JNCIA-DevOps Data Serialization Practice Test 3 — 15 Questions

Question 1

An automation engineer is writing a Python script to push configurations to a Junos device. The script loads a YAML data file containing interface descriptions. One description contains a colon without a following space (e.g., 'Interface:Primary'). What error will PyYAML raise when attempting to parse this file?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

ScannerError. In YAML, a colon must be followed by a whitespace character to be recognized as a mapping key-value separator. If no space follows, PyYAML raises a ScannerError or MappingValuesError.

Answer

TypeError

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YAMLSemanticError

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JSONDecodeError

Question 2

Which Python function deserializes a JSON-formatted string into a native Python dictionary?

Accepted Answer

json.loads(). json.loads() (load string) is used to parse a JSON string into a Python object.

Answer

json.load()

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json.read()

Answer

json.parse()

Question 3

Which of the following describes the fundamental structural difference between JSON and YAML regarding syntax design?

Accepted Answer

JSON relies on explicit punctuation like braces and brackets, whereas YAML relies heavily on indentation.. JSON relies explicitly on structural characters (curly braces, brackets, quotes, commas) to define hierarchies, whereas YAML primarily relies on indentation and whitespace.

Answer

YAML requires all keys to be enclosed in double quotes, whereas JSON does not.

Answer

YAML does not support lists or arrays.

Answer

JSON supports comments natively, whereas YAML does not.

Question 4

A Python automation script parses a Junos telemetry stream in JSON. The JSON payload uses integer keys in a dictionary (e.g., {443: 'HTTPS'}). When loaded into Python using json.loads(), what data type do the dictionary keys become?

Accepted Answer

They are converted to Python string objects.. JSON specification dictates that object keys must be strings. When json.loads() parses an object, any keys (even if numeric-looking) are converted to Python strings.

Answer

They are converted to floating-point numbers.

Answer

They remain integer objects.

Answer

The parser raises a KeyError because JSON keys must be alphabetic.

Question 5

An automation engineer needs to include comments explaining complex network parameters inside a Junos automation data file. Which serialization format should the engineer select?

Accepted Answer

YAML. YAML natively supports comments using the hash (#) symbol, whereas standard JSON does not support comments.

Answer

CSV

Answer

JSON

Answer

Pickle

Question 6

You are writing a Python script that parses a multi-document YAML stream containing Junos device site configurations. One of the documents contains a custom YAML tag. When parsing with yaml.safe_load_all(), how does the safe loader handle custom tags?

Accepted Answer

It raises a ConstructorError unless a custom constructor is registered.. The safe loader in PyYAML does not know how to construct objects from custom tags by default and will raise a ConstructorError unless a custom constructor has been explicitly registered.

Answer

It converts the tagged object into a JSON equivalent.

Answer

It automatically evaluates the custom tag using Python eval().

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It ignores the tag and loads the scalar value as a plain string.

Question 7

Which of the following valid JSON values represents a boolean true state?

Accepted Answer

true. JSON booleans are lowercase words: true and false.

Answer

True

Answer

"true"

Answer

TRUE

Question 8

What is the native data format returned by Junos devices when queried via REST API or NETCONF operations configured with JSON output formatting?

Accepted Answer

JSON. When JSON output is requested from Junos REST or NETCONF, the returned data is serialized in JSON format.

Answer

INI

Answer

YAML

Answer

CSV

Question 9

An automation engineer wants to verify the syntax of a large YAML playbook before executing it against a production Junos device. Which python one-liner command can be run in the terminal to quickly check if the file is syntactically valid YAML?

Accepted Answer

python3 -c 'import yaml, sys; yaml.safe_load(open(sys.argv[1]))' config.yaml. Running python3 -c 'import yaml, sys; yaml.safe_load(open(sys.argv[1]))' filename.yaml attempts to parse the file and will report any syntax errors.

Answer

yaml --validate config.yaml

Answer

netconf-console --check config.yaml

Answer

python3 -m json.tool config.yaml

Question 10

A Python automation script extracts routing table entries from a Junos device. The data structure contains deeply nested dictionaries and lists. The engineer needs to perform a deep copy of this deserialized JSON structure before modifying it. Which Python module provides the deepcopy function needed to duplicate nested containers safely?

Accepted Answer

copy. The 'copy' module in the Python standard library provides the deepcopy() function, which recursively clones nested dictionaries and lists.

Answer

os

Answer

sys

Answer

json

Question 11

An automation script reads interface names and VLAN IDs from a CSV file and converts each row into a JSON object before sending it to a Junos device REST API. Which Python module is specifically designed to parse CSV (Comma-Separated Values) files?

Accepted Answer

csv. The Python standard library includes the 'csv' module, which provides reader and writer objects for tabular CSV data.

Answer

yaml

Answer

json

Answer

xml

Question 12

You are writing a Python script that converts a Junos operational state output from XML (via NETCONF) into JSON. The XML structure contains sibling elements with the same tag name. When converted naively, how do standard XML-to-JSON conversion libraries (like xmltodict) typically represent these repeated sibling elements in the resulting JSON dictionary?

Accepted Answer

As a JSON array containing multiple objects.. Conversion libraries like xmltodict represent repeated sibling XML elements as a JSON array (list) to preserve all instances under a single key.

Answer

By appending numeric indexes to every key name automatically.

Answer

By raising a DuplicateElementException.

Answer

By overwriting previous elements so only the last element is retained.

Question 13

Which of the following primitive data types is NOT supported natively in JSON?

Accepted Answer

Undefined. JSON does not support undefined, functions, or undefined date types natively. Among standard choices, undefined or complex numbers are absent.

Answer

Number

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String

Answer

Null

Question 14

Which TWO of the following are valid primitive data types in JSON? (Choose two)

Accepted Answer

String. JSON primitive types include strings, numbers, booleans, and null. Arrays and objects are composite types.

Answer

Function

Answer

Undefined

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Symbol

Question 15

An automation engineer needs to pretty-print a JSON payload in the Linux terminal for debugging Junos telemetry. Which built-in Python command-line utility can be invoked to validate and pretty-print a JSON file?

Accepted Answer

python3 -m json.tool filename.json. Python provides a command-line JSON tool via the json.tool module, invoked as 'python3 -m json.tool filename.json'.

Answer

python3 -m yaml.format filename.json

Answer

python3 -c 'import json; json.format()'

Answer

netconf-console --pretty filename.json