2. Describe Parsing of Common Data Format (XML, JSON, and YAML) to Python Data Structures 200-901 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Given the following JSON data: { "hostname": "R1", "interfaces": [ {"name": "Gig0/0", "ip": "10.0.0.1"}, {"name": "Gig0/1", "ip": "10.0.0.2"} ] } After parsing this JSON with json.loads(), what Python data type is the value associated with the key "interfaces"?

   • AA dictionary of dictionaries
   • BA list of dictionaries
   • CA string
   • DA tuple of dictionaries
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2. 2application · medium

   A network automation script receives a JSON response from a controller. The JSON contains a field 'interfaces' that is an array of objects. The script must check if any interface has 'admin_status' equal to 'up'. Which Python code snippet correctly performs this check?

   • Afor iface in data: if iface['admin_status'] == 'up': break
   • Bif data['interfaces']['admin_status'] == 'up'
   • Cif 'up' in data['interfaces']
   • Dany(iface['admin_status'] == 'up' for iface in data['interfaces'])
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4. 3expert · hard

   A network automation engineer is writing a script that must parse data from three different sources: a NETCONF device (XML), a REST API (JSON), and a local configuration file (YAML). The script needs to convert all three into a common Python dictionary format for further processing. Which approach is most efficient?

   • AUse a single library that can parse all three formats
   • BUse separate parsers for each format and then normalize the resulting structures
   • CUse yaml.safe_load() for all three formats
   • DConvert all formats to JSON first, then parse with json.loads()
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5. 4expert · hard

   A network automation team is building a system that must exchange data with multiple external services. One service requires XML, another requires JSON, and a third requires YAML. The team wants to maintain a single source of truth in Python and generate the required formats on demand. Which approach is the most maintainable?

   • AStore data in XML and convert to JSON and YAML using libraries
   • BStore data as Python dictionaries and use json.dumps(), xml.etree.ElementTree, and yaml.safe_dump() to serialize as needed
   • CStore data in YAML and convert to JSON and XML using libraries
   • DStore data in JSON and convert to XML and YAML using libraries
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6. 5application · medium

   A Python script receives a REST API response in JSON. The script needs to extract the value of the 'status' field from the first item in a list under the key 'devices'. Which Python expression correctly accomplishes this?

   • Adata['devices'][0]['status']
   • Bdata[0]['devices']['status']
   • Cdata['status'][0]['devices']
   • Ddata['devices']['status'][0]
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