Build a Simple ETL Pipeline (MLOps)

Problem

Implement a simple ETL (Extract-Transform-Load) pipeline for model-ready data preparation.

Given a CSV-like string containing user events with columns: user_id,event_type,value (header included), write a function run_etl(csv_text) that:

1. Extracts rows from the raw CSV text.
2. Transforms data by:
   • Filtering only rows where event_type == "purchase".
   • Converting value to float and dropping invalid rows.
   • Aggregating total purchase value per user_id.
3. Loads the transformed results by returning a list of (user_id, total_value) tuples sorted by user_id ascending.

Assume small inputs (no external libs), handle extra whitespace, and ignore blank lines.

# Implement your function below.

def run_etl(csv_text: str) -> list[tuple[str, float]]:
	"""Run a simple ETL pipeline over CSV text with header user_id,event_type,value.

	Returns a sorted list of (user_id, total_value) for event_type == "purchase".
	"""
	# TODO: implement extract, transform, and load steps
	raise NotImplementedError