程序员
+标签"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "id": "32925020",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:19:12.610166Z",
+ "start_time": "2023-10-24T02:19:12.600165Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[北理工 ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 返回 id为 title 的标签\n",
+ "print(soup.find_all(id='title'))\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e98da6cf",
+ "metadata": {},
+ "source": [
+ "#### 按CSS搜索\n",
+ "\n",
+ "> 按照CSS类名搜索tag的功能非常实用,但标识CSS类名的关键字 class 在Python中是保留字,使用 class 做参数会导致语法错误.从Beautiful Soup的4.1.1版本开始,可以通过 class_ 参数搜索有指定CSS类名的tag"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 60,
+ "id": "c40a98dd",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:27:04.753569Z",
+ "start_time": "2023-10-24T02:27:04.750063Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[北理工 ]\n",
+ "\n",
+ "[北理工 \n",
+ "\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 字符串方式创建 pyquery对象\n",
+ "html = '''\n",
+ "北理工 \n",
+ "\n",
+ "百度一下，你就知道 \n"
+ ]
+ }
+ ],
+ "source": [
+ "# url方式创建 pyquery对象\n",
+ "\n",
+ "from pyquery import PyQuery as pq\n",
+ "\n",
+ "# 创建 pyquery对象\n",
+ "doc = pq(url='http://www.baidu.com')\n",
+ "\n",
+ "# 获取 title标签\n",
+ "print(doc('title'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "id": "f0a3eb84",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:52:41.644248Z",
+ "start_time": "2023-10-24T02:52:41.633368Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Document \n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 文件方式创建 pyquery对象\n",
+ "\n",
+ "from pyquery import PyQuery as pq\n",
+ "\n",
+ "# 创建 pyquery对象\n",
+ "doc = pq(filename='./html/alter.html')\n",
+ "\n",
+ "# 获取 title标签\n",
+ "print(doc('title'))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "ce70334a",
+ "metadata": {},
+ "source": [
+ "### 选择节点\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 71,
+ "id": "d41643e1",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:58:46.980310Z",
+ "start_time": "2023-10-24T03:58:46.971796Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Document \n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 获取当前节点\n",
+ "\n",
+ "from pyquery import PyQuery as pq\n",
+ "\n",
+ "# 创建 pyquery对象\n",
+ "doc = pq(filename='./html/alter.html')\n",
+ "\n",
+ "# 选择 id为t的 标签\n",
+ "print(doc('#t'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 78,
+ "id": "21c84192",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T04:02:44.004050Z",
+ "start_time": "2023-10-24T04:02:43.996194Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "hello \")\n",
+ "\n",
+ "path_to_html_file = './html/alter.html'\n",
+ "d = pq(filename=path_to_html_file)\n",
+ "\n",
+ "d = pq(url='http://www.baidu.com') # 注意：此处url似乎必须写全\n",
+ "\n",
+ "\n",
+ "# 2.html() 和 text() ——获取相应的 HTML块 或 文本块，\n",
+ "p = pq(\"hello \")\n",
+ "\n",
+ "p('head').html() # 返回 hello \n",
+ "p('head').text() # 返回 hello"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 78,
+ "id": "e167b9e9",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:06:14.156634Z",
+ "start_time": "2023-10-24T03:06:14.150034Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "')\n",
+ "\n",
+ "print(d('p')) # 返回 \"\"\")\n",
+ "\n",
+ "# 选择 id为1 的 p标签\n",
+ "print(d('p').filter('#1'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 49,
+ "id": "7f8d497c",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:42:02.452726Z",
+ "start_time": "2023-10-24T03:42:02.447411Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "\")\n",
+ "\n",
+ "# 找到 div标签下的 所有p标签\n",
+ "print(d('div').find('p')) \n",
+ "\n",
+ "# 找到 div标签下的 第一个 p标签\n",
+ "print(d('div').find('p').eq(0)) "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 53,
+ "id": "768697f5",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:45:14.988145Z",
+ "start_time": "2023-10-24T03:45:14.983700Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "'test 1'"
+ ]
+ },
+ "execution_count": 53,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 7.直接根据类名、id名获取元素，例：\n",
+ "d = pq(\"\")\n",
+ "\n",
+ "# 获取 id为1 的标签内容\n",
+ "d('#1').html() # 返回test 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 55,
+ "id": "051fd93a",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:46:52.522269Z",
+ "start_time": "2023-10-24T03:46:52.516744Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "http://hello.com\n",
+ "my_id\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 8.获取属性值，例：\n",
+ "d = pq(\"\")\n",
+ "\n",
+ "# 获取 a标签的 href属性\n",
+ "print(d('a').attr('href')) # 返回 http://hello.com\n",
+ "\n",
+ "# 获取 p标签的 id\n",
+ "print(d('p').attr('id')) # 返回 my_id"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "id": "ae841375",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:47:21.497509Z",
+ "start_time": "2023-10-24T03:47:21.492923Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "http://baidu.com\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 9.修改属性值，例：\n",
+ "d('a').attr('href', 'http://baidu.com') # 把href属性修改为了baidu\n",
+ "print(d('a').attr('href'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "id": "02b3cbbd",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:49:28.352457Z",
+ "start_time": "2023-10-24T03:49:28.348301Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "![]()
\n",
+ "![]()
\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 14.nextAll(selector=None) —— 返回后面全部的元素块，例：\n",
+ "d = pq(\"![]()
\")\n",
+ "\n",
+ "# 获取 第一个 p标签后 所有元素块\n",
+ "print(d('p:first').nextAll())\n",
+ "\n",
+ "# 获取 最后一个 p标签后 所有元素块\n",
+ "print(d('p:last').nextAll())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "id": "2c9591b8",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:57:54.502944Z",
+ "start_time": "2023-10-24T03:57:54.498570Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4c067891",
+ "metadata": {},
+ "source": [
+ "## 数据提取_XPath\n",
+ "[官网](http://lxml.de/index.html)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "12e41d17",
+ "metadata": {},
+ "source": [
+ "### 选取节点"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "36434c52",
+ "metadata": {},
+ "source": [
+ "**节点之间的关系：**\n",
+ "- 父（Parent）\n",
+ "- 子（Children）\n",
+ "- 同胞（Sibling）\n",
+ "- 先辈（Ancestor）\n",
+ "- 后代（Descendant）"
+ ]
+ },
+ {
+ "attachments": {
+ "%E6%88%AA%E5%B1%8F2023-10-24%2012.15.57.png": {
+ "image/png": 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"
+ }
+ },
+ "cell_type": "markdown",
+ "id": "f6a6d411",
+ "metadata": {},
+ "source": [
+ "**常用的路径表达式：**\n",
+ ""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d23d53b0",
+ "metadata": {},
+ "source": [
+ "**选取若干路径：**\n",
+ "\n",
+ "通过在路径表达式中使用“|”运算符，您可以选取若干个路径\n",
+ "\n",
+ "xpath('//div`|`//table') 获取所有的div与table节点"
+ ]
+ },
+ {
+ "attachments": {
+ "%E6%88%AA%E5%B1%8F2023-10-24%2012.20.17.png": {
+ "image/png": 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"
+ }
+ },
+ "cell_type": "markdown",
+ "id": "7e5817e8",
+ "metadata": {},
+ "source": [
+ "**谓语：**\n",
+ "\n",
+ "谓语被嵌在方括号内，用来查找某个特定的节点或包含某个制定的值的节点\n",
+ "\n",
+ ""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "78ab6e2e",
+ "metadata": {},
+ "source": [
+ "**选择XML文件中节点：**\n",
+ "\n",
+ "- element（元素节点）\n",
+ "- attribute（属性节点）\n",
+ "- text （文本节点）\n",
+ "- concat (元素节点,元素节点)\n",
+ "- comment （注释节点）\n",
+ "- root （根节点）"
+ ]
+ },
+ {
+ "attachments": {
+ "%E6%88%AA%E5%B1%8F2023-10-24%2018.19.11.png": {
+ "image/png": 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"
+ }
+ },
+ "cell_type": "markdown",
+ "id": "fe5ec231",
+ "metadata": {},
+ "source": [
+ "**XPath 运算符：**\n",
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 92,
+ "id": "3cadf879",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:22:39.301359Z",
+ "start_time": "2023-10-24T10:22:39.296414Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ ", , , , ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取所有的 `` 标签\"\"\"\n",
+ "from lxml import etree\n",
+ "\n",
+ "# 读取 HTML文件\n",
+ "html = etree.parse('./html/hello.html')\n",
+ "\n",
+ "# 获取 标签\n",
+ "result = html.xpath('//li')\n",
+ "\n",
+ "print (result)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 95,
+ "id": "5a9420a7",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:28:37.391131Z",
+ "start_time": "2023-10-24T10:28:37.385440Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['item-0', 'item-1', 'item-inactive', 'item-1', 'item-0']\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取` `标签的所有 class\"\"\"\n",
+ "result = html.xpath('//li/@class')\n",
+ "print (result)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 96,
+ "id": "55927e51",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:29:27.999978Z",
+ "start_time": "2023-10-24T10:29:27.995068Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[]\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取 `` 标签下 href 为 link1.html 的 `` 标签\"\"\"\n",
+ "result = html.xpath('//li/a[@href=\"link1.html\"]')\n",
+ "print(result)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 97,
+ "id": "a45460c8",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:31:38.075629Z",
+ "start_time": "2023-10-24T10:31:38.066302Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[]\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取` `标签下的所有 `` 标签\"\"\"\n",
+ "\n",
+ "result = html.xpath('//li/span') # 这么写是不对的\n",
+ "\n",
+ "# 因为 / 是用来获取子元素的，而 并不是 的子元素，所以，要用双斜杠\n",
+ "result = html.xpath('//li//span')\n",
+ "print(result)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 98,
+ "id": "df404cba",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:32:43.458909Z",
+ "start_time": "2023-10-24T10:32:43.454371Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['bold']\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取 ` ` 标签下的所有 class，不包括` `\"\"\"\n",
+ "result = html.xpath('//li/a//@class')\n",
+ "print(result)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 99,
+ "id": "6fbbbf2b",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:34:32.794532Z",
+ "start_time": "2023-10-24T10:34:32.789424Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['link5.html']\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取最后一个 ` ` 的 `` 的 href\"\"\"\n",
+ "result = html.xpath('//li[last()]/a/@href')\n",
+ "print(result)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 100,
+ "id": "766ddc44",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:35:10.693885Z",
+ "start_time": "2023-10-24T10:35:10.688184Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "fourth item\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取倒数第二个元素的内容\"\"\"\n",
+ "result = html.xpath('//li[last()-1]/a')\n",
+ "print(result[0].text)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 101,
+ "id": "961c6d44",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:35:51.800780Z",
+ "start_time": "2023-10-24T10:35:51.796044Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "span\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"获取 class 为 bold 的标签名\"\"\"\n",
+ "result = html.xpath('//*[@class=\"bold\"]')\n",
+ "print(result[0].tag)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d746cac3",
+ "metadata": {},
+ "source": [
+ "## 数据提取_jsonPath"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "cf901a7f",
+ "metadata": {},
+ "source": [
+ "### Json\n",
+ "json简单说就是 javascript 中的对象 和 数组，所以这两种结构就是对象和数组两种结构\n",
+ "\n",
+ "1. 对象：对象在js中表示为{ }括起来的内容，数据结构为 { key：value, key：value, ... }的键值对的结构，在面向对象的语言中，key为对象的属性，value为对应的属性值，所以很容易理解，取值方法为 对象.key 获取属性值，这个属性值的类型可以是数字、字符串、数组、对象这几种\n",
+ " \n",
+ "2. 数组：数组在js中是中括号[ ]括起来的内容，数据结构为 [\"Python\", \"javascript\", \"C++\", ...]，取值方式和所有语言中一样，使用索引获取，字段值的类型可以是 数字、字符串、数组、对象几种"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "702f049d",
+ "metadata": {},
+ "source": [
+ "### json.loads()\n",
+ "\n",
+ "> 把Json格式字符串解码转换成 Python 对象 从 json到python 的类型转化对照如下："
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 103,
+ "id": "9609d5ea",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:43:32.998146Z",
+ "start_time": "2023-10-24T10:43:32.994078Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1, 2, 3, 4]\n",
+ "{'city': '北京', 'name': '范爷'}\n"
+ ]
+ }
+ ],
+ "source": [
+ "import json\n",
+ "\n",
+ "strList = '[1, 2, 3, 4]'\n",
+ "strDict = '{\"city\": \"北京\", \"name\": \"范爷\"}'\n",
+ "\n",
+ "# string -> json\n",
+ "print(json.loads(strList))\n",
+ "\n",
+ "# string -> json\n",
+ "print(json.loads(strDict))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "07ec8fab",
+ "metadata": {},
+ "source": [
+ "### json.dumps()\n",
+ "\n",
+ "> 实现 python 类型转化为 json 字符串，返回一个 str 对象 把一个 Python对象编码转换成 Json字符串\n",
+ "\n",
+ "> 从python原始类型向json类型的转化对照如下："
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 104,
+ "id": "c5846941",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:45:54.912027Z",
+ "start_time": "2023-10-24T10:45:54.904853Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1, 2, 3, 4]\n",
+ "[1, 2, 3, 4]\n",
+ "{\"city\": \"\\u5317\\u4eac\", \"name\": \"\\u8303\\u7237\"}\n",
+ "{\"city\": \"北京\", \"name\": \"范爷\"}\n"
+ ]
+ }
+ ],
+ "source": [
+ "import json\n",
+ "\n",
+ "\n",
+ "listStr = [1, 2, 3, 4]\n",
+ "tupleStr = (1, 2, 3, 4)\n",
+ "dictStr = {\"city\": \"北京\", \"name\": \"范爷\"}\n",
+ "\n",
+ "# list -> json字符串\n",
+ "print(json.dumps(listStr))\n",
+ "\n",
+ "# tuple -> json字符串\n",
+ "print(json.dumps(tupleStr))\n",
+ "\n",
+ "\n",
+ "# 注意：json.dumps() 序列化时默认使用的 ascii编码\n",
+ "# 添加参数 ensure_ascii=False 禁用ascii编码，按 utf-8编码\n",
+ "\n",
+ "print(json.dumps(dictStr))\n",
+ "print(json.dumps(dictStr, ensure_ascii=False))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2aeccb13",
+ "metadata": {},
+ "source": [
+ "### json.dump()\n",
+ "\n",
+ "> 将Python内置类型序列化为 json对象后写入文件"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 105,
+ "id": "5f961f56",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:48:05.380569Z",
+ "start_time": "2023-10-24T10:48:05.375664Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "import json\n",
+ "\n",
+ "# 列表 -> json文件\n",
+ "listStr = [{\"city\": \"北京\"}, {\"name\": \"范爷\"}]\n",
+ "json.dump(listStr, open(\"./data/listStr.json\", \"w\"), ensure_ascii=False)\n",
+ "\n",
+ "# 字典 -> json文件\n",
+ "dictStr = {\"city\": \"北京\", \"name\": \"范爷\"}\n",
+ "json.dump(dictStr, open(\"./data/dictStr.json\", \"w\"), ensure_ascii=False)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fcf0d230",
+ "metadata": {},
+ "source": [
+ "### json.load()\n",
+ "\n",
+ "> 读取文件中json形式 的字符串元素 转化成python类型"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 107,
+ "id": "a546d932",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:49:52.826618Z",
+ "start_time": "2023-10-24T10:49:52.821023Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[{'city': '北京'}, {'name': '范爷'}]\n",
+ "{'city': '北京', 'name': '范爷'}\n"
+ ]
+ }
+ ],
+ "source": [
+ "import json\n",
+ "\n",
+ "# json -> list\n",
+ "strList = json.load(open(\"./data/listStr.json\"))\n",
+ "print(strList)\n",
+ "\n",
+ "# json -> dict\n",
+ "strDict = json.load(open(\"./data/dictStr.json\"))\n",
+ "print(strDict)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "d005f128",
+ "metadata": {},
+ "source": [
+ "### JsonPath\n",
+ "\n",
+ "JsonPath 是一种信息抽取类库，是从 JSON文档 中抽取指定信息的工具"
+ ]
+ },
+ {
+ "attachments": {
+ "%E6%88%AA%E5%B1%8F2023-10-24%2018.51.09.png": {
+ "image/png": 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"
+ }
+ },
+ "cell_type": "markdown",
+ "id": "c4b8e6e4",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 113,
+ "id": "12a9ecc6",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T11:01:01.272898Z",
+ "start_time": "2023-10-24T11:01:01.141254Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['安阳', '安庆', '安康', '安顺', '鞍山', '澳门', '阿拉善盟', '阿坝藏族羌族自治州', '阿拉尔', '北京', '保定', '包头', '滨州', '蚌埠', '宝鸡', '北海', '亳州', '毕节', '百色', '保山', '本溪', '巴音郭楞', '巴中', '白银', '巴彦淖尔', '白城', '白山', '北屯', '成都', '长沙', '重庆', '长春', '常州', '沧州', '郴州', '赤峰', '承德', '常德', '滁州', '潮州', '朝阳', '楚雄', '澄迈', '池州', '昌吉', '崇左', '昌都', '东莞', '大连', '德州', '德阳', '大理', '大同', '东营', '达州', '大庆', '丹东', '定西', '德宏', '儋州', '大兴安岭', '鄂尔多斯', '鄂州', '恩施', '佛山', '福州', '阜阳', '抚州', '阜新', '抚顺', '防城港', '广州', '贵阳', '赣州', '桂林', '广安', '贵港', '甘孜藏族自治州', '广元', '甘南', '杭州', '合肥', '惠州', '哈尔滨', '海口', '呼和浩特', '湖州', '邯郸', '菏泽', '衡水', '淮安', '海外', '衡阳', '黄石', '怀化', '黄冈', '淮南', '淮北', '河源', '鹤壁', '汉中', '黑河', '河池', '呼伦贝尔', '红河', '葫芦岛', '黄山', '哈密', '海东', '贺州', '黄南', '济南', '金华', '嘉兴', '江门', '济宁', '揭阳', '九江', '荆州', '晋中', '焦作', '锦州', '景德镇', '吉林', '佳木斯', '晋城', '吉安', '荆门', '金昌', '酒泉', '济源', '嘉峪关', '昆明', '开封', '喀什', '克拉玛依', '廊坊', '兰州', '洛阳', '临沂', '聊城', '柳州', '连云港', '乐山', '丽水', '六安', '临汾', '泸州', '漯河', '龙岩', '吕梁', '凉山彝族自治州', '丽江', '拉萨', '娄底', '六盘水', '辽阳', '临沧', '辽源', '陵水黎族自治县', '临夏', '林芝', '来宾', '陇南', '绵阳', '眉山', '茂名', '梅州', '马鞍山', '牡丹江', '南京', '宁波', '南昌', '南宁', '南通', '南阳', '宁德', '南充', '内江', '南平', '莆田', '平顶山', '盘锦', '濮阳', '萍乡', '普洱', '攀枝花', '平凉', '青岛', '泉州', '清远', '秦皇岛', '曲靖', '衢州', '齐齐哈尔', '钦州', '庆阳', '琼海', '七台河', '黔南', '黔东南', '黔西南', '日照', '日喀则', '上海', '深圳', '苏州', '沈阳', '石家庄', '汕头', '绍兴', '宿迁', '商丘', '三亚', '上饶', '韶关', '宿州', '十堰', '汕尾', '遂宁', '邵阳', '绥化', '随州', '三门峡', '三明', '松原', '四平', '石嘴山', '朔州', '石河子', '商洛', '山南', '神农架林区', '天津', '太原', '台州', '唐山', '泰州', '泰安', '通辽', '铜仁', '通化', '铜陵', '铁岭', '天水', '台湾', '铜川', '天门', '铁门关', '武汉', '无锡', '温州', '潍坊', '芜湖', '乌鲁木齐', '威海', '梧州', '渭南', '乌兰察布', '武威', '文山', '万宁', '乌海', '文昌', '五家渠', '五指山', '西安', '厦门', '徐州', '新乡', '襄阳', '邢台', '咸阳', '香港', '许昌', '孝感', '西宁', '信阳', '新余', '湘潭', '咸宁', '宣城', '西双版纳', '仙桃', '忻州', '湘西土家族苗族自治州', '兴安盟', '锡林郭勒盟', '烟台', '扬州', '银川', '盐城', '宜宾', '宜昌', '阳江', '玉林', '岳阳', '宜春', '运城', '营口', '榆林', '玉溪', '益阳', '雅安', '云浮', '阳泉', '永州', '鹰潭', '延边', '伊犁', '延安', '伊春', '郑州', '珠海', '中山', '淄博', '株洲', '漳州', '湛江', '肇庆', '镇江', '遵义', '枣庄', '周口', '驻马店', '张家口', '长治', '资阳', '舟山', '张掖', '昭通', '自贡', '张家界', '中卫']\n"
+ ]
+ }
+ ],
+ "source": [
+ "from urllib.request import urlopen\n",
+ "from urllib.request import Request\n",
+ "import jsonpath\n",
+ "import json\n",
+ "\n",
+ "url = 'http://www.lagou.com/lbs/getAllCitySearchLabels.json'\n",
+ "\n",
+ "# 构建 Request请求对象\n",
+ "request = Request(url)\n",
+ "\n",
+ "# 发送请求\n",
+ "response = urlopen(request)\n",
+ "\n",
+ "# 获取数据\n",
+ "html = response.read()\n",
+ "\n",
+ "# json格式字符串 -> python对象\n",
+ "jsonobj = json.loads(html)\n",
+ "\n",
+ "# 从根节点开始，匹配 name节点\n",
+ "citylist = jsonpath.jsonpath(jsonobj, '$..name')\n",
+ "print(citylist)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6ca60acf",
+ "metadata": {},
+ "source": [
+ "### 注意事项\n",
+ "\n",
+ "- json.loads() 是把 Json格式字符串 解码转换成 Python对象，如果在 json.loads 的时候出错，要注意被解码的Json字符的编码。\n",
+ " 如果传入的字符串的编码 不是 UTF-8 的话，需要指定字符编码的 参数 encoding"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a35f0ff5",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"\n",
+ "dataDict = json.loads(jsonStrGBK)\n",
+ " \n",
+ "# dataJsonStr 是JSON字符串，假设其编码本身是非 UTF-8的话而是 GBK 的，那么上述代码会导致出错，改为对应的：\n",
+ "dataDict = json.loads(jsonStrGBK, encoding=\"GBK\");\n",
+ "\n",
+ " \n",
+ "# 如果 dataJsonStr 通过 encoding 指定了合适的编码，\n",
+ "# 但是其中又包含了其他编码的字符，则需要先去将 dataJsonStr 转换为 Unicode，然后再指定编码格式调用json.loads()\n",
+ "dataJsonStrUni = dataJsonStr.decode(\"GB2312\"); \n",
+ "dataDict = json.loads(dataJsonStrUni, encoding=\"GB2312\");\n",
+ "\n",
+ "\"\"\"\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0cb65efe",
+ "metadata": {},
+ "source": [
+ "### 字符串编码转换\n",
+ "\n",
+ "其实编码问题很好搞定，只要记住一点：\n",
+ "\n",
+ "**任何平台的任何编码 都能和 Unicode 互相转换**\n",
+ "\n",
+ "UTF-8 与 GBK 互相转换，那就先把 UTF-8 转换成 Unicode，再从 Unicode 转换成 GBK，反之同理"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 116,
+ "id": "25e3d5c0",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T11:15:15.413326Z",
+ "start_time": "2023-10-24T11:15:15.408580Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "你好地球\n",
+ "b'\\xc4\\xe3\\xba\\xc3\\xb5\\xd8\\xc7\\xf2'\n",
+ "你好地球\n",
+ "b'\\xe4\\xbd\\xa0\\xe5\\xa5\\xbd\\xe5\\x9c\\xb0\\xe7\\x90\\x83'\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 这是一个 UTF-8 编码的字符串\n",
+ "utf8Str = \"你好地球\"\n",
+ "\n",
+ "# 1. 将 UTF-8 编码的字符串 转换成 Unicode 编码\n",
+ "unicodeStr = utf8Str.encode('UTF-8').decode(\"UTF-8\")\n",
+ "print(unicodeStr)\n",
+ "\n",
+ "# 2. 再将 Unicode 编码格式字符串 转换成 GBK 编码\n",
+ "gbkData = unicodeStr.encode(\"GBK\")\n",
+ "print(gbkData)\n",
+ "\n",
+ "# 1. 再将 GBK 编码格式字符串 转化成 Unicode\n",
+ "unicodeStr = gbkData.decode(\"gbk\")\n",
+ "print(unicodeStr)\n",
+ "\n",
+ "# 2. 再将 Unicode 编码格式字符串转换成 UTF-8\n",
+ "utf8Str = unicodeStr.encode(\"UTF-8\")\n",
+ "print(utf8Str)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "86cf233e",
+ "metadata": {},
+ "source": [
+ "## 实战：猫眼电影"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0d95bbff",
+ "metadata": {},
+ "source": [
+ "### 猫眼电影 bs4 单电影"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 126,
+ "id": "95d1c29b",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T11:51:52.335321Z",
+ "start_time": "2023-10-24T11:51:52.299004Z"
+ },
+ "collapsed": true
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/macbook/opt/anaconda3/lib/python3.9/site-packages/bs4/__init__.py:435: MarkupResemblesLocatorWarning: The input looks more like a filename than markup. You may want to open this file and pass the filehandle into Beautiful Soup.\n",
+ " warnings.warn(\n"
+ ]
+ },
+ {
+ "ename": "IndexError",
+ "evalue": "list index out of range",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mIndexError\u001b[0m Traceback (most recent call last)",
+ "Input \u001b[0;32mIn [126]\u001b[0m, in \u001b[0;36m| \u001b[0;34m()\u001b[0m\n\u001b[1;32m 34\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m电影名：\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m 类型：\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtypes\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m 演员：\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mactors\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 37\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;18m__name__\u001b[39m \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__main__\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[0;32m---> 38\u001b[0m \u001b[43mstart\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+ "Input \u001b[0;32mIn [126]\u001b[0m, in \u001b[0;36mstart\u001b[0;34m()\u001b[0m\n\u001b[1;32m 19\u001b[0m soup \u001b[38;5;241m=\u001b[39m BeautifulSoup(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m./html/猫眼电影.html\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mlxml\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 21\u001b[0m \u001b[38;5;66;03m# 获取电影名称\u001b[39;00m\n\u001b[0;32m---> 22\u001b[0m name \u001b[38;5;241m=\u001b[39m \u001b[43msoup\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mselect\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mh1.name\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[1;32m 23\u001b[0m \u001b[38;5;28mprint\u001b[39m(name)\n\u001b[1;32m 25\u001b[0m \u001b[38;5;66;03m# 获取电影类型\u001b[39;00m\n",
+ "\u001b[0;31mIndexError\u001b[0m: list index out of range"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"猫眼电影 bs4 单电影\"\"\"\n",
+ "from random import betavariate\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from bs4 import BeautifulSoup\n",
+ "\n",
+ "\n",
+ "def format_actors(a_list):\n",
+ " actor_set = set()\n",
+ " for a in a_list:\n",
+ " actor_set.add(a.text.strip())\n",
+ " return actor_set\n",
+ "\n",
+ "\n",
+ "def start():\n",
+ "\n",
+ " # URL地址\n",
+ " url = 'https://maoyan.com/films/1299372'\n",
+ " \n",
+ " # 随机生成用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " \n",
+ " # 创建 BeautifulSoup对象\n",
+ " soup = BeautifulSoup(resp.text, 'lxml')\n",
+ "\n",
+ " # 获取 class为name的 h1标签列表 -- 选取符合要求的第一个标签内容\n",
+ " name = soup.select('h1.name')[0].text.strip()\n",
+ " \n",
+ " # 获取 class为ellipsis的 li标签列表 -- 选取符合要求的第一个标签内容\n",
+ " types = soup.select('li.ellipsis')[0].text.strip()\n",
+ " \n",
+ " # 获取 class为ellipsis actor 的 li标签下的 div标签下的 a标签列表\n",
+ " actors_m = soup.select('li.celebrity.actor > div > a')\n",
+ " \n",
+ " # 去重\n",
+ " actors = format_actors(actors_m)\n",
+ " print(f'电影名：{name} 类型：{types} 演员：{actors}')\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a615a2a7",
+ "metadata": {},
+ "source": [
+ "### 猫眼电影 bs4 多电影"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "0751bbeb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"猫眼电影 bs4 多电影\"\"\"\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from bs4 import BeautifulSoup\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def get_list():\n",
+ " num = int(input('请输入要获取多少页数据：'))\n",
+ "\n",
+ " for i in range(num):\n",
+ " url = 'https://maoyan.com/films?showType=3&offset={i*30}'\n",
+ "\n",
+ " # 随机生成 用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " \n",
+ " # 创建 BeautifulSoup对象\n",
+ " soup = BeautifulSoup(resp.text, 'lxml')\n",
+ "\n",
+ " # 选择 div标签下 data-act属性为 movies-click 的 a标签\n",
+ " all_a = soup.select('div > a[data-act=\"movies-click\"]')\n",
+ " \n",
+ " # 获取 a标签的 href属性\n",
+ " return [a.get('href') for a in all_a]\n",
+ "\n",
+ "\n",
+ "def format_actors(a_list):\n",
+ " \"\"\"去重\"\"\"\n",
+ " actor_set = set()\n",
+ " for a in a_list:\n",
+ " actor_set.add(a.text.strip())\n",
+ " return actor_set\n",
+ "\n",
+ "\n",
+ "def start():\n",
+ " \n",
+ " # 获取 a标签的 href属性\n",
+ " all_href = get_list()\n",
+ "\n",
+ " for a in all_href:\n",
+ " sleep(2)\n",
+ " url = f'https://maoyan.com{a}'\n",
+ " \n",
+ " # 随机生成 用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " \n",
+ " # 创建 BeautifulSoup\n",
+ " soup = BeautifulSoup(resp.text, 'lxml')\n",
+ "\n",
+ " # 获取 class为name的 h1标签列表 -- 选取符合要求的第一个标签内容\n",
+ " name = soup.select('h1.name')[0].text.strip()\n",
+ " \n",
+ " # 获取 class为ellipsis的 li标签列表 -- 选取符合要求的第一个标签内容\n",
+ " types = soup.select('li.ellipsis')[0].text.strip()\n",
+ " \n",
+ " # 获取 class为ellipsis actor 的 li标签下的 div标签下的 a标签列表\n",
+ " actors_m = soup.select('li.celebrity.actor > div > a')\n",
+ " \n",
+ " # 去重\n",
+ " actors = format_actors(actors_m)\n",
+ " print(f'电影名：{name} 类型：{types} 演员：{actors}')\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "06e49e37",
+ "metadata": {},
+ "source": [
+ "### 猫眼电影 bs4 优化"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "db6fa1e8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"猫眼电影 bs4 优化\"\"\"\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from bs4 import BeautifulSoup\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def get_html(url):\n",
+ " \n",
+ " # 随机生成 用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " sleep(2)\n",
+ " \n",
+ " # 如果成功访问\n",
+ " if resp.status_code == 200:\n",
+ " \n",
+ " # 进行 UTF-8编码\n",
+ " resp.encoding = 'utf-8'\n",
+ " \n",
+ " # 返回 HTML内容\n",
+ " return resp.text\n",
+ " else:\n",
+ " return None\n",
+ "\n",
+ "\n",
+ "def get_list(html):\n",
+ " \n",
+ " # 创建 BeautifulSoup对象\n",
+ " soup = BeautifulSoup(html, 'lxml')\n",
+ " \n",
+ " # 选择 div标签下的 data-act属性为movies-click的 a标签列表\n",
+ " all_a = soup.select('div > a[data-act=\"movies-click\"]')\n",
+ " \n",
+ " # 获取 a标签的 href属性\n",
+ " return [a.get('href') for a in all_a]\n",
+ "\n",
+ "\n",
+ "def get_index(html):\n",
+ " \n",
+ " # 创建 BeautifulSoup对象\n",
+ " soup = BeautifulSoup(html, 'lxml')\n",
+ " \n",
+ " # 获取 class为name的 h1标签列表 -- 选取符合要求的第一个标签内容\n",
+ " name = soup.select('h1.name')[0].text.strip()\n",
+ " \n",
+ " # 获取 class为ellipsis的 li标签列表 -- 选取符合要求的第一个标签内容\n",
+ " types = soup.select('li.ellipsis')[0].text.strip()\n",
+ " \n",
+ " # 获取 class为ellipsis actor 的 li标签下的 div标签下的 a标签列表\n",
+ " actors_m = soup.select('li.celebrity.actor > div > a')\n",
+ " \n",
+ " # 去重\n",
+ " actors = format_actors(actors_m)\n",
+ " \n",
+ " return f'电影名：{name} 类型：{types} 演员：{actors}'\n",
+ "\n",
+ "\n",
+ "def format_actors(a_list):\n",
+ " \"\"\"去重\"\"\"\n",
+ " actor_set = set()\n",
+ " for a in a_list:\n",
+ " actor_set.add(a.text.strip())\n",
+ " return actor_set\n",
+ "\n",
+ "\n",
+ "def start():\n",
+ " num = int(input('请输入要获取多少页数据：'))\n",
+ " for i in range(num):\n",
+ " url = f'https://maoyan.com/films?showType=3&offset={i*30}'\n",
+ " \n",
+ " # 获取 HTML\n",
+ " html = get_html(url)\n",
+ " \n",
+ " # 获取 href属性\n",
+ " all_href = get_list(html)\n",
+ " \n",
+ " # 遍历\n",
+ " for a in all_href:\n",
+ " url = f'https://maoyan.com{a}'\n",
+ " \n",
+ " # 获取 HTML\n",
+ " index_html = get_html(url)\n",
+ " \n",
+ " # 返回信息\n",
+ " info = get_index(index_html)\n",
+ " print(info)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8af49c12",
+ "metadata": {},
+ "source": [
+ "### 猫眼电影 pyquery获取"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "db60e576",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"猫眼电影 pyquery获取\"\"\"\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from pyquery import PyQuery\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def get_html(url):\n",
+ " \"\"\"获取 HTML内容\"\"\"\n",
+ " \n",
+ " # 随机生成 用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " sleep(2)\n",
+ " \n",
+ " # 如果成功获取 \n",
+ " if resp.status_code == 200:\n",
+ " \n",
+ " # 进行 UTF-8编码\n",
+ " resp.encoding = 'utf-8'\n",
+ " return resp.text\n",
+ " else:\n",
+ " return None\n",
+ "\n",
+ "\n",
+ "def get_list(html):\n",
+ " \"\"\"获取 a标签的 href属性\"\"\"\n",
+ " \n",
+ " # 创建 PyQuery对象\n",
+ " pq = PyQuery(html)\n",
+ " \n",
+ " # 获取 div标签下 data-act属性为 movies-click的 a标签\n",
+ " all_a = pq('div > a[data-act=\"movies-click\"]')\n",
+ " \n",
+ " # 获取 a标签的 href属性\n",
+ " return [a.get('href') for a in all_a]\n",
+ "\n",
+ "\n",
+ "def get_index(html):\n",
+ " \"\"\"获取信息\"\"\"\n",
+ " \n",
+ " # 创建 PyQuery对象\n",
+ " pq = PyQuery(html)\n",
+ " \n",
+ " # 获取 class为name的 h1标签列表 -- 选取符合要求的第一个标签内容\n",
+ " name = pq('h1.name').eq(0).text()\n",
+ " \n",
+ " # 获取 class为ellipsis的 li标签列表 -- 选取符合要求的第一个标签内容\n",
+ " types = pq('li.ellipsis').eq(0).text()\n",
+ " \n",
+ " # 获取 class为ellipsis actor 的 li标签下的 div标签下的 a标签列表\n",
+ " actors_m = pq('li.celebrity.actor > div > a')\n",
+ " \n",
+ " # 去重\n",
+ " actors = format_actors(actors_m)\n",
+ " return f'电影名：{name} 类型：{types} 演员：{actors}'\n",
+ "\n",
+ "\n",
+ "def format_actors(a_list):\n",
+ " \"\"\"去重\"\"\"\n",
+ " actor_set = set()\n",
+ " for a in a_list:\n",
+ " actor_set.add(a.text.strip())\n",
+ " return actor_set\n",
+ "\n",
+ "\n",
+ "def start():\n",
+ " num = int(input('请输入要获取多少页数据：'))\n",
+ " for i in range(num):\n",
+ " url = f'https://maoyan.com/films?showType=3&offset={i*30}'\n",
+ " \n",
+ " # 获取 HTML页面\n",
+ " html = get_html(url)\n",
+ " \n",
+ " # 获取 a标签的 href 属性\n",
+ " all_href = get_list(html)\n",
+ " \n",
+ " # 遍历\n",
+ " for a in all_href:\n",
+ " url = f'https://maoyan.com{a}'\n",
+ " \n",
+ " # 获取 HTML页面\n",
+ " index_html = get_html(url)\n",
+ " \n",
+ " # 获取信息\n",
+ " info = get_index(index_html)\n",
+ " print(info)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e77e4ff4",
+ "metadata": {},
+ "source": [
+ "### 猫眼电影 XPath 获取"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a2970da8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"猫眼电影 XPath 获取\"\"\"\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from lxml import etree\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def get_html(url):\n",
+ " \"\"\"获取 HTML\"\"\"\n",
+ " \n",
+ " # 随机生成 用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " sleep(3)\n",
+ " \n",
+ " # 如果成功获取\n",
+ " if resp.status_code == 200:\n",
+ " \n",
+ " # 进行 UTF-8编码\n",
+ " resp.encoding = 'utf-8'\n",
+ " return resp.text\n",
+ " else:\n",
+ " return None\n",
+ "\n",
+ "\n",
+ "def get_list(html):\n",
+ " \"\"\"获取 href属性的内容\"\"\"\n",
+ " \n",
+ " # 创建 etree对象\n",
+ " e = etree.HTML(html)\n",
+ " \n",
+ " # div标签下的 data-act属性为 movies-click 的 a标签 的 href属性内容\n",
+ " all_a = e.xpath('//div/a[@data-act=\"movies-click\"]/@href')\n",
+ " return all_a\n",
+ "\n",
+ "\n",
+ "def get_index(html):\n",
+ " \"\"\"获取信息\"\"\"\n",
+ " \n",
+ " # 创建 etree对象\n",
+ " e = etree.HTML(html)\n",
+ " \n",
+ " # 获取 class为 name的 h1标签的内容\n",
+ " name = ''.join(e.xpath('//h1[@class=\"name\"]/text()'))\n",
+ " \n",
+ " # 获取 class为 ellipsis的 li标签下的 a标签内容\n",
+ " types = e.xpath('//li[@class=\"ellipsis\"]/a/text()')\n",
+ " \n",
+ " # 获取 class为 celebrity actor 的 li标签下的 div标签下的 a标签内容\n",
+ " actors_m = e.xpath('//li[@class=\"celebrity actor\"]/div/a/text()')\n",
+ " \n",
+ " # 去重\n",
+ " actors = format_actors(actors_m)\n",
+ " \n",
+ " return f'电影名：{name} 类型：{types} 演员：{actors}'\n",
+ "\n",
+ "\n",
+ "def format_actors(a_list):\n",
+ " \"\"\"去重\"\"\"\n",
+ " actor_set = set()\n",
+ " for a in a_list:\n",
+ " actor_set.add(a.strip())\n",
+ " return actor_set\n",
+ "\n",
+ "\n",
+ "def start():\n",
+ " num = int(input('请输入要获取多少页数据：'))\n",
+ " for i in range(num):\n",
+ " url = f'https://maoyan.com/films?showType=3&offset={i*30}'\n",
+ " \n",
+ " # 获取 HTML\n",
+ " html = get_html(url)\n",
+ " \n",
+ " # 获取 a标签下的 href属性\n",
+ " all_href = get_list(html)\n",
+ " \n",
+ " # 遍历\n",
+ " for a in all_href:\n",
+ " url = f'https://maoyan.com{a}'\n",
+ " \n",
+ " # 获取 HTML\n",
+ " index_html = get_html(url)\n",
+ " \n",
+ " # 获取信息\n",
+ " info = get_index(index_html)\n",
+ " \n",
+ " print(info)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "741d6ccf",
+ "metadata": {},
+ "source": [
+ "### 猫眼电影 re 获取"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "1acbe8ce",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"猫眼电影 re 获取\"\"\"\n",
+ "\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "import re\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def get_html(url):\n",
+ " \"\"\"获取 HTML内容\"\"\"\n",
+ " \n",
+ " # 随机生成用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " sleep(5)\n",
+ " \n",
+ " # 如果获取成功\n",
+ " if resp.status_code == 200:\n",
+ " \n",
+ " # 进行 UTF-8编码\n",
+ " resp.encoding = 'utf-8'\n",
+ " return resp.text\n",
+ " else:\n",
+ " return None\n",
+ "\n",
+ "\n",
+ "def get_list(html):\n",
+ " \"\"\"获取 a标签下的 href属性\"\"\"\n",
+ " \n",
+ " all_a = re.findall(\n",
+ " '.+?', html)\n",
+ " return all_a\n",
+ "\n",
+ "\n",
+ "def get_index(html):\n",
+ " \"\"\"获取信息\"\"\"\n",
+ "\n",
+ " # 正则表达式，获取电影名\n",
+ " name = re.findall(' | ', html)\n",
+ " \n",
+ " # 去重\n",
+ " actors = format_actors(actors_m)\n",
+ " \n",
+ " return f'电影名：{name} 类型：{types} 演员：{actors}'\n",
+ "\n",
+ "\n",
+ "def format_actors(a_list):\n",
+ " \"\"\"去重\"\"\"\n",
+ " actor_set = set()\n",
+ " for a in a_list:\n",
+ " actor_set.add(a.strip())\n",
+ " return actor_set\n",
+ "\n",
+ "\n",
+ "def start():\n",
+ " num = int(input('请输入要获取多少页数据：'))\n",
+ " for i in range(num):\n",
+ " url = f'https://maoyan.com/films?showType=3&offset={i*30}'\n",
+ " \n",
+ " # 获取 HTML内容\n",
+ " html = get_html(url)\n",
+ " \n",
+ " # 获取 href属性内容\n",
+ " all_href = get_list(html)\n",
+ " \n",
+ " # 遍历\n",
+ " for a in all_href:\n",
+ " url = f'https://maoyan.com{a}'\n",
+ " \n",
+ " # 获取 HTML\n",
+ " index_html = get_html(url)\n",
+ " \n",
+ " # 获取信息\n",
+ " info = get_index(index_html)\n",
+ " print(info)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " start()\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "e7538bf6",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.12"
+ },
+ "toc": {
+ "base_numbering": 1,
+ "nav_menu": {},
+ "number_sections": true,
+ "sideBar": true,
+ "skip_h1_title": false,
+ "title_cell": "Table of Contents",
+ "title_sidebar": "Contents",
+ "toc_cell": false,
+ "toc_position": {
+ "height": "calc(100% - 180px)",
+ "left": "10px",
+ "top": "150px",
+ "width": "288px"
+ },
+ "toc_section_display": true,
+ "toc_window_display": true
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git "a/02_\351\253\230\347\272\247\347\210\254\350\231\253\344\270\216Selenium.ipynb" "b/02_\351\253\230\347\272\247\347\210\254\350\231\253\344\270\216Selenium.ipynb"
new file mode 100644
index 0000000000000000000000000000000000000000..db0fd536d1e59e56706c7b79c5487e4232e06d52
--- /dev/null
+++ "b/02_\351\253\230\347\272\247\347\210\254\350\231\253\344\270\216Selenium.ipynb"
@@ -0,0 +1,2766 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "23777228",
+ "metadata": {},
+ "source": [
+ "## 多线程爬虫"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "975b85f2",
+ "metadata": {},
+ "source": [
+ "我们之前写的爬虫都是单个线程的，一旦一个地方卡住不动了，那不就永远等待下去了？为此我们可以使用多线程或者多进程来处理"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f781ac03",
+ "metadata": {},
+ "source": [
+ "爬虫使用多线程来处理网络请求，使用线程来处理URL队列中的url，然后将url返回的结果保存在另一个队列中，其它线程在读取这个队列中的数据，然后写到文件中去"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "afac729b",
+ "metadata": {},
+ "source": [
+ "### URL队列和结果队列\n",
+ "将要爬取的 url 放在一个队列中，这里使用标准库Queue。访问url后的结果保存在结果队列中\n",
+ "\n",
+ "初始化一个URL队列："
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "6bab93d1",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T01:53:02.653170Z",
+ "start_time": "2023-10-25T01:53:02.642540Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from queue import Queue\n",
+ "\n",
+ "urls_queue = Queue()\n",
+ "out_queue = Queue()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c27cb7c0",
+ "metadata": {},
+ "source": [
+ "**Queue模块中的常用方法:**\n",
+ "\n",
+ "Python的 Queue模块 中提供了同步的、线程安全的队列类，包括FIFO（先入先出)队列Queue，LIFO（后入先出）队列LifoQueue，和优先级队列PriorityQueue。这些队列都实现了锁原语，能够在多线程中直接使用。可以使用队列来实现线程间的同步\n",
+ "\n",
+ "- Queue.qsize() \n",
+ " - 返回队列的大小\n",
+ "- Queue.empty() \n",
+ " - 如果队列为空，返回True, 反之False\n",
+ "- Queue.full() \n",
+ " - 如果队列满了，返回True, 反之False\n",
+ "- Queue.full \n",
+ " - 与 maxsize 大小对应\n",
+ "- Queue.get([block[, timeout]]) \n",
+ " - 获取队列，timeout等待时间\n",
+ "- Queue.get_nowait() \n",
+ " - 相当 Queue.get(False)\n",
+ "- Queue.put(item) \n",
+ " - 写入队列，timeout等待时间\n",
+ "- Queue.put_nowait(item) \n",
+ " - 相当Queue.put(item, False)\n",
+ "- Queue.task_done() \n",
+ " - 在完成一项工作之后，Queue.task_done()函数向任务已经完成的队列发送一个信号\n",
+ "- Queue.join() \n",
+ " - 实际上意味着等到队列为空，再执行别的操作"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "8837d97b",
+ "metadata": {},
+ "source": [
+ "### 类包装\n",
+ "\n",
+ "使用多个线程，不停的取URL队列中的url，并进行处理："
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "9aae0358",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T02:01:15.814084Z",
+ "start_time": "2023-10-25T02:01:15.805802Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "import threading\n",
+ "\n",
+ "class ThreadCrawl(threading.Thread):\n",
+ " \"\"\"爬取数据的线程\"\"\"\n",
+ " \n",
+ " def __init__(self, queue, out_queue):\n",
+ " \n",
+ " # 线程初始化\n",
+ " threading.Thread.__init__(self)\n",
+ " \n",
+ " # URL队列\n",
+ " self.queue = queue\n",
+ " self.out_queue = out_queue\n",
+ "\n",
+ " def run(self):\n",
+ " \n",
+ " # 取出 URL队列\n",
+ " while True:\n",
+ " item = self.queue.get()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b82f3c50",
+ "metadata": {},
+ "source": [
+ "如果队列为空，线程就会被阻塞，直到队列不为空。处理队列中的一条数据后，就需要通知队列已经处理完该条数据"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "f1b10c9f",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:13:21.193924Z",
+ "start_time": "2023-10-26T00:13:21.181692Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=1&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=3&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=2&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=4&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=6&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=5&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=7&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=8&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=9&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=10&pageSize=50\n"
+ ]
+ }
+ ],
+ "source": [
+ "from threading import Thread\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from time import sleep\n",
+ "from queue import Queue\n",
+ "\n",
+ "\n",
+ "class MyThread(Thread):\n",
+ " def __init__(self):\n",
+ " Thread.__init__(self)\n",
+ "\n",
+ " def run(self):\n",
+ " \"\"\"线程执行的函数\"\"\"\n",
+ " \n",
+ " # 如果队列不为空\n",
+ " while not url_queue.empty():\n",
+ " \n",
+ " # 获取 URL地址\n",
+ " url = url_queue.get()\n",
+ " \n",
+ " # 随机生成用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " \n",
+ " sleep(3)\n",
+ " \n",
+ " if resp.status_code == 200:\n",
+ " print(f'成功获取{url}')\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " \n",
+ " # 创建队列\n",
+ " url_queue = Queue()\n",
+ " \n",
+ " # 为队列添加 URL地址\n",
+ " for i in range(1, 11):\n",
+ " url = f'https://www.hupu.com/home/v1/news?pageNo={i}&pageSize=50'\n",
+ " url_queue.put(url)\n",
+ "\n",
+ " # 启动线程\n",
+ " for i in range(3):\n",
+ " t1 = MyThread()\n",
+ " t1.start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1850d462",
+ "metadata": {},
+ "source": [
+ "### 函数包装"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "34ed2d82",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T02:01:19.768946Z",
+ "start_time": "2023-10-25T02:01:19.765356Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "from threading import Thread\n",
+ "\n",
+ "def func(args):\n",
+ " pass\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " \n",
+ " # URL队列\n",
+ " info_html = Queue()\n",
+ " \n",
+ " # 创建线程\n",
+ " t1 = Thread(target=func, # 线程要执行的函数\n",
+ " args=(info_html,)) # 传入参数"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "442178d0",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:10:08.271999Z",
+ "start_time": "2023-10-26T00:10:08.259663Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=1&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=2&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=3&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=5&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=4&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=6&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=7&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=9&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=8&pageSize=50\n",
+ "成功获取https://www.hupu.com/home/v1/news?pageNo=10&pageSize=50\n"
+ ]
+ }
+ ],
+ "source": [
+ "from threading import Thread\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from time import sleep\n",
+ "from queue import Queue\n",
+ "\n",
+ "\n",
+ "def spider():\n",
+ "\n",
+ " # 如果 URL队列不为空\n",
+ " while not url_queue.empty():\n",
+ "\n",
+ " # 获取 URL地址\n",
+ " url = url_queue.get()\n",
+ " \n",
+ " # 随机生成 用户代理\n",
+ " headers = {'User-Agent': UserAgent().chrome}\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " resp = requests.get(url, headers=headers)\n",
+ " \n",
+ " sleep(3)\n",
+ " \n",
+ " # 如果获取成功，则打印\n",
+ " if resp.status_code == 200:\n",
+ " print(f'成功获取{url}')\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " \n",
+ " # 创建队列\n",
+ " url_queue = Queue()\n",
+ " \n",
+ " # 添加 URL地址\n",
+ " for i in range(1, 11):\n",
+ " url = f'https://www.hupu.com/home/v1/news?pageNo={i}&pageSize=50'\n",
+ " url_queue.put(url)\n",
+ "\n",
+ " # 启动 3个线程\n",
+ " for i in range(3):\n",
+ " t1 = Thread(target=spider)\n",
+ " t1.start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e3e28449",
+ "metadata": {},
+ "source": [
+ "### 线程池"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "d239aafe",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T09:35:58.043706Z",
+ "start_time": "2023-10-25T09:35:57.016973Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0678314259\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "101112131415171819\n",
+ "\n",
+ "\n",
+ "\n",
+ "16\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 简单往队列中传输线程数\n",
+ "import threading\n",
+ "import time\n",
+ "import queue\n",
+ "\n",
+ "\n",
+ "class Threadingpool():\n",
+ " \"\"\"线程池类\"\"\"\n",
+ " \n",
+ " def __init__(self, max_num=10):\n",
+ " \n",
+ " # 创建一个容量为10 的队列\n",
+ " self.queue = queue.Queue(max_num)\n",
+ " \n",
+ " # 为队列添加 10个线程\n",
+ " for i in range(max_num):\n",
+ " self.queue.put(threading.Thread)\n",
+ "\n",
+ " def getthreading(self):\n",
+ " \"\"\"取线程\"\"\"\n",
+ " return self.queue.get()\n",
+ "\n",
+ " def addthreading(self):\n",
+ " \"\"\"添加线程\"\"\"\n",
+ " self.queue.put(threading.Thread)\n",
+ "\n",
+ "\n",
+ "def func(p, i):\n",
+ " \"\"\"线程执行的函数：传入线程池、\"\"\"\n",
+ " time.sleep(1)\n",
+ " print(i)\n",
+ " p.addthreading()\n",
+ "\n",
+ "\n",
+ "if __name__ == \"__main__\":\n",
+ " \n",
+ " # 创建线程池\n",
+ " p = Threadingpool()\n",
+ " \n",
+ " for i in range(20):\n",
+ " # 取线程\n",
+ " thread = p.getthreading()\n",
+ " \n",
+ " # 配置线程\n",
+ " t = thread(target=func, # 要执行的函数\n",
+ " args=(p, i)) # 要传递的参数\n",
+ " \n",
+ " # 开启线程\n",
+ " t.start()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "4d74944d",
+ "metadata": {},
+ "source": [
+ "## 多进程爬虫\n",
+ "multiprocessing 是python的多进程管理包，和 threading.Thread 类似\n",
+ "\n",
+ "### multiprocessing模块\n",
+ "\n",
+ "在multiprocessing中，通过创建Process对象生成进程，然后调用它的 start() 方法"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "e2299a62",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T09:48:59.303621Z",
+ "start_time": "2023-10-25T09:48:59.219784Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Traceback (most recent call last):\n",
+ " File \"\", line 1, in \n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 116, in spawn_main\n",
+ " exitcode = _main(fd, parent_sentinel)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 126, in _main\n",
+ " self = reduction.pickle.load(from_parent)\n",
+ "AttributeError: Can't get attribute 'func1' on \n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"jupyter notebook中，下列代码无法被正常执行，请在Pycharm中尝试\"\"\"\n",
+ "\n",
+ "from multiprocessing import Process\n",
+ "\n",
+ "def func1(name):\n",
+ " \"\"\"进程执行的函数\"\"\"\n",
+ " print('hello', name)\n",
+ "\n",
+ "\n",
+ "if __name__ == \"__main__\":\n",
+ " \n",
+ " # 创建进程\n",
+ " p = Process(target=func1,args=('BIT',))\n",
+ " \n",
+ " # 开启进程\n",
+ " p.start()\n",
+ " \n",
+ " # 等待进程执行完毕\n",
+ " p.join()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "36654bc1",
+ "metadata": {},
+ "source": [
+ "### Manager类\n",
+ "\n",
+ "在使用并发设计的时候最好 避免共享数据，尤其是在使用多进程的时候。 \n",
+ "\n",
+ "如果你真有需要 要共享数据，可以使用由 Manager() 返回的manager提供list, dict, Namespace, Lock, RLock, Semaphore, BoundedSemaphore, Condition, Event, Barrier, Queue, Value and Array类型的支持"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "8bc5cbc0",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T10:05:42.660155Z",
+ "start_time": "2023-10-25T10:05:42.496264Z"
+ },
+ "collapsed": true
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Traceback (most recent call last):\n",
+ " File \"\", line 1, in \n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 116, in spawn_main\n",
+ " exitcode = _main(fd, parent_sentinel)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 126, in _main\n",
+ " self = reduction.pickle.load(from_parent)\n",
+ "AttributeError: Can't get attribute 'put_num' on \n",
+ "Traceback (most recent call last):\n",
+ " File \"\", line 1, in \n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 116, in spawn_main\n",
+ " exitcode = _main(fd, parent_sentinel)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 126, in _main\n",
+ " self = reduction.pickle.load(from_parent)\n",
+ "AttributeError: Can't get attribute 'put_num' on \n",
+ "Traceback (most recent call last):\n",
+ " File \"\", line 1, in \n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 116, in spawn_main\n",
+ " exitcode = _main(fd, parent_sentinel)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/spawn.py\", line 126, in _main\n",
+ " self = reduction.pickle.load(from_parent)\n",
+ "AttributeError: Can't get attribute 'get_num' on \n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"jupyter notebook中，下列代码无法被正常执行，请在Pycharm中尝试\"\"\"\n",
+ "\n",
+ "from multiprocessing import Process, Manager, Lock\n",
+ "\n",
+ "\n",
+ "def put_num(info_queue, l, lo):\n",
+ " \"\"\"添加数字\"\"\"\n",
+ " \n",
+ " # 获得锁\n",
+ " with lo:\n",
+ " \n",
+ " # 向队列添加数字\n",
+ " for n in l:\n",
+ " info_queue.put(n)\n",
+ "\n",
+ "\n",
+ "def get_num(info_queue, lo):\n",
+ " \"\"\"取出数字\"\"\"\n",
+ " \n",
+ " # 获取锁\n",
+ " with lo:\n",
+ " \n",
+ " # 如果队列不为空，则取出数字\n",
+ " while not info_queue.empty():\n",
+ " print(info_queue.get())\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " \n",
+ " # 创建 Manager对象\n",
+ " manager = Manager()\n",
+ " \n",
+ " # 创建 Queue队列\n",
+ " into_html = manager.Queue()\n",
+ " \n",
+ " # 锁对象\n",
+ " lock = Lock()\n",
+ " a = [1, 2, 3, 4, 5]\n",
+ " b = [11, 12, 13, 14, 15]\n",
+ "\n",
+ " # 开启第一个进程\n",
+ " p1 = Process(target=put_num, args=(into_html, a, lock))\n",
+ " p1.start()\n",
+ " \n",
+ " # 开启第二个进程\n",
+ " p2 = Process(target=put_num, args=(into_html, b, lock))\n",
+ " p2.start()\n",
+ " \n",
+ " # 开启第三个进程\n",
+ " p3 = Process(target=get_num, args=(into_html, lock))\n",
+ " p3.start()\n",
+ " \n",
+ " # 等待 3个进程完成\n",
+ " p1.join()\n",
+ " p2.join()\n",
+ " p3.join()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2503fdf6",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"jupyter notebook中，下列代码无法被正常执行，请在Pycharm中尝试\"\"\"\n",
+ "from multiprocessing import Process\n",
+ "from multiprocessing import Manager\n",
+ "import time\n",
+ "from fake_useragent import UserAgent\n",
+ "import requests\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def spider(url_queue):\n",
+ " \n",
+ " # 如果 队列不为空\n",
+ " while not url_queue.empty():\n",
+ " try:\n",
+ " # 获取 URL地址\n",
+ " url = url_queue.get(timeout = 1)\n",
+ " \n",
+ " print(f'成功获取{url}')\n",
+ " \n",
+ " sleep(1)\n",
+ " \n",
+ " except Exception as e:\n",
+ " print(e)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " \n",
+ " # 创建队列\n",
+ " url_queue = Manager().Queue()\n",
+ " \n",
+ " # 添加 URL地址\n",
+ " for i in range(1,11):\n",
+ " url = f'https://www.hupu.com/home/v1/news?pageNo={i}&pageSize=50'\n",
+ " url_queue.put(url)\n",
+ " \n",
+ " # 存储进程信息\n",
+ " all_process = []\n",
+ " \n",
+ " # 开启进程\n",
+ " for i in range(3):\n",
+ " p1 = Process(target=spider,args=(url_queue,))\n",
+ " p1.start()\n",
+ " all_process.append(p1)\n",
+ " \n",
+ " # 等待所有进程结束，主进程再结束\n",
+ " [p.join() for p in all_process] "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b490eb8d",
+ "metadata": {},
+ "source": [
+ "### 进程池的使用\n",
+ "\n",
+ "- 进程池内部维护一个进程序列，当使用时，则去进程池中获取一个进程，如果进程池序列中没有可供使用的进程，那么程序就会等待，直到进程池中有可用进程为止。\n",
+ "\n",
+ "- 进程池中有两个方法：\n",
+ " - apply 同步执行 - 串行\n",
+ " - apply_async 异步执行 - 并行"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "d9261365",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T10:23:00.150817Z",
+ "start_time": "2023-10-25T10:22:47.710399Z"
+ },
+ "collapsed": true
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "Process SpawnPoolWorker-2:\n",
+ "Process SpawnPoolWorker-4:\n",
+ "Process SpawnPoolWorker-3:\n",
+ "Traceback (most recent call last):\n",
+ "Traceback (most recent call last):\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 315, in _bootstrap\n",
+ " self.run()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 108, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/pool.py\", line 114, in worker\n",
+ " task = get()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/queues.py\", line 368, in get\n",
+ " return _ForkingPickler.loads(res)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 315, in _bootstrap\n",
+ " self.run()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 108, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ "AttributeError: Can't get attribute 'get_num' on \n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/pool.py\", line 114, in worker\n",
+ " task = get()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/queues.py\", line 368, in get\n",
+ " return _ForkingPickler.loads(res)\n",
+ "Traceback (most recent call last):\n",
+ "AttributeError: Can't get attribute 'put_num' on \n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 315, in _bootstrap\n",
+ " self.run()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 108, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/pool.py\", line 114, in worker\n",
+ " task = get()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/queues.py\", line 368, in get\n",
+ " return _ForkingPickler.loads(res)\n",
+ "AttributeError: Can't get attribute 'put_num' on \n",
+ "Process SpawnPoolWorker-6:\n",
+ "Process SpawnPoolWorker-5:\n",
+ "Process SpawnPoolWorker-7:\n",
+ "Traceback (most recent call last):\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 315, in _bootstrap\n",
+ " self.run()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 108, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/pool.py\", line 114, in worker\n",
+ " task = get()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/queues.py\", line 365, in get\n",
+ " with self._rlock:\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/synchronize.py\", line 95, in __enter__\n",
+ " return self._semlock.__enter__()\n",
+ "Traceback (most recent call last):\n",
+ "KeyboardInterrupt\n",
+ "Traceback (most recent call last):\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 315, in _bootstrap\n",
+ " self.run()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 108, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/pool.py\", line 114, in worker\n",
+ " task = get()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/queues.py\", line 366, in get\n",
+ " res = self._reader.recv_bytes()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/connection.py\", line 221, in recv_bytes\n",
+ " buf = self._recv_bytes(maxlength)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/connection.py\", line 419, in _recv_bytes\n",
+ " buf = self._recv(4)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/connection.py\", line 384, in _recv\n",
+ " chunk = read(handle, remaining)\n",
+ "KeyboardInterrupt\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 315, in _bootstrap\n",
+ " self.run()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/process.py\", line 108, in run\n",
+ " self._target(*self._args, **self._kwargs)\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/pool.py\", line 114, in worker\n",
+ " task = get()\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/queues.py\", line 365, in get\n",
+ " with self._rlock:\n",
+ " File \"/Users/macbook/opt/anaconda3/lib/python3.9/multiprocessing/synchronize.py\", line 95, in __enter__\n",
+ " return self._semlock.__enter__()\n",
+ "KeyboardInterrupt\n"
+ ]
+ },
+ {
+ "ename": "KeyboardInterrupt",
+ "evalue": "",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
+ "Input \u001b[0;32mIn [2]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 34\u001b[0m pool\u001b[38;5;241m.\u001b[39mclose()\n\u001b[1;32m 36\u001b[0m \u001b[38;5;66;03m# 进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭\u001b[39;00m\n\u001b[0;32m---> 37\u001b[0m \u001b[43mpool\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/multiprocessing/pool.py:662\u001b[0m, in \u001b[0;36mPool.join\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 660\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_state \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m (CLOSE, TERMINATE):\n\u001b[1;32m 661\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIn unknown state\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m--> 662\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_worker_handler\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 663\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_task_handler\u001b[38;5;241m.\u001b[39mjoin()\n\u001b[1;32m 664\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_result_handler\u001b[38;5;241m.\u001b[39mjoin()\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/threading.py:1053\u001b[0m, in \u001b[0;36mThread.join\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 1050\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot join current thread\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 1052\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m timeout \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 1053\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_wait_for_tstate_lock\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1054\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1055\u001b[0m \u001b[38;5;66;03m# the behavior of a negative timeout isn't documented, but\u001b[39;00m\n\u001b[1;32m 1056\u001b[0m \u001b[38;5;66;03m# historically .join(timeout=x) for x<0 has acted as if timeout=0\u001b[39;00m\n\u001b[1;32m 1057\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_wait_for_tstate_lock(timeout\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mmax\u001b[39m(timeout, \u001b[38;5;241m0\u001b[39m))\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/threading.py:1073\u001b[0m, in \u001b[0;36mThread._wait_for_tstate_lock\u001b[0;34m(self, block, timeout)\u001b[0m\n\u001b[1;32m 1070\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m 1072\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1073\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[43mlock\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43macquire\u001b[49m\u001b[43m(\u001b[49m\u001b[43mblock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtimeout\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 1074\u001b[0m lock\u001b[38;5;241m.\u001b[39mrelease()\n\u001b[1;32m 1075\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_stop()\n",
+ "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"jupyter notebook中，下列代码无法被正常执行，请在Pycharm中尝试\"\"\"\n",
+ "\n",
+ "from multiprocessing import Pool, Manager\n",
+ "\n",
+ "\n",
+ "def put_num(info_queue, l):\n",
+ " \"\"\"添加数字\"\"\"\n",
+ " for n in l:\n",
+ " info_queue.put(n)\n",
+ "\n",
+ "\n",
+ "def get_num(info_queue):\n",
+ " \"\"\"获取数字\"\"\"\n",
+ " \n",
+ " # 当队列不为空时，获取数字\n",
+ " while not info_queue.empty():\n",
+ " print(info_queue.get())\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ "\n",
+ " # 创建 Queue队列\n",
+ " html_queue = Manager().Queue()\n",
+ " a = [11, 12, 13, 14, 15]\n",
+ " b = [1, 2, 3, 4, 5]\n",
+ "\n",
+ " # 创建容量为3 的进程池\n",
+ " pool = Pool(3)\n",
+ "\n",
+ " # 异步执行\n",
+ " pool.apply_async(func=put_num, args=(html_queue, a))\n",
+ " pool.apply_async(func=put_num, args=(html_queue, b))\n",
+ " pool.apply_async(func=get_num, args=(html_queue,))\n",
+ "\n",
+ " # 这里join一定是在close之后，且必须要加join，否则主进程不等待创建的子进程执行完毕\n",
+ " pool.close()\n",
+ "\n",
+ " # 进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭\n",
+ " pool.join()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "5b6faf7c",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "\"\"\"jupyter notebook中，下列代码无法被正常执行，请在Pycharm中尝试\"\"\"\n",
+ "\n",
+ "from multiprocessing import Pool, Manager\n",
+ "from time import sleep\n",
+ "\n",
+ "\n",
+ "def spider(url_queue):\n",
+ " \n",
+ " # 如果 URL队列不为空\n",
+ " while not url_queue.empty():\n",
+ " try:\n",
+ " \n",
+ " # 获取 URL\n",
+ " url = url_queue.get(timeout=1)\n",
+ " \n",
+ " print(f'成功获取{url}')\n",
+ " \n",
+ " sleep(1)\n",
+ " \n",
+ " except Exception as e:\n",
+ " print(e)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ "\n",
+ " # 创建 队列\n",
+ " url_queue = Manager().Queue()\n",
+ "\n",
+ " # 为队列 添加 URL地址\n",
+ " for i in range(1, 11):\n",
+ " url = f'https://www.hupu.com/home/v1/news?pageNo={i}&pageSize=50'\n",
+ " url_queue.put(url)\n",
+ "\n",
+ " # 创建 容量为3的进程池\n",
+ " pool = Pool(3)\n",
+ "\n",
+ " # 异步执行\n",
+ " pool.apply_async(func=spider, args=(url_queue,))\n",
+ " pool.apply_async(func=spider, args=(url_queue,))\n",
+ " pool.apply_async(func=spider, args=(url_queue,))\n",
+ " \n",
+ " # 关闭进程池\n",
+ " pool.close()\n",
+ " \n",
+ " # 等待子进程结束，主进程才结束\n",
+ " pool.join()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "db345218",
+ "metadata": {},
+ "source": [
+ "## 多协程爬虫"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a82ee42e",
+ "metadata": {},
+ "source": [
+ "### 示例"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "69c0c319",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-25T10:22:25.388668Z",
+ "start_time": "2023-10-25T10:22:24.951333Z"
+ },
+ "collapsed": true
+ },
+ "outputs": [
+ {
+ "ename": "RuntimeError",
+ "evalue": "This event loop is already running",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
+ "Input \u001b[0;32mIn [1]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 21\u001b[0m loop \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mget_event_loop()\n\u001b[1;32m 23\u001b[0m \u001b[38;5;66;03m# 执行 main函数\u001b[39;00m\n\u001b[0;32m---> 24\u001b[0m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmain\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/asyncio/base_events.py:623\u001b[0m, in \u001b[0;36mBaseEventLoop.run_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 612\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Run until the Future is done.\u001b[39;00m\n\u001b[1;32m 613\u001b[0m \n\u001b[1;32m 614\u001b[0m \u001b[38;5;124;03mIf the argument is a coroutine, it is wrapped in a Task.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 620\u001b[0m \u001b[38;5;124;03mReturn the Future's result, or raise its exception.\u001b[39;00m\n\u001b[1;32m 621\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 622\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_closed()\n\u001b[0;32m--> 623\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_running\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 625\u001b[0m new_task \u001b[38;5;241m=\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m futures\u001b[38;5;241m.\u001b[39misfuture(future)\n\u001b[1;32m 626\u001b[0m future \u001b[38;5;241m=\u001b[39m tasks\u001b[38;5;241m.\u001b[39mensure_future(future, loop\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m)\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/asyncio/base_events.py:583\u001b[0m, in \u001b[0;36mBaseEventLoop._check_running\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 581\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_check_running\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 582\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_running():\n\u001b[0;32m--> 583\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThis event loop is already running\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 584\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m events\u001b[38;5;241m.\u001b[39m_get_running_loop() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 585\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 586\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCannot run the event loop while another loop is running\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
+ "\u001b[0;31mRuntimeError\u001b[0m: This event loop is already running"
+ ]
+ }
+ ],
+ "source": [
+ "import aiohttp\n",
+ "import asyncio\n",
+ "\n",
+ "async def main():\n",
+ " \n",
+ " # 对网址发送 GET请求\n",
+ " async with aiohttp.ClientSession() as session:\n",
+ " async with session.get('http://python.org') as response:\n",
+ " \n",
+ " # 打印 响应码\n",
+ " print(\"Status:\", response.status)\n",
+ " \n",
+ " # 打印 获取的数据类型\n",
+ " print(\"Content-type:\", response.headers['content-type'])\n",
+ "\n",
+ " # 获取内容\n",
+ " html = await response.text()\n",
+ " print(\"Body:\", html[:15], \"...\")\n",
+ "\n",
+ "# 创建 协程\n",
+ "loop = asyncio.get_event_loop()\n",
+ "\n",
+ "# 执行 main函数\n",
+ "loop.run_until_complete(main())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "effccca2",
+ "metadata": {},
+ "source": [
+ "### clientSession的使用"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "affbdf5e",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:04:43.295619Z",
+ "start_time": "2023-10-26T00:04:42.477263Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "\"\"\"header设置\"\"\"\n",
+ "import aiohttp\n",
+ "import asyncio\n",
+ "\n",
+ "# 设置请求头\n",
+ "headers = {\"Authorization\": \"Basic bG9naW46cGFzcw==\"}\n",
+ "\n",
+ "# 发送 GET请求\n",
+ "async with aiohttp.ClientSession(headers=headers) as session:\n",
+ " async with session.get(\"http://httpbin.org/headers\") as r:\n",
+ " \n",
+ " # 转成 Json格式\n",
+ " json_body = await r.json()\n",
+ " \n",
+ " # 设置\n",
+ " assert json_body['headers']['Authorization'] == 'Basic bG9naW46cGFzcw=='"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "3589b7dc",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:04:46.654372Z",
+ "start_time": "2023-10-26T00:04:46.069363Z"
+ }
+ },
+ "outputs": [],
+ "source": [
+ "\"\"\"Cookie的使用\"\"\"\n",
+ "\n",
+ "url = 'http://httpbin.org/cookies'\n",
+ "cookies = {'cookies_are': 'working'}\n",
+ "\n",
+ "# 设置 cookies，发送 GET请求\n",
+ "async with aiohttp.ClientSession(cookies=cookies) as session:\n",
+ " async with session.get(url) as resp:\n",
+ " assert await resp.json() == {\"cookies\": {\"cookies_are\": \"working\"}}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "a8b43aa4",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:04:49.444359Z",
+ "start_time": "2023-10-26T00:04:48.799486Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "400\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"Proxy的使用\"\"\"\n",
+ "\n",
+ "# 发送 GET请求，设置代理\n",
+ "async with aiohttp.ClientSession() as session:\n",
+ " async with session.get(\"http://python.org\", proxy=\"http://proxy.com\") as resp:\n",
+ " \n",
+ " # 获取状态\n",
+ " print(resp.status)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2f39bdee",
+ "metadata": {},
+ "source": [
+ "**Response的使用**\n",
+ "\n",
+ "- 属性\n",
+ " - status 状态码\n",
+ " - url url地址\n",
+ " - cookies cookie内容\n",
+ " - headers 响应头\n",
+ " \n",
+ "- 方法\n",
+ " - read() 读bytes类型\n",
+ " - text() 读文本内容"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "2bcda6dd",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:28:26.494061Z",
+ "start_time": "2023-10-26T00:28:26.434772Z"
+ },
+ "collapsed": true
+ },
+ "outputs": [
+ {
+ "ename": "RuntimeError",
+ "evalue": "This event loop is already running",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+ "\u001b[0;31mRuntimeError\u001b[0m Traceback (most recent call last)",
+ "Input \u001b[0;32mIn [11]\u001b[0m, in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 61\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;18m__name__\u001b[39m \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m__main__\u001b[39m\u001b[38;5;124m'\u001b[39m:\n\u001b[1;32m 62\u001b[0m \n\u001b[1;32m 63\u001b[0m \u001b[38;5;66;03m# 启动协程\u001b[39;00m\n\u001b[1;32m 64\u001b[0m loop \u001b[38;5;241m=\u001b[39m asyncio\u001b[38;5;241m.\u001b[39mget_event_loop()\n\u001b[0;32m---> 65\u001b[0m \u001b[43mloop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_until_complete\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtest_cookie\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/asyncio/base_events.py:623\u001b[0m, in \u001b[0;36mBaseEventLoop.run_until_complete\u001b[0;34m(self, future)\u001b[0m\n\u001b[1;32m 612\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Run until the Future is done.\u001b[39;00m\n\u001b[1;32m 613\u001b[0m \n\u001b[1;32m 614\u001b[0m \u001b[38;5;124;03mIf the argument is a coroutine, it is wrapped in a Task.\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 620\u001b[0m \u001b[38;5;124;03mReturn the Future's result, or raise its exception.\u001b[39;00m\n\u001b[1;32m 621\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 622\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_closed()\n\u001b[0;32m--> 623\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_running\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 625\u001b[0m new_task \u001b[38;5;241m=\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m futures\u001b[38;5;241m.\u001b[39misfuture(future)\n\u001b[1;32m 626\u001b[0m future \u001b[38;5;241m=\u001b[39m tasks\u001b[38;5;241m.\u001b[39mensure_future(future, loop\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m)\n",
+ "File \u001b[0;32m~/opt/anaconda3/lib/python3.9/asyncio/base_events.py:583\u001b[0m, in \u001b[0;36mBaseEventLoop._check_running\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 581\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_check_running\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 582\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mis_running():\n\u001b[0;32m--> 583\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThis event loop is already running\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 584\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m events\u001b[38;5;241m.\u001b[39m_get_running_loop() \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 585\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\n\u001b[1;32m 586\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCannot run the event loop while another loop is running\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
+ "\u001b[0;31mRuntimeError\u001b[0m: This event loop is already running"
+ ]
+ }
+ ],
+ "source": [
+ "import aiohttp\n",
+ "import asyncio\n",
+ "\n",
+ "\n",
+ "async def first():\n",
+ " \n",
+ " # 发送 GET请求\n",
+ " async with aiohttp.ClientSession() as session: # aiohttp.ClientSession() == import requests 模块\n",
+ " async with session.get('http://httpbin.org/get') as resp:\n",
+ " \n",
+ " # 获取内容\n",
+ " rs = await resp.text()\n",
+ " print(rs[:100])\n",
+ "\n",
+ "headers = {'User-Agent': 'aaaaaa123'}\n",
+ "\n",
+ "async def test_header():\n",
+ " \n",
+ " # 设置请求头，发送 GET请求\n",
+ " async with aiohttp.ClientSession(headers=headers) as session:\n",
+ " async with session.get('http://httpbin.org/get') as resp:\n",
+ " \n",
+ " # 获取内容\n",
+ " rs = await resp.text()\n",
+ " print(rs[:100])\n",
+ "\n",
+ "\n",
+ "async def test_params():\n",
+ " \n",
+ " # 设置请求头，发送带参数的 GET请求\n",
+ " async with aiohttp.ClientSession(headers=headers) as session:\n",
+ " async with session.get('http://httpbin.org/get', params={'name': 'bjsxt'}) as resp:\n",
+ " \n",
+ " # 获取内容\n",
+ " rs = await resp.text()\n",
+ " print(rs[:100])\n",
+ "\n",
+ "\n",
+ "async def test_cookie():\n",
+ " \n",
+ " # 设置请求头，添加 cookies，发送带参数的 GET请求\n",
+ " async with aiohttp.ClientSession(headers=headers, cookies={'token': 'sxt123id'}) as session:\n",
+ " async with session.get('http://httpbin.org/get', params={'name': 'bjsxt'}) as resp:\n",
+ " \n",
+ " # 获取内容\n",
+ " rs = await resp.text()\n",
+ " print(rs[:100])\n",
+ "\n",
+ "\n",
+ "async def test_proxy():\n",
+ " \n",
+ " # 设置请求头，添加 cookies与代理，发送带参数的 GET请求\n",
+ " async with aiohttp.ClientSession(headers=headers, cookies={'token': 'sxt123id'}) as session:\n",
+ " async with session.get('http://httpbin.org/get', params={'name': 'bjsxt'}, proxy='http://name:pwd@ip:port') as resp:\n",
+ " \n",
+ " # 获取内容\n",
+ " rs = await resp.text()\n",
+ " print(rs)\n",
+ "\n",
+ "\n",
+ "if __name__ == '__main__':\n",
+ " \n",
+ " # 启动协程\n",
+ " loop = asyncio.get_event_loop()\n",
+ " loop.run_until_complete(test_cookie())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e0c18202",
+ "metadata": {},
+ "source": [
+ "## Selenium初步使用"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "4d09b0cc",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-26T00:53:20.927547Z",
+ "start_time": "2023-10-26T00:53:17.865837Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "
+
diff --git a/gaode.html b/gaode.html
new file mode 100644
index 0000000000000000000000000000000000000000..732f29c1d3f3c6c89b81b4f6558d690db3f2eba5
--- /dev/null
+++ b/gaode.html
@@ -0,0 +1,296 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 高德地图
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ Document
+
+
+
+ frame
+
+
+
+
+
+
+ inner
+
+
+ Level Locate
+
+
+
+
+jQuery UI Draggable - Auto-scroll
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/html/test01.html b/html/test01.html
new file mode 100644
index 0000000000000000000000000000000000000000..8b3f426fd512cc662aa65c989cb80ec9410e8cf9
--- /dev/null
+++ b/html/test01.html
@@ -0,0 +1,39 @@
+
+
+
+ Level Locate
+
+
+
+
+ 猫眼电影PC端
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 高德地图
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ | | |
Welcome to BIT
, ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(soup.find_all('div'))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "cb1f0641",
+ "metadata": {},
+ "source": [
+ "#### 正则表达式过滤器\n",
+ "\n",
+ "如果传入正则表达式作为参数, Beautiful Soup 会通过正则表达式的 match() 来匹配内容"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 56,
+ "id": "25d17812",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:19:40.283579Z",
+ "start_time": "2023-10-24T02:19:40.277763Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[Welcome to BIT
, ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 返回所有的 div标签\n",
+ "print (soup.find_all(re.compile(\"^div\")))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "2f1187bc",
+ "metadata": {},
+ "source": [
+ "#### 列表\n",
+ "\n",
+ "> 如果传入列表参数, Beautiful Soup 会将与列表中任一元素匹配的内容返回"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 57,
+ "id": "c752c102",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:20:51.774346Z",
+ "start_time": "2023-10-24T02:20:51.770836Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[Good Good Study, ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 返回所有匹配到的span a标签\n",
+ "print(soup.find_all(['span', 'a']))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3e833676",
+ "metadata": {},
+ "source": [
+ "#### keyword\n",
+ "\n",
+ "> 如果一个指定名字的参数不是搜索内置的参数名, 搜索时会把该参数当作指定名字tag的属性来搜索"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 59,
+ "id": "abb19104",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:27:01.494476Z",
+ "start_time": "2023-10-24T02:27:01.489045Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[Welcome to BIT
, ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 返回 class为 info 的标签\n",
+ "print(soup.find_all(class_='info'))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "17283da0",
+ "metadata": {},
+ "source": [
+ "#### 按属性的搜索"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 61,
+ "id": "01ea8f6e",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:27:08.096466Z",
+ "start_time": "2023-10-24T02:27:08.088797Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[]\n",
+ "[Welcome to BIT
]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 返回 float为 right 的标签\n",
+ "print(soup.find_all(attrs={'float': 'right'}))\n",
+ "\n",
+ "# 返回 div标签，要求其 float属性为 left\n",
+ "print(soup.find_all('div', attrs={'float': 'left'}))\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "1f560ce8",
+ "metadata": {},
+ "source": [
+ "#### CSS选择器"
+ ]
+ },
+ {
+ "attachments": {
+ "%E6%88%AA%E5%B1%8F2023-10-24%2010.27.45.png": {
+ "image/png": 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"
+ }
+ },
+ "cell_type": "markdown",
+ "id": "7f05c0a2",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 64,
+ "id": "e93ce64f",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:31:38.829129Z",
+ "start_time": "2023-10-24T02:31:38.821257Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[Welcome to BIT
, ]\n",
+ "\n",
+ "[Welcome to BIT
, ]\n",
+ "\n",
+ "[Good Good Study]\n",
+ "\n",
+ "[]\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 选择 div标签\n",
+ "print(soup.select('div'), end='\\n\\n')\n",
+ "\n",
+ "# 选择 id为 title的标签\n",
+ "print(soup.select('#title'), end='\\n\\n')\n",
+ "\n",
+ "# 选择 class为 info的标签\n",
+ "print(soup.select('.info'), end='\\n\\n')\n",
+ "\n",
+ "# 选取 div标签下的 span标签\n",
+ "print(soup.select('div > span'), end='\\n\\n')\n",
+ "\n",
+ "# 选择 class为 info的 div标签下的 a标签\n",
+ "print(soup.select('div.info > a'), end='\\n\\n')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "25de8881",
+ "metadata": {},
+ "source": [
+ "## 数据提取_pyquery\n",
+ "[官网](https://pythonhosted.org/pyquery/)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "3dbec2ed",
+ "metadata": {},
+ "source": [
+ "### 初始化方式"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 68,
+ "id": "5f4d170f",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:46:38.173608Z",
+ "start_time": "2023-10-24T02:46:38.166830Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Welcome to BIT
\n",
+ "\n",
+ "\n",
+ "'''\n",
+ "from pyquery import PyQuery as pq\n",
+ "\n",
+ "# 创建 pyquery对象\n",
+ "doc = pq(html)\n",
+ "\n",
+ "# 获取 title标签\n",
+ "print(doc('title'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "id": "06093690",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T02:49:30.192571Z",
+ "start_time": "2023-10-24T02:49:30.119227Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "程序员
\n", + " \n" + ] + } + ], + "source": [ + "\"\"\"\n", + "获取父节点\n", + "- 获取到当前节点后使用 parent 方法\n", + " \n", + "获取兄弟节点\n", + "- 获取到当前节点后使用 siblings 方法\n", + "\"\"\"\n", + " \n", + "from pyquery import PyQuery as pq\n", + "doc = pq(filename='./html/alter.html')\n", + "\n", + "# 获取 id为 main的 子节点内容\n", + "print(doc('#main').children())" + ] + }, + { + "cell_type": "markdown", + "id": "d72263c2", + "metadata": {}, + "source": [ + "### 获取属性" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "id": "2c5466e8", + "metadata": { + "ExecuteTime": { + "end_time": "2023-10-24T04:06:34.571041Z", + "start_time": "2023-10-24T04:06:34.559544Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "北理工\n" + ] + } + ], + "source": [ + "from pyquery import PyQuery as pq\n", + "\n", + "# 创建 PyQuery对象\n", + "doc = pq(filename='./html/alter.html')\n", + "\n", + "# 获取 id为 main的 标签\n", + "a = doc('#main')\n", + "\n", + "# 获取标签的 href属性内容\n", + "print(a.attr('href'))" + ] + }, + { + "cell_type": "markdown", + "id": "2d451e94", + "metadata": {}, + "source": [ + "### 获取内容" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "id": "762d553d", + "metadata": { + "ExecuteTime": { + "end_time": "2023-10-24T04:09:45.275713Z", + "start_time": "2023-10-24T04:09:45.269196Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "程序员
\n", + " \n", + "程序员\n" + ] + } + ], + "source": [ + "\n", + "from pyquery import PyQuery as pq\n", + "\n", + "doc = pq(filename='./html/alter.html')\n", + "\n", + "# 获取 id=main的 标签\n", + "div = doc('#main')\n", + "\n", + "# 获取该标签内的 html内容\n", + "print(div.html())\n", + "\n", + "# 获取该标签内的 文字信息\n", + "print(div.text()) \n" + ] + }, + { + "cell_type": "markdown", + "id": "7d1fef2f", + "metadata": {}, + "source": [ + "### 示例" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "id": "f22c3981", + "metadata": { + "ExecuteTime": { + "end_time": "2023-10-24T03:05:06.727557Z", + "start_time": "2023-10-24T03:05:06.550536Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'hello'" + ] + }, + "execution_count": 76, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from pyquery import PyQuery as pq\n", + "\n", + "# 1.可加载一段 HTML字符串，或一个HTML文件，或是一个url地址，\n", + "d = pq(\"test 1
test 2
\n", + "test 1\n" + ] + } + ], + "source": [ + "# 3.根据 HTML标签来获取元素，\n", + "d = pq('test 1
test 2
test 1
test 2
\n", + "\n", + "# 注意：当获取到的元素不只一个时，html()方法只返回首个元素的相应内容块\n", + "print(d('p').html()) # 返回 test 1" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "cd6a9a4b", + "metadata": { + "ExecuteTime": { + "end_time": "2023-10-24T03:07:10.797591Z", + "start_time": "2023-10-24T03:07:10.792066Z" + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "test 2\n" + ] + } + ], + "source": [ + "# 4.eq(index) —— 根据给定的索引号得到指定元素。接上例，若想得到第二个p标签内的内容，则可以：\n", + "print(d('p').eq(1).html()) # 返回 test 2" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "360c9953", + "metadata": { + "ExecuteTime": { + "end_time": "2023-10-24T03:41:10.487062Z", + "start_time": "2023-10-24T03:41:10.483125Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "test 1
\n" + ] + } + ], + "source": [ + "# 5.filter() —— 根据类名、id名得到指定元素，例：\n", + "\n", + "from pyquery import PyQuery as pq\n", + "# 创建 pyquery对象\n", + "d = pq(\"\"\"test 1
test 3
test 1
test 2
\n", + "test 1
\n" + ] + } + ], + "source": [ + "# 6.find() —— 查找嵌套元素，例：\n", + "d = pq(\"test 1
test 2
test 1
牛逼
\n"
+ ]
+ }
+ ],
+ "source": [
+ "# 10.addClass(value) ——为元素添加类，例：\n",
+ "d = pq('牛逼
')\n",
+ "\n",
+ "# 添加类属性\n",
+ "d.addClass('my_class')\n",
+ "\n",
+ "print(d('.my_class'))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 60,
+ "id": "5fe406dd",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:49:54.970281Z",
+ "start_time": "2023-10-24T03:49:54.964543Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "True"
+ ]
+ },
+ "execution_count": 60,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# 11.hasClass(name) # 返回判断元素是否包含给定的类，例：\n",
+ "d = pq(\"\")\n",
+ "\n",
+ "d.hasClass('my_class') # 返回True"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 62,
+ "id": "539c169a",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T03:51:27.283742Z",
+ "start_time": "2023-10-24T03:51:27.279373Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "hello
world
\n", + "world
\n" + ] + } + ], + "source": [ + "# 12.children(selector=None) ——获取子元素，例：\n", + "d = pq(\"hello
world
\")\n", + "\n", + "# 获取 子元素\n", + "print(d.children())\n", + "\n", + "# 获取 子元素中 id为2 的标签\n", + "print(d.children('#2'))" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "id": "a7bc9d17", + "metadata": { + "ExecuteTime": { + "end_time": "2023-10-24T03:54:13.413094Z", + "start_time": "2023-10-24T03:54:13.408031Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "hello world
hello
world
\n", + "hello
world
\n", + "hello world
hello world
world
hello
world
test 1
\n" + ] + } + ], + "source": [ + "# 15.not_(selector) ——返回不匹配选择器的元素，例：\n", + "d = pq(\"test 1
test 2
\")\n", + "\n", + "# 返回 id不为2的 p标签\n", + "print(d('p').not_('#2')) # 返回[\n",
+ "
\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "from lxml import etree\n",
+ "text = '''\n",
+ "- \n",
+ "
- first item \n", + "
- second item \n", + "
- third item \n", + "
- fourth item \n", + "
- fifth item\n", + "
\n",
+ "
\n",
+ "'''\n",
+ "# 利用etree 初始化 HTML\n",
+ "html = etree.HTML(text)\n",
+ "\n",
+ "# 将 HTML变成字符串\n",
+ "result = etree.tostring(html)\n",
+ "\n",
+ "# 打印，发现 HTML被自动修正 -- 不仅补全了 li 标签，还添加了 body，html 标签\n",
+ "print(result.decode())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 93,
+ "id": "aa3fd673",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:25:12.370440Z",
+ "start_time": "2023-10-24T10:25:12.362346Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "- \n",
+ "
- first item \n", + "
- second item \n", + "
- third item \n", + "
- fourth item \n", + "
- fifth item\n", + "
\n",
+ "
\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "\"\"\"利用 parse 方法来读取文件\"\"\"\n",
+ "from lxml import etree\n",
+ "\n",
+ "# 读取 HTML文件\n",
+ "html = etree.parse('./html/hello.html')\n",
+ "\n",
+ "# 将 HTML变成 string\n",
+ "result = etree.tostring(html, pretty_print=True)\n",
+ "\n",
+ "print(result.decode())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "30439290",
+ "metadata": {},
+ "source": [
+ "### XPath具体使用"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 94,
+ "id": "2f6b9320",
+ "metadata": {
+ "ExecuteTime": {
+ "end_time": "2023-10-24T10:27:30.751904Z",
+ "start_time": "2023-10-24T10:27:30.744667Z"
+ }
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[- \n",
+ "
- first item \n", + "
- second item \n", + "
- third item \n", + "
- fourth item \n", + "
- fifth item \n", + "
(.+?)
', html)[0]\n", + " \n", + " # 获取电影类型\n", + " types = re.findall('- \\s+?
- \\s+?([\\S\\s]+?) ', html)[0]\n", + " types = re.findall('\\s*(.+)\\s*', types)\n", + " \n", + " # 获取演员信息\n", + " actors_m = re.findall(\n", + " '
- \\s*
+
+
+
+
+ 在天安门...周边搜
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 退出全屏
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/html/.DS_Store b/html/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..be1dcde6e33ee12414c506ab2e7b4f53dd0caa18
Binary files /dev/null and b/html/.DS_Store differ
diff --git a/html/alter.html b/html/alter.html
new file mode 100644
index 0000000000000000000000000000000000000000..668b49f8eb3a55b05deb87e415c5b8b8327940ff
--- /dev/null
+++ b/html/alter.html
@@ -0,0 +1,17 @@
+
+
+
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/html/drop_down.html b/html/drop_down.html
new file mode 100644
index 0000000000000000000000000000000000000000..be4c130385040c0995601d6d0415b7e739ce714c
--- /dev/null
+++ b/html/drop_down.html
@@ -0,0 +1,14 @@
+
+
+
+
+
\ No newline at end of file
diff --git a/html/frame.html b/html/frame.html
new file mode 100644
index 0000000000000000000000000000000000000000..3a20c0fae174ef8c98baa42ee0f62403ed5d90ab
--- /dev/null
+++ b/html/frame.html
@@ -0,0 +1,21 @@
+
+
+
+
+
+
+
+
diff --git a/html/hello.html b/html/hello.html
new file mode 100644
index 0000000000000000000000000000000000000000..76292fbdecbdfbf1577190379c3783ff9f7e8483
--- /dev/null
+++ b/html/hello.html
@@ -0,0 +1,9 @@
+
+
+ frame
+ +
+
\ No newline at end of file
diff --git a/html/inner.html b/html/inner.html
new file mode 100644
index 0000000000000000000000000000000000000000..836af237a5b5c6ea8c11f935b6f3faf960a24005
--- /dev/null
+++ b/html/inner.html
@@ -0,0 +1,15 @@
+
+
+
+ -
+
- first item +
- second item +
- third item +
- fourth item +
- fifth item +
+
+
+
diff --git a/html/level_locate.html b/html/level_locate.html
new file mode 100644
index 0000000000000000000000000000000000000000..a8e615b32254c01ccda5e1bd7ead03c66e4c30dc
--- /dev/null
+++ b/html/level_locate.html
@@ -0,0 +1,41 @@
+
+
+
+
+
+ inner
+ + click +Level locate
+
+
+
+
+
+ Link1
+
+
+
+
+
+
+
\ No newline at end of file
diff --git a/html/scroll.html b/html/scroll.html
new file mode 100644
index 0000000000000000000000000000000000000000..741793a62ce7f2fa789971e90c24db473f0ffe99
--- /dev/null
+++ b/html/scroll.html
@@ -0,0 +1,38 @@
+
+
+
+
+
+
+
+
+ Link2
+
+
+ Level locate
+
+
+
+
+
+ Link1
+
+
+
+
+
+
diff --git "a/html/\347\214\253\347\234\274\347\224\265\345\275\261.html" "b/html/\347\214\253\347\234\274\347\224\265\345\275\261.html"
new file mode 100644
index 0000000000000000000000000000000000000000..2f7d60b6e3e0a56f92874bc2c8846e3e670c35c3
--- /dev/null
+++ "b/html/\347\214\253\347\234\274\347\224\265\345\275\261.html"
@@ -0,0 +1,222 @@
+
+
+
+
+
+
+
+
+
+
+ Link2
+
+
+
+
+
+
+
+
+
+ 
+
+
+
+
+
+
+ 加载中...
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/scrap.py b/scrap.py
new file mode 100644
index 0000000000000000000000000000000000000000..a3f0be9e85b5d8fdc831c3b7b53db8c6b368b244
--- /dev/null
+++ b/scrap.py
@@ -0,0 +1,22 @@
+"""quote: 进行URL编码，发送中文请求"""
+
+from urllib.request import urlopen,Request
+from fake_useragent import UserAgent
+from urllib.parse import quote
+
+url = f'https://www.amap.com'
+
+# 随机生成用户代理
+ua = UserAgent()
+headers = {
+ 'User-Agent':ua.chrome
+}
+
+# 创建 request对象
+req = Request(url,headers = headers)
+
+# 发送请求
+resp = urlopen(req)
+
+with open("./gaode.html", 'w') as f:
+ f.write(resp.read().decode())
\ No newline at end of file
diff --git a/scrapy/.DS_Store b/scrapy/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..6df9f8e2c4f947b5490a370caf496170ef7a08f3
Binary files /dev/null and b/scrapy/.DS_Store differ
diff --git a/scrapy/__init__.py b/scrapy/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/__pycache__/__init__.cpython-39.pyc b/scrapy/__pycache__/__init__.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..b157f8cf8797b56de225e5ac9d4000f4c86c1d39
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diff --git a/scrapy/gaode/gaode.html b/scrapy/gaode/gaode.html
new file mode 100644
index 0000000000000000000000000000000000000000..732f29c1d3f3c6c89b81b4f6558d690db3f2eba5
--- /dev/null
+++ b/scrapy/gaode/gaode.html
@@ -0,0 +1,296 @@
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ + 关于猫眼 : + 关于我们 + + 董事会成员 + + 投资者关系 + + 友情链接 : + 美团网 + + 格瓦拉 + + 美团下载 + + 欢喜首映 +
++ 商务合作邮箱：v@maoyan.com + 客服电话：10105335 + 违法和不良信息/涉未成年人有害信息举报电话：4006018900 +
++ 用户举报/涉未成年人有害信息举报邮箱：tousujubao@meituan.com + 舞弊线索举报邮箱：wubijubao@maoyan.com +
++ 中华人民共和国增值电信业务经营许可证 京B2-20190350 + + 营业性演出许可证 京演（机构）（2019）4094号 +
++ 广播电视节目制作经营许可证 （京）字第08478号 + + 网络文化经营许可证 京网文（2022）1334-041号 +
++ 艺术品经营单位备案证明 京东艺（2022）0095号 +
++ 猫眼用户服务协议 + + 猫眼平台交易规则总则 + + 隐私政策 +
++ 京公网安备 + 11010102003232号 + + 京ICP备16022489号-1 +
+北京猫眼文化传媒有限公司
++ © + 猫眼电影 www.maoyan.com
+ +
+ 
+ 
+
+
+
+
+
+ 在天安门...周边搜
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+ 退出全屏
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
diff --git a/scrapy/gaode/gaode/__init__.py b/scrapy/gaode/gaode/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/gaode/gaode/__pycache__/__init__.cpython-311.pyc b/scrapy/gaode/gaode/__pycache__/__init__.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..b1fd81a0dd23f0cd9bca9d06f5e9e4b7b6fa9e1e
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diff --git a/scrapy/gaode/gaode/__pycache__/middlewares.cpython-311.pyc b/scrapy/gaode/gaode/__pycache__/middlewares.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..3c5ddb3e63f0a47de563f7bdae9091f464f5f983
Binary files /dev/null and b/scrapy/gaode/gaode/__pycache__/middlewares.cpython-311.pyc differ
diff --git a/scrapy/gaode/gaode/__pycache__/settings.cpython-311.pyc b/scrapy/gaode/gaode/__pycache__/settings.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..21fa264255bd07444e3e69e8cce5f67b350e7dcf
Binary files /dev/null and b/scrapy/gaode/gaode/__pycache__/settings.cpython-311.pyc differ
diff --git a/scrapy/gaode/gaode/items.py b/scrapy/gaode/gaode/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..a75b7f96cdae842891f22298c8b75e72c885d57c
--- /dev/null
+++ b/scrapy/gaode/gaode/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class GaodeItem(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/gaode/gaode/middlewares.py b/scrapy/gaode/gaode/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..bcc21fed18ae9458729c8c2a353fd3b9a843bc5d
--- /dev/null
+++ b/scrapy/gaode/gaode/middlewares.py
@@ -0,0 +1,117 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+from random import choice
+from gaode.settings import USER_AGENT_LIST
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+
+
+class GaodeSpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info("Spider opened: %s" % spider.name)
+
+
+class GaodeDownloaderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the downloader middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_request(self, request, spider):
+ # Called for each request that goes through the downloader
+ # middleware.
+
+ # Must either:
+ # - return None: continue processing this request
+ # - or return a Response object
+ # - or return a Request object
+ # - or raise IgnoreRequest: process_exception() methods of
+ # installed downloader middleware will be called
+ return None
+
+ def process_response(self, request, response, spider):
+ # Called with the response returned from the downloader.
+
+ # Must either;
+ # - return a Response object
+ # - return a Request object
+ # - or raise IgnoreRequest
+ return response
+
+ def process_exception(self, request, exception, spider):
+ # Called when a download handler or a process_request()
+ # (from other downloader middleware) raises an exception.
+
+ # Must either:
+ # - return None: continue processing this exception
+ # - return a Response object: stops process_exception() chain
+ # - return a Request object: stops process_exception() chain
+ pass
+
+ def spider_opened(self, spider):
+ spider.logger.info("Spider opened: %s" % spider.name)
+
+class MyRandomUserAgentMiddleware:
+
+ def process_request(self, request, spider):
+ UA = choice(USER_AGENT_LIST)
+ request.headers['User-Agent'] = UA
+ # 不要返回任何东西
+
+ def process_response(self, request, response, spider):
+ return response
+
+ def process_exception(self, request, exception, spider):
+ pass
\ No newline at end of file
diff --git a/scrapy/gaode/gaode/pipelines.py b/scrapy/gaode/gaode/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..9bec53948c780a93d4d91ae07d8f5c3e407df36a
--- /dev/null
+++ b/scrapy/gaode/gaode/pipelines.py
@@ -0,0 +1,13 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+
+
+class GaodePipeline:
+ def process_item(self, item, spider):
+ return item
diff --git a/scrapy/gaode/gaode/settings.py b/scrapy/gaode/gaode/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..29e342ac7bfcafafaec2d538dd94c7ed71a77c3e
--- /dev/null
+++ b/scrapy/gaode/gaode/settings.py
@@ -0,0 +1,116 @@
+# Scrapy settings for gaode project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = "gaode"
+
+SPIDER_MODULES = ["gaode.spiders"]
+NEWSPIDER_MODULE = "gaode.spiders"
+LOG_LEVEL = 'WARNING'
+
+# settings里添加
+USER_AGENT_LIST = [
+ 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36',
+ 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2919.83 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2866.71 Safari/537.36',
+ 'Mozilla/5.0 (X11; Ubuntu; Linux i686 on x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2820.59 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2762.73 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2656.18 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/44.0.2403.155 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.1 Safari/537.36',
+ 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2226.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.4; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2224.3 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 10.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/40.0.2214.93 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/37.0.2062.124 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/37.0.2049.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 4.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/37.0.2049.0 Safari/537.36',
+]
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = "gaode (+http://www.yourdomain.com)"
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
+# "Accept-Language": "en",
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# "gaode.middlewares.GaodeSpiderMiddleware": 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+DOWNLOADER_MIDDLEWARES = {
+ "gaode.middlewares.MyRandomUserAgentMiddleware": 543,
+}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# "scrapy.extensions.telnet.TelnetConsole": None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+#ITEM_PIPELINES = {
+# "gaode.pipelines.GaodePipeline": 300,
+#}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = "httpcache"
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = "scrapy.extensions.httpcache.FilesystemCacheStorage"
+
+# Set settings whose default value is deprecated to a future-proof value
+REQUEST_FINGERPRINTER_IMPLEMENTATION = "2.7"
+TWISTED_REACTOR = "twisted.internet.asyncioreactor.AsyncioSelectorReactor"
+FEED_EXPORT_ENCODING = "utf-8"
diff --git a/scrapy/gaode/gaode/spiders/__init__.py b/scrapy/gaode/gaode/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/gaode/gaode/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/gaode/gaode/spiders/__pycache__/__init__.cpython-311.pyc b/scrapy/gaode/gaode/spiders/__pycache__/__init__.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..9f74043edf99b7fab9cb5be188456568ac50a161
Binary files /dev/null and b/scrapy/gaode/gaode/spiders/__pycache__/__init__.cpython-311.pyc differ
diff --git a/scrapy/gaode/gaode/spiders/__pycache__/bit.cpython-311.pyc b/scrapy/gaode/gaode/spiders/__pycache__/bit.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..385d5eac0be7a24edbf5e791b3769bb36bd17788
Binary files /dev/null and b/scrapy/gaode/gaode/spiders/__pycache__/bit.cpython-311.pyc differ
diff --git a/scrapy/gaode/gaode/spiders/bit.py b/scrapy/gaode/gaode/spiders/bit.py
new file mode 100644
index 0000000000000000000000000000000000000000..0c76a4238d7a7c563c351934fcd57742fd0aec81
--- /dev/null
+++ b/scrapy/gaode/gaode/spiders/bit.py
@@ -0,0 +1,11 @@
+import scrapy
+
+
+class BitSpider(scrapy.Spider):
+ name = "bit"
+ allowed_domains = ["amap.com"]
+ start_urls = ["https://www.amap.com/search?query=北京理工大学&city=100000&geoobj=112.063%7C37.029506%7C122.079296%7C41.867776&zoom=6.97"]
+
+ def parse(self, response):
+ with open("./gaode.html", 'w') as f:
+ f.write(response.text)
diff --git a/scrapy/gaode/scrapy.cfg b/scrapy/gaode/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..2a02d50a8428d93505bbd8beab302791e70b2701
--- /dev/null
+++ b/scrapy/gaode/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = gaode.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = gaode
diff --git a/scrapy/scrapy01/data/game.txt b/scrapy/scrapy01/data/game.txt
new file mode 100644
index 0000000000000000000000000000000000000000..2215b45b846aa6a185f64181a19b13fefa6e68c4
--- /dev/null
+++ b/scrapy/scrapy01/data/game.txt
@@ -0,0 +1,207 @@
+三国很忙: 策略类: 2023-10-26
+寻找盛装的男孩: 益智类: 2023-10-26
+指尖投篮: 敏捷篇: 2023-10-26
+地下隧道大逃脱: 益智类: 2023-10-26
+南瓜噩梦: 敏捷篇: 2023-10-26
+救援埃莉诺: 益智类: 2023-10-26
+甲板清洁工: 益智类: 2023-10-26
+方块世界大爆破3: 益智类: 2023-10-26
+营救皇家动物: 益智类: 2023-10-26
+小恐龙逃离: 益智类: 2023-10-26
+救援工作人员: 益智类: 2023-10-26
+方块球球: 益智类: 2023-10-26
+拼接英语单词: 益智类: 2023-10-26
+逃离工地: 益智类: 2023-10-26
+新生的奥秘: 益智类: 2023-10-26
+救助受困的鱼: 射击类: 2023-10-26
+摆动蜘蛛过障碍: 敏捷篇: 2023-10-26
+水疗中心的服务: 益智类: 2023-10-26
+露西四季时尚达人: 装扮类: 2023-10-26
+下水道逃脱: 益智类: 2023-10-26
+从前时光: 益智类: 2023-10-26
+幽灵酒馆: 益智类: 2023-10-26
+美丽蝴蝶大逃脱: 益智类: 2023-10-26
+NBA英雄: 体育类: 2023-10-25
+救援小海豚: 益智类: 2023-10-25
+盒子的秘密: 益智类: 2023-10-25
+拯救笼中白母鸡: 益智类: 2023-10-25
+天空探险队: 益智类: 2023-10-25
+可爱小马逃脱: 益智类: 2023-10-25
+圆球华容道: 益智类: 2023-10-25
+逃离景区河流: 益智类: 2023-10-25
+火柴人出逃记: 益智类: 2023-10-25
+给客人做饭H5: 休闲类: 2023-10-25
+拯救笼中小猪: 益智类: 2023-10-25
+红方块闯迷宫: 益智类: 2023-10-25
+保护我的南瓜: 益智类: 2023-10-25
+救援名人夫妇: 益智类: 2023-10-25
+小黑花花射飞镖H5: 益智类: 2023-10-25
+拯救狞猫: 益智类: 2023-10-25
+寻找心理医生: 益智类: 2023-10-25
+寻找汽车钥匙: 益智类: 2023-10-25
+绵羊过障碍: 敏捷篇: 2023-10-25
+逗小猴开心系列812: 益智类: 2023-10-25
+音乐笔记: 益智类: 2023-10-25
+深渊契约: 冒险类: 2023-10-24
+海岛小分队: 休闲类: 2023-10-24
+村庄洞穴逃脱: 益智类: 2023-10-24
+逃离简易房屋129: 益智类: 2023-10-24
+夏季露营探险: 休闲类: 2023-10-24
+救援草裙姑娘: 益智类: 2023-10-24
+神秘空间站: 益智类: 2023-10-24
+前期准备工作: 益智类: 2023-10-24
+鸟群贪吃蛇: 敏捷篇: 2023-10-24
+花朵壁画屋逃脱: 益智类: 2023-10-24
+信徒: 策略类: 2023-10-24
+逃离沙漠地区: 益智类: 2023-10-24
+玫瑰仙境逃脱: 益智类: 2023-10-24
+逃离薄雾森林: 益智类: 2023-10-24
+双人激战3D: 射击类: 2023-10-24
+救出小马: 益智类: 2023-10-24
+公路赛车挑战: 敏捷篇: 2023-10-24
+宇宙猫生存: 射击类: 2023-10-24
+逃离魔法锅屋: 益智类: 2023-10-24
+拯救孔雀龙: 益智类: 2023-10-24
+红腹灰雀逃脱: 益智类: 2023-10-23
+火柴人升阶战: 益智类: 2023-10-23
+狂野大冒险: 敏捷篇: 2023-10-23
+寻找结婚礼服: 益智类: 2023-10-23
+一笔画出来: 益智类: 2023-10-23
+救援暹罗猫: 益智类: 2023-10-23
+奇妙的化妆术: 装扮类: 2023-10-23
+逗小猴开心系列811: 益智类: 2023-10-23
+纸杯蛋糕的线索: 益智类: 2023-10-23
+目的地之谜: 益智类: 2023-10-23
+找到海港走私者: 益智类: 2023-10-23
+暴打小僵尸: 射击类: 2023-10-23
+山鹿逃出山谷: 益智类: 2023-10-23
+维京人逃生记2: 冒险类: 2023-10-23
+隧道冲击: 敏捷篇: 2023-10-23
+昏暗儿童房逃生130: 益智类: 2023-10-22
+沉没的宝藏2: 益智类: 2023-10-22
+古墓诡影: 益智类: 2023-10-22
+迷路的猫: 益智类: 2023-10-22
+管道冒险: 冒险类: 2023-10-22
+色彩小球转换: 敏捷篇: 2023-10-22
+荒野狩猎: 射击类: 2023-10-22
+绵羊家族逃脱: 益智类: 2023-10-22
+寻找纸袋玩具: 益智类: 2023-10-22
+新坦克对战: 策略类: 2023-10-22
+逃离破落村落: 益智类: 2023-10-22
+修车店的秘密: 益智类: 2023-10-22
+寻找丢失的黄金: 益智类: 2023-10-22
+油条冰淇淋: 休闲类: 2023-10-22
+建造天柱: 敏捷篇: 2023-10-22
+寻找铅笔男孩: 益智类: 2023-10-22
+上帝的祝福: 益智类: 2023-10-22
+红色蘑菇林逃脱: 益智类: 2023-10-22
+魔法大厨: 休闲类: 2023-10-21
+推动选取器: 敏捷篇: 2023-10-21
+疯狂克隆人: 冒险类: 2023-10-21
+爱吃苹果的男孩: 敏捷篇: 2023-10-21
+救援气球女孩: 益智类: 2023-10-21
+机器人翻翻看: 益智类: 2023-10-21
+救援美人鱼模仿者: 益智类: 2023-10-21
+汉字消方块: 益智类: 2023-10-21
+混乱的化学家: 益智类: 2023-10-21
+暗黑系公主婚礼: 装扮类: 2023-10-21
+逃离荒废的营地: 益智类: 2023-10-21
+小猪消消: 益智类: 2023-10-21
+老城区酒吧: 益智类: 2023-10-21
+封印魔法之门: 益智类: 2023-10-21
+寻找美容师: 益智类: 2023-10-21
+挪了个车: 益智类: 2023-10-21
+儿童洗衣房: 装扮类: 2023-10-21
+昏暗儿童房逃生134: 益智类: 2023-10-21
+双人PK挑战: 休闲类: 2023-10-21
+小飞象逃脱: 益智类: 2023-10-20
+寻找滑冰男孩: 益智类: 2023-10-20
+首席医生救援: 益智类: 2023-10-20
+乌鸦森林大逃脱: 益智类: 2023-10-20
+制作甜披萨的楠楠: 装扮类: 2023-10-20
+梦想海岛王: 休闲类: 2023-10-20
+剑镇三界: 冒险类: 2023-10-20
+布置我的别墅: 休闲类: 2023-10-20
+西瓜拼接: 益智类: 2023-10-20
+救援金色鸭子: 益智类: 2023-10-20
+蘑菇兄弟: 冒险类: 2023-10-20
+救援华丽的小姑娘: 益智类: 2023-10-20
+热带麻将: 益智类: 2023-10-20
+烧脑大挑战合集: 益智类: 2023-10-20
+营救男子: 益智类: 2023-10-20
+田野之间: 益智类: 2023-10-20
+闪亮少女换装: 装扮类: 2023-10-20
+救援时尚的蜘蛛侠: 益智类: 2023-10-20
+被诅咒的电影院: 益智类: 2023-10-20
+阳光大花园: 益智类: 2023-10-20
+老六别坑了: 益智类: 2023-10-20
+黑暗的窄屋逃脱: 益智类: 2023-10-20
+逃离简易房屋127: 益智类: 2023-10-20
+僵尸兄弟闯密室3: 益智类: 2023-10-20
+寻找茄子玩具: 益智类: 2023-10-19
+昏暗儿童房逃生129: 益智类: 2023-10-19
+逃离森林的爱情鸟: 益智类: 2023-10-19
+寻找公主雕像: 益智类: 2023-10-19
+英勇营救姑娘: 益智类: 2023-10-19
+逃离迷人的花园: 益智类: 2023-10-19
+快乐男孩亨利逃脱: 益智类: 2023-10-19
+自然森林大逃脱: 益智类: 2023-10-19
+逃离橄榄树园: 益智类: 2023-10-19
+棕色母鸡逃脱: 益智类: 2023-10-19
+营救学生: 益智类: 2023-10-19
+逃离顶尖音乐会: 益智类: 2023-10-19
+救援一对猫: 益智类: 2023-10-19
+救援兽人战士: 益智类: 2023-10-19
+城堡的大秘密: 益智类: 2023-10-19
+时尚女学生穿搭: 装扮类: 2023-10-19
+流浪的星球: 敏捷篇: 2023-10-19
+合并战兵2048: 敏捷篇: 2023-10-19
+鲜花城堡: 益智类: 2023-10-19
+最后一件: 益智类: 2023-10-19
+烧脑大师: 益智类: 2023-10-19
+寻找气球姑娘: 益智类: 2023-10-19
+葫芦娃各显神通: 策略类: 2023-10-18
+停车我最强: 体育类: 2023-10-18
+寻找游戏玩具: 益智类: 2023-10-18
+救援工作人员约翰: 益智类: 2023-10-18
+寻找飞马的翅膀: 益智类: 2023-10-18
+吃火锅H5: 敏捷篇: 2023-10-18
+布鲁姆吉城堡: 射击类: 2023-10-18
+狐狸逃出沙漠: 益智类: 2023-10-18
+开澡堂H5: 模拟经营: 2023-10-18
+营救笼中狮子: 益智类: 2023-10-18
+飞机极限着陆: 体育类: 2023-10-18
+部落男人逃脱: 益智类: 2023-10-18
+营救花栗鼠: 益智类: 2023-10-18
+逃离趣味冒险屋: 益智类: 2023-10-18
+寻找企鹅伙伴: 益智类: 2023-10-18
+机器人修复师: 冒险类: 2023-10-18
+寻找长生不老药水: 益智类: 2023-10-18
+救出小白兔: 益智类: 2023-10-18
+逗小猴开心系列810: 益智类: 2023-10-18
+克服心中恐惧: 益智类: 2023-10-18
+盛开的樱花树: 益智类: 2023-10-18
+逃出诡异之地: 益智类: 2023-10-17
+拯救笼中爱鸟: 益智类: 2023-10-17
+野生袋鼠救援: 益智类: 2023-10-17
+寻找喜爱的裙子: 益智类: 2023-10-17
+西部牛仔大逃脱: 益智类: 2023-10-17
+救援虎猫: 益智类: 2023-10-17
+黄鸟救援: 益智类: 2023-10-17
+抵御怪物入侵: 策略类: 2023-10-17
+寻找狮子王: 益智类: 2023-10-17
+菜鸟小忍者: 休闲类: 2023-10-17
+飞天战机: 射击类: 2023-10-17
+辛巴找水: 益智类: 2023-10-17
+双枪牛仔: 射击类: 2023-10-17
+合成射击: 射击类: 2023-10-17
+校园阴影: 益智类: 2023-10-17
+荒野生存模拟: 冒险类: 2023-10-17
+初秋时尚穿搭: 装扮类: 2023-10-17
+面具进化: 敏捷篇: 2023-10-17
+姑娘的约会夜: 装扮类: 2023-10-17
+蚂蚁逃离: 益智类: 2023-10-17
+小黑花花糖果砸巫婆H5: 射击类: 2023-10-16
+逗小猴开心系列809: 益智类: 2023-10-16
+回响的街道: 益智类: 2023-10-16
+快速改道: 益智类: 2023-10-16
diff --git a/scrapy/scrapy01/scrapy.cfg b/scrapy/scrapy01/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..13130c7cd5019be3edb97a110af47515b201b40e
--- /dev/null
+++ b/scrapy/scrapy01/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy01.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy01
diff --git a/scrapy/scrapy01/scrapy01/__init__.py b/scrapy/scrapy01/scrapy01/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy01/scrapy01/__pycache__/__init__.cpython-39.pyc b/scrapy/scrapy01/scrapy01/__pycache__/__init__.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..3a33b617fb98ea84ff0b0c80f4da9393488dfa1a
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diff --git a/scrapy/scrapy01/scrapy01/__pycache__/items.cpython-39.pyc b/scrapy/scrapy01/scrapy01/__pycache__/items.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..c6ae4e6637aff09c80ec6a841274bb4bf3996f0e
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diff --git a/scrapy/scrapy01/scrapy01/__pycache__/pipelines.cpython-39.pyc b/scrapy/scrapy01/scrapy01/__pycache__/pipelines.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..c49793ea0710b8beaf133f0ae765702204c74dfa
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diff --git a/scrapy/scrapy01/scrapy01/__pycache__/settings.cpython-39.pyc b/scrapy/scrapy01/scrapy01/__pycache__/settings.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..a78435d8408a9270d54800eee81e621b652ca1b8
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diff --git a/scrapy/scrapy01/scrapy01/items.py b/scrapy/scrapy01/scrapy01/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..44165cd515e4b49721fe39393e130fa732ced29e
--- /dev/null
+++ b/scrapy/scrapy01/scrapy01/items.py
@@ -0,0 +1,14 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class GameItem(scrapy.Item):
+ # 定义 Item的 Key值
+ name = scrapy.Field()
+ category = scrapy.Field()
+ date = scrapy.Field()
+
diff --git a/scrapy/scrapy01/scrapy01/middlewares.py b/scrapy/scrapy01/scrapy01/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..364921b0b386c2560ac650fddb64f16d5d400ccf
--- /dev/null
+++ b/scrapy/scrapy01/scrapy01/middlewares.py
@@ -0,0 +1,103 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+
+
+class Scrapy01SpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
+
+
+class Scrapy01DownloaderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the downloader middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_request(self, request, spider):
+ # Called for each request that goes through the downloader
+ # middleware.
+
+ # Must either:
+ # - return None: continue processing this request
+ # - or return a Response object
+ # - or return a Request object
+ # - or raise IgnoreRequest: process_exception() methods of
+ # installed downloader middleware will be called
+ return None
+
+ def process_response(self, request, response, spider):
+ # Called with the response returned from the downloader.
+
+ # Must either;
+ # - return a Response object
+ # - return a Request object
+ # - or raise IgnoreRequest
+ return response
+
+ def process_exception(self, request, exception, spider):
+ # Called when a download handler or a process_request()
+ # (from other downloader middleware) raises an exception.
+
+ # Must either:
+ # - return None: continue processing this exception
+ # - return a Response object: stops process_exception() chain
+ # - return a Request object: stops process_exception() chain
+ pass
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
diff --git a/scrapy/scrapy01/scrapy01/pipelines.py b/scrapy/scrapy01/scrapy01/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..46c027bd6374819ac86e527506c4adf26891626e
--- /dev/null
+++ b/scrapy/scrapy01/scrapy01/pipelines.py
@@ -0,0 +1,28 @@
+
+from itemadapter import ItemAdapter
+
+# 注意：管道默认是不生效的，需要去settings里面开启管道
+class Scrapy01Pipeline:
+ """类名随便取"""
+
+ def process_item(self, item, # item接收 spider传来的数据
+ spider): # 爬虫对象
+ """函数名不可改"""
+
+ print(item)
+ print(spider.name)
+ # 将解析的数据传递给 下一个 管道pipeline，注意管道之间的优先级
+ return item
+
+
+class NewPipeline:
+ def process_item(self, item, spider):
+
+ # 写入文件
+ with open("./data/game.txt", 'a') as f:
+ name, category, date = item.get('name'), item.get('category'), item.get('date')
+ s1 = name + ": " + category + ": " + date + '\n'
+ f.write(s1)
+
+ # 将解析的数据传递给 下一个 管道pipeline
+ return item
\ No newline at end of file
diff --git a/scrapy/scrapy01/scrapy01/settings.py b/scrapy/scrapy01/scrapy01/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..2cca20fabe19afc1b909af651f21e8579f5134e3
--- /dev/null
+++ b/scrapy/scrapy01/scrapy01/settings.py
@@ -0,0 +1,95 @@
+# Scrapy settings for scrapy01 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy01'
+
+SPIDER_MODULES = ['scrapy01.spiders']
+NEWSPIDER_MODULE = 'scrapy01.spiders'
+
+# 设置日志级别：DEBUG、INFO、WARNING、ERROR、CRITICAL
+LOG_LEVEL = 'WARNING' # 我们只显示 WARNING 以上级别 的日志
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = 'scrapy01 (+http://www.yourdomain.com)'
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = True
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# 'scrapy01.middlewares.Scrapy01SpiderMiddleware': 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+#DOWNLOADER_MIDDLEWARES = {
+# 'scrapy01.middlewares.Scrapy01DownloaderMiddleware': 543,
+#}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+""" 开启 Pipelines """
+ITEM_PIPELINES = {
+ # 管道路径：管道的优先级 -- key:value
+ # 数越小，优先级越高
+ 'scrapy01.pipelines.Scrapy01Pipeline': 300,
+ 'scrapy01.pipelines.NewPipeline': 200
+}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy01/scrapy01/spiders/__init__.py b/scrapy/scrapy01/scrapy01/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy01/scrapy01/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy01/scrapy01/spiders/__pycache__/__init__.cpython-39.pyc b/scrapy/scrapy01/scrapy01/spiders/__pycache__/__init__.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..1c52151a1e38cad28784700446d1a54ebf169ff1
Binary files /dev/null and b/scrapy/scrapy01/scrapy01/spiders/__pycache__/__init__.cpython-39.pyc differ
diff --git a/scrapy/scrapy01/scrapy01/spiders/__pycache__/game.cpython-39.pyc b/scrapy/scrapy01/scrapy01/spiders/__pycache__/game.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..165cf7288a7d08f0d3233afa37ab19ccfc26b4fc
Binary files /dev/null and b/scrapy/scrapy01/scrapy01/spiders/__pycache__/game.cpython-39.pyc differ
diff --git a/scrapy/scrapy01/scrapy01/spiders/game.py b/scrapy/scrapy01/scrapy01/spiders/game.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb82b9f9acaaaafa0572264c25bb987a6d8ac1dd
--- /dev/null
+++ b/scrapy/scrapy01/scrapy01/spiders/game.py
@@ -0,0 +1,52 @@
+import scrapy
+from scrapy01.items import GameItem
+
+class GameSpider(scrapy.Spider):
+ # 爬虫名，唯一且必须
+ name = 'game'
+
+ # 允许访问的域名
+ allowed_domains = ['4399.com']
+
+ # 最开始访问的 URL
+ start_urls = ['http://www.4399.com/flash/']
+
+ def parse(self, response):
+ """重写解析数据的函数"""
+
+ # 拿到页面源代码
+ html = response.text
+
+ # 提取数据
+ """
+ response.json() # 获取 JSON数据
+ response.xpath("") # 利用 XPath对数据进行解析
+ response.css() # 利用 CSS选择器解析
+ """
+
+ # 获取 游戏名 -- 返回的是 选择器 Selector对象
+ names = response.xpath('//ul[@class="n-game cf"]/li/a/b/text()')
+
+ # 提取游戏名
+ names = names.extract()
+
+ # 分块提取数据
+ li_list = response.xpath('//ul[@class="n-game cf"]/li')
+ for li in li_list:
+ ## 取游戏名
+ # extract_first()：提取第一项，有则提取，无则跳过
+ name = li.xpath('./a/b/text()').extract_first()
+
+ # 取类别
+ category = li.xpath('./em/a/text()').extract_first()
+
+ # 取发布日期
+ date = li.xpath('./em/text()').extract_first()
+
+ item = GameItem()
+ item['name'] = name
+ item['category'] = category
+ item['date'] = date
+
+ # 需要用 yield 将数据传递给 管道pipelines.py
+ yield item
\ No newline at end of file
diff --git a/scrapy/scrapy02/.DS_Store b/scrapy/scrapy02/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..951ca66b803bf341e8272315a195edb223292dcf
Binary files /dev/null and b/scrapy/scrapy02/.DS_Store differ
diff --git a/scrapy/scrapy02/data/game.csv b/scrapy/scrapy02/data/game.csv
new file mode 100644
index 0000000000000000000000000000000000000000..5942fab6d8288e07b32b998d3128065ee38b3f1c
--- /dev/null
+++ b/scrapy/scrapy02/data/game.csv
@@ -0,0 +1,207 @@
+三国很忙,策略类,2023-10-26
+寻找盛装的男孩,益智类,2023-10-26
+指尖投篮,敏捷篇,2023-10-26
+地下隧道大逃脱,益智类,2023-10-26
+南瓜噩梦,敏捷篇,2023-10-26
+救援埃莉诺,益智类,2023-10-26
+甲板清洁工,益智类,2023-10-26
+方块世界大爆破3,益智类,2023-10-26
+营救皇家动物,益智类,2023-10-26
+小恐龙逃离,益智类,2023-10-26
+救援工作人员,益智类,2023-10-26
+方块球球,益智类,2023-10-26
+拼接英语单词,益智类,2023-10-26
+逃离工地,益智类,2023-10-26
+新生的奥秘,益智类,2023-10-26
+救助受困的鱼,射击类,2023-10-26
+摆动蜘蛛过障碍,敏捷篇,2023-10-26
+水疗中心的服务,益智类,2023-10-26
+露西四季时尚达人,装扮类,2023-10-26
+下水道逃脱,益智类,2023-10-26
+从前时光,益智类,2023-10-26
+幽灵酒馆,益智类,2023-10-26
+美丽蝴蝶大逃脱,益智类,2023-10-26
+NBA英雄,体育类,2023-10-25
+救援小海豚,益智类,2023-10-25
+盒子的秘密,益智类,2023-10-25
+拯救笼中白母鸡,益智类,2023-10-25
+天空探险队,益智类,2023-10-25
+可爱小马逃脱,益智类,2023-10-25
+圆球华容道,益智类,2023-10-25
+逃离景区河流,益智类,2023-10-25
+火柴人出逃记,益智类,2023-10-25
+给客人做饭H5,休闲类,2023-10-25
+拯救笼中小猪,益智类,2023-10-25
+红方块闯迷宫,益智类,2023-10-25
+保护我的南瓜,益智类,2023-10-25
+救援名人夫妇,益智类,2023-10-25
+小黑花花射飞镖H5,益智类,2023-10-25
+拯救狞猫,益智类,2023-10-25
+寻找心理医生,益智类,2023-10-25
+寻找汽车钥匙,益智类,2023-10-25
+绵羊过障碍,敏捷篇,2023-10-25
+逗小猴开心系列812,益智类,2023-10-25
+音乐笔记,益智类,2023-10-25
+深渊契约,冒险类,2023-10-24
+海岛小分队,休闲类,2023-10-24
+村庄洞穴逃脱,益智类,2023-10-24
+逃离简易房屋129,益智类,2023-10-24
+夏季露营探险,休闲类,2023-10-24
+救援草裙姑娘,益智类,2023-10-24
+神秘空间站,益智类,2023-10-24
+前期准备工作,益智类,2023-10-24
+鸟群贪吃蛇,敏捷篇,2023-10-24
+花朵壁画屋逃脱,益智类,2023-10-24
+信徒,策略类,2023-10-24
+逃离沙漠地区,益智类,2023-10-24
+玫瑰仙境逃脱,益智类,2023-10-24
+逃离薄雾森林,益智类,2023-10-24
+双人激战3D,射击类,2023-10-24
+救出小马,益智类,2023-10-24
+公路赛车挑战,敏捷篇,2023-10-24
+宇宙猫生存,射击类,2023-10-24
+逃离魔法锅屋,益智类,2023-10-24
+拯救孔雀龙,益智类,2023-10-24
+红腹灰雀逃脱,益智类,2023-10-23
+火柴人升阶战,益智类,2023-10-23
+狂野大冒险,敏捷篇,2023-10-23
+寻找结婚礼服,益智类,2023-10-23
+一笔画出来,益智类,2023-10-23
+救援暹罗猫,益智类,2023-10-23
+奇妙的化妆术,装扮类,2023-10-23
+逗小猴开心系列811,益智类,2023-10-23
+纸杯蛋糕的线索,益智类,2023-10-23
+目的地之谜,益智类,2023-10-23
+找到海港走私者,益智类,2023-10-23
+暴打小僵尸,射击类,2023-10-23
+山鹿逃出山谷,益智类,2023-10-23
+维京人逃生记2,冒险类,2023-10-23
+隧道冲击,敏捷篇,2023-10-23
+昏暗儿童房逃生130,益智类,2023-10-22
+沉没的宝藏2,益智类,2023-10-22
+古墓诡影,益智类,2023-10-22
+迷路的猫,益智类,2023-10-22
+管道冒险,冒险类,2023-10-22
+色彩小球转换,敏捷篇,2023-10-22
+荒野狩猎,射击类,2023-10-22
+绵羊家族逃脱,益智类,2023-10-22
+寻找纸袋玩具,益智类,2023-10-22
+新坦克对战,策略类,2023-10-22
+逃离破落村落,益智类,2023-10-22
+修车店的秘密,益智类,2023-10-22
+寻找丢失的黄金,益智类,2023-10-22
+油条冰淇淋,休闲类,2023-10-22
+建造天柱,敏捷篇,2023-10-22
+寻找铅笔男孩,益智类,2023-10-22
+上帝的祝福,益智类,2023-10-22
+红色蘑菇林逃脱,益智类,2023-10-22
+魔法大厨,休闲类,2023-10-21
+推动选取器,敏捷篇,2023-10-21
+疯狂克隆人,冒险类,2023-10-21
+爱吃苹果的男孩,敏捷篇,2023-10-21
+救援气球女孩,益智类,2023-10-21
+机器人翻翻看,益智类,2023-10-21
+救援美人鱼模仿者,益智类,2023-10-21
+汉字消方块,益智类,2023-10-21
+混乱的化学家,益智类,2023-10-21
+暗黑系公主婚礼,装扮类,2023-10-21
+逃离荒废的营地,益智类,2023-10-21
+小猪消消,益智类,2023-10-21
+老城区酒吧,益智类,2023-10-21
+封印魔法之门,益智类,2023-10-21
+寻找美容师,益智类,2023-10-21
+挪了个车,益智类,2023-10-21
+儿童洗衣房,装扮类,2023-10-21
+昏暗儿童房逃生134,益智类,2023-10-21
+双人PK挑战,休闲类,2023-10-21
+小飞象逃脱,益智类,2023-10-20
+寻找滑冰男孩,益智类,2023-10-20
+首席医生救援,益智类,2023-10-20
+乌鸦森林大逃脱,益智类,2023-10-20
+制作甜披萨的楠楠,装扮类,2023-10-20
+梦想海岛王,休闲类,2023-10-20
+剑镇三界,冒险类,2023-10-20
+布置我的别墅,休闲类,2023-10-20
+西瓜拼接,益智类,2023-10-20
+救援金色鸭子,益智类,2023-10-20
+蘑菇兄弟,冒险类,2023-10-20
+救援华丽的小姑娘,益智类,2023-10-20
+热带麻将,益智类,2023-10-20
+烧脑大挑战合集,益智类,2023-10-20
+营救男子,益智类,2023-10-20
+田野之间,益智类,2023-10-20
+闪亮少女换装,装扮类,2023-10-20
+救援时尚的蜘蛛侠,益智类,2023-10-20
+被诅咒的电影院,益智类,2023-10-20
+阳光大花园,益智类,2023-10-20
+老六别坑了,益智类,2023-10-20
+黑暗的窄屋逃脱,益智类,2023-10-20
+逃离简易房屋127,益智类,2023-10-20
+僵尸兄弟闯密室3,益智类,2023-10-20
+寻找茄子玩具,益智类,2023-10-19
+昏暗儿童房逃生129,益智类,2023-10-19
+逃离森林的爱情鸟,益智类,2023-10-19
+寻找公主雕像,益智类,2023-10-19
+英勇营救姑娘,益智类,2023-10-19
+逃离迷人的花园,益智类,2023-10-19
+快乐男孩亨利逃脱,益智类,2023-10-19
+自然森林大逃脱,益智类,2023-10-19
+逃离橄榄树园,益智类,2023-10-19
+棕色母鸡逃脱,益智类,2023-10-19
+营救学生,益智类,2023-10-19
+逃离顶尖音乐会,益智类,2023-10-19
+救援一对猫,益智类,2023-10-19
+救援兽人战士,益智类,2023-10-19
+城堡的大秘密,益智类,2023-10-19
+时尚女学生穿搭,装扮类,2023-10-19
+流浪的星球,敏捷篇,2023-10-19
+合并战兵2048,敏捷篇,2023-10-19
+鲜花城堡,益智类,2023-10-19
+最后一件,益智类,2023-10-19
+烧脑大师,益智类,2023-10-19
+寻找气球姑娘,益智类,2023-10-19
+葫芦娃各显神通,策略类,2023-10-18
+停车我最强,体育类,2023-10-18
+寻找游戏玩具,益智类,2023-10-18
+救援工作人员约翰,益智类,2023-10-18
+寻找飞马的翅膀,益智类,2023-10-18
+吃火锅H5,敏捷篇,2023-10-18
+布鲁姆吉城堡,射击类,2023-10-18
+狐狸逃出沙漠,益智类,2023-10-18
+开澡堂H5,模拟经营,2023-10-18
+营救笼中狮子,益智类,2023-10-18
+飞机极限着陆,体育类,2023-10-18
+部落男人逃脱,益智类,2023-10-18
+营救花栗鼠,益智类,2023-10-18
+逃离趣味冒险屋,益智类,2023-10-18
+寻找企鹅伙伴,益智类,2023-10-18
+机器人修复师,冒险类,2023-10-18
+寻找长生不老药水,益智类,2023-10-18
+救出小白兔,益智类,2023-10-18
+逗小猴开心系列810,益智类,2023-10-18
+克服心中恐惧,益智类,2023-10-18
+盛开的樱花树,益智类,2023-10-18
+逃出诡异之地,益智类,2023-10-17
+拯救笼中爱鸟,益智类,2023-10-17
+野生袋鼠救援,益智类,2023-10-17
+寻找喜爱的裙子,益智类,2023-10-17
+西部牛仔大逃脱,益智类,2023-10-17
+救援虎猫,益智类,2023-10-17
+黄鸟救援,益智类,2023-10-17
+抵御怪物入侵,策略类,2023-10-17
+寻找狮子王,益智类,2023-10-17
+菜鸟小忍者,休闲类,2023-10-17
+飞天战机,射击类,2023-10-17
+辛巴找水,益智类,2023-10-17
+双枪牛仔,射击类,2023-10-17
+合成射击,射击类,2023-10-17
+校园阴影,益智类,2023-10-17
+荒野生存模拟,冒险类,2023-10-17
+初秋时尚穿搭,装扮类,2023-10-17
+面具进化,敏捷篇,2023-10-17
+姑娘的约会夜,装扮类,2023-10-17
+蚂蚁逃离,益智类,2023-10-17
+小黑花花糖果砸巫婆H5,射击类,2023-10-16
+逗小猴开心系列809,益智类,2023-10-16
+回响的街道,益智类,2023-10-16
+快速改道,益智类,2023-10-16
diff --git a/scrapy/scrapy02/scrapy.cfg b/scrapy/scrapy02/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..528fb1f205399c3baa8348ca594dfa9d5e723c40
--- /dev/null
+++ b/scrapy/scrapy02/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy02.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy02
diff --git a/scrapy/scrapy02/scrapy02/__init__.py b/scrapy/scrapy02/scrapy02/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy02/scrapy02/__pycache__/__init__.cpython-39.pyc b/scrapy/scrapy02/scrapy02/__pycache__/__init__.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..bc8a5243b53581cf12752ed7162a31a656174f32
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diff --git a/scrapy/scrapy02/scrapy02/__pycache__/items.cpython-39.pyc b/scrapy/scrapy02/scrapy02/__pycache__/items.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..10f36e4b025595d77cad7bdacebe0333928213d7
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diff --git a/scrapy/scrapy02/scrapy02/__pycache__/pipelines.cpython-39.pyc b/scrapy/scrapy02/scrapy02/__pycache__/pipelines.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..483e88a2eaeb39e9837998fac6e015b15d73fa37
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diff --git a/scrapy/scrapy02/scrapy02/__pycache__/settings.cpython-39.pyc b/scrapy/scrapy02/scrapy02/__pycache__/settings.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..eb6eab84df5c0ac6566bca06a4fcef5ae12fcbc6
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diff --git a/scrapy/scrapy02/scrapy02/items.py b/scrapy/scrapy02/scrapy02/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..cefe637fa77e421b1bec8415acca79f348e990f0
--- /dev/null
+++ b/scrapy/scrapy02/scrapy02/items.py
@@ -0,0 +1,13 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class GameItem(scrapy.Item):
+ # 定义 Item的 Key值
+ name = scrapy.Field()
+ category = scrapy.Field()
+ date = scrapy.Field()
diff --git a/scrapy/scrapy02/scrapy02/middlewares.py b/scrapy/scrapy02/scrapy02/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..14a306280f1efc7b62e8f4ad2170b075d7d6c8a0
--- /dev/null
+++ b/scrapy/scrapy02/scrapy02/middlewares.py
@@ -0,0 +1,103 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+
+
+class CaipiaoSpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
+
+
+class CaipiaoDownloaderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the downloader middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_request(self, request, spider):
+ # Called for each request that goes through the downloader
+ # middleware.
+
+ # Must either:
+ # - return None: continue processing this request
+ # - or return a Response object
+ # - or return a Request object
+ # - or raise IgnoreRequest: process_exception() methods of
+ # installed downloader middleware will be called
+ return None
+
+ def process_response(self, request, response, spider):
+ # Called with the response returned from the downloader.
+
+ # Must either;
+ # - return a Response object
+ # - return a Request object
+ # - or raise IgnoreRequest
+ return response
+
+ def process_exception(self, request, exception, spider):
+ # Called when a download handler or a process_request()
+ # (from other downloader middleware) raises an exception.
+
+ # Must either:
+ # - return None: continue processing this exception
+ # - return a Response object: stops process_exception() chain
+ # - return a Request object: stops process_exception() chain
+ pass
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
diff --git a/scrapy/scrapy02/scrapy02/pipelines.py b/scrapy/scrapy02/scrapy02/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..6718c29d28b4d054f6f8b07d0cf0b04554842d2e
--- /dev/null
+++ b/scrapy/scrapy02/scrapy02/pipelines.py
@@ -0,0 +1,81 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+import pymysql
+
+
+# 写入 csv文件
+class GamePipeline_CSV:
+
+ # 启动 爬虫时，执行一次
+ def open_spider(self, spider):
+ print("爬虫启动了...")
+
+ # 打开文件
+ self.f = open('./data/game.csv', mode="a", encoding="utf-8")
+
+ # 每次spider返回一条数据. 这里就要运行一次.
+ def process_item(self, item, spider):
+ """处理spider爬取的数据"""
+
+ # csv中的格式：期号, 红球1_红球2_红球3.., 篮球
+ self.f.write(item['name'])
+ self.f.write(",")
+ self.f.write(item['category'])
+ self.f.write(",")
+ self.f.write(item['date'])
+ self.f.write("\n")
+
+ # 传入下一个 pipeline
+ return item
+
+ # 关闭爬虫时，执行一次
+ def close_spider(self, spider):
+ print("爬虫结束了...")
+ # 关闭文件
+ self.f.close()
+
+# 写入 mysql数据库
+class GamePipeline_MySQL:
+
+ def open_spider(self, spider):
+ """在爬虫开始的时候，连接数据库"""
+ self.conn = pymysql.connect(host="127.0.0.1",
+ port=3306,
+ user="root",
+ password="zxydsg123",
+ database="scrapy")
+
+ def close_spider(self, spider):
+ """爬虫结束的时候，关闭数据库连接"""
+ self.conn.close()
+
+ # 每次spider返回一条数据. 这里就要运行一次.
+ def process_item(self, item, spider):
+ try:
+ # 弄个游标
+ cursor = self.conn.cursor()
+
+ # sql语句：插入数据
+ sql = "insert into game(name, category, date) values(%s, %s, %s)"
+
+ # 执行 sql
+ cursor.execute(sql, (item['name'], item['category'], item['date']))
+
+ # 提交事务
+ self.conn.commit()
+
+ except Exception as e:
+ # 如果报错. 回滚
+ print(e)
+ self.conn.rollback()
+
+ print("存储完毕...")
+
+ return item # 如果不return. 后续的管道将接受不到数据
+
diff --git a/scrapy/scrapy02/scrapy02/settings.py b/scrapy/scrapy02/scrapy02/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..a1274d59efdb4d5d0f3e7c907d2621ce5ea0140b
--- /dev/null
+++ b/scrapy/scrapy02/scrapy02/settings.py
@@ -0,0 +1,92 @@
+# Scrapy settings for scrapy02 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy02'
+LOG_LEVEL = "ERROR"
+
+SPIDER_MODULES = ['scrapy02.spiders']
+NEWSPIDER_MODULE = 'scrapy02.spiders'
+
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = 'scrapy02 (+http://www.yourdomain.com)'
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# 'scrapy02.middlewares.CaipiaoSpiderMiddleware': 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+#DOWNLOADER_MIDDLEWARES = {
+# 'scrapy02.middlewares.CaipiaoDownloaderMiddleware': 543,
+#}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+# 启动指定的 pipelines
+ITEM_PIPELINES = {
+ # 'scrapy02.pipelines.GamePipeline_CSV': 300,
+ 'scrapy02.pipelines.GamePipeline_MySQL': 301,
+}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy02/scrapy02/spiders/__init__.py b/scrapy/scrapy02/scrapy02/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy02/scrapy02/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy02/scrapy02/spiders/__pycache__/__init__.cpython-39.pyc b/scrapy/scrapy02/scrapy02/spiders/__pycache__/__init__.cpython-39.pyc
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diff --git a/scrapy/scrapy02/scrapy02/spiders/game.py b/scrapy/scrapy02/scrapy02/spiders/game.py
new file mode 100644
index 0000000000000000000000000000000000000000..045a89511cab4f2055a90871befebd5dfee6d34b
--- /dev/null
+++ b/scrapy/scrapy02/scrapy02/spiders/game.py
@@ -0,0 +1,39 @@
+import scrapy
+from scrapy02.items import GameItem
+
+class GameSpider(scrapy.Spider):
+
+ # 爬虫的名字
+ name = 'game'
+
+ # 允许爬取的域名
+ allowed_domains = ['4399.com']
+
+ # 开始爬取的 页面
+ start_urls = ['http://www.4399.com/flash/']
+
+
+ def parse(self, response):
+ """必须重写 解析函数 parse"""
+
+ # 提取数据
+ li_list = response.xpath('//ul[@class="n-game cf"]/li')
+ for li in li_list:
+ ## 取游戏名
+ # extract_first()：提取第一项，有则提取，无则跳过
+ name = li.xpath('./a/b/text()').extract_first()
+
+ # 取类别
+ category = li.xpath('./em/a/text()').extract_first()
+
+ # 取发布日期
+ date = li.xpath('./em/text()').extract_first()
+
+ item = GameItem()
+ item['name'] = name
+ item['category'] = category
+ item['date'] = date
+
+ print(item)
+ # 需要用 yield 将数据传递给 管道pipelines.py
+ yield item
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diff --git a/scrapy/scrapy03/scrapy.cfg b/scrapy/scrapy03/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..0524b38886a5859bbf179be6dc326eabe35d92ea
--- /dev/null
+++ b/scrapy/scrapy03/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy03.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy03
diff --git a/scrapy/scrapy03/scrapy03/__init__.py b/scrapy/scrapy03/scrapy03/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
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diff --git a/scrapy/scrapy03/scrapy03/__pycache__/settings.cpython-39.pyc b/scrapy/scrapy03/scrapy03/__pycache__/settings.cpython-39.pyc
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diff --git a/scrapy/scrapy03/scrapy03/items.py b/scrapy/scrapy03/scrapy03/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..ff8ac7d4e4ec0b7b539ea3f3a93a7ca0d7457862
--- /dev/null
+++ b/scrapy/scrapy03/scrapy03/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class TupianItem(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/scrapy03/scrapy03/middlewares.py b/scrapy/scrapy03/scrapy03/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..13d39bf7197361e158cc0f5625453a55a2a91498
--- /dev/null
+++ b/scrapy/scrapy03/scrapy03/middlewares.py
@@ -0,0 +1,103 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+
+
+class TupianSpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
+
+
+class TupianDownloaderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the downloader middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_request(self, request, spider):
+ # Called for each request that goes through the downloader
+ # middleware.
+
+ # Must either:
+ # - return None: continue processing this request
+ # - or return a Response object
+ # - or return a Request object
+ # - or raise IgnoreRequest: process_exception() methods of
+ # installed downloader middleware will be called
+ return None
+
+ def process_response(self, request, response, spider):
+ # Called with the response returned from the downloader.
+
+ # Must either;
+ # - return a Response object
+ # - return a Request object
+ # - or raise IgnoreRequest
+ return response
+
+ def process_exception(self, request, exception, spider):
+ # Called when a download handler or a process_request()
+ # (from other downloader middleware) raises an exception.
+
+ # Must either:
+ # - return None: continue processing this exception
+ # - return a Response object: stops process_exception() chain
+ # - return a Request object: stops process_exception() chain
+ pass
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
diff --git a/scrapy/scrapy03/scrapy03/pipelines.py b/scrapy/scrapy03/scrapy03/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..cc47d151eb1588b1b7b71dcdcc29bea8df8021d2
--- /dev/null
+++ b/scrapy/scrapy03/scrapy03/pipelines.py
@@ -0,0 +1,38 @@
+
+from itemadapter import ItemAdapter
+
+from scrapy.pipelines.images import ImagesPipeline
+from scrapy.pipelines.files import FilesPipeline
+from scrapy import Request
+
+
+class PicturePipeline(ImagesPipeline):
+ """进行图片下载"""
+
+ def get_media_requests(self, item, info):
+ """向图片所在的网址发送请求"""
+
+ # 获取图片的网址
+ src = item['src']
+
+ # 获取图片名字
+ name = item['name']
+
+ # 发送请求，请求对象传值的最佳方案: meta
+ yield Request(src, meta={"img_src": src, 'img_name':name})
+
+ def file_path(self, request, response=None, info=None, *, item=None):
+ """保存至本地"""
+
+ # 设置文件名
+ name = request.meta['img_name']
+
+ # 返回文件的保存路径，需要注名文件格式 jpg
+ return f"/{name}.jpg"
+
+
+ def item_completed(self, results, item, info):
+ """最后的收尾工作"""
+
+ # 将数据传递给 下一个管道
+ return item
\ No newline at end of file
diff --git a/scrapy/scrapy03/scrapy03/settings.py b/scrapy/scrapy03/scrapy03/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..ceabf63d370a23fa8dc7eadb1bee13a460e373cd
--- /dev/null
+++ b/scrapy/scrapy03/scrapy03/settings.py
@@ -0,0 +1,95 @@
+# Scrapy settings for scrapy03 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy03'
+
+SPIDER_MODULES = ['scrapy03.spiders']
+NEWSPIDER_MODULE = 'scrapy03.spiders'
+
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/104.0.0.0 Safari/537.36'
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+LOG_LEVEL = "WARNING"
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+# DOWNLOAD_DELAY = 1 # 重点。做人留一线
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# 'scrapy03.middlewares.TupianSpiderMiddleware': 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+#DOWNLOADER_MIDDLEWARES = {
+# 'scrapy03.middlewares.TupianDownloaderMiddleware': 543,
+#}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+ITEM_PIPELINES = {
+ 'scrapy03.pipelines.PicturePipeline': 300,
+}
+
+# 图片保存的路径 -- 必须要有
+IMAGES_STORE = "./pictures"
+
+# 在下载文件（图片）可能会出现302的问题
+MEDIA_ALLOW_REDIRECTS = True
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy03/scrapy03/spiders/__init__.py b/scrapy/scrapy03/scrapy03/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy03/scrapy03/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy03/scrapy03/spiders/__pycache__/__init__.cpython-39.pyc b/scrapy/scrapy03/scrapy03/spiders/__pycache__/__init__.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..2f22aaa801bfdf8f006598d37a4fa6837f7b21b4
Binary files /dev/null and b/scrapy/scrapy03/scrapy03/spiders/__pycache__/__init__.cpython-39.pyc differ
diff --git a/scrapy/scrapy03/scrapy03/spiders/__pycache__/picture.cpython-39.pyc b/scrapy/scrapy03/scrapy03/spiders/__pycache__/picture.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..28a4ecb54f9432e095a7e4fa4bc95d970e13ceeb
Binary files /dev/null and b/scrapy/scrapy03/scrapy03/spiders/__pycache__/picture.cpython-39.pyc differ
diff --git a/scrapy/scrapy03/scrapy03/spiders/picture.py b/scrapy/scrapy03/scrapy03/spiders/picture.py
new file mode 100644
index 0000000000000000000000000000000000000000..57a760585399417bb1c9315c5647d575becbe1ef
--- /dev/null
+++ b/scrapy/scrapy03/scrapy03/spiders/picture.py
@@ -0,0 +1,75 @@
+import scrapy
+
+
+
+class PictureSpider(scrapy.Spider):
+ name = 'picture'
+ allowed_domains = ['4399.com']
+ start_urls = ['http://www.4399.com/flash/']
+
+ def parse(self, resp):
+ # 查看是 哪个网页 返回来的数据
+ print(resp.url)
+
+ # 获取 游戏网站的 多个页面地址
+ img_srcs = resp.xpath("//div[@id='pagg']/a[@target='_self']/@href").extract()
+ # print(img_srcs)
+ for img_src in img_srcs:
+
+ # 生成完整的 页面 URL地址
+ child_url = resp.urljoin(img_src)
+
+ # 发送请求，经过 引擎 -> 调度器 -> 引擎 -> 下载器 -> 网页返回数据，执行回调函数
+ yield scrapy.Request(url=child_url, callback=self.NextParse)
+
+
+ def NextParse(self, resp, **kwargs):
+
+ # 查看 爬取的是哪个网页
+ print(resp.url)
+
+ # 每个网页，只获取一张图片
+ img_src = resp.xpath("//ul[@class='n-game cf']/li/a/img/@lz_src")[0].extract()
+ img_src = resp.urljoin(img_src)
+
+ img_name = resp.xpath("//ul[@class='n-game cf']/li/a/b/text()")[0].extract()
+
+ print(img_src, img_name)
+ # 发送给 Pipeline进行数据保存
+ yield {
+ 'name':img_name,
+ "src": img_src
+ }
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+# # 题外内容
+# if __name__ == '__main__':
+# s = "https://desk.zol.com.cn/dongman/周杰伦"
+# child = "/hehe/haha/houhou.html"
+#
+# # 用urllib来做url的拼接。
+# from urllib.parse import urljoin
+# ssss = urljoin(s, child) # 拼接路径的时候。 不需要考虑是否以/开头
+#
+# print(ssss)
diff --git a/scrapy/scrapy04/scrapy.cfg b/scrapy/scrapy04/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..a4f72d88ad03629cb47feddab9b53249392db796
--- /dev/null
+++ b/scrapy/scrapy04/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy04.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy04
diff --git a/scrapy/scrapy04/scrapy04/__init__.py b/scrapy/scrapy04/scrapy04/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy04/scrapy04/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy04/scrapy04/__pycache__/__init__.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..b75153db605483e6d7ea543350e2db239d6eeb32
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diff --git a/scrapy/scrapy04/scrapy04/__pycache__/settings.cpython-311.pyc b/scrapy/scrapy04/scrapy04/__pycache__/settings.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..d1383b3317212e5f8abf04f4f12f04260351f0ef
Binary files /dev/null and b/scrapy/scrapy04/scrapy04/__pycache__/settings.cpython-311.pyc differ
diff --git a/scrapy/scrapy04/scrapy04/items.py b/scrapy/scrapy04/scrapy04/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..92542c03e604420806a8b0cd6e73c548ae0599de
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class Scrapy04Item(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/scrapy04/scrapy04/middlewares.py b/scrapy/scrapy04/scrapy04/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..e9f7bab51a039e9b7b59a9f5756cb6b80ff0b8bb
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/middlewares.py
@@ -0,0 +1,103 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+
+
+class Scrapy04SpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info("Spider opened: %s" % spider.name)
+
+
+class Scrapy04DownloaderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the downloader middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_request(self, request, spider):
+ # Called for each request that goes through the downloader
+ # middleware.
+
+ # Must either:
+ # - return None: continue processing this request
+ # - or return a Response object
+ # - or return a Request object
+ # - or raise IgnoreRequest: process_exception() methods of
+ # installed downloader middleware will be called
+ return None
+
+ def process_response(self, request, response, spider):
+ # Called with the response returned from the downloader.
+
+ # Must either;
+ # - return a Response object
+ # - return a Request object
+ # - or raise IgnoreRequest
+ return response
+
+ def process_exception(self, request, exception, spider):
+ # Called when a download handler or a process_request()
+ # (from other downloader middleware) raises an exception.
+
+ # Must either:
+ # - return None: continue processing this exception
+ # - return a Response object: stops process_exception() chain
+ # - return a Request object: stops process_exception() chain
+ pass
+
+ def spider_opened(self, spider):
+ spider.logger.info("Spider opened: %s" % spider.name)
diff --git a/scrapy/scrapy04/scrapy04/pipelines.py b/scrapy/scrapy04/scrapy04/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..58fe61b46ce7ebdfa3d9457225c1f14653c2aabd
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/pipelines.py
@@ -0,0 +1,13 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+
+
+class Scrapy04Pipeline:
+ def process_item(self, item, spider):
+ return item
diff --git a/scrapy/scrapy04/scrapy04/settings.py b/scrapy/scrapy04/scrapy04/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..86bcbc4d03c71e9af5ca9005fadee0e1048a28d8
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/settings.py
@@ -0,0 +1,101 @@
+# Scrapy settings for scrapy04 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = "scrapy04"
+
+SPIDER_MODULES = ["scrapy04.spiders"]
+NEWSPIDER_MODULE = "scrapy04.spiders"
+
+LOG_LEVEL = 'WARNING'
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = "scrapy04 (+http://www.yourdomain.com)"
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+
+# 设置 cookie
+COOKIES_ENABLED = False
+DEFAULT_REQUEST_HEADERS = {
+ 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+ 'Accept-Language': 'en',
+ 'Cookie': "GUID=d69afa45-6723-43a7-9d9c-1845e6df0d4c; c_channel=0; c_csc=web; Hm_lvt_9793f42b498361373512340937deb2a0=1698411700,1698416042,1698416654; accessToken=avatarUrl%3Dhttps%253A%252F%252Fcdn.static.17k.com%252Fuser%252Favatar%252F02%252F82%252F71%252F102357182.jpg-88x88%253Fv%253D1698411887000%26id%3D102357182%26nickname%3DY%25E9%25AA%2581%25E5%258B%2587%25E5%2596%2584%25E6%2588%2598Y%26e%3D1713968655%26s%3Da357e246664654ad; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%22102357182%22%2C%22%24device_id%22%3A%2218b717fe9c8101-0cdaf2cd30d718-17525634-1296000-18b717fe9c9fc2%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E7%9B%B4%E6%8E%A5%E6%B5%81%E9%87%8F%22%2C%22%24latest_referrer%22%3A%22%22%2C%22%24latest_referrer_host%22%3A%22%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC_%E7%9B%B4%E6%8E%A5%E6%89%93%E5%BC%80%22%7D%2C%22first_id%22%3A%22d69afa45-6723-43a7-9d9c-1845e6df0d4c%22%7D; Hm_lpvt_9793f42b498361373512340937deb2a0=1698416662"
+,
+ "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/101.0.4951.54 Safari/537.36"
+}
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
+# "Accept-Language": "en",
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# "scrapy04.middlewares.Scrapy04SpiderMiddleware": 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+#DOWNLOADER_MIDDLEWARES = {
+# "scrapy04.middlewares.Scrapy04DownloaderMiddleware": 543,
+#}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# "scrapy.extensions.telnet.TelnetConsole": None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+#ITEM_PIPELINES = {
+# "scrapy04.pipelines.Scrapy04Pipeline": 300,
+#}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = "httpcache"
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = "scrapy.extensions.httpcache.FilesystemCacheStorage"
+
+# Set settings whose default value is deprecated to a future-proof value
+REQUEST_FINGERPRINTER_IMPLEMENTATION = "2.7"
+TWISTED_REACTOR = "twisted.internet.asyncioreactor.AsyncioSelectorReactor"
+FEED_EXPORT_ENCODING = "utf-8"
diff --git a/scrapy/scrapy04/scrapy04/spiders/__init__.py b/scrapy/scrapy04/scrapy04/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy04/scrapy04/spiders/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy04/scrapy04/spiders/__pycache__/__init__.cpython-311.pyc
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diff --git a/scrapy/scrapy04/scrapy04/spiders/__pycache__/login1.cpython-311.pyc b/scrapy/scrapy04/scrapy04/spiders/__pycache__/login1.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..366b7230f6dd318f23b711ca650efc460fc64c62
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diff --git a/scrapy/scrapy04/scrapy04/spiders/__pycache__/login2.cpython-311.pyc b/scrapy/scrapy04/scrapy04/spiders/__pycache__/login2.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..eef91ac99261b3da8b5bb54eb90891bf4beaef67
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diff --git a/scrapy/scrapy04/scrapy04/spiders/__pycache__/login3.cpython-311.pyc b/scrapy/scrapy04/scrapy04/spiders/__pycache__/login3.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..141269365af7eff72dcd49893b9b5f1e3e48b979
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diff --git a/scrapy/scrapy04/scrapy04/spiders/login1.py b/scrapy/scrapy04/scrapy04/spiders/login1.py
new file mode 100644
index 0000000000000000000000000000000000000000..34cb70f480101c227f321f0c9d603a3d02a8726a
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/spiders/login1.py
@@ -0,0 +1,27 @@
+import scrapy
+from scrapy import Request, FormRequest
+
+class LoginSpider(scrapy.Spider):
+ name = 'login1'
+ allowed_domains = ['17k.com']
+ start_urls = ['https://user.17k.com/www/']
+
+ def parse(self, response):
+ print(response.text)
+
+ def start_requests(self):
+ # 直接从 浏览器复制 cookie
+ cookies = "GUID=d69afa45-6723-43a7-9d9c-1845e6df0d4c; c_channel=0; c_csc=web; Hm_lvt_9793f42b498361373512340937deb2a0=1698411700,1698416042,1698416654; accessToken=avatarUrl%3Dhttps%253A%252F%252Fcdn.static.17k.com%252Fuser%252Favatar%252F02%252F82%252F71%252F102357182.jpg-88x88%253Fv%253D1698411887000%26id%3D102357182%26nickname%3DY%25E9%25AA%2581%25E5%258B%2587%25E5%2596%2584%25E6%2588%2598Y%26e%3D1713968655%26s%3Da357e246664654ad; sensorsdata2015jssdkcross=%7B%22distinct_id%22%3A%22102357182%22%2C%22%24device_id%22%3A%2218b717fe9c8101-0cdaf2cd30d718-17525634-1296000-18b717fe9c9fc2%22%2C%22props%22%3A%7B%22%24latest_traffic_source_type%22%3A%22%E7%9B%B4%E6%8E%A5%E6%B5%81%E9%87%8F%22%2C%22%24latest_referrer%22%3A%22%22%2C%22%24latest_referrer_host%22%3A%22%22%2C%22%24latest_search_keyword%22%3A%22%E6%9C%AA%E5%8F%96%E5%88%B0%E5%80%BC_%E7%9B%B4%E6%8E%A5%E6%89%93%E5%BC%80%22%7D%2C%22first_id%22%3A%22d69afa45-6723-43a7-9d9c-1845e6df0d4c%22%7D; Hm_lpvt_9793f42b498361373512340937deb2a0=1698416662"
+
+ # 将 cookie 以字典形式存储
+ cookie_dic = {}
+ for c in cookies.split("; "):
+ k, v = c.split("=")
+ cookie_dic[k] = v
+
+ # 发送请求
+ yield Request(
+ url=LoginSpider.start_urls[0],
+ cookies=cookie_dic,
+ callback=self.parse # 执行回调函数
+ )
\ No newline at end of file
diff --git a/scrapy/scrapy04/scrapy04/spiders/login2.py b/scrapy/scrapy04/scrapy04/spiders/login2.py
new file mode 100644
index 0000000000000000000000000000000000000000..8cd3a2ad47c7d7ec43e20611be7ca1653e36f10b
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/spiders/login2.py
@@ -0,0 +1,51 @@
+import scrapy
+from scrapy import Request, FormRequest
+
+class LoginSpider(scrapy.Spider):
+ name = 'login2'
+ allowed_domains = ['17k.com']
+ start_urls = ['https://user.17k.com/www/']
+
+ def start_requests(self):
+ """首次发送请求：进行登录"""
+
+ # 用户名和密码
+ username = "18370942865"
+ password = "zxydsg123"
+
+ # 登录界面的 URL
+ url = "https://passport.17k.com/"
+
+ # 发送 post请求 -- 拿到 cookie值
+ yield FormRequest(
+ url=url,
+ formdata={
+ "user": username,
+ "pass": password
+ }, # key值 与 页面保持一致
+ callback=self.parse # 回调函数
+ )
+
+ """
+ # 另一种方式：发送post请求
+ yield Request(
+ url=url,
+ method="post",
+ body="user=18370942865&pass=zxydsg123",
+ callback=self.parse
+ )
+ """
+
+
+ def parse(self, response):
+ """解析数据"""
+
+ # 发送请求
+ yield Request(
+ url=LoginSpider.start_urls[0],
+ callback=self.parse_detail # 回调函数
+ )
+
+ def parse_detail(self, resp):
+ """检查是否登录成功"""
+ print(resp)
\ No newline at end of file
diff --git a/scrapy/scrapy04/scrapy04/spiders/login3.py b/scrapy/scrapy04/scrapy04/spiders/login3.py
new file mode 100644
index 0000000000000000000000000000000000000000..e98799168d82a091d61bc020e44aed3fe7a9677f
--- /dev/null
+++ b/scrapy/scrapy04/scrapy04/spiders/login3.py
@@ -0,0 +1,10 @@
+import scrapy
+from scrapy import Request, FormRequest
+
+class LoginSpider(scrapy.Spider):
+ name = 'login3'
+ allowed_domains = ['17k.com']
+ start_urls = ['https://user.17k.com/www/']
+
+ def parse(self, response):
+ print(response)
diff --git a/scrapy/scrapy05/.DS_Store b/scrapy/scrapy05/.DS_Store
new file mode 100644
index 0000000000000000000000000000000000000000..8506b2ad58cd9593e5874713ff2ee5bf69b8ca22
Binary files /dev/null and b/scrapy/scrapy05/.DS_Store differ
diff --git a/scrapy/scrapy05/__init__.py b/scrapy/scrapy05/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy05/scrapy.cfg b/scrapy/scrapy05/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..557f647a3242ce9955beed4f4a7922114a84462a
--- /dev/null
+++ b/scrapy/scrapy05/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy05.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy05
diff --git a/scrapy/scrapy05/scrapy05/__init__.py b/scrapy/scrapy05/scrapy05/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy05/scrapy05/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy05/scrapy05/__pycache__/__init__.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..fa3e66d0c633f7576298f7547026df0fc3ece72e
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diff --git a/scrapy/scrapy05/scrapy05/__pycache__/middlewares.cpython-311.pyc b/scrapy/scrapy05/scrapy05/__pycache__/middlewares.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..8277d541dfa74a89c963602baa2a2f09f95b96c7
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diff --git a/scrapy/scrapy05/scrapy05/__pycache__/settings.cpython-311.pyc b/scrapy/scrapy05/scrapy05/__pycache__/settings.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..be8b0e4efefb66b62d994ce91613cf4f0c2b4ce8
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diff --git a/scrapy/scrapy05/scrapy05/items.py b/scrapy/scrapy05/scrapy05/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..d2f8c648eb45e6e3fa27eb835f3db4939f3ddb07
--- /dev/null
+++ b/scrapy/scrapy05/scrapy05/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class MidItem(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/scrapy05/scrapy05/middlewares.py b/scrapy/scrapy05/scrapy05/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..364a7673c6f8c5e1850b3297fa17879ffff93e38
--- /dev/null
+++ b/scrapy/scrapy05/scrapy05/middlewares.py
@@ -0,0 +1,68 @@
+"""中间件"""
+from scrapy import signals
+
+
+class MidSpiderMiddleware:
+ """爬虫中间件, 介于spider和引擎之间"""
+ pass
+
+
+class MidDownloaderMiddleware1:
+ """下载器中间件1, 介于下载器和引擎之间"""
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ """设置 在什么时间，执行什么方法"""
+
+ # 在爬虫启动时，执行 spider_opened方法
+ s = cls()
+ crawler.signals.connect(s.spider_opened, # 爬虫启动时
+ signal=signals.spider_opened) # 执行的方法
+ return s
+
+ def process_request(self, request, spider):
+ """
+ 在引擎将请求的信息交给下载器之前, 自动的调用该方法
+ :param request: 当前请求
+ :param spider: 发出该请求的 spider
+ :return:
+ 注意, process_request返回值是有规定的.
+ 1. 如果返回的None, 不做拦截. 继续向后面的中间件执行.
+ 2. 如果返回的是Request. 后续的中间件将不再执行.将请求重新交给引擎. 引擎重新扔给调度器
+ 3. 如果返回的是Response. 后续的中间件将不再执行.将响应信息交给引擎. 引擎将响应丢给spider. 进行数据处理
+ """
+ print("ware1, 我是process_requests")
+ return None
+
+ def process_response(self, request, response, spider):
+ """
+ 在下载器返回响应准备交给引擎之间. 自动调用该方法
+ :param request: 当前请求
+ :param response: 响应内容
+ :param spider: 发送请求的爬虫
+ :return:
+ 1. request. 直接把请求交给引擎, 引擎将请求丢给调度器
+ 2. response. 不做拦截, 继续向前进行提交返回
+ """
+ print("ware1", "process_response")
+ return response
+
+ def process_exception(self, request, exception, spider):
+ # 当前请求执行过程中, 出错了. 自动执行它
+ pass
+
+ def spider_opened(self, spider):
+ """爬虫启动时，执行该方法 -- 只执行一次"""
+ print("我是spider_opened")
+
+class MidDownloaderMiddleware2:
+ """下载器中间件2, 介于下载器和引擎之间"""
+ def process_request(self, request, spider):
+ """处理请求"""
+ print("ware2, 我是process_requests")
+ return None
+
+ def process_response(self, request, response, spider):
+ """处理响应"""
+ print("我是ware2", "process_response")
+ return response
diff --git a/scrapy/scrapy05/scrapy05/pipelines.py b/scrapy/scrapy05/scrapy05/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..b1bbda5b1685e76828d702f7c5d90281ec973b66
--- /dev/null
+++ b/scrapy/scrapy05/scrapy05/pipelines.py
@@ -0,0 +1,13 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+
+
+class MidPipeline:
+ def process_item(self, item, spider):
+ return item
diff --git a/scrapy/scrapy05/scrapy05/settings.py b/scrapy/scrapy05/scrapy05/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..3e4ad2c2888112be3ada98ccd973915dc0fc07f6
--- /dev/null
+++ b/scrapy/scrapy05/scrapy05/settings.py
@@ -0,0 +1,93 @@
+# Scrapy settings for scrapy05 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy05'
+
+SPIDER_MODULES = ['scrapy05.spiders']
+NEWSPIDER_MODULE = 'scrapy05.spiders'
+
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = 'scrapy05 (+http://www.yourdomain.com)'
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+
+LOG_LEVEL = "WARNING"
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+# SPIDER_MIDDLEWARES = {
+# 'scrapy05.middlewares.MidSpiderMiddleware': 543,
+# }
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+
+# 开启中间件
+DOWNLOADER_MIDDLEWARES = {
+ # key:value -- 中间件名字:优先级 -- 数字越小，优先级越高
+ 'scrapy05.middlewares.MidDownloaderMiddleware1': 543,
+ 'scrapy05.middlewares.MidDownloaderMiddleware2': 544,
+}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+# ITEM_PIPELINES = {
+# 'scrapy05.pipelines.MidPipeline': 300,
+# }
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy05/scrapy05/spiders/__init__.py b/scrapy/scrapy05/scrapy05/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy05/scrapy05/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy05/scrapy05/spiders/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy05/scrapy05/spiders/__pycache__/__init__.cpython-311.pyc
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diff --git a/scrapy/scrapy05/scrapy05/spiders/__pycache__/baidu.cpython-311.pyc b/scrapy/scrapy05/scrapy05/spiders/__pycache__/baidu.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..05bb7033c54f50672905d41307f5e25d3398bf01
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diff --git a/scrapy/scrapy05/scrapy05/spiders/baidu.py b/scrapy/scrapy05/scrapy05/spiders/baidu.py
new file mode 100644
index 0000000000000000000000000000000000000000..b5e223b6118b50f8683b68db9d45ce312aee4f78
--- /dev/null
+++ b/scrapy/scrapy05/scrapy05/spiders/baidu.py
@@ -0,0 +1,10 @@
+import scrapy
+
+
+class BaiduSpider(scrapy.Spider):
+ name = 'baidu'
+ allowed_domains = ['baidu.com']
+ start_urls = ['http://www.baidu.com/']
+
+ def parse(self, response):
+ print(response.xpath("//title/text()").extract_first()) # 百度一下
diff --git a/scrapy/scrapy06/__init__.py b/scrapy/scrapy06/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy06/scrapy.cfg b/scrapy/scrapy06/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..6581e7b94a41e508d36db153111bdde0433ad73f
--- /dev/null
+++ b/scrapy/scrapy06/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy06.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy06
diff --git a/scrapy/scrapy06/scrapy06/__init__.py b/scrapy/scrapy06/scrapy06/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
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index 0000000000000000000000000000000000000000..cf8223deb7181fef4741de608af76a0f78103e4f
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diff --git a/scrapy/scrapy06/scrapy06/items.py b/scrapy/scrapy06/scrapy06/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..d309d3a96d07a1ce588c8699a84b00ab623a8c2c
--- /dev/null
+++ b/scrapy/scrapy06/scrapy06/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class DoubanItem(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/scrapy06/scrapy06/middlewares.py b/scrapy/scrapy06/scrapy06/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..bc9cea9e34b3ced213ffc5f4063870fbbb9cb311
--- /dev/null
+++ b/scrapy/scrapy06/scrapy06/middlewares.py
@@ -0,0 +1,94 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+from scrapy06.settings import USER_AGENT_LIST, PROXY_IP_LIST
+from random import choice
+from w3lib.http import basic_auth_header
+
+
+class DoubanSpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
+
+
+class DoubanDownloaderMiddleware:
+
+ def process_request(self, request, spider):
+ ua = choice(USER_AGENT_LIST)
+ request.headers['User-Agent'] = ua
+ return None # 不能返回任何东西
+
+
+# 免费代理
+class ProxyDownloaderMiddleware:
+ def process_request(self, request, spider):
+
+ # 选择 IP
+ ip = choice(PROXY_IP_LIST)
+
+ # 设置代理
+ request.meta['proxy'] = "https://" + ip
+
+ # 放行
+ return None
+
+# 付费代理
+class MoneyProxyDownloaderMiddleware:
+
+ def process_request(self, request, spider):
+ proxy = "tps138.kdlapi.com:15818"
+
+ # 设置代理
+ request.meta['proxy'] = f"http://{proxy}"
+
+ # 用户名密码认证
+ request.headers['Proxy-Authorization'] = basic_auth_header('t12831993520578', 't72a13xu') # 白名单认证可注释此行
+ request.headers["Connection"] = "close"
diff --git a/scrapy/scrapy06/scrapy06/pipelines.py b/scrapy/scrapy06/scrapy06/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..8684bbbdd681c8af4fe65ffe4320fdc450b5c4ab
--- /dev/null
+++ b/scrapy/scrapy06/scrapy06/pipelines.py
@@ -0,0 +1,13 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+
+
+class DoubanPipeline:
+ def process_item(self, item, spider):
+ return item
diff --git a/scrapy/scrapy06/scrapy06/settings.py b/scrapy/scrapy06/scrapy06/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..09e39922efbc6bf653af91e608537721492702b3
--- /dev/null
+++ b/scrapy/scrapy06/scrapy06/settings.py
@@ -0,0 +1,132 @@
+# Scrapy settings for scrapy06 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy06'
+
+SPIDER_MODULES = ['scrapy06.spiders']
+NEWSPIDER_MODULE = 'scrapy06.spiders'
+
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+# 设置User-Agent
+# USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36'
+
+USER_AGENT_LIST = [
+ 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36',
+ 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2919.83 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2866.71 Safari/537.36',
+ 'Mozilla/5.0 (X11; Ubuntu; Linux i686 on x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/53.0.2820.59 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2762.73 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/49.0.2656.18 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.36 (KHTML like Gecko) Chrome/44.0.2403.155 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2228.0 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.1 Safari/537.36',
+ 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2227.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2226.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.4; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.3; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2225.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 5.1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2224.3 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 10.0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/40.0.2214.93 Safari/537.36',
+ 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/37.0.2062.124 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/37.0.2049.0 Safari/537.36',
+ 'Mozilla/5.0 (Windows NT 4.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/37.0.2049.0 Safari/537.36',
+]
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+LOG_LEVEL = "WARNING"
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# 'scrapy06.middlewares.DoubanSpiderMiddleware': 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+DOWNLOADER_MIDDLEWARES = {
+ 'scrapy06.middlewares.DoubanDownloaderMiddleware': 543,
+ 'scrapy06.middlewares.MoneyProxyDownloaderMiddleware': 544,
+ # 'scrapy06.middlewares.ProxyDownloaderMiddleware': 544,
+}
+
+PROXY_IP_LIST = [
+ "123.171.5.133:8118",
+ "101.200.127.149:3129",
+ "117.69.230.254:3256",
+ "111.72.25.46:3256",
+ "121.230.210.200:3256",
+ "121.230.211.68:3256",
+ "121.230.210.18:3256",
+ "111.72.25.125:3256",
+ "47.104.15.198:80",
+ "60.167.20.58:1133",
+ "223.240.209.141:1133",
+ "163.125.249.131:8118",
+ "112.195.242.170:3256",
+ "27.208.227.213:8060",
+ "110.43.136.72:3128",
+]
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+#ITEM_PIPELINES = {
+# 'scrapy06.pipelines.DoubanPipeline': 300,
+#}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy06/scrapy06/spiders/__init__.py b/scrapy/scrapy06/scrapy06/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy06/scrapy06/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy06/scrapy06/spiders/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy06/scrapy06/spiders/__pycache__/__init__.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..0c3c29e892176ca1c270e1ef3eff7f1ece3227c0
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diff --git a/scrapy/scrapy06/scrapy06/spiders/__pycache__/movie.cpython-311.pyc b/scrapy/scrapy06/scrapy06/spiders/__pycache__/movie.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..92e33d4032c6f486892a3d339af2fb3a0fa7c860
Binary files /dev/null and b/scrapy/scrapy06/scrapy06/spiders/__pycache__/movie.cpython-311.pyc differ
diff --git a/scrapy/scrapy06/scrapy06/spiders/movie.py b/scrapy/scrapy06/scrapy06/spiders/movie.py
new file mode 100644
index 0000000000000000000000000000000000000000..905a5031c6bf2c77aa88f542f701a4d8473891c3
--- /dev/null
+++ b/scrapy/scrapy06/scrapy06/spiders/movie.py
@@ -0,0 +1,10 @@
+import scrapy
+
+
+class MovieSpider(scrapy.Spider):
+ name = 'movie'
+ allowed_domains = ['douban.com']
+ start_urls = ['https://movie.douban.com/typerank?type_name=%E5%89%A7%E6%83%85&type=11&interval_id=100:90&action=']
+
+ def parse(self, response):
+ print(response.text)
diff --git a/scrapy/scrapy07/__init__.py b/scrapy/scrapy07/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy07/scrapy.cfg b/scrapy/scrapy07/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..9605ddc8da796c2337523ef4faf2a50239a59ae6
--- /dev/null
+++ b/scrapy/scrapy07/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy07.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy07
diff --git a/scrapy/scrapy07/scrapy07/__init__.py b/scrapy/scrapy07/scrapy07/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy07/scrapy07/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy07/scrapy07/__pycache__/__init__.cpython-311.pyc
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diff --git a/scrapy/scrapy07/scrapy07/__pycache__/middlewares.cpython-311.pyc b/scrapy/scrapy07/scrapy07/__pycache__/middlewares.cpython-311.pyc
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diff --git a/scrapy/scrapy07/scrapy07/__pycache__/request.cpython-311.pyc b/scrapy/scrapy07/scrapy07/__pycache__/request.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..e6106a5f3b28143cb388ff9898966981433d3d39
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diff --git a/scrapy/scrapy07/scrapy07/__pycache__/settings.cpython-311.pyc b/scrapy/scrapy07/scrapy07/__pycache__/settings.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..c1f38d13e6eb8af363a8f0ff135987886da0a344
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diff --git a/scrapy/scrapy07/scrapy07/items.py b/scrapy/scrapy07/scrapy07/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..fe1581167411fcbc43c7e21a97296ccb30d2b859
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class BossItem(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/scrapy07/scrapy07/middlewares.py b/scrapy/scrapy07/scrapy07/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..e209f890fb04ae243800cfd0533203fea5cb24ce
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/middlewares.py
@@ -0,0 +1,115 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+import time
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+from scrapy07.request import SeleniumRequest
+from selenium.webdriver import Chrome
+from scrapy.http.response.html import HtmlResponse
+
+class BossSpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
+
+
+class BossDownloaderMiddleware:
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ """对中间件进行总体设置"""
+ s = cls()
+
+ # 在爬虫开始的时候. 执行spider_opened
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+
+ # 在爬虫结束的时候. 执行spider_closed
+ crawler.signals.connect(s.spider_closed, signal=signals.spider_closed)
+
+ return s
+
+ def process_request(self, request, spider):
+ """处理请求"""
+ if isinstance(request, SeleniumRequest):
+
+ # selenium发送请求
+ self.web.get(request.url)
+ time.sleep(3)
+
+ # 获取页面源码
+ page_source = self.web.page_source
+
+ # 包装成 Response，往引擎中传
+ return HtmlResponse(url=request.url, # 响应的地址
+ encoding='utf-8', # 编码格式
+ request=request, # 回应的请求
+ body=page_source) # 返回的源码
+
+ def process_response(self, request, response, spider):
+ """处理响应"""
+ return response
+
+ def process_exception(self, request, exception, spider):
+ """处理异常"""
+ pass
+
+ def spider_opened(self, spider):
+ """爬虫开启时，执行该函数"""
+
+ # 创建浏览器
+ self.web = Chrome()
+
+ # 隐式等待
+ self.web.implicitly_wait(10)
+
+ print("创建浏览器")
+
+ def spider_closed(self, spider):
+ """爬虫结束时，执行该函数"""
+ self.web.close()
+ print("关闭浏览器")
diff --git a/scrapy/scrapy07/scrapy07/pipelines.py b/scrapy/scrapy07/scrapy07/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..031e76ff285469aa71727c34bbdaddc20abfaf2c
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/pipelines.py
@@ -0,0 +1,13 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+
+
+class BossPipeline:
+ def process_item(self, item, spider):
+ return item
diff --git a/scrapy/scrapy07/scrapy07/request.py b/scrapy/scrapy07/scrapy07/request.py
new file mode 100644
index 0000000000000000000000000000000000000000..844e40669118cbc5c8809aedcc317b95f0a65acc
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/request.py
@@ -0,0 +1,6 @@
+from scrapy import Request
+
+
+class SeleniumRequest(Request):
+ # 继承Request. 导致, 当前的SeleniumRequest在功能上和Request一样的
+ pass
diff --git a/scrapy/scrapy07/scrapy07/settings.py b/scrapy/scrapy07/scrapy07/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..3388ad917a18814a3e32fd8b30c4e3b3779c26e6
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/settings.py
@@ -0,0 +1,91 @@
+# Scrapy settings for scrapy07 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy07'
+
+SPIDER_MODULES = ['scrapy07.spiders']
+NEWSPIDER_MODULE = 'scrapy07.spiders'
+
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = 'scrapy07 (+http://www.yourdomain.com)'
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+LOG_LEVEL = "WARNING"
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# 'scrapy07.middlewares.BossSpiderMiddleware': 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+DOWNLOADER_MIDDLEWARES = {
+ # 由于我们想替换掉原来的downloader, 原来的中间件其实对我来说没有意义
+ # 原来的中间件最小的优先级是100
+ 'scrapy07.middlewares.BossDownloaderMiddleware': 99,
+}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+#ITEM_PIPELINES = {
+# 'scrapy07.pipelines.BossPipeline': 300,
+#}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy07/scrapy07/spiders/__init__.py b/scrapy/scrapy07/scrapy07/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy07/scrapy07/spiders/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy07/scrapy07/spiders/__pycache__/__init__.cpython-311.pyc
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diff --git a/scrapy/scrapy07/scrapy07/spiders/__pycache__/zhipin.cpython-311.pyc b/scrapy/scrapy07/scrapy07/spiders/__pycache__/zhipin.cpython-311.pyc
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index 0000000000000000000000000000000000000000..ec836fdb99296f3a1e6f272cf12ae70bc467c022
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diff --git a/scrapy/scrapy07/scrapy07/spiders/zhipin.py b/scrapy/scrapy07/scrapy07/spiders/zhipin.py
new file mode 100644
index 0000000000000000000000000000000000000000..f0dd1eb3b4b3136c1f31d6509cc140978041c4a6
--- /dev/null
+++ b/scrapy/scrapy07/scrapy07/spiders/zhipin.py
@@ -0,0 +1,33 @@
+import scrapy
+from scrapy07.request import SeleniumRequest
+
+class BeijingSpider(scrapy.Spider):
+ name = 'zhipin'
+ allowed_domains = ['zhipin.com']
+ start_urls = ['https://www.zhipin.com/job_detail/?query=python&city=101010100&industry=&position=beijing']
+
+ def start_requests(self):
+ yield SeleniumRequest(
+ url=BeijingSpider.start_urls[0],
+ callback=self.parse,
+ )
+
+ def parse(self, resp, **kwargs):
+ """解析数据"""
+ li_list = resp.xpath('//*[@id="main"]/div/div[3]/ul/li')
+ for li in li_list:
+ href = li.xpath("./div[1]/div[1]/div[1]/div[1]/div[1]/span[1]/a[1]/@href").extract_first()
+ name = li.xpath("./div[1]/div[1]/div[1]/div[1]/div[1]/span[1]/a[1]/text()").extract_first()
+
+ print(name, href)
+ print(resp.urljoin(href))
+
+ # 发送 SeleniumRequest
+ yield SeleniumRequest(
+ url=resp.urljoin(href),
+ callback=self.parse_detail, # 回调函数
+ )
+
+ def parse_detail(self, resp, **kwargs):
+ """再次解析数据"""
+ print("招聘人", resp.xpath('//*[@id="main"]/div[3]/div/div[2]/div[1]/h2').extract())
diff --git a/scrapy/scrapy08/__init__.py b/scrapy/scrapy08/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy08/scrapy.cfg b/scrapy/scrapy08/scrapy.cfg
new file mode 100644
index 0000000000000000000000000000000000000000..6233702bd2b3306dc98cf55428c5b0cec0858984
--- /dev/null
+++ b/scrapy/scrapy08/scrapy.cfg
@@ -0,0 +1,11 @@
+# Automatically created by: scrapy startproject
+#
+# For more information about the [deploy] section see:
+# https://scrapyd.readthedocs.io/en/latest/deploy.html
+
+[settings]
+default = scrapy08.settings
+
+[deploy]
+#url = http://localhost:6800/
+project = scrapy08
diff --git a/scrapy/scrapy08/scrapy08/__init__.py b/scrapy/scrapy08/scrapy08/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/scrapy/scrapy08/scrapy08/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy08/scrapy08/__pycache__/__init__.cpython-311.pyc
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diff --git a/scrapy/scrapy08/scrapy08/__pycache__/middlewares.cpython-311.pyc b/scrapy/scrapy08/scrapy08/__pycache__/middlewares.cpython-311.pyc
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diff --git a/scrapy/scrapy08/scrapy08/__pycache__/settings.cpython-311.pyc b/scrapy/scrapy08/scrapy08/__pycache__/settings.cpython-311.pyc
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index 0000000000000000000000000000000000000000..dc94621059e79fc63345428c6f000a833161bb0a
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diff --git a/scrapy/scrapy08/scrapy08/items.py b/scrapy/scrapy08/scrapy08/items.py
new file mode 100644
index 0000000000000000000000000000000000000000..4cd1999613283ab524c723b45922efad54298f43
--- /dev/null
+++ b/scrapy/scrapy08/scrapy08/items.py
@@ -0,0 +1,12 @@
+# Define here the models for your scraped items
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/items.html
+
+import scrapy
+
+
+class ChaojiyingItem(scrapy.Item):
+ # define the fields for your item here like:
+ # name = scrapy.Field()
+ pass
diff --git a/scrapy/scrapy08/scrapy08/middlewares.py b/scrapy/scrapy08/scrapy08/middlewares.py
new file mode 100644
index 0000000000000000000000000000000000000000..4442e05058228289bfb5ee1ebc5fb120f0dc4239
--- /dev/null
+++ b/scrapy/scrapy08/scrapy08/middlewares.py
@@ -0,0 +1,126 @@
+# Define here the models for your spider middleware
+#
+# See documentation in:
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+from scrapy import signals
+
+# useful for handling different item types with a single interface
+from itemadapter import is_item, ItemAdapter
+from selenium.webdriver import Chrome
+from selenium.webdriver.common.by import By
+import requests
+import time
+import json
+
+
+class ChaojiyingSpiderMiddleware:
+ # Not all methods need to be defined. If a method is not defined,
+ # scrapy acts as if the spider middleware does not modify the
+ # passed objects.
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ # This method is used by Scrapy to create your spiders.
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_spider_input(self, response, spider):
+ # Called for each response that goes through the spider
+ # middleware and into the spider.
+
+ # Should return None or raise an exception.
+ return None
+
+ def process_spider_output(self, response, result, spider):
+ # Called with the results returned from the Spider, after
+ # it has processed the response.
+
+ # Must return an iterable of Request, or item objects.
+ for i in result:
+ yield i
+
+ def process_spider_exception(self, response, exception, spider):
+ # Called when a spider or process_spider_input() method
+ # (from other spider middleware) raises an exception.
+
+ # Should return either None or an iterable of Request or item objects.
+ pass
+
+ def process_start_requests(self, start_requests, spider):
+ # Called with the start requests of the spider, and works
+ # similarly to the process_spider_output() method, except
+ # that it doesn’t have a response associated.
+
+ # Must return only requests (not items).
+ for r in start_requests:
+ yield r
+
+ def spider_opened(self, spider):
+ spider.logger.info('Spider opened: %s' % spider.name)
+
+
+class ChaojiyingDownloaderMiddleware:
+
+ @classmethod
+ def from_crawler(cls, crawler):
+ """配置中间件"""
+ s = cls()
+ crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
+ return s
+
+ def process_request(self, request, spider):
+ """处理请求"""
+
+ # 判断是否有cookie
+ if not request.cookies:
+ # 没有cookie就设置一下
+ request.cookies = self.cookie
+ return None
+
+ def spider_opened(self, spider):
+ """开启spider时，执行该函数"""
+
+ # 开启浏览器
+ web = Chrome()
+
+ # 发送请求
+ web.get("https://www.chaojiying.com/user/login/")
+
+ # 输入电话号码
+ web.find_element(by=By.XPATH, value='/html/body/div[3]/div/div[3]/div[1]/form/p[1]/input').send_keys('18614075987')
+
+ # 输入密码
+ web.find_element(by=By.XPATH, value='/html/body/div[3]/div/div[3]/div[1]/form/p[2]/input').send_keys('q6035945')
+
+ # 查找 验证码图片地址
+ img = web.find_element(by=By.XPATH, value='/html/body/div[3]/div/div[3]/div[1]/form/div/img')
+
+ # 识别验证码
+ verify_code = self.base64_api("q6035945", "q6035945", img.screenshot_as_base64, 3)
+
+ # 输入验证码
+ web.find_element(by=By.XPATH, value='/html/body/div[3]/div/div[3]/div[1]/form/p[3]/input').send_keys(verify_code)
+
+ # 点击登录
+ web.find_element(by=By.XPATH, value="/html/body/div[3]/div/div[3]/div[1]/form/p[4]/input").click()
+
+ # 画面显示 2秒
+ time.sleep(2)
+
+ # 读取 cookie, web.get_cookies() = [{name: k1, value: v1}, {name: k2, value: v2}...]
+ self.cookie = {item['name']: item['value'] for item in web.get_cookies()}
+ web.close()
+
+ def base64_api(self, uname, pwd, b64, typeid):
+ """识别验证码"""
+ # 发送 POST请求
+ data = {"username": uname, "password": pwd, "typeid": typeid, "image": b64}
+
+ # 返回验证码
+ result = json.loads(requests.post("http://api.ttshitu.com/predict", json=data).text)
+ if result['success']:
+ return result["data"]["result"]
+ else:
+ return result["message"]
diff --git a/scrapy/scrapy08/scrapy08/pipelines.py b/scrapy/scrapy08/scrapy08/pipelines.py
new file mode 100644
index 0000000000000000000000000000000000000000..592e667386ebd507eb8040ec7cb4f25debfbb147
--- /dev/null
+++ b/scrapy/scrapy08/scrapy08/pipelines.py
@@ -0,0 +1,13 @@
+# Define your item pipelines here
+#
+# Don't forget to add your pipeline to the ITEM_PIPELINES setting
+# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+
+
+# useful for handling different item types with a single interface
+from itemadapter import ItemAdapter
+
+
+class ChaojiyingPipeline:
+ def process_item(self, item, spider):
+ return item
diff --git a/scrapy/scrapy08/scrapy08/settings.py b/scrapy/scrapy08/scrapy08/settings.py
new file mode 100644
index 0000000000000000000000000000000000000000..b6d12da7b973db0cb0ed8a45d563dbf2e57b2a46
--- /dev/null
+++ b/scrapy/scrapy08/scrapy08/settings.py
@@ -0,0 +1,89 @@
+# Scrapy settings for scrapy08 project
+#
+# For simplicity, this file contains only settings considered important or
+# commonly used. You can find more settings consulting the documentation:
+#
+# https://docs.scrapy.org/en/latest/topics/settings.html
+# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+
+BOT_NAME = 'scrapy08'
+
+SPIDER_MODULES = ['scrapy08.spiders']
+NEWSPIDER_MODULE = 'scrapy08.spiders'
+
+
+# Crawl responsibly by identifying yourself (and your website) on the user-agent
+#USER_AGENT = 'scrapy08 (+http://www.yourdomain.com)'
+
+# Obey robots.txt rules
+ROBOTSTXT_OBEY = False
+LOG_LEVEL = "WARNING"
+
+# Configure maximum concurrent requests performed by Scrapy (default: 16)
+#CONCURRENT_REQUESTS = 32
+
+# Configure a delay for requests for the same website (default: 0)
+# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
+# See also autothrottle settings and docs
+#DOWNLOAD_DELAY = 3
+# The download delay setting will honor only one of:
+#CONCURRENT_REQUESTS_PER_DOMAIN = 16
+#CONCURRENT_REQUESTS_PER_IP = 16
+
+# Disable cookies (enabled by default)
+#COOKIES_ENABLED = False
+
+# Disable Telnet Console (enabled by default)
+#TELNETCONSOLE_ENABLED = False
+
+# Override the default request headers:
+#DEFAULT_REQUEST_HEADERS = {
+# 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+# 'Accept-Language': 'en',
+#}
+
+# Enable or disable spider middlewares
+# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
+#SPIDER_MIDDLEWARES = {
+# 'scrapy08.middlewares.ChaojiyingSpiderMiddleware': 543,
+#}
+
+# Enable or disable downloader middlewares
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
+DOWNLOADER_MIDDLEWARES = {
+ 'scrapy08.middlewares.ChaojiyingDownloaderMiddleware': 543,
+}
+
+# Enable or disable extensions
+# See https://docs.scrapy.org/en/latest/topics/extensions.html
+#EXTENSIONS = {
+# 'scrapy.extensions.telnet.TelnetConsole': None,
+#}
+
+# Configure item pipelines
+# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
+#ITEM_PIPELINES = {
+# 'scrapy08.pipelines.ChaojiyingPipeline': 300,
+#}
+
+# Enable and configure the AutoThrottle extension (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
+#AUTOTHROTTLE_ENABLED = True
+# The initial download delay
+#AUTOTHROTTLE_START_DELAY = 5
+# The maximum download delay to be set in case of high latencies
+#AUTOTHROTTLE_MAX_DELAY = 60
+# The average number of requests Scrapy should be sending in parallel to
+# each remote server
+#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
+# Enable showing throttling stats for every response received:
+#AUTOTHROTTLE_DEBUG = False
+
+# Enable and configure HTTP caching (disabled by default)
+# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
+#HTTPCACHE_ENABLED = True
+#HTTPCACHE_EXPIRATION_SECS = 0
+#HTTPCACHE_DIR = 'httpcache'
+#HTTPCACHE_IGNORE_HTTP_CODES = []
+#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
diff --git a/scrapy/scrapy08/scrapy08/spiders/__init__.py b/scrapy/scrapy08/scrapy08/spiders/__init__.py
new file mode 100644
index 0000000000000000000000000000000000000000..ebd689ac51d69c5e1dbbe80083c2b20a39f8bb79
--- /dev/null
+++ b/scrapy/scrapy08/scrapy08/spiders/__init__.py
@@ -0,0 +1,4 @@
+# This package will contain the spiders of your Scrapy project
+#
+# Please refer to the documentation for information on how to create and manage
+# your spiders.
diff --git a/scrapy/scrapy08/scrapy08/spiders/__pycache__/__init__.cpython-311.pyc b/scrapy/scrapy08/scrapy08/spiders/__pycache__/__init__.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..214835511977067f57383f60bb9af0529c400ceb
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diff --git a/scrapy/scrapy08/scrapy08/spiders/__pycache__/login.cpython-311.pyc b/scrapy/scrapy08/scrapy08/spiders/__pycache__/login.cpython-311.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..ffc5bed22d5ab6d8f8911f035ca3e02501972fb5
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diff --git a/scrapy/scrapy08/scrapy08/spiders/login.py b/scrapy/scrapy08/scrapy08/spiders/login.py
new file mode 100644
index 0000000000000000000000000000000000000000..ee261332e30d90412711d6be15dfdf7cd8d4e1d3
--- /dev/null
+++ b/scrapy/scrapy08/scrapy08/spiders/login.py
@@ -0,0 +1,10 @@
+import scrapy
+import time
+
+class LoginSpider(scrapy.Spider):
+ name = 'login'
+ allowed_domains = ['scrapy08.com']
+ start_urls = ['https://www.chaojiying.com/user/']
+
+ def parse(self, response):
+ print(response.text)