爬虫逆向实战(二十)--某99网站登录

一、数据接口分析

主页地址:某99网站

1、抓包

通过抓包可以发现登录接口是AC_userlogin
在这里插入图片描述

2、判断是否有加密参数

  1. 请求参数是否加密?
    通过查看“载荷”可以发现txtPasswordaws是加密参数
    在这里插入图片描述
  2. 请求头是否加密?
  3. 响应是否加密?
  4. cookie是否加密?

二、加密位置定位

1、看启动器

查看启动器发现有一个NDUser_Login.js文件的匿名方法,点进去查看
在这里插入图片描述
点进去后发现,此处拼接了一个登录的地址,并且上方会赋值passwordaws,大概率是在此处进行的加密。下断点,再次登录。
在这里插入图片描述发现可以断住,所以此处就是加密位置

三、扣js代码

通过定位到的加密位置,扣出加密代码,缺啥补啥即可。
aws是可以写死的,每次生成的都是一样的。

通过断点进入password的加密方法,发现是加盐的md5,通过控制台测试字符串’1’,可以看出时标准的md5
在这里插入图片描述
但是当我使用标准的md5加密加盐后的字符串时,却发现与网站加密出的密文不同
在这里插入图片描述
所以此处要将网站使用的MD5算法扣出,不能使用标准的md5

四、验证码

1、分析接口

通过不断点击图片验证码可以看出,网站每次获取验证码都会发送三个请求在这里插入图片描述
通过观察这三个请求可以发现,第二个请求会携带第一个请求返回响应中的ticket,第二个请求返回的响应中有第三个请求的地址。
在这里插入图片描述
在这里插入图片描述
在这里插入图片描述

五、登录流程

首先我们需要先请求图片验证码的第一个接口,获取到ticket,再携带ticket请求第二个接口获取到图片验证码的地址,请求该地址获取到图片,破解图片验证码(我使用的是打码平台)。生成加密参数,携带加密参数以及图片验证码请求登录接口。注意:以上请求均需要携带参数callback,写死即可。
JavaScript源码:

var CryptoJS = require('crypto-js')
var hex_chr = "0123456789abcdef";
function rhex(num) {str = "";for (j = 0; j <= 3; j++)str += hex_chr.charAt((num >> (j * 8 + 4)) & 0x0F) + hex_chr.charAt((num >> (j * 8)) & 0x0F);return str;
}
function str2blks_MD5(str) {nblk = ((str.length + 8) >> 6) + 1;blks = new Array(nblk * 16);for (i = 0; i < nblk * 16; i++)blks[i] = 0;for (i = 0; i < str.length; i++)blks[i >> 2] |= str.charCodeAt(i) << ((i % 4) * 8);blks[i >> 2] |= 0x80 << ((i % 4) * 8);blks[nblk * 16 - 2] = str.length * 8;return blks;
}
function add(x, y) {var lsw = (x & 0xFFFF) + (y & 0xFFFF);var msw = (x >> 16) + (y >> 16) + (lsw >> 16);return (msw << 16) | (lsw & 0xFFFF);
}
function rol(num, cnt) {return (num << cnt) | (num >>> (32 - cnt));
}
function cmn(q, a, b, x, s, t) {return add(rol(add(add(a, q), add(x, t)), s), b);
}
function ff(a, b, c, d, x, s, t) {return cmn((b & c) | ((~b) & d), a, b, x, s, t);
}
function gg(a, b, c, d, x, s, t) {return cmn((b & d) | (c & (~d)), a, b, x, s, t);
}
function hh(a, b, c, d, x, s, t) {return cmn(b ^ c ^ d, a, b, x, s, t);
}
function ii(a, b, c, d, x, s, t) {return cmn(c ^ (b | (~d)), a, b, x, s, t);
}function MD5(str) {x = str2blks_MD5(str);var a = 1732584193;var b = -271733879;var c = -1732584194;var d = 271733878;for (i = 0; i < x.length; i += 16) {var olda = a;var oldb = b;var oldc = c;var oldd = d;a = ff(a, b, c, d, x[i + 0], 7, -680876936);d = ff(d, a, b, c, x[i + 1], 12, -389564586);c = ff(c, d, a, b, x[i + 2], 17, 606105819);b = ff(b, c, d, a, x[i + 3], 22, -1044525330);a = ff(a, b, c, d, x[i + 4], 7, -176418897);d = ff(d, a, b, c, x[i + 5], 12, 1200080426);c = ff(c, d, a, b, x[i + 6], 17, -1473231341);b = ff(b, c, d, a, x[i + 7], 22, -45705983);a = ff(a, b, c, d, x[i + 8], 7, 1770035416);d = ff(d, a, b, c, x[i + 9], 12, -1958414417);c = ff(c, d, a, b, x[i + 10], 17, -42063);b = ff(b, c, d, a, x[i + 11], 22, -1990404162);a = ff(a, b, c, d, x[i + 12], 7, 1804603682);d = ff(d, a, b, c, x[i + 13], 12, -40341101);c = ff(c, d, a, b, x[i + 14], 17, -1502002290);b = ff(b, c, d, a, x[i + 15], 22, 1236535329);a = gg(a, b, c, d, x[i + 1], 5, -165796510);d = gg(d, a, b, c, x[i + 6], 9, -1069501632);c = gg(c, d, a, b, x[i + 11], 14, 643717713);b = gg(b, c, d, a, x[i + 0], 20, -373897302);a = gg(a, b, c, d, x[i + 5], 5, -701558691);d = gg(d, a, b, c, x[i + 10], 9, 38016083);c = gg(c, d, a, b, x[i + 15], 14, -660478335);b = gg(b, c, d, a, x[i + 4], 20, -405537848);a = gg(a, b, c, d, x[i + 9], 5, 568446438);d = gg(d, a, b, c, x[i + 14], 9, -1019803690);c = gg(c, d, a, b, x[i + 3], 14, -187363961);b = gg(b, c, d, a, x[i + 8], 20, 1163531501);a = gg(a, b, c, d, x[i + 13], 5, -1444681467);d = gg(d, a, b, c, x[i + 2], 9, -51403784);c = gg(c, d, a, b, x[i + 7], 14, 1735328473);b = gg(b, c, d, a, x[i + 12], 20, -1926607734);a = hh(a, b, c, d, x[i + 5], 4, -378558);d = hh(d, a, b, c, x[i + 8], 11, -2022574463);c = hh(c, d, a, b, x[i + 11], 16, 1839030562);b = hh(b, c, d, a, x[i + 14], 23, -35309556);a = hh(a, b, c, d, x[i + 1], 4, -1530992060);d = hh(d, a, b, c, x[i + 4], 11, 1272893353);c = hh(c, d, a, b, x[i + 7], 16, -155497632);b = hh(b, c, d, a, x[i + 10], 23, -1094730640);a = hh(a, b, c, d, x[i + 13], 4, 681279174);d = hh(d, a, b, c, x[i + 0], 11, -358537222);c = hh(c, d, a, b, x[i + 3], 16, -722521979);b = hh(b, c, d, a, x[i + 6], 23, 76029189);a = hh(a, b, c, d, x[i + 9], 4, -640364487);d = hh(d, a, b, c, x[i + 12], 11, -421815835);c = hh(c, d, a, b, x[i + 15], 16, 530742520);b = hh(b, c, d, a, x[i + 2], 23, -995338651);a = ii(a, b, c, d, x[i + 0], 6, -198630844);d = ii(d, a, b, c, x[i + 7], 10, 1126891415);c = ii(c, d, a, b, x[i + 14], 15, -1416354905);b = ii(b, c, d, a, x[i + 5], 21, -57434055);a = ii(a, b, c, d, x[i + 12], 6, 1700485571);d = ii(d, a, b, c, x[i + 3], 10, -1894986606);c = ii(c, d, a, b, x[i + 10], 15, -1051523);b = ii(b, c, d, a, x[i + 1], 21, -2054922799);a = ii(a, b, c, d, x[i + 8], 6, 1873313359);d = ii(d, a, b, c, x[i + 15], 10, -30611744);c = ii(c, d, a, b, x[i + 6], 15, -1560198380);b = ii(b, c, d, a, x[i + 13], 21, 1309151649);a = ii(a, b, c, d, x[i + 4], 6, -145523070);d = ii(d, a, b, c, x[i + 11], 10, -1120210379);c = ii(c, d, a, b, x[i + 2], 15, 718787259);b = ii(b, c, d, a, x[i + 9], 21, -343485551);a = add(a, olda);b = add(b, oldb);c = add(c, oldc);d = add(d, oldd);}return rhex(a) + rhex(b) + rhex(c) + rhex(d);
}function getMD5Value(data) {var a = data;var b = "\xa3\xac\xa1\xa3";var c = "fdjf,jkgfkl";var s = a + b + c;return MD5(s);
}var x64Add = function(m, n) {m = [m[0] >>> 16, m[0] & 65535, m[1] >>> 16, m[1] & 65535];n = [n[0] >>> 16, n[0] & 65535, n[1] >>> 16, n[1] & 65535];var o = [0, 0, 0, 0];o[3] += m[3] + n[3];o[2] += o[3] >>> 16;o[3] &= 65535;o[2] += m[2] + n[2];o[1] += o[2] >>> 16;o[2] &= 65535;o[1] += m[1] + n[1];o[0] += o[1] >>> 16;o[1] &= 65535;o[0] += m[0] + n[0];o[0] &= 65535;return [(o[0] << 16) | o[1], (o[2] << 16) | o[3]]};var x64Multiply = function(m, n) {m = [m[0] >>> 16, m[0] & 65535, m[1] >>> 16, m[1] & 65535];n = [n[0] >>> 16, n[0] & 65535, n[1] >>> 16, n[1] & 65535];var o = [0, 0, 0, 0];o[3] += m[3] * n[3];o[2] += o[3] >>> 16;o[3] &= 65535;o[2] += m[2] * n[3];o[1] += o[2] >>> 16;o[2] &= 65535;o[2] += m[3] * n[2];o[1] += o[2] >>> 16;o[2] &= 65535;o[1] += m[1] * n[3];o[0] += o[1] >>> 16;o[1] &= 65535;o[1] += m[2] * n[2];o[0] += o[1] >>> 16;o[1] &= 65535;o[1] += m[3] * n[1];o[0] += o[1] >>> 16;o[1] &= 65535;o[0] += (m[0] * n[3]) + (m[1] * n[2]) + (m[2] * n[1]) + (m[3] * n[0]);o[0] &= 65535;return [(o[0] << 16) | o[1], (o[2] << 16) | o[3]]};var x64Rotl = function(m, n) {n %= 64;if (n === 32) {return [m[1], m[0]]} else {if (n < 32) {return [(m[0] << n) | (m[1] >>> (32 - n)), (m[1] << n) | (m[0] >>> (32 - n))]} else {n -= 32;return [(m[1] << n) | (m[0] >>> (32 - n)), (m[0] << n) | (m[1] >>> (32 - n))]}}};var x64LeftShift = function(m, n) {n %= 64;if (n === 0) {return m} else {if (n < 32) {return [(m[0] << n) | (m[1] >>> (32 - n)), m[1] << n]} else {return [m[1] << (n - 32), 0]}}};var x64Xor = function(m, n) {return [m[0] ^ n[0], m[1] ^ n[1]]};var x64Fmix = function(h) {h = x64Xor(h, [0, h[0] >>> 1]);h = x64Multiply(h, [4283543511, 3981806797]);h = x64Xor(h, [0, h[0] >>> 1]);h = x64Multiply(h, [3301882366, 444984403]);h = x64Xor(h, [0, h[0] >>> 1]);return h};var Fingerprint2_x64hash128 = function(key, seed) {key = key || "";seed = seed || 0;var remainder = key.length % 16;var bytes = key.length - remainder;var h1 = [0, seed];var h2 = [0, seed];var k1 = [0, 0];var k2 = [0, 0];var c1 = [2277735313, 289559509];var c2 = [1291169091, 658871167];for (var i = 0; i < bytes; i = i + 16) {k1 = [((key.charCodeAt(i + 4) & 255)) | ((key.charCodeAt(i + 5) & 255) << 8) | ((key.charCodeAt(i + 6) & 255) << 16) | ((key.charCodeAt(i + 7) & 255) << 24), ((key.charCodeAt(i) & 255)) | ((key.charCodeAt(i + 1) & 255) << 8) | ((key.charCodeAt(i + 2) & 255) << 16) | ((key.charCodeAt(i + 3) & 255) << 24)];k2 = [((key.charCodeAt(i + 12) & 255)) | ((key.charCodeAt(i + 13) & 255) << 8) | ((key.charCodeAt(i + 14) & 255) << 16) | ((key.charCodeAt(i + 15) & 255) << 24), ((key.charCodeAt(i + 8) & 255)) | ((key.charCodeAt(i + 9) & 255) << 8) | ((key.charCodeAt(i + 10) & 255) << 16) | ((key.charCodeAt(i + 11) & 255) << 24)];k1 = x64Multiply(k1, c1);k1 = x64Rotl(k1, 31);k1 = x64Multiply(k1, c2);h1 = x64Xor(h1, k1);h1 = x64Rotl(h1, 27);h1 = x64Add(h1, h2);h1 = x64Add(x64Multiply(h1, [0, 5]), [0, 1390208809]);k2 = x64Multiply(k2, c2);k2 = x64Rotl(k2, 33);k2 = x64Multiply(k2, c1);h2 = x64Xor(h2, k2);h2 = x64Rotl(h2, 31);h2 = x64Add(h2, h1);h2 = x64Add(x64Multiply(h2, [0, 5]), [0, 944331445])}k1 = [0, 0];k2 = [0, 0];switch (remainder) {case 15:k2 = x64Xor(k2, x64LeftShift([0, key.charCodeAt(i + 14)], 48));case 14:k2 = x64Xor(k2, x64LeftShift([0, key.charCodeAt(i + 13)], 40));case 13:k2 = x64Xor(k2, x64LeftShift([0, key.charCodeAt(i + 12)], 32));case 12:k2 = x64Xor(k2, x64LeftShift([0, key.charCodeAt(i + 11)], 24));case 11:k2 = x64Xor(k2, x64LeftShift([0, key.charCodeAt(i + 10)], 16));case 10:k2 = x64Xor(k2, x64LeftShift([0, key.charCodeAt(i + 9)], 8));case 9:k2 = x64Xor(k2, [0, key.charCodeAt(i + 8)]);k2 = x64Multiply(k2, c2);k2 = x64Rotl(k2, 33);k2 = x64Multiply(k2, c1);h2 = x64Xor(h2, k2);case 8:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 7)], 56));case 7:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 6)], 48));case 6:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 5)], 40));case 5:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 4)], 32));case 4:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 3)], 24));case 3:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 2)], 16));case 2:k1 = x64Xor(k1, x64LeftShift([0, key.charCodeAt(i + 1)], 8));case 1:k1 = x64Xor(k1, [0, key.charCodeAt(i)]);k1 = x64Multiply(k1, c1);k1 = x64Rotl(k1, 31);k1 = x64Multiply(k1, c2);h1 = x64Xor(h1, k1)}h1 = x64Xor(h1, [0, key.length]);h2 = x64Xor(h2, [0, key.length]);h1 = x64Add(h1, h2);h2 = x64Add(h2, h1);h1 = x64Fmix(h1);h2 = x64Fmix(h2);h1 = x64Add(h1, h2);h2 = x64Add(h2, h1);return ("00000000" + (h1[0] >>> 0).toString(16)).slice(-8) + ("00000000" + (h1[1] >>> 0).toString(16)).slice(-8) + ("00000000" + (h2[0] >>> 0).toString(16)).slice(-8) + ("00000000" + (h2[1] >>> 0).toString(16)).slice(-8)};function printComponents(components) {var values = components.map(function(component) {return component.value});var hash = Fingerprint2_x64hash128(values.join(''), 31);return hash
}var components = [{"key": "userAgent","value": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36"},{"key": "webdriver","value": false},{"key": "language","value": "zh-CN"},{"key": "colorDepth","value": 24},{"key": "deviceMemory","value": 8},{"key": "hardwareConcurrency","value": 12},{"key": "screenResolution","value": [1920,1080]},{"key": "availableScreenResolution","value": [1920,1032]},{"key": "timezoneOffset","value": -480},{"key": "timezone","value": "Asia/Shanghai"},{"key": "sessionStorage","value": true},{"key": "localStorage","value": true},{"key": "indexedDb","value": true},{"key": "addBehavior","value": false},{"key": "openDatabase","value": true},{"key": "cpuClass","value": "not available"},{"key": "platform","value": "Win32"},{"key": "plugins","value": [["PDF Viewer","Portable Document Format",[["application/pdf","pdf"],["text/pdf","pdf"]]],["Chrome PDF Viewer","Portable Document Format",[["application/pdf","pdf"],["text/pdf","pdf"]]],["Chromium PDF Viewer","Portable Document Format",[["application/pdf","pdf"],["text/pdf","pdf"]]],["Microsoft Edge PDF Viewer","Portable Document Format",[["application/pdf","pdf"],["text/pdf","pdf"]]],["WebKit built-in PDF","Portable Document Format",[["application/pdf","pdf"],["text/pdf","pdf"]]]]},{"key": "canvas","value": ["canvas winding:yes","canvas fp:data:image/png;base64,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"]},{"key": "webgl","value": ["data:image/png;base64,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","extensions:ANGLE_instanced_arrays;EXT_blend_minmax;EXT_color_buffer_half_float;EXT_disjoint_timer_query;EXT_float_blend;EXT_frag_depth;EXT_shader_texture_lod;EXT_texture_compression_bptc;EXT_texture_compression_rgtc;EXT_texture_filter_anisotropic;EXT_sRGB;KHR_parallel_shader_compile;OES_element_index_uint;OES_fbo_render_mipmap;OES_standard_derivatives;OES_texture_float;OES_texture_float_linear;OES_texture_half_float;OES_texture_half_float_linear;OES_vertex_array_object;WEBGL_color_buffer_float;WEBGL_compressed_texture_s3tc;WEBGL_compressed_texture_s3tc_srgb;WEBGL_debug_renderer_info;WEBGL_debug_shaders;WEBGL_depth_texture;WEBGL_draw_buffers;WEBGL_lose_context;WEBGL_multi_draw","webgl aliased line width range:[1, 1]","webgl aliased point size range:[1, 1024]","webgl alpha bits:8","webgl antialiasing:yes","webgl blue bits:8","webgl depth bits:24","webgl green bits:8","webgl max anisotropy:16","webgl max combined texture image units:32","webgl max cube map texture size:16384","webgl max fragment uniform vectors:1024","webgl max render buffer size:16384","webgl max texture image units:16","webgl max texture size:16384","webgl max varying vectors:30","webgl max vertex attribs:16","webgl max vertex texture image units:16","webgl max vertex uniform vectors:4095","webgl max viewport dims:[32767, 32767]","webgl red bits:8","webgl renderer:WebKit WebGL","webgl shading language version:WebGL GLSL ES 1.0 (OpenGL ES GLSL ES 1.0 Chromium)","webgl stencil bits:0","webgl vendor:WebKit","webgl version:WebGL 1.0 (OpenGL ES 2.0 Chromium)","webgl unmasked vendor:Google Inc. (NVIDIA)","webgl unmasked renderer:ANGLE (NVIDIA, NVIDIA GeForce GTX 1050 Ti Direct3D11 vs_5_0 ps_5_0, D3D11)","webgl vertex shader high float precision:23","webgl vertex shader high float precision rangeMin:127","webgl vertex shader high float precision rangeMax:127","webgl vertex shader medium float precision:23","webgl vertex shader medium float precision rangeMin:127","webgl vertex shader medium float precision rangeMax:127","webgl vertex shader low float precision:23","webgl vertex shader low float precision rangeMin:127","webgl vertex shader low float precision rangeMax:127","webgl fragment shader high float precision:23","webgl fragment shader high float precision rangeMin:127","webgl fragment shader high float precision rangeMax:127","webgl fragment shader medium float precision:23","webgl fragment shader medium float precision rangeMin:127","webgl fragment shader medium float precision rangeMax:127","webgl fragment shader low float precision:23","webgl fragment shader low float precision rangeMin:127","webgl fragment shader low float precision rangeMax:127","webgl vertex shader high int precision:0","webgl vertex shader high int precision rangeMin:31","webgl vertex shader high int precision rangeMax:30","webgl vertex shader medium int precision:0","webgl vertex shader medium int precision rangeMin:31","webgl vertex shader medium int precision rangeMax:30","webgl vertex shader low int precision:0","webgl vertex shader low int precision rangeMin:31","webgl vertex shader low int precision rangeMax:30","webgl fragment shader high int precision:0","webgl fragment shader high int precision rangeMin:31","webgl fragment shader high int precision rangeMax:30","webgl fragment shader medium int precision:0","webgl fragment shader medium int precision rangeMin:31","webgl fragment shader medium int precision rangeMax:30","webgl fragment shader low int precision:0","webgl fragment shader low int precision rangeMin:31","webgl fragment shader low int precision rangeMax:30"]},{"key": "webglVendorAndRenderer","value": "Google Inc. (NVIDIA)~ANGLE (NVIDIA, NVIDIA GeForce GTX 1050 Ti Direct3D11 vs_5_0 ps_5_0, D3D11)"},{"key": "adBlock","value": false},{"key": "hasLiedLanguages","value": false},{"key": "hasLiedResolution","value": false},{"key": "hasLiedOs","value": false},{"key": "hasLiedBrowser","value": false},{"key": "touchSupport","value": [0,false,false]},{"key": "fonts","value": ["Arial","Arial Black","Arial Narrow","Book Antiqua","Bookman Old Style","Calibri","Cambria","Cambria Math","Century","Century Gothic","Comic Sans MS","Consolas","Courier","Courier New","Georgia","Helvetica","Impact","Lucida Console","Lucida Handwriting","Lucida Sans Unicode","Microsoft Sans Serif","Monotype Corsiva","MS Gothic","MS PGothic","MS Reference Sans Serif","MS Sans Serif","MS Serif","Palatino Linotype","Segoe Print","Segoe Script","Segoe UI","Segoe UI Light","Segoe UI Semibold","Segoe UI Symbol","Tahoma","Times","Times New Roman","Trebuchet MS","Verdana","Wingdings","Wingdings 2","Wingdings 3"]},{"key": "audio","value": "124.04347527516074"}
]
function get_login_url(CallBack, userName, checkCode, password) {password = getMD5Value(password)aws = printComponents(components)var url = 'https://aq.99.com/AjaxAction/AC_userlogin.ashx'return url + "?CallBack=" + CallBack + "&siteflag=995&nduseraction=login&txtUserName=" + userName + "&txtPassword=" + password + "&checkcode=" + checkCode + "&Rnd=" + Math.random() + "&aws=" + aws;
}

Python源码:

"""
Email:912917367@qq.com
Date: 2023/8/24 10:18
"""
import re
import timeimport execjs
import requestsfrom utils.chaojiying import ChaojiyingClientclass Spider:def __init__(self, username, password):self.session = requests.session()self.session.headers = {"authority": "checkcode.99.com","referer": "https://aq.99.com/","user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36"}self.callback = 'jQuery112401962284678331523_1692843120473'self.ticket = ''self.img_url = ''self.pic_str = ''self.username = usernameself.password = passworddef get_ticket(self):url = "https://checkcode.99.com/token"params = {"action": "getticket","bussiness": "aq_login","callback": self.callback,"_": str(int(time.time() * 1000))}response = self.session.get(url, params=params)pattern = r'"ticket":"(.*?)"'self.ticket = re.findall(pattern, response.text)[0]print('ticket:', self.ticket)def get_img_url(self):url = "https://aq.99.com/AjaxAction/AC_verifycode.ashx"params = {"CallBack": self.callback,"nduseraction": "getverifycodestate","verifycodetype": "UserLogin","bussiness": "aq_login","ticket": self.ticket,"SiteFlag": "995","RND": "0.7099289496089389","_": str(int(time.time() * 1000))}response = self.session.get(url, params=params)pattern = r'"VerifyCodeUrl":"(.*?)"'self.img_url = re.findall(pattern, response.text)[0]print('img_url:', self.img_url)def get_img_code(self):response = self.session.get(self.img_url)with open('img.png', 'wb') as f:f.write(response.content)cjy = ChaojiyingClient('打码平台账号', '打码平台密码', '946014')im = open('img.png', 'rb').read()pic_data = cjy.post_pic(im, 1902)self.pic_str = pic_data['pic_str']print('pic_str:', self.pic_str)def login(self):with open('get_params.js', 'r', encoding='utf-8') as f:js_obj = execjs.compile(f.read())url = js_obj.call('get_login_url', self.callback, self.username, self.pic_str, self.password)response = self.session.get(url)print(response.text)print(response)if __name__ == '__main__':s = Spider('账号', '密码')s.get_ticket()s.get_img_url()s.get_img_code()s.login()

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.mzph.cn/news/52458.shtml

如若内容造成侵权/违法违规/事实不符,请联系多彩编程网进行投诉反馈email:809451989@qq.com,一经查实,立即删除!

相关文章

Source Insight 宏-局部替换

编码中有没有遇到这种情况&#xff1a;添加一个新的函数&#xff0c;参考某某函数。然后我们新加一个函数名&#xff0c;把某某函数的内容全部拷贝过来&#xff0c;参数不一样时&#xff0c;再把拷贝过来的内容里的参数全部替换成新的参数。source insight 里替换的命令是ctrlh…

基于SSM的OA办公系统Java企业人事信息管理jsp源代码MySQL

本项目为前几天收费帮学妹做的一个项目&#xff0c;Java EE JSP项目&#xff0c;在工作环境中基本使用不到&#xff0c;但是很多学校把这个当作编程入门的项目来做&#xff0c;故分享出本项目供初学者参考。 一、项目描述 基于SSM的OA办公系统 系统有1权限&#xff1a;管理员…

深度丨Serverless + AIGC,一场围绕加速创新的升维布局

作者&#xff1a;褚杏娟 上图来源于基于函数计算部署 SD实现光影效果 前言&#xff1a; Serverless 在中国发展这些年&#xff0c;经历了高潮、低谷、现在重新回到大众视野。很多企业都非常感兴趣&#xff0c;部分企业开始大规模应用&#xff1b;也有一些企业对在生产环境真正…

RTSP/Onvif视频服务器EasyNVR安防视频云服务平台出现崩溃并重启的情况解决方案

EasyNVR安防视频云服务平台的特点是基于RTSP/Onvif协议将前端设备统一接入&#xff0c;在平台进行转码、直播、处理及分发&#xff0c;在安防监控场景中&#xff0c;EasyNVR可实现实时监控、云端录像、云存储、告警、级联等视频能力&#xff0c;极大满足行业的视频监控需求。 有…

网络安全入口设计模式

网络安全入口涵盖了几种设计模式&#xff0c;包括全局路由模式、全局卸载模式和健康终端监控模式。网络安全入口侧重于&#xff1a;全局路由、低延迟故障切换和在边缘处减轻攻击。 上图包含了3个需求。 •网络安全入口模式封装了全局路由模式。因此&#xff0c;实现可以将请求路…

2023年高教社杯数学建模思路 - 复盘:校园消费行为分析

文章目录 0 赛题思路1 赛题背景2 分析目标3 数据说明4 数据预处理5 数据分析5.1 食堂就餐行为分析5.2 学生消费行为分析 建模资料 0 赛题思路 &#xff08;赛题出来以后第一时间在CSDN分享&#xff09; https://blog.csdn.net/dc_sinor?typeblog 1 赛题背景 校园一卡通是集…

线性代数的学习和整理4: 求逆矩阵的多种方法汇总

目录 原始问题&#xff1a;如何求逆矩阵&#xff1f; 1 EXCEL里&#xff0c;直接可以用黑盒表内公式 minverse() 数组公式求A- 2 非线性代数方法&#xff1a;解方程组的方法 3 增广矩阵的方法 4 用行列式的方法计算&#xff08;未验证&#xff09; 5 A-1/|A|*A* &…

报名开启 | HarmonyOS第一课“营”在暑期系列直播

<HarmonyOS第一课>2023年再次启航&#xff01; 特邀HarmonyOS布道师云集华为开发者联盟直播间 聚焦HarmonyOS 4版本新特性 邀您一同学习赢好礼&#xff01; 你准备好了吗&#xff1f; ↓↓↓预约报名↓↓↓ 点击关注了解更多资讯&#xff0c;报名学习

用pytorch实现Resnet

ResNet&#xff08;Residual Network&#xff09;是一种深度卷积神经网络架构&#xff0c;由Kaiming He等人于2015年提出。它在计算机视觉领域引起了革命性的变革&#xff0c;使得训练更深的神经网络成为可能&#xff0c;超越了传统网络架构的限制。 ResNet的主要创新在于…

动态规划入门:斐波那契数列模型以及多状态(C++)

斐波那契数列模型以及多状态 动态规划简述斐波那契数列模型1.第 N 个泰波那契数&#xff08;简单&#xff09;2.三步问题&#xff08;简单&#xff09;3.使⽤最⼩花费爬楼梯&#xff08;简单&#xff09;4.解码方法&#xff08;中等&#xff09; 简单多状态1.打家劫舍&#xff…

Redis 重写 AOF 日志期间,主进程可以正常处理命令吗?

重写 AOF 日志的过程是怎样的&#xff1f; Redis 的重写 AOF 过程是由后台子进程 bgrewriteaof 来完成的&#xff0c;这么做有以下两个好处。 子进程进行 AOF 重写期间&#xff0c;主进程可以继续处理命令请求&#xff0c;从而避免阻塞主进程子进程带有主进程的数据副本。这里…

leetcode359周赛

2828. 判别首字母缩略词 核心思想:枚举。只需要枚举首字母和s是否一一对应即可。 2829. k-avoiding 数组的最小总和 核心思想&#xff1a;自己的方法就是哈希表&#xff0c;枚举i的时候&#xff0c;将k-i统计起来&#xff0c;如果出现了那么就跳过。灵神的方法是数学法&#…

OpenCV项目开发实战--基于Python/C++实现鼠标注释图像和轨迹栏来控制图像大小

鼠标指针是图形用户界面 (GUI) 中的关键组件。没有它,您就无法真正考虑与 GUI 进行交互。那么,让我们深入了解 OpenCV 中鼠标和轨迹栏的内置函数。我们将演示如何使用鼠标来注释图像,以及如何使用轨迹栏来控制图像的大小 我们将使用下图来演示 OpenCV 中鼠标指针和轨迹栏功能…

stm32之16.外设定时器——TIM3

----------- 源码 void tim3_init(void) {NVIC_InitTypeDef NVIC_InitStructure;TIM_TimeBaseInitTypeDef TIM_TimeBaseStructure;//使能TIM3的硬件时钟RCC_APB1PeriphClockCmd(RCC_APB1Periph_TIM3,ENABLE);//配置TIM3的定时时间TIM_TimeBaseStructure.TIM_Period 10000-1…

短视频seo源码矩阵系统开源---代码php分享

前言&#xff1a;短视频seo源码 短视频seo矩阵系统源码私有化部署 短视频seo源码 短视频seo矩阵系统源码私有化怎么部署&#xff1f; 首先我们来给大家普及一下什么是短视频seo矩阵系统&#xff1f;视频矩阵分为多平台矩阵与一个平台多账号矩阵&#xff0c;加上seo排名优化&…

R语言快速生成三线表(1)

R语言的优势在于批量处理&#xff0c;常使用到循环和函数&#xff0c;三线表是科研文章中必备的内容。利用函数实现自动判断数据类型和计算。使用R包&#xff08;table1&#xff09;。 # 创建连续性变量 continuous_var1 <- c(1.2, 2.5, 3.7, 4.8, 5.9) continuous_var2 &l…

uniapp踩坑合集

1、onPullDownRefresh下拉刷新不生效 pages.json对应的style中enablePullDownRefresh设置为true&#xff0c;开启下拉刷新 {"path" : "pages/list/list","style" :{"navigationBarTitleText": "页面标题名称","enable…

Mybatis的动态SQL分页及特殊字符的使用

目录 一、分页 ( 1 ) 应用场景 ( 2 ) 使用 二、特殊字符 2.1 介绍 2.2 使用 给我们带来的收获 一、分页 分页技术的出现是为了解决大数据量展示、页面加载速度、页面长度控制和用户体验等问题。通过将数据分成多个页面&#xff0c;用户可以根据需求选择查看不同页的数据…

Oracle 查询(当天,月,年)的数据

Trunc 在oracle中&#xff0c;可利用 trunc函数 查询当天数据&#xff0c;该函数可用于截取时间或者数值&#xff0c;将该函数与 select 语句配合使用可查询时间段数据 查询当天数据 --sysdate是获取系统当前时间函数 --TRUNC函数用于截取时间或者数值&#xff0c;返回指定的…

Leetcode.73矩阵置零

给定一个 m x n 的矩阵&#xff0c;如果一个元素为 0 &#xff0c;则将其所在行和列的所有元素都设为 0 。请使用 原地 算法 class Solution {public void setZeroes(int[][] matrix) {int m matrix.length, n matrix[0].length;boolean[] row new boolean[m];boolean[] col…