Create spaces_utils.py

spaces_utils.py

@@ -0,0 +1,43 @@
+import os
+import csv
+import pandas as pd
+from datetime import datetime
+from datasets import load_dataset, Dataset
+from huggingface_hub import Repository
+
+
+# Load tokens
+GRADIO_TOKEN = os.environ.get("GRADIO_ORG")  # read
+WRITE_TOKEN = os.environ.get("WRITE_PER")  # write
+
+
+def write_logs(message, dataset_url, dataset_path, log_type="Prediction"):
+    """
+    Write logs
+    """
+    with Repository(local_dir="data", clone_from=dataset_url, use_auth_token=WRITE_TOKEN).commit(
+        commit_message="from private", blocking=False
+    ):
+        with open(dataset_path, "a") as csvfile:
+            writer = csv.DictWriter(csvfile, fieldnames=["name", "message", "time"])
+            writer.writerow({"name": log_type, "message": message, "time": str(datetime.now())})
+    return
+
+
+def authenticate(username, password, dataset_url, dataset_path):
+    """
+    Verify if the provided tuple (username, password) is in the database
+    """
+    df_password = load_dataset(
+        "sandl/test_passwords", data_files="test_password.csv", delimiter=";", use_auth_token=GRADIO_TOKEN
+    )
+    df_password = pd.DataFrame(df_password["train"])
+
+    if username not in list(df_password["username"]):
+        return False
+
+    authentication_sucess = df_password[df_password["username"] == username]["password"].iloc[0] == password
+    if authentication_sucess:
+        message = f"{username} logged"
+        write_logs(message, dataset_url, dataset_path, log_type="Authentication")
+    return authentication_sucess