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csv.DictReader()默认情况下，将列中的值作为字符串提取。 有没有办法为某些列指定转换？

每次我访问由csv.DictReader()其中包含非字符串元素创建的字典列表时，我最终都会做很多这样的小麻烦：

with open("data.csv","r") as data_file:
    items = csv.DictReader(data_file, fieldnames=('id', 'length', 'note'))
    for item in items:
        item['length'] = float(item['length'])  #### <--- MINOR ANNOYANCE 
        # ... do loop stuff

如果我能告诉csv.DictReader它当它到达某个字段时，它应该进行float()（或int()等date()）转换会更容易。

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1 回答 1

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不是开箱即用，不。您可以子类DictReader()化或创建为您映射行的生成器函数：

def convert_fields(iterable, **conversions):
    for item in iterable:
        for key in item.viewkeys() & conversions:
            item[key] = conversions[key](item[key])
        yield item

对于 Python 3，替换dict.viewkeys()为dict.keys()，因为 Python 3 默认返回字典视图。

用它包装你csv.DictReader()，为你的每一列添加转换函数：

with open("data.csv","r") as data_file:
    items = csv.DictReader(data_file, fieldnames=('id', 'length', 'note'))
    items = convert_fields(items, length=float)
    for item in items:
        # item['length'] is now always a float

对于不映射到 python 标识符（带有空格等）的列名，请使用**{..}语法传入字典：

with open("data.csv","r") as data_file:
    items = csv.DictReader(data_file, fieldnames=('id', 'length', 'note'))
    fieldconv = {'id': int, 'length': float, 'spaced column': float}
    items = convert_fields(items, **fieldconv)
    for item in items:
        # item['length'] and item['spaced column'] are now floats
        # item['id'] is always an int
于 2013-09-22T15:39:50.050 回答