Support paths as strings in public fetching API (skrub-data#453)

* Add target directory as optional argument

* Add changelog entry

* Support str in public fetching API

* Update changelog entry

* Make paths absolute

* Remove unnecessary path conversion in test

CHANGES.rst

@@ -50,6 +50,10 @@ Minor changes
  which can be used to specify where to save and load from datasets.
  :pr:`432` by :user:`Lilian Boulard <LilianBoulard>`
 
+* Fetching functions now have an additional argument ``directory``,
+ which can be used to specify where to save and load from datasets.
+ :pr:`432` and :pr:`453` by :user:`Lilian Boulard <LilianBoulard>`
+
 * The :class:`TableVectorizer`'s default `OneHotEncoder` for low cardinality categorical variables now defaults
  to `handle_unknown="ignore"` instead of `handle_unknown="error"` (for sklearn >= 1.0.0).
  This means that categories seen only at test time will be encoded by a vector of zeroes instead of raising an error. :pr:`473` by :user:`Leo Grinsztajn <LeoGrin>`

dirty_cat/datasets/_fetching.py

@@ -18,7 +18,7 @@
 from dataclasses import dataclass
 from itertools import chain
 from pathlib import Path
-from typing import Any, Dict, List, Optional, Union
+from typing import Any, Dict, List, Optional, TextIO, Union
 from urllib.error import URLError
 from zipfile import BadZipFile, ZipFile
 
@@ -530,6 +530,7 @@ def _export_gz_data_to_csv(
  atdata_found = False
  with destination_file.open(mode="w", encoding="utf8") as csv:
  with gzip.open(compressed_dir_path, mode="rt", encoding="utf8") as gz:
+ gz: TextIO # Clarify for IDEs
  csv.write(_features_to_csv_format(features))
  csv.write("\n")
  # We will look at each line of the file until we find
@@ -552,7 +553,7 @@ def _fetch_dataset_as_dataclass(
  dataset_id: Union[int, str],
  target: Optional[str],
  load_dataframe: bool,
- data_directory: Optional[Path] = None,
+ data_directory: Optional[Union[Path, str]] = None,
  read_csv_kwargs: Optional[dict] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """
@@ -582,6 +583,9 @@ def _fetch_dataset_as_dataclass(
  If `load_dataframe=False`
 
  """
+ if isinstance(data_directory, str):
+ data_directory = Path(data_directory)
+
  if source == "openml":
  info = _fetch_openml_dataset(dataset_id, data_directory)
  elif source == "world_bank":
@@ -635,7 +639,7 @@ def fetch_employee_salaries(
  load_dataframe: bool = True,
  drop_linked: bool = True,
  drop_irrelevant: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the employee_salaries dataset (regression), available at
  https://openml.org/d/42125
@@ -689,7 +693,7 @@ def fetch_employee_salaries(
 
 def fetch_road_safety(
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the road safety dataset (classification), available at
  https://openml.org/d/42803
@@ -723,7 +727,7 @@ def fetch_road_safety(
 
 def fetch_medical_charge(
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the medical charge dataset (regression), available at
  https://openml.org/d/42720
@@ -762,7 +766,7 @@ def fetch_medical_charge(
 
 def fetch_midwest_survey(
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the midwest survey dataset (classification), available at
  https://openml.org/d/42805
@@ -794,7 +798,7 @@ def fetch_midwest_survey(
 
 def fetch_open_payments(
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the open payments dataset (classification), available at
  https://openml.org/d/42738
@@ -828,7 +832,7 @@ def fetch_open_payments(
 
 def fetch_traffic_violations(
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the traffic violations dataset (classification), available at
  https://openml.org/d/42132
@@ -864,7 +868,7 @@ def fetch_traffic_violations(
 
 def fetch_drug_directory(
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches the drug directory dataset (classification), available at
  https://openml.org/d/43044
@@ -898,7 +902,7 @@ def fetch_drug_directory(
 def fetch_world_bank_indicator(
  indicator_id: str,
  load_dataframe: bool = True,
- directory: Optional[Path] = None,
+ directory: Optional[Union[Path, str]] = None,
 ) -> Union[DatasetAll, DatasetInfoOnly]:
  """Fetches a dataset of an indicator from the World Bank
  open data platform.

dirty_cat/datasets/tests/test_fetching.py

@@ -1,4 +1,3 @@
-from pathlib import Path
 from tempfile import TemporaryDirectory
 from typing import Callable, Tuple
 from unittest import mock
@@ -41,10 +40,6 @@ def test_openml_fetching(
  Test a function that loads data from OpenML.
  """
  with TemporaryDirectory() as temp_dir_1, TemporaryDirectory() as temp_dir_2:
- # Convert to path objects
- temp_dir_1 = Path(temp_dir_1).absolute()
- temp_dir_2 = Path(temp_dir_2).absolute()
-
  # Fetch without loading into memory
  try:
  dataset_wo_load: _fetching.DatasetInfoOnly = fetching_function(
@@ -126,7 +121,6 @@ def test_fetch_world_bank_indicator():
  }
 
  with TemporaryDirectory() as temp_dir:
- temp_dir = Path(temp_dir).absolute()
  try:
  # First, we want to purposefully test FileNotFoundError exceptions.
  with pytest.raises(FileNotFoundError):