Initial code to generate HOIP Subscriber list - replacement for

Hamshack Hotline.

hoipdownload.py

@@ -0,0 +1,56 @@
+from ldap3 import Server, Connection, ALL, SUBTREE
+import pandas as pd
+
+# LDAP connection details from the wiki
+server_url = 'ldap://207.246.98.219:389'  # Server and port (no TLS, as per "TLS Mode: LDAP or No" – use 'ldaps://' if TLS needed)
+search_base = 'ou=people,dc=hamsoverip,dc=com'
+search_filter = '(telephoneNumber=*)'  # Fetch all entries with an extension; adjust if needed, e.g., '(objectClass=person)'
+attributes = ['cn', 'sn', 'telephoneNumber']  # Key attributes; add more if you discover others like 'callsign'
+
+# Connect anonymously (no auth)
+server = Server(server_url, get_info=ALL)
+conn = Connection(server, auto_bind=True)  # No user/password
+
+# Perform the search
+conn.search(
+    search_base=search_base,
+    search_filter=search_filter,
+    search_scope=SUBTREE,
+    attributes=attributes
+)
+
+# Extract data
+data = []
+for entry in conn.entries:
+    extension = entry.telephoneNumber.value if 'telephoneNumber' in entry else ''
+    cn_value = entry.cn.value if 'cn' in entry else ''
+    sn_value = entry.sn.value if 'sn' in entry else ''
+
+    # clean up data
+    hoipnumber = extension.partition(' ')[0]
+    callsign = cn_value.partition(' ')[0]
+    hamname = sn_value.partition(' ')[0]
+
+    if hoipnumber:  # Only include entries with extensions
+        data.append({
+            'HOIP Extension': hoipnumber,
+            'Call': callsign,
+            'Name': hamname       # Include raw for reference
+        })
+
+# Save to CSV
+if data:
+    df = pd.DataFrame(data)
+
+    # CSV output for debugging...
+    df.to_csv('hoip_subscribers.csv', index=False)
+    print(f'Saved {len(data)} entries to hoip_subscribers.csv')
+
+    # Excel output for production...
+    df.to_excel('hoip_subscribers.xlsx', index=False)
+    print(f'Saved {len(data)} entries to hoip_subscribers.xlsx')
+else:
+    print('No entries found – check filter or connection.')
+
+# Unbind
+conn.unbind()