Download all files (#1188)

* Towards downloading buckets

* Download entire bucket instead of dataset file

* Dont download arff, skip files already cached

* Automatically unzip any downloaded archives

* Make downloading the bucket optional

Additionally, rename old cached files to the new filename format.

* Allow users to download the full bucket when pq is already cached

Otherwise the only way would be to delete the cache.

* Add unit test stub

* Remove redundant try/catch

* Remove commented out print statement

* Still download arff

* Towards downloading buckets

* Download entire bucket instead of dataset file

* Dont download arff, skip files already cached

* Automatically unzip any downloaded archives

* Make downloading the bucket optional

Additionally, rename old cached files to the new filename format.

* Allow users to download the full bucket when pq is already cached

Otherwise the only way would be to delete the cache.

* Add unit test stub

* Remove redundant try/catch

* Remove commented out print statement

* Still download arff

* ADD: download all files from minio bucket

* Add note for #1184

* Fix pre-commit issues (mypy, flake)

Co-authored-by: Matthias Feurer <[email protected]>

doc/progress.rst

@@ -12,10 +12,12 @@ Changelog
  * FIX#1058, #1100: Avoid ``NoneType`` error when printing task without ``class_labels`` attribute.
  * FIX#1110: Make arguments to ``create_study`` and ``create_suite`` that are defined as optional by the OpenML XSD actually optional.
  * FIX#1147: ``openml.flow.flow_exists`` no longer requires an API key.
+ * FIX#1184: Automatically resolve proxies when downloading from minio. Turn this off by setting environment variable ``no_proxy="*"``.
  * MAIN#1088: Do CI for Windows on Github Actions instead of Appveyor.
  * MAINT#1104: Fix outdated docstring for ``list_task``.
  * MAIN#1146: Update the pre-commit dependencies.
  * ADD#1103: Add a ``predictions`` property to OpenMLRun for easy accessibility of prediction data.
+ * ADD#1188: EXPERIMENTAL. Allow downloading all files from a minio bucket with ``download_all_files=True`` for ``get_dataset``.
 
 
 0.12.2

openml/_api_calls.py

@@ -12,6 +12,7 @@
 import xmltodict
 from urllib3 import ProxyManager
 from typing import Dict, Optional, Union
+import zipfile
 
 import minio
 
@@ -44,6 +45,7 @@ def resolve_env_proxies(url: str) -> Optional[str]:
     selected_proxy = requests.utils.select_proxy(url, resolved_proxies)
     return selected_proxy
 
+
 def _create_url_from_endpoint(endpoint: str) -> str:
     url = config.server
     if not url.endswith("/"):
@@ -137,18 +139,18 @@ def _download_minio_file(
 
     proxy_client = ProxyManager(proxy) if proxy else None
 
-    client = minio.Minio(
-        endpoint=parsed_url.netloc,
-        secure=False,
-        http_client=proxy_client
-    )
+    client = minio.Minio(endpoint=parsed_url.netloc, secure=False, http_client=proxy_client)
 
     try:
         client.fget_object(
             bucket_name=bucket,
             object_name=object_name,
             file_path=str(destination),
         )
+        if destination.is_file() and destination.suffix == ".zip":
+            with zipfile.ZipFile(destination, "r") as zip_ref:
+                zip_ref.extractall(destination.parent)
+
     except minio.error.S3Error as e:
         if e.message.startswith("Object does not exist"):
             raise FileNotFoundError(f"Object at '{source}' does not exist.") from e
@@ -157,6 +159,39 @@ def _download_minio_file(
         raise FileNotFoundError("Bucket does not exist or is private.") from e
 
 
+def _download_minio_bucket(
+    source: str,
+    destination: Union[str, pathlib.Path],
+    exists_ok: bool = True,
+) -> None:
+    """Download file ``source`` from a MinIO Bucket and store it at ``destination``.
+
+    Parameters
+    ----------
+    source : Union[str, pathlib.Path]
+        URL to a MinIO bucket.
+    destination : str
+        Path to a directory to store the bucket content in.
+    exists_ok : bool, optional (default=True)
+        If False, raise FileExists if a file already exists in ``destination``.
+    """
+
+    destination = pathlib.Path(destination)
+    parsed_url = urllib.parse.urlparse(source)
+
+    # expect path format: /BUCKET/path/to/file.ext
+    bucket = parsed_url.path[1:]
+
+    client = minio.Minio(endpoint=parsed_url.netloc, secure=False)
+
+    for file_object in client.list_objects(bucket, recursive=True):
+        _download_minio_file(
+            source=source + "/" + file_object.object_name,
+            destination=pathlib.Path(destination, file_object.object_name),
+            exists_ok=True,
+        )
+
+
 def _download_text_file(
     source: str,
     output_path: Optional[str] = None,

openml/datasets/functions.py

@@ -5,6 +5,7 @@
 import os
 from pyexpat import ExpatError
 from typing import List, Dict, Union, Optional, cast
+import warnings
 
 import numpy as np
 import arff
@@ -356,6 +357,7 @@ def get_dataset(
     error_if_multiple: bool = False,
     cache_format: str = "pickle",
     download_qualities: bool = True,
+    download_all_files: bool = False,
 ) -> OpenMLDataset:
     """Download the OpenML dataset representation, optionally also download actual data file.
 
@@ -389,11 +391,20 @@ def get_dataset(
         no.of.rows is very high.
     download_qualities : bool (default=True)
         Option to download 'qualities' meta-data in addition to the minimal dataset description.
+    download_all_files: bool (default=False)
+        EXPERIMENTAL. Download all files related to the dataset that reside on the server.
+        Useful for datasets which refer to auxiliary files (e.g., meta-album).
+
     Returns
     -------
     dataset : :class:`openml.OpenMLDataset`
         The downloaded dataset.
     """
+    if download_all_files:
+        warnings.warn(
+            "``download_all_files`` is experimental and is likely to break with new releases."
+        )
+
     if cache_format not in ["feather", "pickle"]:
         raise ValueError(
             "cache_format must be one of 'feather' or 'pickle. "
@@ -434,7 +445,12 @@ def get_dataset(
 
         arff_file = _get_dataset_arff(description) if download_data else None
         if "oml:minio_url" in description and download_data:
-            parquet_file = _get_dataset_parquet(description)
+            try:
+                parquet_file = _get_dataset_parquet(
+                    description, download_all_files=download_all_files
+                )
+            except urllib3.exceptions.MaxRetryError:
+                parquet_file = None
         else:
             parquet_file = None
         remove_dataset_cache = False
@@ -967,7 +983,9 @@ def _get_dataset_description(did_cache_dir, dataset_id):
 
 
 def _get_dataset_parquet(
-    description: Union[Dict, OpenMLDataset], cache_directory: str = None
+    description: Union[Dict, OpenMLDataset],
+    cache_directory: str = None,
+    download_all_files: bool = False,
 ) -> Optional[str]:
     """Return the path to the local parquet file of the dataset. If is not cached, it is downloaded.
 
@@ -987,23 +1005,40 @@ def _get_dataset_parquet(
         Folder to store the parquet file in.
         If None, use the default cache directory for the dataset.
 
+    download_all_files: bool, optional (default=False)
+        If `True`, download all data found in the bucket to which the description's
+        ``minio_url`` points, only download the parquet file otherwise.
+
     Returns
     -------
     output_filename : string, optional
         Location of the Parquet file if successfully downloaded, None otherwise.
     """
     if isinstance(description, dict):
-        url = description.get("oml:minio_url")
+        url = cast(str, description.get("oml:minio_url"))
         did = description.get("oml:id")
     elif isinstance(description, OpenMLDataset):
-        url = description._minio_url
+        url = cast(str, description._minio_url)
         did = description.dataset_id
     else:
         raise TypeError("`description` should be either OpenMLDataset or Dict.")
 
     if cache_directory is None:
         cache_directory = _create_cache_directory_for_id(DATASETS_CACHE_DIR_NAME, did)
-    output_file_path = os.path.join(cache_directory, "dataset.pq")
+    output_file_path = os.path.join(cache_directory, f"dataset_{did}.pq")
+
+    old_file_path = os.path.join(cache_directory, "dataset.pq")
+    if os.path.isfile(old_file_path):
+        os.rename(old_file_path, output_file_path)
+
+    # For this release, we want to be able to force a new download even if the
+    # parquet file is already present when ``download_all_files`` is set.
+    # For now, it would be the only way for the user to fetch the additional
+    # files in the bucket (no function exists on an OpenMLDataset to do this).
+    if download_all_files:
+        if url.endswith(".pq"):
+            url, _ = url.rsplit("/", maxsplit=1)
+        openml._api_calls._download_minio_bucket(source=cast(str, url), destination=cache_directory)
 
     if not os.path.isfile(output_file_path):
         try:

tests/test_datasets/test_dataset_functions.py

@@ -322,6 +322,15 @@ def test_get_dataset_by_name(self):
         openml.config.server = self.production_server
         self.assertRaises(OpenMLPrivateDatasetError, openml.datasets.get_dataset, 45)
 
+    @pytest.mark.skip("Feature is experimental, can not test against stable server.")
+    def test_get_dataset_download_all_files(self):
+        # openml.datasets.get_dataset(id, download_all_files=True)
+        # check for expected files
+        # checking that no additional files are downloaded if
+        # the default (false) is used, seems covered by
+        # test_get_dataset_lazy
+        raise NotImplementedError
+
     def test_get_dataset_uint8_dtype(self):
         dataset = openml.datasets.get_dataset(1)
         self.assertEqual(type(dataset), OpenMLDataset)