This codebase contains solutions for an interview task assigned which involves extracting and processing data from a file to identify top scorers. The problem statement can be found in PDF file problem_statement.pdf in the same directory.
- Python 3.x
get_top_scorers.py: Includes functions to parse the CSV and identify top scorers.test_top_scorers.py: Contains unittests for the functions inget_top_scorers.py.
python get_top_scorers.py
python -m unittest tests/test_top_scorers.py
###Design Choices and Assumptions
#####Functional Approach: Chose a simple, straightforward script with distinct functions (load_csv, parse_csv, find_top_scorers) instead of a class-based approach to avoid unnecessary complexity. Separation of Concerns: Each function handles a single task, ensuring simplicity and adherence to the Single Responsibility Principle. Data Format: Utilized a list of tuples to store parsed data, with each tuple containing a full name (string) and score (integer) for easy handling. Exception Handling: Basic error management is included to handle common issues like file not found or incorrect data format.
#####Assumptions: Data Format: Assumes file data is structured as (first name, second name, score) and score is an integer, also assumes that the first line in the data is the headers. Data Validity: Assumes that the provided data is clean and does not require extensive validation.
######Why Not a Class? A class might bring additional complexity without clear benefits for this simple, linear flow of operations. A functional approach offers clear, readable, and easily testable code. If the script grows in functionality in the future (e.g., additional filtering, handling various data formats), considering a class structure might be revisited.