20 Python JSON Interview Questions and Answers

JSON is a popular data format used for storing and exchanging data. If you’re applying for a position that involves Python and JSON, it’s important to be prepared for questions about your skills and experience. In this article, we review some of the most common JSON interview questions and provide tips on how to answer them.

Python JSON Interview Questions and Answers

Here are 20 commonly asked Python JSON interview questions and answers to prepare you for your interview:

1. What is JSON?

JSON is a syntax for storing and exchanging data.

2. Can you explain what a nested dictionary in Python is? How can we access values stored in it?

A nested dictionary is a dictionary that contains other dictionaries as values. We can access values stored in a nested dictionary by using the square bracket notation. For example, if we have a dictionary called “dict” that contains a nested dictionary called “nested_dict”, we can access the value “foo” in the nested dictionary by doing the following: dict[“nested_dict”][“foo”].

3. Can you explain the difference between JSON and XML?

JSON and XML are both markup languages that are used to store data. JSON is a newer format that is becoming increasingly popular because it is more compact and easier to read. XML is more verbose and can be more difficult to parse.

4. What are some advantages of using JSON over XML?

JSON is often seen as being faster and easier to work with than XML because it is less verbose. JSON also uses fewer data types than XML, which can make it easier to work with for some people. Additionally, JSON supports a range of data types that XML does not, such as arrays and objects.

5. Is it possible to convert an object into JSON in Python? If yes, then how?

Yes, it is possible to convert an object into JSON in Python. This can be done using the json.dumps() function.

6. Is there any way to get all keys from a JSON file’s data structure in Python?

Yes, you can use the json.loads() function to load the JSON file’s data structure into a Python dictionary, and then use the dictionary’s keys() method to get a list of all the keys.

7. What do you understand about serialization and deserialization?

Serialization is the process of converting data into a format that can be stored or transmitted. Deserialization is the process of converting data back into its original form.

8. What does the json.loads() method do in Python?

The json.loads() method in Python takes a string as input and converts it into a Python object (usually a dictionary). This is useful when you are working with data that is in JSON format, as it can help you convert it into a format that is more easily manipulable in Python.

9. Can you explain what a JSON-RPC request is?

A JSON-RPC request is a type of request that uses the JSON format for its parameters. This makes it possible to call methods and functions with parameters that are in the JSON format, which is convenient for many applications.

10. What is the difference between JSON and JavaScript objects?

JSON is a data format that is used to store and transmit data. JavaScript objects are data structures that are used to store data. JSON is based on the JavaScript object syntax, but it is not the same as a JavaScript object.

11. Is it possible to use tuples as keys for dictionaries in Python?

Yes, it is possible to use tuples as keys for dictionaries in Python. This is because tuples are immutable, meaning that they cannot be changed once they are created. This makes them ideal for use as keys in dictionaries, as they will not be able to be changed by the user and will thus always point to the same data.

12. In Python, what is the best way to extract data from a list of dictionaries?

The best way to extract data from a list of dictionaries is to use the built-in Python function, “zip.” This function will take two or more lists and “zip” them together into a single list of tuples. Each tuple will contain one element from each of the original lists. This can be very useful for extracting data from a list of dictionaries because it allows you to easily iterate over the data in a structured way.

13. What are the main differences between lists and dictionaries in Python?

The main difference between lists and dictionaries is that lists are ordered while dictionaries are unordered. This means that you can access items in a list by their index, but you cannot do the same with dictionaries. Additionally, dictionaries can store data of any type, while lists can only store data of a single type.

14. What are the different ways that you can use to encode and decode JSON in Python?

There are two main ways to encode and decode JSON in Python. The first is using the built-in json module, and the second is using the third-party simplejson module. The json module is the standard way to work with JSON in Python, and it is included in the standard library. The simplejson module is a third-party module that is not included in the standard library, but it is popular and easy to use.

15. What do you understand by JSON Schema Validation?

JSON Schema Validation is the process of validating a JSON document against a JSON schema. A JSON schema is a document that defines the structure of a JSON document, and can be used to validate that a JSON document conforms to the schema.

16. Why is it necessary to validate JSON in your code?

JSON validation is important because it helps to ensure that the data being passed into your code is in the correct format. This can help to avoid errors and can also help to ensure that your code is working as intended.

17. What is the usage of the “with” statement in Python?

The “with” statement is used to automatically release resources held by an object, such as a file or lock, when the with block is exited. This ensures that resources are always properly cleaned up, even if an exception is raised in the with block.

18. What do you understand by Nested Dictionaries in Python?

A nested dictionary is a dictionary that contains another dictionary as a value. This can be useful if you want to store data in a more structured way. For example, you could store information about a person in a nested dictionary, with the nested dictionary containing information about that person’s address, phone number, and so on.

19. What is the purpose of the load() and loads() methods in Python?

The load() method is used to load a JSON file, while the loads() method is used to load a JSON string.

20. What is the function of the dump() and dumps() methods in Python?

The dump() method is used to serialize data from a Python object into a JSON formatted string, whereas the dumps() method is used to serialize data from a Python object into a JSON formatted string that is returned as a Python string.