'''
Medium Rehashing Show result 

25% Accepted
The size of the hash table is not determinate at the very beginning. If the total size of keys is too large (e.g. size >= capacity / 10), we should double the size of the hash table and rehash every keys. Say you have a hash table looks like below:

size=3, capacity=4

[null, 21, 14, null]
       ↓    ↓
       9   null
       ↓
      null
The hash function is:

int hashcode(int key, int capacity) {
    return key % capacity;
}
here we have three numbers, 9, 14 and 21, where 21 and 9 share the same position as they all have the same hashcode 1 (21 % 4 = 9 % 4 = 1). We store them in the hash table by linked list.

rehashing this hash table, double the capacity, you will get:

size=3, capacity=8

index:   0    1    2    3     4    5    6   7
hash : [null, 9, null, null, null, 21, 14, null]
Given the original hash table, return the new hash table after rehashing .

Have you met this question in a real interview? Yes
Example
Given [null, 21->9->null, 14->null, null],

return [null, 9->null, null, null, null, 21->null, 14->null, null]

Note
For negative integer in hash table, the position can be calculated as follow:

C++/Java: if you directly calculate -4 % 3 you will get -1. You can use function: a % b = (a % b + b) % b to make it is a non negative integer.
Python: you can directly use -1 % 3, you will get 2 automatically.
'''



"""
Definition of ListNode
class ListNode(object):

    def __init__(self, val, next=None):
        self.val = val
        self.next = next
"""
class Solution:
    """
    @param hashTable: A list of The first node of linked list
    @return: A list of The first node of linked list which have twice size
    """
    def rehashing(self, hashTable):
        if not hashTable: return 
    
        old_size = len(hashTable)
        new_size = old_size * 2
        newHashtable = [None for i in xrange(new_size)]
        
        for start in hashTable:
                while start != None:
                    index = start.val % new_size 
                    temp = newHashtable[index]
                    if temp != None:
                        while temp and temp.next:
                            temp = temp.next 
                        temp.next = ListNode(start.val)
                    else:
                        newHashtable[index] = ListNode(start.val)
                        
                    start = start.next 
        
        return newHashtable
            

Create Rehash.py