def test_inferr_file_format_no_extension(tmp_path: Path):
"""Raise error if file has no extension."""
file_path = tmp_path / "dummy"
file_path.touch()
with pytest.raises(
ValueError,
match=
"Cannot determine format of file .+?, please provide an explicit format"
):
inferr_file_format(file_path)
def load_parameters(file_name: StrOrPath, format_name: str = None, **kwargs) -> ParameterGroup:
"""Create a :class:`ParameterGroup` instance from the specs defined in a file.
Parameters
----------
file_name : StrOrPath
File containing the parameter specs.
format_name : str
Format the file is in, if not provided it will be inferred from the file extension.
**kwargs: Any
Additional keyword arguments passes to the ``load_parameters`` implementation
of the project io plugin.
Returns
-------
ParameterGroup
:class:`ParameterGroup` instance created from the file.
"""
io = get_project_io(format_name or inferr_file_format(file_name))
parameters = io.load_parameters( # type: ignore[call-arg]
Path(file_name).as_posix(),
**kwargs,
)
parameters.source_path = Path(file_name).as_posix()
return parameters
def test_inferr_file_format_allow_folder(tmp_path: Path, is_file: bool):
"""If there is no extension, return folder."""
file_path = tmp_path / "dummy"
if is_file:
file_path.touch()
assert inferr_file_format(file_path, allow_folder=True) == "folder"
def save_dataset(
file_name: str,
dataset: xr.Dataset | xr.DataArray,
format_name: str = None,
*,
allow_overwrite: bool = False,
**kwargs: Any,
) -> None:
"""Save data from :xarraydoc:`Dataset` or :xarraydoc:`DataArray` to a file.
Parameters
----------
file_name : str
File to write the data to.
format_name : str
Format the file should be in, if not provided it will be inferred from the file extension.
dataset: xr.Dataset|xr.DataArray
Data to be written to file.
allow_overwrite : bool
Whether or not to allow overwriting existing files, by default False
**kwargs: Any
Additional keyword arguments passes to the ``write_dataset`` implementation
of the data io plugin. If you aren't sure about those use ``get_datawriter``
to get the implementation with the proper help and autocomplete.
"""
protect_from_overwrite(file_name, allow_overwrite=allow_overwrite)
io = get_data_io(format_name or inferr_file_format(file_name, needs_to_exist=False))
io.save_dataset( # type: ignore[call-arg]
file_name=file_name,
dataset=dataset,
**kwargs,
)
def save_result(
result_path: str,
result: Result,
format_name: str = None,
*,
allow_overwrite: bool = False,
**kwargs: Any,
) -> None:
"""Write a :class:`Result` instance to a spec file.
Parameters
----------
result_path : str
Path to write the result data to.
result : Result
:class:`Result` instance to write.
format_name : str
Format the result should be saved in, if not provided and it is a file
it will be inferred from the file extension.
allow_overwrite : bool
Whether or not to allow overwriting existing files, by default False
**kwargs: Any
Additional keyword arguments passes to the ``save_result`` implementation
of the project io plugin.
"""
protect_from_overwrite(result_path, allow_overwrite=allow_overwrite)
io = get_project_io(format_name or inferr_file_format(
result_path, needs_to_exist=False, allow_folder=True))
io.save_result( # type: ignore[call-arg]
result_path=result_path,
result=result,
**kwargs,
)
def save_scheme(
file_name: str,
scheme: Scheme,
format_name: str = None,
*,
allow_overwrite: bool = False,
**kwargs: Any,
) -> None:
"""Save a :class:`Scheme` instance to a spec file.
Parameters
----------
file_name : str
File to write the scheme specs to.
scheme : Scheme
:class:`Scheme` instance to save to specs file.
format_name : str
Format the file should be in, if not provided it will be inferred from the file extension.
allow_overwrite : bool
Whether or not to allow overwriting existing files, by default False
**kwargs: Any
Additional keyword arguments passes to the ``save_scheme`` implementation
of the project io plugin.
"""
protect_from_overwrite(file_name, allow_overwrite=allow_overwrite)
io = get_project_io(format_name
or inferr_file_format(file_name, needs_to_exist=False))
io.save_scheme(file_name=file_name, scheme=scheme,
**kwargs) # type: ignore[call-arg]
def load_dataset(file_name: StrOrPath,
format_name: str = None,
**kwargs: Any) -> xr.Dataset:
"""Read data from a file to :xarraydoc:`Dataset` or :xarraydoc:`DataArray`.
Parameters
----------
file_name : StrOrPath
File containing the data.
format_name : str
Format the file is in, if not provided it will be inferred from the file extension.
**kwargs : Any
Additional keyword arguments passes to the ``read_dataset`` implementation
of the data io plugin. If you aren't sure about those use ``get_dataloader``
to get the implementation with the proper help and autocomplete.
Returns
-------
xr.Dataset
Data loaded from the file.
"""
io = get_data_io(format_name or inferr_file_format(file_name))
dataset = io.load_dataset(Path(file_name).as_posix(),
**kwargs) # type: ignore[call-arg]
if isinstance(dataset, xr.DataArray):
dataset = dataset.to_dataset(name="data")
dataset.attrs["loader"] = load_dataset
dataset.attrs["source_path"] = Path(file_name).as_posix()
return dataset
def save_result(
result: Result,
result_path: StrOrPath,
format_name: str = None,
*,
allow_overwrite: bool = False,
update_source_path: bool = True,
saving_options: SavingOptions = SAVING_OPTIONS_DEFAULT,
**kwargs: Any,
) -> list[str]:
"""Write a :class:`Result` instance to a spec file.
Parameters
----------
result : Result
:class:`Result` instance to write.
result_path : StrOrPath
Path to write the result data to.
format_name : str
Format the result should be saved in, if not provided and it is a file
it will be inferred from the file extension.
allow_overwrite : bool
Whether or not to allow overwriting existing files, by default False
update_source_path: bool
Whether or not to update the ``source_path`` attribute to ``result_path`` when saving.
by default True
saving_options : SavingOptions
Options for the saved result.
**kwargs : Any
Additional keyword arguments passes to the ``save_result`` implementation
of the project io plugin.
Returns
-------
list[str] | None
List of file paths which were saved.
"""
protect_from_overwrite(result_path, allow_overwrite=allow_overwrite)
io = get_project_io(
format_name or inferr_file_format(result_path, needs_to_exist=False, allow_folder=True)
)
paths = io.save_result( # type: ignore[call-arg]
result_path=Path(result_path).as_posix(),
result=result,
saving_options=saving_options,
**kwargs,
)
if update_source_path is True:
result.source_path = Path(result_path).as_posix()
return paths
def save_dataset(
dataset: xr.Dataset | xr.DataArray,
file_name: StrOrPath,
format_name: str = None,
*,
data_filters: list[str] | None = None,
allow_overwrite: bool = False,
update_source_path: bool = True,
**kwargs: Any,
) -> None:
"""Save data from :xarraydoc:`Dataset` or :xarraydoc:`DataArray` to a file.
Parameters
----------
dataset : xr.Dataset | xr.DataArray
Data to be written to file.
file_name : StrOrPath
File to write the data to.
format_name : str
Format the file should be in, if not provided it will be inferred from the file extension.
data_filters : list[str] | None
Optional list of items in the dataset to be saved.
allow_overwrite : bool
Whether or not to allow overwriting existing files, by default False
update_source_path: bool
Whether or not to update the ``source_path`` attribute to ``file_name`` when saving.
by default True
**kwargs : Any
Additional keyword arguments passes to the ``write_dataset`` implementation
of the data io plugin. If you aren't sure about those use ``get_datawriter``
to get the implementation with the proper help and autocomplete.
"""
protect_from_overwrite(file_name, allow_overwrite=allow_overwrite)
io = get_data_io(format_name
or inferr_file_format(file_name, needs_to_exist=False))
if "loader" in dataset.attrs:
del dataset.attrs["loader"]
if "source_path" in dataset.attrs:
orig_source_path: str = dataset.attrs["source_path"]
del dataset.attrs["source_path"]
io.save_dataset( # type: ignore[call-arg]
file_name=Path(file_name).as_posix(),
dataset=dataset,
**kwargs,
)
dataset.attrs["loader"] = load_dataset
if update_source_path is True or "orig_source_path" not in locals():
dataset.attrs["source_path"] = Path(file_name).as_posix()
else:
dataset.attrs["source_path"] = Path(orig_source_path).as_posix()
def load_model(file_name: StrOrPath, format_name: str = None, **kwargs: Any) -> Model:
"""Create a Model instance from the specs defined in a file.
Parameters
----------
file_name : StrOrPath
File containing the model specs.
format_name : str
Format the file is in, if not provided it will be inferred from the file extension.
**kwargs: Any
Additional keyword arguments passes to the ``load_model`` implementation
of the project io plugin.
Returns
-------
Model
Model instance created from the file.
"""
io = get_project_io(format_name or inferr_file_format(file_name))
model = io.load_model(Path(file_name).as_posix(), **kwargs) # type: ignore[call-arg]
model.source_path = Path(file_name).as_posix()
return model
def load_scheme(file_name: str,
format_name: str = None,
**kwargs: Any) -> Scheme:
"""Create a :class:`Scheme` instance from the specs defined in a file.
Parameters
----------
file_name : str
File containing the parameter specs.
format_name : str
Format the file is in, if not provided it will be inferred from the file extension.
**kwargs: Any
Additional keyword arguments passes to the ``load_scheme`` implementation
of the project io plugin.
Returns
-------
Scheme
:class:`Scheme` instance created from the file.
"""
io = get_project_io(format_name or inferr_file_format(file_name))
return io.load_scheme(file_name, **kwargs) # type: ignore[call-arg]
def load_dataset(
file_name: str, format_name: str = None, **kwargs: Any
) -> xr.Dataset | xr.DataArray:
"""Read data from a file to :xarraydoc:`Dataset` or :xarraydoc:`DataArray`.
Parameters
----------
file_name : str
File containing the data.
format_name : str
Format the file is in, if not provided it will be inferred from the file extension.
**kwargs: Any
Additional keyword arguments passes to the ``read_dataset`` implementation
of the data io plugin. If you aren't sure about those use ``get_dataloader``
to get the implementation with the proper help and autocomplete.
Returns
-------
xr.Dataset|xr.DataArray
Data loaded from the file.
"""
io = get_data_io(format_name or inferr_file_format(file_name))
return io.load_dataset(file_name, **kwargs) # type: ignore[call-arg]
def load_result(result_path: str,
format_name: str = None,
**kwargs: Any) -> Result:
"""Create a :class:`Result` instance from the specs defined in a file.
Parameters
----------
result_path : str
Path containing the result data.
format_name : str
Format the result is in, if not provided and it is a file
it will be inferred from the file extension.
**kwargs: Any
Additional keyword arguments passes to the ``load_result`` implementation
of the project io plugin.
Returns
-------
Result
:class:`Result` instance created from the saved format.
"""
io = get_project_io(format_name or inferr_file_format(result_path))
return io.load_result(result_path, **kwargs) # type: ignore[call-arg]
def save_scheme(
scheme: Scheme,
file_name: StrOrPath,
format_name: str = None,
*,
allow_overwrite: bool = False,
update_source_path: bool = True,
**kwargs: Any,
) -> None:
"""Save a :class:`Scheme` instance to a spec file.
Parameters
----------
scheme : Scheme
:class:`Scheme` instance to save to specs file.
file_name : StrOrPath
File to write the scheme specs to.
format_name : str
Format the file should be in, if not provided it will be inferred from the file extension.
allow_overwrite : bool
Whether or not to allow overwriting existing files, by default False
update_source_path: bool
Whether or not to update the ``source_path`` attribute to ``file_name`` when saving.
by default True
**kwargs : Any
Additional keyword arguments passes to the ``save_scheme`` implementation
of the project io plugin.
"""
protect_from_overwrite(file_name, allow_overwrite=allow_overwrite)
io = get_project_io(format_name or inferr_file_format(file_name, needs_to_exist=False))
io.save_scheme( # type: ignore[call-arg]
file_name=Path(file_name).as_posix(),
scheme=scheme,
**kwargs,
)
if update_source_path is True:
scheme.source_path = Path(file_name).as_posix()
def test_inferr_file_format_none_existing_file():
"""Raise error if file does not exists."""
with pytest.raises(ValueError, match="There is no file "):
inferr_file_format("none-existing-file.yml")
def test_inferr_file_format(tmp_path: Path, extension: str, expected: str):
"""Inferr type from existing files with extension."""
file_path = tmp_path / f"dummy.{extension}"
file_path.touch()
assert inferr_file_format(file_path) == expected
