在不可描述的标记之间刮取文本

Question

在某些情况下，我的文本介于模糊的值和在整个文件中多次重复出现的属性之间（例如“重复使用）。在

最后，我想拉出：“Prev Close:”和“565.07”并将这些信息放入字符串或列表中（请提出建议）。在

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相关HTML源的一部分：

<div class="yui-u first yfi-start-content"><div class="yfi_quote_summary"><div id="yfi_quote_summary_data" class="rtq_table"><table id="table1"><tr><th scope="row" width="48%">Prev Close:</th><td class="yfnc_tabledata1">565.07</td></tr>

---

我的代码（Python 3.4.1）：

^{pr2}$

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错误

Traceback (most recent call last):
    next_FirstTable_tag = FirstTable_tag.findNextSibling          
AttributeError: 'NoneType' object has no attribute 'findNextSibling'
<<< Process finished. (Exit code 1)

---

编辑

Here is the initial and full source as requested

虽然我已经开始使用雅虎的API了，这显然是一种更好的方法，但我仍在尝试通过@scandinavian_u的帮助来解决问题

我更新了上面的代码，但仍然有相同的错误。

---

编辑2

此后，本帖将关注斯堪的纳维亚半岛正在协助开发的解决方案：

import sys
import urllib.request
url = "http://finance.yahoo.com/q?s=GOOG"
urlRunner = urllib.request.urlopen(url)
data = urlRunner.read()

from bs4 import BeautifulSoup
soup = BeautifulSoup(data)

import re
tables = soup.findAll("table", id = re.compile('^table'))
result = {}
for table in tables:
    for th, td in zip(table.findAll("th"), table.findAll("td")):
        result[th.text] = td.text
print(result)

结果：

{'52wk Range:': '502.80 - 604.83', 'Market Cap:': '381.04B', 'Next Earnings Date:': 'N/A', 'P/E (ttm):': '29.52', 'Avg Vol (3m):': '1,701,610', 'EPS (ttm):': '19.09', '1y Target Est:': 'N/A', 'Volume:': '561,384', 'Ask:': '563.98 x 100', 'Div & Yield:': 'N/A (N/A) ', 'Bid:': '563.56 x 100', 'Beta:': '1.144', 'Open:': '568.00', "Day's Range:": '562.53 - 569.77', 'Prev Close:': '566.37'}

Answer 1

这是基于我认为你想要的，但是没有适当的数据样本是不可能说的。我猜不出它是怎么构成的。在您的描述中，数据听起来是不规则的，这在您的示例中是不可能看到的。在

from bs4 import BeautifulSoup
from itertools import izip

html = """<div class="yui-u first yfi-start-content">
    <div class="yfi_quote_summary">
        <div id="yfi_quote_summary_data" class="rtq_table">
            <table id="table1">
                <tr>
                    <th scope="row" width="48%">Target Point:</th>
                    <td class="yfnc_tabledata1">200.22</td>
                </tr>
                <tr>
                    <th scope="row" width="48%">Target Point:</th>
                    <td class="yfnc_tabledata1">200.22</td>
                </tr>
                <tr>
                    <th scope="row" width="48%">Target Point:</th>
                    <td class="yfnc_tabledata1">200.22</td>
                </tr>
            </table>
        </div>
    </div>
</div>"""

bs = BeautifulSoup(html)

result = {}

ths = bs.findAll("th")
tds = bs.findAll("td")
elements = izip(ths, tds)

result = []

for x, y in elements:
    result.append((x.text, y.text))

print result

编辑：

Yahoo API解决方案，请考虑使用此解决方案：

^{pr2}$

这将打印：

565.07
561.78

以下是股票的可用数据：

AfterHoursChangeRealtime
AnnualizedGain
Ask
AskRealtime
AverageDailyVolume
Bid
BidRealtime
BookValue
Change
Change_PercentChange
ChangeFromFiftydayMovingAverage
ChangeFromTwoHundreddayMovingAverage
ChangeFromYearHigh
ChangeFromYearLow
ChangeinPercent
ChangePercentRealtime
ChangeRealtime
Commission
Currency
DaysHigh
DaysLow
DaysRange
DaysRangeRealtime
DaysValueChange
DaysValueChangeRealtime
DividendPayDate
DividendShare
DividendYield
EarningsShare
EBITDA
EPSEstimateCurrentYear
EPSEstimateNextQuarter
EPSEstimateNextYear
ErrorIndicationreturnedforsymbolchangedinvalid
ExDividendDate
FiftydayMovingAverage
HighLimit
HoldingsGain
HoldingsGainPercent
HoldingsGainPercentRealtime
HoldingsGainRealtime
HoldingsValue
HoldingsValueRealtime
LastTradeDate
LastTradePriceOnly
LastTradeRealtimeWithTime
LastTradeTime
LastTradeWithTime
LowLimit
MarketCapitalization
MarketCapRealtime
MoreInfo
Name
Notes
OneyrTargetPrice
Open
OrderBookRealtime
PEGRatio
PERatio
PERatioRealtime
PercebtChangeFromYearHigh
PercentChange
PercentChangeFromFiftydayMovingAverage
PercentChangeFromTwoHundreddayMovingAverage
PercentChangeFromYearLow
PreviousClose
PriceBook
PriceEPSEstimateCurrentYear
PriceEPSEstimateNextYear
PricePaid
PriceSales
SharesOwned
ShortRatio
StockExchange
symbol
Symbol
TickerTrend
TradeDate
TwoHundreddayMovingAverage
Volume
YearHigh
YearLow
YearRange