python 头条 sign 参数 此篇针对实时列表 请使用73版本的谷歌浏览器

2023-11-15

1.首先谷歌浏览器打开今日头条F12调试找到sources,以旅游模块为例以此类推都一样,网站如https://www.toutiao.com/ch/news_travel/
在这里插入图片描述2.ctrl+shift+f全局搜索 window.byted_acrawler.sign回车,点击下面的js。
在这里插入图片描述
3.然后再js代码框中按ctrl+f 搜索window.byted_acrawler.sign找到它的位置打上断点。
在这里插入图片描述
4.按F5刷新,观察i参数及上面的值。注意观察这个url的变化。
在这里插入图片描述
5.点击如图向下运行
在这里插入图片描述
在这里插入图片描述
6.当运行url和参数结果如下图时正是我们要找的逻辑。为啥这样说,下面会做解释。
在这里插入图片描述
在这里插入图片描述
7.观察这条url是不是和上面断点运行的参数很像呢。所有及那次参数是我们想要的。
在这里插入图片描述
8.我们认真观察一下参数结构,然后大胆改造。这里的正则意思是如果存在https://www.toutiao.com开头之类的就直接使用如果不存在就用本机ip代替或者说是本机访问的url当做e。
在这里插入图片描述
9.所以我将其改造如下:
在这里插入图片描述
10.至于这个传入的t是什么?让我们来一起康康,其实上面第6步不难发现传入的值。所有这里就不写过程了直接上代码~~嘻嘻!!

//Function(function(t){return'w={S(S,y){if(!K[S]){K[S]={};for(T=0;T<S;T)K[S][S.charAt(T)]=T}K[S][y]}y=String.fromCharCode,K={},T={x:(y){null==y?"":""==y?null:T.y(y,32,(K){S("ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/=",y.charAt(K})},y:(S,K,T){z,a,I,J,i,n,r,L=[],o=4,p=4,m=3,q="",k=[],h={val:T(0),position:K,index:1};for(z=0;z<3;z+=1)L[z]=z;for(I=0,i=Math.pow(2,2),n=1;n!=i;)J=h.val&h.position,h.position>>=1,0==h.position&&(h.position=K,h.val=T(h.index,I|=(J>0?1:0)*n,n<<=1;switch(I){case 0:for(I=0,i=Math.pow(2,8),n=1;n!=i;)J=h.val&h.position,h.position>>=1,0==h.position&&(h.position=K,h.val=T(h.index,I|=(J>0?1:0)*n,n<<=1;r=y(I)1:for(I=0,i=Math.pow(2,16),n=1;n!=i;)J=h.val&h.position,h.position>>=1,0==h.position&&(h.position=K,h.val=T(h.index,I|=(J>0?1:0)*n,n<<=1;r=y(I)2:""}for(L[3]=r,a=r,k.push(r);;){if(h.index>S)"";for(I=0,i=Math.pow(2,m),n=1;n!=i;)J=h.val&h.position,h.position>>=1,0==h.position&&(h.position=K,h.val=T(h.index,I|=(J>0?1:0)*n,n<<=1;switch(r=I){case 0:for(I=0,i=Math.pow(2,8),n=1;n!=i;)J=h.val&h.position,h.position>>=1,0==h.position&&(h.position=K,h.val=T(h.index,I|=(J>0?1:0)*n,n<<=1;L[p]=y(I),r=p-1,o--1:for(I=0,i=Math.pow(2,16),n=1;n!=i;)J=h.val&h.position,h.position>>=1,0==h.position&&(h.position=K,h.val=T(h.index,I|=(J>0?1:0)*n,n<<=1;L[p]=y(I),r=p-1,o--2:k.join("")}if(0==o&&(o=Math.pow(2,m),m),L[r])q=L[r]if(r!==p)null;q=a+a.charAt(0)}k.push(q),L[p]=a+q.charAt(0),a=q,0==--o&&(o=Math.pow(2,m),m)}}};T};""==typeof define&&define.amd?define({w}):"undefined"!=typeof module&&null!=module?module.exports=w:"undefined"!=typeof angular&&null!=angular&&angular.module("w",[]).factory("w",{w}),eval(w.x("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";'.replace(/[-]/g,function(m){return t[m.charCodeAt(0)&15]})}("var function ().length++return ));break;case ;else{".split("")))();
function vmx(t) {
//	var t={"max_behot_time":"1583390547","max_behot_time_tmp":"1583390547","tadrequire": true,"as":"A1750EE67039F53","cp":"5E60393F95933E1","_signatrue":"eSswjQAAJ01wZ0qYHJBG4XkrMJ"}
       window.byted_acrawler.init({
                aid: 24,
                dfp: true
            });
        var e="https://www.toutiao.com/toutiao/api/pc/feed/";
        var n = "";
        /^http/.test(e) || (/\/toutiao\//.test(e) || (e = "/toutiao" + e),
        e = location.protocol + "//" + location.host + e);
        for (var r in t){
            n += "&" + r + "=" + encodeURIComponent(t[r]);
	console.log(n);
	}
        e += e.indexOf("?") > -1 ? e.indexOf("&") > -1 ? n : n.slice(1) : "?" + n.slice(1);
console.log(e);
        var o = {
            url: e
        }
          , i = window.byted_acrawler.sign ? window.byted_acrawler.sign(o) : "";
console.log(o);
        return i
    }


function get_timedate() {
            return parseInt((new Date).getTime()/1000)
 }

function s() {
    var t = Math.floor((new Date).getTime() / 1e3)
        , e = t.toString(16).toUpperCase()
        , i = (0,o)(t).toString().toUpperCase();
    if (8 != e.length)
        return {
            as: "479BB4B7254C150",
            cp: "7E0AC8874BB0985"
        };
    for (var n = i.slice(0, 5), s = i.slice(-5), a = "", r = 0; r < 5; r++)
        a += n[r] + e[r];
    for (var l = "", u = 0; u < 5; u++)
        l += e[u + 3] + s[u];
    return {
        as: "A1" + a + e.slice(-3),
        cp: e.slice(0, 3) + l + "E1",

    }
}

function o(t, e, i) {
    return e ? i ? b(e, t) : C(e, t) : i ? w(t) : y(t)
}

function y(t) {
    return v(w(t))
}

function v(t) {
    var e, i, n = "0123456789abcdef", s = "";
    for (i = 0; i < t.length; i += 1)
        e = t.charCodeAt(i),
            s += n.charAt(e >>> 4 & 15) + n.charAt(15 & e);
    return s
}

function w(t) {
    return _(g(t))
}

function g(t) {
    return unescape(encodeURIComponent(t))
}

function _(t) {
    function a(t, e) {
        var i = (65535 & t) + (65535 & e)
            , n = (t >> 16) + (e >> 16) + (i >> 16);
        return n << 16 | 65535 & i
    }
    function o(t, e) {
        return t << e | t >>> 32 - e
    }
    function r(t, e, i, n, s, r) {
        return a(o(a(a(e, t), a(n, r)), s), i)
    }
    function l(t, e, i, n, s, a, o) {
        return r(e & i | ~e & n, t, e, s, a, o)
    }
    function u(t, e, i, n, s, a, o) {
        return r(e & n | i & ~n, t, e, s, a, o)
    }
    function c(t, e, i, n, s, a, o) {
        return r(e ^ i ^ n, t, e, s, a, o)
    }
    function d(t, e, i, n, s, a, o) {
        return r(i ^ (e | ~n), t, e, s, a, o)
    }
    function f(t, e) {

        function l(t, e, i, n, s, a, o) {
            function r(t, e, i, n, s, r) {
                function a(t, e) {
                    var i = (65535 & t) + (65535 & e)
                        , n = (t >> 16) + (e >> 16) + (i >> 16);
                    return n << 16 | 65535 & i
                }
                function o(t, e) {
                    return t << e | t >>> 32 - e
                }
                return a(o(a(a(e, t), a(n, r)), s), i)
            }
            return r(e & i | ~e & n, t, e, s, a, o)
        }
        function u(t, e, i, n, s, a, o) {
            function r(t, e, i, n, s, r) {
                function a(t, e) {
                    var i = (65535 & t) + (65535 & e)
                        , n = (t >> 16) + (e >> 16) + (i >> 16);
                    return n << 16 | 65535 & i
                }
                function o(t, e) {
                    return t << e | t >>> 32 - e
                }
                return a(o(a(a(e, t), a(n, r)), s), i)
            }
            return r(e & n | i & ~n, t, e, s, a, o)
        }
        function c(t, e, i, n, s, a, o) {
            function r(t, e, i, n, s, r) {
                function a(t, e) {
                    var i = (65535 & t) + (65535 & e)
                        , n = (t >> 16) + (e >> 16) + (i >> 16);
                    return n << 16 | 65535 & i
                }
                function o(t, e) {
                    return t << e | t >>> 32 - e
                }
                return a(o(a(a(e, t), a(n, r)), s), i)
            }
            return r(e ^ i ^ n, t, e, s, a, o)
        }


        t[e >> 5] |= 128 << e % 32,
            t[(e + 64 >>> 9 << 4) + 14] = e;
        var i, n, s, o, r, f = 1732584193, h = -271733879, p = -1732584194, _ = 271733878;
        for (i = 0; i < t.length; i += 16)
            n = f,
                s = h,
                o = p,
                r = _,
                f = l(f, h, p, _, t[i], 7, -680876936),
                _ = l(_, f, h, p, t[i + 1], 12, -389564586),
                p = l(p, _, f, h, t[i + 2], 17, 606105819),
                h = l(h, p, _, f, t[i + 3], 22, -1044525330),
                f = l(f, h, p, _, t[i + 4], 7, -176418897),
                _ = l(_, f, h, p, t[i + 5], 12, 1200080426),
                p = l(p, _, f, h, t[i + 6], 17, -1473231341),
                h = l(h, p, _, f, t[i + 7], 22, -45705983),
                f = l(f, h, p, _, t[i + 8], 7, 1770035416),
                _ = l(_, f, h, p, t[i + 9], 12, -1958414417),
                p = l(p, _, f, h, t[i + 10], 17, -42063),
                h = l(h, p, _, f, t[i + 11], 22, -1990404162),
                f = l(f, h, p, _, t[i + 12], 7, 1804603682),
                _ = l(_, f, h, p, t[i + 13], 12, -40341101),
                p = l(p, _, f, h, t[i + 14], 17, -1502002290),
                h = l(h, p, _, f, t[i + 15], 22, 1236535329),
                f = u(f, h, p, _, t[i + 1], 5, -165796510),
                _ = u(_, f, h, p, t[i + 6], 9, -1069501632),
                p = u(p, _, f, h, t[i + 11], 14, 643717713),
                h = u(h, p, _, f, t[i], 20, -373897302),
                f = u(f, h, p, _, t[i + 5], 5, -701558691),
                _ = u(_, f, h, p, t[i + 10], 9, 38016083),
                p = u(p, _, f, h, t[i + 15], 14, -660478335),
                h = u(h, p, _, f, t[i + 4], 20, -405537848),
                f = u(f, h, p, _, t[i + 9], 5, 568446438),
                _ = u(_, f, h, p, t[i + 14], 9, -1019803690),
                p = u(p, _, f, h, t[i + 3], 14, -187363961),
                h = u(h, p, _, f, t[i + 8], 20, 1163531501),
                f = u(f, h, p, _, t[i + 13], 5, -1444681467),
                _ = u(_, f, h, p, t[i + 2], 9, -51403784),
                p = u(p, _, f, h, t[i + 7], 14, 1735328473),
                h = u(h, p, _, f, t[i + 12], 20, -1926607734),
                f = c(f, h, p, _, t[i + 5], 4, -378558),
                _ = c(_, f, h, p, t[i + 8], 11, -2022574463),
                p = c(p, _, f, h, t[i + 11], 16, 1839030562),
                h = c(h, p, _, f, t[i + 14], 23, -35309556),
                f = c(f, h, p, _, t[i + 1], 4, -1530992060),
                _ = c(_, f, h, p, t[i + 4], 11, 1272893353),
                p = c(p, _, f, h, t[i + 7], 16, -155497632),
                h = c(h, p, _, f, t[i + 10], 23, -1094730640),
                f = c(f, h, p, _, t[i + 13], 4, 681279174),
                _ = c(_, f, h, p, t[i], 11, -358537222),
                p = c(p, _, f, h, t[i + 3], 16, -722521979),
                h = c(h, p, _, f, t[i + 6], 23, 76029189),
                f = c(f, h, p, _, t[i + 9], 4, -640364487),
                _ = c(_, f, h, p, t[i + 12], 11, -421815835),
                p = c(p, _, f, h, t[i + 15], 16, 530742520),
                h = c(h, p, _, f, t[i + 2], 23, -995338651),
                f = d(f, h, p, _, t[i], 6, -198630844),
                _ = d(_, f, h, p, t[i + 7], 10, 1126891415),
                p = d(p, _, f, h, t[i + 14], 15, -1416354905),
                h = d(h, p, _, f, t[i + 5], 21, -57434055),
                f = d(f, h, p, _, t[i + 12], 6, 1700485571),
                _ = d(_, f, h, p, t[i + 3], 10, -1894986606),
                p = d(p, _, f, h, t[i + 10], 15, -1051523),
                h = d(h, p, _, f, t[i + 1], 21, -2054922799),
                f = d(f, h, p, _, t[i + 8], 6, 1873313359),
                _ = d(_, f, h, p, t[i + 15], 10, -30611744),
                p = d(p, _, f, h, t[i + 6], 15, -1560198380),
                h = d(h, p, _, f, t[i + 13], 21, 1309151649),
                f = d(f, h, p, _, t[i + 4], 6, -145523070),
                _ = d(_, f, h, p, t[i + 11], 10, -1120210379),
                p = d(p, _, f, h, t[i + 2], 15, 718787259),
                h = d(h, p, _, f, t[i + 9], 21, -343485551),
                f = a(f, n),
                h = a(h, s),
                p = a(p, o),
                _ = a(_, r);
        return [f, h, p, _]
    }
    function p(t) {
        var e, i = [];
        for (i[(t.length >> 2) - 1] = void 0,
                 e = 0; e < i.length; e += 1)
            i[e] = 0;
        for (e = 0; e < 8 * t.length; e += 8)
            i[e >> 5] |= (255 & t.charCodeAt(e / 8)) << e % 32;
        return i
    }
    function h(t) {
        var e, i = "";
        for (e = 0; e < 32 * t.length; e += 8)
            i += String.fromCharCode(t[e >> 5] >>> e % 32 & 255);
        return i
    }
    return h(f(p(t), 8 * t.length))
}

//var max_behot_time=get_timedate()
var max_behot_time=0
//return {"as": s().as,"cp": s().cp,"max_behot_time":max_behot_time,"_signatrue":vmx({"max_behot_time":max_behot_time,"max_behot_time_tmp":max_behot_time,"tadrequire": true,"as":s().as,"cp":s().cp})}
document.getElementById("demo").innerHTML = "{\"as\":\"" +s().as+"\",\"cp\":\"" +s().cp+ "\",\"max_behot_time\":\""+max_behot_time+"\",\"_signature\":\""+vmx({"category": "news_travel","utm_source": "toutiao","widen": 1,"max_behot_time":max_behot_time,"max_behot_time_tmp":max_behot_time,"tadrequire": true,"as":s().as,"cp":s().cp})+"\"}";


在最后一句调用了vmt(t)方法 其余的参数都是原样照搬的
document.getElementById(“demo”).innerHTML=xxxxx

要怎么用呢?当然自己写一个index.html调用js就可以了随便写一个标签id=demo就ok啦。
如下:
在这里插入图片描述
在这里插入图片描述
一定要注意最前面要引用

还有vmt(t)方法中的初始化,当然我都写好了。

 <script>
            window.byted_acrawler.init({
                aid: 24,
                dfp: true
            });
        </script>
#https://sf1-ttcdn-tos.pstatp.com/obj/ttfe/rc/acrawler.js  #这个里面有监测的   如果用webdriver去调用时 会带上识别属性

#所有加密的方式带上监测 所以访问不了

option = webdriver.ChromeOptions()
# 隐藏webdriver
option.add_experimental_option('excludeSwitches', ['enable-automation'])

driver = webdriver.Chrome(chrome_options=option)
#每次请求前带上 
driver.delete_all_cookies()
driver.refresh()

这两个条件缺一不可,缺少一个都不算成功不信试试~~~
好了今天的小白分享就到这里啦!!!!!!加油
**

(声明此文章只作用于学习用途,如有人用于非法途径后果自负,不要带上我,谢谢!)

**

本文内容由网友自发贡献,版权归原作者所有,本站不承担相应法律责任。如您发现有涉嫌抄袭侵权的内容,请联系:hwhale#tublm.com(使用前将#替换为@)

python 头条 sign 参数 此篇针对实时列表 请使用73版本的谷歌浏览器 的相关文章

  • 从 SHAP 值中获取特征重要性

    我想要获得重要功能的数据框 通过下面的代码 我得到了 shap values 但我不确定这些值的含义是什么 在我的 df 中有 142 个特征和 67 个实验 但得到了一个带有 ca 的数组 2500 个值 explainer shap T
  • 将 transaction.commit_manually() 升级到 Django > 1.6

    我继承了为 Django 1 4 编写的应用程序的一些代码 我们需要更新代码库以使用 Django 1 7 并最终更新到 1 8 作为下一个长期支持版本 在一些地方它使用旧风格 transaction commit manually and
  • numpy python 中的“AttributeError:'matrix'对象没有属性'strftime'”错误

    我有一个维度为 72000 1 的矩阵 该矩阵涉及时间戳 我想使用 strftime 如下所示 strftime d m y 为了得到像这样的输出 11 03 02 我有这样一个矩阵 M np matrix timestamps 我使用了
  • 从 Python 下载/安装 Windows 更新

    我正在编写一个脚本来自动安装 Windows 更新 我可以将其部署在多台计算机上 这样我就不必担心手动更新它们 我想用 Python 编写这个 但找不到任何关于如何完成此操作的信息 我需要知道如何搜索更新 下载更新并从 python 脚本安
  • 字符串中的注释和注释中的字符串

    我正在尝试使用 Python 和 Regex 计算 C 代码中包含的注释中的字符数 但没有成功 我可以先删除字符串以删除字符串中的注释 但这也会删除注释中的字符串 结果会很糟糕 是否有机会通过使用正则表达式来询问不匹配注释中的字符串 反之亦
  • PyTorch 给出 cuda 运行时错误

    我对我的代码做了一些小小的修改 以便它不使用 DataParallel and DistributedDataParallel 代码如下 import argparse import os import shutil import time
  • Python中列表中两个连续元素的平均值

    我有一个偶数个浮点数的列表 2 34 3 45 4 56 1 23 2 34 7 89 我的任务是计算 1 和 2 个元素 3 和 4 5 和 6 等元素的平均值 在 Python 中执行此操作的快捷方法是什么 data 2 34 3 45
  • 将 numpy 代码点数组与字符串相互转换

    我有一个很长的 unicode 字符串 alphabet range 0x0FFF mystr join chr random choice alphabet for in range 100 mystr re sub W mystr 我想
  • 对使用 importlib.util 导入的对象进行酸洗

    我在使用Python的pickle时遇到了一个问题 我需要通过将文件路径提供给 importlib util 来加载一些 Python 模块 如下所示 import importlib util spec importlib util sp
  • 如何使用 Bokeh 动态隐藏字形和图例项

    我正在尝试在散景中实现复选框 其中每个复选框应显示 隐藏与其关联的行 我知道可以通过图例来实现这一点 但我希望这种效果同时在两个图中发生 此外 图例也应该更新 在下面的示例中 出现了复选框 但不执行任何操作 我显然不明白如何更新用作源的数据
  • 如何从 JSON 响应重定向?

    所以我尝试使用 Flask 和 Javascript 上传器 Dropzone 上传文件并在上传完成后重定向 文件上传正常 但在烧瓶中使用传统的重定向 return redirect http somesite com 不执行任何操作 页面
  • 如何在 Django 中使用基于类的视图创建注册视图?

    当我开始使用 Django 时 我几乎使用 FBV 基于函数的视图 来处理所有事情 包括注册新用户 但当我更深入地研究项目时 我意识到基于类的视图通常更适合大型项目 因为它们更干净且可维护 但这并不是说 FBV 不是 无论如何 我将整个项目
  • Python、subprocess、call()、check_call 和 returncode 来查找命令是否存在

    我已经弄清楚如何使用 call 让我的 python 脚本运行命令 import subprocess mycommandline lumberjack sleep all night work all day subprocess cal
  • 迭代列表的奇怪速度差异

    我创建了两个重复两个不同值的长列表 在第一个列表中 值交替出现 在第二个列表中 一个值出现在另一个值之前 a1 object object 10 6 a2 a1 2 a1 1 2 然后我迭代它们 不对它们执行任何操作 for in a1 p
  • 如何在 Azure 数据工厂 - Databricks 中使用 continuation_token 获取 ADF Pipeline 运行详细信息的下一页?

    我在用 adf client pipeline runs query by factory resourceGroupName 工厂名称 过滤器参数 的方法azure mgmt datafactory DataFactoryManageme
  • 在 Spyder 的变量资源管理器中查看局部变量

    我是 python 新手 正在使用 Spyder 的 IDE 我欣赏它的一项功能是它的变量资源管理器 然而 根据一些研究 我发现它只显示全局变量 我找到的解决方法是使用检查模块 import inspect local vars def m
  • Flask 应用程序的测试覆盖率不起作用

    您好 想在终端的 Flask 应用程序中测试 删除路由 我可以看到测试已经过去 它说 test user delete test app LayoutTestCase ok 但是当我打开封面时 它仍然是红色的 这意味着没有覆盖它 请有人向我
  • Python对象初始化性能

    我只是做了一些快速的性能测试 我注意到一般情况下初始化列表比显式初始化列表慢大约四到六倍 这些可能是错误的术语 我不确定这里的行话 例如 gt gt gt import timeit gt gt gt print timeit timeit
  • 通过 Web 界面执行 python 单元测试

    是否可以通过 Web 界面执行单元测试 如果可以 如何执行 EDIT 现在我想要结果 对于测试 我希望它们是自动化的 可能每次我对代码进行更改时 抱歉我忘了说得更清楚 EDIT 这个答案此时已经过时了 Use Jenkins https j
  • 如何使用Python保存“完整的网页”而不仅仅是基本的html

    我正在使用以下代码来使用 Python 保存网页 import urllib import sys from bs4 import BeautifulSoup url http www vodafone de privat tarife r

随机推荐

  • c#基础之WPF

    学习平台 微软开发者博客 DevBlogs Microsoft Developer Blogs 微软文档与学习 Microsoft Learn 培养开拓职业生涯新机遇的技能 微软开发者平台 Microsoft Developer WPF基础
  • Java-String类

    Java String类 1 概述 String 字符串 使用一对 引起来表示 String声明为final的 不可被继承 String实现了Serializable接口 表示字符串是支持序列化的 实现了Comparable接口 表示Str
  • Iptables封禁IP,记录地址

    前言 前段时间开了台国外的vps 以前机房的物理防火墙有十年网工大佬维护 我们对外访问的nginx上就没遇到过这种攻击 毕竟有问题的IP全被防火墙那层直接拦截了 而我这通过安全组把其中2个web端口放开了所有网段 而nginx再限制网段 导
  • 疫情日记(01)

    时间 2022年12月16日15 01 14 天气 阴天 地点 西安 12月8日全面放开以来 确诊这个词语也再是谈之色变了 似乎一旦 规定 疫情没有了 就真的没有了一样 两天前知道了ljc可能是确诊了 再后来就是办公室两个小兄弟 jc和qy
  • FAT文件系统初识

    最近在阅读 现代操作系统 的时候看到了fat32系统的讲解 在这里记录一下 我觉得fat32文件系统首先是基于链表分配的机制的 首先有一个基础知识 就是文件是由一系列的块组成的 想要访问完整的文件 就必须知道这个文件的所有的块的位置 链表分
  • Unity3d C#使用XCharts数据显示格式说明(如:数据类型、数据显示为百分比%等)

    前言 XCharts是开源且比较强大的插件 在Unity3d中搭建UI时常常使用的数据图表的制作插件 特别是当下的数字沙盘 数字孪生等项目中应用较广 笔者公司也一直在使用该插件 本文主要是在开发过程中的一个小需求引发的整理分享 在项目中需要
  • 前端自动化测试精讲

    单元测试 端对端测试 持续集成方案 在项目中落地前端自动化测试 作者介绍 祯民 字节跳动前端开发工程师 掘金小册 SSR实战 官网开发指南 作者 公众号 祯民讲前端 作者 曾负责 抖音前端技术团队官网 和 字节官网中文版 的开发 现维护抖音
  • git撤销加入暂存区(git add)的文件

    直接使用git reset加对应的文件或 来撤销 这个命令可以理解为git add的反向操作 可以撤销单个文件 也可批量 如 git reset xxx xxx xxx 或 git reset
  • C语言常见问题——++i与i++详解

    目录 一 i与i 1 引例 2 i i i 与 i i i 3 总结 二 函数中的 1 printf中的 2 作为函数的参数 3 总结 一 i与i 1 引例 对于如下程序 其输出结果是什么 include
  • 《算法导论》15章-动态规划 15.1 钢条切割(含有C++代码)

    一 引入 动态规划方法通常用来求解最优化问题 optimizationproblem 这类问题可以有很多可行解 每个解都有一个值 我们希望寻找具有最优值 最小值或最大值 的解 我们称这样的解为问 题的一个最优解 an optimal sol
  • 蓝桥杯2023年第十四届省赛真题python A组 (个人的做题记录,没有全对,可以通过部分测试点)

    试题 A 特殊日期 本题总分 5 分 问题描述 记一个日期为 yy 年 mm 月 dd 日 统计从 2000 年 1 月 1 日到 2000000 年 1 月 1 日 有多少个日期满足年份 yy 是月份 mm 的倍数 同时也是 dd 的倍数
  • 【ElasticSearch(五)进阶】两种_search检索方式,match_all检索,Query DSL基本使用...

    ElasticSearch 五 进阶 两种 search检索方式 match all检索 Query DSL基本使用 一 导入测试数据 ElasticSearch官方为我们准备了一部分测试数据供调试使用 我们可以Kinaba内进行数据导入处
  • SSH 整合Swagger2

    之前用的是springboot整合swagger2 新公司这边的系统是之前开发的 用的是SSH框架 这里记录一下 整合过程 以及遇到的坑 1 导入依赖
  • 华为OD机试 - 字符串分隔(C++ & Java & JS & Python)

    目录 描述 输入描述 输出描述 示例1 C 实现 Java实现 python实现 描
  • 如何提高oracle数据库的性能,关于提高Oracle数据库性能的四个误区

    为了提高性能 我们针对Oracle数据库本身提供了的方法或方案进行过不少的尝试 主要包括 共享服务器模式 MTS 集群技术 Clustering RAC 分区 并行处理 主要是并行查询 Oracle提供的这些特性确实是用来进行性能改善的 但
  • iOS证书申请打包上传App Store审核完整流程(7个步骤)

    上架基本需求资料 1 苹果开发者账号 2 开发好的APP 通过本篇教程 可以学习到ios证书申请和打包ipa上传到appstoreconnect apple com进行TestFlight测试然后提交审核的完整流程 上架App Store审
  • Golang JSON-序列化map,切片(slice),结构体(struct)

    package main import encoding json fmt func mapJson testMap make map string interface testMap name typ testMap age 123 te
  • python爬虫第9天 用爬虫测试网站 远程采集

    网站的前端通常并没 有自动化测试 尽管前端才是整个项目中真正与用户零距离接触的唯一一个部分 想象有一个由测试驱动的网络开发项目 每天进行测试以保证网络接口的每个环节的功能 都是正常的 每当有新的特性加入网站 或者一个元素的位置改变时 就执行
  • RecycleView 添加底部加载更多

    在阅读此文章前 请先看 http blog csdn net fangchao3652 article details 43148871 与开头的连接文章思想类似 只不过那个是图片文字按钮等多种布局的混排 而添加底部只是普通Item 与底部
  • python 头条 sign 参数 此篇针对实时列表 请使用73版本的谷歌浏览器

    1 首先谷歌浏览器打开今日头条F12调试找到sources 以旅游模块为例以此类推都一样 网站如https www toutiao com ch news travel 2 ctrl shift f全局搜索 window byted acr