Specify "spawn" start method

Use multiprocessing.get_context to set "spawn" start method.
"fork" (default in POSIX systems) is deprecated.

eda_report/_analysis.py

@@ -1,4 +1,4 @@
-from multiprocessing import Pool
+from multiprocessing import get_context
 from typing import Dict, Iterable, Optional, Union
 
 import pandas as pd
@@ -9,6 +9,8 @@
 from eda_report.plotting import _plot_dataset, _plot_variable
 from eda_report.univariate import Variable, _analyze_univariate
 
+mp_context = get_context("spawn")  # Use "spawn" start method
+
 
 def _get_contingency_tables(
     categorical_df: pd.DataFrame, groupby_data: pd.Series
@@ -77,7 +79,7 @@ def _analyze_variables(self) -> Dict[str, Variable]:
             Dict[str, Variable]: Univariate analysis results.
         """
         data = self.dataset.data
-        with Pool() as p:
+        with mp_context.Pool() as p:
             univariate_stats = dict(
                 tqdm(
                     # Analyze variables concurrently
@@ -132,7 +134,8 @@ def _get_univariate_graphs(self) -> Dict[str, Dict]:
         Returns:
             Dict[str, Dict]: Univariate graphs.
         """
-        with Pool() as p:
+
+        with mp_context.Pool() as p:
             data = self.dataset.data
             variable_data_hue_and_color = [
                 (

eda_report/plotting.py

@@ -1,5 +1,5 @@
 from io import BytesIO
-from multiprocessing import Pool
+from multiprocessing import get_context
 from typing import Dict, Iterable, Optional, Sequence, Tuple, Union
 
 import matplotlib as mpl
@@ -458,7 +458,7 @@ def _plot_dataset(variables: Dataset, color: str = None) -> Optional[Dict]:
         pairs_to_include = [
             pair for pair, _ in variables._correlation_values[:20]
         ]
-        with Pool() as p:
+        with get_context("spawn").Pool() as p:
             paired_data = [
                 (variables.data.loc[:, pair], color)
                 for pair in pairs_to_include