rename work_dir to metadata_cache
MODIFY
pangeo_forge_recipes/recipes/reference_hdf_zarr.py
pangeo_forge_recipes/recipes/reference_hdf_zarr.py
@@ -73,7 +73,7 @@ class ReferenceHDFRecipe(BaseRecipe):
netcdf_url: Union[str, List[str]]
output_url: str
output_target: FSSpecTarget
- _work_dir: MetadataTarget
+ metadata_cache: MetadataTarget
netcdf_storage_options: dict = field(default_factory=dict)
inline_threshold: int = 500
output_storage_options: dict = field(default_factory=dict)
@@ -103,7 +103,7 @@ class ReferenceHDFRecipe(BaseRecipe):
def store_chunk(self) -> Callable[[Hashable], None]:
"""Store a chunk of data in the target.
"""
- return functools.partial(_one_chunk, work_dir=self._work_dir)
+ return functools.partial(_one_chunk, metadata_cache=self.metadata_cache)
@property
def finalize_target(self) -> Callable[[], None]:
@@ -116,7 +116,7 @@ class ReferenceHDFRecipe(BaseRecipe):
proto = fsspec.utils.get_protocol(self.netcdf_url[0])
return functools.partial(
_finalize,
- work_dir=self._work_dir,
+ metadata_cache=self.metadata_cache,
out_url=self.output_url,
out_target=self.output_target,
out_so=self.output_storage_options,
@@ -128,15 +128,15 @@ class ReferenceHDFRecipe(BaseRecipe):
)
-def _one_chunk(of, work_dir):
+def _one_chunk(of, metadata_cache):
with of as f:
fn = os.path.basename(f.name + ".json")
h5chunks = SingleHdf5ToZarr(f, _unstrip_protocol(f.name, f.fs), inline_threshold=300)
- work_dir[fn] = h5chunks.translate()
+ metadata_cache[fn] = h5chunks.translate()
def _finalize(
- work_dir,
+ metadata_cache,
out_url,
out_target,
out_so,
@@ -147,7 +147,7 @@ def _finalize(
template_count,
):
files = list(
- work_dir.getitems(list(work_dir.get_mapper())).values()
+ metadata_cache.getitems(list(metadata_cache.get_mapper())).values()
) # returns dicts from remote
if len(files) == 1:
out = files[0]

rename work_dir to metadata_cache