Adaface Public Python Questions
Adaface assessments are tailored to your job description by our subject matter experts from our library of 10000+ questions. We've made a small portion of our library public to demonstrate the quality of questions in our library. All questions used in Adaface assessments are non-googleable and designed to test for on-the-job skills.
|🧐 Question||🔧 Skill||💪 Difficulty||⌛ Time|
|ZeroDivisionError and IndexError - What will the following Pyt...||Python||Medium||2 min|
|Session - The function high_sess shou...||Python||Hard||2 min|
|Max Code - Below are code lines to cre...||Python||Easy||2 min|
ZeroDivisionError and IndexError
What will the following Python code output?
The function high_sess should compute the highest number of events ...
Customized by subject matter experts to cater to job roles for all experience levels (fresh grads to 8-10 years) within your organization.
Adaface assessments have an average test taking rate of 86% as compared to an industry standard of 50%.
Adaface assessments have relevant questions that test for on-the-job skills. We do not expect candidates to solve puzzles/ trick questions.
About Adaface Python Questions
Adaface Python questions are designed by experts in the Python programming language to test for on-the-jobs skills, not just theoretical knowledge. Some of the popular topics the questions will cover are:
- Classes, Objects, Loops, Exceptions
- Strings, Lists, Tuples, Dictionary
- Dictionaries and Sets
- Conditional Execution & Loops
- Scopes and Namespaces
- File Handling
- Object Oriented Programming
- Iterator, Generator, Decorators
- Lambda Expressions
- Regular expressions
- CGI programming
- Socket programming
- Writing Libraries
- Building Frameworks
- Closure, Function Factory, Method Chaining
- Exception Handling, Context Manager
- Metaclasses, Introspection
- Multithreading, Multiprocessing
We evaluated several of their competitors and found Adaface to be the most compelling. Great default library of questions that are designed to test for fit rather than memorization of algorithms.