如何找到一个很长的字符串的所有唯一子串?

时间:2014-05-20 17:45:13

标签: python string algorithm memory large-data

我有一个很长的字符串。我想找到这个字符串的所有唯一子串。我尝试编写代码,我使用 set (python)存储所有子字符串以确保唯一性。我得到了许多中大字符串的正确结果,但是如果字符串很大,我会得到一个MemoryError。我google了一下,发现python中的 set 数据结构有一个很大的RAM占用空间,这也许就是我得到MemoryError的原因。

这是我的代码:

a = set()
for i in range(n):
    string = raw_input()
    j = 1
    while True:
        for i in xrange(len(string)-j+1):   
            a.add(string[i:i+j])
        if j==len(string):   break
        j+=1
print sorted(list(a))

有没有办法避免大字符串的这个错误?或者任何人都可以在我的代码中建议更好的修改来处理这个问题?

P.S:我没有选择在32位和64位版本之间转换。

2 个答案:

答案 0 :(得分:4)

如果你真的需要它在内存中,那么你可以尝试制作一个后缀树。尝试不是外来数据结构,因此可能有很好的实现可用于主流语言,如Python,它们可用于实现后缀树。 Marisa-Trie应该可以获得良好的内存使用率。

  1. 创建一个空的trie。
  2. 对于[0,len(s)]中的每个n,将长度为n的后缀添加到Trie。
  3. 来自trie根的每条路径都是字符串中的子字符串,没有这样的路径不是字符串中的子字符串,路径是唯一的。

答案 1 :(得分:0)

这是一些基于O(n)后缀树结构的Python代码,用于从输入字符串集合中生成唯一的子字符串(输出应按排序顺序显示,因此之后无需对字符串进行排序)。 / p>

由于可能有O(n ^ 2)个输出字符串,实际输出所有字符串可能需要很长时间。

from collections import defaultdict

class SuffixTree:
    def __init__(self):
        """Returns an empty suffix tree"""
        self.T=''
        self.E={}
        self.nodes=[-1]

    def add(self,s):
        """Adds the input string to the suffix tree.

        This inserts all substrings into the tree.
        End the string with a unique character if you want a leaf-node for every suffix.

        Produces an edge graph keyed by (node,character) that gives (first,last,end)
        This means that the edge has characters from T[first:last+1] and goes to node end."""
        origin,first,last = 0,len(self.T),len(self.T)-1
        self.T+=s
        nc = len(self.nodes)
        self.nodes += [-1]*(2*len(s))
        T=self.T
        E=self.E
        nodes=self.nodes

        Lm1=len(T)-1
        for last_char_index in xrange(first,len(T)):
            c=T[last_char_index]
            last_parent_node = -1                    
            while 1:
                parent_node = origin
                if first>last:
                    if (origin,c) in E:
                        break             
                else:
                    key = origin,T[first]
                    edge_first, edge_last, edge_end = E[key]
                    span = last - first
                    A = edge_first+span
                    m = T[A+1]
                    if m==c:
                        break
                    E[key] = (edge_first, A, nc)
                    nodes[nc] = origin
                    E[nc,m] = (A+1,edge_last,edge_end)
                    parent_node = nc
                    nc+=1  
                E[parent_node,c] = (last_char_index, Lm1, nc)
                nc+=1  
                if last_parent_node>0:
                    nodes[last_parent_node] = parent_node
                last_parent_node = parent_node
                if origin==0:
                    first+=1
                else:
                    origin = nodes[origin]

                if first <= last:
                    edge_first,edge_last,edge_end=E[origin,T[first]]
                    span = edge_last-edge_first
                    while span <= last - first:
                        first+=span+1
                        origin = edge_end
                        if first <= last:
                            edge_first,edge_last,edge_end = E[origin,T[first]]
                            span = edge_last - edge_first

            if last_parent_node>0:
                nodes[last_parent_node] = parent_node
            last+=1
            if first <= last:
                    edge_first,edge_last,edge_end=E[origin,T[first]]
                    span = edge_last-edge_first
                    while span <= last - first:
                        first+=span+1
                        origin = edge_end
                        if first <= last:
                            edge_first,edge_last,edge_end = E[origin,T[first]]
                            span = edge_last - edge_first
        return self

    def make_choices(self):
        """Construct a sorted list for each node of the possible continuing characters"""
        choices = self.choices = [list() for n in xrange(len(self.nodes))] # Contains set of choices for each node
        for (origin,c),edge in self.E.items():
            choices[origin].append(c)
        choices=[sorted(s) for s in choices] # should not have any repeats by construction
        return choices

    def find_substrings(self,A,term):
        """Recurses through the tree appending unique substrings into A.
        Strings assumed to use term as the terminating character"""
        choices = self.make_choices()
        def f(node,depth):
            t=0
            for c in choices[node]:
                if c==term: continue
                first,last,end = self.E[node,c]
                # All end points along this edge result in new unique substrings
                edge_len = last-first+1
                a = first-depth
                for b in range(first,last+1):
                    if self.T[b]!=term:
                        A.append( self.T[a:b+1] )
                f(end,depth+edge_len)
            return t
        return f(0,0)

def fast_find_all_substrings(strings):
    S = SuffixTree()
    term = '\0'
    for string in strings:
        S.add(string+term)
    A=[]
    S.find_substrings(A,term)
    return A

A="abc","abcd","bca"
print fast_find_all_substrings(A)