def import_tushare_adj_factor(chain_param=None, ):
"""
插入股票日线数据到最近一个工作日-1。
如果超过 BASE_LINE_HOUR 时间，则获取当日的数据
:return:
"""
table_name = 'tushare_stock_daily_adj_factor'
primary_keys = ["ts_code", "trade_date"]
logging.info("更新 %s 开始", table_name)
# 进行表格判断，确定是否含有 table_name
has_table = engine_md.has_table(table_name)
# sqlite_file_name = 'eDB_adjfactor.db'
check_sqlite_db_primary_keys(table_name, primary_keys)
if has_table:
sql_str = """
select cal_date
FROM
(
select * from tushare_trade_date trddate
where( cal_date>(SELECT max(trade_date) FROM {table_name}))
)tt
where (is_open=1
and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate())
and exchange='SSE') """.format(table_name=table_name)
else:
sql_str = """
SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1
AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate())
AND exchange='SSE') ORDER BY cal_date"""
logger.warning('%s 不存在，仅使用 tushare_stock_info 表进行计算日期范围', table_name)
with with_db_session(engine_md) as session:
# 获取交易日数据
table = session.execute(sql_str)
trade_date_list = [row[0] for row in table.fetchall()]
trade_date_count, data_count_tot = len(trade_date_list), 0
try:
for num, trade_date in enumerate(trade_date_list, start=1):
trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS)
data_df = pro.adj_factor(ts_code='', trade_date=trade_date)
if data_df is not None and data_df.shape[0] > 0:
data_count = bunch_insert(
data_df,
table_name=table_name,
dtype=DTYPE_TUSHARE_STOCK_DAILY_ADJ_FACTOR,
primary_keys=primary_keys)
data_count_tot += data_count
logging.info("%d/%d) %s 表 %s %d 条信息被更新", num, trade_date_count,
table_name, trade_date, data_count)
else:
logging.info("%d/%d) %s 表 %s 数据信息可被更新", num, trade_date_count,
table_name, trade_date)
except:
logger.exception("更新 %s 异常", table_name)
finally:
logging.info("%s 表 %d 条记录更新完成", table_name, data_count_tot)
def import_tushare_daily_basic(chain_param=None):
"""
插入股票日线数据到最近一个工作日-1。
如果超过 BASE_LINE_HOUR 时间，则获取当日的数据
:return:
"""
table_name = 'tushare_stock_daily_basic'
primary_keys = ["ts_code", "trade_date"]
logging.info("更新 %s 开始", table_name)
check_sqlite_db_primary_keys(table_name, primary_keys)
has_table = engine_md.has_table(table_name)
# 下面一定要注意引用表的来源，否则可能是串，提取混乱！！！
# 比如本表是 tushare_daily_basic，所以引用的也是这个，如果引用错误，就全部乱了
if has_table:
sql_str = """
select cal_date
FROM
(
select * from tushare_trade_date trddate
where( cal_date>(SELECT max(trade_date) FROM {table_name} ))
)tt
where (is_open=1
and cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate())
and exchange='SSE') """.format(table_name=table_name)
else:
sql_str = """
SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1
AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate())
AND exchange='SSE') ORDER BY cal_date"""
logger.warning('%s 不存在，仅使用 tushare_stock_info 表进行计算日期范围', table_name)
with with_db_session(engine_md) as session:
# 获取交易日数据
table = session.execute(sql_str)
trade_date_list = list(row[0] for row in table.fetchall())
try:
for_count = len(trade_date_list)
for num, trade_date in enumerate(trade_date_list, start=1):
trade_date = datetime_2_str(trade_date, STR_FORMAT_DATE_TS)
data_df = invoke_daily_basic(ts_code='', trade_date=trade_date)
if data_df is not None and data_df.shape[0] > 0:
data_count = bunch_insert(
data_df, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_DAILY_BASIC,
primary_keys=primary_keys)
logging.info("%d/%d) %s 更新 %s 结束 %d 条信息被更新", num, for_count, trade_date, table_name, data_count)
else:
logging.info("%d/%d) %s 无数据信息可被更新", num, for_count, trade_date)
except:
logger.exception("更新 %s 表异常", table_name)
def import_tushare_stock_daily(chain_param=None, ts_code_set=None):
"""
插入股票日线数据到最近一个工作日-1。
如果超过 BASE_LINE_HOUR 时间，则获取当日的数据
:return:
"""
table_name = 'tushare_stock_daily_md'
primary_keys = ["ts_code", "trade_date"]
check_sqlite_db_primary_keys(table_name, primary_keys)
logging.info("更新 %s 开始", table_name)
has_table = engine_md.has_table(table_name)
# 进行表格判断，确定是否含有tushare_stock_daily
if has_table:
sql_str = """
SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to
FROM
(
SELECT info.ts_code, ifnull(trade_date, list_date) date_frm, delist_date,
if(hour(now())<16, subdate(curdate(),1), curdate()) end_date
FROM
tushare_stock_info info
LEFT OUTER JOIN
(SELECT ts_code, adddate(max(trade_date),1) trade_date FROM {table_name} GROUP BY ts_code) daily
ON info.ts_code = daily.ts_code
) tt
WHERE date_frm <= if(delist_date<end_date, delist_date, end_date)
ORDER BY ts_code""".format(table_name=table_name)
else:
sql_str = """
SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to
FROM
(
SELECT info.ts_code, list_date date_frm, delist_date,
if(hour(now())<16, subdate(curdate(),1), curdate()) end_date
FROM tushare_stock_info info
) tt
WHERE date_frm <= if(delist_date<end_date, delist_date, end_date)
ORDER BY ts_code"""
logger.warning('%s 不存在，仅使用 tushare_stock_info 表进行计算日期范围', table_name)
sql_trade_date_str = """
SELECT cal_date FROM tushare_trade_date trddate WHERE (trddate.is_open=1
AND cal_date <= if(hour(now())<16, subdate(curdate(),1), curdate())
AND exchange='SSE') ORDER BY cal_date"""
with with_db_session(engine_md) as session:
table = session.execute(sql_trade_date_str)
trade_date_list = [row[0] for row in table.fetchall()]
trade_date_list.sort()
# 获取每只股票需要获取日线数据的日期区间
table = session.execute(sql_str)
# 计算每只股票需要获取日线数据的日期区间
begin_time = None
# 获取date_from,date_to，将date_from,date_to做为value值
code_date_range_dic = {
ts_code: (date_from if begin_time is None else min([date_from, begin_time]), date_to)
for ts_code, date_from, date_to in table.fetchall() if
ts_code_set is None or ts_code in ts_code_set}
# data_len = len(code_date_range_dic)
data_df_list, data_count, all_data_count, data_len = [], 0, 0, len(code_date_range_dic)
logger.info('%d data will been import into %s', data_len, table_name)
# 将data_df数据，添加到data_df_list
try:
for num, (ts_code, (date_from_tmp, date_to_tmp)) in enumerate(code_date_range_dic.items(), start=1):
date_from = get_first(trade_date_list, lambda x: x >= date_from_tmp)
date_to = get_last(trade_date_list, lambda x: x <= date_to_tmp)
if date_from is None or date_to is None or date_from > date_to:
logger.debug('%d/%d) %s [%s - %s] 跳过', num, data_len, ts_code, date_from, date_to)
continue
logger.debug('%d/%d) %s [%s - %s]', num, data_len, ts_code, date_from, date_to)
data_df = invoke_daily(ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS),
end_date=datetime_2_str(date_to, STR_FORMAT_DATE_TS))
# data_df = df
if len(data_df) > 0:
while try_2_date(data_df['trade_date'].iloc[-1]) > date_from:
last_date_in_df_last, last_date_in_df_cur = try_2_date(data_df['trade_date'].iloc[-1]), None
df2 = invoke_daily(ts_code=ts_code, start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS),
end_date=datetime_2_str(
try_2_date(data_df['trade_date'].iloc[-1]) - timedelta(days=1),
STR_FORMAT_DATE_TS))
if df2 is not None and len(df2) > 0:
last_date_in_df_cur = try_2_date(df2['trade_date'].iloc[-1])
if last_date_in_df_cur < last_date_in_df_last:
data_df = pd.concat([data_df, df2])
# df = df2
elif last_date_in_df_cur == last_date_in_df_last:
break
if data_df is None:
logger.warning('%d/%d) %s has no data during %s %s', num, data_len, ts_code, date_from,
date_to)
continue
logger.info('%d/%d) %d data of %s between %s and %s', num, data_len, data_df.shape[0], ts_code,
date_from, date_to)
else:
break
# 把数据攒起来
if data_df is not None and data_df.shape[0] > 0:
data_count += data_df.shape[0]
data_df_list.append(data_df)
# 大于阀值有开始插入
if data_count >= 500:
data_df_all = pd.concat(data_df_list)
data_count = bunch_insert(
data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_DAILY_MD,
primary_keys=primary_keys)
all_data_count += data_count
data_df_list, data_count = [], 0
if DEBUG and len(data_df_list) > 1:
break
finally:
# 导入数据库
if len(data_df_list) > 0:
data_df_all = pd.concat(data_df_list)
data_count = bunch_insert(
data_df_all, table_name=table_name, dtype=DTYPE_TUSHARE_STOCK_DAILY_MD,
primary_keys=primary_keys)
all_data_count = all_data_count + data_count
logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
def import_tushare_stock_cashflow(chain_param=None, ts_code_set=None):
"""
插入股票日线数据到最近一个工作日-1。
如果超过 BASE_LINE_HOUR 时间，则获取当日的数据
:return:
"""
table_name = 'tushare_stock_cashflow'
primary_keys = ['ts_code', 'ann_date', 'end_date']
logging.info("更新 %s 开始", table_name)
check_sqlite_db_primary_keys(table_name, primary_keys)
has_table = engine_md.has_table(table_name)
# 进行表格判断，确定是否含有tushare_stock_daily
if has_table:
sql_str = """
SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to
FROM
(
SELECT info.ts_code, ifnull(ann_date, list_date) date_frm, delist_date,
if(hour(now())<16, subdate(curdate(),1), curdate()) end_date
FROM
tushare_stock_info info
LEFT OUTER JOIN
(SELECT ts_code, adddate(max(ann_date),1) ann_date
FROM {table_name} GROUP BY ts_code) cashflow
ON info.ts_code = cashflow.ts_code
) tt
WHERE date_frm <= if(delist_date<end_date, delist_date, end_date)
ORDER BY ts_code""".format(table_name=table_name)
else:
sql_str = """
SELECT ts_code, date_frm, if(delist_date<end_date, delist_date, end_date) date_to
FROM
(
SELECT info.ts_code, list_date date_frm, delist_date,
if(hour(now())<16, subdate(curdate(),1), curdate()) end_date
FROM tushare_stock_info info
) tt
WHERE date_frm <= if(delist_date<end_date, delist_date, end_date)
ORDER BY ts_code"""
logger.warning('%s 不存在，仅使用 tushare_stock_info 表进行计算日期范围', table_name)
with with_db_session(engine_md) as session:
# 获取每只股票需要获取日线数据的日期区间
table = session.execute(sql_str)
# 计算每只股票需要获取日线数据的日期区间
begin_time = None
# 获取date_from,date_to，将date_from,date_to做为value值
code_date_range_dic = {
ts_code:
(date_from if begin_time is None else min([date_from, begin_time]),
date_to)
for ts_code, date_from, date_to in table.fetchall()
if ts_code_set is None or ts_code in ts_code_set
}
data_df_list, data_count, all_data_count, data_len = [], 0, 0, len(
code_date_range_dic)
logger.info('%d data will been import into %s', data_len, table_name)
# 将data_df数据，添加到data_df_list
cycles = 1
try:
for num, (ts_code, (date_from,
date_to)) in enumerate(code_date_range_dic.items(),
start=1):
logger.debug('%d/%d) %s [%s - %s]', num, data_len, ts_code,
date_from, date_to)
df = invoke_cashflow(
ts_code=ts_code,
start_date=datetime_2_str(date_from, STR_FORMAT_DATE_TS),
end_date=datetime_2_str(date_to, STR_FORMAT_DATE_TS))
# logger.info(' %d data of %s between %s and %s', df.shape[0], ts_code, date_from, date_to)
data_df = df
if data_df is not None and len(data_df) > 0:
while try_2_date(df['ann_date'].iloc[-1]) > date_from:
last_date_in_df_last, last_date_in_df_cur = try_2_date(
df['ann_date'].iloc[-1]), None
df2 = invoke_cashflow(
ts_code=ts_code,
start_date=datetime_2_str(date_from,
STR_FORMAT_DATE_TS),
end_date=datetime_2_str(
try_2_date(df['ann_date'].iloc[-1]) -
timedelta(days=1), STR_FORMAT_DATE_TS))
if len(df2) > 0:
last_date_in_df_cur = try_2_date(
df2['ann_date'].iloc[-1])
if last_date_in_df_cur < last_date_in_df_last:
data_df = pd.concat([data_df, df2])
df = df2
elif last_date_in_df_cur == last_date_in_df_last:
break
elif len(df2) <= 0:
break
if data_df is None:
logger.warning('%d/%d) %s has no data during %s %s', num,
data_len, ts_code, date_from, date_to)
continue
elif data_df is not None:
logger.info('%d/%d) %d 条 %s 的现金流被提取，起止时间为 %s 和 %s', num,
data_len, data_df.shape[0], ts_code, date_from,
date_to)
# 把数据攒起来
if data_df is not None and data_df.shape[0] > 0:
data_count += data_df.shape[0]
data_df_list.append(data_df)
# 大于阀值有开始插入
if data_count >= 1000 and len(data_df_list) > 0:
data_df_all = pd.concat(data_df_list)
bunch_insert(data_df_all,
table_name=table_name,
dtype=DTYPE_TUSHARE_CASHFLOW,
primary_keys=primary_keys)
logger.info('%d 条现金流数据已插入 %s 表', data_count, table_name)
all_data_count += data_count
data_df_list, data_count = [], 0
# # 数据插入数据库
# data_count = bunch_insert_on_duplicate_update(data_df, table_name, engine_md, DTYPE_TUSHARE_CASHFLOW)
# logging.info("更新 %s 结束 %d 条信息被更新", table_name, data_count)
# 仅调试使用
cycles = cycles + 1
if DEBUG and cycles > 10:
break
finally:
# 导入数据库
if len(data_df_list) > 0:
data_df_all = pd.concat(data_df_list)
data_count = bunch_insert(data_df_all,
table_name=table_name,
dtype=DTYPE_TUSHARE_CASHFLOW,
primary_keys=primary_keys)
all_data_count = all_data_count + data_count
logging.info("更新 %s 结束 %d 条信息被更新", table_name, all_data_count)
