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Python (Coding): Data Structures Test

The Python Data Structures Test evaluates a candidate's proficiency in implementing and manipulating various data structures using Python. Through a combination of MCQs and coding questions, it assesses understanding of lists, tuples, dictionaries, sets, and advanced structures like stacks, queues, and trees. The test gauges the ability to choose appropriate data structures for different scenarios and optimize code performance.

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Screen candidates with a 30 mins test

Test duration:  ~ 30 mins
Difficulty level:  Moderate
Availability:  Available as custom test
Questions:
  • 5 Python MCQs
  • 1 Python Coding Question
Covered skills:
Lists
Tuples
Dictionaries
Sets
Arrays
Stacks
Queues
Linked Lists
Trees
Graphs
Hash Tables
Heaps
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The Python (Coding): Data Structures Test helps recruiters and hiring managers identify qualified candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves time by filtering out unqualified candidates at the first step of the hiring process.

The test screens for the following skills that hiring managers look for in candidates:

  • Demonstrate proficiency in implementing and manipulating various Python data structures
  • Efficiently utilize lists and tuples for storing and accessing ordered collections of data
  • Skillfully work with dictionaries to create key-value pair mappings and perform quick lookups
  • Effectively use sets for managing unique, unordered collections of elements
  • Implement and navigate complex tree structures, including binary trees and search trees
  • Design and manipulate graph data structures for representing relationships between objects
  • Utilize hash tables for efficient data retrieval and storage
  • Implement and manage stack and queue data structures for specific algorithmic needs
  • Work with linked lists to create dynamic, memory-efficient data structures
  • Apply heap data structures for priority queue implementations and sorting algorithms
  • Optimize data structure choices based on specific problem requirements and performance considerations
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Screen candidates with the highest quality questions

We have a very high focus on the quality of questions that test for on-the-job skills. Every question is non-googleable and we have a very high bar for the level of subject matter experts we onboard to create these questions. We have crawlers to check if any of the questions are leaked online. If/ when a question gets leaked, we get an alert. We change the question for you & let you know.

How we design questions

These are just a small sample from our library of 15,000+ questions. The actual questions on this Python (Coding): Data Structures Test will be non-googleable.

🧐 Question

Medium

ZeroDivisionError and IndexError
Exceptions
Solve
What will the following Python code output?
 image

Medium

Session
File Handling
Dictionary
Solve
 image
The function high_sess should compute the highest number of events per session of each user in the database by reading a comma-separated value input file of session data. The result should be returned from the function as a dictionary. The first column of each line in the input file is expected to contain the user’s name represented as a string. The second column is expected to contain an integer representing the events in a session. Here is an example input file:
Tony,10
Stark,12
Black,25
Your program should ignore a non-conforming line like this one.
Stark,3
Widow,6
Widow,14
The resulting return value for this file should be the following dictionary: { 'Stark':12, 'Black':25, 'Tony':10, 'Widow':14 }
What should replace the CODE TO FILL line to complete the function?
 image

Medium

Max Code
Arrays
Solve
Below are code lines to create a Python function. Ignoring indentation, what lines should be used and in what order for the following function to be complete:
 image

Medium

Recursive Function
Recursion
Dictionary
Lists
Solve
Consider the following Python code:
 image
In the above code, recursive_search is a function that takes a dictionary (data) and a target key (target) as arguments. It searches for the target key within the dictionary, which could potentially have nested dictionaries and lists as values, and returns the value associated with the target key. If the target key is not found, it returns None.

nested_dict is a dictionary that contains multiple levels of nested dictionaries and lists. The recursive_search function is then called with nested_dict as the data and 'target_key' as the target.

What will the output be after executing the above code?

Medium

Stacking problem
Stack
Linkedlist
Solve
What does the below function ‘fun’ does?
 image
A: Sum of digits of the number passed to fun.
B: Number of digits of the number passed to fun.
C: 0 if the number passed to fun is divisible by 10. 1 otherwise.
D: Sum of all digits number passed to fun except for the last digit.
🧐 Question🔧 Skill

Medium

ZeroDivisionError and IndexError
Exceptions

2 mins

Python
Solve

Medium

Session
File Handling
Dictionary

2 mins

Python
Solve

Medium

Max Code
Arrays

2 mins

Python
Solve

Medium

Recursive Function
Recursion
Dictionary
Lists

3 mins

Python
Solve

Medium

Stacking problem
Stack
Linkedlist

4 mins

Python
Solve
🧐 Question🔧 Skill💪 Difficulty⌛ Time
ZeroDivisionError and IndexError
Exceptions
Python
Medium2 mins
Solve
Session
File Handling
Dictionary
Python
Medium2 mins
Solve
Max Code
Arrays
Python
Medium2 mins
Solve
Recursive Function
Recursion
Dictionary
Lists
Python
Medium3 mins
Solve
Stacking problem
Stack
Linkedlist
Python
Medium4 mins
Solve

Test candidates on core Python (Coding): Data Structures Hiring Test topics

Lists: Lists are ordered, mutable sequences in Python. They allow storing multiple items of different data types and provide various methods for manipulation. Proficiency in lists is crucial for efficient data handling and algorithm implementation.

Tuples: Tuples are immutable, ordered sequences in Python. They offer performance benefits over lists for read-only operations and are commonly used for fixed data structures. Understanding tuples is essential for writing memory-efficient and secure code.

Dictionaries: Dictionaries are hash table-based data structures that store key-value pairs. They provide fast lookup and insertion operations, making them ideal for data organization and caching. Mastery of dictionaries is vital for efficient data management in Python.

Sets: Sets are unordered collections of unique elements in Python. They support mathematical set operations and are optimized for membership testing. Proficiency in sets is important for tasks involving unique data and set theory applications.

Arrays: Arrays are fixed-size, homogeneous data structures that offer efficient memory usage and fast access times. While not a built-in type in Python, understanding array concepts is crucial for low-level optimization and working with libraries like NumPy.

Stacks: Stacks are Last-In-First-Out (LIFO) data structures used for managing function calls, parsing expressions, and backtracking algorithms. Implementing and using stacks effectively is a fundamental skill in computer science and programming.

Queues: Queues are First-In-First-Out (FIFO) data structures essential for managing tasks, breadth-first searches, and scheduling algorithms. Proficiency in queue operations is crucial for developing efficient systems and algorithms.

Linked Lists: Linked lists are dynamic data structures consisting of nodes connected by pointers. They offer efficient insertion and deletion operations and are fundamental to understanding more complex data structures. Mastery of linked lists demonstrates strong algorithmic thinking.

Trees: Trees are hierarchical data structures with nodes connected by edges. They are used in various applications, including file systems, decision-making algorithms, and databases. Understanding tree structures and traversals is crucial for advanced algorithm design.

Graphs: Graphs are versatile data structures representing relationships between entities. They are essential for modeling networks, solving optimization problems, and implementing artificial intelligence algorithms. Proficiency in graph algorithms is highly valued in software engineering.

Hash Tables: Hash tables are data structures that provide constant-time average-case complexity for insertion, deletion, and lookup operations. They are fundamental to implementing efficient dictionaries and caches. Understanding hash tables is crucial for optimizing data retrieval in large datasets.

Heaps: Heaps are specialized tree-based data structures that satisfy the heap property. They are used in priority queues, sorting algorithms, and graph algorithms. Proficiency in heap operations is essential for developing efficient algorithms in various domains.

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Have questions about the Python (Coding): Data Structures Hiring Test?

What roles can I use the Python (Coding): Data Structures Assessment Test for?

Here are few roles for which we recommend this test:

  • Python Developer
  • Data Scientist
  • Software Engineer
  • Machine Learning Engineer
  • Backend Developer
  • Full Stack Developer
  • Data Analyst
  • DevOps Engineer
  • Artificial Intelligence Engineer
  • Research Scientist
Can I combine Python (Coding): Data Structures Test with SQL questions?

Yes, recruiters can request a custom test that includes both Python and SQL questions. Check out the Python & SQL Test for more details on assessing SQL skills.

How to use Python (Coding): Data Structures Test in my hiring process?

We recommend using this test as a pre-screening tool at the start of your hiring process. Add the test link in your job post or directly invite candidates via email.

Can I combine multiple skills into one custom assessment?

Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify. Here's a quick guide on how you can request a custom test.

How do I interpret test scores?

The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. A skills assessment is optimized to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best candidate for the role. So the ideal way to use an assessment is to decide a threshold score (typically 55%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.

Does every candidate get the same questions?

Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating/ proctoring features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.

What is the cost of using this test?

You can check out our pricing plans.

I just moved to a paid plan. How can I request a custom assessment?

Here is a quick guide on how to request a custom assessment on Adaface.

What is Python (Coding): Data Structures Test?

The Python (Coding): Data Structures Test is designed to evaluate a candidate's understanding and proficiency in using data structures in Python. This test is used by recruiters to identify candidates with strong Python programming skills, particularly in handling data structures.

What topics are evaluated in the Python (Coding): Data Structures Test?

This test evaluates knowledge in Lists, Tuples, Dictionaries, Sets, Arrays, Stacks, Queues, Linked Lists, Trees, Graphs, Hash Tables, and Heaps. For senior roles, it also assesses advanced skills like implementing hash tables, working with heaps, and applying graph algorithms.

What are the main coding tests?
Do you have any anti-cheating or proctoring features in place?

We have the following anti-cheating features in place:

  • Non-googleable questions
  • IP proctoring
  • Screen proctoring
  • Web proctoring
  • Webcam proctoring
  • Plagiarism detection
  • Secure browser
  • Copy paste protection

Read more about the proctoring features.

What experience level can I use this test for?

Each Adaface assessment is customized to your job description/ ideal candidate persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for any experience level.

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No. Unfortunately, we do not support practice tests at the moment. However, you can use our sample questions for practice.

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