def futures_spot_price_previous(date: str = "20110110") -> pd.DataFrame:
"""
#TODO 修改该接口并观察历史数据能否获取
:param date:
:type date:
:return:
:rtype:
"""
date = cons.convert_date(
date) if date is not None else datetime.date.today()
if date < datetime.date(2011, 1, 4):
raise Exception("数据源开始日期为 20110104, 请将获取数据时间点设置在 20110104 后")
if date.strftime("%Y%m%d") not in calendar:
warnings.warn(f"{date.strftime('%Y%m%d')}非交易日")
return None
url = date.strftime('http://www.100ppi.com/sf2/day-%Y-%m-%d.html')
content = pandas_read_html_link(url)
main = content[1]
# Header
header = _join_head(main)
# Values
values = main[main[4].str.endswith('%')]
values.columns = header
# Basis
basis = pd.concat(content[2:-1])
basis.columns = ['主力合约基差', '主力合约基差(%)']
basis['商品'] = values['商品'].tolist()
basis = pd.merge(values[["商品", "现货价格", "主力合约代码", "主力合约价格"]], basis)
basis = pd.merge(
basis, values[["商品", "180日内主力基差最高", "180日内主力基差最低", "180日内主力基差平均"]])
return basis
def futures_spot_price(date: str = "20200110",
vars_list=cons.contract_symbols):
"""
某个交易日大宗商品现货价格及相应基差
:param date: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
:param vars_list: 合约品种如RB、AL等列表 为空时为所有商品
:return: pandas.DataFrame
展期收益率数据:
var 商品品种 string
sp 现货价格 float
near_symbol 临近交割合约 string
near_price 临近交割合约结算价 float
dom_symbol 主力合约 string
dom_price 主力合约结算价 float
near_basis 临近交割合约相对现货的基差 float
dom_basis 主力合约相对现货的基差 float
near_basis_rate 临近交割合约相对现货的基差率 float
dom_basis_rate 主力合约相对现货的基差率 float
date 日期 string YYYYMMDD
"""
date = cons.convert_date(
date) if date is not None else datetime.date.today()
if date < datetime.date(2011, 1, 4):
raise Exception("数据源开始日期为 20110104, 请将获取数据时间点设置在 20110104 后")
if date.strftime("%Y%m%d") not in calendar:
warnings.warn(f"{date.strftime('%Y%m%d')}非交易日")
return None
u1 = cons.SYS_SPOT_PRICE_LATEST_URL
u2 = cons.SYS_SPOT_PRICE_URL.format(date.strftime("%Y-%m-%d"))
i = 1
while True:
for url in [u2, u1]:
try:
# url = u2
r = pandas_read_html_link(url)
string = r[0].loc[1, 1]
news = "".join(re.findall(r"[0-9]", string))
if news[3:11] == date.strftime("%Y%m%d"):
records = _check_information(r[1], date)
records.index = records["symbol"]
var_list_in_market = [
i for i in vars_list if i in records.index
]
temp_df = records.loc[var_list_in_market, :]
temp_df.reset_index(drop=True, inplace=True)
return temp_df
else:
time.sleep(3)
except:
print(
f"{date.strftime('%Y-%m-%d')}日生意社数据连接失败，第{str(i)}次尝试，最多5次")
i += 1
if i > 5:
print(
f"{date.strftime('%Y-%m-%d')}日生意社数据连接失败, 如果当前交易日是 2018-09-12, 由于生意社源数据缺失, 无法访问, 否则为重复访问已超过5次，您的地址被网站墙了，请保存好返回数据，稍后从该日期起重试"
)
return False
def get_shfe_receipt_1(date: str = None,
vars_list: List = cons.contract_symbols):
"""
抓取上海期货交易所注册仓单数据, 适用20081006至20140518(包括) 20100126、20101029日期交易所格式混乱，直接回复脚本中DataFrame, 20100416、20130821日期交易所数据丢失
:param date: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
:param vars_list: 合约品种如RB、AL等列表 为空时为所有商品
:return: pd.DataFrame
展期收益率数据(DataFrame):
var 商品品种 string
receipt 仓单数 int
date 日期 string YYYYMMDD
"""
date = cons.convert_date(date).strftime(
'%Y%m%d') if date is not None else datetime.date.today()
if date not in calendar:
warnings.warn(f"{date.strftime('%Y%m%d')}非交易日")
return None
if date == '20100126':
shfe_20100126['date'] = date
return shfe_20100126
elif date == '20101029':
shfe_20101029['date'] = date
return shfe_20101029
elif date in ['20100416', '20130821']:
return warnings.warn('20100416、20130821日期交易所数据丢失')
else:
var_list = [
'天然橡胶', '沥青仓库', '沥青厂库', '热轧卷板', '燃料油', '白银', '线材', '螺纹钢', '铅', '铜',
'铝', '锌', '黄金', '锡', '镍'
]
url = cons.SHFE_RECEIPT_URL_1 % date
data = pandas_read_html_link(url)[0]
indexes = [x for x in data.index if (data[0].tolist()[x] in var_list)]
last_index = [
x for x in data.index if '注' in str(data[0].tolist()[x])
][0] - 1
records = pd.DataFrame()
for i in list(range(len(indexes))):
if i != len(indexes) - 1:
data_cut = data.loc[indexes[i]:indexes[i + 1] - 1, :]
else:
data_cut = data.loc[indexes[i]:last_index, :]
data_cut = data_cut.fillna(method='pad')
data_dict = dict()
data_dict['var'] = chinese_to_english(data_cut[0].tolist()[0])
data_dict['receipt'] = int(data_cut[2].tolist()[-1])
data_dict['receipt_chg'] = int(data_cut[3].tolist()[-1])
data_dict['date'] = date
records = records.append(pd.DataFrame(data_dict, index=[0]))
if len(records.index) != 0:
records.index = records['var']
vars_in_market = [i for i in vars_list if i in records.index]
records = records.loc[vars_in_market, :]
return records.reset_index(drop=True)
def get_dce_receipt(date: str = None,
symbol_list: List = cons.contract_symbols):
"""
大连商品交易所注册仓单数据
:param date: format 开始日期: YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象, 为空时为当天
:param symbol_list: 合约品种如 RB, AL等列表, 为空时为所有商品数据从 20060106开始，每周五更新仓单数据。直到20090407起，每交易日都更新仓单数据
:return: pd.DataFrame
展期收益率数据(DataFrame):
var 商品品种 string
receipt 仓单数 int
date 日期 string YYYYMMDD
"""
if not isinstance(symbol_list, list):
return warnings.warn(f"symbol_list: 必须是列表")
date = cons.convert_date(
date) if date is not None else datetime.date.today()
if date.strftime('%Y%m%d') not in calendar:
warnings.warn(f"{date.strftime('%Y%m%d')}非交易日")
return None
payload = {
"weekQuotes.variety": "all",
"year": date.year,
"month": date.month - 1, # 网站月份描述少 1 个月, 属于网站问题
"day": date.day
}
data = pandas_read_html_link(cons.DCE_RECEIPT_URL,
method="post",
data=payload,
headers=cons.dce_headers)[0]
records = pd.DataFrame()
for x in data.to_dict(orient='records'):
if isinstance(x['品种'], str):
if x['品种'][-2:] == '小计':
var = x['品种'][:-2]
temp_data = {
'var': chinese_to_english(var),
'receipt': int(x['今日仓单量']),
'receipt_chg': int(x['增减']),
'date': date.strftime('%Y%m%d')
}
records = records.append(pd.DataFrame(temp_data, index=[0]))
if len(records.index) != 0:
records.index = records['var']
vars_in_market = [i for i in symbol_list if i in records.index]
records = records.loc[vars_in_market, :]
return records.reset_index(drop=True)