import requests, time, json, demjson
from datetime import datetime
import pandas as pd
from urllib.request import Request, urlopen
from html.parser import unescape
def get_price_data(query):
r = requests.get("https://finance.google.com/finance/getprices", params=query)
lines = r.text.splitlines()
data = []
index = []
basetime = 0
for price in lines:
cols = price.split(",")
if cols[0][0] == 'a':
basetime = int(cols[0][1:])
index.append(datetime.fromtimestamp(basetime))
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
elif cols[0][0].isdigit():
date = basetime + (int(cols[0])*int(query['i']))
index.append(datetime.fromtimestamp(date))
data.append([float(cols[4]), float(cols[2]), float(cols[3]), float(cols[1]), int(cols[5])])
return pd.DataFrame(data, index = index, columns = ['Open', 'High', 'Low', 'Close', 'Volume'])
def buildNewsUrl(symbol, qs='&start=0&num=5'):
return 'http://www.google.com/finance/company_news?output=json&q=' \
+ symbol + qs
def request(symbols):
url = buildUrl(symbols)
req = Request(url)
resp = urlopen(req)
# remove special symbols such as the pound symbol
content = resp.read().decode('ascii', 'ignore').strip()
content = content[3:]
return content
def getNews(symbol):
url = buildNewsUrl(symbol)
content = urlopen(url).read().decode('utf-8')
content_json = demjson.decode(content)
article_json = []
news_json = content_json['clusters']
for cluster in news_json:
for article in cluster:
if article == 'a':
article_json.extend(cluster[article])
return [[unescape(art['t']).strip(), art['u']] for art in article_json]
