Init libvirt-xml2netbox-csv_interfaces.py

Signed-off-by: Georg <georg@lysergic.dev>

scripts/python/libvirt-xml2netbox-csv_interfaces.py

@@ -0,0 +1,51 @@
+#!/usr/bin/python3
+"""
+Takes a directory with libvirt XML domain dumps and creates a NetBox importable CSV with VM interfaces. Intended to be used subsequently to libvirt-xml2netbox.py.
+Note: we want the VM interfaces to be created with the interface name the operating system is seeing. Since libvirt only knows the host-side interface or network association, and since it was decided that integrating an automated interface name extraction process with a different source which merges with the libvirt data would not be economic, manual editing of the interface names in the resulting CSV - according to the data presented by the VM operating systems - is required.
+
+Created and Last modified: 02/01/2022 by Georg Pfuetzenreuter <georg@lysergic.dev>
+"""
+
+import os
+import xml.etree.ElementTree as xmlet
+import pandas
+
+cluster = "xxx"
+indir = "xmls/" + cluster + "/domains"
+outfile = cluster + "_interfaces.csv"
+
+columns = [ "virtual_machine", "name", "enabled", "mac_address", "mtu", "description", "mode" ]
+rows = []
+
+
+for domainxml in os.listdir(indir):
+    xmlparse = xmlet.parse(indir + "/" + domainxml)
+    xmlroot = xmlparse.getroot()
+    domain = xmlroot.find("name").text
+    for interface in xmlroot.findall("devices/interface"):
+        interface_type = next(iter(interface.attrib.values()))
+        if interface_type ==  "network":
+            source = interface.find("source").attrib["network"]
+        if interface_type ==  "bridge":
+            source = interface.find("source").attrib["bridge"]
+        mac_address = interface.find("mac").attrib["address"]
+        model = interface.find("model").attrib["type"]
+        enabled = "true"
+        mtu  = "1500"
+        mode = "access"
+        description = "Imported from libvirt. Model: " + model +  "."
+
+        rows.append(
+                {
+                    "virtual_machine": domain,
+                    "name": source,
+                    "enabled": enabled,
+                    "mac_address": mac_address,
+                    "mtu": mtu,
+                    "description": description,
+                    "mode": mode
+                }
+        )
+
+convert = pandas.DataFrame(rows, columns=columns)
+convert.to_csv(outfile, index=False)