def get_data(url):
"""
:param page_url: 待获取url
:return:
"""
try:
# 获取url中的html文本
con = CrawlerUtils.get_html(url,
headers=CrawlerUtils.get_headers(COOKIES),
proxies=proxies)
# 获取css url，及tag，由于文本与数字class 前缀不同，所以需要分别获取
num_re_compile = "<b><span class=\"(.*?)\"></span>" # 定义数字class匹配正则
str_re_compile = '<span class="addr"><span class=\"(.*?)\"></span>' # 定义地址class匹配正则
# 获取css的URL
css_url = get_css(con)
# 获取数字class前缀
num_svg_tag = get_tag(re.findall(num_re_compile, con))
# 获取文本class前缀
str_svg_tag = get_tag(re.findall(str_re_compile, con))
# 获取css对应名与像素的映射字典
css_and_px_dict = get_css_and_px_dict(css_url)
# 对html文本使用 etree.HTML(html)解析，得到Element对象
doc = etree.HTML(con)
# 获取所有商家标签
shops = doc.xpath('//div[@id="shop-all-list"]/ul/li')
for shop in shops[1:]:
# 商铺id
shop_id = shop.xpath(
'.//div[@class="tit"]/a')[0].attrib["data-shopid"]
logger.info("shop_id", shop_id)
# 店名
shop_name = shop.xpath('.//div[@class="tit"]/a')[0].attrib["title"]
shop_name = bytes(shop_name.encode('utf-8')).decode('utf-8')
comment_num = 0
per_capita_price = taste = service = environment = 0
# 获取星级评分数
star_num = int(
str(
shop.xpath('.//div[@class="comment"]/span')
[0].attrib["class"]).split("sml-str")[-1])
# 获取点评总数
comment_and_price_datas = shop.xpath('.//div[@class="comment"]')
for comment_and_price_data in comment_and_price_datas:
_comment_data = comment_and_price_data.xpath(
'a[@class="review-num"]/b/node()')
comment_num = get_last_value(css_url, _comment_data,
css_and_px_dict, num_svg_tag)
comment_num = int(comment_num) if comment_num else 0
if comment_num == 0:
return
# 获取人均消费价格
_price = comment_and_price_data.xpath(
'a[@class="mean-price"]/b/node()')
per_capita_price = get_last_value(css_url, _price,
css_and_px_dict, num_svg_tag)
per_capita_price = int(
per_capita_price[1:]) if per_capita_price else 0
# 获取口味，环境，服务评分
others_num_node = shop.xpath('.//span[@class="comment-list"]/span')
for others_datas in others_num_node:
if others_datas.xpath('text()') and others_datas.xpath(
'text()')[0] == u"口味":
_taste_data = others_datas.xpath('b/node()')
taste = get_last_value(css_url, _taste_data,
css_and_px_dict, num_svg_tag)
taste = float(taste) if taste else 0
if others_datas.xpath('text()') and others_datas.xpath(
'text()')[0] == u"服务":
_taste_data = others_datas.xpath('b/node()')
service = get_last_value(css_url, _taste_data,
css_and_px_dict, num_svg_tag)
service = float(service) if service else 0
if others_datas.xpath('text()') and others_datas.xpath(
'text()')[0] == u"环境":
_taste_data = others_datas.xpath('b/node()')
environment = get_last_value(css_url, _taste_data,
css_and_px_dict, num_svg_tag)
environment = float(environment) if environment else 0
# 获取地址
_ress = shop.xpath(
'.//div[@class="tag-addr"]/span[@class="addr"]/node()')
address = get_last_value(css_url,
_ress,
css_and_px_dict,
str_svg_tag,
is_num=False)
data = {
'shop_id': shop_id,
'shop_name': shop_name,
'address': address,
'per_capita_price': per_capita_price,
'total_number_comments': comment_num,
'stars': int(star_num),
'taste': taste,
'surroundings': environment,
'serve': service,
}
logger.info('开始保存数据: %s' % (data, ))
# 保存数据
DBUtils.save_to_db(Shop, data)
except Exception as e:
logger.error(e)
def spiderDazhong(shop_id, now_page):
global page
global proxies
try:
url = "http://www.dianping.com/shop/" + str(
shop_id) + "/review_all/p" + str(now_page)
print("url==========", url)
req = requests.get(url, headers=headers) # , proxies=proxies
if CrawlerUtils.get_bs(req.text, 'div#log'):
proxies = CrawlerUtils.get_proxies(api_url)
page -= 1
return True
# 获取svg的阈值与数字集合的映射
css_url = CrawlerUtils.get_css(req.content.decode('utf-8'))
str_re_compile = '<span class=\"(.*?)\"></span>'
addr_tag = CrawlerUtils.get_bs(req.text, 'div.review-truncated-words')
if addr_tag != []:
addr_tag = str(addr_tag[0])
else:
addr_tag = str(
CrawlerUtils.get_bs(req.text, 'div.review-words')[0])
_tag = CrawlerUtils.get_tag(re.findall(str_re_compile, addr_tag))
css_and_px_dict = CrawlerUtils.get_css_and_px_dict(css_url)
doc = pq(req.text)
# print(doc)
if doc:
# # 存入csv文件
# out = open('./data/Stu_csv.csv', 'a', newline='', encoding="utf-8")
# # 设定写入模式
# csv_write = csv.writer(out, dialect='excel')
# shopName = doc("div.review-list-header > h1 > a").text()
# shopurl = "http://www.dianping.com" + doc("div.review-list-header > h1 > a").attr("href")
# csv_write.writerow(["店铺名称", "店铺网址"])
# csv_write.writerow([shopName, shopurl])
# csv_write.writerow(["用户名", "用户ID链接", "评定星级", "评论描述", "评论详情", "评论时间", "评论商铺", "评论图片","是否VIP","推荐菜品"])
# 解析评论
pinglunLi = doc("div.reviews-items > ul > li").items()
li_num = 1
for data in pinglunLi:
userName = data(
"div.main-review > div.dper-info > a").text() # 用户名
shopName = data(
"div.main-review > div.misc-info.clearfix > span.shop"
).text() #
userID = ''
user_id_link = data(
"div.main-review > div.dper-info > a").attr("href")
if user_id_link != None:
userID = "http://www.dianping.com" + user_id_link
start_sapn = data(
"div.review-rank > span.sml-rank-stars.sml-str10.star")
if start_sapn:
startShop = str(
start_sapn.attr("class")).split(" ")[1].replace(
"sml-str", "")
else:
startShop = 0
describeShop = data("div.review-rank > span.score").text()
msg_values = etree.HTML(req.content.decode('utf-8')).xpath(
'//div[@class="reviews-items"]/ul/li[' + str(li_num) +
']/div[@class="main-review"]/div[@class="review-words Hide"]/node()'
) #
if msg_values == []:
msg_values = etree.HTML(req.content.decode('utf-8')).xpath(
'//div[@class="reviews-items"]/ul/li[' + str(li_num) +
']/div[@class="main-review"]/div[@class="review-words"]/node()'
)
pinglunShop = CrawlerUtils.get_last_value(css_url,
msg_values,
css_and_px_dict,
_tag,
is_num=False)
if pinglunShop == '':
continue
timeShop = data(
"div.main-review > div.misc-info.clearfix > span.time"
).text()
Shop = data(
"div.main-review > div.misc-info.clearfix > span.shop"
).text()
imgShop = data(
"div > div.review-pictures > ul > li> a").items()
imgList = []
for img in imgShop:
imgList.append("http://www.dianping.com" +
img.attr("href"))
vip_span = data("div.main-review > div.dper-info > span")
is_vip = 1 if vip_span.attr("class") == "vip" else 0
recommend = data(
"div.main-review > div.review-recommend > a").text()
print("===========", pinglunShop)
uuid = CrawlerUtils.get_md5_value(
str(shop_id) + pinglunShop + str(timeShop))
# # 写入具体内容
# csv_write.writerow([userName, userID, startShop, describeShop, pinglunShop, timeShop, Shop, imgList])
# print("successful insert csv!")
print(", 用户名：userName: {}\n, "
"商铺名称：shoName: {}\n, "
"用户ID链接：userID: {}\n, "
"评定星级：startShop: {}\n, "
"评论描述：describeShop : {}\n, "
"星级评分：startShop: {}\n, "
"评论详情：pinglunShop:{}\n, "
"评论时间：timeShop :{}\n, "
"评论商铺：Shop:{}\n, "
"评论图片：imgList:{}\n, "
"推荐菜品：recommend:{}\n, "
"是否vip：is_vip:{} "
"\n ".format(userName, shopName, userID, startShop,
describeShop, startShop, pinglunShop,
timeShop, Shop, imgList, recommend, is_vip))
data = {
'uuid': uuid,
'shop_id': shop_id,
'username': userName,
'shop_name': shopName,
'is_vip': is_vip,
'comment': pinglunShop,
'recommend': recommend,
'stars': startShop,
'comment_create_time': timeShop,
}
DBUtils.save_to_db(Comment, data)
li_num += 1
sleep(1)
if not CrawlerUtils.get_tags(req.text, '.NextPage'):
return False
return True
except Exception as e:
raise e
