我首先将主图书列表读入一个dict，并键入图书的ID：

import csv

books: dict[str, list[str]] = {}

with open("books.csv", newline="", encoding="utf-8") as f:
    reader = csv.reader(f)
    header = next(reader)
    assert header == ["ID", "Title", "Author"], f"{header} != {['ID', 'Title', 'Author']}"

    for row in reader:
        books[row[0]] = row

字符串
阅读此CSV后：

ID,Title,Author
1,A Closed and Common Orbit,Becky Chambers
2,The Clan of the Cave Bear,Jean M. Auel
3,Sum,David Eagleman
4,the 13 1/2 lives of Captain Bluebear,Walter Moers

型
字典看起来像：

{
    "1": ["1", "A Closed and Common Orbit", "Becky Chambers"],
    "2": ["2", "The Clan of the Cave Bear", "Jean M. Auel"],
    "3": ["3", "Sum", "David Eagleman"],
    "4": ["4", "the 13 1/2 lives of Captain Bluebear", "Walter Moers"],
}

型
然后，我将贷款CSV读入一个单独的dict，并将 checkout 和返回的时间戳解析为真实的日期值（这将使数学和统计数据更容易，更准确）：

from datetime import date, datetime, timedelta

DATE_FMT = r"%Y/%m/%d"

loans: dict[str, list[tuple[date, date]]] = {}

with open("book_loans.csv", newline="", encoding="utf-8") as f:
    reader = csv.reader(f)

    for row in reader:
        book_id = row[0]
        checked_out = datetime.strptime(row[1], DATE_FMT).date()
        returned = datetime.strptime(row[2], DATE_FMT).date()

        if book_id not in loans:
            loans[book_id] = []

        loans[book_id].append((checked_out, returned))

型
阅读此贷款CSV后：

1,2000/01/01,2000/01/13
2,2000/01/01,2000/01/10
3,2000/01/04,2000/01/16
2,2000/01/11,2000/02/01
3,2000/01/12,2000/01/13
1,2000/01/12,2000/01/26

型
贷款dict看起来像：

{
    "1": [(date(2000, 1, 1), date(2000, 1, 13)), (date(2000, 1, 12), date(2000, 1, 26))],
    "2": [(date(2000, 1, 1), date(2000, 1, 10)), (date(2000, 1, 11), date(2000, 2, 1))],
    "3": [(date(2000, 1, 4), date(2000, 1, 16)), (date(2000, 1, 12), date(2000, 1, 13))],
}

型
一个图书ID，它指向一个日期对列表（每对日期都被检出并返回）。

• 注：第4册，船长。蓝熊，从未被租借。*

现在，有了所有可用书籍的完整列表和每本书（实际上是借出的）的借阅日期列表，您可以应用您需要的任何逻辑/数学。
我去了：

for book_id, row in books.items():
    title = row[1]
    author = row[2]

    if book_id not in loans:
        print(f"'{title}' by {author} was never loaned out. 🙁")
        continue

    loan_dates = loans[book_id]
    first_checked_out = date.max
    last_returned = date.min
    loan_durations: list[timedelta] = []

    for checked_out, returned in loan_dates:
        if checked_out < first_checked_out:
            first_checked_out = checked_out
        if returned > last_returned:
            last_returned = returned
        loan_durations.append(returned - checked_out)

    # https://stackoverflow.com/a/3617540/246801, give sum() a starting value of timedelta(0)
    avg_loan = sum(loan_durations, timedelta(0)) / len(loan_durations)

    print(
        f"'{title}', by {author}, was loaned {len(loan_durations)} times.  It was first checked out on {first_checked_out} and last returned on {last_returned}.  The average loan was {avg_loan.days} days."
    )

型
它打印：

'A Closed and Common Orbit', by Becky Chambers, was loaned 2 times.  It was first checked out on 2000-01-01 and last returned on 2000-01-26.  The average loan was 13 days.
'The Clan of the Cave Bear', by Jean M. Auel, was loaned 2 times.  It was first checked out on 2000-01-01 and last returned on 2000-02-01.  The average loan was 15 days.
'Sum', by David Eagleman, was loaned 2 times.  It was first checked out on 2000-01-04 and last returned on 2000-01-16.  The average loan was 6 days.
'the 13 1/2 lives of Captain Bluebear' by Walter Moers was never loaned out. 🙁

型