JNCIA-DevOps Data Serialization Practice Test 4 — 15 Questions

Question 1

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 2

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().

Answer

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

Question 3

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

Accepted Answer

true. JSON (RFC 8259) defines boolean literals as lowercase 'true' and 'false' only. Any other casing or quoting is invalid JSON or represents a different type, so 'true' is the only valid boolean true value among the options.

Answer

True

Answer

"true"

Answer

TRUE

Question 4

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. Junos devices natively return JSON when REST API or NETCONF operations are configured with JSON output formatting, because JSON is the structured data format the device emits for programmatic consumption. The 'accept: application/json' header or equivalent RPC attribute triggers this output.

Answer

INI

Answer

YAML

Answer

CSV

Question 5

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 6

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 7

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 csv module in Python is specifically designed to read and write CSV files. It provides functionality to parse rows of comma-separated values into lists or dictionaries, handling quoting and delimiter variations. This makes it the correct choice for reading interface names and VLAN IDs from a CSV file before converting to JSON.

Answer

yaml

Answer

json

Answer

xml

Question 8

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 9

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

Accepted Answer

Undefined. JSON supports a limited set of primitive data types defined in RFC 8259: string, number, boolean, null, object, and array. 'Undefined' is not one of them — it is a JavaScript-specific value that has no representation in the JSON specification. When JavaScript serializes an object with JSON.stringify(), any property whose value is undefined is simply omitted from the output rather than encoded.

Answer

Number

Answer

String

Answer

Null

Question 10

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

Accepted Answer

String. Option A (String) is correct because JSON defines string as one of its six primitive data types, representing a sequence of Unicode characters enclosed in double quotes. Option C (Boolean) is correct because JSON natively supports the boolean primitive values true and false. The other options do not belong: Function, Undefined, and Symbol are JavaScript-specific types that are not part of the JSON specification and cannot be represented in JSON text.

Answer

Function

Answer

Undefined

Answer

Symbol

Question 11

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. The command 'python3 -m json.tool filename.json' invokes the built-in json.tool module, which validates and pretty-prints JSON from a file or stdin. It is a standard utility available in any Python 3 installation.

Answer

python3 -m yaml.format filename.json

Answer

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

Answer

netconf-console --pretty filename.json

Question 12

You are writing a Python automation script that processes configuration data. The script reads a YAML file containing Junos firewall filters, modifies them, and writes them back out. However, you notice that all the original comments in the file are stripped out in the output. What is the fundamental reason for this behavior in standard PyYAML dump operations?

Accepted Answer

Comments are stripped during parsing because they are not part of the YAML data model.. PyYAML parses YAML files into abstract syntax trees (AST) or Python native data structures, discarding comments during the parsing phase because comments are not part of the data model.

Answer

The yaml.safe_dump() function explicitly deletes comments for security reasons.

Answer

YAML specification mandates that all comments are ephemeral and cannot be serialized.

Answer

Comments must be re-injected using the 'preserve_comments=True' parameter.

Question 13

Which TWO of the following are valid extensions commonly used for YAML files? (Choose two)

Accepted Answer

.yaml. Option C (.yaml) is correct because .yaml is the canonical, officially recommended file extension for YAML documents, as defined by the YAML specification and used by tools like PyYAML, Kubernetes manifests, and Ansible playbooks. Option E (.yml) is also correct because .yml is the widely accepted short-form alternative extension for YAML files, supported by virtually all YAML parsers and commonly seen in CI/CD configs such as .travis.yml, docker-compose.yml, and GitHub Actions workflows. Option A (.xml) is incorrect because it denotes Extensible Markup Language files, a completely different markup syntax with angle-bracket tags, not YAML's indentation-based structure. Option B (.jsn) is incorrect because it is not a standard extension for any common serialization format; JSON files use .json, and .jsn is not a recognized YAML extension. Option D (.txt) is incorrect because plain-text files have no defined structure and are not parsed as YAML by convention, even though YAML is technically a text format.

Answer

.xml

Answer

.jsn

Answer

.txt

Question 14

Which TWO methods are provided by the Python standard library 'json' module for deserializing JSON data? (Choose two)

Accepted Answer

json.loads(). Option C, json.loads(), is correct because it deserializes a JSON-formatted string (or bytes) directly into a Python object such as a dict or list. Option D, json.load(), is correct because it reads JSON data from a file-like object (for example, an open file handle) and deserializes it into a Python object. These are the two deserialization functions actually exposed by the standard library json module. Options A (json.read()), B (json.decode()), and E (json.parse()) are not functions provided by the json module, so they cannot be used for deserialization.

Answer

json.read()

Answer

json.decode()

Answer

json.parse()

Question 15

Which TWO features are supported by YAML but are notably absent in standard JSON? (Choose two)

Accepted Answer

Anchors and aliases for data reuse within the document.. Option D is correct because YAML provides anchors (&) and aliases (*) that let you define a node once and reference it elsewhere in the same document, a reuse mechanism JSON lacks entirely. Option E is correct because YAML natively supports comments introduced by the hash (#) symbol, whereas standard JSON (per RFC 8259) defines no comment syntax at all. Option A is wrong because neither YAML nor JSON executes natively in browsers; JSON is parsed via JSON.parse() and YAML requires a library such as js-yaml. Option B is wrong because JSON requires double quotes on keys, while YAML permits unquoted keys, so this is a JSON trait, not a YAML-only feature. Option C is wrong because YAML uses indentation for structure but does not enforce strict block scoping the way the option implies, and JSON uses braces and brackets rather than indentation.

Answer

Native browser execution support without parsing libraries.

Answer

Strict enforcement of double quotes on all string keys.

Answer

Strict indentation-based block scoping.