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test_v2.py
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import json
from collections.abc import Iterator
from typing import Any, Literal
import numcodecs.vlen
import numpy as np
import pytest
from numcodecs import Delta
from numcodecs.blosc import Blosc
from numcodecs.zstd import Zstd
import zarr
import zarr.core.buffer
import zarr.storage
from zarr import config
from zarr.abc.store import Store
from zarr.core.buffer.core import default_buffer_prototype
from zarr.core.sync import sync
from zarr.storage import MemoryStore, StorePath
@pytest.fixture
async def store() -> Iterator[StorePath]:
return StorePath(await MemoryStore.open())
def test_simple(store: StorePath) -> None:
data = np.arange(0, 256, dtype="uint16").reshape((16, 16))
a = zarr.create_array(
store / "simple_v2",
zarr_format=2,
shape=data.shape,
chunks=(16, 16),
dtype=data.dtype,
fill_value=0,
)
a[:, :] = data
assert np.array_equal(data, a[:, :])
@pytest.mark.parametrize("store", ["memory"], indirect=True)
@pytest.mark.parametrize(
("dtype", "fill_value"),
[
("bool", False),
("int64", 0),
("float64", 0.0),
("|S1", b""),
("|U1", ""),
("object", ""),
(str, ""),
],
)
def test_implicit_fill_value(store: MemoryStore, dtype: str, fill_value: Any) -> None:
arr = zarr.create(store=store, shape=(4,), fill_value=None, zarr_format=2, dtype=dtype)
assert arr.metadata.fill_value is None
assert arr.metadata.to_dict()["fill_value"] is None
result = arr[:]
if dtype is str:
# special case
numpy_dtype = np.dtype(object)
else:
numpy_dtype = np.dtype(dtype)
expected = np.full(arr.shape, fill_value, dtype=numpy_dtype)
np.testing.assert_array_equal(result, expected)
def test_codec_pipeline() -> None:
# https://github.com/zarr-developers/zarr-python/issues/2243
store = MemoryStore()
array = zarr.create(
store=store,
shape=(1,),
dtype="i4",
zarr_format=2,
filters=[Delta(dtype="i4").get_config()],
compressor=Blosc().get_config(),
)
array[:] = 1
result = array[:]
expected = np.ones(1)
np.testing.assert_array_equal(result, expected)
@pytest.mark.parametrize(
("dtype", "expected_dtype", "fill_value", "fill_value_encoding"),
[
("|S", "|S0", b"X", "WA=="),
("|V", "|V0", b"X", "WA=="),
("|V10", "|V10", b"X", "WAAAAAAAAAAAAA=="),
],
)
async def test_v2_encode_decode(dtype, expected_dtype, fill_value, fill_value_encoding) -> None:
with config.set(
{
"array.v2_default_filters.bytes": [{"id": "vlen-bytes"}],
"array.v2_default_compressor.bytes": None,
}
):
store = zarr.storage.MemoryStore()
g = zarr.group(store=store, zarr_format=2)
g.create_array(
name="foo", shape=(3,), chunks=(3,), dtype=dtype, fill_value=fill_value, compressor=None
)
result = await store.get("foo/.zarray", zarr.core.buffer.default_buffer_prototype())
assert result is not None
serialized = json.loads(result.to_bytes())
expected = {
"chunks": [3],
"compressor": None,
"dtype": expected_dtype,
"fill_value": fill_value_encoding,
"filters": [{"id": "vlen-bytes"}] if dtype == "|S" else None,
"order": "C",
"shape": [3],
"zarr_format": 2,
"dimension_separator": ".",
}
assert serialized == expected
data = zarr.open_array(store=store, path="foo")[:]
expected = np.full((3,), b"X", dtype=dtype)
np.testing.assert_equal(data, expected)
@pytest.mark.parametrize("dtype_value", [["|S", b"Y"], ["|U", "Y"], ["O", b"Y"]])
def test_v2_encode_decode_with_data(dtype_value):
dtype, value = dtype_value
with config.set(
{
"array.v2_default_filters": {
"string": [{"id": "vlen-utf8"}],
"bytes": [{"id": "vlen-bytes"}],
},
}
):
expected = np.full((3,), value, dtype=dtype)
a = zarr.create(
shape=(3,),
zarr_format=2,
dtype=dtype,
)
a[:] = expected
data = a[:]
np.testing.assert_equal(data, expected)
@pytest.mark.parametrize("dtype", [str, "str"])
async def test_create_dtype_str(dtype: Any) -> None:
arr = zarr.create(shape=3, dtype=dtype, zarr_format=2)
assert arr.dtype.kind == "O"
assert arr.metadata.to_dict()["dtype"] == "|O"
assert arr.metadata.filters == (numcodecs.vlen.VLenBytes(),)
arr[:] = [b"a", b"bb", b"ccc"]
result = arr[:]
np.testing.assert_array_equal(result, np.array([b"a", b"bb", b"ccc"], dtype="object"))
@pytest.mark.parametrize("filters", [[], [numcodecs.Delta(dtype="<i4")], [numcodecs.Zlib(level=2)]])
@pytest.mark.parametrize("order", ["C", "F"])
def test_v2_filters_codecs(filters: Any, order: Literal["C", "F"]) -> None:
array_fixture = [42]
with config.set({"array.order": order}):
arr = zarr.create(shape=1, dtype="<i4", zarr_format=2, filters=filters)
arr[:] = array_fixture
result = arr[:]
np.testing.assert_array_equal(result, array_fixture)
@pytest.mark.filterwarnings("ignore")
@pytest.mark.parametrize("store", ["memory"], indirect=True)
def test_create_array_defaults(store: Store):
"""
Test that passing compressor=None results in no compressor. Also test that the default value of the compressor
parameter does produce a compressor.
"""
g = zarr.open(store, mode="w", zarr_format=2)
arr = g.create_array("one", dtype="i8", shape=(1,), chunks=(1,), compressor=None)
assert arr._async_array.compressor is None
assert not (arr.filters)
arr = g.create_array("two", dtype="i8", shape=(1,), chunks=(1,))
assert arr._async_array.compressor is not None
assert not (arr.filters)
arr = g.create_array("three", dtype="i8", shape=(1,), chunks=(1,), compressor=Zstd())
assert arr._async_array.compressor is not None
assert not (arr.filters)
with pytest.raises(ValueError):
g.create_array(
"four", dtype="i8", shape=(1,), chunks=(1,), compressor=None, compressors=None
)
@pytest.mark.parametrize("array_order", ["C", "F"])
@pytest.mark.parametrize("data_order", ["C", "F"])
@pytest.mark.parametrize("memory_order", ["C", "F"])
def test_v2_non_contiguous(
array_order: Literal["C", "F"], data_order: Literal["C", "F"], memory_order: Literal["C", "F"]
) -> None:
store = MemoryStore()
arr = zarr.create_array(
store,
shape=(10, 8),
chunks=(3, 3),
fill_value=np.nan,
dtype="float64",
zarr_format=2,
filters=None,
compressors=None,
overwrite=True,
order=array_order,
config={"order": memory_order},
)
# Non-contiguous write
a = np.arange(arr.shape[0] * arr.shape[1]).reshape(arr.shape, order=data_order)
arr[6:9, 3:6] = a[6:9, 3:6] # The slice on the RHS is important
np.testing.assert_array_equal(arr[6:9, 3:6], a[6:9, 3:6])
np.testing.assert_array_equal(
a[6:9, 3:6],
np.frombuffer(
sync(store.get("2.1", default_buffer_prototype())).to_bytes(), dtype="float64"
).reshape((3, 3), order=array_order),
)
if memory_order == "F":
assert (arr[6:9, 3:6]).flags.f_contiguous
else:
assert (arr[6:9, 3:6]).flags.c_contiguous
store = MemoryStore()
arr = zarr.create_array(
store,
shape=(10, 8),
chunks=(3, 3),
fill_value=np.nan,
dtype="float64",
zarr_format=2,
compressors=None,
filters=None,
overwrite=True,
order=array_order,
config={"order": memory_order},
)
# Contiguous write
a = np.arange(9).reshape((3, 3), order=data_order)
if data_order == "F":
assert a.flags.f_contiguous
else:
assert a.flags.c_contiguous
arr[6:9, 3:6] = a
np.testing.assert_array_equal(arr[6:9, 3:6], a)
def test_default_compressor_deprecation_warning():
with pytest.warns(DeprecationWarning, match="default_compressor is deprecated"):
zarr.storage.default_compressor = "zarr.codecs.zstd.ZstdCodec()"
@pytest.mark.parametrize(
"dtype_expected",
[
["b", "zstd", None],
["i", "zstd", None],
["f", "zstd", None],
["|S1", "zstd", "vlen-bytes"],
["|U1", "zstd", "vlen-utf8"],
],
)
def test_default_filters_and_compressor(dtype_expected: Any) -> None:
with config.set(
{
"array.v2_default_compressor": {
"numeric": {"id": "zstd", "level": "0"},
"string": {"id": "zstd", "level": "0"},
"bytes": {"id": "zstd", "level": "0"},
},
"array.v2_default_filters": {
"numeric": [],
"string": [{"id": "vlen-utf8"}],
"bytes": [{"id": "vlen-bytes"}],
},
}
):
dtype, expected_compressor, expected_filter = dtype_expected
arr = zarr.create(shape=(3,), path="foo", store={}, zarr_format=2, dtype=dtype)
assert arr.metadata.compressor.codec_id == expected_compressor
if expected_filter is not None:
assert arr.metadata.filters[0].codec_id == expected_filter
@pytest.mark.parametrize("fill_value", [None, (b"", 0, 0.0)], ids=["no_fill", "fill"])
def test_structured_dtype_roundtrip(fill_value, tmp_path) -> None:
a = np.array(
[(b"aaa", 1, 4.2), (b"bbb", 2, 8.4), (b"ccc", 3, 12.6)],
dtype=[("foo", "S3"), ("bar", "i4"), ("baz", "f8")],
)
array_path = tmp_path / "data.zarr"
za = zarr.create(
shape=(3,),
store=array_path,
chunks=(2,),
fill_value=fill_value,
zarr_format=2,
dtype=a.dtype,
)
if fill_value is not None:
assert (np.array([fill_value] * a.shape[0], dtype=a.dtype) == za[:]).all()
za[...] = a
za = zarr.open_array(store=array_path)
assert (a == za[:]).all()
@pytest.mark.parametrize("fill_value", [None, b"x"], ids=["no_fill", "fill"])
def test_other_dtype_roundtrip(fill_value, tmp_path) -> None:
a = np.array([b"a\0\0", b"bb", b"ccc"], dtype="V7")
array_path = tmp_path / "data.zarr"
za = zarr.create(
shape=(3,),
store=array_path,
chunks=(2,),
fill_value=fill_value,
zarr_format=2,
dtype=a.dtype,
)
if fill_value is not None:
assert (np.array([fill_value] * a.shape[0], dtype=a.dtype) == za[:]).all()
za[...] = a
za = zarr.open_array(store=array_path)
assert (a == za[:]).all()