Merge pull request #28 from p2p-ld/hdf5-3_12
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close hdf5 files, use hdfpy 3.12
This commit is contained in:
Jonny Saunders 2024-09-26 20:12:15 -07:00 committed by GitHub
commit 69dbe39557
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GPG key ID: B5690EEEBB952194
5 changed files with 71 additions and 58 deletions

3
.gitignore vendored
View file

@ -161,4 +161,5 @@ cython_debug/
.pdm-python
ndarray.pyi
prof/
prof/
__tmp__

View file

@ -4,7 +4,15 @@
### 1.6.*
#### 1.6.2 - 24-09-35
#### 1.6.3 - 24-09-26
**Bugfix**
- h5py v3.12.0 was actually fine, but we did need to change the way that
the hdf5 tests work to not hold the file open during the test. Easy enough change.
the version cap has been removed from h5py (which is optional anyway,
so any version could be installed separately)
#### 1.6.2 - 24-09-25
Very minor bugfix and CI release

View file

@ -5,7 +5,7 @@
groups = ["default", "arrays", "dask", "dev", "docs", "hdf5", "tests", "video", "zarr"]
strategy = ["cross_platform", "inherit_metadata"]
lock_version = "4.5.0"
content_hash = "sha256:dee4ba1fabeacedf80f85b145bcb2ef83a2005cac6454f9672eb9a873cadd70b"
content_hash = "sha256:cc2b0fb32896c6df0ad747ddb5dee89af22f5c4c4643ee7a52db47fef30da936"
[[metadata.targets]]
requires_python = "~=3.9"
@ -731,31 +731,40 @@ files = [
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name = "h5py"
version = "3.11.0"
requires_python = ">=3.8"
version = "3.12.1"
requires_python = ">=3.9"
summary = "Read and write HDF5 files from Python"
groups = ["arrays", "dev", "docs", "hdf5", "tests"]
dependencies = [
"numpy>=1.17.3",
"numpy>=1.19.3",
]
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View file

@ -1,6 +1,6 @@
[project]
name = "numpydantic"
version = "1.6.2"
version = "1.6.3"
description = "Type and shape validation and serialization for arbitrary array types in pydantic models"
authors = [
{name = "sneakers-the-rat", email = "sneakers-the-rat@protonmail.com"},
@ -53,8 +53,7 @@ dask = [
"dask>=2024.4.0",
]
hdf5 = [
"h5py>=3.10.0,<3.12.0;sys_platform!='darwin'",
"h5py>=3.10.0;sys_platform=='darwin'",
"h5py>=3.10.0",
]
video = [
"opencv-python>=4.9.0.80",

View file

@ -104,18 +104,11 @@ def model_blank() -> Type[BaseModel]:
return BlankModel
@pytest.fixture(scope="function")
def hdf5_file(tmp_output_dir_func) -> h5py.File:
h5f_file = tmp_output_dir_func / "h5f.h5"
h5f = h5py.File(h5f_file, "w")
yield h5f
h5f.close()
@pytest.fixture(scope="function")
def hdf5_array(
hdf5_file, request
request, tmp_output_dir_func
) -> Callable[[Tuple[int, ...], Union[np.dtype, type]], H5ArrayPath]:
hdf5_file = tmp_output_dir_func / "h5f.h5"
def _hdf5_array(
shape: Tuple[int, ...] = (10, 10),
@ -132,8 +125,8 @@ def hdf5_array(
data.fill(datetime.now(timezone.utc).isoformat().encode("utf-8"))
else:
data = np.random.random(shape).astype(dtype)
_ = hdf5_file.create_dataset(array_path, data=data)
return H5ArrayPath(Path(hdf5_file.filename), array_path)
h5path = H5ArrayPath(hdf5_file, array_path)
else:
if dtype is str:
dt = np.dtype([("data", np.dtype("S10")), ("extra", "i8")])
@ -148,8 +141,11 @@ def hdf5_array(
else:
dt = np.dtype([("data", dtype), ("extra", "i8")])
data = np.zeros(shape, dtype=dt)
_ = hdf5_file.create_dataset(array_path, data=data)
return H5ArrayPath(Path(hdf5_file.filename), array_path, "data")
h5path = H5ArrayPath(hdf5_file, array_path, "data")
with h5py.File(hdf5_file, "w") as h5f:
_ = h5f.create_dataset(array_path, data=data)
return h5path
return _hdf5_array