def newspage(request):
info = ts.get_latest_news(top=2, show_content=True)
newstmp1 = models.News.objects.order_by('-pk')[0]
newstmp2 = models.News.objects.order_by('-pk')[1]
news = models.News()
news.title = info.title[0].__str__()
news.content = info.content[0].__str__()
if news.title != newstmp1.title and news.title != newstmp2.title:
news.save()
news = models.News()
news.title = info.title[1].__str__()
news.content = info.content[1].__str__()
if news.title != newstmp1.title and news.title != newstmp2.title:
news.save()
news = models.News.objects.order_by('-pk')
news1 = news[0]
news2 = news[1]
news3 = news[2]
news = news[3:]
return render(request, 'news.html', {
'news': news,
'news1': news1,
'news2': news2,
'news3': news3
})
def Newsget(self):
#PDnews=ts.get_latest_news(top=self.newslength,show_content=self.show_c)
PDnews = ts.get_latest_news(top=self.newslength, show_content=False)
try:
if PDnews.ix[0, 'time'] != self.latesttime:
Newsmemory = pandas.concat([self.Newsmemory, PDnews],
axis=0) #按行合并
#self.latesttime=PDnews.ix[0,'time']
if self.show_c:
try:
Content = None
C_C = 0
while not Content and C_C < 5:
Content = ts.latest_content(PDnews.ix[0, 'url'])
C_C += 1
except:
print('latest_content api fail to load url:%s' %
PDnews.ix[0, 'url'])
Content = ''
#self.latestnew=PDnews.ix[0,'classify']+PDnews.ix[0,'title']+Content
self.latestnew = PDnews.ix[0, 'title'] + Content
else:
#self.latestnew=PDnews.ix[0,'classify']+PDnews.ix[0,'title'] #maybe content later
self.latestnew = PDnews.ix[0, 'title']
print(PDnews[['classify', 'title', 'time']])
if PDnews.ix[0, 'time']:
print('old latesttime %s' % self.latesttime)
self.latesttime = PDnews.ix[0, 'time']
print('new latesttime %s' % self.latesttime)
except:
print('Get Latest News Error')
def get_news():
timer = Timer(24 * 60 * 60, get_news)
timer.start()
session = db.session()
old = session.query(News).all()
for one in old:
session.delete(one)
session.commit()
session.close()
session = db.session()
info = tushare.get_latest_news(top=30, show_content=True)
for i in range(30):
news = News(info.title[i].__str__(), info.content[i].__str__(),
info.time[i].__str__())
session.add(news)
session.commit()
session.close()
def get_latest_news(self,topN):
newslist = ts.get_latest_news(topN)
latest_news = ()
i = 0
for record in newslist:
print record.title[i]
return latest_news
def store_news():
# 获取新浪股吧的最新新闻
sina_news = ts.guba_sina(show_content=True)
# 防止数据未更新插入重复数据 2018/04/22 0:33
# TODO 集合为空时的容错处理
for i in db.news.sina.find().sort([("_id", -1)]).limit(1):
for j in sina_news[:6][-1:].get("title"):
if i.get("title") != j:
db.news.sina.insert(
json.loads(sina_news[:6].to_json(orient='records')))
# 获取前6条最新的即时新闻
immediate_news = ts.get_latest_news(top=6, show_content=True)
for i in db.news.immediate.find().sort([("_id", -1)]).limit(1):
for j in immediate_news[-1:].get("title"):
if i.get("title") != j:
db.news.immediate.insert(
json.loads(immediate_news.to_json(orient='records')))
# 获取个股信息地雷数据
mines_news = ts.get_notices()
if not mines_news is None:
db.news.mines.insert(json.loads(mines_news.to_json(orient='records')))
def get_latest_news():
col = db['sina_finance']
df = ts.get_latest_news(show_content=True)
for _, row in df.iterrows():
if row['content'] is None:
continue
col.replace_one({
'url': row['url'],
}, {
'classify':
row['classify'],
'title':
row['title'],
'time':
row['time'],
'year':
2018,
'url':
row['url'],
'content': [
c.strip()
for c in row['content'].split('\n') if len(c.strip()) > 0
],
'crawl_time':
datetime.datetime.fromtimestamp(time.time()),
},
upsert=True)
def news_real(engine):
tbl = "news_real"
cnt = 0
tsl.log(tbl + " start...")
df = ts.get_latest_news()
if df is None:
tsl.log("no latest news")
return
st = datetime.datetime.today()
et = st - datetime.timedelta(hours=2)
st = '%02i-%02i %02i:00' % (st.month, st.day, st.hour)
et = '%02i-%02i %02i:00' % (et.month, et.day, et.hour)
df = df[df.time >= et]
df = df[df.time < st]
urls = df.url.values
contents = ['' for i in range(len(df))]
for i in range(len(df)):
if 'blog.sina.com.cn' in urls[i]:
continue
try:
content = ts.latest_content(urls[i])
if content is not None:
contents[i] = unicode(content)#.encode('raw_unicode_escape').decode('utf8')
cnt += 1
except BaseException, e:
print e
print urls[i]
def nlpHandle(nlp, mic, profile, wxbot=None):
"""
Arguments:
text -- user-input, typically transcribed speech
mic -- used to interact with the user (for both input and output)
profile -- contains information related to the user (e.g., phone
number)
wxbot -- wechat bot instance
"""
def get_news(data):
rs = []
for index, row in data.iterrows():
rs.append(str(index + 1))
for col_name in data.columns:
rs.append(row[col_name])
rs.append('\n')
return ' '.join(rs)
sys.path.append(mic.dingdangpath.LIB_PATH)
from app_utils import wechatUser
text = nlp['text']
if any(word in text for word in [u"财经新闻"]):
news = ts.get_latest_news(top=10, show_content=False)
t = mic.asyncSay("已获取财经新闻," +
('将发送到您的微信' if wxbot != None else "篇幅较长，请登录微信获取"))
if wxbot != None:
wechatUser(profile, wxbot, '财经新闻', get_news(news))
t.join()
elif any(word in text for word in [u"信息地雷"]):
orgName = None
code = None
items = nlp['items']
for item in items:
if item['ne'] == u'ORG':
orgName = item['item']
break
if orgName:
code = db.get_instance().get_stock_code(orgName)
else:
m = pattern.search(text)
if m:
code = m.group(2)
if code:
orgName = db.get_instance().get_stock_name(code)
if not orgName:
mic.say("股票代码可能不存在")
return
notices = ts.get_notices(code)
notices = notices[0:10]
tit = orgName + '的信息地雷'
t = mic.asyncSay("已获取" + tit + "," +
('将发送到您的微信' if wxbot != None else "篇幅较长，请登录微信获取"))
if wxbot != None:
wechatUser(profile, wxbot, tit, get_news(notices))
t.join()
else:
mic.say("没能获取股票代码")
def test():
ts.get_sz50s()
ts.get_hs300s()
ts.get_zz500s()
ts.realtime_boxoffice()
ts.get_latest_news()
ts.get_notices(tk)
ts.guba_sina()
ts.get_cpi()
ts.get_ppi()
ts.get_stock_basics()
ts.get_concept_classified()
ts.get_money_supply()
ts.get_gold_and_foreign_reserves()
ts.top_list() #每日龙虎榜列表
ts.cap_tops() #个股上榜统计
ts.broker_tops() #营业部上榜统计
ts.inst_tops() # 获取机构席位追踪统计数据
ts.inst_detail()
def prepare_data():
latest_news = ts.get_latest_news()
if latest_news is None or latest_news.empty:
return
latest_news_json = latest_news.to_json(orient='records')
collection = mongoConfig.get_collection_default("latest_news")
current_date = time.strftime("%Y-%m-%d")
mongoConfig.clear_collection(collection)
print(latest_news_json)
mongoConfig.insert_json(collection, json.loads(latest_news_json))
def get_news_url(num: int = 1000) -> None:
df = ts.get_latest_news(top=num, show_content=False)
df['timestamp'] = int(time.time())
data = df.to_dict(orient="records")
def update(d):
db.break_news.update({"url": d["url"]}, {"$set": d}, True)
logging.info(d["url"])
with ThreadPoolExecutor(max_workers=3) as executor:
executor.map(update, data)
def newspage(request):
info = ts.get_latest_news(top=2, show_content=True)
news = models.News()
news.title = info.title[0].__str__()
news.content = info.content[0].__str__()
news.save()
news = models.News()
news.title = info.title[1].__str__()
news.content = info.content[1].__str__()
news.save()
news = models.News.objects.all()
return render(request, 'news.html', {'news': news})
def sina_news_notification(bot):
'''
新浪新闻提醒
:param:
:return:
'''
path = sys.path[0]
today_ISO = datetime.today().date().isoformat()
# initialize the notices_last
filename = 'notices'
try:
notices_last = pd.read_excel('./Notices/' + filename + '_' +
today_ISO + '.xlsx')
except:
notices_last = pd.DataFrame(
columns=['classify', 'title', 'time', 'url', 'content'])
today_md = strftime("%m-%d 00:00", localtime())
if len(notices_last) > 0:
notices_last = notices_last[notices_last.time >= today_md]
try:
notices = ts.get_latest_news(show_content=True)
notices = notices[notices.time >= today_md]
for title in notices.title:
if len(notices_last[notices_last.title == title]) <= 0:
notices_last = notices_last.append(
notices[notices.title == title])
# load keyword
filename = 'key_word'
key_word = pd.read_excel(io=path + '/Notices/' + filename +
'.xlsx')
for word in key_word.key_word:
if word in title:
msg = title + ' - ' + notices[notices.title ==
title].iloc[0, 3]
if key_word[key_word.key_word == word].iloc[0,
1] == 'Y':
bot.friends().search('Yang Hui')[0].send(msg)
if key_word[key_word.key_word == word].iloc[0,
2] == 'Y':
bot.friends().search('欣')[0].send(msg)
except:
print(
strftime("%Y-%m-%d %H:%M:%S", localtime()) +
'-Warning: tushare server maybe down! try again later.')
# 保存消息
notices_last.sort_values(by='time', ascending=False, inplace=True)
filename = 'notices'
notices_last.to_excel(path + '/Notices/' + filename + '_' + today_ISO +
'.xlsx',
encoding='GBK')
return
def get_news(top=None, show_content=True):
"""获取即时财经新闻，类型包括国内财经、证券、外汇、期货、港股和美股等新闻信息。数据更新较快，使用过程中可用定时任务来获取。"""
data_df = None
logger.info('Begin get latest news.')
try:
data_df = ts.get_latest_news(top, show_content)
now = str(get_time())
logger.info('End get latest news.')
except Exception as e:
logger.exception('Error get latest news.')
finally:
return data_df
def get_latest_news():
try:
df = ts.get_latest_news(top=5, show_content=True)
del df["url"]
rsl = [df.loc[i].to_dict() for i, trial in df.iterrows()]
result = {"result": rsl}
except Exception as e:
result = {"error": "true", "message": str(e)}
print("result")
print(result)
return result
def updatenews():
newsdatalist=ts.get_latest_news()
newsdata=pd.DataFrame(newsdatalist)
conn= ms.connect(host='localhost',port = 3306,user='******', passwd='123456',db ='investment',charset="utf8")
cur = conn.cursor()
values=[]
for index,row in newsdata.iterrows():
values.append((row['classify'],row['title'],row['time'],row['url']))
cur.execute('delete from news')
cur.executemany('insert into news (classify,title,time,url) values(%s,%s,%s,%s)',values)
conn.commit()
cur.close()
conn.close()
def _wordcould():
# df=pd.read_csv('english.txt')
# df1=ts.get_industry_classified()
# print(df1)
# df2=ts.get_concept_classified()
# print(df2)
df3=ts.get_latest_news()
print(df3)
mylist=df3['title']
word_list=[' '.join(jieba.cut(sentense)) for sentense in mylist]
new_text=' '.join(word_list)
#new_text='you are my friends, and you not sure'
print(new_text)
'''
def _wordcould():
# df=pd.read_csv('english.txt')
# df1=ts.get_industry_classified()
# print(df1)
# df2=ts.get_concept_classified()
# print(df2)
df3 = ts.get_latest_news()
print(df3)
mylist = df3['title']
word_list = [' '.join(jieba.cut(sentense)) for sentense in mylist]
new_text = ' '.join(word_list)
#new_text='you are my friends, and you not sure'
print(new_text)
'''
def update_news():
df = ts.get_latest_news(show_content=True, top=5000)
df["date"] = df["time"].map(lambda x: "2017-" + x.split(' ')[0])
dates = df["date"].unique()
for date in dates:
date_df = df[df["date"] == date]
print date_df.shape
filename = "%s%s.csv" % (csv_dir, date)
print filename
if os.path.exists(filename):
old_df = pd.read_csv(filename)
if old_df.shape[0] < date_df.shape[0]:
date_df.to_csv(filename, index=False, encoding='utf-8')
else:
date_df.to_csv(filename, index=False, encoding='utf-8')
def get_news_keywords():
try:
df = ts.get_latest_news(top=10,show_content=True)
df["keywords"]=df["content"].apply(
lambda i: jieba.analyse.extract_tags(
i, topK=5, withWeight=False, allowPOS=()) if i else [])
del df["content"]
rsl = [df.loc[i].to_dict() for i,trial in df.iterrows()]
result = {"result": rsl}
except Exception as e:
result = {"error": "true", "message": str(e)}
print("result")
print(result)
return result
def getMarketNews():
num = 50
news = ts.get_latest_news(top=num)
classify = list(news['classify'])
title = list(news['title'])
time = list(news['time'])
url = list(news['url'])
print(num)
for i in classify:
print(i)
for i in title:
print(i)
for i in time:
print(i)
for i in url:
print(i)
def fetchBlockTradeByCode(self, code, date, vol=500, drop=False):
tableName = 'blockTradeRecords'
param = []
try:
db, dbname = connectConfigDB('database')
cursor = db.cursor()
cursor.execute("SET NAMES utf8mb4;")
if drop:
cursor.execute("DROP TABLE IF EXISTS %s" % tableName)
# db.commit()
# create table
sql = """
CREATE TABLE
`%s`.`%s` (
`code` VARCHAR(20) NOT NULL COMMENT '股票代码',
`name` VARCHAR(45) NOT NULL COMMENT '股票名称',
`date` VARCHAR(20) NULL COMMENT '日期',
`time` VARCHAR(20) NULL COMMENT '时间',
`price` DOUBLE NULL COMMENT '当前价格',
`volume` DOUBLE NULL COMMENT '成交手',
`preprice` DOUBLE NULL COMMENT '上一笔价格',
`type` VARCHAR(45) NULL COMMENT '买卖类型【买盘、卖盘、中性盘】'
) DEFAULT CHARSET=utf8mb4;
""" % (dbname, tableName
) # !IMPORTANT: DEFAULT CHARSET=utf8mb4;
cursor.execute(sql)
print('table %s created' % tableName)
# fetch and insert data
res = ts.get_latest_news()
sql = 'INSERT IGNORE INTO `' + tableName + \
"""` values(%s, %s, %s, %s, %s, %s, %s, %s)
"""
for row in res.values:
tmp = row.tolist()
tmp.insert(2, date)
param.append(tmp)
cursor.executemany(sql, param)
db.commit()
print('\ntable %s inserted %s records.' %
(tableName, len(res.values)))
except:
print_exc()
db.rollback()
return False
finally:
db.close()
return True
def getNews():
df = ts.get_latest_news()
df1 = df[['title', 'url', 'classify', 'time']]
# print df1
#insert()
#存入数据库
#df1.to_sql('news',engine, if_exists='append',index_label='url')
#df1.to_sql('news',engine, if_exists='append',index_label='title,url,classify,time',index=False)
print(engine.execute('delete from news'))
df1.to_sql('news',
engine,
if_exists='append',
index_label='title,url,classify,time',
index=False)
print('---ok---')
def __call__(self, conns):
self.base = Base()
self.financial_data = conns['financial_data']
'''即时财经新闻'''
latest_news = ts.get_latest_news()
self.base.batchwri(latest_news, 'latest_news', self.financial_data)
'''
名称：个股信息地雷
功能：获得个股信息地雷数据
参数
code：股票代码
date：信息公布日期
'''
notices = ts.get_notices()
self.base.batchwri(notices, 'notices', self.financial_data)
'''新浪股吧新闻'''
guba_sina = ts.guba_sina()
self.base.batchwri(guba_sina, 'guba_sina', self.financial_data)
def getnews(request):
"""
调用 tushare ；一次抓取一百条财经新闻，并放在sqlite里存起来
"""
df = ts.get_latest_news(top=100, show_content=True)
path = os.path.abspath('Result.csv')
df.to_csv(path)
df = pandas.read_csv(path)
print(df)
for index, row in df.iterrows():
# time.sleep(2) # 休眠1秒
news.objects.create(classify=row[1],
title=row[2],
time=row[3],
url=row[4],
content=row[5])
#print('add success')
return HttpResponse("add success")
def show_stats_home():
"""大盘指数"""
df = ts.get_index()
market_index = df2DictList(df, True)
"""自选股数据"""
df = ts.get_realtime_quotes(
['000002', '300122', '002230', '300166', '603189', '000005'])
self_stock = df2DictList(df)
"""新闻数据"""
df = ts.get_latest_news()
news = df2DictList(df)
"""电影票房"""
df = ts.realtime_boxoffice()
boxoffice = df2DictList(df)
return dict(market_index=market_index,
self_stock=self_stock,
news=news,
boxoffice=boxoffice)
def index():
whole_indicators = json.loads(ts.get_index()[:4].to_json(orient='records'))
whole_news = []
whole_news = json.loads(
ts.get_latest_news(top=7).to_json(orient="records"))
notice = Article.query.order_by(Article.updatedTime.desc()).limit(7)
dates = datetime.datetime.now()
week = datetime.datetime.now().weekday()
if week in [5, 6]:
days = 4 - week
dates = dates + datetime.timedelta(days=days)
dates = dates.strftime('%Y-%m-%d')
return render_template('main/index.html',
whole_indicators=whole_indicators,
news=whole_news,
notices=notice,
dates=dates)
def get_all_price(code_list):
'''''process all stock'''
df = ts.get_realtime_quotes(STOCK)
print df
df = ts.get_latest_news()
print df
df = ts.get_cpi()
print df
df = ts.get_stock_basics()
print df
df = ts.get_sz50s()
print df
df = ts.get_hist_data('600848')
print df
def fetchFinancialNews(self, drop=False):
tableName = 'financialNews'
param = []
try:
db, dbname = connectConfigDB('database')
cursor = db.cursor()
cursor.execute("SET NAMES utf8mb4;")
if drop:
cursor.execute("DROP TABLE IF EXISTS %s" % tableName)
# db.commit()
# create table
sql = """
CREATE TABLE
`%s`.`%s` (
`classify` VARCHAR(20) NOT NULL COMMENT '新闻类型',
`title` TEXT NULL COMMENT '标题',
`date` VARCHAR(45) NULL COMMENT '日期',
`url` TEXT NULL COMMENT '链接',
PRIMARY KEY ( `title`, `date`)
) DEFAULT CHARSET=utf8mb4;
""" % (dbname, tableName
) # !IMPORTANT: DEFAULT CHARSET=utf8mb4;
cursor.execute(sql)
print('table %s created' % tableName)
# fetch and insert data
res = ts.get_latest_news()
sql = 'INSERT IGNORE INTO `' + tableName + \
"""` values(%s, %s, %s, %s)
"""
for row in res.values:
param.append(row.tolist())
cursor.executemany(sql, param)
db.commit()
print('\ntable %s inserted %s records.' %
(tableName, len(res.values)))
except:
print_exc()
db.rollback()
return False
finally:
db.close()
return True
def updatenews():
newsdatalist = ts.get_latest_news()
newsdata = pd.DataFrame(newsdatalist)
conn = ms.connect(host='localhost',
port=3306,
user='******',
passwd='123456',
db='investment',
charset="utf8")
cur = conn.cursor()
values = []
for index, row in newsdata.iterrows():
values.append((row['classify'], row['title'], row['time'], row['url']))
cur.execute('delete from news')
cur.executemany(
'insert into news (classify,title,time,url) values(%s,%s,%s,%s)',
values)
conn.commit()
cur.close()
conn.close()
def job_6():
try:
print("I'm working......新闻事件数据")
# 即时新闻
latest_news = ts.get_latest_news()
data = pd.DataFrame(latest_news)
data.to_sql('latest_news',engine,index=True,if_exists='replace')
print("即时新闻......done")
# 信息地雷
notices = ts.get_notices()
data = pd.DataFrame(notices)
data.to_sql('notices',engine,index=True,if_exists='replace')
print("信息地雷......done")
# 新浪股吧
guba_sina = ts.guba_sina()
data = pd.DataFrame(guba_sina)
data.to_sql('guba_sina',engine,index=True,if_exists='replace')
print("新浪股吧......done")
except Exception as e:
print(e)
def get_data_from_tushare():
# 1- 通过接口获取股票数据，pandas.core.frame.DataFrame
# data = ts.get_k_data('hs300', start='2019-01-01', end='2019-06-05')
# 2- 设置 DataFrame 索引
# data.set_index('date', inplace=True)
# 3- 画出股价走势图。下面的写法等价于 data.close.plot(figsize=(10, 6))
# data['close'].plot(figsize=(10, 6))
# print(data.head())
# plt.show()
# 4- 获取数据，tushare 不支持多股票查询。
# data1 = ts.get_k_data('600030') # 默认前复权价格
# data2 = ts.get_k_data('600030', autype='hfq') # 不复权
# data3 = ts.get_k_data('600030', ktype='5') # 两个日期之间的前复权价格
# 4.1- 获取历史逐笔交易数据
# df = ts.get_tick_data('601166', date='2019-06-06')
# print(type(df))
# df.sort_index(inplace=True, ascending=False)
# print(df.head())
# 4.2- 获取当前主流指数列表
# df = ts.get_index()
# print(df.head())
# 4.3- 获取股票基本面数据
# df = ts.get_stock_basics()
# print(df.head)
# df.set_index('code', inplace=True)
# data = ts.get_profit_data(2019, 1)
# print(data.head)
# date = df.ix['600848']['timeToMarket']
# print(date)
# 4.4- 获取非结构化新闻、舆情数据。接口获取不了数据
data = ts.get_latest_news(top=5, show_content=True) # 显示最多5条新闻，并打印新闻内容
print(type(data))
__author__='Bill Dan'
import tushare as ts
import pymongo
from pymongo import MongoClient
import json
# conn=pymongo.Connection('127.0.0.1',port=27017)
client = MongoClient()
client = MongoClient('mongodb://47.92.39.111:27017/')
db=client.refdata
print 'start ...'
df =ts.get_latest_news(top=5,show_content=True)
#get current year shibor
#df = ts.shibor_data(2014) #get 2014 year shibor
# df.sort('date', ascending=False).head(10)
db.shibor_data.insert(json.loads(df.to_json(orient='records')))
print 'success'
def news():
getnews = ts.get_latest_news()
print(type(getnews))
print(getnews)
# print(getnews)
'''
def getlastedNews(self):
return ts.get_latest_news(10, True)
import tushare as ts import sys df =ts.get_latest_news() df.to_csv(sys.argv[1],encoding="utf8")
@author: colec
"""
import tushare as ts
import time
file_result = open("NewsWaterfall.txt", "w+")
isLoop = True
while isLoop:
resultTime = time.localtime(time.time())
formatResultTime = time.strftime("%Y-%m-%d %H:%M:%S", resultTime)
file_result.write(formatResultTime)
file_result.write("\n")
newsList = ts.get_latest_news()
if newsList is None:
continue
print("test")
for idx, dataRow in newsList.iterrows():
file_result.write(str(idx))
file_result.write(" ")
file_result.write(dataRow["classify"].encode("utf-8"))
file_result.write(" ")
file_result.write(dataRow["title"].encode("utf-8"))
file_result.write(" ")
file_result.write(dataRow["time"])
file_result.write(" ")
file_result.write(dataRow["url"])
file_result.write("\n")