第二种记忆方法

  1. cache = {}
  2. def wrap(*args):
  3. if args not in cache:
  4. cache[args] = func(*args)
  5. return cache[args]
  6. return wrap
  7. @memo
  8. def fib(i):
  9. if i < 2:
  10. return 1
  11. return fib(i-1) + fib(i-2)

第三种方法

  1. def fib(n):
  2. a, b = 0, 1
  3. for _ in xrange(n):
  4. a, b = b, a + b
  5. return b

2 变态台阶问题

一只青蛙一次可以跳上1级台阶,也可以跳上2级……它也可以跳上n级。求该青蛙跳上一个n级的台阶总共有多少种跳法。

  1. fib = lambda n: n if n < 2 else 2 * fib(n - 1)

3 矩形覆盖

我们可以用2*1的小矩形横着或者竖着去覆盖更大的矩形。请问用n个2*1的小矩形无重叠地覆盖一个2*n的大矩形,总共有多少种方法?

  1. f = lambda n: 1 if n < 2 else f(n - 1) + f(n - 2)

4 杨氏矩阵查找

在一个m行n列二维数组中,每一行都按照从左到右递增的顺序排序,每一列都按照从上到下递增的顺序排序。请完成一个函数,输入这样的一个二维数组和一个整数,判断数组中是否含有该整数。

使用Step-wise线性搜索。

  1. def get_value(l, r, c):
  2. return l[r][c]
  3. def find(l, x):
  4. m = len(l) - 1
  5. n = len(l[0]) - 1
  6. r = 0
  7. c = n
  8. while c >= 0 and r <= m:
  9. value = get_value(l, r, c)
  10. if value == x:
  11. return True
  12. elif value > x:
  13. c = c - 1
  14. elif value < x:
  15. r = r + 1
  16. return False

5 去除列表中的重复元素

用集合

  1. list(set(l))

用字典

  1. l1 = ['b','c','d','b','c','a','a']
  2. l2 = {}.fromkeys(l1).keys()
  3. print l2

用字典并保持顺序

  1. l1 = ['b','c','d','b','c','a','a']
  2. l2 = list(set(l1))
  3. l2.sort(key=l1.index)
  4. print l2

列表推导式

  1. l1 = ['b','c','d','b','c','a','a']
  2. l2 = []
  3. [l2.append(i) for i in l1 if not i in l2]

sorted排序并且用列表推导式.

6 链表成对调换

1->2->3->4转换成2->1->4->3.

7 创建字典的方法

  1. dict = {'name':'earth', 'port':'80'}
  1. items=[('name','earth'),('port','80')]
  2. dict2=dict(items)
  3. dict1=dict((['name','earth'],['port','80']))
  1. dict1={}.fromkeys(('x','y'),-1)
  2. dict={'x':-1,'y':-1}
  3. dict2={}.fromkeys(('x','y'))
  4. dict2={'x':None, 'y':None}

知乎远程面试要求编程

尾递归

  1. def _recursion_merge_sort2(l1, l2, tmp):
  2. if len(l1) == 0 or len(l2) == 0:
  3. tmp.extend(l1)
  4. tmp.extend(l2)
  5. return tmp
  6. else:
  7. if l1[0] < l2[0]:
  8. tmp.append(l1[0])
  9. del l1[0]
  10. else:
  11. tmp.append(l2[0])
  12. del l2[0]
  13. return _recursion_merge_sort2(l1, l2, tmp)
  14. def recursion_merge_sort2(l1, l2):
  15. return _recursion_merge_sort2(l1, l2, [])

思路:

定义一个新的空列表

比较两个列表的首个元素

小的就插入到新列表里

把已经插入新列表的元素从旧列表删除

直到两个旧列表有一个为空

再把旧列表加到新列表后面

  1. def loop_merge_sort(l1, l2):
  2. tmp = []
  3. while len(l1) > 0 and len(l2) > 0:
  4. if l1[0] < l2[0]:
  5. tmp.append(l1[0])
  6. del l1[0]
  7. else:
  8. tmp.append(l2[0])
  9. del l2[0]
  10. tmp.extend(l1)
  11. tmp.extend(l2)
  12. return tmp

pop弹出

  1. a = [1,2,3,7]
  2. b = [3,4,5]
  3. def merge_sortedlist(a,b):
  4. c = []
  5. while a and b:
  6. if a[0] >= b[0]:
  7. c.append(b.pop(0))
  8. else:
  9. c.append(a.pop(0))
  10. while a:
  11. c.append(a.pop(0))
  12. while b:
  13. c.append(b.pop(0))
  14. return c
  15. print merge_sortedlist(a,b)

9 交叉链表求交点

  1. # 使用a,b两个list来模拟链表,可以看出交叉点是 7这个节点
  2. a = [1,2,3,7,9,1,5]
  3. b = [4,5,7,9,1,5]
  4. for i in range(1,min(len(a),len(b))):
  5. if i==1 and (a[-1] != b[-1]):
  6. print "No"
  7. break
  8. else:
  9. if a[-i] != b[-i]:
  10. print "交叉节点:",a[-i+1]
  11. break
  12. else:
  13. pass

另外一种比较正规的方法,构造链表类

  1. class ListNode:
  2. def __init__(self, x):
  3. self.val = x
  4. def node(l1, l2):
  5. length1, lenth2 = 0, 0
  6. # 求两个链表长度
  7. while l1.next:
  8. length1 += 1
  9. while l2.next:
  10. l2 = l2.next
  11. length2 += 1
  12. # 长的链表先走
  13. if length1 > lenth2:
  14. for _ in range(length1 - length2):
  15. l1 = l1.next
  16. else:
  17. for _ in range(length2 - length1):
  18. l2 = l2.next
  19. while l1 and l2:
  20. if l1.next == l2.next:
  21. return l1.next
  22. else:
  23. l1 = l1.next
  24. l2 = l2.next

修改了一下:

  1. #coding:utf-8
  2. class ListNode:
  3. def __init__(self, x):
  4. self.val = x
  5. self.next = None
  6. def node(l1, l2):
  7. length1, length2 = 0, 0
  8. # 求两个链表长度
  9. while l1.next:
  10. l1 = l1.next#尾节点
  11. length1 += 1
  12. while l2.next:
  13. l2 = l2.next#尾节点
  14. length2 += 1
  15. #如果相交
  16. if l1.next == l2.next:
  17. # 长的链表先走
  18. if length1 > length2:
  19. for _ in range(length1 - length2):
  20. l1 = l1.next
  21. return l1#返回交点
  22. else:
  23. for _ in range(length2 - length1):
  24. l2 = l2.next
  25. return l2#返回交点
  26. # 如果不相交
  27. else:
  28. return

思路:

10 二分查找

参考: http://blog.csdn.net/u013205877/article/details/76411718

11 快排

  1. #coding:utf-8
  2. def quicksort(list):
  3. if len(list)<2:
  4. return list
  5. else:
  6. midpivot = list[0]
  7. lessbeforemidpivot = [i for i in list[1:] if i<=midpivot]
  8. biggerafterpivot = [i for i in list[1:] if i > midpivot]
  9. finallylist = quicksort(lessbeforemidpivot)+[midpivot]+quicksort(biggerafterpivot)
  10. return finallylist
  11. print quicksort([2,4,6,7,1,2,5])

12 找零问题

  1. #coding:utf-8
  2. #values是硬币的面值values = [ 25, 21, 10, 5, 1]
  3. #valuesCounts 钱币对应的种类数
  4. #money 找出来的总钱数
  5. #coinsUsed 对应于目前钱币总数i所使用的硬币数目
  6. def coinChange(values,valuesCounts,money,coinsUsed):
  7. #遍历出从1到money所有的钱数可能
  8. for cents in range(1,money+1):
  9. minCoins = cents
  10. #把所有的硬币面值遍历出来和钱数做对比
  11. for kind in range(0,valuesCounts):
  12. if (values[kind] <= cents):
  13. temp = coinsUsed[cents - values[kind]] +1
  14. if (temp < minCoins):
  15. minCoins = temp
  16. coinsUsed[cents] = minCoins
  17. print ('面值:{0}的最少硬币使用数为:{1}'.format(cents, coinsUsed[cents]))

思路:

方法: http://www.cnblogs.com/ChenxofHit/archive/2011/03/18/1988431.html

13 广度遍历和深度遍历二叉树

给定一个数组,构建二叉树,并且按层次打印这个二叉树

14 二叉树节点

  1. class Node(object):
  2. def __init__(self, data, left=None, right=None):
  3. self.data = data
  4. self.left = left
  5. self.right = right
  6. tree = Node(1, Node(3, Node(7, Node(0)), Node(6)), Node(2, Node(5), Node(4)))
  1. def lookup(root):
  2. stack = [root]
  3. while stack:
  4. current = stack.pop(0)
  5. print current.data
  6. if current.left:
  7. stack.append(current.left)
  8. if current.right:
  9. stack.append(current.right)

16 深度遍历

  1. def deep(root):
  2. if not root:
  3. return
  4. print root.data
  5. deep(root.left)
  6. deep(root.right)
  7. if __name__ == '__main__':
  8. lookup(tree)
  9. deep(tree)

17 前中后序遍历

深度遍历改变顺序就OK了

  1. #coding:utf-8
  2. #二叉树的遍历
  3. #简单的二叉树节点类
  4. class Node(object):
  5. def __init__(self,value,left,right):
  6. self.value = value
  7. self.left = left
  8. self.right = right
  9. #中序遍历:遍历左子树,访问当前节点,遍历右子树
  10. def mid_travelsal(root):
  11. mid_travelsal(root.left)
  12. print(root.value)
  13. if root.right is not None:
  14. mid_travelsal(root.right)
  15. #前序遍历:访问当前节点,遍历左子树,遍历右子树
  16. def pre_travelsal(root):
  17. print (root.value)
  18. if root.left is not None:
  19. pre_travelsal(root.left)
  20. if root.right is not None:
  21. pre_travelsal(root.right)
  22. #后续遍历:遍历左子树,遍历右子树,访问当前节点
  23. def post_trvelsal(root):
  24. if root.left is not None:
  25. post_trvelsal(root.left)
  26. if root.right is not None:
  27. post_trvelsal(root.right)
  28. print (root.value)

18 求最大树深

  1. def maxDepth(root):
  2. if not root:
  3. return 0
  4. return max(maxDepth(root.left), maxDepth(root.right)) + 1

19 求两棵树是否相同

  1. def isSameTree(p, q):
  2. if p == None and q == None:
  3. return True
  4. elif p and q :
  5. return p.val == q.val and isSameTree(p.left,q.left) and isSameTree(p.right,q.right)
  6. else :
  7. return False

20 前序中序求后序

推荐:

  1. def rebuild(pre, center):
  2. if not pre:
  3. return
  4. cur = Node(pre[0])
  5. index = center.index(pre[0])
  6. cur.left = rebuild(pre[1:index + 1], center[:index])
  7. cur.right = rebuild(pre[index + 1:], center[index + 1:])
  8. return cur
  9. def deep(root):
  10. if not root:
  11. return
  12. deep(root.left)
  13. deep(root.right)
  14. print root.data

21 单链表逆置

思路: http://blog.csdn.net/feliciafay/article/details/6841115

  1. class Anagram:
  2. """
  3. @:param s1: The first string
  4. @:param s2: The second string
  5. @:return true or false
  6. """
  7. def Solution1(s1,s2):
  8. alist = list(s2)
  9. pos1 = 0
  10. stillOK = True
  11. while pos1 < len(s1) and stillOK:
  12. pos2 = 0
  13. found = False
  14. while pos2 < len(alist) and not found:
  15. if s1[pos1] == alist[pos2]:
  16. found = True
  17. else:
  18. pos2 = pos2 + 1
  19. if found:
  20. alist[pos2] = None
  21. else:
  22. stillOK = False
  23. pos1 = pos1 + 1
  24. return stillOK
  25. print(Solution1('abcd','dcba'))
  26. def Solution2(s1,s2):
  27. alist1 = list(s1)
  28. alist2 = list(s2)
  29. alist1.sort()
  30. alist2.sort()
  31. pos = 0
  32. matches = True
  33. while pos < len(s1) and matches:
  34. if alist1[pos] == alist2[pos]:
  35. pos = pos + 1
  36. else:
  37. matches = False
  38. return matches
  39. print(Solution2('abcde','edcbg'))
  40. def Solution3(s1,s2):
  41. c1 = [0]*26
  42. c2 = [0]*26
  43. for i in range(len(s1)):
  44. pos = ord(s1[i])-ord('a')
  45. c1[pos] = c1[pos] + 1
  46. for i in range(len(s2)):
  47. pos = ord(s2[i])-ord('a')
  48. c2[pos] = c2[pos] + 1
  49. j = 0
  50. stillOK = True
  51. while j<26 and stillOK:
  52. if c1[j] == c2[j]:
  53. j = j + 1
  54. else:
  55. stillOK = False
  56. return stillOK

23 动态规划问题

可参考: