在python3中的类中向列表中添加行时出现无限循环

Question

我有一个包含两个类的脚本。 （显然，我删除了很多我认为与我正在处理的错误无关的内容。）最终的任务是创建决策树，正如我在 这个问题。

不幸的是，我遇到了无限循环，并且很难确定原因。我已经确定了出错的代码行，但我认为迭代器和我要添加的列表将是不同的对象。列表的 .append 功能是否有一些我不知道的副作用？或者我犯了其他一些明显的错误？

class Dataset:
    individuals = [] #Becomes a list of dictionaries, in which each dictionary is a row from the CSV with the headers as keys
    def field_set(self): #Returns a list of the fields in individuals[] that can be used to split the data (i.e. have more than one value amongst the individuals
    def classified(self, predicted_value): #Returns True if all the individuals have the same value for predicted_value
    def fields_exhausted(self, predicted_value): #Returns True if all the individuals are identical except for predicted_value
    def lowest_entropy_value(self, predicted_value): #Returns the field that will reduce <a href="http://en.wikipedia.org/wiki/Entropy_%28information_theory%29">entropy</a> the most
    def __init__(self, individuals=[]):

我的初始化代码

class Node:
    ds = Dataset() #The data that is associated with this Node
    links = [] #List of Nodes, the offspring Nodes of this node
    level = 0 #Tree depth of this Node
    split_value = '' #Field used to split out this Node from the parent node
    node_value = '' #Value used to split out this Node from the parent Node

    def split_dataset(self, split_value): #Splits the dataset into a series of smaller datasets, each of which has a unique value for split_value.  Then creates subnodes to store these datasets.
        fields = [] #List of options for split_value amongst the individuals
        datasets = {} #Dictionary of Datasets, each one with a value from fields[] as its key
        for field in self.ds.field_set()[split_value]: #Populates the keys of fields[]
            fields.append(field)
            datasets[field] = Dataset()
        for i in self.ds.individuals: #Adds individuals to the datasets.dataset that matches their result for split_value
            datasets[i[split_value]].individuals.append(i) #<---Causes an infinite loop on the second hit
        for field in fields: #Creates subnodes from each of the datasets.Dataset options
            self.add_subnode(datasets[field],split_value,field)

    def add_subnode(self, dataset, split_value='', node_value=''):
    def __init__(self, level, dataset=Dataset()):

目前是：

if __name__ == '__main__':
    filename = (sys.argv[1]) #Takes in a CSV file
    predicted_value = "# class" #Identifies the field from the CSV file that should be predicted
    base_dataset = parse_csv(filename) #Turns the CSV file into a list of lists
    parsed_dataset = individual_list(base_dataset) #Turns the list of lists into a list of dictionaries
    root = Node(0, Dataset(parsed_dataset)) #Creates a root node, passing it the full dataset
    root.split_dataset(root.ds.lowest_entropy_value(predicted_value)) #Performs the first split, creating multiple subnodes
    n = root.links[0] 
    n.split_dataset(n.ds.lowest_entropy_value(predicted_value)) #Attempts to split the first subnode.

Answer 1

class Dataset:
    individuals = []

可疑的。除非您希望有一个由 Dataset 的所有实例共享的静态成员列表，否则您不应该这样做。如果您在 __init__ 中设置 self.individuals= Something，那么您也不需要在此处设置 individuals。

    def __init__(self, individuals=[]):

还是很可疑。您是否将 individuals 参数分配给 self.individuals ？如果是这样，您将在函数定义时创建的相同individuals列表分配给使用默认参数创建的每个Dataset。将一项添加到一个Dataset 的列表中，并且在没有显式individuals 参数的情况下创建的所有其他项也将获得该项。

类似地：

class Node:
    def __init__(self, level, dataset=Dataset()):

所有在没有显式dataset参数的情况下创建的Node都将接收完全相同的默认Dataset实例。

这是可变默认参数问题以及破坏性的类型- 它产生的迭代似乎很可能导致无限循环。

Answer 2

我怀疑您正在附加到您正在迭代的同一个列表，导致它在迭代器到达末尾之前增加大小。尝试迭代列表的副本：

for i in list(self.ds.individuals):
    datasets[i[split_value]].individuals.append(i)