Adapt Parser to Numeric Words | Dataford Interview Questions

Describe how you would refactor a current implementation to accommodate a new requirement such as parsing numeric words instead of literal integers for order processing.

Implement normalize_order_quantities(orders). Each order is a dictionary containing a quantity whose value is either an integer or a numeric word representing a value from 0 through 99. Return new order dictionaries with quantities converted to integers, preserving every other field and the original input order. Support case-insensitive words, spaces, and hyphens. Raise ValueError for unsupported values.

Constraints

0 <= len(orders) <= 10^4
Each order contains a quantity field
Quantities are integers or numeric words representing values from 0 through 99
Numeric words use English forms such as "seven", "twenty", or "forty-two"
Unsupported quantity values must raise ValueError
The input order list and its dictionaries must not be mutated

Function Signature

def normalize_order_quantities(orders):

Your question is Adapt Parser to Numeric Words. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.

Problem

Describe how you would refactor a current implementation to accommodate a new requirement such as parsing numeric words instead of literal integers for order processing.

Constraints

0 <= len(orders) <= 10^4
Each order contains a quantity field
Quantities are integers or numeric words representing values from 0 through 99
Numeric words use English forms such as "seven", "twenty", or "forty-two"
Unsupported quantity values must raise ValueError
The input order list and its dictionaries must not be mutated

Function Signature

def normalize_order_quantities(orders):

Your question is Adapt Parser to Numeric Words. Start with the requirements in the Question tab.

Run and submit as often as you like. When you're ready, talk me through your approach or go straight to the code.