以爬取NASDAQ的股票数据为例

依赖

from lxml import html //获取网页信息
import requests //地址请求数据
from time import sleep //延时用
import json //生成json
import argparse //python 执行参数读取 暂时不用
from random import randint //生成延时随机数
import pymongo //写入mongodb

获取数据

设置请求头

headers = {
        "Referer": "http://www.nasdaq.com",
        "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/64.0.3282.119 Safari/537.36"
    }

请求网页数据

url = "http://www.nasdaq.com/symbol/%s" % (ticker)
response = requests.get(url, verify=False)
print("respose code:%d" % (response.status_code))
if response.status_code != 200:
    raise ValueError("Invalid Response Received From Webserver")

解析和组装数据（解析规则参考html.fromstring.xpath）

parser = html.fromstring(response.text)
xpath_head = "//div[@id='qwidget_pageheader']//h1//text()"
xpath_key_stock_table = '//div[@class="row overview-results relativeP"]//div[contains(@class,"table-table")]/div'
xpath_open_price = '//b[contains(text(),"Open Price:")]/following-sibling::span/text()'
xpath_open_date = '//b[contains(text(),"Open Date:")]/following-sibling::span/text()'
xpath_close_price = '//b[contains(text(),"Close Price:")]/following-sibling::span/text()'
xpath_close_date = '//b[contains(text(),"Close Date:")]/following-sibling::span/text()'
xpath_key = './/div[@class="table-cell"]/b/text()'
xpath_value = './/div[@class="table-cell"]/text()'
raw_name = parser.xpath(xpath_head)
key_stock_table = parser.xpath(xpath_key_stock_table)
raw_open_price = parser.xpath(xpath_open_price)
raw_open_date = parser.xpath(xpath_open_date)
raw_close_price = parser.xpath(xpath_close_price)
raw_close_date = parser.xpath(xpath_close_date)

company_name = raw_name[0].replace("Common Stock Quote & Summary Data", "").strip() if raw_name else ''
open_price = raw_open_price[0].strip() if raw_open_price else None
open_date = raw_open_date[0].strip() if raw_open_date else None
close_price = raw_close_price[0].strip() if raw_close_price else None
close_date = raw_close_date[0].strip() if raw_close_date else None
# Grabbing ans cleaning keystock data
for i in key_stock_table:
    key = i.xpath(xpath_key)
    value = i.xpath(xpath_value)
    key = ''.join(key).strip().replace(".", "_")
    value = ' '.join(''.join(value).split())
    key_stock_dict[key] = value

    nasdaq_data = {
        "company_name": company_name,
        "ticker": ticker,
        "url": url,
        "open_price": open_price,
        "open_date": open_date,
        "close_price": close_price,
        "close_date": close_date,
        "key_stock_data": key_stock_dict
   }
return nasdaq_data

主函数执行

symbols = ['aapl', 'gluu', 'mu', 'ntap', 'msft', 'intc', 'znga', 'csco', 'siri', 'jd', 'fb', 'nvda', 'bl', 'ftnt', 'chrs', 'loco', 'catm', 'cnce', 'fizz', 'acor', 'fldm', 'sptn', 'cent', 'xent', 'adap', 'gpro', 'brks', 'sgms', 'iova', 'aaon', 'eigi', 'amzn', 'nflx', 'tsla']
    for ticker in symbols:
        print("Fetching data for %s" % (ticker))
        scraped_data = parse_finance_page(ticker)
        print("Writing scraped data to output file")
        with open('%s-summary.json' % (ticker), 'w') as fp:
            json.dump(scraped_data, fp, indent=4, ensure_ascii=False)
        myclient = pymongo.MongoClient('mongodb://localhost:27107/')
        mydb = myclient['resthub']
        mycol = mydb["stocks"]
        x = mycol.insert_one(scraped_data)
        print(x.inserted_id)

结果

Fetching data for aapl
respose code:200
Parsing http://www.nasdaq.com/symbol/aapl
Writing scraped data to output file
5d44642d79c3f9765ab465fa
Fetching data for gluu
respose code:200
Parsing http://www.nasdaq.com/symbol/gluu
Writing scraped data to output file
5d44642f79c3f9765ab465fc
Fetching data for mu
respose code:200
Parsing http://www.nasdaq.com/symbol/mu
Writing scraped data to output file
5d44643179c3f9765ab465fe
Fetching data for ntap
respose code:200
Parsing http://www.nasdaq.com/symbol/ntap
Writing scraped data to output file
5d44643579c3f9765ab46600

需要mongodb已启动在端口27107