ImportError: cannot import name 'clean_data_dir' from 'sklift.datasets'

[TDL77]

🐛 Bug

To Reproduce

Steps to reproduce the behavior:

1.from sklift.datasets import fetch_x5
1.dataset = fetch_x5()
1.

Expected behavior

Environment

• scikit-uplift version (e.g., 0.1.2):
• scikit-learn version (e.g., 0.22.2):
• Python version (e.g., 3.7):
• OS (e.g., Linux):
• Any other relevant information:

Additional context

---

ValueError Traceback (most recent call last)
Cell In[7], line 1
----> 1 dataset = fetch_x5()
2 dataset.data.keys()

File ~/mambaforge/envs/main/lib/python3.11/site-packages/sklift/datasets/datasets.py:333, in fetch_x5(data_home, dest_subdir, download_if_missing)
327 csv_purchases_path = _get_data(data_home=data_home, url=x5_metadata['url_purchases'], dest_subdir=dest_subdir,
328 dest_filename=file_purchases,
329 download_if_missing=download_if_missing,
330 desc=x5_metadata['desc_purchases'])
332 if _get_file_hash(csv_purchases_path) != x5_metadata['hash_purchases']:
--> 333 raise ValueError(f"The {file_purchases} file is broken, please clean the directory "
334 f"with the clean_data_dir() function, and run the function again")
336 purchases = pd.read_csv(csv_purchases_path)
337 purchases_features = list(purchases.columns)

ValueError: The purchases.csv.gz file is broken, please clean the directory with the clean_data_dir() function, and run the function again

[TDL77]

from sklift.datasets import fetch_x5
dataset = fetch_x5(data_home='./my_data')

вот так проблема решилась