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Testing Discrete Space Implementation in OpenAI Gym

This test suite validates the functionality of Discrete space implementation in OpenAI Gym’s spaces module. It focuses on verifying discrete space sampling behavior and legacy pickle compatibility, ensuring robust space manipulation and state preservation.

Test Coverage Overview

The test suite provides comprehensive coverage of Discrete space functionality in OpenAI Gym:

Legacy pickle state handling and compatibility
Discrete space sampling with masking
Start parameter validation
Shape and dtype preservation

Implementation Analysis

The testing approach employs pytest-style unit tests with direct assertions. It uses numpy arrays for mask testing and validates both legacy compatibility and modern features of the Discrete space implementation.

State manipulation testing through __setstate__
Masked sampling verification
Boundary condition checks

Technical Details

Testing Framework: pytest
Dependencies: numpy
Key Classes: gym.spaces.Discrete
Test Scope: Unit tests
State Management: pickle compatibility

Best Practices Demonstrated

The test suite exemplifies several testing best practices:

Explicit state verification
Comprehensive edge case coverage
Clear test function naming
Isolated test cases
Proper assertion usage

openai/gym

tests/spaces/test_discrete.py

            
import numpy as np

from gym.spaces import Discrete


def test_space_legacy_pickling():
    """Test the legacy pickle of Discrete that is missing the `start` parameter."""
    legacy_state = {
        "shape": (
            1,
            2,
            3,
        ),
        "dtype": np.int64,
        "np_random": np.random.default_rng(),
        "n": 3,
    }
    space = Discrete(1)
    space.__setstate__(legacy_state)

    assert space.shape == legacy_state["shape"]
    assert space.np_random == legacy_state["np_random"]
    assert space.n == 3
    assert space.dtype == legacy_state["dtype"]

    # Test that start is missing
    assert "start" in space.__dict__
    del space.__dict__["start"]  # legacy did not include start param
    assert "start" not in space.__dict__

    space.__setstate__(legacy_state)
    assert space.start == 0


def test_sample_mask():
    space = Discrete(4, start=2)
    assert 2 <= space.sample() < 6
    assert space.sample(mask=np.array([0, 1, 0, 0], dtype=np.int8)) == 3
    assert space.sample(mask=np.array([0, 0, 0, 0], dtype=np.int8)) == 2
    assert space.sample(mask=np.array([0, 1, 0, 1], dtype=np.int8)) in [3, 5]