Python拆分字符串与多个字典

Question

所以我试图解析来自Google Financial API的数据。我已经为单股报价工作，但多个股票报价不起作用。 json loads不适用于多个字典。

import urllib.request 
import json 
import time 

def get_stock(url, y): 
    data = urllib.request.urlopen(url) 
    read = data.read().decode('UTF-8') 
    json_data = json.loads(read[5:-2]) 
    for n in range(int(len(y.replace(",", ""))/4)): 
     print(y[4*n:4*n+4].upper(), json_data['l']) 

x = '' 
while x != 'exit': 
    x = input("Enter how often, in minutes (minimum one minute), you want the stock price to be updated; or type 'exit': ") 
    z = input("Enter the market that your stock(s) are in: ") 
    y = input("Enter the stock(s) that you want to retrieve information for (use commas if neccesary); or type 'exit': ") 
    y = y.replace(" ", "") 
    url = 'http://finance.google.com/finance/info?client=ig&q=%s:%s' % (z, y) 
    while True: 
     get_stock(url, y) 
     leave = input("Type 'exit' to leave, or wait until the next quote: ") 
     if leave == 'exit': 
      break 
     time.sleep(int(x)) 

下面是从谷歌API输出的JSON的一个例子：

{ 
"id": "304466804484872" 
,"t" : "GOOG" 
,"e" : "NASDAQ" 
,"l" : "496.18" 
,"l_fix" : "496.18" 
,"l_cur" : "496.18" 
,"s": "2" 
,"ltt":"4:14PM EST" 
,"lt" : "Jan 13, 4:14PM EST" 
,"lt_dts" : "2015-01-13T16:14:24Z" 
,"c" : "+3.63" 
,"c_fix" : "3.63" 
,"cp" : "0.74" 
,"cp_fix" : "0.74" 
,"ccol" : "chg" 
,"pcls_fix" : "492.55" 
,"el": "497.00" 
,"el_fix": "497.00" 
,"el_cur": "497.00" 
,"elt" : "Jan 13, 7:59PM EST" 
,"ec" : "+0.82" 
,"ec_fix" : "0.82" 
,"ecp" : "0.17" 
,"ecp_fix" : "0.17" 
,"eccol" : "chg" 
,"div" : "" 
,"yld" : "" 
} 
,{ 
"id": "22144" 
,"t" : "AAPL" 
,"e" : "NASDAQ" 
,"l" : "110.22" 
,"l_fix" : "110.22" 
,"l_cur" : "110.22" 
,"s": "2" 
,"ltt":"4:14PM EST" 
,"lt" : "Jan 13, 4:14PM EST" 
,"lt_dts" : "2015-01-13T16:14:23Z" 
,"c" : "+0.97" 
,"c_fix" : "0.97" 
,"cp" : "0.89" 
,"cp_fix" : "0.89" 
,"ccol" : "chg" 
,"pcls_fix" : "109.25" 
,"el": "110.30" 
,"el_fix": "110.30" 
,"el_cur": "110.30" 
,"elt" : "Jan 13, 7:59PM EST" 
,"ec" : "+0.08" 
,"ec_fix" : "0.08" 
,"ecp" : "0.07" 
,"ecp_fix" : "0.07" 
,"eccol" : "chg" 
,"div" : "0.47" 
,"yld" : "1.71" 
} 

我似乎无法找到一个有效的解决方案。 split方法不会工作，因为字符串中无处不在的逗号。 linesplit将无法​​工作，因为众多的\n换行符。

我只是需要得到字符串拆分，所以我可以使用json dumps，然后对每个使用json loads运行迭代来解析数据以进行访问。

Answer 1

只需添加一对夫妇的括号，也将努力：

>>> import json 
>>> src = """{ 
"id": "304466804484872" 
,"t" : "GOOG" 
,"e" : "NASDAQ" 
,"l" : "496.18" 
,"l_fix" : "496.18" 
,"l_cur" : "496.18" 
,"s": "2" 
,"ltt":"4:14PM EST" 
,"lt" : "Jan 13, 4:14PM EST" 
,"lt_dts" : "2015-01-13T16:14:24Z" 
,"c" : "+3.63" 
,"c_fix" : "3.63" 
,"cp" : "0.74" 
,"cp_fix" : "0.74" 
,"ccol" : "chg" 
,"pcls_fix" : "492.55" 
,"el": "497.00" 
,"el_fix": "497.00" 
,"el_cur": "497.00" 
,"elt" : "Jan 13, 7:59PM EST" 
,"ec" : "+0.82" 
,"ec_fix" : "0.82" 
,"ecp" : "0.17" 
,"ecp_fix" : "0.17" 
,"eccol" : "chg" 
,"div" : "" 
,"yld" : "" 
} 
,{ 
"id": "22144" 
,"t" : "AAPL" 
,"e" : "NASDAQ" 
,"l" : "110.22" 
,"l_fix" : "110.22" 
,"l_cur" : "110.22" 
,"s": "2" 
,"ltt":"4:14PM EST" 
,"lt" : "Jan 13, 4:14PM EST" 
,"lt_dts" : "2015-01-13T16:14:23Z" 
,"c" : "+0.97" 
,"c_fix" : "0.97" 
,"cp" : "0.89" 
,"cp_fix" : "0.89" 
,"ccol" : "chg" 
,"pcls_fix" : "109.25" 
,"el": "110.30" 
,"el_fix": "110.30" 
,"el_cur": "110.30" 
,"elt" : "Jan 13, 7:59PM EST" 
,"ec" : "+0.08" 
,"ec_fix" : "0.08" 
,"ecp" : "0.07" 
,"ecp_fix" : "0.07" 
,"eccol" : "chg" 
,"div" : "0.47" 
,"yld" : "1.71" 
}""" 

>>> json.loads(src) 
Traceback (most recent call last): 
    File "<stdin>", line 1, in <module> 
    File "/usr/lib/python2.7/json/__init__.py", line 326, in loads 
    return _default_decoder.decode(s) 
    File "/usr/lib/python2.7/json/decoder.py", line 369, in decode 
    raise ValueError(errmsg("Extra data", s, end, len(s))) 
ValueError: Extra data: line 30 column 1 - line 58 column 2 (char 512 - 1022) 
>>> src = u"[%s]" % src 
>>> json.loads(src) 
[{u'el': u'497.00', u'eccol': u'chg', u'ec': u'+0.82', u'l_fix': u'496.18', u'cp': u'0.74', u'id': u'304466804484872', u'yld': u'', u'el_fix': u'497.00', u'lt': u'Jan 13, 4:14PM EST', u'ecp_fix': u'0.17', u'elt': u'Jan 13, 7:59PM EST', u'cp_fix': u'0.74', u'c_fix': u'3.63', u'pcls_fix': u'492.55', u'ecp': u'0.17', u'div': u'', u'l_cur': u'496.18', u'c': u'+3.63', u'e': u'NASDAQ', u'ltt': u'4:14PM EST', u'l': u'496.18', u's': u'2', u't': u'GOOG', u'el_cur': u'497.00', u'lt_dts': u'2015-01-13T16:14:24Z', u'ec_fix': u'0.82', u'ccol': u'chg'}, {u'el': u'110.30', u'eccol': u'chg', u'ec': u'+0.08', u'l_fix': u'110.22', u'cp': u'0.89', u'id': u'22144', u'yld': u'1.71', u'el_fix': u'110.30', u'lt': u'Jan 13, 4:14PM EST', u'ecp_fix': u'0.07', u'elt': u'Jan 13, 7:59PM EST', u'cp_fix': u'0.89', u'c_fix': u'0.97', u'pcls_fix': u'109.25', u'ecp': u'0.07', u'div': u'0.47', u'l_cur': u'110.22', u'c': u'+0.97', u'e': u'NASDAQ', u'ltt': u'4:14PM EST', u'l': u'110.22', u's': u'2', u't': u'AAPL', u'el_cur': u'110.30', u'lt_dts': u'2015-01-13T16:14:23Z', u'ec_fix': u'0.08', u'ccol': u'chg'}] 
>>>