我正在尝试设置pd.DataFrame的子类，该子类在初始化时具有两个必需的参数（group和timestamp_col）。我想对那些参数group和timestamp_col进行验证，因此我对每个属性都有一个setter方法。这一切都有效，直到我尝试set_index()并获得TypeError: 'NoneType' object is not iterable。在test_set_index和test_assignment_with_indexed_obj中似乎没有参数传递给我的setter函数。如果将if g == None: return添加到我的setter函数中，则可以通过测试用例，但认为这不是正确的解决方案。
我应该如何为这些必需的参数实现属性验证？
下面是我的课：
import pandas as pd
import numpy as np
class HistDollarGains(pd.DataFrame):
@property
def _constructor(self):
return HistDollarGains._internal_ctor
_metadata = ["group", "timestamp_col", "_group", "_timestamp_col"]
@classmethod
def _internal_ctor(cls, *args, **kwargs):
kwargs["group"] = None
kwargs["timestamp_col"] = None
return cls(*args, **kwargs)
def __init__(
self,
data,
group,
timestamp_col,
index=None,
columns=None,
dtype=None,
copy=True,
):
super(HistDollarGains, self).__init__(
data=data, index=index, columns=columns, dtype=dtype, copy=copy
)
self.group = group
self.timestamp_col = timestamp_col
@property
def group(self):
return self._group
@group.setter
def group(self, g):
if g == None:
return
if isinstance(g, str):
group_list = [g]
else:
group_list = g
if not set(group_list).issubset(self.columns):
raise ValueError("Data does not contain " + '[' + ', '.join(group_list) + ']')
self._group = group_list
@property
def timestamp_col(self):
return self._timestamp_col
@timestamp_col.setter
def timestamp_col(self, t):
if t == None:
return
if not t in self.columns:
raise ValueError("Data does not contain " + '[' + t + ']')
self._timestamp_col = t
这是我的测试用例：
import pytest
import pandas as pd
import numpy as np
from myclass import *
@pytest.fixture(scope="module")
def sample():
samp = pd.DataFrame(
[
{"timestamp": "2020-01-01", "group": "a", "dollar_gains": 100},
{"timestamp": "2020-01-01", "group": "b", "dollar_gains": 100},
{"timestamp": "2020-01-01", "group": "c", "dollar_gains": 110},
{"timestamp": "2020-01-01", "group": "a", "dollar_gains": 110},
{"timestamp": "2020-01-01", "group": "b", "dollar_gains": 90},
{"timestamp": "2020-01-01", "group": "d", "dollar_gains": 100},
]
)
return samp
@pytest.fixture(scope="module")
def sample_obj(sample):
return HistDollarGains(sample, "group", "timestamp")
def test_constructor_without_args(sample):
with pytest.raises(TypeError):
HistDollarGains(sample)
def test_constructor_with_string_group(sample):
hist_dg = HistDollarGains(sample, "group", "timestamp")
assert hist_dg.group == ["group"]
assert hist_dg.timestamp_col == "timestamp"
def test_constructor_with_list_group(sample):
hist_dg = HistDollarGains(sample, ["group", "timestamp"], "timestamp")
def test_constructor_with_invalid_group(sample):
with pytest.raises(ValueError):
HistDollarGains(sample, "invalid_group", np.random.choice(sample.columns))
def test_constructor_with_invalid_timestamp(sample):
with pytest.raises(ValueError):
HistDollarGains(sample, np.random.choice(sample.columns), "invalid_timestamp")
def test_assignment_with_indexed_obj(sample_obj):
b = sample_obj.set_index(sample_obj.group + [sample_obj.timestamp_col])
def test_set_index(sample_obj):
# print(isinstance(a, pd.DataFrame))
assert sample_obj.set_index(sample_obj.group + [sample_obj.timestamp_col]).index.names == ['group', 'timestamp']
set_index()方法将在内部调用self.copy()以创建您的DataFrame对象的副本（请参见源代码here），在其中它使用您的自定义构造函数方法_internal_ctor()来创建新对象（ source）。请注意，self._constructor()与self._internal_ctor()相同，这是几乎所有熊猫类的通用内部方法，用于在诸如深复制或切片之类的操作期间创建新实例。您的问题实际上源自此功能：
class HistDollarGains(pd.DataFrame):
...
@classmethod
def _internal_ctor(cls, *args, **kwargs):
kwargs["group"] = None
kwargs["timestamp_col"] = None
return cls(*args, **kwargs) # this is equivalent to calling
# HistDollarGains(data, group=None, timestamp_col=None)
我想您是从the github issue复制了此代码。kwargs["**"] = None行明确告诉构造函数将None设置为group和timestamp_col。最后，设置器/验证器将None作为新值，并引发错误。
因此，应将可接受的值设置为group和timestamp_col。
@classmethod
def _internal_ctor(cls, *args, **kwargs):
kwargs["group"] = []
kwargs["timestamp_col"] = 'timestamp' # or whatever name that makes your validator happy
return cls(*args, **kwargs)
然后您可以删除验证器中的if g == None: return行。