工作上涉及公司网站SEO优化相关的工作，但是在Title、Keywords、Description这块有点不清楚。于是，参考了一些与自己公司业务上有相同的公司网站内容，在进行词语分析选取一些关键词，在结合本公司的业务内容关键词进行综合，完成了网站SEO优化的Keywords。
废话也不多说了，关于爬虫相关使用的教程在前面以及介绍了，而且还有栗子，这里主要贴上相关代码。除了爬取数据之外，本程序还把处理好的数据进行分析选取出现频率最多Keywords，以及把爬取的数据存储到excel中。
思路
抓取数据 -> 解析 -> 存储 -> 分析
特色
在本次爬虫中，运用了gevent协程，玩python不清楚协程的同学请自行脑补。
代码
# -*- coding: utf-8 -*-
"""
------------------------------------------------
describe:
用来抓取指定的物流公司官网的信息，包含title、keywords、description。
usage:
python comp_infos_grab.py
base_info:
__version__ = "v.10"
__author__ = "PyGo"
__time__ = "2019/12/3"
__mail__ = "gaoming971366@163.com"
------------------------------------------------
"""
import requests
import gevent
import xlrd
import xlwt
from gevent import monkey; monkey.patch_all()
from bs4 import BeautifulSoup
import jieba
PUBLIC_URL_LIST = {
"IML俄罗斯海外仓": "http://www.imlb2c.com/",
"旺集科技": "http://www.wangjigroup.com/",
"黑龙江俄速通国际物流有限公司": "http://www.ruston.cc/",
"AliExpress全球速卖通": "https://sell.aliexpress.com/zh/__pc/shipping/aliexpress_shipping.htm",
"中外运集装箱运输有限公司": "http://www.sinolines.com/",
"乐泰国际物流有限公司": "http://www.letaimzl.com/",
"NOEL诺艾尔集团": "http://www.noelworld.com/",
"慧承国际物流": "http://www.hcwuliu.com/",
"满洲里新颖国际货运代理有限公司": "http://www.mzlxinying.com/",
"运盟国际物流": "http://www.ym-trans.com/",
"如易科技": "http://www.ruecom.cn/"
}
class companyGrap(object):
_instance = None
def __init__(self):
super(companyGrap, self).__init__()
def __new__(cls, *args, **kwargs):
if companyGrap._instance is None:
companyGrap._instance = object.__new__(cls, *args, **kwargs)
return companyGrap._instance
def _get_infos(self, url):
results = dict()
results['url'] = url
if not url:
return results
payload = ""
headers = {
"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36"
}
response = requests.get(url, data=payload, headers=headers)
if response.status_code == 200:
soup = BeautifulSoup(response.content, 'html.parser')
head = soup.head
titles = head.find_all('title')
tl = titles[0].string if titles else ""
results['title'] = tl
keywords = head.find_all('meta', attrs={'name': 'keywords'})
kw = keywords[0].attrs.get('content') if keywords else ""
results['keyword'] = kw
descriptions = head.find_all('meta', attrs={'name': 'description'})
desc = descriptions[0].attrs.get('content') if descriptions else ""
results['description'] = desc
return results
def to_excel(self, datas, exlname):
"""
generate data of excel format to save
:param datas: excel data
:param exlname: excel name
:return: None, excel data
"""
f = xlwt.Workbook(encoding='utf-8')
sheet = f.add_sheet('sheet', cell_overwrite_ok=True)
EXCEL_TITLES = ["ID", "NAME", "URL", 'TITLE', 'KEYWORDS', 'DESCRIPTION', "REMARK"]
BUSINESS = "BUSINESS"
style_title = xlwt.XFStyle()
font = xlwt.Font()
font.name = 'Times New Roman'
font.bold = True
font.color_index = 4
font.height = 220
style_title.font = font
style_content = xlwt.XFStyle()
font = xlwt.Font()
font.name = 'Times New Roman'
font.bold = False
font.color_index = 4
font.height = 220
style_content.font = font
# 标题
for i in range(0, len(EXCEL_TITLES)):
sheet.write(0, i, EXCEL_TITLES[i], style_title)
# 合并 && 重写
sheet.write_merge(0, 0, 3, 5, BUSINESS, style_title)
sheet.write_merge(0, 1, 0, 0, 'ID', style_title)
sheet.write_merge(0, 1, 1, 1, 'NAME', style_title)
sheet.write_merge(0, 1, 2, 2, 'URL', style_title)
sheet.write_merge(0, 1, 6, 6, 'REMARK', style_title)
for i in range(3, 6):
sheet.write(1, i, EXCEL_TITLES[i], style_content)
row = 2
count = 1
for line in datas:
sheet.write(row, 0, count, style_title)
sheet.write(row, 1, line.get('name'), style_content)
sheet.write(row, 2, line.get('url'), style_content)
sheet.write(row, 3, line.get('title'), style_content)
sheet.write(row, 4, line.get('keyword'), style_content)
sheet.write(row, 5, line.get('description'), style_content)
row += 1
count += 1
f.save(exlname)
def _deal_url(self, k, v):
return self._get_infos(v)
def to_generate_kw(self, datas):
keywords_src = ""
for data in datas:
if not data:
continue
keywords_src += data.get('keyword')
keywords = jieba.lcut(keywords_src, cut_all=False)
counts = dict()
for word in keywords:
if not word:
continue
if isinstance(word, unicode):
word = word.encode('utf-8')
if word in ('|', ',', ' ', '-', '，'):
continue
counts[word] = counts.get(word, 0) + 1
ord_counts = sorted(counts.items(), key=lambda x: x[1], reverse=True)
for k in ord_counts:
print "%s: %s" % (k[0], k[1])
def run(self, to_excel=False):
"""
process run
:param to_excel:
:return:
"""
jobs = list()
names = list()
excel_datas = list()
for k, v in PUBLIC_URL_LIST.iteritems():
if not k or not v:
continue
names.append(k)
jobs.append(gevent.spawn(self._deal_url, k, v))
gevent.joinall(jobs)
for name, job in zip(names, jobs):
value = job.value
print '==================%s==================' % name
print 'Title: %s' % value.get('title')
print 'Keyword: %s' % value.get('keyword')
print 'Description: %s' % value.get('description')
value['name'] = name
excel_datas.append(value)
self.to_generate_kw(excel_datas)
if to_excel:
print '---------excel ok'
self.to_excel(excel_datas, 'companys.xls')
if __name__ == '__main__':
companyGrap().run(to_excel=False)
