爬取iciba.com的翻译数据

ICIBA接口调研

访问ICIBA网站接口默认传参URL

http://www.iciba.com/index.php?callback=jQuery190037237954499612624_1521877397217&a=getWordMean&c=search&list=1,2,3,4,5,8,9,10,12,13,14,15,18,21,22,24,3003,3004,3005&word=test&_=1521877397218

接口传参意义，分析传参含义

1. callback：iciba JQuery回调函数形式返回到该网站

2. a=getWordMean：获取单词参数

3. c=search：查询单词参数

4. word：传递所需要的单词

5. list=1,2,3,4,5,8,9,10,12,13,14,15,18,21,22,24,3003,3004,3005

   1. 1参数显示基础单词信息，路径：JSON.baesInfo
   2. 2参数显示单词分析信息，路径：JSON.sameAnalysis
   3. 3柯林斯高阶英汉双解学习词典，路径：JSON.collins
   4. 4英英词典，路径：JSON.ee_mean
   5. 5行业词典，路径：JSON.trade_means
   6. 8双语例句，路径：JSON.sentence
   7. 9（1,9组合会出现网络释义，路径JSON.netmean），路径：JSON.baesInfo
   8. 10权威例句，路径：JSON.auth_sentence
   9. 12释义变形（此参数并没有显示在页面里），路径：JSON.synonym
   10. 14词组和句型，路径：JSON.phrase
   11. 15词根词缀，路径：JSON.stems_affixes
   12. 18百度百科，路径：JSON.encyclopedia
   13. 21四级真题，路径：JSON.cetFour
   14. 3003词性、中英例句、翻译并未在页面展示 ，路径：JSON.bidec
   15. 3005句式用法，路径：JSON.jushi
   16. 如果list不传参或者输入0默认显示所有信息

产品需求数据

• 输入单词：JSON.baesInfo.word_name
• 音标+翻译：JSON.baesInfo.symbols
• 变形：JSON.baesInfo.exchange
• 双语例句：JSON.sentence
• 句式用法：JSON.jushi
• 权威例句：JSON.auth_sentence

此时list参数传参值为：1,6,8,10,3005 ，减少无用参数，优化请求速度。

http://www.iciba.com/index.php?&a=getWordMean&c=search&list=1,6,8,10,3005&word=test

数据库设计

数据表名：dic_auth_sentence注释：权威例句表

字段	数据类型	注释	类型
id	int(11)	权威例句id	主键
content	varchar(255)	内容
link	varchar(255)	相关链接
source	varchar(50)	来源
word_id	int(11)	单词id

数据表名：dic_base_info注释：音标表

字段	数据类型	注释	类型
id	int(11)	单词id	主键
word	varchar(128)	单词
ph_en	varchar(255)	英 音标
ph_am	varchar(255)	美 音标
ph_en_mp3	varchar(255)	英 音标mp3
ph_am_mp3	varchar(255)	美 音标mp3
create_time	datetime	创建时间

数据表名：dic_base_info_test注释： 音标表

字段	数据类型	注释	类型
id	int(11)	单词id	主键
word	varchar(128)	单词
ph_en	varchar(255)	英 音标
ph_am	varchar(255)	美 音标
ph_en_mp3	varchar(255)	英 音标mp3
ph_am_mp3	varchar(255)	美 音标mp3
create_time	datetime	创建时间

数据表名：dic_exchange注释： 单词变形表

字段	数据类型	注释	类型
word_id	int(11)	单词id	主键
word_pl	varchar(128)	复数
word_past	varchar(128)	过去式
word_done	varchar(128)	过去分词
word_ing	varchar(128)	现在分词
word_third	varchar(128)	第三人称单数
word_er	varchar(128)	比较级
word_est	varchar(128)	最高级
word_prep	varchar(128)	代词
word_adv	varchar(128)	副词
word_verb	varchar(128)	动词
word_noun	varchar(128)	名词
word_adj	varchar(128)	形容词
word_conn	varchar(128)	系连词

数据表名：dic_jushi注释： 句式用法表

字段	数据类型	注释	类型
id	int(11)	句式用法id	主键
word_id	int(11)	单词id
english	varchar(255)	英语例句
chinese	varchar(255)	中文例句

数据表名：dic_parts注释：翻译表

字段	数据类型	注释	类型
id	int(11)	词性id	主键
word_id	int(11)	单词id
part	varchar(50)	词性
means	varchar(255)	释义

数据表名：dic_sentence注释：双语例句表

字段	数据类型	注释	类型
id	int(11)	例句id	主键
word_id	int(11)	单词id
english	varchar(255)	例句英文
chinese	varchar(255)	例句中文

数据表名：dic_temp_word注释： 跑批单词

字段	数据类型	注释	类型
id	int(11)	单词id	主键
word	varchar(255)	单词
is_set	tinyint(1) unsigned zerofill	0未跑1跑过

JAVA实现方案

• HTTPUtils：请求接口，获取资源

String url = "http://www.iciba.com/index.php&a=getWordMean&c=search&list=1,6,8,10,3005&word=";
			//get请求翻译API
            try {
                wordMean = java.net.URLEncoder.encode(wordMean, "UTF-8");//把特殊字符转码
            } catch (UnsupportedEncodingException e) {
                e.printStackTrace();
            }
            final HttpResponse response = WS.url(url + wordMean).get();//get请求url
            final String res = WS.getResponseAsString(response);

• Fastjson：解析获取到的JSON，找到所需要数据的路径

       JSONObject jsonObject = JSON.parseObject(res);
            int errno = (int) JSONPath.eval(jsonObject, "$.errno");
            if (errno == 404) {
                 return FAIL;
            }
JSONObject symbols = (JSONObject) JSONPath.eval(jsonObject, "$.baesInfo.symbols[0]");//音标+mp3
JSONObject exchange = (JSONObject) JSONPath.eval(jsonObject, "$.baesInfo.exchange");//变形单词
ArrayList<JSONObject> sentences = (ArrayList<JSONObject>) JSONPath.eval(jsonObject, "$.sentence[0:2]");//双语例句
ArrayList<JSONObject> jushi = (ArrayList<JSONObject>) JSONPath.eval(jsonObject, "$.jushi[0:2]");//句式语法
ArrayList<JSONObject> authSentence = (ArrayList<JSONObject>) JSONPath.eval(jsonObject, "$.auth_sentence[0:2]");//权威例句
String wordName = (String) JSONPath.eval(jsonObject, "$.baesInfo.word_name");//单词名

• 遍历获取到的数据并存入MYSQL

            int wordId;
            if (wordMeanMapper.checkWord(wordName) != null) {
                ReturnT.FAIL.setMsg("单词已经存在");
                return FAIL;
            }
            wordMeanMapper.insertWord(wordName);
            wordId = (int) wordMeanMapper.checkWord(wordName).get("id");
            try {
                if (symbols != null) {//没有音标一定没有该单词的释义，直接取得单词的网络翻译
                    //发音音标
                    String ph_en = symbols.getString("ph_en");// 英 音标
                    String ph_am = symbols.getString("ph_am");//美 音标
//                String ph_other = symbols.getString("ph_other");
                    String ph_en_mp3 = symbols.getString("ph_en_mp3");//英 音标发音
                    String ph_am_mp3 = symbols.getString("ph_am_mp3");//美 音标发音
                    String ph_tts_mp3 = symbols.getString("ph_tts_mp3");//tts原生 发音
                    wordMeanMapper.insertSymbols(wordId, ph_en, ph_am, ph_en_mp3, ph_am_mp3, ph_tts_mp3);
                    //变形词汇
                    String reg = "[\\[\\]\"]";
                    String word_pl = exchange.getString("word_pl").replaceAll(reg, "");
                    String word_third = exchange.getString("word_third").replaceAll(reg, "");
                    String word_past = exchange.getString("word_past").replaceAll(reg, "");
                    String word_done = exchange.getString("word_done").replaceAll(reg, "");
                    String word_ing = exchange.getString("word_ing").replaceAll(reg, "");
                    String word_er = exchange.getString("word_er").replaceAll(reg, "");
                    String word_est = exchange.getString("word_est").replaceAll(reg, "");
                    String word_prep = exchange.getString("word_prep").replaceAll(reg, "");
                    String word_adv = exchange.getString("word_adv").replaceAll(reg, "");
                    String word_verb = exchange.getString("word_verb").replaceAll(reg, "");
                    String word_noun = exchange.getString("word_noun").replaceAll(reg, "");
                    String word_adj = exchange.getString("word_adj").replaceAll(reg, "");
                    String word_conn = exchange.getString("word_conn").replaceAll(reg, "");
                    wordMeanMapper.insertExchange(wordId, word_pl, word_past, word_done, word_ing, word_third, word_er, word_est, word_prep, word_adv, word_verb, word_noun, word_adj, word_conn
                    );
                    //词性翻译
                    JSONArray parts = symbols.getJSONArray("parts");
                    for (Object partObj : parts) {
                        JSONObject partJSONObject = (JSONObject) partObj;
                        String means = partJSONObject.getString("means");
                        means = means.replaceAll(reg, "");
                        String part = partJSONObject.getString("part");
                        wordMeanMapper.insertParts(part, means, wordId);
                    }
                } else {
                    String translateResult = (String) JSONPath.eval(jsonObject, "$.baesInfo.translate_result");
                    wordMeanMapper.updateTranslateResult(wordMean, translateResult);
                }
            } catch (Exception e) {
                e.printStackTrace();
                return FAIL;
            }
            //双语例句
            for (JSONObject sentence : sentences) {
                String networkEN = sentence.getString("Network_en");
                String networkCN = sentence.getString("Network_cn");
                String mp3 = sentence.getString("tts_mp3");
                String mp3Size = sentence.getString("tts_size");
                wordMeanMapper.insertSentence(networkEN, networkCN, mp3, mp3Size, wordId);
            }
            //句式用法
            for (JSONObject jushiObj : jushi) {
                String english = jushiObj.getString("english");
                String chinese = jushiObj.getString("chinese");
                String mp3 = jushiObj.getString("mp3");
                wordMeanMapper.insertJushi(english, chinese, mp3, wordId);
            }
            //权威例句
            for (JSONObject authSentenceObj : authSentence) {
                String content = authSentenceObj.getString("content");
                String link = authSentenceObj.getString("link");
                String source = authSentenceObj.getString("source");
                String mp3 = authSentenceObj.getString("tts_mp3");
                String mp3Size = authSentenceObj.getString("tts_size");
                wordMeanMapper.insertAuthSentence(content, link, source, mp3, mp3Size, wordId);
            }

Mapper

   @Insert("INSERT INTO fanyi_word(word)VALUES(#{word})")//插入传入的单词
   int insertWord(String word);
   @Insert("UPDATE fanyi_word SET translate_result=#{translate_result} WHERE word=#{word}")
   int updateTranslateResult(@Param("word")String word,@Param("translate_result")String translateResult);//网络翻译结果

   @Insert("INSERT INTO fanyi_sentence(english,chinese,tts_mp3,tts_size,word_id) VALUES(#{english},#{chinese},#{tts_mp3},#{tts_size},#{word_id})")//插入例句
   int insertSentence(@Param("english") String english,
                      @Param("chinese") String chinese,
                      @Param("tts_mp3") String tts_mp3,
                      @Param("tts_size") String tts_size,
                      @Param("word_id") int wordId);

   @Insert("INSERT INTO fanyi_auth_sentence(content,link,source,tts_mp3,tts_size,word_id)VALUES(#{content},#{link},#{source},#{tts_mp3},#{tts_size},#{word_id})")//权威例句
   int insertAuthSentence(@Param("content") String content,
                          @Param("link") String link,
                          @Param("source") String source,
                          @Param("tts_mp3") String tts_mp3,
                          @Param("tts_size") String tts_size,
                          @Param("word_id") int wordId);

   @Insert("INSERT INTO fanyi_jushi(english,chinese,mp3,word_id)VALUES(#{english},#{chinese},#{mp3},#{word_id})")//句式
   int insertJushi(@Param("english") String english,
                   @Param("chinese") String chinese,
                   @Param("mp3") String mp3,
                   @Param("word_id") int wordId);

   @Insert("INSERT INTO fanyi_symbols(word_id,ph_en,ph_am,ph_en_mp3,ph_am_mp3,ph_tts_mp3)VALUES(#{word_id},#{ph_en},#{ph_am},#{ph_en_mp3},#{ph_am_mp3},#{ph_tts_mp3})")//音标资源
   int insertSymbols(@Param("word_id") int wordId,
                     @Param("ph_en") String ph_en,
                     @Param("ph_am") String ph_am,
                     @Param("ph_en_mp3") String ph_en_mp3,
                     @Param("ph_am_mp3") String ph_am_mp3,
                     @Param("ph_tts_mp3") String ph_tts_mp3);

   @Insert("INSERT INTO fanyi_parts(part,means,word_id)VALUES(#{part},#{means},#{word_id})")
//翻译+词性
   int insertParts(@Param("part")String part,
                   @Param("means")String means,
                   @Param("word_id")int wordId);
   @Insert("INSERT INTO fanyi_exchange (`word_id`, `word_pl`, `word_past`, `word_done`, `word_ing`, `word_third`, `word_er`, `word_est`, `word_prep`, `word_adv`, `word_verb`, `word_noun`, `word_adj`, `word_conn`)" +
           "VALUES(#{word_id},#{word_pl},#{word_past},#{word_done},#{word_ing},#{word_third},#{word_er},#{word_est},#{word_prep},#{word_adv},#{word_verb},#{word_noun},#{word_adj},#{word_conn})")//单词变形
   int insertExchange(@Param("word_id")int wordId,
                      @Param("word_pl")String word_pl,
                      @Param("word_past")String word_past,
                      @Param("word_done")String word_done,
                      @Param("word_ing")String word_ing,
                      @Param("word_third")String word_third,
                      @Param("word_er")String word_er,
                      @Param("word_est")String word_est,
                      @Param("word_prep")String word_prep,
                      @Param("word_adv")String word_adv,
                      @Param("word_verb")String word_verb,
                      @Param("word_noun")String word_noun,
                      @Param("word_adj")String word_adj,
                      @Param("word_conn")String word_conn);

   @Select("SELECT word,id FROM fanyi_word WHERE word = #{word}")//检查单词是否存在
   Map checkWord(String word);

Python 实现方案

import sys
import io
import json
import jsonpath

from utils import get_redis_conn
from examples.iciba.crawler import Crawler
from utils import mysql_util

sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf8')  # 为了xxl-job输出不出现乱码，格式化为utf8

host = 'http://www.iciba.com/index.php?&a=getWordMean&c=search&list=1,6,8,10,3005&word='
waiting_set = 'iciba:seeds:to_crawl'
seeds_all = 'iciba:seeds:all'
info_set = 'iciba:info:wordmsg'

# Not considering concurrent security
common_crawler = Crawler()


def init_db():
    redis_client = get_redis_conn(db=2)
    return redis_client


def get_info(word):
    """get user info"""
    url = host + word
    html = common_crawler.get(url)
    if not html:
        return
    py_obj = json.loads(html.encode('utf8'))
    try:
        word_name = jsonpath.jsonpath(py_obj, "$.baesInfo.word_name")  # 单词名称
        exchanges = jsonpath.jsonpath(py_obj, "$.baesInfo.exchange")  # 变形单词
        symbols = jsonpath.jsonpath(py_obj, "$.baesInfo.symbols[0]")  # 音标+mp3
        parts = jsonpath.jsonpath(py_obj, "$.baesInfo.symbols[0].parts")  # 翻译词性
        translate_result = jsonpath.jsonpath(py_obj, "$.baesInfo.translate_result")  # 网络翻译
        is_errno = jsonpath.jsonpath(py_obj, "$.errno")  # 单词是否存在

        auth_sentence = jsonpath.jsonpath(py_obj, "$.auth_sentence[:3]")  # 权威例句
        jushi = jsonpath.jsonpath(py_obj, "$.jushi[:3]")  # 句式语法
        sentence = jsonpath.jsonpath(py_obj, "$.sentence[:3]")  # 双语例句

        if translate_result or is_errno[0] == 404:  # 单词是否错误翻译，使用网络翻译，返回单词id
            print('单词不存在，单词出错')
            return
        word_id = mysql_util.insert_word(word_name[0])
        if not word_id: #如果单词已经存在则直接跳出
            return
        for symbol in symbols: #发音音标
            mysql_util.insert_symbols(word_id, symbol['ph_en'], symbol['ph_am'], symbol['ph_en_mp3'],
                                      symbol['ph_am_mp3'], symbol['ph_tts_mp3'])

        for part in parts[0]: # 词性翻译
            mysql_util.insert_parts(word_id, part['part'], part['means'])
        if  auth_sentence:
            for i in auth_sentence:  # 单词权威例句
                mysql_util.insert_auth_sentence(i['content'], i['link'], i['source'], i['tts_mp3'], i['tts_size'], word_id)
        if  jushi:
            for i in jushi:  # 句式
                mysql_util.insert_jushi(i['english'], i['chinese'], i['mp3'], word_id)
        if  sentence:
            for i in sentence:  # 双语例句
                mysql_util.insert_sentence(i['Network_en'], i['Network_cn'], i['tts_mp3'], i['tts_size'], word_id)

        for exchange in exchanges: # 单词变形 把空数组赋值为NULL，并存入
            for key,value in exchange.items():
                if not value:
                    exchange[key]=None

            mysql_util.insert_exchange(word_id, exchange['word_pl'], exchange['word_past'], exchange['word_done'],
                                       exchange['word_ing'], exchange['word_third'], exchange['word_er'],
                                       exchange['word_est'], exchange['word_prep'], exchange['word_adv'],
                                       exchange['word_verb'], exchange['word_noun'], exchange['word_adj'],
                                       exchange['word_conn'])

    except Exception as e:
        print(e)
        return

    return html


def start():
    redis_client = init_db()
    while not redis_client.scard(waiting_set):
        # block if there is no seed in waitting_set
        print("%s里的单词全部跑完，等待下次跑批" % waiting_set)
        return

    # fetch seeds from waitting_set
    word = redis_client.spop(waiting_set).decode()

    print("正在获取%s单词数据中……" % word)
    word_data = get_info(word)
    redis_client.hset(info_set, word, word_data)
    # redis_client.sadd(info_set, user)
    print("%s单词已经保存" % word)


def xxl_job(): # xxl_job调用的函数  waiting_set的单词从Redis里获取然后跑入到MySQL
    redis_conn = init_db()
    while True:
        if not redis_conn.scard(waiting_set):
            print("所有单词已经跑完，等待下次跑批")
            break
        start()


if __name__ == '__main__':
    init_seeds = ['test'] # 直接运行测试数据
    redis_conn = init_db()
    redis_conn.sadd(waiting_set, *init_seeds)
    redis_conn.sadd(seeds_all, *init_seeds)
    while True:
        start()

MySQL_util.py

from config.settings import (MYSQL_DATABASE, MYSQL_HOST, MYSQL_PASSWORD, MYSQL_PROT, MYSQL_USER, MYSQL_CHARSET)
import pymysql.cursors


def get_conn_mysql():
    connection = pymysql.connect(host=MYSQL_HOST,
                                 user=MYSQL_USER,
                                 port=MYSQL_PROT,
                                 passwd=MYSQL_PASSWORD,
                                 db=MYSQL_DATABASE,
                                 charset=MYSQL_CHARSET)
    return connection


def insert_word(word):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_word = "INSERT INTO `fanyi_word` (`id`,`word`) VALUES (%s, %s)"
        check_word = "SELECT word FROM `fanyi_word` WHERE word=%s LIMIT 1"
        result = cursor.execute(check_word, word)  # 检查表内是否有该单词
        if not result:
            cursor.execute(insert_word, (cursor.lastrowid, word))
            connection.commit()
            return cursor.lastrowid
        else:
            return
    finally:
        connection.close()


def insert_symbols(word_id, ph_en, ph_am, ph_en_mp3, ph_am_mp3, ph_tts_mp3):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_symbols = "INSERT INTO `fanyi_symbols` (`word_id`, `ph_en`, `ph_am`, `ph_en_mp3`, `ph_am_mp3`, `ph_tts_mp3`) VALUES (%s, %s, %s, %s, %s, %s)"
        cursor.execute(insert_symbols, (word_id, ph_en, ph_am, ph_en_mp3, ph_am_mp3, ph_tts_mp3))
        connection.commit()
    finally:
        connection.close()


def insert_parts(word_id, part, means):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_parts = "INSERT INTO `fanyi_parts` (`part`, `means`, `word_id`) VALUES (%s, %s, %s)"
        means_str = ','.join(means)
        cursor.execute(insert_parts, (part, means_str, word_id))
        connection.commit()
    finally:
        connection.close()


def insert_sentence(english, chinese, tts_mp3, tts_size, word_id):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_sentence = "INSERT INTO `fanyi_sentence` (`english`, `chinese`, `tts_mp3`, `tts_size`, `word_id`) VALUES (%s, %s, %s,%s, %s)"
        cursor.execute(insert_sentence, (english, chinese, tts_mp3, tts_size, word_id))
        connection.commit()
    finally:
        connection.close()


def insert_jushi(english, chinese, mp3, word_id):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_jushi = "INSERT INTO `fanyi_jushi` (`english`, `chinese`, `mp3`, `word_id`) VALUES ( %s, %s,%s, %s)"
        cursor.execute(insert_jushi, (english, chinese, mp3, word_id))
        connection.commit()
    finally:
        connection.close()


def insert_auth_sentence(content, link, source, tts_mp3, tts_size, word_id):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_auth_sentence = "INSERT INTO `fanyi_auth_sentence` (`content`, `link`, `source`, `tts_mp3`, `tts_size`, `word_id`) VALUES (%s, %s,%s, %s,%s,%s)"
        cursor.execute(insert_auth_sentence, (content, link, source, tts_mp3, tts_size, word_id))
        connection.commit()
    finally:
        connection.close()


def insert_exchange(word_id, word_pl, word_past, word_done, word_ing, word_third, word_er, word_est, word_prep,
                    word_adv, word_verb, word_noun, word_adj, word_conn):
    try:
        connection = get_conn_mysql()
        cursor = connection.cursor()
        insert_exchange = "INSERT INTO `fanyi_exchange` (`word_id`, `word_pl`, `word_past`, `word_done`, `word_ing`, `word_third`, `word_er`, `word_est`, `word_prep`, `word_adv`, `word_verb`, `word_noun`, `word_adj`, `word_conn`) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"
        cursor.execute(insert_exchange, (
        word_id, word_pl, word_past, word_done, word_ing, word_third, word_er, word_est, word_prep, word_adv, word_verb,
        word_noun, word_adj, word_conn))
        connection.commit()
    finally:
        connection.close()

使用Spring Boot 对Redis缓存单词

package com.xxl.job.executor.mvc.controller;

import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.boot.autoconfigure.EnableAutoConfiguration;
import org.springframework.data.redis.RedisConnectionFailureException;
import org.springframework.data.redis.core.StringRedisTemplate;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.PathVariable;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod;
import org.springframework.web.bind.annotation.ResponseBody;

@Controller
@EnableAutoConfiguration
public class IndexController {

    @Autowired
    private StringRedisTemplate stringRedisTemplate;

    @RequestMapping(value = "/redis/addWord/{value}", method = RequestMethod.GET)
    @ResponseBody
    public String redisTest(@PathVariable String value) {
        String waitingSet = "iciba:seeds:to_crawl";
        String seedsAll = "iciba:seeds:all";
        try {
            stringRedisTemplate.opsForSet().add(waitingSet, value);
            stringRedisTemplate.opsForSet().add(seedsAll, value);
            return String.format("%s已经成功添加！", value);
        }catch (RedisConnectionFailureException e){
            e.printStackTrace();
            return "redis连接失败";
        }
    }
}

使用xxl-job调度中心执行

https://github.com/xuxueli/xxl-job

• Java ：在xxl-job里运行模式选择Bean模式
  使用Java版本在调度中心设置JobHandler执行器名称和，并执行器内添加注解

  @JobHandler(value="demoJobHandler")

• Python：使用GLUE（Python）模式

注：如果在Linux下Python有多个版本，可以在com.xxl.job.core.glue.GlueTypeEnum下修改脚本执行前缀，如：GLUE_PYTHON("GLUE(Python)", true, "python3.6", ".py")

GLUE(Python)模式代码：

#!/usr/bin/python3.6
# -*- coding: UTF-8 -*-
import time
import sys
print(sys.stdout)
sys.path.append('F:\\workspace\\haipproxy-0.1') # Windows下的项目路径，Linux下需要更换
from examples.iciba.iciba_spider import xxl_job
xxl_job()
exit(0)

使用haipproxy匿名代理爬取

https://github.com/SpiderClub/haipproxy

这个开源项目爬取一些免费的代理网站，获取代理IP地址，然后对这些IP进行筛选打分，打分策略针对各个IP请求成功率、响应速度、最近验证时间和是否匿名这四个维度。

这个项目的详细文档在github上的wiki里，我在配置一些Python环境和依赖踩了不少坑，为了用这个项目去特意学习了Python和Redis…