def get_member_rank(obj, trading_date=None, rank_by='volume', **kwargs):
"""获取指定日期最近的期货会员排名数据
:param obj： 期货合约或品种代码
:param trading_date: 日期
:param rank_by: 排名依据字段
:keyword start_date
:keyword end_date
:returns pandas.DataFrame or None
"""
if not kwargs:
trading_date = ensure_date_or_today_int(trading_date)
ret = get_client().execute("futures.get_member_rank", obj,
trading_date, rank_by)
else:
start_date = kwargs.pop("start_date", None)
end_date = kwargs.pop("end_date", None)
if kwargs:
raise ValueError('unknown kwargs: {}'.format(kwargs))
elif start_date and end_date:
start_date, end_date = ensure_date_int(
start_date), ensure_date_int(end_date)
ret = get_client().execute("futures.get_member_rank_v2", obj,
start_date, end_date, rank_by)
else:
raise ValueError('please ensure start_date and end_date exist')
if not ret:
return
df = pd.DataFrame(ret).sort_values(by=['trading_date', 'rank'])
df.set_index('trading_date', inplace=True)
return df
def get_instrument_industry(order_book_ids,
source='sws',
level=1,
date=None,
market="cn"):
"""获取股票对应的行业
:param order_book_ids: 股票列表，如['000001.XSHE', '000002.XSHE']
:param source: 分类来源。sws: 申万, citics: 中信, gildata: 聚源
:param date: 如 '2015-01-07' (Default value = None)
:param level: (Default value = 1)
:param market: (Default value = "cn")
:returns: code, name
返回输入日期最近交易日的股票对应行业
"""
order_book_ids = ensure_order_book_ids(order_book_ids)
source = ensure_string_in(source, ["sws", "citics", "gildata"], "source")
check_items_in_container(level, [0, 1, 2, 3], 'level')
date = ensure_date_or_today_int(date)
r = get_client().execute("get_instrument_industry",
order_book_ids,
source,
level,
date,
market=market)
if not r:
return
return pd.DataFrame(r).set_index("order_book_id")
def concept_list(date=None, market="cn"):
"""获取所有股票概念.
:param date: 可指定日期，默认按当前日期返回.
:param market: 地区代码, 如 'cn' (Default value = "cn")
:returns: 符合指定日期内出现过的所有概念列表
"""
date = ensure_date_or_today_int(date)
return get_client().execute("concept_list", date, market=market)
def _is_st_stock(order_book_id, date=None, market="cn"):
"""判断股票在给定日期是否是ST股
:param order_book_id: 股票id
:param date: (Default value = None)
:param market: (Default value = "cn")
:returns: True or False
"""
order_book_id = ensure_order_book_id(order_book_id, type="CS", market=market)
date = ensure_date_or_today_int(date)
df = is_st_stock(order_book_id, start_date=date, end_date=date, market=market)
if df is None or df.empty:
return False
else:
return df[order_book_id][0]
def concept_names(order_book_id, date=None, market="cn"):
"""获取证券所属的概念列表。
:param order_book_id: 证券ID
:param date: 可指定日期，默认按当前日期返回。
:param market: 地区代码, 如 'cn' (Default value = "cn")
:returns: 概念列表
"""
date = ensure_date_or_today_int(date)
return get_client().execute("concept_names",
order_book_id,
date,
market=market)
def get_instrument_industry(order_book_ids,
source='citics',
level=1,
date=None,
market="cn"):
"""获取股票对应的行业
:param order_book_ids: 股票列表，如['000001.XSHE', '000002.XSHE']
:param source: 分类来源。citics 以及 citics_2019: 中信, gildata: 聚源
:param date: 如 '2015-01-07' (Default value = None)
:param level: (Default value = 1)
:param market: (Default value = "cn")
:returns: code, name
返回输入日期最近交易日的股票对应行业
"""
order_book_ids = ensure_order_book_ids(order_book_ids)
source = ensure_string_in(source,
["sws", "citics", "gildata", "citics_2019"],
"source")
if source == "citics_2019":
check_items_in_container(level, [0, 1, 2, 3, "citics_sector"], 'level')
else:
check_items_in_container(level, [0, 1, 2, 3], 'level')
date = ensure_date_or_today_int(date)
r = get_client().execute("get_instrument_industry",
order_book_ids,
source,
level,
date,
market=market)
if not r:
return
res = [i['order_book_id'] for i in r]
if source == "citics_2019" and level == "citics_sector":
# is_special industry是否传入的是风格版块，产业板块和上下游产业版块
from rqdatac.services import basic
res_list = basic.instruments(res)
date = to_date_str(date)
for index, order_book in enumerate(res_list):
if order_book.de_listed_date == "0000-00-00" or order_book.de_listed_date is None:
order_book.de_listed_date = "2099-12-31"
if not order_book.listed_date <= date <= order_book.de_listed_date:
r.pop(index)
return pd.DataFrame(r).set_index("order_book_id")
def concept(*concepts, **kwargs):
"""获取对应某个概念的股票列表。
可指定日期，默认按当前日期返回。目前支持的概念列表可以查询以下网址:
https://www.ricequant.com/api/research/chn#concept-API-industry
:param concepts: 概念字符串,如 '民营医院'
:param date: 可指定日期，默认按当前日期返回.
:param market: 地区代码, 如 'cn'
:returns: 符合对应概念的股票列表
"""
date = kwargs.pop("date", None)
market = kwargs.pop("market", "cn")
date = ensure_date_or_today_int(date)
if kwargs:
raise ValueError('unknown kwargs: {}'.format(kwargs))
return get_client().execute("concept", concepts, date, market=market)
def get_industry(industry, source='sws', date=None, market="cn"):
"""获取行业股票列表
:param industry: 行业名称或代码
:param source: 分类来源。sws: 申万, citics: 中信, gildata: 聚源
:param date: 查询日期，默认为当前最新日期
:param market: (Default value = "cn")
:return: 所属目标行业的order_book_id list or None
"""
industry = ensure_string(industry, "industry")
source = ensure_string_in(source, ["sws", "citics", "gildata"], "source")
date = ensure_date_or_today_int(date)
res = get_client().execute("get_industry",
industry,
source,
date,
market=market)
return sorted(res)
def concept_names(order_book_id, date=None, expect_type="str", market="cn"):
"""获取证券所属的概念列表。
:param order_book_id: 证券ID
:param date: 可指定日期，默认按当前日期返回。
:param expect_type: 期望返回结果类型，可选址为："str"：返回字符串，"list"：返回列表，默认为str。
:param market: 地区代码, 如 "cn" (Default value = "cn")
:returns: 概念列表
"""
date = ensure_date_or_today_int(date)
data = get_client().execute("concept_names",
order_book_id,
date,
market=market)
if expect_type == "str":
return data
elif expect_type == "list":
return data.split("|")
raise ValueError("expect_type should be str like 'str' or 'list'")
def get_industry(industry, source='citics', date=None, market="cn"):
"""获取行业股票列表
:param industry: 行业名称或代码
:param source: 分类来源。citics 以及 citics_2019: 中信, gildata: 聚源
:param date: 查询日期，默认为当前最新日期
:param market: (Default value = "cn")
:return: 所属目标行业的order_book_id list or None
"""
industry = ensure_string(industry, "industry")
source = ensure_string_in(source,
["sws", "citics", "gildata", "citics_2019"],
"source")
date = ensure_date_or_today_int(date)
res = get_client().execute("get_industry",
industry,
source,
date,
market=market)
if not res:
return res
if res[-1] == "have_sector_name":
# have_sector_name 代表 industry传入的是风格版块，产业板块或者上下游产业版块
from rqdatac.services import basic
res_list = basic.instruments(res[:-1])
res = []
date = to_date_str(date)
for order_book in res_list:
if order_book.de_listed_date == "0000-00-00" or order_book.de_listed_date is None:
order_book.de_listed_date = "2099-12-31"
if order_book.listed_date <= date <= order_book.de_listed_date:
res.append(order_book.order_book_id)
return sorted(res)
def get_trading_hours(order_book_id,
date=None,
expected_fmt="str",
frequency="1m",
market="cn"):
"""获取合约指定日期交易时间
:param order_book_id: 合约代码
:param date: 日期，默认为今天
:param expected_fmt: 返回格式，默认为str, 也支持datetime.time和datetime.datetime格式
:param frequency: 频率，默认为1m, 对应米筐分钟线时间段的起始, tick和1m相比区别在于每个交易时间段开盘往前移一分钟
:param market: (Default value = "cn")
:return: trading_hours str or list of datetime.time/datetime.datetime list or None
"""
date = ensure_date_or_today_int(date)
if not is_trading_date(date, market):
warnings.warn(" %d is not a trading date" % date)
return
ensure_string(order_book_id, "order_book_id")
ins = instruments(order_book_id)
if ins is None:
return
ensure_string_in(expected_fmt, ("str", "time", "datetime"), "expected_fmt")
ensure_string_in(frequency, ("1m", "tick"), "frequency")
date_str = to_date_str(date)
if ins.listed_date > date_str:
return
if ins.type in (
"Future", "Option"
) and ins.de_listed_date < date_str and ins.de_listed_date != "0000-00-00":
return
if ins.type not in (
"Future", "Option"
) and ins.de_listed_date <= date_str and ins.de_listed_date != "0000-00-00":
return
if ins.type == "Repo":
trading_hours = "09:31-11:30,13:01-15:30"
elif ins.type == "Spot":
if has_night_trading(date, market):
trading_hours = "20:01-02:30,09:01-15:30"
else:
trading_hours = "09:01-15:30"
elif ins.type not in ("Future",
"Option") or (ins.type == "Option"
and ins.exchange in ("XSHG", "XSHE")):
trading_hours = "09:31-11:30,13:01-15:00"
else:
trading_hours = get_client().execute("get_trading_hours",
ins.underlying_symbol,
date,
market=market)
if trading_hours is None:
return
# 前一天放假或者该品种上市首日没有夜盘
no_night_trading = (not has_night_trading(date, market)
or get_underlying_listed_date(
ins.underlying_symbol, ins.type) == date_str)
if no_night_trading and not trading_hours.startswith("09"):
trading_hours = trading_hours.split(",", 1)[-1]
if frequency == "tick":
trading_hours = ",".join([
s[:4] + str(int(s[4]) - 1) + s[5:]
for s in trading_hours.split(",")
])
if expected_fmt != "str":
trading_hours = [t.split("-", 1) for t in trading_hours.split(",")]
for i, (start, end) in enumerate(trading_hours):
trading_hours[i][0] = str_to_dt_time(start)
trading_hours[i][1] = str_to_dt_time(end)
if expected_fmt == "datetime":
td = int8_to_date(date)
prev_td = get_previous_trading_date(date)
prev_td_next = prev_td + datetime.timedelta(days=1)
for i, (start, end) in enumerate(trading_hours):
if start.hour > 16:
start_dt = prev_td
end_dt = start_dt if end.hour > 16 else prev_td_next
else:
start_dt = end_dt = td
trading_hours[i][0] = datetime.datetime.combine(
start_dt, start)
trading_hours[i][1] = datetime.datetime.combine(end_dt, end)
return trading_hours
def get_securities_margin(order_book_ids,
start_date=None,
end_date=None,
fields=None,
expect_df=False,
market="cn"):
"""获取股票融资融券数据
:param order_book_ids: 股票代码或代码列表
:param start_date: 开始时间，支持 str, date, datetime, pandasTimestamp
默认为 end_date 之前一个月 (Default value = None)
:param end_date: 结束时间 默认为当前日期前一天 (Default value = None)
:param fields: str 或 list 类型. 默认为 None, 返回所有字段。可选字段包括：
today, week, month, three_month, six_month, year, current_year, total
(Default value = None)
:param expect_df: 返回 MultiIndex DataFrame (Default value = False)
:param market: 地区代码, 如: 'cn' (Default value = "cn")
:returns: 如果传入多个股票代码，且 fields 为多个或者 None，返回 pandas.Panel
如果传入一只股票或者 fields 为单个字段，则返回 pandas.DataFrame
如果传入的股票代码和字段数都是1，则返回 pandas.Series
"""
order_book_ids = ensure_list_of_string(order_book_ids, "order_book_ids")
all_list = []
for order_book_id in order_book_ids:
if order_book_id.upper() in MARGIN_SUMMARY_MAP:
all_list.append(MARGIN_SUMMARY_MAP[order_book_id.upper()])
else:
inst = instruments(order_book_id, market)
if inst.type in ["CS", "ETF", "LOF"]:
all_list.append(inst.order_book_id)
else:
warnings.warn(
"{} is not stock, ETF, or LOF.".format(order_book_id))
order_book_ids = all_list
if not order_book_ids:
raise ValueError("no valid securities in {}".format(order_book_ids))
if fields is None:
fields = list(MARGIN_FIELDS)
else:
fields = ensure_list_of_string(fields, "fields")
check_items_in_container(fields, MARGIN_FIELDS, "fields")
fields = ensure_order(fields, MARGIN_FIELDS)
start_date, end_date = ensure_date_range(start_date, end_date)
if end_date > ensure_date_or_today_int(None):
end_date = ensure_date_or_today_int(
get_previous_trading_date(datetime.date.today()))
trading_dates = pd.to_datetime(
get_trading_dates(start_date, end_date, market=market))
data = get_client().execute("get_securities_margin",
order_book_ids,
start_date,
end_date,
market=market)
if not data:
return
if expect_df:
df = pd.DataFrame(data)
df.sort_values(["order_book_id", "date"], inplace=True)
df.set_index(["order_book_id", "date"], inplace=True)
df = df.reindex(columns=fields)
return df
pl = pd.Panel(items=fields,
major_axis=trading_dates,
minor_axis=order_book_ids)
for r in data:
for field in fields:
value = r.get(field)
pl.at[field, r["date"], r["order_book_id"]] = value
if len(order_book_ids) == 1:
pl = pl.minor_xs(order_book_ids[0])
if len(fields) == 1:
pl = pl[fields[0]]
if len(order_book_ids) != 1 and len(fields) != 1:
warnings.warn(
"Panel is removed after pandas version 0.25.0."
" the default value of 'expect_df' will change to True in the future."
)
return pl
