def get_fundamentals_n(table,
symbols,
end_date,
fields=None,
filter=None,
order_by=None,
count=1,
df=False):
"""
查询基本面财务数据,每个股票在end_date的前n条
"""
fields_str, fields_list = standard_fields(fields, letter_upper=True)
data = fundamentalapi.get_fundamentals_n(table=table,
symbols=symbols,
end_date=end_date,
fields=fields_str,
filter=filter,
order_by=order_by,
count=count)
if df:
data = pd.DataFrame(data)
if fields_list:
fields_list = ['symbol', 'pub_date', 'end_date'] + fields_list
columns = [field for field in fields_list if field in data.columns]
data = data[columns]
return data
def get_fundamentals(table,
symbols,
start_date,
end_date,
fields=None,
filter=None,
order_by=None,
limit=1000,
df=False):
"""
查询基本面财务数据
"""
fields_str, fields_list = standard_fields(fields, letter_upper=True)
start_date = utils.to_datestr(start_date)
end_date = utils.to_datestr(end_date)
data = fundamentalapi.get_fundamentals(table=table,
symbols=symbols,
start_date=start_date,
end_date=end_date,
fields=fields_str,
filter=filter,
order_by=order_by,
limit=limit)
if df:
data = pd.DataFrame(data)
if fields_list:
fields_list = ['symbol', 'pub_date', 'end_date'] + fields_list
columns = [field for field in fields_list if field in data.columns]
data = data[columns]
return data
def get_history_bars(self,
symbols,
frequency,
start_time,
end_time,
fields=None,
skip_suspended=True,
fill_missing=None,
adjust=ADJUST_NONE,
adjust_end_time='',
df=False):
self._init_addr()
req = GetHistoryBarsReq(symbols=symbols,
frequency=frequency,
start_time=start_time,
end_time=end_time,
fields=fields,
skip_suspended=skip_suspended,
fill_missing=fill_missing,
adjust=adjust,
adjust_end_time=adjust_end_time)
resp = self.stub.GetHistoryBars(
req,
metadata=[
(str('authorization'), context.token),
(str('grpc-internal-encoding-request'), str('gzip')),
(str('sdk-lang'), context.sdk_lang),
(str('sdk-version'), context.sdk_version),
(str('sdk-arch'), context.sdk_arch),
(str('sdk-os'), context.sdk_os),
])
datas = [
protobuf_to_dict(bar,
is_utc_time=True,
including_default_value_fields=True)
for bar in resp.data
]
fields_str, fields_list = standard_fields(fields, letter_upper=False)
if not fields_list:
datas = datas if not df else pd.DataFrame(datas)
return datas
else:
result = []
for data in datas:
info = {}
for field in fields_list:
info[field] = data.get(field)
result.append(info)
result = result if not df else pd.DataFrame(result)
return result
def get_constituents(index, fields=None, df=False):
"""
查询指数最新成分股
返回的list每项是个字典,包含的key值有:
symbol 股票symbol
weight 权重
"""
fields_str, fields_list = standard_fields(fields, letter_upper=False)
data = fundamentalapi.get_constituents(index, fields, df)
if df:
data = pd.DataFrame(data)
if fields_list:
columns = [field for field in fields_list if field in data.columns]
data = data[columns]
return data
def get_history_instruments(symbols,
fields=None,
start_date=None,
end_date=None,
df=False):
"""
返回指定的symbols的标的日指标数据
"""
fields_str, fields_list = standard_fields(fields, letter_upper=False)
data = fundamentalapi.get_history_instruments(symbols, fields_str,
start_date, end_date)
if df:
data = pd.DataFrame(data)
if fields_list:
columns = [field for field in fields_list if field in data.columns]
data = data[columns]
return data
def get_instrumentinfos(symbols=None,
exchanges=None,
sec_types=None,
names=None,
fields=None,
df=False):
"""
查询交易标的基本信息
如果没有数据的话,返回空列表. 有的话, 返回list[dict]这样的列表. 其中 listed_date, delisted_date 为 datetime 类型
@:param fields: 可以是 'symbol, sec_type' 这样的字符串, 也可以是 ['symbol', 'sec_type'] 这样的字符list
"""
fields_str, fields_list = standard_fields(fields, letter_upper=False)
data = fundamentalapi.get_instrumentinfos(symbols, exchanges, sec_types,
names, fields)
if df:
data = pd.DataFrame(data)
if fields_list:
columns = [field for field in fields_list if field in data.columns]
data = data[columns]
return data
def get_instruments(symbols=None,
exchanges=None,
sec_types=None,
names=None,
skip_suspended=True,
skip_st=True,
fields=None,
df=False):
"""
查询最新交易标的信息,有基本数据及最新日频数据
"""
fields_str, fields_list = standard_fields(fields, letter_upper=False)
data = fundamentalapi.get_instruments(symbols, exchanges, sec_types, names,
skip_suspended, skip_st, fields_str)
if df:
data = pd.DataFrame(data)
if fields_list:
columns = [field for field in fields_list if field in data.columns]
data = data[columns]
return data
