Top 15 Dictionary Programming Interview Questions and Answers for Aspiring Developers

Dictionaries are one of the most useful and versatile data structures in programming. They allow you to store data in key-value pairs for efficient lookup and access. Hence, it’s no surprise that dictionary interview questions regularly feature in coding interviews for developers.

In this comprehensive guide, we will explore the top 15 dictionary programming interview questions that test your understanding of this data structure. Whether you are prepping for your dream developer role or want to brush up core concepts, these questions will provide key insights.

So let’s get started!

What is a Dictionary in Python?

A python dictionary is an unordered collection of data values. It stores elements in key-value pairs where keys are used to access values.

Dictionaries are declared using curly braces {} or the dict() constructor. They are mutable, meaning elements can be added, updated or deleted. Keys must be unique and immutable while values can be any Python data type.

Common uses for dictionaries include

• Storing user profiles in web applications
• Caching/memoization to store pre-computed values
• Counting word frequency in text documents
• Graph data structure representation

How are Dictionaries Implemented in Python?

Python dictionaries are implemented under the hood as hash tables. The key is hashed to generate a hash value which maps to the location of the value in memory.

This enables highly optimized key lookup times as the key directly leads to the memory address. Looking up values by key is O(1) on average.

However, improper hash functions can lead to collisions degrading performance to O(n) in worst case. Python uses dynamic resizing and efficient collision handling to minimize this.

Is Python Dictionary Ordered or Unordered?

Python dictionaries are unordered data structures. Elements stored in a dictionary do not maintain any specific order.

The key-value pairs are inserted based on the hash table implementation. Their order can change upon operations like insertions or deletions.

If preservation of insertion order is needed, OrderedDict class from collections module can be used. It maintains order by linking keys to values through a doubly linked list.

Is Python Dictionary Mutable or Immutable?

Python dictionaries are mutable datatypes. Their contents can be modified after creation.

We can add, update, remove keys and values in a dictionary. However, while keys must remain immutable, values can be modified.

Immutable dictionaries that cannot be changed after creation are not directly supported in Python. But the immutabledict module provides immutable dictionary implementations.

How are Dictionaries Different from Lists or Arrays?

The major differences between dictionaries and lists/arrays are:

• Dictionaries are unordered, whereas lists are ordered sequences.
• Dictionary elements are accessed via keys rather than numerical indexes.
• Keys are used only once in a dictionary while list elements can be duplicated.
• Dictionaries are mutable, but lists are immutable (contents can’t be changed).
• Dictionaries can store heterogeneous data types as values, but lists usually store a single type.

How to Create a Dictionary in Python?

There are several ways to create dictionaries in Python:

# With curly bracesdict1 = {'name': 'John', 'age': 20} # Using dict constructordict2 = dict(name='Mary', age=25)# From sequence of key-value pairsdict3 = dict([('name', 'Steve'), ('age', 30)])

We can also initialize an empty dictionary using empty curly braces {} or dict() constructor without any arguments.

How to Access Elements from a Dictionary?

Elements can be accessed from a dictionary by specifying keys inside square brackets [].

For example:

dict = {'name': 'John', 'age': 20}print(dict['name']) # Prints 'John'print(dict['age']) # Prints 20

Trying to access a non-existent key throws a KeyError. The get() method can avoid this by returning a default value if key is missing.

How to Add or Change Elements in Dictionary?

We can add a new key-value pair by simply assigning value to a new key:

dict['gender'] = 'Male' 

This inserts ‘gender’ into dict if it doesn’t exist. If the key already exists, the value gets updated.

Another way is to use the update() method to update multiple keys:

dict.update({'gender': 'Male', 'age': 21})

How to Iterate through a Dictionary?

We can iterate through keys, values or key-value pairs in a dictionary using special methods:

dict = {'name': 'John', 'age': 20}# Iterate over keys for key in dict.keys():    print(key)# Iterate over valuesfor val in dict.values():   print(val)      # Iterate over key-value pairs  for key, val in dict.items():    print(key, val)

We can also directly iterate over the dictionary to loop through its keys.

How to Delete or Remove Elements from Dictionary?

To remove an item, use:

del dict['name'] # Removes 'name' 

The pop() method deletes and returns the value of the key passed:

dict.pop('age') # Removes 'age' and returns 20

popitem() deletes and returns an arbitrary key-value pair.

clear() empties the entire dictionary.

How to Check if Key Exists in Dictionary?

To check if a key exists, we can use ‘in’ keyword rather than catching KeyError:

if 'name' in dict:   print('Present')else:   print('Not present')  

Alternatively, get() can return a default value if key is missing. Checking for this can also indicate presence.

How are Dictionaries Used in Python Programs?

Here are some common use cases of dictionaries in Python:

• Storing configuration or settings as key-value pairs
• Caching expensive function calls by memoization
• Passing keyword arguments to functions using dicts
• Counting frequency of words in text by storing in dictionary
• Representing graphs with adjacency list structure
• Lookup tables for efficient O(1) access of data

What are the Different Methods in Dictionary?

Some useful dictionary methods are:

• clear() – removes all elements
• copy() – shallow copy of dictionary
• fromkeys() – creates dictionary from sequence of keys
• get() – returns value for key or default if missing
• items() – returns tuple view of keys and values
• keys() – returns view object of keys
• pop() – removes and returns value of passed key
• popitem() – removes and returns arbitrary key-value pair
• update() – updates dictionary with elements from another
• values() – returns view object of values

How are Dictionaries Different from Hashtables?

Though Python dictionaries are implemented internally using hashtables, they have some differences:

• Hashtables are lower level, dict is high level data structure
• Dictionaries have more methods and utilities for easy access
• Dicts can store heterogeneous data while hashtables store only hashes
• Dicts are integrated into Python while hashtables are a standalone DS

What is Dictionary Comprehension in Python?

Dictionary comprehension is an elegant way to create dictionaries in a declarative way similar to list comprehensions.

The basic syntax is:

{key: value for vars in iterable}

This generates a dict with key mapped to value for elements in iterable.

For example:

dict = {i: i*2 for i in range(5)} # {0: 0, 1: 2, 2: 4, 3: 6, 4: 8}

How to Sort a Dictionary by Keys or Values?

Since dictionaries are inherently unordered, we need to obtain a sorted list of tuples first:

dict = {'c': 1, 'a': 3, 'b': 2} # Sort by keyssorted_keys = sorted(dict.keys()) # Sort by values sorted_values = sorted(dict.values())

To recover dict from the sorted list, pass it to dict() constructor:

sorted_dict = dict(sorted(dict.items(), key=lambda x: x[0])) # sorted keyssorted_dict = dict(sorted(dict.items(), key=lambda x: x[1])) # sorted values

This sorts the dictionary in increasing order of keys or values.

We have covered the most common and important dictionary interview questions that you need to know. Practice these questions to gain confidence for tackling dictionary problems in coding interviews.