使用 reader + itertools 创建带有嵌套列表的字典（从 txt 文件读取）

Question

I have created this file and want the return-parameter be a dictionary with the form {animal name: [date, weight]...}

import itertools
import csv
        def readanimal(file):
      animal_map = {}
      with open(filnamn, encoding="utf-8") as file:
        reader = csv.reader(file, delimiter="\t")

        for new_animal, rows in itertools.groupby(reader, lambda row: len(row) == 1):
          if new_animal:
            animal = next(rader)[0]
          else:
            animal_map[animal] = list(rows)
            del animal
      return(animal_map)

I read from a file with the following format:

Pig
21-10-26  96.58
21-10-27  95.35
21-10-28  94.36
21-10-29  94.00
21-11-01  93.26
21-11-02  91.93
21-11-03  93.52
21-11-04  93.58
21-11-05  95.00
21-11-08  95.36
21-11-09  95.89
21-11-10  96.26
Bear
21-10-22\t [weight] (for every date below)
21-10-25
21-10-26
21-10-27
21-10-28
21-10-29
21-11-01
21-11-02
21-11-03
21-11-04
21-11-05

But all I get is an empty dictionary when doing print(readanimal("filename.txt")). What have I done wrong?

Answer 1

I don't think groupby adds a lot of value here; it's easier to just keep track of which animal you're on as you add each row to the dictionary. (It would be a lot easier of the type of animal was a column instead of a header row -- then you could indeed groupby that value and this would practically be a one-liner.)

Simplified input file animals.txt (since yours wasn't valid as-is):

Pig
21-10-26        96.58
21-10-27        95.35
Bear
21-10-22        100
21-10-25        100

and code that just builds the dict as I described:

import csv


def readanimal(filename):
    animal_map = {}
    current = []
    with open(filename, encoding="utf-8") as file:
        for row in csv.reader(file, delimiter="\t"):
            if len(row) == 1:
                current = []
                animal_map[row[0]] = current
            else:
                current.append(row)
    return animal_map


print(readanimal("animals.txt"))

prints:

{'Pig': [['21-10-26', '96.58'], ['21-10-27', '95.35']], 'Bear': [['21-10-22', '100'], ['21-10-25', '100']]}