fix(py): one name, clawhdf5, for the Python distribution and module
pyproject.toml named the distribution rustyhdf5 while the extension module is clawhdf5, and the package's tests imported rustyhdf5, so pytest failed at collection. Distribution, module-name and tests now agree; the module gains __version__. maturin develop + pytest: 28 pass. Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
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osobh
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"""Tests for clawhdf5 Python bindings."""
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import os
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import tempfile
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import numpy as np
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import pytest
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import clawhdf5
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@pytest.fixture
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def tmp_h5(tmp_path):
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"""Return a temporary HDF5 file path."""
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return str(tmp_path / "test.h5")
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@pytest.fixture
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def sample_read_file(tmp_h5):
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"""Create a sample HDF5 file for reading tests."""
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("temperatures", data=np.array([22.5, 23.1, 21.8]))
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f.create_dataset("counts", data=np.array([10, 20, 30], dtype=np.int32))
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f.attrs["version"] = 1
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f.attrs["description"] = "test file"
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return tmp_h5
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@pytest.fixture
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def grouped_read_file(tmp_h5):
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"""Create an HDF5 file with groups for reading tests."""
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("root_data", data=np.array([0.0, 1.0]))
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grp = f.create_group("sensors")
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grp.create_dataset("temperature", data=np.array([22.5, 23.1, 21.8]))
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grp.create_dataset("humidity", data=np.array([45, 50, 55], dtype=np.int32))
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grp.attrs["location"] = "lab"
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grp2 = f.create_group("metadata")
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grp2.create_dataset("timestamps", data=np.array([1000, 2000, 3000], dtype=np.int64))
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return tmp_h5
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# ---------------------------------------------------------------------------
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# Test: open and read datasets
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# ---------------------------------------------------------------------------
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def test_open_and_read_f64(sample_read_file):
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f = clawhdf5.File(sample_read_file, "r")
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ds = f["temperatures"]
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data = ds[:]
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np.testing.assert_array_almost_equal(data, [22.5, 23.1, 21.8])
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f.close()
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def test_open_and_read_i32(sample_read_file):
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f = clawhdf5.File(sample_read_file, "r")
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ds = f["counts"]
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data = ds[:]
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np.testing.assert_array_equal(data, [10, 20, 30])
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assert data.dtype == np.int32
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f.close()
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# ---------------------------------------------------------------------------
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# Test: dataset properties (shape, dtype)
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# ---------------------------------------------------------------------------
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def test_dataset_shape(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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ds = f["temperatures"]
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assert ds.shape == (3,)
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def test_dataset_dtype(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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assert f["temperatures"].dtype == "float64"
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assert f["counts"].dtype == "int32"
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# ---------------------------------------------------------------------------
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# Test: read attributes
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# ---------------------------------------------------------------------------
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def test_read_root_attrs(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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assert f.attrs["version"] == 1
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assert f.attrs["description"] == "test file"
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def test_attrs_len(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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assert len(f.attrs) >= 2
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def test_attrs_contains(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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assert "version" in f.attrs
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assert "nonexistent" not in f.attrs
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def test_attrs_keys(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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keys = f.attrs.keys()
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assert "version" in keys
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assert "description" in keys
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# ---------------------------------------------------------------------------
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# Test: read groups
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# ---------------------------------------------------------------------------
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def test_read_group_keys(grouped_read_file):
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with clawhdf5.File(grouped_read_file, "r") as f:
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keys = f.keys()
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assert "sensors" in keys
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assert "metadata" in keys
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assert "root_data" in keys
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def test_read_group_dataset(grouped_read_file):
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with clawhdf5.File(grouped_read_file, "r") as f:
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grp = f["sensors"]
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ds = grp["temperature"]
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data = ds[:]
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np.testing.assert_array_almost_equal(data, [22.5, 23.1, 21.8])
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def test_read_group_attrs(grouped_read_file):
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with clawhdf5.File(grouped_read_file, "r") as f:
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grp = f["sensors"]
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assert grp.attrs["location"] == "lab"
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def test_nested_path_access(grouped_read_file):
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"""Test f['group/dataset'] path navigation."""
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with clawhdf5.File(grouped_read_file, "r") as f:
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ds = f["sensors/temperature"]
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data = ds[:]
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np.testing.assert_array_almost_equal(data, [22.5, 23.1, 21.8])
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# ---------------------------------------------------------------------------
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# Test: context manager
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# ---------------------------------------------------------------------------
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def test_context_manager(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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data = f["temperatures"][:]
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np.testing.assert_array_almost_equal(data, [22.5, 23.1, 21.8])
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# File should be closed after with block
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assert repr(f) == "<HDF5 File (closed)>"
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# ---------------------------------------------------------------------------
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# Test: create files / write mode
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# ---------------------------------------------------------------------------
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def test_write_simple(tmp_h5):
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=np.array([1.0, 2.0, 3.0]))
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# Verify by reading back
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with clawhdf5.File(tmp_h5, "r") as f:
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data = f["data"][:]
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np.testing.assert_array_almost_equal(data, [1.0, 2.0, 3.0])
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def test_write_with_attrs(tmp_h5):
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("values", data=np.array([10, 20], dtype=np.int32))
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f.attrs["author"] = "test"
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f.attrs["count"] = 42
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with clawhdf5.File(tmp_h5, "r") as f:
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assert f.attrs["author"] == "test"
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assert f.attrs["count"] == 42
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def test_write_with_group(tmp_h5):
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with clawhdf5.File(tmp_h5, "w") as f:
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grp = f.create_group("experiment")
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grp.create_dataset("results", data=np.array([3.14, 2.72]))
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grp.attrs["version"] = 1
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with clawhdf5.File(tmp_h5, "r") as f:
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ds = f["experiment/results"]
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np.testing.assert_array_almost_equal(ds[:], [3.14, 2.72])
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grp = f["experiment"]
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assert grp.attrs["version"] == 1
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# ---------------------------------------------------------------------------
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# Test: numpy array types round-trip
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# ---------------------------------------------------------------------------
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def test_roundtrip_float64(tmp_h5):
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original = np.array([1.1, 2.2, 3.3], dtype=np.float64)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=original)
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with clawhdf5.File(tmp_h5, "r") as f:
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result = f["data"][:]
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np.testing.assert_array_almost_equal(result, original)
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assert result.dtype == np.float64
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def test_roundtrip_float32(tmp_h5):
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original = np.array([1.5, 2.5, 3.5], dtype=np.float32)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=original)
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with clawhdf5.File(tmp_h5, "r") as f:
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result = f["data"][:]
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np.testing.assert_array_almost_equal(result, original)
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assert result.dtype == np.float32
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def test_roundtrip_int32(tmp_h5):
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original = np.array([-10, 0, 10, 100], dtype=np.int32)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=original)
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with clawhdf5.File(tmp_h5, "r") as f:
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result = f["data"][:]
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np.testing.assert_array_equal(result, original)
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assert result.dtype == np.int32
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def test_roundtrip_int64(tmp_h5):
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original = np.array([-1, 0, 1, 2**40], dtype=np.int64)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=original)
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with clawhdf5.File(tmp_h5, "r") as f:
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result = f["data"][:]
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np.testing.assert_array_equal(result, original)
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assert result.dtype == np.int64
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def test_roundtrip_uint8(tmp_h5):
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original = np.array([0, 127, 255], dtype=np.uint8)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=original)
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with clawhdf5.File(tmp_h5, "r") as f:
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result = f["data"][:]
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np.testing.assert_array_equal(result, original)
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assert result.dtype == np.uint8
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# ---------------------------------------------------------------------------
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# Test: chunked + compressed datasets
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# ---------------------------------------------------------------------------
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def test_chunked_gzip(tmp_h5):
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original = np.arange(100, dtype=np.float64)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset(
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"compressed",
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data=original,
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chunks=(50,),
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compression="gzip",
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compression_opts=6,
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)
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with clawhdf5.File(tmp_h5, "r") as f:
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result = f["compressed"][:]
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np.testing.assert_array_equal(result, original)
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# ---------------------------------------------------------------------------
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# Test: h5py interoperability
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# ---------------------------------------------------------------------------
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def test_h5py_can_read_our_file(tmp_h5):
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"""Verify that h5py can read files we create."""
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import h5py
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("values", data=np.array([1.0, 2.0, 3.0]))
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f.attrs["meta"] = "hello"
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with h5py.File(tmp_h5, "r") as f:
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np.testing.assert_array_equal(f["values"][:], [1.0, 2.0, 3.0])
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# h5py reads fixed-length strings as bytes
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assert f.attrs["meta"] == b"hello"
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def test_we_can_read_h5py_file(tmp_h5):
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"""Verify that we can read files created by h5py."""
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import h5py
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with h5py.File(tmp_h5, "w") as f:
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f.create_dataset("data", data=np.array([10.0, 20.0, 30.0]))
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f.attrs["version"] = 2
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with clawhdf5.File(tmp_h5, "r") as f:
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data = f["data"][:]
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np.testing.assert_array_equal(data, [10.0, 20.0, 30.0])
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assert f.attrs["version"] == 2
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# ---------------------------------------------------------------------------
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# Test: 2D array shape
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# ---------------------------------------------------------------------------
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def test_2d_array_roundtrip(tmp_h5):
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original = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=np.float64)
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with clawhdf5.File(tmp_h5, "w") as f:
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f.create_dataset("matrix", data=original)
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with clawhdf5.File(tmp_h5, "r") as f:
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ds = f["matrix"]
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assert ds.shape == (2, 3)
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result = ds[:]
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np.testing.assert_array_almost_equal(result, original)
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# ---------------------------------------------------------------------------
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# Test: error handling
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# ---------------------------------------------------------------------------
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def test_open_nonexistent_file():
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with pytest.raises(OSError):
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clawhdf5.File("/nonexistent/path.h5", "r")
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def test_invalid_mode(tmp_h5):
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with pytest.raises(ValueError):
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clawhdf5.File(tmp_h5, "x")
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def test_key_error_on_missing_dataset(sample_read_file):
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with clawhdf5.File(sample_read_file, "r") as f:
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with pytest.raises(KeyError):
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f["nonexistent"]
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