import datetime
import talib as ta
import tushare as ts
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.db.stock_trade_calendar_dao as stock_trade_calendar_dao
import freedom.log.logger as my_logger
__logger = my_logger.getlogger('common')
def is_open_day(date):
"""
查看指定日期是否是交易日
:param date: 字符串日期，格式%Y-%m-%d
:return: True | False
"""
result = stock_trade_calendar_dao.select_one(date)
if result and result['is_open'] == 1:
return True
return False
def get_the_day_before_yesterday(date):
"""
获取指定日期前一天的日期
:param date
:return: date
"""
import datetime
import pandas as pd
import talib as ta
import freedom.common as my_common
import freedom.db.stock_base_dao as stock_base_dao
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.db.stock_trade_calendar_dao as stock_trade_calendar_dao
import freedom.log.logger as my_logger
import freedom.model.common_indicator as my_common_indicator
__logger = my_logger.getlogger("ma_scatter")
def sma_upward(code, date, timeperiod):
"""
计算指定日期指定周期均线是否开始拐头向上
:param code:
:param date:
:param timeperiod:
:return: True | False
"""
count = timeperiod + 2
stock_df = stock_trade_daily_dao.query_stock_trade_daily_limit_size(
code, str(date), count)
if len(stock_df) >= count:
last_trade_date = stock_df[len(stock_df) - 1:]['trade_date'].values[0]
if date.strftime('%Y-%m-%d') == str(last_trade_date):
sma_list = ta.SMA(stock_df['close'], timeperiod)
sma_1 = sma_list[len(sma_list) - 3]
import talib as ta
import freedom.common as my_common
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.log.logger as my_logger
__logger = my_logger.getlogger('common_indicator')
def avg_volume_ratio(code, date, avg_day=5):
"""
计算当日成交量是指定周期成交量均值的倍率
:param code:
:param date:
:param avg_day:
:return:
"""
last_date = my_common.get_the_day_before_yesterday(date)
df1 = stock_trade_daily_dao.query_stock_trade_daily_limit_size(
code, str(last_date), avg_day)
if len(df1) >= avg_day:
sma = ta.SMA(df1['volume'][len(df1) - avg_day:], avg_day)
v_avg = sma.values[len(sma) - 1]
# 当日成交量
df2 = stock_trade_daily_dao.query_stock_trade_daily(
code, str(date), str(date))
if not df2.empty:
v_current = df2[0:1]['volume'].values[0]
return v_current / v_avg
else:
__logger.warn("获取当前成交量信息为空, code = {}, date = {}".format(
import datetime
import pandas as pd
import talib as ta
import freedom.db.stock_base_dao as stock_base_dao
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.log.logger as my_logger
import freedom.common as my_common
import freedom.model.common_indicator as my_common_indicator
__logger = my_logger.getlogger('candle_stick')
def white_line_over_sma5_10_20(code, date):
"""
筛选上一个交易日的收盘价和当天收盘价由下到上穿越5、10、20日均线
:param df:
:return:
"""
df = stock_trade_daily_dao.query_stock_trade_daily_limit_size(code, str(date), 20)
if len(df) < 20:
# __logger.warn("Valid DataFrame data size less than 20, code = {}, date = {}".format(code, str(date)))
return False
# 当前收盘价
current_close = df[len(df) - 1:]['close'].values[0]
# 上一个交易日收盘价
yesterday_close = df[len(df) - 2:len(df) - 1]['close'].values[0]
if current_close > yesterday_close:
# 5日均线
import pandas as pd
import freedom.db.dbutil as db_util
import freedom.log.logger as my_logger
logger = my_logger.getlogger('stock_trade_daily_dao')
def query_stock_trade_daily(code, start_date, end_date):
"""
根据code、起止日期（包含）查询数据，并按照交易日期升序排序
:param code:
:param start_date:
:param end_date:
:return: DafaFrame
`code`, `open`, `high`, `low`, `close`, `volume`, `amount`, `turn_over_ratio`, `increase`, `amplitude`, `trade_date`
"""
sql = 'select `code`, `open`, `high`, `low`, `close`, `volume`, `amount`, `turn_over_ratio`, `increase`, `amplitude`, `trade_date` from stock_trade_daily where `code` = "{code}" and `trade_date` BETWEEN "{start_date}" and "{end_date}" order by `trade_date`'.format(
code=code, start_date=start_date, end_date=end_date)
try:
return pd.read_sql(sql, con=db_util.get_connection())
except:
logger.exception("query_stock_trade_daily error")
return None
def query_stock_trade_daily_limit_size(code, end_date, size):
"""
查询指定交易日期（包含）前指定数量的数据
"""
回测连续涨停的股票
"""
import pandas as pd
import freedom.db.stock_base_dao as stock_base_dao
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.log.logger as my_logger
__logger = my_logger.getlogger('continuous_increase')
def _t1():
columns = ["code", "status", "trade_date"]
three_day_list = []
four_day_list = []
# 涨停
increase_upper = 9.8
start_date = '2017-01-01'
end_date = '2018-10-01'
stock_base_list = stock_base_dao.query_stock_base()
# stock_base_list = stock_base_list[0:100]
for stock_base in stock_base_list:
df = stock_trade_daily_dao.query_stock_trade_daily(
stock_base['code'], start_date, end_date)
start_index = 0
end_index = start_index + 1
length = len(df)
while end_index <= length:
increase = df[start_index:end_index]['increase'].values[0]
import datetime
import pandas as pd
import freedom.common as my_common
import freedom.db.stock_base_dao as stock_base_dao
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.log.logger as my_logger
import freedom.model.common_indicator as my_common_indicator
__logger = my_logger.getlogger('high_open')
def is_jump_high(code, date):
"""
是否是跳空高开的数据
:param code: 代码
:return: True | False
"""
some_gap_date = date - datetime.timedelta(days=1)
stock_trade_df = stock_trade_daily_dao.query_stock_trade_daily(
code, str(some_gap_date), str(date))
if len(stock_trade_df) >= 2:
last = stock_trade_df[len(stock_trade_df) - 1:]
last2 = stock_trade_df[len(stock_trade_df) - 2:len(stock_trade_df) - 1]
last_low = last['low'].values[0]
last2_high = last2['high'].values[0]
if last_low - last2_high > 0:
return True
import freedom.db.dbutil as db_util
import freedom.log.logger as my_logger
__logger = my_logger.getlogger('stock_trade_calendar_dao')
def select_one(date):
"""
根据日期查询是否是交易日信息
:param date:
:return:
"""
result = {}
sql = 'select `date`, is_open from stock_trade_calendar where `date` = "{}"'.format(
date)
conn = db_util.get_connection()
try:
cur = conn.cursor()
cur.execute(sql)
res = cur.fetchone()
cur.close()
if len(res) > 0:
result['date'] = str(res[0])
result['is_open'] = res[1]
except:
__logger.exception("Query stock_trade_calendar error")
return result
import pandas as pd
import freedom.db.dbutil as db_util
import freedom.log.logger as my_logger
__logger = my_logger.getlogger('stock_base_dao')
def update_stock_status(code, status):
"""
修改stock交易状态
:param code:
:param status: 1: 正常; 2: 停牌
:return:
"""
sql = 'update stock_base set status = {} where code = "{}" and type = 1'.format(
status, code)
conn = db_util.get_connection()
try:
cur = conn.cursor()
cur.execute(sql)
conn.commit()
cur.close()
except:
conn.rollback()
__logger.exception("Update stock_status error")
def query_stock_base():
"""
import datetime
import tushare as ts
import pandas as pd
import freedom.common as my_common
import freedom.db.stock_base_dao as stock_base_dao
import freedom.db.stock_trade_daily_dao as stock_trade_daily_dao
import freedom.log.logger as my_logger
__logger = my_logger.getlogger('gather_data')
def check_stock_status(trade_date):
"""
利用当日成交数据校验系统中的数据停牌、交易状态是否正确
:return:
"""
if my_common.is_open_day(str(trade_date)):
day_all_df = ts.get_day_all(str(trade_date))
if not day_all_df.empty:
stock_series = stock_base_dao.query_stock_base_to_map()
for index, row in day_all_df.iterrows():
code = my_common.convert_standard_code(row['code'])
stock_local = stock_series.get(code)
# 本系统中无此stock数据
if not stock_local:
__logger.warning(
"Stock is not exists in local system, code = {}".
format(code))
continue