# Created on savesnippets.com · https://savesnippets.com/nCa1Q6yjvVs9AE
import csv
from pathlib import Path
from typing import Iterator

def csv_rows(path: str | Path) -> Iterator[dict[str, str]]:
    with Path(path).open("r", encoding="utf-8-sig", newline="") as f:
        yield from csv.DictReader(f)

for row in csv_rows("export.csv"):
    print(row["email"], row["signup_date"])
    # uses ~constant memory regardless of file size

# Count by category lazily — only one row in RAM at a time
from collections import Counter
counts = Counter(row["category"] for row in csv_rows("transactions.csv"))
print(counts.most_common(10))