[ADD] 添加java三道排序题: 冒泡排序，选择排序和插入排序

Author: jiangsir404

bitmap/bitmap.py

@@ -1,82 +1,82 @@
-#!/usr/bin/env python		
-#coding:utf-8
-
-"""
-python实现BitMap数据结构
-"""
-
-class BitMap1():
-	"""使用列表实现的bitmap位图功能, 不节省空间，只为了直观展示理解用途"""
-	def __init__(self, nbits):
-		self.nbits = nbits
-		self.bytes = [0] * (nbits + 1)
-
-	def set(self, k):
-		if k > self.nbits:
-			return
-		self.bytes[k] = self.bytes[k] | 1
-
-	def get(self, k):
-		if k > self.nbits:return false;
-		res = self.bytes[k] & 1 != 0
-		return res
-
-class BitMap2():
-	"""将数据存储有符号整数的前31位上面(兼容其他语言的整数最大表示大小，python已经不限制了)"""
-	def __init__(self, m):
-		"""
-		:param m: max size
-		"""
-		self.max_size = m
-		self.array = [0] * int((m + 31 -1) / 31) #多个整数来表示，防止大小不够
-
-	def bit_index(self, k):
-		"""获取第k个位置位索引下标
-		"""
-		return k % 31
-
-	def set(self, k):
-		"""设置第k个索引位置为1
-		"""
-		if k > self.max_size: return
-		array_index = k // 31 # 获取数组索引，即第k的位置落在数组第几个元素上
-		bit_index = self.bit_index(k) # 获取位索引
-		self.array[array_index] = self.array[array_index] | (1 << bit_index)
-
-	def get(self, k):
-		"""验证第k的索引位置是否为1
-		"""
-		if k > self.max_size: return false
-		array_index = k // 31
-		bit_index = self.bit_index(k)
-		return self.array[array_index] & (1 << bit_index) != 0 
-
-
-def test_bitmap1():
-	bit_map = BitMap1(100)
-	bit_map.set(5)
-	print bit_map.bytes
-	print bit_map.get(5)
-	print bit_map.get(4)
-
-def test_bitmap2():
-	bit_map = BitMap2(128)
-	# 存储字符串
-	string1 = "http://www.baidu.com"
-	for c in string1:
-		bit_map.set(ord(c))
-	print bit_map.array
-
-	# 验证字符串
-	string2 = "https://www.baidu.com"
-	flag = True
-	for c in string2:
-		flag = flag & bit_map.get(ord(c))
-	if flag:
-		print True
-	else:
-		print False
-
-
-if __name__ == '__main__':
-	test_bitmap2()
+#!/usr/bin/env python		
+#coding:utf-8
+
+"""
+python实现BitMap数据结构
+"""
+
+class BitMap1():
+	"""使用列表实现的bitmap位图功能, 不节省空间，只为了直观展示理解用途"""
+	def __init__(self, nbits):
+		self.nbits = nbits
+		self.bytes = [0] * (nbits + 1)
+
+	def set(self, k):
+		if k > self.nbits:
+			return
+		self.bytes[k] = self.bytes[k] | 1
+
+	def get(self, k):
+		if k > self.nbits:return false;
+		res = self.bytes[k] & 1 != 0
+		return res
+
+class BitMap2():
+	"""将数据存储有符号整数的前31位上面(兼容其他语言的整数最大表示大小，python已经不限制了)"""
+	def __init__(self, m):
+		"""
+		:param m: max size
+		"""
+		self.max_size = m
+		self.array = [0] * int((m + 31 -1) / 31) #多个整数来表示，防止大小不够
+
+	def bit_index(self, k):
+		"""获取第k个位置位索引下标
+		"""
+		return k % 31
+
+	def set(self, k):
+		"""设置第k个索引位置为1
+		"""
+		if k > self.max_size: return
+		array_index = k // 31 # 获取数组索引，即第k的位置落在数组第几个元素上
+		bit_index = self.bit_index(k) # 获取位索引
+		self.array[array_index] = self.array[array_index] | (1 << bit_index)
+
+	def get(self, k):
+		"""验证第k的索引位置是否为1
+		"""
+		if k > self.max_size: return false
+		array_index = k // 31
+		bit_index = self.bit_index(k)
+		return self.array[array_index] & (1 << bit_index) != 0 
+
+
+def test_bitmap1():
+	bit_map = BitMap1(100)
+	bit_map.set(5)
+	print bit_map.bytes
+	print bit_map.get(5)
+	print bit_map.get(4)
+
+def test_bitmap2():
+	bit_map = BitMap2(128)
+	# 存储字符串
+	string1 = "http://www.baidu.com"
+	for c in string1:
+		bit_map.set(ord(c))
+	print bit_map.array
+
+	# 验证字符串
+	string2 = "https://www.baidu.com"
+	flag = True
+	for c in string2:
+		flag = flag & bit_map.get(ord(c))
+	if flag:
+		print True
+	else:
+		print False
+
+
+if __name__ == '__main__':
+	test_bitmap2()

bitmap/bloomfilter.py

@@ -1,2 +1,2 @@
-#!/usr/bin/env python		
-#coding:utf-8
+#!/usr/bin/env python		
+#coding:utf-8

heap/getLeastNumbers.py

@@ -1,33 +1,33 @@
-#!/usr/bin/env python		
-#coding:utf-8
-
-"""
-面试题40. 最小的k个数
-
-https://leetcode-cn.com/problems/zui-xiao-de-kge-shu-lcof/
-"""
-
-from heapq import heappush, heappop
-class Solution(object):
-    def getLeastNumbers(self, arr, k):
-        """
-        :type arr: List[int]
-        :type k: int
-        :rtype: List[int]
-
-        解法1: 直接利用py的heapq构建最小堆即可 时间复杂度: n * logk
-        """
-        if not arr:
-            return -1
-        min_heap = [] # 最小堆
-        rets = []
-        for i in arr:
-            heappush(min_heap, i)
-        for j in range(k):
-            rets.append(heappop(min_heap))
-        return rets
-
-if __name__ == '__main__':
-	s = Solution()
-	nums = [4,5,1,6,2,7,3,8]
+#!/usr/bin/env python		
+#coding:utf-8
+
+"""
+面试题40. 最小的k个数
+
+https://leetcode-cn.com/problems/zui-xiao-de-kge-shu-lcof/
+"""
+
+from heapq import heappush, heappop
+class Solution(object):
+    def getLeastNumbers(self, arr, k):
+        """
+        :type arr: List[int]
+        :type k: int
+        :rtype: List[int]
+
+        解法1: 直接利用py的heapq构建最小堆即可 时间复杂度: n * logk
+        """
+        if not arr:
+            return -1
+        min_heap = [] # 最小堆
+        rets = []
+        for i in arr:
+            heappush(min_heap, i)
+        for j in range(k):
+            rets.append(heappop(min_heap))
+        return rets
+
+if __name__ == '__main__':
+	s = Solution()
+	nums = [4,5,1,6,2,7,3,8]
 	print(s.getLeastNumbers(nums, 4))

queue/__init__.py

@@ -1,67 +1,67 @@
-#!/usr/bin/env python		
-#coding:utf-8
-
-
-"""
-用数组实现的队列
-"""
-class ArrayQueue(object):
-	def __init__(self, capacity):
-		self._items = []
-		self._capacity = capacity
-		self._head = 0
-		self._tail = 0
-
-	def enqueue(self, item):
-		"""入队操作
-		"""
-		# tail == capacity表示队列末尾没有空间了
-		if self._tail == self._capacity:
-			# tail == capacity && head==0表示整个队列都占满了
-			if self._head == 0:
-				return False
-			else:
-				# 执行数据搬移操作
-				for i in range(0, self._tail - self._head):
-					self._items[i] = self._items[i + self._head]
-				# 更新head和tail
-				self._tail = self._tail - self._head
-				self._head = 0
-		self._items.insert(self._tail, item)
-		self._tail += 1
-		return True
-
-	def dequeue(self):
-		# 出队操作dequeue()的队空的条件是队头下标等于队尾下标。
-		if self._head != self._tail:
-			item = self._items[self._head]
-			self._head += 1
-			return item
-		else:
-			return None
-
-	def __repr__(self):
-		return " ".join("%s" % item for item in self._items[self._head : self._tail])
-
-
-class ListQueue(object):
-	"""使用List数据结构实现的简单版队列"""
-	def __init__(self, n):
-		self._items = []
-
-	def enqueue(self, item):
-		"""入队"""
-		self._items.insert(0, item)
-
-	def dequeue(self):
-		"""出队"""
-		# 队头在右边，因此pop()即为弹出队头
-		return self._items.pop()
-	def __repr__(self):
-		return " ".join("%s" % i for i in self._items)
-
-def test_ArrayQueue():
-	queue = ArrayQueue(10)
-	queue.enqueue(1)
-	queue.enqueue(2)
-	print queue
+#!/usr/bin/env python		
+#coding:utf-8
+
+
+"""
+用数组实现的队列
+"""
+class ArrayQueue(object):
+	def __init__(self, capacity):
+		self._items = []
+		self._capacity = capacity
+		self._head = 0
+		self._tail = 0
+
+	def enqueue(self, item):
+		"""入队操作
+		"""
+		# tail == capacity表示队列末尾没有空间了
+		if self._tail == self._capacity:
+			# tail == capacity && head==0表示整个队列都占满了
+			if self._head == 0:
+				return False
+			else:
+				# 执行数据搬移操作
+				for i in range(0, self._tail - self._head):
+					self._items[i] = self._items[i + self._head]
+				# 更新head和tail
+				self._tail = self._tail - self._head
+				self._head = 0
+		self._items.insert(self._tail, item)
+		self._tail += 1
+		return True
+
+	def dequeue(self):
+		# 出队操作dequeue()的队空的条件是队头下标等于队尾下标。
+		if self._head != self._tail:
+			item = self._items[self._head]
+			self._head += 1
+			return item
+		else:
+			return None
+
+	def __repr__(self):
+		return " ".join("%s" % item for item in self._items[self._head : self._tail])
+
+
+class ListQueue(object):
+	"""使用List数据结构实现的简单版队列"""
+	def __init__(self, n):
+		self._items = []
+
+	def enqueue(self, item):
+		"""入队"""
+		self._items.insert(0, item)
+
+	def dequeue(self):
+		"""出队"""
+		# 队头在右边，因此pop()即为弹出队头
+		return self._items.pop()
+	def __repr__(self):
+		return " ".join("%s" % i for i in self._items)
+
+def test_ArrayQueue():
+	queue = ArrayQueue(10)
+	queue.enqueue(1)
+	queue.enqueue(2)
+	print queue