feat: Set up comprehensive Python testing infrastructure with Poetry

.gitignore

@@ -20,4 +20,56 @@ realsense/realsense
 
 commands.txt
 visualization.push.png
-visualization.grasp.png
+visualization.grasp.png
+
+# Testing related
+.pytest_cache/
+.coverage
+htmlcov/
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.tox/
+.nox/
+
+# Claude settings
+.claude/*
+
+# Virtual environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# IDE files
+.vscode/
+.idea/
+*.swp
+*.swo
+*~
+.DS_Store
+
+# Build artifacts
+dist/
+build/
+*.egg-info/
+*.egg
+.eggs/
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version

pyproject.toml

@@ -0,0 +1,90 @@
+[tool.poetry]
+name = "visual-pushing-grasping"
+version = "0.1.0"
+description = "Visual Pushing and Grasping - Learning Synergies between Pushing and Grasping with Self-supervised Deep Reinforcement Learning"
+authors = ["Andy Zeng <andyz@princeton.edu>"]
+readme = "README.md"
+packages = [{include = "real"}, {include = "simulation"}]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+numpy = "^1.21.0"
+scipy = "^1.7.0"
+opencv-python = "^4.5.0"
+matplotlib = "^3.4.0"
+torch = ">=1.9.0"
+torchvision = ">=0.10.0"
+
+[tool.poetry.group.dev.dependencies]
+pytest = "^7.4.0"
+pytest-cov = "^4.1.0"
+pytest-mock = "^3.11.0"
+
+[tool.poetry.scripts]
+test = "pytest:main"
+tests = "pytest:main"
+
+[tool.pytest.ini_options]
+minversion = "7.0"
+addopts = [
+    "-ra",
+    "--strict-markers",
+    "--strict-config",
+    "-vv",
+]
+testpaths = ["tests"]
+python_files = ["test_*.py", "*_test.py"]
+python_classes = ["Test*"]
+python_functions = ["test_*"]
+markers = [
+    "unit: Unit tests (fast, isolated)",
+    "integration: Integration tests (may be slower)",
+    "slow: Slow tests (deselect with '-m \"not slow\"')",
+]
+filterwarnings = [
+    "error",
+    "ignore::UserWarning",
+    "ignore::DeprecationWarning",
+]
+
+[tool.coverage.run]
+source = ["tests"]
+omit = [
+    "*/tests/*",
+    "*/test_*",
+    "*/__pycache__/*",
+    "*/site-packages/*",
+    ".venv/*",
+    "venv/*",
+    "setup.py",
+    "*/migrations/*",
+    "*/config/*",
+    "*/settings/*",
+]
+
+[tool.coverage.report]
+precision = 2
+show_missing = true
+skip_covered = false
+fail_under = 80
+exclude_lines = [
+    "pragma: no cover",
+    "def __repr__",
+    "if self.debug:",
+    "if settings.DEBUG",
+    "raise AssertionError",
+    "raise NotImplementedError",
+    "if 0:",
+    "if __name__ == .__main__.:",
+    "if TYPE_CHECKING:",
+]
+
+[tool.coverage.html]
+directory = "htmlcov"
+
+[tool.coverage.xml]
+output = "coverage.xml"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"

tests/conftest.py

@@ -0,0 +1,211 @@
+"""
+Shared pytest fixtures for the visual-pushing-grasping test suite.
+
+This module provides common fixtures that can be used across unit and integration tests.
+"""
+
+import os
+import tempfile
+import shutil
+from pathlib import Path
+from unittest.mock import Mock, MagicMock
+
+import pytest
+import numpy as np
+import torch
+
+
+@pytest.fixture
+def temp_dir():
+    """Create a temporary directory that is cleaned up after the test."""
+    temp_path = tempfile.mkdtemp()
+    yield Path(temp_path)
+    shutil.rmtree(temp_path)
+
+
+@pytest.fixture
+def mock_config():
+    """Provide a mock configuration object for testing."""
+    config = Mock()
+    config.is_sim = True
+    config.obj_mesh_dir = 'objects/blocks'
+    config.num_obj = 10
+    config.push_rewards = True
+    config.experience_replay = True
+    config.explore_rate_decay = True
+    config.is_testing = False
+    config.test_preset_cases = False
+    config.save_visualizations = False
+    config.load_snapshot = False
+    config.snapshot_file = None
+    config.random_seed = 1234
+    config.force_cpu = False
+    config.logging_directory = 'logs'
+    return config
+
+
+@pytest.fixture
+def sample_rgb_image():
+    """Create a sample RGB image for testing."""
+    # Create a 224x224x3 RGB image with random values
+    return np.random.randint(0, 255, size=(224, 224, 3), dtype=np.uint8)
+
+
+@pytest.fixture
+def sample_depth_image():
+    """Create a sample depth image for testing."""
+    # Create a 224x224 depth image with values in millimeters
+    return np.random.uniform(300, 2000, size=(224, 224)).astype(np.float32)
+
+
+@pytest.fixture
+def sample_rgbd_image(sample_rgb_image, sample_depth_image):
+    """Create a sample RGB-D image pair for testing."""
+    return {
+        'rgb': sample_rgb_image,
+        'depth': sample_depth_image
+    }
+
+
+@pytest.fixture
+def mock_robot():
+    """Provide a mock robot object for testing."""
+    robot = Mock()
+    robot.get_camera_data = MagicMock(return_value=(
+        np.random.randint(0, 255, size=(480, 640, 3), dtype=np.uint8),
+        np.random.uniform(300, 2000, size=(480, 640)).astype(np.float32)
+    ))
+    robot.grasp = MagicMock(return_value=True)
+    robot.push = MagicMock(return_value=True)
+    robot.restart_sim = MagicMock()
+    robot.check_sim = MagicMock(return_value=True)
+    robot.get_obj_positions = MagicMock(return_value=np.random.rand(10, 3))
+    robot.get_obj_positions_and_orientations = MagicMock(
+        return_value=(np.random.rand(10, 3), np.random.rand(10, 3))
+    )
+    return robot
+
+
+@pytest.fixture
+def mock_trainer():
+    """Provide a mock trainer object for testing."""
+    trainer = Mock()
+    trainer.forward = MagicMock(return_value=(
+        torch.rand(1, 1, 224, 224),  # push predictions
+        torch.rand(1, 1, 224, 224),  # grasp predictions
+        torch.tensor([0.5])  # state value
+    ))
+    trainer.get_label_value = MagicMock(return_value=(
+        torch.ones(1, 320, 320),  # label
+        torch.tensor([1.0])  # label value
+    ))
+    trainer.backprop = MagicMock()
+    trainer.save_model = MagicMock()
+    trainer.load_model = MagicMock()
+    return trainer
+
+
+@pytest.fixture
+def mock_logger():
+    """Provide a mock logger object for testing."""
+    logger = Mock()
+    logger.save_camera_info = MagicMock()
+    logger.save_heightmap = MagicMock()
+    logger.save_images = MagicMock()
+    logger.save_model = MagicMock()
+    logger.save_backup_model = MagicMock()
+    logger.save_transitions = MagicMock()
+    logger.write_to_log = MagicMock()
+    return logger
+
+
+@pytest.fixture
+def sample_heightmap():
+    """Create a sample heightmap for testing."""
+    return np.random.rand(224, 224).astype(np.float32)
+
+
+@pytest.fixture
+def sample_action():
+    """Create a sample action for testing."""
+    return {
+        'action_type': 'grasp',  # or 'push'
+        'position': [112, 112],  # pixel coordinates
+        'angle': 45.0,  # rotation angle in degrees
+        'heightmap_idx': 0
+    }
+
+
+@pytest.fixture
+def vrep_connection():
+    """Mock V-REP connection for testing simulation components."""
+    connection = Mock()
+    connection.simxGetObjectHandle = MagicMock(return_value=(0, 1))
+    connection.simxSetObjectPosition = MagicMock(return_value=0)
+    connection.simxSetObjectOrientation = MagicMock(return_value=0)
+    connection.simxStartSimulation = MagicMock(return_value=0)
+    connection.simxStopSimulation = MagicMock(return_value=0)
+    connection.simxGetVisionSensorImage = MagicMock(return_value=(
+        0,
+        [255] * (640 * 480 * 3)  # Flattened RGB image
+    ))
+    connection.simxGetVisionSensorDepthBuffer = MagicMock(return_value=(
+        0,
+        [0.5] * (640 * 480)  # Flattened depth buffer
+    ))
+    return connection
+
+
+@pytest.fixture
+def sample_workspace_limits():
+    """Define workspace limits for testing."""
+    return np.array([
+        [-0.724, -0.276],  # x limits
+        [-0.224, 0.224],   # y limits
+        [-0.0001, 0.4]     # z limits
+    ])
+
+
+@pytest.fixture
+def sample_torch_model():
+    """Create a simple torch model for testing."""
+    class SimpleModel(torch.nn.Module):
+        def __init__(self):
+            super(SimpleModel, self).__init__()
+            self.conv1 = torch.nn.Conv2d(3, 64, kernel_size=3, padding=1)
+            self.relu = torch.nn.ReLU()
+            self.conv2 = torch.nn.Conv2d(64, 1, kernel_size=1)
+
+        def forward(self, x):
+            x = self.conv1(x)
+            x = self.relu(x)
+            x = self.conv2(x)
+            return x
+
+    return SimpleModel()
+
+
+@pytest.fixture(autouse=True)
+def reset_random_seeds():
+    """Reset random seeds before each test for reproducibility."""
+    np.random.seed(42)
+    torch.manual_seed(42)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(42)
+
+
+@pytest.fixture
+def gpu_available():
+    """Check if GPU is available for testing."""
+    return torch.cuda.is_available()
+
+
+@pytest.fixture
+def capture_stdout(monkeypatch):
+    """Capture stdout for testing print statements."""
+    import io
+    import sys
+
+    captured_output = io.StringIO()
+    monkeypatch.setattr(sys, 'stdout', captured_output)
+    return captured_output