80 lines
2.5 KiB
Python
Executable File
80 lines
2.5 KiB
Python
Executable File
#!/usr/bin/python3
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import os
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import xml.etree.ElementTree as xmlet
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import pandas
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import math
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outfile = 'xxx.csv'
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columns = [ "name", "status", "role", "cluster", "tenant", "platform", "vcpus", "memory", "disk", "comments" ]
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rows = []
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domaindir = 'xmls/domains'
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diskdir = 'xmls/disks'
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status = 'Active'
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cluster = 'xxx'
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tenant = 'xxx'
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comment = 'Imported from libvirt. Manual verification pending.'
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for domainxml in os.listdir(domaindir):
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domainparse = xmlet.parse(domaindir + "/" + domainxml)
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domainroot = domainparse.getroot()
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name = domainroot.find("name").text
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vcpus = domainroot.find("vcpu").text
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memory = int(domainroot.find("memory").text)
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memorysize = round(memory*0.001024)
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diskxml = diskdir + "/" + name + ".disk.export.xml"
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diskparse = xmlet.parse(diskxml)
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diskroot = diskparse.getroot()
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diskcapacity = int(diskroot.find("capacity").text)
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disksize = round(diskcapacity / (math.pow(1024, (int(math.floor(math.log(diskcapacity, 1024)))))))
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while True:
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role_choice = input ("Assign a role for " + name + ":\n1) Internal Client\n2) Internal Server\n3) ???\n4) ???\n> ")
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if role_choice == "1":
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role = "Virtual Machine (Internal, Client)"
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break
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if role_choice == "2":
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role = "Virtual Machine (Internal, Server)"
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break
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if role_choice == "3":
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role = "Virtual Machine (Customer)"
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break
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if role_choice not in ["1", "2", "3"]:
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print("Invalid choice.")
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while True:
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platform_choice = input ("Assign platform for " + name + ":\n 1) openSUSE-x86_64\n2)OpenBSD-x86_64\n3)FreeBSD-x86_64\n> ")
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if platform_choice == "1":
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platform = "openSUSE-x86_64"
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break
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if platform_choice == "2":
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platform = "OpenBSD-x86_64"
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break
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if platform_choice == "3":
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platform = "FreeBSD-x86_64"
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break
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if platform_choice not in ["1", "2", "3"]:
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print("Invalid choice.")
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rows.append(
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{
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"name": name,
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"status": status,
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"role": role,
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"cluster": cluster,
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"tenant": tenant,
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"platform": platform,
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"vcpus": vcpus,
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"memory": memorysize,
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"disk": disksize,
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"comments": comment
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}
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)
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convert = pandas.DataFrame(rows, columns=columns)
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convert.to_csv(outfile, index=False)
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