def evaluation_stock(code):
# 以上一交易日的收盘价为判断点
try:
#print 'evaluation', getSixDigitalStockCode(code), 'begin'
date_end = datetime.date.today() + datetime.timedelta(-1)
df = get_stock_k_line(code)
if df is None:
return
else:
nearest_date = df.head(1)['date']
#print nearest_date
if str(nearest_date.values[0]) != str(date_end):
return
if len(df.index) > 30:
maStrategy = MACD_LIVE_TEST.MAStrategy(df=df)
signal = maStrategy.select_Time_Mix()
if signal > 0:
#print stock.name, stock.current, (float(stock.current)-float(stock.close))/float(stock.close)*100, '%'
print '>' * 5, 'Buy now!', getSixDigitalStockCode(code)
stock_buy_list.append(getSixDigitalStockCode(code))
elif signal < 0:
#print stock.name, stock.current, (float(stock.current)-float(stock.close))/float(stock.close)*100, '%'
print '>' * 5, 'Sale now!', getSixDigitalStockCode(code)
stock_sale_list.append(getSixDigitalStockCode(code))
except Exception as e:
print str(e)
def evaluation_stock(code):
# 以上一交易日的收盘价为判断点
try:
#print 'evaluation', getSixDigitalStockCode(code), 'begin'
date_end = datetime.date.today() + datetime.timedelta(-1)
df = get_stock_k_line(code)
if df is None:
return
else:
nearest_date = df.head(1)['date']
#print nearest_date
if str(nearest_date.values[0]) != str(date_end):
return
if len(df.index) > 30:
maStrategy = MACD_LIVE_TEST.MAStrategy(df=df)
signal = maStrategy.select_Time_Mix()
if signal > 0:
#print stock.name, stock.current, (float(stock.current)-float(stock.close))/float(stock.close)*100, '%'
print '>' * 5, 'Buy now!', getSixDigitalStockCode(code)
stock_buy_list.append(getSixDigitalStockCode(code))
elif signal < 0:
#print stock.name, stock.current, (float(stock.current)-float(stock.close))/float(stock.close)*100, '%'
print '>' * 5, 'Sale now!', getSixDigitalStockCode(code)
stock_sale_list.append(getSixDigitalStockCode(code))
except Exception as e:
print str(e)
def get_stock_k_line(code, date_start='', date_end=datetime.date.today()):
code = getSixDigitalStockCode(code)
fileName = 'h_kline_' + str(code) + '.csv'
df = None
#如果存在则直接取
if cm.DB_WAY == 'csv':
if os.path.exists(cm.DownloadDir+fileName):
df = pd.read_csv(cm.DownloadDir+fileName)
# 不存在则立即下载
# else:
# df = download_stock_kline(code, date_start, date_end)
elif cm.DB_WAY == 'redis':
r = redis.Redis(host='127.0.0.1', port=6379)
if len(date_start) == 0:
date_start = r.hget(cm.PRE_STOCK_BASIC+code, cm.KEY_TimeToMarket)
#date_start = '20150101'
date_start = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date_start.strftime("%Y-%m-%d")
date_end = date_end.strftime("%Y-%m-%d")
keys = r.lrange(cm.INDEX_STOCK_KLINE+code, 0, -1)
listSeries = []
for key in keys:
if key > date_start and key < date_end:
dict = r.hgetall(cm.PRE_STOCK_KLINE+code +':'+ key)
#_se = pd.Series(dict, index=[cm.KEY_DATE, cm.KEY_OPEN, cm.KEY_HIGH, cm.KEY_CLOSE, cm.KEY_LOW, cm.KEY_VOLUME,cm.KEY_AMOUNT])
_se = pd.Series(dict, index=[cm.KEY_DATE, cm.KEY_CLOSE])
listSeries.append(_se)
df = pd.DataFrame(listSeries)
elif cm.DB_WAY == 'sqlite':
#engine = create_engine('sqlite:///:memory:')
engine = create_engine('sqlite:///..\stocks.db3')
if len(date_start) == 0:
# date_start = r.hget(cm.PRE_STOCK_BASIC+code, cm.KEY_TimeToMarket)
# date_start = datetime.datetime.strptime(str(date_start), "%Y%m%d")
# date_start = date_start.strftime("%Y-%m-%d")
date_start = '2015-01-01'
date_end = date_end.strftime("%Y-%m-%d")
try:
sql = "select %s, %s from %s where %s > '%s' and %s < '%s' order by %s asc" % \
(cm.KEY_DATE, cm.KEY_CLOSE, cm.PRE_STOCK_KLINE_Sqlite+code, cm.KEY_DATE, date_start, \
cm.KEY_DATE, date_end, cm.KEY_DATE)
df = pd.read_sql_query(sql, engine)
except Exception as e:
print str(e)
return df
def download_stock_kline_to_redis(code, date_start="", date_end=datetime.date.today()):
code = util.getSixDigitalStockCode(code)
try:
if date_start == "":
dates = r.lrange(cm.INDEX_STOCK_KLINE + code, 0, -1)
if len(dates) > 0:
nearstDate = dates[0]
date = datetime.datetime.strptime(str(nearstDate), "%Y-%m-%d") + datetime.timedelta(1)
date_start = date.strftime("%Y-%m-%d")
else:
se = get_stock_info(code)
date_start = se["timeToMarket"]
date = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date.strftime("%Y-%m-%d")
date_end = date_end.strftime("%Y-%m-%d")
print "download " + str(code) + " k-line >>>begin (", date_start + u" 到 " + date_end + ")"
df_qfq = ts.get_h_data(str(code), start=date_start, end=date_end) # 前复权
if df_qfq is None:
return None
print "choose redis"
# 查数据库大小
print "\ndbsize:%s" % r.dbsize()
# 看连接
print "ping %s" % r.ping()
for idx, row in df_qfq.iterrows():
strDate = str(idx)[0:10]
mapStock = {
cm.KEY_DATE: strDate,
cm.KEY_OPEN: float(row["open"]),
cm.KEY_HIGH: float(row["high"]),
cm.KEY_CLOSE: float(row["close"]),
cm.KEY_VOLUME: float(row["volume"]),
cm.KEY_AMOUNT: float(row["amount"]),
}
# 写入hash表
r.hmset(cm.PRE_STOCK_KLINE + code + ":" + strDate, mapStock)
# 索引
r.rpush(cm.INDEX_STOCK_KLINE + code, strDate)
print "\ndownload " + str(code) + " k-line to redis finish"
except Exception as e:
print str(e)
return None
def download_stock_kline_to_redis(code, date_start='', date_end=datetime.date.today()):
code = util.getSixDigitalStockCode(code)
try:
if date_start == '':
dates = r.lrange(INDEX_STOCK_KLINE+code, 0, -1)
if len(dates) > 0:
nearstDate = dates[0]
date = datetime.datetime.strptime(str(nearstDate), "%Y-%m-%d") + datetime.timedelta(1)
date_start = date.strftime('%Y-%m-%d')
else:
se = get_stock_info(code)
date_start = se['timeToMarket']
date = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date.strftime('%Y-%m-%d')
date_end = date_end.strftime('%Y-%m-%d')
print 'download ' + str(code) + ' k-line >>>begin (', date_start+u' 到 '+date_end+')'
df_qfq = ts.get_h_data(str(code), start=date_start, end=date_end) # 前复权
if df_qfq is None:
return None
print 'choose redis'
# 查数据库大小
print '\ndbsize:%s' %r.dbsize()
# 看连接
print 'ping %s' %r.ping()
for idx, row in df_qfq.iterrows():
strDate = str(idx)[0:10]
mapStock = {KEY_DATE:strDate,KEY_OPEN:float(row['open']),KEY_HIGH:float(row['high']),\
KEY_CLOSE:float(row['close']), KEY_VOLUME:float(row['volume']),\
KEY_AMOUNT:float(row['amount'])}
# 写入hash表
r.hmset(PRE_STOCK_KLINE+code + ':' + strDate, mapStock)
#索引
r.rpush(INDEX_STOCK_KLINE+code, strDate)
print '\ndownload ' + str(code) + ' k-line to redis finish'
except Exception as e:
print str(e)
return None
def download_stock_quotes(code, date_start='', date_end=str(datetime.date.today())):
code = util.getSixDigitalStockCode(code)
try:
if date_start == '':
date = datetime.datetime.today().date() + datetime.timedelta(-365*3)
date_start = str(date)
dateStart = datetime.datetime.strptime(str(date_start), "%Y-%m-%d")
for i in range(du.diff_day(date_start, date_end)):
date = dateStart + datetime.timedelta(i)
strDate = date.strftime("%Y-%m-%d")
df = ts.get_tick_data(code, strDate)
print df
except Exception as e:
print str(e)
def download_stock_quotes(code, date_start='', date_end=str(datetime.date.today())):
code = util.getSixDigitalStockCode(code)
try:
if date_start == '':
date = datetime.datetime.today().date() + datetime.timedelta(-365*3)
date_start = str(date)
dateStart = datetime.datetime.strptime(str(date_start), "%Y-%m-%d")
for i in range(du.diff_day(date_start, date_end)):
date = dateStart + datetime.timedelta(i)
strDate = date.strftime("%Y-%m-%d")
df = ts.get_tick_data(code, strDate)
print df
except Exception as e:
print str(e)
def download_stock_kline_to_sql(code, date_start='', date_end=datetime.date.today()):
code = util.getSixDigitalStockCode(code)
try:
if date_start == '':
try:
sql = 'select %s from %s order by %s desc limit 1' % (KEY_DATE, PRE_STOCK_KLINE+code, KEY_DATE)
df = pd.read_sql_query(sql, engine)
dates = df[KEY_DATE].get_values()
except Exception, e:
print str(e)
dates = ''
if len(dates) > 0:
#print dates
nearstDate = str(dates[0])[:10]
date = datetime.datetime.strptime(str(nearstDate), "%Y-%m-%d") + datetime.timedelta(1)
date_start = date.strftime('%Y-%m-%d')
else:
se = get_stock_info(code)
date_start = se['timeToMarket']
date = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date.strftime('%Y-%m-%d')
date_end = date_end.strftime('%Y-%m-%d')
if date_start >= date_end:
return
print 'download ' + str(code) + ' k-line >>>begin (', date_start+u' 到 '+date_end+')'
df_qfq = download_kline_source_select(code, date_start, date_end)
if df_qfq is None:
return None
print df_qfq[-10:]
print 'choose mysql'
df_qfq.to_sql(PRE_STOCK_KLINE+code, engine,if_exists='append')
print '\ndownload ' + str(code) + ' k-line to mysql finish'
def get_stock_k_line(code, date_start='', date_end='', all_columns = False):
code = getSixDigitalStockCode(code)
if len(date_end) == 0:
date_end=datetime.date.today().strftime("%Y-%m-%d")
#DB_WAY == 'mysql':
try:
if len(date_start) == 0:
sql = "select * from %s where %s <= '%s' order by %s asc" % \
(PRE_STOCK_KLINE+code, KEY_DATE, date_end, KEY_DATE)
else:
sql = "select * from %s where %s >= '%s' and %s <= '%s' order by %s asc" % \
(PRE_STOCK_KLINE+code, KEY_DATE, date_start, KEY_DATE, date_end, KEY_DATE)
df = pd.read_sql_query(sql, engine)
return df
except Exception as e:
print str(e)
return None
def download_stock_kline_to_sqlite(code, date_start="", date_end=datetime.date.today()):
code = util.getSixDigitalStockCode(code)
try:
if date_start == "":
sql = "select %s from %s order by %s desc" % (cm.KEY_DATE, cm.PRE_STOCK_KLINE_Sqlite + code, cm.KEY_DATE)
df = pd.read_sql_query(sql, engine)
dates = df[cm.KEY_DATE].get_values()
if len(dates) > 0:
nearstDate = dates[0][:10]
date = datetime.datetime.strptime(str(nearstDate), "%Y-%m-%d") + datetime.timedelta(1)
date_start = date.strftime("%Y-%m-%d")
else:
se = get_stock_info(code)
date_start = se["timeToMarket"]
date = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date.strftime("%Y-%m-%d")
date_end = date_end.strftime("%Y-%m-%d")
# if date_start == '2015-07-11':
# return;
print "download " + str(code) + " k-line >>>begin (", date_start + u" 到 " + date_end + ")"
df_qfq = download_kline_source_select(False, code, date_start, date_end)
if df_qfq is None:
return None
print "choose sqlite"
df_qfq.to_sql(cm.PRE_STOCK_KLINE_Sqlite + code, engine, index=False, if_exists="append")
print "\ndownload " + str(code) + " k-line to sqlite finish"
except Exception as e:
print str(e)
return None
def download_stock_basic_info():
try:
df = ts.get_stock_basics()
# 直接保存
if cm.DB_WAY == "csv":
print "choose csv"
df.to_csv(cm.DownloadDir + cm.TABLE_STOCKS_BASIC + ".csv")
print "download csv finish"
elif cm.DB_WAY == "mysql":
print "choose mysql"
engineString = "mysql://" + cm.DB_USER + ":" + cm.DB_PWD + "@127.0.0.1/" + cm.DB_NAME + "?charset=utf8"
print engineString
engine = create_engine(engineString)
df.to_sql(cm.TABLE_STOCKS_BASIC, engine, if_exists="replace")
sql = "select * from " + cm.TABLE_STOCKS_BASIC + ' where code = "600000"'
dfRead = pd.read_sql(sql, engine)
print dfRead
elif cm.DB_WAY == "redis":
print "choose redis"
# 查数据库大小
print "\ndbsize:%s" % r.dbsize()
# 看连接
print "ping %s" % r.ping()
for idx, row in df.iterrows():
print idx, row
mapStock = {
cm.KEY_CODE: idx,
cm.KEY_NAME: row["name"],
cm.KEY_INDUSTRY: row["industry"],
cm.KEY_AREA: row["area"],
cm.KEY_TimeToMarket: row["timeToMarket"],
}
# 写入hash表
r.hmset(cm.PRE_STOCK_BASIC + idx, mapStock)
# 索引
r.sadd(cm.INDEX_STOCK_BASIC, idx)
# r.rpush(cm.INDEX_STOCK_BASIC, idx)
# print r.hgetall(PRE_BASIC+idx)
elif cm.DB_WAY == "sqlite":
con = sqlite3.connect("..\stocks.db3")
con.text_factory = str
cur = con.cursor()
# 创建基本信息表
sql_create_basic = (
"create table if not exists %s ( %s TEXT PRIMARY KEY, %s TEXT, %s TEXT \
, %s TEXT, %s REAL, %s REAL, %s REAL, %s TEXT)"
% (
cm.INDEX_STOCK_BASIC,
cm.KEY_CODE,
cm.KEY_NAME,
cm.KEY_INDUSTRY,
cm.KEY_AREA,
cm.KEY_PE,
cm.KEY_EPS,
cm.KEY_PB,
cm.KEY_TimeToMarket,
)
)
cur.execute(sql_create_basic)
# 清空表
cur.execute("delete from %s" % (cm.INDEX_STOCK_BASIC))
# 转换基本信息表
df = ts.get_stock_basics()
for idx, row in df.iterrows():
# print idx, row
code = util.getSixDigitalStockCode(idx)
sql_insert = "insert into %s (%s, %s, %s, %s, %s, %s, %s, %s) values(?,?,?,?,?,?,?,?)" % (
cm.INDEX_STOCK_BASIC,
cm.KEY_CODE,
cm.KEY_NAME,
cm.KEY_INDUSTRY,
cm.KEY_AREA,
cm.KEY_PE,
cm.KEY_EPS,
cm.KEY_PB,
cm.KEY_TimeToMarket,
)
cur.execute(
sql_insert,
(
code,
row["name"],
row["industry"],
row["area"],
float(row["pe"]),
float(row["esp"]),
float(row["pb"]),
row["timeToMarket"],
),
)
con.commit()
# 关闭数据库
con.close()
except Exception as e:
print str(e)
def download_stock_kline(code, date_start="", date_end=datetime.date.today()):
code = util.getSixDigitalStockCode(code)
try:
fileName = "h_kline_" + str(code) + ".csv"
writeMode = "w"
if os.path.exists(cm.DownloadDir + fileName):
# print (">>exist:" + code)
df = pd.DataFrame.from_csv(path=cm.DownloadDir + fileName)
se = df.head(1).index # 取已有文件的最近日期
dateNew = se[0] + datetime.timedelta(1)
date_start = dateNew.strftime("%Y-%m-%d")
# print date_start
writeMode = "a"
if date_start == "":
se = get_stock_info(code)
date_start = se["timeToMarket"]
date = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date.strftime("%Y-%m-%d")
date_end = date_end.strftime("%Y-%m-%d")
date_end = "2015-06-30"
# 已经是最新的数据
if date_start >= date_end:
df = pd.read_csv(cm.DownloadDir + fileName)
return df
print "download " + str(code) + " k-line >>>begin (", date_start + u" 到 " + date_end + ")"
df_qfq = ts.get_h_data(str(code), start=date_start, end=date_end) # 前复权
df_nfq = ts.get_h_data(str(code), start=date_start, end=date_end, autype=None) # 不复权
df_hfq = ts.get_h_data(str(code), start=date_start, end=date_end, autype="hfq") # 后复权
if df_qfq is None or df_nfq is None or df_hfq is None:
return None
df_qfq["open_no_fq"] = df_nfq["open"]
df_qfq["high_no_fq"] = df_nfq["high"]
df_qfq["close_no_fq"] = df_nfq["close"]
df_qfq["low_no_fq"] = df_nfq["low"]
df_qfq["open_hfq"] = df_hfq["open"]
df_qfq["high_hfq"] = df_hfq["high"]
df_qfq["close_hfq"] = df_hfq["close"]
df_qfq["low_hfq"] = df_hfq["low"]
if writeMode == "w":
df_qfq.to_csv(cm.DownloadDir + fileName)
else:
df_old = pd.DataFrame.from_csv(cm.DownloadDir + fileName)
# 按日期由远及近
df_old = df_old.reindex(df_old.index[::-1])
df_qfq = df_qfq.reindex(df_qfq.index[::-1])
df_new = df_old.append(df_qfq)
# print df_new
# 按日期由近及远
df_new = df_new.reindex(df_new.index[::-1])
df_new.to_csv(cm.DownloadDir + fileName)
# df_qfq = df_new
print "\ndownload " + str(code) + " k-line to csv finish"
return pd.read_csv(cm.DownloadDir + fileName)
except Exception as e:
print str(e)
return None
def download_stock_kline_csv(code, date_start='', date_end=datetime.date.today()):
code = util.getSixDigitalStockCode(code)
try:
fileName = 'h_kline_' + str(code) + '.csv'
writeMode = 'w'
if os.path.exists(DownloadDir+fileName):
#print (">>exist:" + code)
df = pd.DataFrame.from_csv(path=DownloadDir+fileName)
se = df.head(1).index #取已有文件的最近日期
dateNew = se[0] + datetime.timedelta(1)
date_start = dateNew.strftime("%Y-%m-%d")
#print date_start
writeMode = 'a'
if date_start == '':
se = get_stock_info(code)
date_start = se['timeToMarket']
date = datetime.datetime.strptime(str(date_start), "%Y%m%d")
date_start = date.strftime('%Y-%m-%d')
date_end = date_end.strftime('%Y-%m-%d')
date_end = '2015-06-30'
# 已经是最新的数据
if date_start >= date_end:
df = pd.read_csv(DownloadDir+fileName)
return df
print 'download ' + str(code) + ' k-line >>>begin (', date_start+u' 到 '+date_end+')'
df_qfq = ts.get_h_data(str(code), start=date_start, end=date_end) # 前复权
df_nfq = ts.get_h_data(str(code), start=date_start, end=date_end, autype=None) # 不复权
df_hfq = ts.get_h_data(str(code), start=date_start, end=date_end, autype='hfq') # 后复权
if df_qfq is None or df_nfq is None or df_hfq is None:
return None
df_qfq['open_no_fq'] = df_nfq['open']
df_qfq['high_no_fq'] = df_nfq['high']
df_qfq['close_no_fq'] = df_nfq['close']
df_qfq['low_no_fq'] = df_nfq['low']
df_qfq['open_hfq']=df_hfq['open']
df_qfq['high_hfq']=df_hfq['high']
df_qfq['close_hfq']=df_hfq['close']
df_qfq['low_hfq']=df_hfq['low']
if writeMode == 'w':
df_qfq.to_csv(DownloadDir+fileName)
else:
df_old = pd.DataFrame.from_csv(DownloadDir + fileName)
# 按日期由远及近
df_old = df_old.reindex(df_old.index[::-1])
df_qfq = df_qfq.reindex(df_qfq.index[::-1])
df_new = df_old.append(df_qfq)
#print df_new
# 按日期由近及远
df_new = df_new.reindex(df_new.index[::-1])
df_new.to_csv(DownloadDir+fileName)
#df_qfq = df_new
print '\ndownload ' + str(code) + ' k-line to csv finish'
return pd.read_csv(DownloadDir+fileName)
except Exception as e:
print str(e)
return None
