def job_new_share(start, end):
df_col_list = dbs["stock_basic"]["new_share"]["query_cols"].split(",")
day_interval = (end - start).days
if day_interval > 3000:
gap = day_interval
for i in range(3000, 0, -1):
if gap % i == 0:
day_interval = i
break
new_share = pd.DataFrame(columns=df_col_list)
num = (end - start).days
pro = ts.pro_api()
for i in range(0, num, day_interval):
new_share = new_share.append(
pro.new_share(
start_date=(start +
datetime.timedelta(days=i)).strftime('%Y%m%d'),
end_date=(start + datetime.timedelta(days=i + day_interval)
).strftime('%Y%m%d'),
fields=dbs["stock_basic"]["new_share"]["query_cols"]))
float_to_str_list = [
'issue_date', 'amount', 'market_amount', 'price', 'pe', 'limit_amount',
'funds', 'ballot'
]
new_share = basicFunctions.floatToStr(new_share, float_to_str_list, False)
sqlFunctions.insertSql(
"stock_basic", new_share, "new_share",
tuple(dbs["stock_basic"]["new_share"]["query_cols"].split(",")))
def get_namechange(first):
pro = ts.pro_api()
if first:
start_dt = '19901219'
else:
start_dt = open(basicFunctions.startDt, 'r').read()
namechange = pro.namechange(
start_date=start_dt,
end_date=end_dt,
fields=dbs["stock_basic"]["namechange"]["query_cols"])
sqlFunctions.insertSql(
"stock_basic", namechange, "namechange",
tuple(dbs["stock_basic"]["namechange"]["query_cols"].split(",")))
print("已获取股票曾用名")
def get_stock_basic_d(first):
"""
无area、industry。
:param first:
:return:
"""
pro = ts.pro_api()
stock_basic_d = pro.stock_basic(
list_status='D',
fields=dbs["stock_basic"]["stock_basic_d"]["query_cols"])
sqlFunctions.insertSql(
"stock_basic", stock_basic_d, "stock_basic_d",
tuple(dbs["stock_basic"]["stock_basic_d"]["query_cols"].split(",")))
print("已获取退市股票列表")
def job_stk_managers(ts_code_listStr):
df_col_list = dbs["stock_basic"]["stk_managers"]["query_cols"].split(",")
interval = 150
stk_managers = pd.DataFrame(columns=df_col_list)
pro = ts.pro_api()
print("正在获取", ts_code_listStr[:9], "等上市公司管理层")
for i in range(0, len(ts_code_listStr), interval):
stk_managers = stk_managers.append(
pro.stk_managers(
ts_code=ts_code_listStr[i:i + interval],
fields=dbs["stock_basic"]["stk_managers"]["query_cols"]))
time.sleep(0.6)
print("stock_basic.stk_managers 开始插入：", len(stk_managers))
sqlFunctions.insertSql(
"stock_basic", stk_managers, "stk_managers",
tuple(dbs["stock_basic"]["stk_managers"]["query_cols"].split(",")))
def get_moneyflow(start_dt, ts_code):
df_col_list = dbs["stock_daily"]["moneyflow"]["query_cols"].split(",")
moneyflow = pd.DataFrame(columns=df_col_list)
day_interval = 2000
start_dt_query = start_dt
if start_dt == "19901219":
time_temp = datetime.datetime(
1990, 12, 19) + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
else:
time_temp = datetime.datetime.now()
end_dt_query = end_dt
pro = ts.pro_api()
while start_dt_query <= end_dt:
moneyflow = moneyflow.append(pro.moneyflow(
ts_code=ts_code.replace("_", "."),
start_date=start_dt_query,
end_date=end_dt_query,
fields=dbs["stock_daily"]["moneyflow"]["query_cols"]),
sort=False)
time.sleep(0.6)
time_temp = time_temp + datetime.timedelta(days=1)
start_dt_query = time_temp.strftime('%Y%m%d')
time_temp = time_temp + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
if moneyflow is not None:
if len(moneyflow) > 0:
float_to_str_list = [
"buy_sm_vol", "buy_sm_amount", "sell_sm_vol", "sell_sm_amount",
"buy_md_vol", "buy_md_amount", "sell_md_vol", "sell_md_amount",
"buy_lg_vol", "buy_lg_amount", "sell_lg_vol", "sell_lg_amount",
"buy_elg_vol", "buy_elg_amount", "sell_elg_vol",
"sell_elg_amount", "net_mf_vol", "net_mf_amount"
]
moneyflow = basicFunctions.floatToStr(moneyflow, float_to_str_list,
False)
print("开始插入", ts_code, "个股资金流向数据：", len(moneyflow))
sqlFunctions.insertSql(
"stock_daily", moneyflow, ts_code,
tuple(
dbs["stock_daily"]["moneyflow"]["query_cols"].split(",")))
else:
print(ts_code, "无个股资金流向数据")
else:
print(ts_code, "无个股资金流向数据")
def get_stock_basic_l_or_p(first):
"""
无delist_date
:param first:
:return:
"""
pro = ts.pro_api()
stock_basic_L = pro.stock_basic(
list_status='L',
fields=dbs["stock_basic"]["stock_basic_l_or_p"]["query_cols"])
stock_basic_P = pro.stock_basic(
list_status='P',
fields=dbs["stock_basic"]["stock_basic_l_or_p"]["query_cols"])
stock_basic_l_or_p = stock_basic_L.append(stock_basic_P)
sqlFunctions.insertSql(
"stock_basic", stock_basic_l_or_p, "stock_basic_l_or_p",
tuple(
dbs["stock_basic"]["stock_basic_l_or_p"]["query_cols"].split(",")))
print("已获取上市股票列表")
def get_daily_basic(start_dt, ts_code):
df_col_list = dbs["stock_daily"]["daily_basic"]["query_cols"].split(",")
daily_basic = pd.DataFrame(columns=df_col_list)
day_interval = 2000
start_dt_query = start_dt
if start_dt == "19901219":
time_temp = datetime.datetime(
1990, 12, 19) + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
else:
time_temp = datetime.datetime.now()
end_dt_query = end_dt
pro = ts.pro_api()
while start_dt_query <= end_dt:
daily_basic = daily_basic.append(pro.daily_basic(
ts_code=ts_code.replace("_", "."),
start_date=start_dt_query,
end_date=end_dt_query,
fields=dbs["stock_daily"]["daily_basic"]["query_cols"]),
sort=False)
time.sleep(0.6)
time_temp = time_temp + datetime.timedelta(days=1)
start_dt_query = time_temp.strftime('%Y%m%d')
time_temp = time_temp + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
if daily_basic is not None:
if len(daily_basic) > 0:
float_to_str_list = [
"turnover_rate", "turnover_rate_f", "volume_ratio", "pe",
"pe_ttm", "pb", "ps", "ps_ttm", "total_share", "float_share",
"free_share", "total_mv", "circ_mv"
]
daily_basic = basicFunctions.floatToStr(daily_basic,
float_to_str_list, False)
print("开始插入", ts_code, "每日指标数据：", len(daily_basic))
sqlFunctions.insertSql(
"stock_daily", daily_basic, ts_code,
tuple(dbs["stock_daily"]["daily_basic"]["query_cols"].split(
",")))
else:
print(ts_code, "无每日指标数据")
else:
print(ts_code, "无每日指标数据")
def get_hs_const(first):
pro = ts.pro_api()
sh_hs_const = pro.hs_const(
hs_type='SH',
is_new=0,
fields=dbs["stock_basic"]["hs_const"]["query_cols"]).append(
pro.hs_const(hs_type='SH',
fields=dbs["stock_basic"]["hs_const"]["query_cols"]))
sz_hs_const = pro.hs_const(
hs_type='SZ',
is_new=0,
fields=dbs["stock_basic"]["hs_const"]["query_cols"]).append(
pro.hs_const(hs_type='SZ',
fields=dbs["stock_basic"]["hs_const"]["query_cols"]))
hs_const = sh_hs_const.append(sz_hs_const)
sqlFunctions.insertSql(
"stock_basic", hs_const, "hs_const",
tuple(dbs["stock_basic"]["hs_const"]["query_cols"].split(",")))
print("已获取沪深股通成份股")
def get_daily(start_dt, ts_code):
df_col_list = dbs["stock_daily"]["daily"]["query_cols"].replace(
"change_", "change").split(",")
daily = pd.DataFrame(columns=df_col_list)
day_interval = 2000
start_dt_query = start_dt
if start_dt == "19901219":
time_temp = datetime.datetime(
1990, 12, 19) + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
else:
time_temp = datetime.datetime.now()
end_dt_query = end_dt
pro = ts.pro_api()
while start_dt_query <= end_dt:
daily = daily.append(pro.daily(
ts_code=ts_code.replace("_", "."),
start_date=start_dt_query,
end_date=end_dt_query,
fields=dbs["stock_daily"]["daily"]["query_cols"].replace(
"change_", "change")),
sort=False)
time.sleep(0.6)
time_temp = time_temp + datetime.timedelta(days=1)
start_dt_query = time_temp.strftime('%Y%m%d')
time_temp = time_temp + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
if daily is not None:
if len(daily) > 0:
float_to_str_list = [
"open", "high", "low", "close", "pre_close", "change",
"pct_chg", "vol", "amount"
]
daily = basicFunctions.floatToStr(daily, float_to_str_list, False)
print("开始插入", ts_code, "日线行情数据：", len(daily))
sqlFunctions.insertSql(
"stock_daily", daily, ts_code,
tuple(dbs["stock_daily"]["daily"]["query_cols"].split(",")))
else:
print(ts_code, "无日线行情数据")
else:
print(ts_code, "无日线行情数据")
def get_stock_company(first):
pro = ts.pro_api()
sse_stock_company = pro.stock_company(
fields=dbs["stock_basic"]["stock_company"]["query_cols"])
szse_stock_company = pro.stock_company(
exchange='SZSE',
fields=dbs["stock_basic"]["stock_company"]["query_cols"])
stock_company = sse_stock_company.append(szse_stock_company)
float_to_str_list = ['reg_capital']
stock_company = basicFunctions.floatToStr(stock_company, float_to_str_list,
False)
float_to_int_to_str_list = ['employees']
stock_company = basicFunctions.floatToStr(stock_company,
float_to_int_to_str_list, True)
sqlFunctions.insertSql(
"stock_basic", stock_company, "stock_company",
tuple(dbs["stock_basic"]["stock_company"]["query_cols"].split(",")))
with open(basicFunctions.lockF, 'w') as f:
f.write("1")
print("已获取上市公司基本信息")
def job_stk_rewards(ts_code_listStr):
df_col_list = dbs["stock_basic"]["stk_rewards"]["query_cols"].split(",")
interval = 50
stk_rewards = pd.DataFrame(columns=df_col_list)
pro = ts.pro_api()
print("正在获取", ts_code_listStr[:9], "等管理层薪酬和持股")
for i in range(0, len(ts_code_listStr), interval):
stk_rewards = stk_rewards.append(
pro.stk_rewards(
ts_code=ts_code_listStr[i:i + interval],
fields=dbs["stock_basic"]["stk_rewards"]["query_cols"]))
time.sleep(0.6)
float_to_str_list = ['reward']
stk_rewards = basicFunctions.floatToStr(stk_rewards, float_to_str_list,
False)
float_to_int_to_str_list = ['hold_vol']
stk_rewards = basicFunctions.floatToStr(stk_rewards,
float_to_int_to_str_list, True)
print("stock_basic.stk_rewards 开始插入：", len(stk_rewards))
sqlFunctions.insertSql(
"stock_basic", stk_rewards, "stk_rewards",
tuple(dbs["stock_basic"]["stk_rewards"]["query_cols"].split(",")))
def get_stk_limit(start_dt, ts_code):
df_col_list = dbs["stock_daily"]["stk_limit"]["query_cols"].split(",")
stk_limit = pd.DataFrame(columns=df_col_list)
day_interval = 2000
start_dt_query = start_dt
if start_dt == "19901219":
time_temp = datetime.datetime(
1990, 12, 19) + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
else:
time_temp = datetime.datetime.now()
end_dt_query = end_dt
pro = ts.pro_api()
while start_dt_query <= end_dt:
stk_limit = stk_limit.append(pro.stk_limit(
ts_code=ts_code.replace("_", "."),
start_date=start_dt_query,
end_date=end_dt_query,
fields=dbs["stock_daily"]["stk_limit"]["query_cols"]),
sort=False)
time.sleep(0.6)
time_temp = time_temp + datetime.timedelta(days=1)
start_dt_query = time_temp.strftime('%Y%m%d')
time_temp = time_temp + datetime.timedelta(days=day_interval)
end_dt_query = time_temp.strftime('%Y%m%d')
if stk_limit is not None:
if len(stk_limit) > 0:
float_to_str_list = ["up_limit", "down_limit"]
stk_limit = basicFunctions.floatToStr(stk_limit, float_to_str_list,
False)
print("开始插入", ts_code, "每日涨跌停价格数据：", len(stk_limit))
sqlFunctions.insertSql(
"stock_daily", stk_limit, ts_code,
tuple(
dbs["stock_daily"]["stk_limit"]["query_cols"].split(",")))
else:
print(ts_code, "无每日涨跌停价格数据")
else:
print(ts_code, "无每日涨跌停价格数据")
def get_trade_cal(first):
pro = ts.pro_api()
if first:
start_dt = '19901219'
else:
start_dt = open(basicFunctions.startDt, 'r').read()
sse_trade_cal = pro.trade_cal(
exchange='SSE',
start_date=start_dt,
end_date=end_dt,
fields=dbs["stock_basic"]["trade_cal"]["query_cols"])
szse_trade_cal = pro.trade_cal(
exchange='SZSE',
start_date=start_dt,
end_date=end_dt,
fields=dbs["stock_basic"]["trade_cal"]["query_cols"])
trade_cal = sse_trade_cal.append(szse_trade_cal)
trade_cal['is_open'] = trade_cal['is_open'].astype(str) # 将一整列由int转为str
sqlFunctions.insertSql(
"stock_basic", trade_cal, "trade_cal",
tuple(dbs["stock_basic"]["trade_cal"]["query_cols"].split(",")))
print("已获取交易日历")