Efficient Python Aggregation | Dataford Interview Questions

How would you implement a function to aggregate data efficiently in Python?

Implement aggregate_data(records, group_by, sum_fields). records is a list of dictionaries, group_by is the grouping-field name, and sum_fields lists numeric fields to sum. Return a list of dictionaries ordered by each group’s first appearance. Each output dictionary contains the grouping field and the requested sums. Assume every record contains all requested fields and grouping values are hashable.

Constraints

0 <= len(records) <= 1000
1 <= len(sum_fields) <= 20
Every record contains group_by and every field in sum_fields
Grouping values are hashable
Values in sum_fields are integers or floating-point numbers
Output groups must follow first-appearance order

Function Signature

def aggregate_data(records, group_by, sum_fields):

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Problem

How would you implement a function to aggregate data efficiently in Python?

Constraints

0 <= len(records) <= 1000
1 <= len(sum_fields) <= 20
Every record contains group_by and every field in sum_fields
Grouping values are hashable
Values in sum_fields are integers or floating-point numbers
Output groups must follow first-appearance order

Function Signature

def aggregate_data(records, group_by, sum_fields):

Your question is Efficient Python Aggregation. 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.