updated script to us h3 bucket and env

.gitignore

@@ -0,0 +1,17 @@
+# Local data files
+files/
+*.csv
+*.json
+*.xlsx
+
+# Python caches
+__pycache__/
+*.pyc
+*.pyo
+*.pyd
+
+# VS Code settings
+.vscode/
+
+#Environment files
+.env

Scripts/Generate_branches.py

@@ -1,4 +1,6 @@
 from faker import Faker
+from dotenv import load_dotenv
+import os
 import pandas as pd
 import boto3
 
@@ -6,14 +8,17 @@ import boto3
 fake = Faker()
 
 # ---- Hetzner S3 setup ----
+# Load .env file
+load_dotenv()
+
 s3 = boto3.resource(
     's3',
-    endpoint_url='https://fsn1.your-objectstorage.com',
+    endpoint_url=os.getenv('STORAGE_ENDPOINT'),
-    aws_access_key_id='LXH38VQ3K0A87TZS0KXP',                 
+    aws_access_key_id=os.getenv('STORAGE_ACCESS_KEY'),
-    aws_secret_access_key='tkJt2iNjmEj1KAqtx2Tvb3WqQNkOxgqJzHC7Iq1H'             
+    aws_secret_access_key=os.getenv('STORAGE_SECRET_KEY')
 )
 
-bucket_name = 'CamDoesData'
+bucket_name = os.getenv('STORAGE_BUCKET')
 s3_key = 'DataLab/branches/branches.csv'  
 
 # ---- Generate branch data ----
@@ -31,9 +36,9 @@ for i in range(1, 11):  # 10 Branches
 df = pd.DataFrame(branches)
 
 # ---- Save locally (optional) ----
-# local_file = "branches.csv"
+local_file = "branches.csv"
-# df.to_csv(local_file, index=False)
+df.to_csv(local_file, index=False)
-# print("Generated 10 branches locally.")
+print("Generated 10 branches locally.")
 
 # ---- Upload to S3 ----
 s3.Bucket(bucket_name).upload_file(local_file, s3_key)