Update app.py

app.py

@@ -23,8 +23,32 @@ from opinionated.core import download_googlefont
 download_googlefont('Quicksand', add_to_cache=True)
 plt.rc('font', family='Quicksand')
 
-!wget https://github.com/scikit-learn-contrib/hdbscan/raw/master/notebooks/clusterable_data.npy
-!wget https://github.com/mwaskom/seaborn-data/raw/master/penguins.csv
+#wget https://github.com/scikit-learn-contrib/hdbscan/raw/master/notebooks/clusterable_data.npy
+#!wget https://github.com/mwaskom/seaborn-data/raw/master/penguins.csv
+
+
+import requests
+
+# URLs of the files to download
+clusterable_data_url = "https://github.com/scikit-learn-contrib/hdbscan/raw/master/notebooks/clusterable_data.npy"
+penguins_csv_url = "https://github.com/mwaskom/seaborn-data/raw/master/penguins.csv"
+
+# Function to download and save a file from a URL
+def download_file(url, local_filename):
+    with requests.get(url, stream=True) as r:
+        r.raise_for_status()
+        with open(local_filename, 'wb') as f:
+            for chunk in r.iter_content(chunk_size=8192):
+                f.write(chunk)
+
+# Download the files
+download_file(clusterable_data_url, "clusterable_data.npy")
+download_file(penguins_csv_url, "penguins.csv")
+
+print("Files downloaded successfully.")
+
+
+
 
 hdbscan_example_data = np.load('clusterable_data.npy')
 penguins_dataset = pd.read_csv('penguins.csv')[['bill_length_mm','bill_depth_mm','flipper_length_mm']].dropna().values