爬取诗词名句网数据并做简单数据分析
爬取诗词总量为二十九万两千六百零二条数据
一、爬虫编写
目标网站：诗词名句网
环境
window10；
python3.7；
scrapy框架；
mysql数据库;
数据库设计
根据要爬取的字段定义，爬取内容为诗词链接，简介，标题，作者，朝代，内容，注释，作者发表的文章数量，图片url
如图
1.创建项目和爬虫文件
scrapy startproject scmjw cd scmjw scrapy genspider scmj www.xxx.com
2.定义爬取字段
items.py
import scrapy
class ScmjwItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
table = ‘scmjw‘
url = scrapy.Field()
category = scrapy.Field()
title = scrapy.Field()
auther = scrapy.Field()
dynasty = scrapy.Field()
content = scrapy.Field()
contents = scrapy.Field()
amount = scrapy.Field()
beiyong1 = scrapy.Field()3.编写爬虫规则
scmj.py
# -*- coding: utf-8 -*-
import scrapy
from scmjw.items import ScmjwItem
class ScmjSpider(scrapy.Spider):
name = ‘scmj‘
# allowed_domains = [‘www.shicimingju.com‘]
start_urls = [‘http://www.shicimingju.com‘]
def parse(self, response):
list_urls = response.xpath(‘//div[@id="top_left_menu"]/ul/li‘)
for list_url in list_urls:
main_list = ‘http://www.shicimingju.com‘ + list_url.xpath(‘./a/@href‘).extract_first()
if ‘shicimark‘ in main_list:
print(main_list)
yield scrapy.Request(url=main_list,callback=self.get_list)
if ‘category‘ in main_list:
print(main_list)
yield scrapy.Request(url=main_list,callback=self.get_list_cate)
"""爬取分类类别"""
def get_list(self,response):
div_lists = response.xpath(‘//div[@class="mark_card"]‘)
for d in div_lists:
item = ScmjwItem()
next_url = ‘http://www.shicimingju.com‘ + d.xpath(‘./a/@href‘).extract_first()
images = d.xpath(‘./a/img/@src‘).extract_first()
item[‘beiyong1‘] = images
yield scrapy.Request(url=next_url,callback=self.get_cate,meta={‘item‘:item})
def get_cate(self,response):
item = response.meta[‘item‘]
next_urls = response.xpath(‘//a[contains(text(), "《") and contains(text(), "》")]‘)
item[‘amount‘] = response.xpath(‘//div[@class="card"]/h1/text()‘).re_first(‘\d+‘)
for n in next_urls:
next_url = ‘http://www.shicimingju.com‘ + n.xpath(‘./@href‘).extract_first()
yield scrapy.Request(url=next_url,callback=self.get_detail,meta={‘item‘:item})
self_urls = response.xpath(‘//a[contains(text(), "下一页")]/@href‘).extract_first()
if self_urls:
self_url = ‘http://www.shicimingju.com‘ + self_urls
yield scrapy.Request(url=self_url, callback=self.get_cate, meta={‘item‘: item})
def get_detail(self,response):
item = response.meta[‘item‘]
item[‘url‘] = response.request.url
item[‘category‘] = response.xpath(‘//div[@class="shici-mark"]/a/text()‘).extract_first()
item[‘title‘] = response.xpath(‘//div[@id="item_div"]/h1/text()‘).extract_first()
item[‘auther‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/a/text()‘).extract_first()
item[‘dynasty‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/text()‘).extract_first()
contents = response.xpath(‘//div[@class="item_content"]//text()‘).extract()
content = ‘‘
for c in contents:
content += c.strip() + ‘\n‘
item[‘content‘] = content
shangxi_contents = response.xpath(‘//div[@class="shangxi_content"]//text()‘).extract()
contents = ‘‘
for s in shangxi_contents:
contents += s.strip()
item[‘contents‘] = contents
yield item
"""爬取作者类别"""
def get_list_cate(self,response):
div_lists = response.xpath(‘//div[@class="card zuozhe_card"]‘)
for d in div_lists:
next_url = ‘http://www.shicimingju.com‘ + d.xpath(‘./div[@class="zuozhe_list_item"]/h3/a/@href‘).extract_first()
yield scrapy.Request(url=next_url,callback=self.get_zuozhe)
self_urls = response.xpath(‘//a[contains(text(), "下一页")]/@href‘).extract_first()
if self_urls:
self_url = ‘http://www.shicimingju.com‘ + self_urls
yield scrapy.Request(url=self_url, callback=self.get_list_cate)
def get_zuozhe(self,response):
item = ScmjwItem()
item[‘amount‘] = response.xpath(‘//div[@class="card shici_card"]/h1/text()‘).re_first(‘\d+‘)
next_urls = response.xpath(‘//div[@class="shici_list_main"]‘)
for n in next_urls:
next_url = ‘http://www.shicimingju.com‘ + n.xpath(‘./h3/a/@href‘).extract_first()
yield scrapy.Request(url=next_url,callback=self.get_z_detail,meta={‘item‘:item})
self_urls = response.xpath(‘//a[contains(text(), "下一页")]/@href‘).extract_first()
if self_urls:
self_url = ‘http://www.shicimingju.com‘ + self_urls
yield scrapy.Request(url=self_url, callback=self.get_zuozhe)
def get_z_detail(self,response):
item = response.meta[‘item‘]
item[‘url‘] = response.request.url
item[‘category‘] = response.xpath(‘//div[@class="shici-mark"]/a/text()‘).extract_first()
item[‘title‘] = response.xpath(‘//div[@id="item_div"]/h1/text()‘).extract_first()
item[‘auther‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/a/text()‘).extract_first()
item[‘dynasty‘] = response.xpath(‘//div[@class="niandai_zuozhe"]/text()‘).extract_first()
contents = response.xpath(‘//div[@class="item_content"]//text()‘).extract()
content = ‘‘
for c in contents:
content += c.strip() + ‘\n‘
item[‘content‘] = content
shangxi_contents = response.xpath(‘//div[@class="shangxi_content"]//text()‘).extract()
contents = ‘‘
for s in shangxi_contents:
contents += s.strip()
item[‘contents‘] = contents
by1 = response.xpath(‘//div[@id="item_div"]/img/@src‘).extract_first()
if by1:
item[‘beiyong1‘] = by1
else:
item[‘beiyong1‘] = ‘‘
yield item4.pipline.py中编写写入数据库和下载图片到本地规则
# -*- coding: utf-8 -*-
# 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
import pymysql
from scrapy import Request
from scrapy.exceptions import DropItem
from scrapy.pipelines.images import ImagesPipeline
class ScmjwPipeline:
def process_item(self, item, spider):
return item
class MysqlPipeline:
def __init__(self,host,database,user,password):
self.host = host
self.database = database
self.user = user
self.password = password
def open_spider(self,spider):
self.conn = pymysql.connect(self.host,self.user,self.password,self.database,charset=‘utf8‘)
self.cursor = self.conn.cursor()
# self.old_url = set()
# search_sql = "select url from scmjw"
# self.cursor.execute(search_sql)
# for i in self.cursor.fetchall():
# self.old_url.add(i[0])
def process_item(self,item,spider):
# if item[‘url‘] in self.old_url:
# print(‘数据已入库‘,item[‘title‘])
# raise DropItem
print(‘数据下载中‘,item[‘title‘])
data = dict(item)
keys = ‘, ‘.join(data.keys())
values = ‘, ‘.join([‘% s‘] * len(data))
sql = ‘insert into % s (% s) values (% s)‘ % (item.table, keys, values)
self.cursor.execute(sql, tuple(data.values()))
self.conn.commit()
return item
def close_spider(self,spider):
self.cursor.close()
self.conn.close()
@classmethod
def from_crawler(cls,crawler):
return cls(
host=crawler.settings.get(‘MYSQL_HOST‘),
database=crawler.settings.get(‘MYSQL_DATABASE‘),
user=crawler.settings.get(‘MYSQL_USER‘),
password=crawler.settings.get(‘MYSQL_PASSWORD‘),
)
class ImagePipeline(ImagesPipeline):
def file_path(self, request, response=None, info=None):
url = request.url
file_name = url.split(‘?‘)[0].split(‘/‘)[-1]
return file_name
def item_completed(self, results, item, info):
image_paths = [x[‘path‘] for ok, x in results if ok]
if not image_paths:
raise DropItem(‘Image Downloaded Failed‘)
return item
def get_media_requests(self, item, info):
if item[‘beiyong1‘]:
yield Request(item[‘beiyong1‘])5.settings.py中设置，空值日志输出，数据库信息，开启相应管道文件等
# -*- coding: utf-8 -*-
# Scrapy settings for scmjw 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 = ‘scmjw‘
SPIDER_MODULES = [‘scmjw.spiders‘]
NEWSPIDER_MODULE = ‘scmjw.spiders‘
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = ‘scmjw (+http://www.yourdomain.com)‘
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
LOG_LEVEL = ‘ERROR‘
LOG_FILE = ‘log.txt‘
IMAGES_STORE = ‘./image‘
MYSQL_HOST = ‘localhost‘
MYSQL_DATABASE = ‘lf_01‘
MYSQL_USER = ‘root‘
MYSQL_PASSWORD = ‘root‘
# 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 = {
# ‘scmjw.middlewares.ScmjwSpiderMiddleware‘: 543,
#}
# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
# ‘scmjw.middlewares.ScmjwDownloaderMiddleware‘: 543,
‘scmjw.middlewares.QuChongMiddleware‘: 542,
}
# 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 = {
‘scmjw.pipelines.ScmjwPipeline‘: 300,
‘scmjw.pipelines.MysqlPipeline‘: 301,
‘scmjw.pipelines.ImagePipeline‘: 302,
}
# 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‘6.middleware.py文件中使用下载中间件去重，防止重复下载
# -*- coding: utf-8 -*-
# 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 pymysql
from scrapy.exceptions import IgnoreRequest
class QuChongMiddleware:
def __init__(self,host,database,user,password):
self.conn = pymysql.connect(host, user, password, database, charset=‘utf8‘)
self.cursor = self.conn.cursor()
self.old_url = set()
search_sql = "select url from scmjw"
self.cursor.execute(search_sql)
for i in self.cursor.fetchall():
self.old_url.add(i[0])
def process_request(self,request,spider):
if request.url in self.old_url:
print(‘中间件判断，数据库已存在‘)
raise IgnoreRequest()
@classmethod
def from_crawler(cls,crawler):
return cls(
host=crawler.settings.get(‘MYSQL_HOST‘),
database=crawler.settings.get(‘MYSQL_DATABASE‘),
user=crawler.settings.get(‘MYSQL_USER‘),
password=crawler.settings.get(‘MYSQL_PASSWORD‘),
)
class ScmjwSpiderMiddleware:
# 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, dict 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, dict
# 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 ScmjwDownloaderMiddleware:
# 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)7.在根目录下创建start.py文件用于启动爬虫
from scrapy.crawler import CrawlerProcess from scrapy.utils.project import get_project_settings process = CrawlerProcess(get_project_settings()) process.crawl(‘scmj‘) process.start()
8.爬取结果概览
二、简单对数据进行分析
使用的第三方库为
numpy,pandas,matplotlib
1.代码如下
import pandas as pd
import numpy as np
from sqlalchemy import create_engine
from matplotlib import pyplot as plt
import warnings
‘‘‘
明确分析目标
1.诗词分类前十及占比
2.写诗词数量最多的作者前十分类及占比
3.诗词数量最多的朝代及占比
4.有注释的诗词
5.有图片的诗词
‘‘‘
‘‘‘设置正常显示中文和‘-’号‘‘‘
# 设置正常显示中文
plt.rcParams[‘font.sans-serif‘] = ‘SimHei‘
# 设置正常显示‘-’号
plt.rcParams[‘axes.unicode_minus‘] = False
# 去除顶部轴
plt.rcParams[‘axes.spines.top‘] = False
# 去除右部轴
plt.rcParams[‘axes.spines.right‘] = False
# 屏蔽warning警告
warnings.filterwarnings("ignore")
class Scmj:
def __init__(self):
self.conn = create_engine("mysql+pymysql://root::3306/lf_01?charset=utf8mb4")
self.df = pd.read_sql(‘select * from scmjw‘,self.conn)
self.conn.dispose()
# print(self.df.head())
print(self.df.info())
# print(self.df.describe())
‘‘‘获取一些描述性信息‘‘‘
def get_ty(self):
# 数据总量
self.scmj_all = self.df.shape[0]
print(‘数据总量为:‘,self.scmj_all)
‘‘‘诗词分类前十及占比‘‘‘
def category_top10(self):
category = self.df.groupby(‘category‘)
category_top10 = category.count()[‘id‘].sort_values(ascending=False)[:10]
print(‘分类前十:\n‘,category_top10)
# 折线图
pic = plt.figure(figsize=(12,12),dpi=100)
pic.add_subplot(2,2,1)
plt.title(‘诗词分类前十折线图‘)
plt.xlabel(‘诗词分类‘)
plt.ylabel(‘数量‘)
plt.xticks(rotation=90)
plt.yticks([i for i in range(0,200,10)])
plt.plot(category_top10)
# 条形图
pic.add_subplot(2,2,2)
plt.title(‘诗词分类前十条形图‘)
plt.xlabel(‘诗词分类‘)
plt.ylabel(‘数量‘)
x = range(10)
plt.bar(x,height=category_top10.values,width=0.7)
for i in range(len(category_top10)):
# print(category_top10.values[i])
plt.text(i,category_top10.values[i],‘{}首‘.format(category_top10.values[i]),va=‘bottom‘,ha=‘center‘)
plt.xticks(x,category_top10.index,rotation=90)
# 饼图
pic.add_subplot(2,2,3)
plt.title(‘诗词分类前十饼图‘)
plt.pie(category_top10,autopct=‘%1.1f%%‘,labels=category_top10.index,explode=[0.01 for i in range(10)])
# 箱线图
pic.add_subplot(2,2,4)
plt.title(‘诗词分类前十箱线图‘)
plt.boxplot(category_top10)
plt.savefig(‘./诗词分类前十统计图.png‘)
plt.show()
‘‘‘写诗词数量最多的作者前十及占比‘‘‘
def auther_top10(self):
auther_top10 = self.df[‘auther‘].value_counts().iloc[:10]
print(‘写诗词数量前十作者‘,auther_top10)
fig = plt.figure(figsize=(12,12),dpi=100)
# 折线图
fig.add_subplot(2,2,1)
plt.title(‘折线图‘)
plt.xlabel(‘作者‘)
plt.ylabel(‘写作数量‘)
for i,j in zip(auther_top10.index,auther_top10.values):
plt.text(i,j,j,ha=‘center‘, va=‘bottom‘,)
plt.plot(auther_top10)
# 条形图
fig.add_subplot(2,2,2)
x = range(len(auther_top10))
plt.title(‘条形图‘)
plt.xlabel(‘作者‘)
plt.ylabel(‘写作数量‘)
plt.xticks(x,auther_top10.index)
plt.bar(x=x,height=auther_top10.values,width=0.7)
for i in range(len(auther_top10)):
plt.text(i,auther_top10.values[i],auther_top10.values[i],va=‘bottom‘,ha=‘center‘)
# 饼图
fig.add_subplot(2,2,3)
plt.title(‘饼图‘)
plt.pie(auther_top10.values,autopct=‘%1.1f%%‘,labels=auther_top10.index,explode=[0.01 for i in range(len(auther_top10))])
# 散点图
fig.add_subplot(2,2,4)
plt.title(‘散点图‘)
plt.xlabel(‘作者‘)
plt.ylabel(‘写作数量‘)
plt.scatter(x=auther_top10.index,y=auther_top10.values)
plt.savefig(‘写诗词数量前十作者统计图.png‘)
plt.show()
‘‘‘诗词数量最多的朝代及占比‘‘‘
def dynasty_top10(self):
df1 = self.df
clean_d = df1[‘dynasty‘].fillna(np.nan)
clean_d[clean_d == ‘ [] ‘] = np.nan
df1[‘dynasty‘] = clean_d
# df1[df1[‘dynasty‘] == ‘ [] ‘] = None
df1.dropna(subset=[‘dynasty‘])
dynasty = df1[‘dynasty‘].value_counts()[:10]
fig = plt.figure(dpi=100,figsize=(12,12))
# 折线图
fig.add_subplot(2, 2, 1)
plt.title(‘折线图‘)
plt.xlabel(‘朝代‘)
plt.ylabel(‘写作数量‘)
for i,j in zip(dynasty.index,dynasty.values):
plt.text(i,j,j,ha=‘center‘,va=‘bottom‘)
plt.plot(dynasty)
# 条形图
fig.add_subplot(2,2,2)
plt.title(‘条形图‘)
plt.xlabel(‘朝代‘)
plt.ylabel(‘写作数量‘)
plt.bar(x=dynasty.index,height=dynasty.values,width=0.8)
for i,j in zip(dynasty.index,dynasty.values):
plt.text(i,j,j,va=‘bottom‘,ha=‘center‘)
# 饼图
fig.add_subplot(2,2,3)
plt.title(‘饼图‘)
plt.pie(x=dynasty,autopct=‘%1.1f%%‘,labels=dynasty.index,explode=[0.01 for i in range(len(dynasty))])
# 散点图
fig.add_subplot(2,2,4)
plt.title(‘散点图‘)
plt.xlabel(‘朝代‘)
plt.ylabel(‘写作数量‘)
plt.scatter(x=dynasty.index,y=dynasty.values)
for i,j in zip(dynasty.index,dynasty.values):
plt.text(i,j,j,ha=‘center‘,va=‘center‘)
plt.savefig(‘./诗词数量最多的朝代前十及占比.png‘)
plt.show()
‘‘‘有注释&图片的诗词‘‘‘
def contents_images(self):
df1 = self.df
df1[df1[‘contents‘] == ‘‘] = None
contents = df1.dropna(subset=[‘contents‘]).shape[0]
print(‘有注释的诗词数量为:‘,contents)
df2 = self.df
df2[df2[‘beiyong1‘] == ‘‘] = None
images = df2.dropna(subset=[‘beiyong1‘]).shape[0]
print(‘有图片的诗词数量为:‘,images)
‘‘‘饼图‘‘‘
explode = [0.01,0.01]
fig = plt.figure(figsize=(8,8),dpi=100)
fig.add_subplot(1,2,1)
plt.title(‘有注释的诗词占比‘)
x = [self.scmj_all,contents]
labels = [‘无注释‘,‘有注释‘]
plt.pie(x=x,autopct=‘%1.1f%%‘,labels=labels,explode=explode)
fig.add_subplot(1,2,2)
plt.title(‘有图片的诗词占比‘)
x = [self.scmj_all,images]
labels = [‘无图片‘,‘有图片‘]
plt.pie(x=x,autopct=‘%1.1f%%‘,labels=labels,explode=explode)
plt.savefig(‘./图片&诗词占比.png‘)
plt.show()
def run(self):
self.get_ty()
self.category_top10()
self.auther_top10()
self.dynasty_top10()
self.contents_images()
def __del__(self):
pass
if __name__ == ‘__main__‘:
S = Scmj()
S.run()2.分析结果概览
代码已托管github，地址为 https://github.com/terroristhouse/scmjw.git
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