Skills Tests - Technical
Python test
The Python test evaluates a candidate's ability to write efficient code using Python, covering topics like data structures, libraries, algorithms, and best practices for software development.
Type: Technical
Difficulty: Standard
Duration: 10 mins
Language: English
About the Python test
The Python test is designed to assess a candidate’s proficiency in Python programming, covering a wide range of topics from basic syntax to advanced concepts. The test evaluates both theoretical knowledge and practical coding skills.
Candidates will first be tested on core Python features such as variables, operators, data types, and control flow. Additionally, the test explores fundamental programming concepts like functions, loops, and error handling, which are essential for writing efficient Python code.
The test delves into data structures, including lists, dictionaries, tuples, and sets, as well as more advanced structures like queues and stacks. Candidates will need to demonstrate their ability to choose the most appropriate data structure for specific tasks while optimizing for performance.
Algorithms are another key focus. The test assesses candidates on their ability to implement efficient sorting and searching algorithms. Additionally, candidates will be tested on advanced problem-solving techniques such as recursion and dynamic programming.
Python libraries are an integral part of Python development, and the test covers popular libraries like NumPy, Pandas, and Matplotlib. Candidates should be familiar with using these libraries for data analysis, manipulation, and visualization.
The test includes questions on object-oriented programming (OOP) concepts like classes, inheritance, polymorphism, and encapsulation. Additionally, candidates will be tested on functional programming concepts, including decorators and lambda functions.
Software development best practices are also examined, with an emphasis on writing clean, maintainable code, adhering to PEP 8 standards, and performing debugging and testing. Error handling is another key area, with candidates expected to demonstrate their ability to write resilient code that handles exceptions gracefully.
Finally, candidates will be assessed on their familiarity with version control systems like Git and their ability to collaborate using platforms such as GitHub. Knowledge of Python frameworks like Flask and Django is also covered, with candidates expected to understand how to build web applications or APIs using these frameworks.
Multiple-choice test
Key skills measured
Python syntax and data types
Control flow (loops, conditions)
Functions and error handling
Data structures (lists, sets, dictionaries, etc.)
Algorithms (sorting, searching)
Object-oriented programming (OOP)
Functional programming (lambda, decorators)
Python libraries (NumPy, Pandas, Matplotlib)
Software development best practices
Version control systems (Git)
Python frameworks (Flask, Django)
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