在嵌套函數中，我想調用內部函數

Question

我有一個名為 IrisData 的類。 我在其中定義了一個函數作為描述。

• description 有多個我想要訪問的子功能。

• 我希望我的功能像

  1. 如果調用描述，它應該返回描述中定義的每個函數。 代碼行：打印（I.description（））

  2. 當調用內部函數時，它應該只返回內部函數。 代碼行：打印（I.description.attribute())*

PFB 代碼片段：

class IrisData:

    def urls(self):
        self.url='https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
        return self.url
    def columns(self):
        self.column_name=['sepal length','sepal width','petal length','petal width','class']
        return self.column_name
    def description(self):
        def title():
            self.titles ='Title: Iris Plants Database'
            return self.titles
        def source():
            self.sources='''Sources:
     \t(a) Creator: R.A. Fisher
     \t(b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)
     \t(c) Date: July, 1988'''
            return self.sources
        def info():
            self.descri='''Relevant Information:
     \t--- This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day.  (See Duda & Hart, for
 example.
     \t--- The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly
 separable from each other.
     \t--- Predicted attribute: class of iris plant.
     \t--- This is an exceedingly simple domain.
     \t--- This data differs from the data presented in Fishers article (identified by Steve Chadwick,  spchadwick@espeedaz.net )
     \tThe 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa"
     \twhere the error is in the fourth feature.
     \tThe 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa"
     \twhere the errors are in the second and third features. '''
            return self.descri
        def attribute():
            self.attri="""Attribute Information:
   1. sepal length in cm
   2. sepal width in cm
   3. petal length in cm
   4. petal width in cm
   5. class: 
      -- Iris Setosa
      -- Iris Versicolour
      -- Iris Virginica"""
            return self.attri
        return attribute(),info(),source(),title()

I=IrisData()
print(I.urls())
print(I.columns())
print(I.description())
print(I.description.attribute())

Answer 1

您需要將描述部分設為自己的類。 然后，您需要決定它是包含數據類的屬性，還是返回它的函數； 檢索它的語法是不同的。 您需要的代碼結構大綱（遵循您現有的風格）可以是：

class Description:
  def title(self): ...
  def source(self): ...
  def info(self): ...
  def attribute(self): ...

class IrisData:
  def description(self):
    self.desc = Description()
    return self.desc

data = IrisData()
print(data.description())
print(data.description().attribute())

但是，對於像這樣的簡單數據記錄，更常見的是將事物直接存儲為對象的屬性。 我會寫：

class IrisData:
  def __init__(self, url, description, ...):
    self.url = url
    self.description = description
    # and set the other properties here

  # but there are no accessor functions here
  # and no functions that retrieve object state, but only by mutating it

data = IrisData('https://archive.ics.uci.edu/ml/...',
                Description(...),
                ...)
print(data.url)
print(data.description.attribute)

Answer 2

您可能不會更改某些變量名稱，但這應該可以執行您想要存檔的操作：

class IrisData(object):
    def __init__(self):
        self.descript = self.des()

    def urls(self):
        self.url='https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data'
        return self.url
    def columns(self):
        self.column_name=['sepal length','sepal width','petal length','petal width','class']
        return self.column_name

    def description(self):
        return self.descript.attribute(),self.descript.info(),self.descript.source(),self.descript.title()

    class des():
        def title(self):
            self.titles ='Title: Iris Plants Database'
            return self.titles
        def source(self):
            self.sources='''Sources:
     \t(a) Creator: R.A. Fisher
     \t(b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov)
     \t(c) Date: July, 1988'''
            return self.sources
        def info(self):
            self.descri='''Relevant Information:
     \t--- This is perhaps the best known database to be found in the pattern recognition literature. Fisher's paper is a classic in the field and is referenced frequently to this day.  (See Duda & Hart, for
 example.
     \t--- The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are NOT linearly
 separable from each other.
     \t--- Predicted attribute: class of iris plant.
     \t--- This is an exceedingly simple domain.
     \t--- This data differs from the data presented in Fishers article (identified by Steve Chadwick,  spchadwick@espeedaz.net )
     \tThe 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa"
     \twhere the error is in the fourth feature.
     \tThe 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa"
     \twhere the errors are in the second and third features. '''
            return self.descri
        def attribute(self):
            self.attri="""Attribute Information:
   1. sepal length in cm
   2. sepal width in cm
   3. petal length in cm
   4. petal width in cm
   5. class: 
      -- Iris Setosa
      -- Iris Versicolour
      -- Iris Virginica"""
            return self.attri

if __name__ == "__main__":
    I=IrisData()
    print(I.urls())
    print(I.columns())
    print(I.description())
    print(I.descript.attribute())

我將描述方法更改為一個類，因此它可以存儲變量。 這使得I.description.attribute()可能，你不能在 python 中調用函數。 此外，新類是在 IrisData 類的構造函數中創建的，因此當您創建 IrisData 對象時，它們都會被創建。