初始化期间为namedtuple字段键入转换

时间:2017-06-18 11:29:08

标签: python namedtuple iterable-unpacking

我有一个几乎没有静态字段的类,它是从iterable初始化的(比如csvreader的输出)。 __init__执行从字符串到数字的类型转换:

class PerformanceTestResult(object):
    def __init__(self, csv_row):
        # csv_row[0] is just an ordinal number of the test - skip that
        self.name = csv_row[1]          # Name of the performance test
        self.samples = int(csv_row[2])  # Number of measurement samples taken
        self.min = int(csv_row[3])      # Minimum runtime (ms)
        self.max = int(csv_row[4])      # Maximum runtime (ms)
        self.mean = int(csv_row[5])     # Mean (average) runtime (ms)
        self.sd = float(csv_row[6])     # Standard deviation (ms)

我正在考虑将其转换为namedtuple,因为它没有太多其他内容。但我想在初始化期间保持类型转换。有没有办法用namedtuple执行此操作? (我没有在__init__工厂方法的详细输出中注意到namedtuple方法,这让我暂停了默认初始化程序的工作方式。)

1 个答案:

答案 0 :(得分:1)

您可以使用解包运算符csv_row 解压缩,而不是按原样传入*。例如:

>>> def f(a, b):
...     return a + b
...
>>> csv_row = [1, 2]
>>> f(*csv_row)  # Instead of your current f(csv_row)

这也适用于namedtuple,因为参数的顺序将在解包时保留:

>>> from collections import namedtuple
>>> PerformanceTestResult = namedtuple('PerformanceTestResult', [
...     'name',
...     'samples',
...     'min',
...     'max',
...     'mean',
...     'sd',
... ])
>>> test_row = ['test', '123', 2, 5, 3, None]  # from your csv file
>>> ptr = PerformanceTestResult(*test_row)
>>> ptr
PerformanceTestResult(name='test', samples='123', min=2, max=5, mean=3, sd=None)

这不仅允许您使用namedtuple,这似乎是一个非常好的主意,但它也使您的PerformanceTestResult无需了解CSV文件!抽象是好的,因为现在你可以使用同一个类,无论数据来自何处以及采用何种格式。

如果您需要int()float()转换,则必须编写单独的转换功能。您可以通过子类化将其构建到PerformanceTestResult

_PerformanceTestResult = namedtuple('PerformanceTestResult', [...])

class PerformanceTestResult(_PerformanceTestResult):
    @classmethod
    def from_csv(cls, row):
        return cls(
            row[0],
            int(row[1]),
            int(row[2]),
            int(row[3]),
            int(row[4]),
            int(row[5]),
            float(row[6])
        )

可以这样使用:

>>> ptr = PerformanceTestResult.from_csv(your_csv_row)

或者您可以创建单独的转换功能:

def parse_csv_row(row):
    return (row[0], int(row[1]), ...)

现在使用它在解包之前转换行:

>>> ptr = PerformanceTestResult(*parse_csv_row(your_csv_row))