一、前言
上篇记录了Scrapy搭配selenium的使用方法,有了基本的了解后我们可以将这项技术落实到实际需求中。目前很多股票网站的行情信息都是动态数据,我们可以用Scrapy+selenium对股票进行实时采集并持久化,再进行数据分析、邮件通知等操作。
二、环境搭建
详情请看上篇笔记
三、代码实现
- items
python
class StockSpiderItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
# 股票代码
stock_code = scrapy.Field()
# 股票名称
stock_name = scrapy.Field()
# 最新价
last_price = scrapy.Field()
# 涨跌幅
rise_fall_rate = scrapy.Field()
# 涨跌额
rise_fall_price = scrapy.Field()
- middlewares
python
def __init__(self):
# ----------------firefox的设置------------------------------- #
self.options = firefox_options()
def spider_opened(self, spider):
spider.logger.info('Spider opened: %s' % spider.name)
spider.driver = webdriver.Firefox(options=self.options) # 指定使用的浏览器
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
spider.driver.get("https://quote.eastmoney.com/center/gridlist.html#hs_a_board")
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
response_body = spider.driver.page_source
return HtmlResponse(url=request.url, body=response_body, encoding='utf-8', request=request)
- settings设置
python
# See https://doc.scrapy.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {
'stock_spider.middlewares.StockSpiderSpiderMiddleware': 543,
}
# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
DOWNLOADER_MIDDLEWARES = {
'stock_spider.middlewares.StockSpiderDownloaderMiddleware': 543,
}
- spider文件
python
def parse(self, response):
# 股票代码
stock_code = response.css("table.table_wrapper-table tbody tr td:nth-child(2) a::text").extract()
# 股票名称
stock_name = response.css("table.table_wrapper-table tbody tr td:nth-child(3) a::text").extract()
# 最新价
last_price = response.css("table.table_wrapper-table tbody tr td:nth-child(5) span::text").extract()
# 涨跌幅
rise_fall_rate = response.css("table.table_wrapper-table tbody tr td:nth-child(6) span::text").extract()
# 涨跌额
rise_fall_price = response.css("table.table_wrapper-table tbody tr td:nth-child(7) span::text").extract()
for i in range(len(stock_code)):
item = StockSpiderItem()
item["stock_code"] = stock_code[i]
item["stock_name"] = stock_name[i]
item["last_price"] = last_price[i]
item["rise_fall_rate"] = rise_fall_rate[i]
item["rise_fall_price"] = rise_fall_price[i]
yield item
def close(self, spider):
spider.driver.quit()
- pipelines持久化
python
def process_item(self, item, spider):
"""
接收到提交过来的对象后,写入csv文件
"""
filename = f'stock_info.csv'
with open(filename, 'a+', encoding='utf-8') as f:
line = item["stock_code"] + "," + item["stock_name"] + "," + item["last_price"] + "," + \
item["rise_fall_rate"] + "," + item["rise_fall_price"] + "\n"
f.write(line)
return item
- readme文件
python
1.安装依赖包
- python 3.0+
- pip install -r requirements.txt
2.将最第二层stock_spider文件夹设置为根目录
3.将firefox驱动程序包放到python环境的Scripts文件夹里
4.必须要安装firefox浏览器才会调用到浏览器
5.执行spider_main.py文件启动爬虫