Move default location of data to the user home folder

benchmarks/bench_fuzzy_join_sparse_vs_dense.py

@@ -9,6 +9,7 @@
 """
 
 import math
+from pathlib import Path
 from utils import default_parser, find_result, monitor
 from utils.join import evaluate, fetch_big_data
 from argparse import ArgumentParser
@@ -526,8 +527,12 @@ def benchmark(
     dataset_name: str,
     analyzer: Literal["char_wb", "char", "word"],
     ngram_range: tuple,
+    data_home: Path | str = None,
+    data_directory: str = "benchmarks_data",
 ):
-    left_table, right_table, gt = fetch_big_data(dataset_name)
+    left_table, right_table, gt = fetch_big_data(
+        dataset_name=dataset_name, data_home=data_home, data_directory=data_directory
+    )
 
     start_time = perf_counter()
     joined_fj = fuzzy_join(

benchmarks/utils/join.py

@@ -1,11 +1,13 @@
 import pandas as pd
+from pathlib import Path
 from skrub.datasets._utils import get_data_dir
 
 
-def get_local_data(dataset_name: str, data_directory: str = None):
+def get_local_data(
+    dataset_name: str, data_home: Path | str = None, data_directory: str = None
+):
     """Get the path to the local datasets."""
-    if data_directory is None:
-        data_directory = get_data_dir("benchmarks_data")
+    data_directory = get_data_dir(data_directory, data_home)
     left_path = str(data_directory) + f"/left_{dataset_name}.parquet"
     right_path = str(data_directory) + f"/right_{dataset_name}.parquet"
     gt_path = str(data_directory) + f"/gt_{dataset_name}.parquet"
@@ -20,7 +22,10 @@ def get_local_data(dataset_name: str, data_directory: str = None):
 
 
 def fetch_data(
-    dataset_name: str, save: bool = True
+    dataset_name: str,
+    save: bool = True,
+    data_home: Path | str = None,
+    data_directory: str = None,
 ) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
     """Fetch datasets from https://github.com/Yeye-He/Auto-Join/tree/master/autojoin-Benchmark
 
@@ -32,6 +37,13 @@ def fetch_data(
     save: bool, default=true
         Wheter to save the datasets locally.
 
+    data_home: Path or str, optional
+        The path to the root data directory.
+        By default, will point to the skrub data directory.
+
+    data_directory: str, default=None
+        The name of the subdirectory in which data is stored.
+
     Returns
     -------
     left: pd.DataFrame
@@ -43,7 +55,9 @@ def fetch_data(
     gt: pd.DataFrame
         Ground truth dataset.
     """
-    left_path, right_path, gt_path, file_paths = get_local_data(dataset_name)
+    left_path, right_path, gt_path, file_paths = get_local_data(
+        dataset_name, data_home, data_directory
+    )
     if len(file_paths) == 0:
         repository = "Yeye-He/Auto-Join"
         dataset_name = dataset_name.replace(" ", "%20")
@@ -69,6 +83,8 @@ def fetch_big_data(
     dataset_name: str,
     data_type: str = "Dirty",
     save: bool = True,
+    data_home: Path | str = None,
+    data_directory: str = None,
 ) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]:
     """Fetch datasets from https://github.com/anhaidgroup/deepmatcher/blob/master/Datasets.md
 
@@ -84,6 +100,13 @@ def fetch_big_data(
     save: bool, default=true
         Wheter to save the datasets locally.
 
+    data_home: Path or str, optional
+        The path to the root data directory.
+        By default, will point to the skrub data directory.
+
+    data_directory: str, default=None
+        The name of the subdirectory in which data is stored.
+
     Returns
     -------
     left: pd.DataFrame
@@ -96,7 +119,9 @@ def fetch_big_data(
         Ground truth dataset.
     """
     link = "https://pages.cs.wisc.edu/~anhai/data1/deepmatcher_data/"
-    left_path, right_path, gt_path, file_paths = get_local_data(dataset_name)
+    left_path, right_path, gt_path, file_paths = get_local_data(
+        dataset_name, data_home, data_directory
+    )
     if len(file_paths) == 0:
         test_idx = pd.read_csv(f"{link}/{data_type}/{dataset_name}/exp_data/test.csv")
         train_idx = pd.read_csv(f"{link}/{data_type}/{dataset_name}/exp_data/train.csv")