simulation/modules/IsaacLab/source/isaaclab/test/utils/test_dict.py

# Copyright (c) 2022-2026, The Isaac Lab Project Developers (https://github.com/isaac-sim/IsaacLab/blob/main/CONTRIBUTORS.md).
# All rights reserved.
#
# SPDX-License-Identifier: BSD-3-Clause

import random

import pytest

import isaaclab.utils.dict as dict_utils
import isaaclab.utils.string as string_utils


def _test_function(x):
    """Test function for string <-> callable conversion."""
    return x**2


def _test_lambda_function(x):
    """Test function for string <-> callable conversion."""
    return x**2


def test_print_dict():
    """Test printing of dictionary."""
    # create a complex nested dictionary
    test_dict = {
        "a": 1,
        "b": 2,
        "c": {"d": 3, "e": 4, "f": {"g": 5, "h": 6}},
        "i": 7,
        "j": lambda x: x**2,  # noqa: E731
        "k": dict_utils.class_to_dict,
    }
    # print the dictionary
    dict_utils.print_dict(test_dict)


def test_string_callable_function_conversion():
    """Test string <-> callable conversion for function."""

    # convert function to string
    test_string = dict_utils.callable_to_string(_test_function)
    # convert string to function
    test_function_2 = string_utils.string_to_callable(test_string)
    # check that functions are the same
    assert _test_function(2) == test_function_2(2)


def test_string_callable_function_with_lambda_in_name_conversion():
    """Test string <-> callable conversion for function which has lambda in its name."""

    # convert function to string
    test_string = dict_utils.callable_to_string(_test_lambda_function)
    # convert string to function
    test_function_2 = string_utils.string_to_callable(test_string)
    # check that functions are the same
    assert _test_function(2) == test_function_2(2)


def test_string_callable_lambda_conversion():
    """Test string <-> callable conversion for lambda expression."""

    # create lambda function
    func = lambda x: x**2  # noqa: E731
    # convert function to string
    test_string = dict_utils.callable_to_string(func)
    # convert string to function
    func_2 = string_utils.string_to_callable(test_string)
    # check that functions are the same
    assert test_string == "lambda x: x**2"
    assert func(2) == func_2(2)


def test_dict_to_md5():
    """Test MD5 hash generation for dictionary."""
    # create a complex nested dictionary
    test_dict = {
        "a": 1,
        "b": 2,
        "c": {"d": 3, "e": 4, "f": {"g": 5, "h": 6}},
        "i": random.random(),
        "k": dict_utils.callable_to_string(dict_utils.class_to_dict),
    }
    # generate the MD5 hash
    md5_hash_1 = dict_utils.dict_to_md5_hash(test_dict)

    # check that the hash is correct even after multiple calls
    for _ in range(200):
        md5_hash_2 = dict_utils.dict_to_md5_hash(test_dict)
        assert md5_hash_1 == md5_hash_2


class _CallableCfg:
    class_type = _test_function


def test_update_class_from_dict_keeps_callable_string_lazy():
    """Callable-string updates should remain lazy via ResolvableString."""
    cfg = _CallableCfg()
    dict_utils.update_class_from_dict(cfg, {"class_type": "math:sin"})

    assert isinstance(cfg.class_type, string_utils.ResolvableString)
    # Dunder probing should not force resolution/import side effects.
    assert hasattr(cfg.class_type, "__dataclass_fields__") is False
    # Runtime use still resolves correctly.
    assert pytest.approx(cfg.class_type(0.0), rel=0.0, abs=1e-9) == 0.0


def test_update_class_from_dict_does_not_rewrap_resolvable_string():
    """Existing ResolvableString should be preserved, not re-wrapped."""
    cfg = _CallableCfg()
    existing = string_utils.ResolvableString("math:sin")
    dict_utils.update_class_from_dict(cfg, {"class_type": existing})

    assert cfg.class_type is existing