全面的 python 数据结构备忘单
目录
列表元组套装词典弦乐数组堆栈排队链接列表树堆图表高级数据结构
列表
列表是有序的、可变的序列。
创建
empty_list = []list_with_items = [1, 2, 3]list_from_iterable = list("abc")list_comprehension = [x for x in range(10) if x % 2 == 0]
常用操作
# accessing elementsfirst_item = my_list[0]last_item = my_list[-1]# slicingsubset = my_list[1:4] # elements 1 to 3reversed_list = my_list[::-1]# adding elementsmy_list.append(4) # add to endmy_list.insert(0, 0) # insert at specific indexmy_list.extend([5, 6, 7]) # add multiple elements# removing elementsremoved_item = my_list.pop() # remove and return last itemmy_list.remove(3) # remove first occurrence of 3del my_list[0] # remove item at index 0# other operationslength = len(my_list)index = my_list.index(4) # find index of first occurrence of 4count = my_list.count(2) # count occurrences of 2my_list.sort() # sort in placesorted_list = sorted(my_list) # return new sorted listmy_list.reverse() # reverse in place
先进技术
# list as stackstack = [1, 2, 3]stack.append(4) # pushtop_item = stack.pop() # pop# list as queue (not efficient, use collections.deque instead)queue = [1, 2, 3]queue.append(4) # enqueuefirst_item = queue.pop(0) # dequeue# nested listsmatrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]flattened = [item for sublist in matrix for item in sublist]# list multiplicationrepeated_list = [0] * 5 # [0, 0, 0, 0, 0]# list unpackinga, *b, c = [1, 2, 3, 4, 5] # a=1, b=[2, 3, 4], c=5
元组
元组是有序的、不可变的序列。
创建
empty_tuple = ()single_item_tuple = (1,) # note the commatuple_with_items = (1, 2, 3)tuple_from_iterable = tuple("abc")
常用操作
# accessing elements (similar to lists)first_item = my_tuple[0]last_item = my_tuple[-1]# slicing (similar to lists)subset = my_tuple[1:4]# other operationslength = len(my_tuple)index = my_tuple.index(2)count = my_tuple.count(3)# tuple unpackinga, b, c = (1, 2, 3)
先进技术
# named tuplesfrom collections import namedtuplepoint = namedtuple('point', ['x', 'y'])p = point(11, y=22)print(p.x, p.y)# tuple as dictionary keys (immutable, so allowed)dict_with_tuple_keys = {(1, 2): 'value'}
套
集合是独特元素的无序集合。
创建
empty_set = set()set_with_items = {1, 2, 3}set_from_iterable = set([1, 2, 2, 3, 3]) # {1, 2, 3}set_comprehension = {x for x in range(10) if x % 2 == 0}
常用操作
# adding elementsmy_set.add(4)my_set.update([5, 6, 7])# removing elementsmy_set.remove(3) # raises keyerror if not foundmy_set.discard(3) # no error if not foundpopped_item = my_set.pop() # remove and return an arbitrary element# other operationslength = len(my_set)is_member = 2 in my_set# set operationsunion = set1 | set2intersection = set1 & set2difference = set1 - set2symmetric_difference = set1 ^ set2
先进技术
# frozen sets (immutable)frozen = frozenset([1, 2, 3])# set comparisonsis_subset = set1 = set2is_disjoint = set1.isdisjoint(set2)# set of sets (requires frozenset)set_of_sets = {frozenset([1, 2]), frozenset([3, 4])}
词典
字典是键值对的可变映射。
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创建
empty_dict = {}dict_with_items = {'a': 1, 'b': 2, 'c': 3}dict_from_tuples = dict([('a', 1), ('b', 2), ('c', 3)])dict_comprehension = {x: x**2 for x in range(5)}
常用操作
# accessing elementsvalue = my_dict['key']value = my_dict.get('key', default_value)# adding/updating elementsmy_dict['new_key'] = valuemy_dict.update({'key1': value1, 'key2': value2})# removing elementsdel my_dict['key']popped_value = my_dict.pop('key', default_value)last_item = my_dict.popitem() # remove and return an arbitrary key-value pair# other operationskeys = my_dict.keys()values = my_dict.values()items = my_dict.items()length = len(my_dict)is_key_present = 'key' in my_dict
先进技术
# dictionary unpackingmerged_dict = {**dict1, **dict2}# default dictionariesfrom collections import defaultdictdd = defaultdict(list)dd['key'].append(1) # no keyerror# ordered dictionaries (python 3.7+ dictionaries are ordered by default)from collections import ordereddictod = ordereddict([('a', 1), ('b', 2), ('c', 3)])# counterfrom collections import counterc = counter(['a', 'b', 'c', 'a', 'b', 'b'])print(c.most_common(2)) # [('b', 3), ('a', 2)]
弦乐
字符串是不可变的 unicode 字符序列。
创建
single_quotes = 'hello'double_quotes = "world"triple_quotes = '''multilinestring'''raw_string = r'c:usersname'f_string = f"the answer is {40 + 2}"
常用操作
# accessing charactersfirst_char = my_string[0]last_char = my_string[-1]# slicing (similar to lists)substring = my_string[1:4]# string methodsupper_case = my_string.upper()lower_case = my_string.lower()stripped = my_string.strip()split_list = my_string.split(',')joined = ', '.join(['a', 'b', 'c'])# other operationslength = len(my_string)is_substring = 'sub' in my_stringchar_count = my_string.count('a')
先进技术
# string formattingformatted = "{} {}".format("hello", "world")formatted = "%s %s" % ("hello", "world")# regular expressionsimport repattern = r'd+'matches = re.findall(pattern, my_string)# unicode handlingunicode_string = u'u0061u0062u0063'
数组
数组是紧凑的数值序列（来自数组模块）。
创建和使用
from array import arrayint_array = array('i', [1, 2, 3, 4, 5])float_array = array('f', (1.0, 1.5, 2.0, 2.5))# operations (similar to lists)int_array.append(6)int_array.extend([7, 8, 9])popped_value = int_array.pop()
堆栈
堆栈可以使用lists或collections.deque来实现。
实施和使用
# using liststack = []stack.append(1) # pushstack.append(2)top_item = stack.pop() # pop# using deque (more efficient)from collections import dequestack = deque()stack.append(1) # pushstack.append(2)top_item = stack.pop() # pop
队列
队列可以使用collections.deque或queue.queue来实现。
实施和使用
# using dequefrom collections import dequequeue = deque()queue.append(1) # enqueuequeue.append(2)first_item = queue.popleft() # dequeue# using queue (thread-safe)from queue import queueq = queue()q.put(1) # enqueueq.put(2)first_item = q.get() # dequeue
链表
python没有内置链表，但可以实现。
实施简单
class node: def __init__(self, data): self.data = data self.next = noneclass linkedlist: def __init__(self): self.head = none def append(self, data): if not self.head: self.head = node(data) return current = self.head while current.next: current = current.next current.next = node(data)
树木
树可以使用自定义类来实现。
简单的二叉树实现
class treenode: def __init__(self, value): self.value = value self.left = none self.right = noneclass binarytree: def __init__(self, root): self.root = treenode(root) def insert(self, value): self._insert_recursive(self.root, value) def _insert_recursive(self, node, value): if value < node.value: if node.left is none: node.left = treenode(value) else: self._insert_recursive(node.left, value) else: if node.right is none: node.right = treenode(value) else: self._insert_recursive(node.right, value)
堆
堆可以使用 heapq 模块来实现。
用法
import heapq# create a heapheap = []heapq.heappush(heap, 3)heapq.heappush(heap, 1)heapq.heappush(heap, 4)# pop smallest itemsmallest = heapq.heappop(heap)# create a heap from a listmy_list = [3, 1, 4, 1, 5, 9]heapq.heapify(my_list)
图表
图可以使用字典来实现。
实施简单
class graph: def __init__(self): self.graph = {} def add_edge(self, u, v): if u not in self.graph: self.graph[u] = [] self.graph[u].append(v) def bfs(self, start): visited = set() queue = [start] visited.add(start) while queue: vertex = queue.pop(0) print(vertex, end=' ') for neighbor in self.graph.get(vertex, []): if neighbor not in visited: visited.add(neighbor) queue.append(neighbor)
高级数据结构
特里树
class trienode: def __init__(self): self.children = {} self.is_end = falseclass trie: def __init__(self): self.root = trienode() def insert(self, word): node = self.root for char in word: if char not in node.children: node.children[char] = trienode() node = node.children[char] node.is_end = true def search(self, word): node = self.root for char in word: if char not in node.children: return false node = node.children[char] return node.is_end
不相交集（并查集）
class DisjointSet: def __init__(self, vertices): self.parent = {v: v for v in vertices} self.rank = {v: 0 for v in vertices} def find(self, item): if self.parent[item] != item: self.parent[item] = self.find(self.parent[item]) return self.parent[item] def union(self, x, y): xroot = self.find(x) yroot = self.find(y) if self.rank[xroot] self.rank[yroot]: self.parent[yroot] = xroot else: self.parent[yroot] = xroot self.rank[xroot] += 1
这份全面的备忘单涵盖了广泛的 python 数据结构，从基本的内置类型到更高级的自定义实现。每个部分都包含创建方法、常用操作以及适用的高级技巧。
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