests.resources.dummy_functions_module_override
import tests.resources.extract_column_nodes
import tests.resources.extract_columns_execution_count
import tests.resources.functions_with_generics
import tests.resources.incompatible_input_types
import tests.resources.layered_decorators
import tests.resources.multiple_decorators_together
import tests.resources.optional_dependencies
import tests.resources.parametrized_inputs
import tests.resources.parametrized_nodes
import tests.resources.test_default_args
import tests.resources.typing_vs_not_typing


@pytest.mark.parametrize(
    ("child_name", "parent_name", "expected"),
    [
        ("foo", "foo", True),  # same module
        ("foo.bar", "foo", True),  # direct child
        ("foo.bar.baz", "foo", True),  # nested child
        ("foo.bar.baz", "foo.bar", True),  # nested child of subpackage
        ("foobar", "foo", False),  # not a submodule, just a prefix without dot separator
        ("hamilton.function_modifiers", "modifiers", False),  # substring match, not a submodule
        ("hamilton.function_modifiers.dependencies", "modifiers", False),  # substring deeper
        ("x.foo.y", "foo", False),  # parent name in the middle, not a prefix
        ("bar", "foo", False),  # completely unrelated
    ],
    ids=[
        "same_module",
        "direct_child",
        "nested_child",
        "nested_child_of_subpackage",
        "prefix_without_dot",
        "substring_not_submodule",
        "substring_deeper",
        "parent_in_middle",
        "unrelated",
    ],
)
def test_is_submodule(child_name, parent_name, expected):
    """Tests that is_submodule correctly checks module hierarchy using prefix matching."""
    child = ModuleType(child_name)
    parent = ModuleType(parent_name)
    assert hamilton.graph_utils.is_submodule(child, parent) == expected


def test_find_functions():
    """Tests that we filter out _ functions when passed a module and don't pull in anything from the imports."""
    expected = [
        ("A", tests.resources.dummy_functions.A),
        ("B", tests.resources.dummy_functions.B),
        ("C", tests.resources.dummy_functions.C),
    ]
    actual = hamilton.graph_utils.find_functions(tests.resources.dummy_functions)
    assert len(actual) == len(expected)
    assert actual == expected


def test_find_functions_excludes_imports_with_substring_module_name():
    """Regression test: imported functions should not be included when the user module's
    name is a substring of the imported function's module path.

    Previously, is_submodule used `parent.__name__ in child.__name__` (substring match),
    which caused e.g. a module named 'modifiers' to pull in functions from
    'hamilton.function_modifiers'.
    """
    # Create a fake module named "modifiers" with one real function and two imports
    mod = ModuleType("modifiers")

    def my_func(x: int) -> int:
        return x * 2

    # Assign the function to the module so inspect.getmodule can resolve it
    my_func.__module__ = "modifiers"
    mod.my_func = my_func
    mod.source = fm.source
    mod.value = fm.value

    # Register in sys.modules so inspect.getmodule can find it
    sys.modules["modifiers"] = mod
    try:
        actual = hamilton.graph_utils.find_functions(mod)
        actual_names = [name for name, _ in actual]
        assert actual_names == ["my_func"], (
            f"Expected only ['my_func'] but got {actual_names}. "
            "Imported functions from hamilton.function_modifiers should not be included."
        )
    finally:
        del sys.modules["modifiers"]


def test_find_functions_from_temporary_function_module():
    """Tests that we handle the TemporaryFunctionModule object correctly."""
    expected = [
        ("A", tests.resources.dummy_functions.A),
        ("B", tests.resources.dummy_functions.B),
        ("C", tests.resources.dummy_functions.C),
    ]
    func_module = ad_hoc_utils.create_temporary_module(
        tests.resources.dummy_functions.A,
        tests.resources.dummy_functions.B,
        tests.resources.dummy_functions.C,
    )
    actual = hamilton.graph_utils.find_functions(func_module)
    assert len(actual) == len(expected)
    assert [node_name for node_name, _ in actual] == [node_name for node_name, _ in expected]
    assert [fn.__code__ for _, fn in actual] == [
        fn.__code__ for _, fn in expected
    ]  # easy way to say they're the same


def test_add_dependency_missing_param_type():
    """Tests case that we error if types are missing from a parameter."""
    with pytest.raises(ValueError):
        a_sig = inspect.signature(tests.resources.bad_functions.A)
        node.Node(
            "A", a_sig.return_annotation, "A doc", tests.resources.bad_functions.A
        )  # should error out


def test_add_dependency_missing_function_type():
    """Tests case that we error if types are missing from a function."""
    with pytest.raises(ValueError):
        b_sig = inspect.signature(tests.resources.bad_functions.B)
        node.Node(
            "B", b_sig.return_annotation, "B doc", tests.resources.bad_functions.B
        )  # should error out


def test_add_dependency_strict_node_dependencies():
    """Tests that we add node dependencies between functions correctly.

    Setup here is: B depends on A. So A is depended on by B. B is not depended on by anyone.
    """
    b_sig = inspect.signature(tests.resources.dummy_functions.B)
    func_node = node.Node("B", b_sig.return_annotation, "B doc", tests.resources.dummy_functions.B)
    func_name = "B"
    nodes = {
        "A": node.Node(
            "A",
            inspect.signature(tests.resources.dummy_functions.A).return_annotation,
            "A doc",
            tests.resources.dummy_functions.A,
        )
    }
    param_name = "A"
    param_type = b_sig.parameters["A"].annotation

    graph.add_dependency(
        func_node,
        func_name,
        nodes,
        param_name,
        param_type,
        lifecycle_base.LifecycleAdapterSet(),
    )
    assert nodes["A"] == func_node.dependencies[0]
    assert func_node.depended_on_by == []


def test_add_dependency_input_nodes_mismatch_on_types():
    """Tests that if two functions request an input that has incompatible types, we error out."""
    b_sig = inspect.signature(tests.resources.incompatible_input_types.b)
    c_sig = inspect.signature(tests.resources.incompatible_input_types.c)

    nodes = {
        "b": node.Node.from_fn(tests.resources.incompatible_input_types.b),
        "c": node.Node.from_fn(tests.resources.incompatible_input_types.c),
    }
    nodes["b"]._originating_functions = (tests.resources.incompatible_input_types.b,)
    nodes["c"]._originating_functions = (tests.resources.incompatible_input_types.c,)
    param_name = "a"

    # this adds 'a' to nodes
    graph.add_dependency(
        nodes["b"],
        "b",
        nodes,
        param_name,
        b_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )

    assert "a" in nodes

    # adding dependency of c on a should fail because the types are incompatible
    with pytest.raises(ValueError):
        graph.add_dependency(
            nodes["c"],
            "c",
            nodes,
            param_name,
            c_sig.parameters[param_name].annotation,
            lifecycle_base.LifecycleAdapterSet(),
        )


def test_add_dependency_input_nodes_mismatch_on_types_complex():
    """Tests a more complex scenario we don't support right now with input types."""
    e_sig = inspect.signature(tests.resources.incompatible_input_types.e)
    f_sig = inspect.signature(tests.resources.incompatible_input_types.f)

    nodes = {
        "e": node.Node.from_fn(tests.resources.incompatible_input_types.e),
        "f": node.Node.from_fn(tests.resources.incompatible_input_types.f),
    }
    nodes["e"]._originating_functions = (tests.resources.incompatible_input_types.e,)
    nodes["f"]._originating_functions = (tests.resources.incompatible_input_types.f,)
    param_name = "d"

    # this adds 'a' to nodes
    graph.add_dependency(
        nodes["e"],
        "e",
        nodes,
        param_name,
        e_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )

    assert "d" in nodes

    # adding dependency of c on a should fail because the types are incompatible
    with pytest.raises(ValueError):
        graph.add_dependency(
            nodes["e"],
            "e",
            nodes,
            param_name,
            f_sig.parameters[param_name].annotation,
            lifecycle_base.LifecycleAdapterSet(),
        )


def test_add_dependency_input_nodes_compatible_types():
    """Tests that if functions request an input that we correctly accept compatible types."""
    b_sig = inspect.signature(tests.resources.compatible_input_types.b)
    c_sig = inspect.signature(tests.resources.compatible_input_types.c)
    d_sig = inspect.signature(tests.resources.compatible_input_types.d)

    nodes = {
        "b": node.Node.from_fn(tests.resources.compatible_input_types.b),
        "c": node.Node.from_fn(tests.resources.compatible_input_types.c),
        "d": node.Node.from_fn(tests.resources.compatible_input_types.d),
    }
    nodes["b"]._originating_functions = (tests.resources.compatible_input_types.b,)
    nodes["c"]._originating_functions = (tests.resources.compatible_input_types.c,)
    nodes["d"]._originating_functions = (tests.resources.compatible_input_types.d,)
    # what we want to add
    param_name = "a"

    # this adds 'a' to nodes
    graph.add_dependency(
        nodes["b"],
        "b",
        nodes,
        param_name,
        b_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )

    assert "a" in nodes

    # this adds 'a' to 'c' as well.
    graph.add_dependency(
        nodes["c"],
        "c",
        nodes,
        param_name,
        c_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )

    # test that we shrink the type to the tighter type
    assert nodes["a"].type == str

    graph.add_dependency(
        nodes["d"],
        "d",
        nodes,
        param_name,
        d_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )


def test_add_dependency_input_nodes_compatible_types_order_check():
    """Tests that if functions request an input that we correctly accept compatible types independent of order.

    This just reorders test_add_dependency_input_nodes_compatible_types to ensure the outcome does not change.
    """
    b_sig = inspect.signature(tests.resources.compatible_input_types.b)
    c_sig = inspect.signature(tests.resources.compatible_input_types.c)
    d_sig = inspect.signature(tests.resources.compatible_input_types.d)

    nodes = {
        "b": node.Node.from_fn(tests.resources.compatible_input_types.b),
        "c": node.Node.from_fn(tests.resources.compatible_input_types.c),
        "d": node.Node.from_fn(tests.resources.compatible_input_types.d),
    }
    nodes["b"]._originating_functions = (tests.resources.compatible_input_types.b,)
    nodes["c"]._originating_functions = (tests.resources.compatible_input_types.c,)
    nodes["d"]._originating_functions = (tests.resources.compatible_input_types.d,)
    # what we want to add
    param_name = "a"

    # this adds 'a' to nodes
    graph.add_dependency(
        nodes["c"],
        "c",
        nodes,
        param_name,
        c_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )

    assert "a" in nodes
    assert nodes["a"].type == str

    # this adds 'a' to 'c' as well.
    graph.add_dependency(
        nodes["b"],
        "b",
        nodes,
        param_name,
        b_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )

    # test that type didn't change
    assert nodes["a"].type == str

    graph.add_dependency(
        nodes["d"],
        "d",
        nodes,
        param_name,
        d_sig.parameters[param_name].annotation,
        lifecycle_base.LifecycleAdapterSet(),
    )


def test_typing_to_primitive_conversion():
    """Tests that we can mix function output being typing type, and dependent function using primitive type."""
    b_sig = inspect.signature(tests.resources.typing_vs_not_typing.B)
    func_node = node.Node(
        "B", b_sig.return_annotation, "B doc", tests.resources.typing_vs_not_typing.B
    )
    func_name = "B"
    nodes = {
        "A": node.Node(
            "A",
            inspect.signature(tests.resources.typing_vs_not_typing.A).return_annotation,
            "A doc",
            tests.resources.typing_vs_not_typing.A,
        )
    }
    param_name = "A"
    param_type = b_sig.parameters["A"].annotation

    graph.add_dependency(
        func_node,
        func_name,
        nodes,
        param_name,
        param_type,
        lifecycle_base.LifecycleAdapterSet(),
    )
    assert nodes["A"] == func_node.dependencies[0]
    assert func_node.depended_on_by == []


def test_primitive_to_typing_conversion():
    """Tests that we can mix function output being a primitive type, and dependent function using typing type."""
    b_sig = inspect.signature(tests.resources.typing_vs_not_typing.B2)
    func_node = node.Node(
        "B2", b_sig.return_annotation, "B2 doc", tests.resources.typing_vs_not_typing.B2
    )
    func_name = "B2"
    nodes = {
        "A2": node.Node(
            "A2",
            inspect.signature(tests.resources.typing_vs_not_typing.A2).return_annotation,
            "A2 doc",
            tests.resources.typing_vs_not_typing.A2,
        )
    }
    param_name = "A2"
    param_type = b_sig.parameters["A2"].annotation

    graph.add_dependency(
        func_node,
        func_name,
        nodes,
        param_name,
        param_type,
        lifecycle_base.LifecycleAdapterSet(),
    )
    assert nodes["A2"] == func_node.dependencies[0]
    assert func_node.depended_on_by == []


def test_throwing_error_on_incompatible_types():
    """Tests we error on incompatible types."""
    d_sig = inspect.signature(tests.resources.bad_functions.D)
    func_node = node.Node("D", d_sig.return_annotation, "D doc", tests.resources.bad_functions.D)
    func_name = "D"
    nodes = {
        "C": node.Node(
            "C",
            inspect.signature(tests.resources.bad_functions.C).return_annotation,
            "C doc",
            tests.resources.bad_functions.C,
        )
    }
    param_name = "C"
    param_type = d_sig.parameters["C"].annotation
    with pytest.raises(ValueError):
        graph.add_dependency(
            func_node,
            func_name,
            nodes,
            param_name,
            param_type,
            lifecycle_base.LifecycleAdapterSet(),
        )


def test_add_dependency_user_nodes():
    """Tests that we add node user defined dependencies correctly.

    Setup here is: A depends on b and c. But we're only doing one call. So expecting A having 'b' as a dependency,
    and 'b' is depended on by A.
    """
    a_sig = inspect.signature(tests.resources.dummy_functions.A)
    func_node = node.Node("A", a_sig.return_annotation, "A doc", tests.resources.dummy_functions.A)
    func_name = "A"
    nodes = {}
    param_name = "b"
    param_type = a_sig.parameters["b"].annotation

    graph.add_dependency(
        func_node,
        func_name,
        nodes,
        param_name,
        param_type,
        lifecycle_base.LifecycleAdapterSet(),
    )
    # user node is created and added to nodes.
    assert nodes["b"] == func_node.dependencies[0]
    assert nodes["b"].depended_on_by[0] == func_node
    assert func_node.depended_on_by == []


def create_testing_nodes():
    """Helper function for creating the nodes represented in dummy_functions.py."""
    nodes = {
        "A": node.Node.from_fn(fn=tests.resources.dummy_functions.A, name="A"),
        "B": node.Node.from_fn(fn=tests.resources.dummy_functions.B, name="B"),
        "C": node.Node.from_fn(fn=tests.resources.dummy_functions.C, name="C"),
        "b": node.Node(
            "b",
            inspect.signature(tests.resources.dummy_functions.A).parameters["b"].annotation,
            node_source=NodeType.EXTERNAL,
        ),
        "c": node.Node(
            "c",
            inspect.signature(tests.resources.dummy_functions.A).parameters["c"].annotation,
            node_source=NodeType.EXTERNAL,
        ),
    }
    nodes["A"].dependencies.append(nodes["b"])
    nodes["A"].dependencies.append(nodes["c"])
    nodes["A"].depended_on_by.append(nodes["B"])
    nodes["A"].depended_on_by.append(nodes["C"])
    nodes["b"].depended_on_by.append(nodes["A"])
    nodes["c"].depended_on_by.append(nodes["A"])
    nodes["B"].dependencies.append(nodes["A"])
    nodes["C"].dependencies.append(nodes["A"])
    return nodes


def create_testing_nodes_override_B():
    """Helper function for creating the nodes represented in dummy_functions.py
    with node B overridden by dummy_functions_module_override.py."""
    nodes = {
        "A": node.Node.from_fn(fn=tests.resources.dummy_functions.A, name="A"),
        "B": node.Node.from_fn(fn=tests.resources.dummy_functions_module_override.B, name="B"),
        "C": node.Node.from_fn(fn=tests.resources.dummy_functions.C, name="C"),
        "b": node.Node(
            "b",
            inspect.signature(tests.resources.dummy_functions.A).parameters["b"].annotation,
            node_source=NodeType.EXTERNAL,
        ),
        "c": node.Node(
            "c",
            inspect.signature(tests.resources.dummy_functions.A).parameters["c"].annotation,
            node_source=NodeType.EXTERNAL,
        ),
    }
    nodes["A"].dependencies.append(nodes["b"])
    nodes["A"].dependencies.append(nodes["c"])
    nodes["A"].depended_on_by.append(nodes["B"])
    nodes["A"].depended_on_by.append(nodes["C"])
    nodes["b"].depended_on_by.append(nodes["A"])
    nodes["c"].depended_on_by.append(nodes["A"])
    nodes["B"].dependencies.append(nodes["A"])
    nodes["C"].dependencies.append(nodes["A"])
    return nodes


def test_create_function_graph_simple():
    """Tests that we create a simple function graph."""
    expected = create_testing_nodes()
    actual = graph.create_function_graph(tests.resources.dummy_functions, config={})
    assert actual == expected


def test_create_function_graph_with_override():
    """Tests that we can override nodes from later modules in function graph."""
    override_expected = create_testing_nodes_override_B()
    override_actual = graph.create_function_graph(
        tests.resources.dummy_functions,
        tests.resources.dummy_functions_module_override,
        config={},
        allow_module_overrides=True,
    )
    assert override_expected == override_actual


def test_execute():
    """Tests graph execution along with basic memoization since A is depended on by two functions."""
    nodes = create_testing_nodes()
    inputs = {"b": 2, "c": 5}
    expected = {"A": 7, "B": 49, "C": 14, "b": 2, "c": 5}
    actual = graph_functions.execute_subdag(nodes=nodes.values(), inputs=inputs)
    assert actual == expected
    actual = graph_functions.execute_subdag(nodes=nodes.values(), inputs=inputs, overrides={"A": 8})
    assert actual["A"] == 8


def test_get_required_functions():
    """Exercises getting the subset of the graph for computation on the toy example we have constructed."""
    nodes = create_testing_nodes()
    final_vars = ["A", "B"]
    expected_user_nodes = {nodes["b"], nodes["c"]}
    expected_nodes = {nodes["A"], nodes["B"], nodes["b"], nodes["c"]}  # we skip 'C'
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config={})
    actual_nodes, actual_ud_nodes = fg.get_upstream_nodes(final_vars)
    assert actual_nodes == expected_nodes
    assert actual_ud_nodes == expected_user_nodes


def test_get_downstream_nodes():
    """Exercises getting the downstream subset of the graph for computation on the toy example we have constructed."""
    nodes = create_testing_nodes()
    var_changes = ["A"]
    expected_nodes = {nodes["B"], nodes["C"], nodes["A"]}
    # expected_nodes = {nodes['A'], nodes['B'], nodes['b'], nodes['c']}  # we skip 'C'
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config={})
    actual_nodes = fg.get_downstream_nodes(var_changes)
    assert actual_nodes == expected_nodes


def test_get_upstream_nodes_large_chain_no_recursion_error():
    """Regression test: get_upstream_nodes with only final_node on a large chain DAG.

    A recursive DFS would exceed Python's recursion limit (~1000) when traversing
    a long dependency chain from a single final node. This test verifies that
    the iterative DFS in directional_dfs_traverse handles large DAGs correctly.

    Chain size is chosen to exceed recursion limit: 1200 nodes > 1000.
    """

    def step(prev: float) -> float:
        """Single step in a linear chain."""
        return prev + 1.0

    # Build a linear chain: node_0 -> node_1 -> ... -> node_N
    chain_size = sys.getrecursionlimit() + 200  # Exceeds recursion limit
    config = {}
    for i in range(chain_size):
        prev = f"node_{i - 1}" if i > 0 else 0.0
        config[f"node_{i}"] = {
            "prev": fm.source(prev) if i > 0 else fm.value(0.0),
        }
    decorated = fm.parameterize(**config)(step)
    module = ad_hoc_utils.create_temporary_module(decorated, module_name="large_chain")

    fg = graph.FunctionGraph.from_modules(module, config={})
    final_node = f"node_{chain_size - 1}"

    # This would raise RecursionError with recursive DFS
    nodes, user_nodes = fg.get_upstream_nodes([final_node])

    assert len(nodes) == chain_size
    assert len(user_nodes) == 0
    assert all(fg.nodes[f"node_{i}"] in nodes for i in range(chain_size))


def test_get_upstream_nodes_diamond_dag():
    """Tests that diamond-shaped DAGs don't produce duplicate visits.

    DAG shape:
        x, y (inputs)
          |
        left   right    (both depend on x and y)
           \\   /
           bottom        (depends on left and right)

    The shared inputs x and y are reachable via both left and right.
    With a naive iterative DFS (mark-on-pop), x and y could be pushed
    onto the stack multiple times. This verifies they appear exactly once.
    """

    def left(x: int, y: int) -> int:
        return x + y

    def right(x: int, y: int) -> int:
        return x * y

    def bottom(left: int, right: int) -> int:
        return left + right

    module = ad_hoc_utils.create_temporary_module(left, right, bottom)
    fg = graph.FunctionGraph.from_modules(module, config={})
    nodes, user_nodes = fg.get_upstream_nodes(["bottom"])

    assert len(nodes) == 5  # x, y, left, right, bottom
    assert {n.name for n in nodes} == {"x", "y", "left", "right", "bottom"}
    # x and y are external inputs
    assert {n.name for n in user_nodes} == {"x", "y"}


def test_get_upstream_nodes_single_node():
    """Tests traversal of a single node with no dependencies."""

    def solo() -> int:
        return 42

    module = ad_hoc_utils.create_temporary_module(solo)
    fg = graph.FunctionGraph.from_modules(module, config={})
    nodes, user_nodes = fg.get_upstream_nodes(["solo"])

    assert len(nodes) == 1
    assert {n.name for n in nodes} == {"solo"}
    assert len(user_nodes) == 0


def test_get_upstream_nodes_overlapping_starting_nodes():
    """Tests that overlapping subgraphs from multiple starting nodes are handled correctly.

    DAG shape:
        shared (input)
          / \\
        a     b    (both depend on shared)

    Requesting both a and b as starting nodes means 'shared' is reachable
    from both traversals. It should still appear exactly once in the result.
    """

    def a(shared: int) -> int:
        return shared + 1

    def b(shared: int) -> int:
        return shared + 2

    module = ad_hoc_utils.create_temporary_module(a, b)
    fg = graph.FunctionGraph.from_modules(module, config={})
    nodes, user_nodes = fg.get_upstream_nodes(["a", "b"])

    assert len(nodes) == 3  # shared, a, b
    assert {n.name for n in nodes} == {"shared", "a", "b"}
    assert {n.name for n in user_nodes} == {"shared"}


def test_function_graph_from_multiple_sources():
    fg = graph.FunctionGraph.from_modules(
        tests.resources.dummy_functions, tests.resources.parametrized_nodes, config={}
    )
    assert len(fg.get_nodes()) == 8  # we take the union of all of them, and want to test that


def test_end_to_end_with_parametrized_nodes():
    """Tests that a simple function graph with parametrized nodes works end-to-end"""
    fg = graph.FunctionGraph.from_modules(tests.resources.parametrized_nodes, config={})
    results = fg.execute(fg.get_nodes(), {})
    assert results == {"parametrized_1": 1, "parametrized_2": 2, "parametrized_3": 3}


def test_end_to_end_with_parametrized_inputs():
    fg = graph.FunctionGraph.from_modules(
        tests.resources.parametrized_inputs, config={"static_value": 3}
    )
    results = fg.execute(fg.get_nodes())
    assert results == {
        "input_1": 1,
        "input_2": 2,
        "input_3": 3,
        "output_1": 1 + 3,
        "output_2": 2 + 3,
        "output_12": 1 + 2 + 3,
        "output_123": 1 + 2 + 3 + 3,
        "static_value": 3,
    }


def test_get_required_functions_askfor_config():
    """Tests that a simple function graph with parametrized nodes works end-to-end"""
    fg = graph.FunctionGraph.from_modules(tests.resources.parametrized_nodes, config={"a": 1})
    nodes, user_nodes = fg.get_upstream_nodes(["a", "parametrized_1"])
    (n,) = user_nodes
    assert n.name == "a"
    results = fg.execute(user_nodes)
    assert results == {"a": 1}


def test_end_to_end_with_column_extractor_nodes():
    """Tests that a simple function graph with nodes that extract columns works end-to-end"""
    fg = graph.FunctionGraph.from_modules(tests.resources.extract_column_nodes, config={})
    nodes = fg.get_nodes()
    results = fg.execute(nodes, {}, {})
    df_expected = tests.resources.extract_column_nodes.generate_df()
    pd.testing.assert_series_equal(results["col_1"], df_expected["col_1"])
    pd.testing.assert_series_equal(results["col_2"], df_expected["col_2"])
    pd.testing.assert_frame_equal(results["generate_df"], df_expected)
    assert (
        nodes[0].documentation == "Function that should be parametrized to form multiple functions"
    )


def test_end_to_end_with_multiple_decorators():
    """Tests that a simple function graph with multiple decorators on a function works end-to-end"""
    fg = graph.FunctionGraph.from_modules(
        tests.resources.multiple_decorators_together,
        config={"param0": 3, "param1": 1, "in_value1": 42, "in_value2": "string_value"},
    )
    nodes = fg.get_nodes()
    # To help debug issues:
    # nodez, user_nodes = fg.get_upstream_nodes([n.name for n in nodes],
    #                                           {"param0": 3, "param1": 1,
    #                                            "in_value1": 42, "in_value2": "string_value"})
    # fg.display(
    #     nodez,
    #     user_nodes,
    #     "all_multiple_decorators",
    #     render_kwargs=None,
    #     graphviz_kwargs=None,
    # )
    results = fg.execute(nodes, {}, {})
    df_expected = tests.resources.multiple_decorators_together._sum_multiply(3, 1, 2)
    dict_expected = tests.resources.multiple_decorators_together._sum(3, 1, 2)
    pd.testing.assert_series_equal(results["param1b"], df_expected["param1b"])
    pd.testing.assert_frame_equal(results["to_modify"], df_expected)
    assert results["total"] == dict_expected["total"]
    assert results["to_modify_2"] == dict_expected
    node_dict = {n.name: n for n in nodes}
    print(sorted(list(node_dict.keys())))
    assert (
        node_dict["to_modify"].documentation
        == "This is a dummy function showing extract_columns with does."
    )
    assert (
        node_dict["to_modify_2"].documentation
        == "This is a dummy function showing extract_fields with does."
    )
    # tag only applies right now to outer most node layer
    assert node_dict["uber_decorated_function"].tags == {
        "module": "tests.resources.multiple_decorators_together"
    }  # tags are not propagated
    assert node_dict["out_value1"].tags == {
        "module": "tests.resources.multiple_decorators_together",
        "test_key": "test-value",
    }
    assert node_dict["out_value2"].tags == {
        "module": "tests.resources.multiple_decorators_together",
        "test_key": "test-value",
    }


def test_end_to_end_with_config_modifier():
    config = {
        "fn_1_version": 1,
    }
    fg = graph.FunctionGraph.from_modules(tests.resources.config_modifier, config=config)
    results = fg.execute(fg.get_nodes(), {}, {})
    assert results["fn"] == "version_1"

    config = {
        "fn_1_version": 2,
    }
    fg = graph.FunctionGraph.from_modules(tests.resources.config_modifier, config=config)
    results = fg.execute(fg.get_nodes(), {}, {})
    assert results["fn"] == "version_2"
    config = {
        "fn_1_version": 3,
    }
    fg = graph.FunctionGraph.from_modules(tests.resources.config_modifier, config=config)
    results = fg.execute(fg.get_nodes(), {}, {})
    assert results["fn"] == "version_3"


def test_non_required_nodes():
    fg = graph.FunctionGraph.from_modules(
        tests.resources.test_default_args, config={"required": 10}
    )
    results = fg.execute(
        # D is not on the execution path, so it should not break things
        [n for n in fg.get_nodes() if n.node_role == NodeType.STANDARD and n.name != "D"],
        {},
        {},
    )
    assert results["A"] == 10
    fg = graph.FunctionGraph.from_modules(
        tests.resources.test_default_args, config={"required": 10, "defaults_to_zero": 1}
    )
    results = fg.execute(
        [n for n in fg.get_nodes() if n.node_role == NodeType.STANDARD],
        {},
        {},
    )
    assert results["A"] == 11
    assert results["D"] == 2


def test_config_can_override():
    config = {"new_param": "new_value"}
    fg = graph.FunctionGraph.from_modules(tests.resources.config_modifier, config=config)
    out = fg.execute([n for n in fg.get_nodes()])
    assert out["new_param"] == "new_value"


def test_function_graph_has_cycles_true():
    """Tests whether we catch a graph with cycles -- and expected behaviors"""
    fg = graph.FunctionGraph.from_modules(tests.resources.cyclic_functions, config={"b": 2, "c": 1})
    all_nodes = fg.get_nodes()
    nodes = [n for n in all_nodes if not n.user_defined]
    user_nodes = [n for n in all_nodes if n.user_defined]
    assert fg.has_cycles(nodes, user_nodes) is True
    required_nodes, required_user_nodes = fg.get_upstream_nodes(["A", "B", "C"])
    assert required_nodes == set(nodes + user_nodes)
    assert required_user_nodes == set(user_nodes)
    # We don't want to support this behavior officially -- but this works:
    # result = fg.execute([n for n in nodes if n.name == 'B'], overrides={'A': 1, 'D': 2})
    # assert len(result) == 3
    # assert result['B'] == 3
    with pytest.raises(
        RecursionError
    ):  # throw recursion error when we don't have a way to short circuit
        fg.execute([n for n in nodes if n.name == "B"])


def test_function_graph_has_cycles_false():
    """Tests whether we catch a graph with cycles"""
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config={"b": 1, "c": 2})
    all_nodes = fg.get_nodes()
    # checks it two ways
    nodes = [n for n in all_nodes if not n.user_defined]
    user_nodes = [n for n in all_nodes if n.user_defined]
    assert fg.has_cycles(nodes, user_nodes) is False
    # this is called by the driver
    nodes, user_nodes = fg.get_upstream_nodes(["A", "B", "C"])
    assert fg.has_cycles(nodes, user_nodes) is False


def test_function_graph_display_content(tmp_path: pathlib.Path):
    """Tests that display saves a file"""
    dot_file_path = tmp_path / "dag"
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)
    node_modifiers = {"B": {graph.VisualizationNodeModifiers.IS_OUTPUT}}
    all_nodes = set()
    for n in fg.get_nodes():
        if n.user_defined:
            node_modifiers[n.name] = {graph.VisualizationNodeModifiers.IS_USER_INPUT}
        all_nodes.add(n)
    # hack of a test -- but it works... sort the lines and match them up.
    # why? because for some reason given the same graph, the output file isn't deterministic.
    # for the same reason, order of input nodes are non-deterministic
    expected_set = set(
        [
            '\t\tfunction [fillcolor="#b4d8e4" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]\n',
            '\t\tgraph [fillcolor="#ffffff" fontname=helvetica label=Legend rank=same]\n',
            '\t\tinput [fontname=Helvetica margin=0.15 shape=rectangle style="filled,dashed"]\n',
            '\t\toutput [fillcolor="#FFC857" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]\n',
            "\tA -> B\n",
            "\tA -> C\n",
            '\tA [label=<<b>A</b><br /><br /><i>int</i>> fillcolor="#b4d8e4" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]\n',
            '\tB [label=<<b>B</b><br /><br /><i>int</i>> fillcolor="#FFC857" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]\n',
            '\tC [label=<<b>C</b><br /><br /><i>int</i>> fillcolor="#b4d8e4" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]\n',
            "\tb [label=<<b>b</b><br /><br /><i>1</i>> fontname=Helvetica shape=note style=filled]\n",
            "\tc [label=<<b>c</b><br /><br /><i>2</i>> fontname=Helvetica shape=note style=filled]\n",
            "\t_A_inputs -> A\n",
            # commenting out input node: '\t_A_inputs [label=<<table border="0"><tr><td>c</td><td>int</td></tr><tr><td>b</td><td>int</td></tr></table>> fontname=Helvetica margin=0.15 shape=rectangle style=dashed]\n',
            "\tgraph [compound=true concentrate=true rankdir=LR ranksep=0.4 style=filled]\n",
            '\tnode [fillcolor="#ffffff"]\n',
            "\tsubgraph cluster__legend {\n",
            "\t}\n",
            "// Dependency Graph\n",
            "digraph {\n",
            "}\n",
        ]
    )

    fg.display(
        all_nodes,
        output_file_path=str(dot_file_path),
        node_modifiers=node_modifiers,
        config=config,
        keep_dot=True,
    )
    dot_file = dot_file_path.open("r").readlines()
    dot_set = set(dot_file)

    assert dot_set.issuperset(expected_set) and len(dot_set.difference(expected_set)) == 1


@pytest.mark.parametrize(
    ("filename", "keep_dot"), [("dag", False), ("dag.png", False), ("dag", True), ("dag.png", True)]
)
def test_function_graph_display_output_filename(
    tmp_path: pathlib.Path, filename: str, keep_dot: bool
):
    """Handle file generation with `graph.Digraph` `.render()` and `.pipe()`"""
    output_file_path = f"{tmp_path}/{filename}"
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    fg.display(
        set(fg.get_nodes()),
        output_file_path=output_file_path,
        config=config,
        keep_dot=keep_dot,
    )
    assert pathlib.Path(tmp_path, "dag.png").exists()
    assert pathlib.Path(tmp_path, "dag").exists() == keep_dot


def test_function_graph_display_no_dot_output(tmp_path: pathlib.Path):
    dot_file_path = tmp_path / "dag"
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    fg.display(set(fg.get_nodes()), output_file_path=None, config=config)

    assert not dot_file_path.exists()


def test_function_graph_display_custom_style_node():
    def _styling_function(*, node, node_class):
        return dict(fill_color="aquamarine"), None, "legend_key"

    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    digraph = fg.display(
        set(fg.get_nodes()),
        custom_style_function=_styling_function,
        config=config,
    )

    key_found = False
    for line in digraph.body:  # list of lines of a dot file
        if ("A" in line) and ("aquamarine" in line):
            key_found = True
            break

    assert key_found


def test_function_graph_display_custom_style_legend():
    def _styling_function(*, node, node_class):
        return dict(fill_color="aquamarine"), None, "legend_key"

    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    digraph = fg.display(
        set(fg.get_nodes()),
        custom_style_function=_styling_function,
        config=config,
    )

    key_found = False
    for line in digraph.body:  # list of lines of a dot file
        if ("legend_key" in line) and ("aquamarine" in line):
            key_found = True
            break

    assert key_found


def test_function_graph_display_custom_style_tag():
    def _styling_function(*, node, node_class):
        if node.tags.get("some_key"):
            style = dict(fill_color="aquamarine"), None, "legend_key"
        else:
            style = dict(), None, None
        return style

    nodes = create_testing_nodes()
    nodes["A"].tags["some_key"] = "some_value"
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph(nodes, config=config)

    digraph = fg.display(
        set(fg.get_nodes()),
        custom_style_function=_styling_function,
        config=config,
    )

    # check that style is only applied to tagged nodes
    tag_found = False
    not_tag_found = False
    for line in digraph.body:  # list of lines of a dot file
        if ("A" in line) and ("aquamarine" in line):
            tag_found = True
        elif ("B" in line) and ("aquamarine" not in line):
            not_tag_found = True

    assert tag_found and not_tag_found


@pytest.mark.parametrize("show_legend", [(True), (False)])
def test_function_graph_display_legend(show_legend: bool):
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    dot = fg.display(
        set(fg.get_nodes()),
        show_legend=show_legend,
        config=config,
    )

    found_legend = "cluster__legend" in dot.source
    assert found_legend is show_legend


@pytest.mark.parametrize("orient", [("LR"), ("TB"), ("RL"), ("BT")])
def test_function_graph_display_orient(orient: str):
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    dot = fg.display(
        set(fg.get_nodes()),
        orient=orient,
        config=config,
    )

    # this could break if a rankdir is given to the legend subgraph
    assert f"rankdir={orient}" in dot.source


@pytest.mark.parametrize("hide_inputs", [True, False])
def test_function_graph_display_inputs(hide_inputs: bool):
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    dot = fg.display(
        set(fg.get_nodes()),
        hide_inputs=hide_inputs,
        config=config,
    )

    found_input = any(line.startswith("\t_") for line in dot.body)
    assert found_input is not hide_inputs


def test_function_graph_display_without_saving():
    """Tests that display works when None is passed in for path"""
    config = {"b": 1, "c": 2}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)
    all_nodes = set()
    node_modifiers = {"B": {graph.VisualizationNodeModifiers.IS_OUTPUT}}
    for n in fg.get_nodes():
        if n.user_defined:
            node_modifiers[n.name] = {graph.VisualizationNodeModifiers.IS_USER_INPUT}
        all_nodes.add(n)
    digraph = fg.display(
        all_nodes, output_file_path=None, node_modifiers=node_modifiers, config=config
    )
    assert digraph is not None
    import graphviz

    assert isinstance(digraph, graphviz.Digraph)


@pytest.mark.parametrize("display_fields", [True, False])
def test_function_graph_display_fields(display_fields: bool):
    @schema.output(("foo", "int"), ("bar", "float"), ("baz", "str"))
    def df_with_schema() -> pd.DataFrame:
        pass

    mod = ad_hoc_utils.create_temporary_module(df_with_schema)
    config = {}
    fg = graph.FunctionGraph.from_modules(mod, config=config)

    dot = fg.display(
        set(fg.get_nodes()),
        display_fields=display_fields,
        config=config,
    )
    if display_fields:
        assert any("foo" in line for line in dot.body)
        assert any("bar" in line for line in dot.body)
        assert any("baz" in line for line in dot.body)
        assert any("cluster_df_with_schema" in line for line in dot.body)
    else:
        assert not any("foo" in line for line in dot.body)
        assert not any("bar" in line for line in dot.body)
        assert not any("baz" in line for line in dot.body)
        assert not any("cluster_df_with_schema" in line for line in dot.body)


def test_function_graph_display_fields_shared_schema():
    # This ensures an edge case where they end up getting dropped if there are duplicates
    SCHEMA = (("foo", "int"), ("bar", "float"), ("baz", "str"))

    @schema.output(*SCHEMA)
    def df_1_with_schema() -> pd.DataFrame:
        pass

    @schema.output(*SCHEMA)
    def df_2_with_schema() -> pd.DataFrame:
        pass

    mod = ad_hoc_utils.create_temporary_module(df_1_with_schema, df_2_with_schema)
    config = {}
    fg = graph.FunctionGraph.from_modules(mod, config=config)

    dot = fg.display(
        set(fg.get_nodes()),
        display_fields=True,
        config=config,
    )

    def _get_occurances(var: str, lines: list[str]):
        return [item for item in lines if var in item]

    # We just need to make sure these show up twice
    assert len(_get_occurances("foo=", dot.body)) == 2
    assert len(_get_occurances("bar=", dot.body)) == 2
    assert len(_get_occurances("baz=", dot.body)) == 2


def test_function_graph_display_config_node():
    """Check if config is displayed by low-level hamilton.graph.FunctionGraph.display"""
    config = {"X": 1}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)

    dot = fg.display(set(fg.get_nodes()), config=config)

    # lines start tab then node name; check if "b" is a node in the graphviz object
    assert any(line.startswith("\tX") for line in dot.body)


# TODO use high-level visualization dot as fixtures for reuse across tests
def test_display_config_node():
    """Check if config is displayed by high-level hamilton.driver.display..."""
    from hamilton import driver
    from hamilton.io.materialization import to

    config = {"X": 1}
    dr = driver.Builder().with_modules(tests.resources.dummy_functions).with_config(config).build()

    all_dot = dr.display_all_functions()
    down_dot = dr.display_downstream_of("A")
    up_dot = dr.display_upstream_of("C")
    between_dot = dr.visualize_path_between("A", "C")
    exec_dot = dr.visualize_execution(["C"], inputs={"b": 1, "c": 2})
    materialize_dot = dr.visualize_materialization(
        to.json(id="saver", dependencies=["C"], combine=base.DictResult(), path="saver.json"),
        inputs={"b": 1, "c": 2},
    )

    for dot in [all_dot, down_dot, up_dot, between_dot, exec_dot, materialize_dot]:
        assert any(line.startswith("\tX") for line in dot.body)


def test_create_graphviz_graph():
    """Tests that we create a graphviz graph"""
    config = {}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)
    nodes, user_nodes = fg.get_upstream_nodes(["A", "B", "C"])
    nodez = nodes.union(user_nodes)
    node_modifiers = {
        "b": {graph.VisualizationNodeModifiers.IS_USER_INPUT},
        "c": {graph.VisualizationNodeModifiers.IS_USER_INPUT},
        "B": {graph.VisualizationNodeModifiers.IS_OUTPUT},
    }
    # hack of a test -- but it works... sort the lines and match them up.
    # why? because for some reason given the same graph, the output file isn't deterministic.
    # for the same reason, order of input nodes are non-deterministic
    expected_set = set(
        [
            "// Dependency Graph",
            "",
            "digraph {",
            '\tnode [fillcolor="#ffffff"]',
            "\tgraph [compound=true concentrate=true rankdir=LR ranksep=0.4 ratio=1 style=filled]",
            '\tB [label=<<b>B</b><br /><br /><i>int</i>> fillcolor="#FFC857" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]',
            '\tC [label=<<b>C</b><br /><br /><i>int</i>> fillcolor="#b4d8e4" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]',
            '\tA [label=<<b>A</b><br /><br /><i>int</i>> fillcolor="#b4d8e4" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]',
            "\tA -> B",
            "\tA -> C",
            '\t_A_inputs [label=<<table border="0"><tr><td>b</td><td>int</td></tr><tr><td>b</td><td>int</td></tr></table>> fontname=Helvetica margin=0.15 shape=rectangle style="filled,dashed"]',
            "\t_A_inputs -> A",
            "\tsubgraph cluster__legend {",
            '\t\tgraph [fillcolor="#ffffff" fontname=helvetica label=Legend rank=same]',
            '\t\tinput [fontname=Helvetica margin=0.15 shape=rectangle style="filled,dashed"]',
            '\t\tfunction [fillcolor="#b4d8e4" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]',
            '\t\toutput [fillcolor="#FFC857" fontname=Helvetica margin=0.15 shape=rectangle style="rounded,filled"]',
            "\t}",
            "}",
            "",
        ]
    )

    digraph = graph.create_graphviz_graph(
        nodez,
        "Dependency Graph\n",
        graphviz_kwargs=dict(graph_attr={"ratio": "1"}),
        node_modifiers=node_modifiers,
        strictly_display_only_nodes_passed_in=False,
        config=config,
    )
    # the HTML table isn't deterministic. Replace the value in it with a single one.
    dot_set = set(str(digraph).replace("<td>c</td>", "<td>b</td>").split("\n"))
    assert dot_set == expected_set


def test_create_graphviz_graph_styles_async_nodes():
    async def async_node() -> int:
        return 1

    def sync_node(async_node: int) -> int:
        return async_node + 1

    module = ad_hoc_utils.create_temporary_module(async_node, sync_node)
    fg = graph.FunctionGraph.from_modules(module, config={})

    digraph = graph.create_graphviz_graph(
        set(fg.get_nodes()),
        "Dependency Graph\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        config={},
    )
    dot_source = str(digraph)

    assert (
        "\tasync_node [label=<<b>async_node</b><br /><br /><i>int</i>> "
        'fillcolor="#CDB4DB" fontname=Helvetica margin=0.15 shape=rectangle '
        'style="rounded,filled,bold"]'
    ) in dot_source
    assert (
        '\t\tasync [fillcolor="#CDB4DB" fontname=Helvetica margin=0.15 '
        'shape=rectangle style="rounded,filled,bold"]'
    ) in dot_source


def test_create_networkx_graph():
    """Tests that we create a networkx graph"""
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config={})
    nodes, user_nodes = fg.get_upstream_nodes(["A", "B", "C"])
    digraph = graph.create_networkx_graph(nodes, user_nodes, "test-graph")
    expected_nodes = sorted(["c", "B", "C", "b", "A"])
    expected_edges = sorted([("c", "A"), ("b", "A"), ("A", "B"), ("A", "C")])
    assert sorted(list(digraph.nodes)) == expected_nodes
    assert sorted(list(digraph.edges)) == expected_edges


def test_end_to_end_with_layered_decorators_resolves_true():
    fg = graph.FunctionGraph.from_modules(
        tests.resources.layered_decorators, config={"foo": "bar", "d": 10, "b": 20}
    )
    out = fg.execute([n for n in fg.get_nodes()])
    assert len(out) > 0  # test config.when resolves correctly
    assert out["e"] == (20 + 10)
    assert out["f"] == (20 + 20)


def test_end_to_end_with_layered_decorators_resolves_false():
    config = {"foo": "not_bar", "d": 10, "b": 20}
    fg = graph.FunctionGraph.from_modules(tests.resources.layered_decorators, config=config)
    out = fg.execute(
        [n for n in fg.get_nodes()],
    )
    assert {item: value for item, value in out.items() if item not in config} == {}


def test_combine_inputs_no_collision():
    """Tests the combine_and_validate_inputs functionality when there are no collisions"""
    combined = graph_functions.combine_config_and_inputs({"a": 1}, {"b": 2})
    assert combined == {"a": 1, "b": 2}


def test_combine_inputs_collision():
    """Tests the combine_and_validate_inputs functionality
    when there are collisions of keys but not values"""
    with pytest.raises(ValueError):
        graph_functions.combine_config_and_inputs({"a": 1}, {"a": 2})


def test_combine_inputs_collision_2():
    """Tests the combine_and_validate_inputs functionality
    when there are collisions of keys and values"""
    with pytest.raises(ValueError):
        graph_functions.combine_config_and_inputs({"a": 1}, {"a": 1})


def test_extract_columns_executes_once():
    """Ensures that extract_columns only computes the function once.
    Note this is a bit heavy-handed of a test but its nice to have."""
    fg = graph.FunctionGraph.from_modules(
        tests.resources.extract_columns_execution_count, config={}
    )
    unique_id = str(uuid.uuid4())
    fg.execute([n for n in fg.get_nodes()], inputs={"unique_id": unique_id})
    assert (
        len(tests.resources.extract_columns_execution_count.outputs[unique_id]) == 1
    )  # It should only be called once


def test_end_to_end_with_generics():
    fg = graph.FunctionGraph.from_modules(
        tests.resources.functions_with_generics, config={"b": {}, "c": 1}
    )
    results = fg.execute(fg.get_nodes())
    assert results == {
        "A": ({}, 1),
        "B": [({}, 1), ({}, 1)],
        "C": {"foo": [({}, 1), ({}, 1)]},
        "D": 1.0,
        "b": {},
        "c": 1,
    }


@pytest.mark.parametrize(
    ("config", "inputs", "overrides"),
    [
        # testing with no provided inputs
        ({}, {}, {}),
        # testing with just configs
        ({"a": 11}, {}, {}),
        ({"b": 13, "a": 17}, {}, {}),
        ({"b": 19, "a": 23, "d": 29, "f": 31}, {}, {}),
        # Testing with just inputs
        ({}, {"a": 37}, {}),
        ({}, {"b": 41, "a": 43}, {}),
        ({}, {"b": 41, "a": 43, "d": 47, "f": 53}, {}),
        # Testing with just overrides
        # TBD whether these should be legitimate -- can we override required inputs?
        # Test works now but not part of the contract
        # ({}, {}, {'a': 59}),
        # ({}, {}, {'a': 61, 'b': 67}),
        # ({}, {}, {'a': 71, 'b': 73, 'd': 79, 'f': 83}),
        # testing with a mix
        ({"a": 89}, {"b": 97}, {}),
        ({"a": 101}, {"b": 103, "d": 107}, {}),
    ],
)
def test_optional_execute(config, inputs, overrides):
    """Tests execution of optionals with different assortment of overrides, configs, inputs, etc...
    Be careful adding tests with conflicting values between them.
    """
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config=config)
    # we put a user input node first to ensure that order does not matter with computation order.
    results = fg.execute([fg.nodes["b"], fg.nodes["g"]], inputs=inputs, overrides=overrides)
    do_all_args = {key + "_val": val for key, val in {**config, **inputs, **overrides}.items()}
    expected_results = tests.resources.optional_dependencies._do_all(**do_all_args)
    assert results["g"] == expected_results["g"]


def test_optional_input_behavior():
    """Tests that if we request optional user inputs that are not provided, we do not break. And if they are
    we do the right thing and return them.
    """
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={})
    # nothing passed, so nothing returned
    result = fg.execute([fg.nodes["b"], fg.nodes["a"]], inputs={}, overrides={})
    assert result == {}
    # something passed, something returned via config
    fg2 = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={"a": 10})
    result = fg2.execute([fg.nodes["b"], fg.nodes["a"]], inputs={}, overrides={})
    assert result == {"a": 10}
    # something passed, something returned via inputs
    result = fg.execute([fg.nodes["b"], fg.nodes["a"]], inputs={"a": 10}, overrides={})
    assert result == {"a": 10}
    # something passed, something returned via overrides
    result = fg.execute([fg.nodes["b"], fg.nodes["a"]], inputs={}, overrides={"a": 10})
    assert result == {"a": 10}


@pytest.mark.parametrize("node_order", list(permutations("fhi")))
def test_user_input_breaks_if_required_missing(node_order):
    """Tests that we break because `h` is required but is not passed in."""
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={})
    permutation = [fg.nodes[n] for n in node_order]
    with pytest.raises(NotImplementedError):
        fg.execute(permutation, inputs={}, overrides={})


@pytest.mark.parametrize("node_order", list(permutations("fhi")))
def test_user_input_does_not_break_if_required_provided(node_order):
    """Tests that things work no matter the order because `h` is required and is passed in, while `f` is optional."""
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={"h": 10})
    permutation = [fg.nodes[n] for n in node_order]
    result = fg.execute(permutation, inputs={}, overrides={})
    assert result == {"h": 10, "i": 17}


def test_optional_donot_drop_none():
    """We do not want to drop `None` results from functions. We want to pass them through to the function.

    This is here to enshrine the current behavior.
    """
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={"h": None})
    # enshrine behavior that None is not removed from being passed to the function.
    results = fg.execute([fg.nodes["h"], fg.nodes["i"]], inputs={}, overrides={})
    assert results == {"h": None, "i": 17}
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={})
    results = fg.execute(
        [fg.nodes["j"], fg.nodes["none_result"], fg.nodes["f"]], inputs={}, overrides={}
    )
    assert results == {"j": None, "none_result": None}  # f omitted cause it's optional.


def test_optional_get_required_compile_time():
    """Tests that getting required with optionals at compile time returns everything
    TODO -- change this to be testing a different function (compile time) than runtime.
    """
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={})
    all_upstream, user_required = fg.get_upstream_nodes(["g"])
    assert len(all_upstream) == 7  # 6 total nodes upstream
    assert len(user_required) == 4  # 4 nodes required input


def test_optional_get_required_runtime():
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={})
    all_upstream, user_required = fg.get_upstream_nodes(["g"], runtime_inputs={})  # Nothng required
    assert len(all_upstream) == 3  # 6 total nodes upstream
    assert len(user_required) == 0  # 4 nodes required input


def test_optional_get_required_runtime_with_provided():
    fg = graph.FunctionGraph.from_modules(tests.resources.optional_dependencies, config={})
    all_upstream, user_required = fg.get_upstream_nodes(
        ["g"], runtime_inputs={"b": 109}
    )  # Nothng required
    assert len(all_upstream) == 4  # 6 total nodes upstream
    assert len(user_required) == 1  # 4 nodes required input


def test_in_driver_function_definitions():
    """Tests that we can instantiate a DAG with a function defined in the driver, e.g. notebook context"""

    def my_function(A: int, b: int, c: int) -> int:
        """Function for input below"""
        return A + b + c

    f_module = ad_hoc_utils.create_temporary_module(my_function)
    fg = graph.FunctionGraph.from_modules(
        tests.resources.dummy_functions, f_module, config={"b": 3, "c": 1}
    )
    results = fg.execute([n for n in fg.get_nodes() if n.name in ["my_function", "A"]])
    assert results == {"A": 4, "b": 3, "c": 1, "my_function": 8}


def test_update_dependencies():
    nodes = create_testing_nodes()
    new_nodes = graph.update_dependencies(
        nodes, lifecycle_base.LifecycleAdapterSet(base.DefaultAdapter())
    )
    for node_name, node_ in new_nodes.items():
        assert node_.dependencies == nodes[node_name].dependencies
        assert node_.depended_on_by == nodes[node_name].depended_on_by


# Tests for display_name tag support in graphviz visualization
# See: https://github.com/apache/hamilton/issues/1413


def test_create_graphviz_graph_with_display_name():
    """Tests that display_name tag is used for node labels in visualization."""

    config = {}
    fg = graph.FunctionGraph.from_modules(tests.resources.display_name_functions, config=config)
    nodes, user_nodes = fg.get_upstream_nodes(["output_node"])
    all_nodes = nodes.union(user_nodes)

    digraph = graph.create_graphviz_graph(
        all_nodes,
        "Display Name Test\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        config=config,
    )
    dot_string = str(digraph)

    # Node with display_name should show the display name, not the function name
    assert "My Custom Display Name" in dot_string
    assert "Final Output Node" in dot_string

    # Node without display_name should show the function name
    assert "node_without_display_name" in dot_string


def test_create_graphviz_graph_display_name_html_escaping():
    """Tests that display_name values with special characters are properly HTML escaped."""
    config = {}
    fg = graph.FunctionGraph.from_modules(tests.resources.display_name_functions, config=config)
    nodes, user_nodes = fg.get_upstream_nodes(["node_with_special_chars"])
    all_nodes = nodes.union(user_nodes)

    digraph = graph.create_graphviz_graph(
        all_nodes,
        "HTML Escape Test\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        config=config,
    )
    dot_string = str(digraph)

    # Special characters should be HTML escaped
    # < becomes &lt;, > becomes &gt;, & becomes &amp;, " becomes &quot;
    assert "&lt;" in dot_string  # <
    assert "&gt;" in dot_string  # >
    assert "&amp;" in dot_string  # &
    assert "&quot;" in dot_string  # "

    # The raw special characters should NOT appear unescaped in the label
    # (they would break graphviz HTML parsing)
    assert "label=<<b>Special <Characters>" not in dot_string


def test_create_graphviz_graph_without_display_name_backward_compatible():
    """Tests that nodes without display_name tag still work as before."""
    config = {}
    fg = graph.FunctionGraph.from_modules(tests.resources.dummy_functions, config=config)
    nodes, user_nodes = fg.get_upstream_nodes(["A", "B"])
    all_nodes = nodes.union(user_nodes)

    digraph = graph.create_graphviz_graph(
        all_nodes,
        "Backward Compatibility Test\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        config=config,
    )
    dot_string = str(digraph)

    # Without display_name tag, node names should be used (existing behavior)
    assert "<b>A</b>" in dot_string
    assert "<b>B</b>" in dot_string


def test_get_input_label_with_display_name():
    """Tests that _get_input_label uses display_name tag for input nodes."""
    config = {}
    fg = graph.FunctionGraph.from_modules(tests.resources.display_name_functions, config=config)
    # Get nodes that have inputs (to test _get_input_label)
    nodes, user_nodes = fg.get_upstream_nodes(["output_node"])
    all_nodes = nodes.union(user_nodes)

    digraph = graph.create_graphviz_graph(
        all_nodes,
        "Input Label Test\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        hide_inputs=False,  # Make sure inputs are shown
        config=config,
    )
    dot_string = str(digraph)

    # Input nodes should be displayed in the table format
    # The input_a node doesn't have display_name, so it should show "input_a"
    assert "input_a" in dot_string


def test_get_node_label_explicit_name_overrides_display_name():
    """Tests that explicit name parameter overrides display_name tag in _get_node_label."""
    config = {}
    fg = graph.FunctionGraph.from_modules(tests.resources.display_name_functions, config=config)

    # Get a node that has display_name tag
    target_node = None
    for n in fg.get_nodes():
        if n.name == "node_with_display_name":
            target_node = n
            break

    assert target_node is not None
    assert target_node.tags.get("display_name") == "My Custom Display Name"

    # When we call create_graphviz_graph with config that adds a suffix to node names,
    # the explicit name parameter should take precedence over display_name tag.
    # This is tested implicitly through the config key display logic.
    # The key behavior is: explicit name param > display_name tag > node.name

    # For direct testing, we verify the node has both the tag and the visualization works
    nodes, user_nodes = fg.get_upstream_nodes(["node_with_display_name"])
    all_nodes = nodes.union(user_nodes)

    digraph = graph.create_graphviz_graph(
        all_nodes,
        "Override Test\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        config=config,
    )
    dot_string = str(digraph)

    # display_name should be used when no explicit name is provided
    assert "My Custom Display Name" in dot_string


def test_display_name_list_value_uses_first_element():
    """Tests that when display_name is a list, the first element is used."""
    config = {}
    fg = graph.FunctionGraph.from_modules(
        tests.resources.display_name_list_functions, config=config
    )
    nodes, user_nodes = fg.get_upstream_nodes(["node_with_list_display_name"])
    all_nodes = nodes.union(user_nodes)

    digraph = graph.create_graphviz_graph(
        all_nodes,
        "List Display Name Test\n",
        graphviz_kwargs={},
        node_modifiers={},
        strictly_display_only_nodes_passed_in=False,
        config=config,
    )
    dot_string = str(digraph)

    # When display_name is a list, the first element should be used
    assert "First Name" in dot_string
    # The function name should NOT appear since display_name is set
    assert "<b>node_with_list_display_name</b>" not in dot_string