tsdat/io/storage/file_system.py
import logging
import shutil
from datetime import datetime
from pathlib import Path
from typing import Any, Dict, Iterable, List, Tuple, Union
import xarray as xr
from pydantic import Field, validator
from tsdat.tstring import Template
from ...utils import (
get_fields_from_dataset,
get_fields_from_datastream,
get_file_datetime_str,
)
from ..base import Storage
from ..handlers import FileHandler, NetCDFHandler
logger = logging.getLogger(__name__)
class FileSystem(Storage):
"""Handles data storage and retrieval for file-based data formats.
Formats that write to directories (such as zarr) are not supported by the FileSystem
storage class.
Args:
parameters (Parameters): File-system specific parameters, such as the root path
to where files should be saved, or additional keyword arguments to specific
functions used by the storage API. See the FileSystemStorage.Parameters
class for more details.
handler (FileHandler): The FileHandler class that should be used to handle data
I/O within the storage API.
"""
class Parameters(Storage.Parameters):
data_storage_path: Path = Path("data/{location_id}/{datastream}")
"""The directory structure under storage_root where ancillary files are saved.
Allows substitution of the following parameters using curly braces '{}':
* ``storage_root``: the value from the ``storage_root`` parameter.
* ``datastream``: the ``datastream`` as defined in the dataset config file.
* ``location_id``: the ``location_id`` as defined in the dataset config file.
* ``data_level``: the ``data_level`` as defined in the dataset config file.
* ``year``: the year of the first timestamp in the file.
* ``month``: the month of the first timestamp in the file.
* ``day``: the day of the first timestamp in the file.
* ``extension``: the file extension used by the output file writer.
Defaults to ``data/{location_id}/{datastream}``.
"""
data_filename_template: str = "{datastream}.{date_time}.{extension}"
"""Template string to use for data filenames.
Allows substitution of the following parameters using curly braces '{}':
* ``ext``: the file extension from the storage data handler
* ``datastream`` from the dataset's global attributes
* ``location_id`` from the dataset's global attributes
* ``data_level`` from the dataset's global attributes
* ``date_time``: the first timestamp in the file formatted as "YYYYMMDD.hhmmss"
* Any other global attribute that has a string or integer data type.
At a minimum the template must include ``{date_time}``.
"""
merge_fetched_data_kwargs: Dict[str, Any] = dict()
"""Keyword arguments passed to xr.merge.
Note that this will only be called if the DataReader returns a dictionary of
xr.Datasets for a single input key."""
@validator("storage_root")
def _ensure_storage_root_exists(cls, storage_root: Path) -> Path:
if not storage_root.is_dir():
logger.info("Creating storage root at: %s", storage_root.as_posix())
storage_root.mkdir(parents=True)
return storage_root
parameters: Parameters = Field(default_factory=Parameters) # type: ignore
handler: FileHandler = Field(default_factory=NetCDFHandler)
def save_ancillary_file(
self, filepath: Path, target_path: Union[Path, None] = None
):
"""Saves an ancillary filepath to the datastream's ancillary storage area.
NOTE: In most cases this function should not be used directly. Instead, prefer
using the ``self.uploadable_dir(*args, **kwargs)`` method.
Args:
filepath (Path): The path to the ancillary file. This is expected to have
a standardized filename and should be saved under the ancillary storage
path.
target_path (str): The path to where the data should be saved.
"""
target_path.parent.mkdir(exist_ok=True, parents=True)
saved_filepath = shutil.copy2(filepath, target_path)
logger.info("Saved ancillary file to: %s", saved_filepath)
def save_data(self, dataset: xr.Dataset, **kwargs: Any):
"""-----------------------------------------------------------------------------
Saves a dataset to the storage area.
At a minimum, the dataset must have a 'datastream' global attribute and must
have a 'time' variable with a np.datetime64-like data type.
Args:
dataset (xr.Dataset): The dataset to save.
-----------------------------------------------------------------------------"""
datastream = dataset.attrs["datastream"]
filepath = self._get_dataset_filepath(dataset)
filepath.parent.mkdir(exist_ok=True, parents=True)
self.handler.writer.write(dataset, filepath)
logger.info("Saved %s dataset to %s", datastream, filepath.as_posix())
def fetch_data(
self,
start: datetime,
end: datetime,
datastream: str,
metadata_kwargs: Union[Dict[str, str], None] = None,
**kwargs: Any,
) -> xr.Dataset:
"""-----------------------------------------------------------------------------
Fetches data for a given datastream between a specified time range.
Args:
start (datetime): The minimum datetime to fetch.
end (datetime): The maximum datetime to fetch.
datastream (str): The datastream id to search for.
metadata_kwargs (dict[str, str], optional): Metadata substitutions to help
resolve the data storage path. This is only required if the template
data storage path includes any properties other than datastream or
fields contained in the datastream. Defaults to None.
Returns:
xr.Dataset: A dataset containing all the data in the storage area that spans
the specified datetimes.
-----------------------------------------------------------------------------"""
if metadata_kwargs is None:
metadata_kwargs = {}
metadata_kwargs = {
"datastream": datastream,
**get_fields_from_datastream(datastream),
**metadata_kwargs,
}
data_files = self._find_data(
start,
end,
datastream,
metadata_kwargs=metadata_kwargs,
)
datasets = self._open_data_files(*data_files)
dataset = xr.merge(datasets, **self.parameters.merge_fetched_data_kwargs) # type: ignore
if not dataset:
logger.warning(
"No data found for %s in range %s - %s", datastream, start, end
)
return dataset # empty
return dataset.sel(time=slice(start, end))
def _find_data(
self,
start: datetime,
end: datetime,
datastream: str,
metadata_kwargs: Dict[str, str],
**kwargs: Any,
) -> List[Path]:
dir_template = Template(self.parameters.data_storage_path.as_posix())
extension = self.handler.writer.file_extension
semi_resolved = dir_template.substitute(
{
**dict(
datastream=datastream,
extension=extension,
ext=extension,
),
**metadata_kwargs,
},
allow_missing=True,
)
dirpath, pattern = self._extract_time_substitutions(semi_resolved, start, end)
dirpath = self.parameters.storage_root / dirpath
filepaths = (p for p in dirpath.glob(pattern))
return self._filter_between_dates(filepaths, start, end)
@staticmethod
def _filter_between_dates(
filepaths: Iterable[Path], start: datetime, end: datetime
) -> List[Path]:
start_date_str = start.strftime("%Y%m%d.%H%M%S")
end_date_str = end.strftime("%Y%m%d.%H%M%S")
valid_filepaths: List[Path] = []
for filepath in filepaths:
file_date_str = get_file_datetime_str(filepath)
if start_date_str <= file_date_str <= end_date_str:
valid_filepaths.append(filepath)
return valid_filepaths
def _open_data_files(self, *filepaths: Path) -> List[xr.Dataset]:
dataset_list: List[xr.Dataset] = []
for filepath in filepaths:
data = self.handler.reader.read(filepath.as_posix())
if isinstance(data, dict):
data = xr.merge(data.values()) # type: ignore
dataset_list.append(data)
return dataset_list
def _get_dataset_filepath(self, dataset: xr.Dataset) -> Path:
extension = self.handler.writer.file_extension
substitutions = get_fields_from_dataset(dataset)
substitutions.update(extension=extension, ext=extension)
data_dir = self._get_data_directory(substitutions)
filename_template = Template(self.parameters.data_filename_template)
filename = filename_template.substitute(substitutions)
return data_dir / filename
def _get_data_directory(self, substitutions: Dict[str, str]) -> Path:
dir_template = Template(self.parameters.data_storage_path.as_posix())
dirpath = dir_template.substitute(substitutions)
return self.parameters.storage_root / dirpath
@staticmethod
def _extract_time_substitutions(
template_str: str, start: datetime, end: datetime
) -> Tuple[Path, str]:
"""Extracts the root path above unresolved time substitutions and provides a pattern to search below that."""
year = start.strftime("%Y") if start.year == end.year else "*"
month = (
start.strftime("%m") if year != "*" and start.month == end.month else "*"
)
resolved = Template(template_str).substitute(year=year, month=month, day="*")
if (split := resolved.find("*")) != -1:
return Path(resolved[:split]), resolved[split:] + "/*"
return Path(resolved), "*"
# TODO:
# HACK: Update forward refs to get around error I couldn't replicate with simpler code
# "pydantic.errors.ConfigError: field "parameters" not yet prepared
# so type is still a ForwardRef..."
FileSystem.update_forward_refs(Parameters=FileSystem.Parameters)