基础学习——自己实现一个栈 总结自《学习JavaScript数据结构与算法第3版》 队列和栈其实很像,基础理解就是一个先进先出(队列),一个后进先出(栈),所以大致思路其实也是很像的。所以注释没有栈的详细 export default class Queue {//定义一个Queue类 constructor() { t
描述 有一个容积为n的背包,有m种物品,要求取出若干种物品,正好将背包填满,问一共有多少种取法。每种物品可以取任意多个。 输入 有几组测试数据。每组测试数据两行。第一行是两个整数,n和m, 0< n,m <= 100。 第二行是m个正整数,表示m种物品的体积。物品体积不超过1000。若干组输入数据
效果显示 HTML页面显示 HTML代码 <%@ Page Language="C#" AutoEventWireup="true" CodeFile="Default.aspx.cs" Inherits="_Default" %> <!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http
数据样本 数据获取:关注并私信“关联规则案例” # -*- codeing = utf-8 -*- # @Time : 2021/11/26 22:41 # @Author : Tancy # @File : 病例分析-- Apriori算法.py # @Software : PyCharm # 1.数据读取 import pandas as pd df = pd.read_excel('D:\A_学习\数据仓库与数据挖
使用flex居中对齐: .warp{ display: flex; justify-content: center; align-items: center; } 复制代码 容器属性: flex-direction: display: flex; 1.主轴水平方向,起点在左端,默认值 flex-direction: row; 2.主轴水平方向,起点在右端 flex-direction: row-reverse; 3.主轴垂直方
<el-upload class="upload-demo ml" ref="uploadMutiple" action="http://api110.herbplantist.com/sucai/public/index.php/post/post/uploadFile"
我们可以扩展jquery,自定义方法,在使用的时候可以直接调用 需求: 1. 给 $ 添加4个工具方法: * min(a, b) : 返回较小的值 * max(c, d) : 返回较大的值 * leftTrim() : 去掉字符串左边的空格 * rightTrim() : 去掉字符串右边的空格 2. 给jQuery对象 添加3个
def getText(): txt=open("D:\\test.txt","r").read() txt=txt.lower() punctuation = r"""!"#$%&'()*+,-./:;<=>?@[\]^_`{|}~“”?,!【】()、。:;’‘……¥·""" for ch in punctuation:
1 # 问题描述: 给定一个数组a[],其中除了2个数,其他均出现2次,请找到不重复的2个数并返回. 2 # 问题示例: [1,2,5,2,3,3,4,4,9,9,10,1] 返回[5,10] 3 class Solution: 4 def func(self, lit): 5 for i in range(len(lit)): 6 for j in rang
<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd"> <html> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"> &l
目录什么是计算属性内容分发slot例子第一步: 定义一个待办事项的组件第二步: 我们需要让,待办事项的标题和值实现动态绑定,怎么做呢? 我们可以留出一个插槽!实测自定义事件例子实测逻辑理解 什么是计算属性 计算属性的重点突出在属性两个字上(属性是名词),首先它是个 属性其次这个属
图片的复制无非有两种方法,一种是图片直接上传到服务器,另外一种转换成二进制流的base64码 目前限chrome浏览器使用 首先以um-editor的二进制流保存为例: 打开umeditor.js,找到UM.plugins['autoupload'],然后找到autoUploadHandler方法,注释掉其中的代码。 加入下面的代码: //判断剪贴
import jieba with open ("D:\红楼梦.txt",encoding="ANSI") as file: f = file.read() del_list ={"什么","一个","我们","那里","如今","你们","说道","起来","姑娘","
import jiebatxt=open('D:\桌面\西游记.txt',"r",encoding='utf-8').read()excludes={"什么","一个","那里","怎么","我们","不知","两个","甚么",\"不是","只见&qu
import jiebaexcludes = {"什么","一个","我们","那里","你们","如今","说道","知道","起来","姑娘","这里","出来","他们","众人","自己",
import jieba jieba.setLogLevel(jieba.logging.INFO) f = open('红楼梦.txt', 'r', encoding='utf-8') txt = f.read() f.close() words = jieba.lcut(txt) counts = {} for word in words: if len(word) == 1: continue elif wo
import jiebajieba.setLogLevel(jieba.logging.INFO)txt = open('西游记.txt', 'r', encoding='gb18030').read()words = jieba.lcut(txt)counts = {}for word in words: if len(word) == 1: continue elif word == "大圣" o
import jieba txt = open("聊斋志异白话简写版.txt", "r", encoding='utf-8').read()words = jieba.lcut(txt) # 使用精确模式对文本进行分词counts = {} # 通过键值对的形式存储词语及其出现的次数 for word in words: if len(word) == 1: continue elif
import jieba txt = open("《西游记》.txt", "r", encoding='utf-8').read() words = jieba.lcut(txt) # 使用精确模式对文本进行分词 counts = {} # 通过键值对的形式存储词语及其出现的次数 for word in words: if len(word) == 1: continue
利用jieba库统计西游记重出现最多次的20个词 import jieba f = open('4447.txt', mode='r',encoding='GB18030') txt = f.read() txt = jieba.lcut(txt) buyao = ['。',',',':','“','”','?',
mport jieba def takeSecond(elem): return elem[1] def main(): path = "xiyouji.txt" file = open(path,"r",encoding="utf-8") text=file.read() file.close() words = jieba.lcut(text) counts = {}
import jieba txt = open("聊斋志异白话简写版.txt", "r", encoding='utf-8').read()words = jieba.lcut(txt) # 使用精确模式对文本进行分词counts = {} # 通过键值对的形式存储词语及其出现的次数 for word in words: if len(word) == 1: continue elif
import jieba def takeSecond(elem): return elem[1] def main(): path = "西游记.txt" file = open(path,"r",encoding="utf-8") text=file.read() file.close() words = jieba.lcut(text) counts = {} fo
import jieba txt = open("西游记.txt", "r", encoding='utf-8').read() words = jieba.lcut(txt) counts = {} for word in words: if len(word) == 1: continue elif word == "大圣" or word=="老孙" or wo
代码如下: import jieba txt = open("《西游记》.txt", "r", encoding='utf-8').read()words = jieba.lcut(txt) # 使用精确模式对文本进行分词counts = {} # 通过键值对的形式存储词语及其出现的次数 for word in words: if len(word) == 1: continue elif word =