def futures_dce_position_rank_other(date="20160104"):
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('%s非交易日' % date.strftime('%Y%m%d'))
return {}
url = "http://www.dce.com.cn/publicweb/quotesdata/memberDealPosiQuotes.html"
payload = {
"memberDealPosiQuotes.variety": "c",
"memberDealPosiQuotes.trade_type": "0",
"year": date.year,
"month": date.month - 1,
"day": date.day,
"contract.contract_id": "all",
"contract.variety_id": "c",
"contract": "",
}
r = requests.post(url, data=payload)
soup = BeautifulSoup(r.text, "lxml")
symbol_list = [item["onclick"].strip("javascript:setVariety(").strip("');") for item in
soup.find_all(attrs={"class": "selBox"})[-3].find_all("input")]
big_df = dict()
for symbol in symbol_list:
payload = {
"memberDealPosiQuotes.variety": symbol,
"memberDealPosiQuotes.trade_type": "0",
"year": date.year,
"month": date.month - 1,
"day": date.day,
"contract.contract_id": "all",
"contract.variety_id": symbol,
"contract": "",
}
r = requests.post(url, data=payload)
soup = BeautifulSoup(r.text, "lxml")
contract_list = [item["onclick"].strip("javascript:setContract_id('").strip("');") for item in
soup.find_all(attrs={"name": "contract"})]
if contract_list:
if len(contract_list[0]) == 4:
contract_list = [symbol + item for item in contract_list]
for contract in contract_list:
payload = {
"memberDealPosiQuotes.variety": symbol,
"memberDealPosiQuotes.trade_type": "0",
"year": date.year,
"month": date.month - 1,
"day": date.day,
"contract.contract_id": contract,
"contract.variety_id": symbol,
"contract": "",
}
r = requests.post(url, data=payload)
temp_df = pd.read_html(r.text)[1].iloc[:-1, :]
temp_df.columns = ["rank", "vol_party_name", "vol", "vol_chg", "_", "long_party_name",
"long_open_interest",
"long_open_interest_chg", "_", "short_party_name", "short_open_interest",
"short_open_interest_chg"]
temp_df["variety"] = symbol.upper()
temp_df["symbol"] = contract
temp_df = temp_df[["long_open_interest", "long_open_interest_chg", "long_party_name", "rank",
"short_open_interest", "short_open_interest_chg", "short_party_name",
"vol", "vol_chg", "vol_party_name", "symbol", "variety"]]
big_df[contract] = temp_df
return big_df
def get_cffex_daily(date="20200416"):
"""
中国金融期货交易所日交易数据
:param date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象; 为空时为当天
:return: pandas.DataFrame
中国金融期货交易所日:
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或 None(给定日期没有交易数据)
"""
day = cons.convert_date(
date) if date is not None else datetime.date.today()
if day.strftime("%Y%m%d") not in calendar:
warnings.warn("%s非交易日" % day.strftime("%Y%m%d"))
return None
try:
html = requests_link(
cons.CFFEX_DAILY_URL.format(day.strftime("%Y%m"),
day.strftime("%d"),
day.strftime("%Y%m%d")),
encoding="gbk",
headers=cons.headers,
).text
except requests.exceptions.HTTPError as reason:
if reason.response != 404:
print(
cons.CFFEX_DAILY_URL %
(day.strftime("%Y%m"), day.strftime("%d"),
day.strftime("%Y%m%d")),
reason,
)
return
if html.find("网页错误") >= 0:
return
html = [
i.replace(" ", "").split(",") for i in html.split("\n")[:-2]
if i[0][0] != "小"
]
if html[0][0] != "合约代码":
return
dict_data = list()
day_const = day.strftime("%Y%m%d")
for row in html[1:]:
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {"date": day_const, "symbol": row[0], "variety": m.group(1)}
for i, field in enumerate(cons.CFFEX_COLUMNS):
if row[i + 1] == "":
row_dict[field] = 0.0
elif field in ["volume", "open_interest", "oi_chg"]:
row_dict[field] = int(row[i + 1])
else:
try:
row_dict[field] = float(row[i + 1])
except:
pass
row_dict["pre_settle"] = row_dict["close"] - row_dict["change1"]
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[cons.OUTPUT_COLUMNS]
def get_rank_sum(date="20200727", vars_list=cons.contract_symbols):
"""
抓取四个期货交易所前5、前10、前15、前20会员持仓排名数据
注1：由于上期所和中金所只公布每个品种内部的标的排名, 没有公布品种的总排名;
所以函数输出的品种排名是由品种中的每个标的加总获得, 并不是真实的品种排名列表
注2：大商所只公布了品种排名, 未公布标的排名
:param date: 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
symbol 标的合约 string
var 商品品种 string
vol_top5 成交量前5会员成交量总和 int
vol_chg_top5 成交量前5会员成交量变化总和 int
long_open_interest_top5 持多单前5会员持多单总和 int
long_open_interest_chg_top5 持多单前5会员持多单变化总和 int
short_open_interest_top5 持空单前5会员持空单总和 int
short_open_interest_chg_top5 持空单前5会员持空单变化总和 int
vol_top10 成交量前10会员成交量总和 int
...
date 日期 string YYYYMMDD
"""
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('%s非交易日' % date.strftime('%Y%m%d'))
return None
dce_var = [i for i in vars_list if i in cons.market_exchange_symbols['dce']]
shfe_var = [i for i in vars_list if i in cons.market_exchange_symbols['shfe']]
czce_var = [i for i in vars_list if i in cons.market_exchange_symbols['czce']]
cffex_var = [i for i in vars_list if i in cons.market_exchange_symbols['cffex']]
big_dict = {}
if len(dce_var) > 0:
data = get_dce_rank_table(date, dce_var)
if data is False:
return False
big_dict.update(data)
if len(shfe_var) > 0:
data = get_shfe_rank_table(date, shfe_var)
if data is False:
return False
big_dict.update(data)
if len(czce_var) > 0:
data = get_czce_rank_table(date, czce_var)
if data is False:
return False
big_dict.update(data)
if len(cffex_var) > 0:
data = get_cffex_rank_table(date, cffex_var)
if data is False:
return False
big_dict.update(data)
records = pd.DataFrame()
for symbol, table in big_dict.items():
table = table.applymap(lambda x: 0 if x == '' else x)
for symbol_inner in set(table['symbol']):
var = symbol_varieties(symbol_inner)
if var in vars_list:
if var in czce_var:
for col in [item for item in table.columns if item.find('open_interest') > -1] + ['vol', 'vol_chg']:
table[col] = [float(value.replace(',', '')) if value != '-' else 0.0 for value in table[col]]
table_cut = table[table['symbol'] == symbol_inner]
table_cut['rank'] = table_cut['rank'].astype('float')
table_cut_top5 = table_cut[table_cut['rank'] <= 5]
table_cut_top10 = table_cut[table_cut['rank'] <= 10]
table_cut_top15 = table_cut[table_cut['rank'] <= 15]
table_cut_top20 = table_cut[table_cut['rank'] <= 20]
big_dict = {'symbol': symbol_inner, 'variety': var,
'vol_top5': table_cut_top5['vol'].sum(), 'vol_chg_top5': table_cut_top5['vol_chg'].sum(),
'long_open_interest_top5': table_cut_top5['long_open_interest'].sum(),
'long_open_interest_chg_top5': table_cut_top5['long_open_interest_chg'].sum(),
'short_open_interest_top5': table_cut_top5['short_open_interest'].sum(),
'short_open_interest_chg_top5': table_cut_top5['short_open_interest_chg'].sum(),
'vol_top10': table_cut_top10['vol'].sum(),
'vol_chg_top10': table_cut_top10['vol_chg'].sum(),
'long_open_interest_top10': table_cut_top10['long_open_interest'].sum(),
'long_open_interest_chg_top10': table_cut_top10['long_open_interest_chg'].sum(),
'short_open_interest_top10': table_cut_top10['short_open_interest'].sum(),
'short_open_interest_chg_top10': table_cut_top10['short_open_interest_chg'].sum(),
'vol_top15': table_cut_top15['vol'].sum(),
'vol_chg_top15': table_cut_top15['vol_chg'].sum(),
'long_open_interest_top15': table_cut_top15['long_open_interest'].sum(),
'long_open_interest_chg_top15': table_cut_top15['long_open_interest_chg'].sum(),
'short_open_interest_top15': table_cut_top15['short_open_interest'].sum(),
'short_open_interest_chg_top15': table_cut_top15['short_open_interest_chg'].sum(),
'vol_top20': table_cut_top20['vol'].sum(),
'vol_chg_top20': table_cut_top20['vol_chg'].sum(),
'long_open_interest_top20': table_cut_top20['long_open_interest'].sum(),
'long_open_interest_chg_top20': table_cut_top20['long_open_interest_chg'].sum(),
'short_open_interest_top20': table_cut_top20['short_open_interest'].sum(),
'short_open_interest_chg_top20': table_cut_top20['short_open_interest_chg'].sum(),
'date': date.strftime('%Y%m%d')
}
records = records.append(pd.DataFrame(big_dict, index=[0]))
if len(big_dict.items()) > 0:
add_vars = [i for i in cons.market_exchange_symbols['dce'] + cons.market_exchange_symbols['shfe'] + cons.market_exchange_symbols['cffex'] if
i in records['variety'].tolist()]
for var in add_vars:
records_cut = records[records['variety'] == var]
var_record = pd.DataFrame(records_cut.sum()).T
var_record['date'] = date.strftime('%Y%m%d')
var_record.loc[:, ['variety', 'symbol']] = var
records = records.append(var_record)
return records.reset_index(drop=True)
def get_czce_receipt_3(date: str = None,
vars_list: List = cons.contract_symbols):
"""
抓取郑州商品交易所注册仓单数据
适用20151112(包括)至今
Parameters
------
date: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
vars_list: 合约品种如CF、TA等列表 为空时为所有商品
Return
-------
DataFrame:
展期收益率数据(DataFrame):`1
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("%s非交易日" % date.strftime("%Y%m%d"))
return None
url = cons.CZCE_RECEIPT_URL_3 % (date[:4], date)
r = requests_link(url, encoding="utf-8")
r.encoding = "utf-8"
data = pd.read_html(r.text, encoding="gb2312")
records = pd.DataFrame()
if len(data) < 4:
return records
if int(date) <= 20171227:
data = data[1:]
for data_cut in data:
if len(data_cut.columns) > 3 and len(data_cut.index) > 7:
last_indexes = [
x for x in data_cut.index
if "注：" in str(data_cut[0].tolist()[x])
]
if len(last_indexes) > 0:
last_index = last_indexes[0] - 1
data_cut = data_cut.loc[:last_index, :]
if "PTA" in data_cut[0].tolist()[0]:
var = "TA"
else:
strings = data_cut[0].tolist()[0]
string = strings.split(" ")[0][3:]
if len(string) > 7:
continue
print(string)
var = chinese_to_english(re.sub("[A-Z]+", "", string))
data_cut.columns = data_cut.loc[1, :]
data_cut = data_cut.fillna(method="pad")
try:
receipt = data_cut.loc[:, "仓单数量"].tolist()[-1]
except:
receipt = data_cut.loc[:, "仓单数量(保税)"].tolist()[-1]
receipt_chg = data_cut.loc[:, "当日增减"].tolist()[-1]
data_dict = {
"var": var,
"receipt": int(receipt),
"receipt_chg": int(receipt_chg),
"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_daily(date: str = "20030115") -> pd.DataFrame:
"""
大连商品交易所日交易数据
http://www.dce.com.cn/dalianshangpin/xqsj/tjsj26/rtj/rxq/index.html
:param date: 交易日, e.g., 20200416
:type date: str
:return: 具体交易日的个品种行情数据
:rtype: pandas.DataFrame
"""
day = cons.convert_date(date) if date is not None else datetime.date.today()
if day.strftime("%Y%m%d") not in calendar:
warnings.warn("%s非交易日" % day.strftime("%Y%m%d"))
return None
url = "http://www.dce.com.cn/publicweb/quotesdata/exportDayQuotesChData.html"
headers = {
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9",
"Accept-Encoding": "gzip, deflate",
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"Content-Length": "86",
"Content-Type": "application/x-www-form-urlencoded",
"Host": "www.dce.com.cn",
"Origin": "http://www.dce.com.cn",
"Pragma": "no-cache",
"Referer": "http://www.dce.com.cn/publicweb/quotesdata/dayQuotesCh.html",
"Upgrade-Insecure-Requests": "1",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.105 Safari/537.36",
}
params = {
"dayQuotes.variety": "all",
"dayQuotes.trade_type": "0",
"year": date[:4],
"month": str(int(date[4:6]) - 1),
"day": date[6:],
"exportFlag": "excel",
}
r = requests.post(url, data=params, headers=headers)
data_df = pd.read_excel(BytesIO(r.content))
data_df = data_df[~data_df["商品名称"].str.contains("小计")]
data_df = data_df[~data_df["商品名称"].str.contains("总计")]
data_df["variety"] = data_df["商品名称"].map(lambda x: cons.DCE_MAP[x])
data_df["symbol"] = data_df["variety"] + data_df["交割月份"].astype(int).astype(str)
del data_df["商品名称"]
del data_df["交割月份"]
data_df.columns = ["open", "high", "low", "close",
"pre_settle", "settle", "_", "_",
"volume", "open_interest", "_", "turnover", "variety", "symbol"]
data_df["date"] = date
data_df = data_df[
["symbol", "date", "open", "high", "low", "close", "volume", "open_interest", "turnover", "settle",
"pre_settle", "variety"]]
data_df = data_df.applymap(lambda x: x.replace(",", ""))
data_df = data_df.astype({"open": "float",
"high": "float",
"low": "float",
"close": "float",
"volume": "float",
"open_interest": "float",
"turnover": "float",
"settle": "float",
"pre_settle": "float",
})
return data_df
def get_dce_rank_table(date="20201026", vars_list=cons.contract_symbols):
"""
大连商品交易所前 20 会员持仓排名数据明细
注: 该交易所只公布标的合约排名
:param date: 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, 数据从 20060104 开始，每交易日 16:30 左右更新数据
:return: pandas.DataFrame
rank 排名 int
vol_party_name 成交量排序的当前名次会员 string(中文)
vol 该会员成交量 int
vol_chg 该会员成交量变化量 int
long_party_name 持多单排序的当前名次会员 string(中文)
long_open_interest 该会员持多单 int
long_open_interest_chg 该会员持多单变化量 int
short_party_name 持空单排序的当前名次会员 string(中文)
short_open_interest 该会员持空单 int
short_open_interest_chg 该会员持空单变化量 int
symbol 标的合约 string
var 品种 string
date 日期 string YYYYMMDD
"""
date = cons.convert_date(date) if date is not None else datetime.date.today()
if date < datetime.date(2006, 1, 4):
print(Exception("大连商品交易所数据源开始日期为20060104，跳过"))
return {}
if date.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % date.strftime('%Y%m%d'))
return {}
vars_list = [i for i in vars_list if i in cons.market_exchange_symbols['dce']]
big_dict = {}
for var in vars_list:
symbol_list = _get_dce_contract_list(date, var)
for symbol in symbol_list:
url = cons.DCE_VOL_RANK_URL_1 % (var.lower(), symbol, var.lower(), date.year, date.month - 1, date.day)
list_60_name = []
list_60 = []
list_60_chg = []
rank = []
texts = requests_link(url).content.splitlines()
# print(texts)
if not texts:
return False
if len(texts) > 30:
for text in texts:
line = text.decode("utf-8")
string_list = line.split()
try:
if int(string_list[0]) <= 20:
list_60_name.append(string_list[1])
list_60.append(string_list[2])
list_60_chg.append(string_list[3])
rank.append(string_list[0])
except:
pass
table_cut = pd.DataFrame({'rank': rank[0:20],
'vol_party_name': list_60_name[0:20],
'vol': list_60[0:20],
'vol_chg': list_60_chg[0:20],
'long_party_name': list_60_name[20:40],
'long_open_interest': list_60[20:40],
'long_open_interest_chg': list_60_chg[20:40],
'short_party_name': list_60_name[40:60],
'short_open_interest': list_60[40:60],
'short_open_interest_chg': list_60_chg[40:60]
})
table_cut = table_cut.applymap(lambda x: x.replace(',', ''))
table_cut = _table_cut_cal(table_cut, symbol)
big_dict[symbol] = table_cut.reset_index(drop=True)
return big_dict
def get_receipt(start_day: str = None,
end_day: str = None,
vars_list: List = cons.contract_symbols):
"""
获取大宗商品注册仓单数量
:param start_day: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
:type start_day: str
:param end_day: 结束数据 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
:type end_day: str
:param vars_list: 合约品种如RB、AL等列表 为空时为所有商品
:type vars_list: str
:return: 展期收益率数据
:rtype: pandas.DataFrame
"""
start_day = cons.convert_date(
start_day) if start_day is not None else datetime.date.today()
end_day = cons.convert_date(
end_day) if end_day is not None else cons.convert_date(
cons.get_latest_data_date(datetime.datetime.now()))
records = pd.DataFrame()
while start_day <= end_day:
if start_day.strftime('%Y%m%d') not in calendar:
warnings.warn(f"{start_day.strftime('%Y%m%d')}非交易日")
else:
print(start_day)
for market, market_vars in cons.market_exchange_symbols.items():
if market == 'dce':
if start_day >= datetime.date(2009, 4, 7):
f = get_dce_receipt
else:
print('20090407起，dce每交易日更新仓单数据')
f = None
elif market == 'shfe':
if datetime.date(2008, 10,
6) <= start_day <= datetime.date(
2014, 5, 16):
f = get_shfe_receipt_1
elif start_day > datetime.date(2014, 5, 16):
f = get_shfe_receipt_2
else:
f = None
print('20081006起，shfe每交易日更新仓单数据')
elif market == 'czce':
if datetime.date(2008, 3, 3) <= start_day <= datetime.date(
2010, 8, 24):
f = get_czce_receipt_1
elif datetime.date(2010, 8,
24) < start_day <= datetime.date(
2015, 11, 11):
f = get_czce_receipt_2
elif start_day > datetime.date(2015, 11, 11):
f = get_czce_receipt_3
else:
f = None
print('20080303起，czce每交易日更新仓单数据')
get_vars = [var for var in vars_list if var in market_vars]
if market != 'cffex' and get_vars != []:
if f is not None:
records = records.append(f(start_day, get_vars))
start_day += datetime.timedelta(days=1)
records.reset_index(drop=True, inplace=True)
if "MA" in records["var"].to_list():
replace_index = records[records["var"] == "MA"]["receipt"].astype(
str).str.split("0", expand=True)[0].index
records.loc[replace_index, "receipt"] = records[
records["var"] == "MA"]["receipt"].astype(str).str.split(
"0", expand=True)[0]
return records
def get_czce_daily(date="20200901"):
"""
郑州商品交易所-日频率-量价数据
:param date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象，默认为当前交易日; 日期需要大于200100824
:type date: str or datetime.date
:return: 郑州商品交易所-日频率-量价数据
:rtype: pandas.DataFrame or None
"""
day = cons.convert_date(date) if date is not None else datetime.date.today()
if day.strftime("%Y%m%d") not in calendar:
warnings.warn(f"{day.strftime('%Y%m%d')}非交易日")
return None
if day > datetime.date(2010, 8, 24):
if day > datetime.date(2015, 9, 19):
u = cons.CZCE_DAILY_URL_3
url = u % (day.strftime("%Y"), day.strftime("%Y%m%d"))
elif day < datetime.date(2015, 9, 19):
u = cons.CZCE_DAILY_URL_2
url = u % (day.strftime("%Y"), day.strftime("%Y%m%d"))
listed_columns = cons.CZCE_COLUMNS
output_columns = cons.OUTPUT_COLUMNS
try:
r = requests.get(url)
html = r.text
except requests.exceptions.HTTPError as reason:
if reason.response.status_code != 404:
print(
cons.CZCE_DAILY_URL_3
% (day.strftime("%Y"), day.strftime("%Y%m%d")),
reason,
)
return
if html.find("您的访问出错了") >= 0 or html.find("无期权每日行情交易记录") >= 0:
return
html = [
i.replace(" ", "").split("|")
for i in html.split("\n")[:-4]
if i[0][0] != "小"
]
if day > datetime.date(2015, 9, 19):
if html[1][0] not in ["品种月份", "品种代码"]:
return
dict_data = list()
day_const = int(day.strftime("%Y%m%d"))
for row in html[2:]:
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {"date": day_const, "symbol": row[0], "variety": m.group(1)}
for i, field in enumerate(listed_columns):
if row[i + 1] == "\r":
row_dict[field] = 0.0
elif field in [
"volume",
"open_interest",
"oi_chg",
"exercise_volume",
]:
row[i + 1] = row[i + 1].replace(",", "")
row_dict[field] = int(row[i + 1])
else:
row[i + 1] = row[i + 1].replace(",", "")
row_dict[field] = float(row[i + 1])
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[output_columns]
elif day < datetime.date(2015, 9, 19):
dict_data = list()
day_const = int(day.strftime("%Y%m%d"))
for row in html[1:]:
row = row[0].split(",")
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {"date": day_const, "symbol": row[0], "variety": m.group(1)}
for i, field in enumerate(listed_columns):
if row[i + 1] == "\r":
row_dict[field] = 0.0
elif field in [
"volume",
"open_interest",
"oi_chg",
"exercise_volume",
]:
row_dict[field] = int(float(row[i + 1]))
else:
row_dict[field] = float(row[i + 1])
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[output_columns]
if day <= datetime.date(2010, 8, 24):
u = cons.CZCE_DAILY_URL_1
url = u % day.strftime("%Y%m%d")
listed_columns = cons.CZCE_COLUMNS_2
output_columns = cons.OUTPUT_COLUMNS
df = pd.read_html(url)[1].dropna(how="any")
dict_data = list()
day_const = int(day.strftime("%Y%m%d"))
for row in df.to_dict(orient="records")[1:]:
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {"date": day_const, "symbol": row[0], "variety": m.group(1)}
for i, field in enumerate(listed_columns):
if row[i + 1] == "\r":
row_dict[field] = 0.0
elif field in ["volume", "open_interest", "oi_chg", "exercise_volume"]:
row_dict[field] = int(row[i + 1])
else:
row_dict[field] = float(row[i + 1])
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[output_columns]
def get_roll_yield_bar(type_method="symbol",
var="RB",
date=None,
start_day=None,
end_day=None,
plot=False):
"""
获取展期收益率
:param type_method: 'symbol'：获取某天某品种所有交割月合约的收盘价, 'var'：获取某天所有品种两个主力合约的展期收益率（展期收益率横截面）, ‘date’：获取某品种每天的两个主力合约的展期收益率（展期收益率时间序列）
:param var: 合约品种如RB、AL等
:param date: 某一天日期 format： YYYYMMDD
:param start_day: 开始日期 format：YYYYMMDD
:param end_day: 结束数据 format：YYYYMMDD
:param plot: True or False作图
:return: pd.DataFrame
展期收益率数据(DataFrame):
ry 展期收益率
index 日期或品种
"""
date = cons.convert_date(
date) if date is not None else datetime.date.today()
start_day = (cons.convert_date(start_day)
if start_day is not None else datetime.date.today())
end_day = (cons.convert_date(end_day)
if end_day is not None else cons.convert_date(
cons.get_latest_data_date(datetime.datetime.now())))
if type_method == "symbol":
df = get_futures_daily(start_day=date,
end_day=date,
market=symbol_market(var))
df = df[df["variety"] == var]
if plot:
_plot_bar_2(df[["symbol", "close"]])
return df
if type_method == "var":
df = pd.DataFrame()
for market in ["dce", "cffex", "shfe", "czce"]:
df = df.append(
get_futures_daily(start_day=date, end_day=date, market=market))
var_list = list(set(df["variety"]))
df_l = pd.DataFrame()
for var in var_list:
ry = get_roll_yield(date, var, df=df)
if ry:
df_l = df_l.append(
pd.DataFrame([ry],
index=[var],
columns=["roll_yield", "near_by",
"deferred"]))
df_l["date"] = date
df_l = df_l.sort_values("roll_yield")
if plot:
_plot_bar(df_l["roll_yield"])
return df_l
if type_method == "date":
df_l = pd.DataFrame()
while start_day <= end_day:
try:
ry = get_roll_yield(start_day, var)
if ry:
df_l = df_l.append(
pd.DataFrame(
[ry],
index=[start_day],
columns=["roll_yield", "near_by", "deferred"],
))
except:
pass
start_day += datetime.timedelta(days=1)
if plot:
_plot(df_l["roll_yield"])
return df_l
def get_czce_receipt_3(date: str = None,
vars_list: List = cons.contract_symbols):
"""
抓取郑州商品交易所注册仓单数据
适用20151112(包括)至今
Parameters
------
date: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
vars_list: 合约品种如CF、TA等列表 为空时为所有商品
Return
-------
DataFrame:
展期收益率数据(DataFrame):`1
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('%s非交易日' % date.strftime('%Y%m%d'))
return None
url = cons.CZCE_RECEIPT_URL_3 % (date[:4], date)
r = requests_link(url, encoding='utf-8')
r.encoding = 'utf-8'
data = pd.read_html(r.text, encoding='gb2312')
records = pd.DataFrame()
if len(data) < 4:
return records
if int(date) <= 20171227:
data = data[1:]
for data_cut in data:
if len(data_cut.columns) > 3 and len(data_cut.index) > 7:
last_indexes = [
x for x in data_cut.index
if '注：' in str(data_cut[0].tolist()[x])
]
if len(last_indexes) > 0:
last_index = last_indexes[0] - 1
data_cut = data_cut.loc[:last_index, :]
if 'PTA' in data_cut[0].tolist()[0]:
var = 'TA'
else:
strings = data_cut[0].tolist()[0]
string = strings.split(' ')[0][3:]
if len(string) > 7:
continue
print(string)
var = chinese_to_english(re.sub('[A-Z]+', '', string))
data_cut.columns = data_cut.loc[1, :]
data_cut = data_cut.fillna(method='pad')
try:
receipt = data_cut.loc[:, '仓单数量'].tolist()[-1]
except:
receipt = data_cut.loc[:, '仓单数量(保税)'].tolist()[-1]
receipt_chg = data_cut.loc[:, '当日增减'].tolist()[-1]
data_dict = {
'var': var,
'receipt': int(receipt),
'receipt_chg': int(receipt_chg),
'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_receipt(start_day: str = None,
end_day: str = None,
vars_list: List = cons.contract_symbols):
"""
获取大宗商品注册仓单数量
Parameters
------
start_day: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
end_day: 结束数据 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
vars_list: 合约品种如RB、AL等列表 为空时为所有商品
Return
-------
DataFrame
展期收益率数据(DataFrame):
var 商品品种 string
receipt 仓单数量 int
date 日期 string YYYYMMDD
"""
start_day = cons.convert_date(
start_day) if start_day is not None else datetime.date.today()
end_day = cons.convert_date(
end_day) if end_day is not None else cons.convert_date(
cons.get_latest_data_date(datetime.datetime.now()))
records = pd.DataFrame()
while start_day <= end_day:
if start_day.strftime('%Y%m%d') not in calendar:
warnings.warn(f"{start_day.strftime('%Y%m%d')}非交易日")
else:
print(start_day)
for market, market_vars in cons.market_exchange_symbols.items():
if market == 'dce':
if start_day >= datetime.date(2009, 4, 7):
f = get_dce_receipt
else:
print('20090407起，dce每交易日更新仓单数据')
f = None
elif market == 'shfe':
if datetime.date(2008, 10,
6) <= start_day <= datetime.date(
2014, 5, 16):
f = get_shfe_receipt_1
elif start_day > datetime.date(2014, 5, 16):
f = get_shfe_receipt_2
else:
f = None
print('20081006起，shfe每交易日更新仓单数据')
elif market == 'czce':
if datetime.date(2008, 3, 3) <= start_day <= datetime.date(
2010, 8, 24):
f = get_czce_receipt_1
elif datetime.date(2010, 8,
24) < start_day <= datetime.date(
2015, 11, 11):
f = get_czce_receipt_2
elif start_day > datetime.date(2015, 11, 11):
f = get_czce_receipt_3
else:
f = None
print('20080303起，czce每交易日更新仓单数据')
get_vars = [var for var in vars_list if var in market_vars]
if market != 'cffex' and get_vars != []:
if f is not None:
records = records.append(f(start_day, get_vars))
start_day += datetime.timedelta(days=1)
return records.reset_index(drop=True)
def get_czce_receipt_1(date: str = None,
vars_list: List = cons.contract_symbols):
"""
抓取郑州商品交易所注册仓单数据
适用20080222至20100824(包括)
Parameters
------
date: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
vars_list: 合约品种如CF、TA等列表 为空时为所有商品
Return
-------
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('%s非交易日' % date.strftime('%Y%m%d'))
return None
if date == '20090820':
return pd.DataFrame()
url = cons.CZCE_RECEIPT_URL_1 % date
r = requests_link(url, encoding='utf-8')
context = r.text
data = pd.read_html(context)[1]
records = pd.DataFrame()
indexes = [x for x in data.index if '品种：' in str(data[0].tolist()[x])]
ends = [x for x in data.index if '总计' in str(data[0].tolist()[x])]
for i in list(range(len(indexes))):
if i != len(indexes) - 1:
data_cut = data.loc[indexes[i]:ends[i], :]
data_cut = data_cut.fillna(method='pad')
else:
data_cut = data.loc[indexes[i]:, :]
data_cut = data_cut.fillna(method='pad')
if 'PTA' in data_cut[0].tolist()[0]:
var = 'TA'
else:
var = chinese_to_english(
re.sub(r'[A-Z]+', '', data_cut[0].tolist()[0][3:]))
if var == 'CF':
receipt = data_cut[6].tolist()[-1]
receipt_chg = data_cut[7].tolist()[-1]
else:
receipt = data_cut[5].tolist()[-1]
receipt_chg = data_cut[6].tolist()[-1]
data_dict = {
'var': var,
'receipt': int(receipt),
'receipt_chg': int(receipt_chg),
'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_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_daily(date="20200416", symbol_type="futures", retries=0):
"""
大连商品交易所日交易数据
Parameters
------
date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
symbol_type: 数据类型, 为'futures'期货 或 'option'期权二者之一
retries: int, 当前重试次数，达到3次则获取数据失败
Return
-------
DataFrame
大商所日交易数据(DataFrame):
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或
DataFrame
郑商所每日期权交易数据
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
pre_settle 前结算价
settle 结算价
delta 对冲值
volume 成交量
open_interest 持仓量
oi_change 持仓变化
turnover 成交额
implied_volatility 隐含波动率
exercise_volume 行权量
variety 合约类别
或 None(给定日期没有交易数据)
"""
day = cons.convert_date(
date) if date is not None else datetime.date.today()
if day.strftime("%Y%m%d") not in calendar:
warnings.warn("%s非交易日" % day.strftime("%Y%m%d"))
return None
if retries > 3:
print("maximum retires for DCE market data: ", day.strftime("%Y%m%d"))
return
if symbol_type == "futures":
url = (cons.DCE_DAILY_URL + "?" +
urllib.parse.urlencode({
"currDate": day.strftime("%Y%m%d"),
"year": day.strftime("%Y"),
"month": str(int(day.strftime("%m")) - 1),
"day": day.strftime("%d"),
}))
listed_columns = cons.DCE_COLUMNS
output_columns = cons.OUTPUT_COLUMNS
elif symbol_type == "option":
url = (cons.DCE_DAILY_URL + "?" +
urllib.parse.urlencode({
"currDate": day.strftime("%Y%m%d"),
"year": day.strftime("%Y"),
"month": str(int(day.strftime("%m")) - 1),
"day": day.strftime("%d"),
"dayQuotes.trade_type": "1",
}))
listed_columns = cons.DCE_OPTION_COLUMNS
output_columns = cons.OPTION_OUTPUT_COLUMNS
else:
print("invalid symbol_type :" + symbol_type +
', should be one of "futures" or "option"')
return
try:
response = requests_link(url, method="post", headers=cons.headers).text
except requests.exceptions.ContentDecodingError as reason:
return get_dce_daily(day, retries=retries + 1)
except requests.exceptions.HTTPError as reason:
if reason.response == 504:
return get_dce_daily(day, retries=retries + 1)
elif reason.response != 404:
print(cons.DCE_DAILY_URL, reason)
return
if "错误：您所请求的网址（URL）无法获取" in response:
return get_dce_daily(day, retries=retries + 1)
elif "暂无数据" in response:
return
data = BeautifulSoup(response, "html.parser").find_all("tr")
if len(data) == 0:
return
dict_data = list()
implied_data = list()
for i_data in data[1:]:
if "小计" in i_data.text or "总计" in i_data.text:
continue
x = i_data.find_all("td")
if symbol_type == "futures":
row_dict = {"variety": cons.DCE_MAP[x[0].text.strip()]}
row_dict["symbol"] = row_dict["variety"] + x[1].text.strip()
for i, field in enumerate(listed_columns):
field_content = x[i + 2].text.strip()
if "-" in field_content:
row_dict[field] = 0
elif field in ["volume", "open_interest"]:
row_dict[field] = int(field_content.replace(",", ""))
else:
row_dict[field] = float(field_content.replace(",", ""))
dict_data.append(row_dict)
elif len(x) == 16:
m = cons.FUTURES_SYMBOL_PATTERN.match(x[1].text.strip())
if not m:
continue
row_dict = {
"symbol": x[1].text.strip(),
"variety": m.group(1).upper(),
"contract_id": m.group(0),
}
for i, field in enumerate(listed_columns):
field_content = x[i + 2].text.strip()
if "-" in field_content:
row_dict[field] = 0
elif field in ["volume", "open_interest"]:
row_dict[field] = int(field_content.replace(",", ""))
else:
row_dict[field] = float(field_content.replace(",", ""))
dict_data.append(row_dict)
elif len(x) == 2:
implied_data.append({
"contract_id": x[0].text.strip(),
"implied_volatility": float(x[1].text.strip()),
})
df = pd.DataFrame(dict_data)
df["date"] = day.strftime("%Y%m%d")
if symbol_type == "futures":
return df[output_columns]
else:
return pd.merge(
df,
pd.DataFrame(implied_data),
on="contract_id",
how="left",
indicator=False,
)[output_columns]
def get_czce_rank_table(date=None, vars_list=cons.contract_symbols):
"""
郑州商品交易所前 20 会员持仓排名数据明细
注：该交易所既公布了品种排名, 也公布了标的排名
:param date: 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, 数据从20050509开始，每交易日16:30左右更新数据
:return: pd.DataFrame
rank 排名 int
vol_party_name 成交量排序的当前名次会员 string(中文)
vol 该会员成交量 int
vol_chg 该会员成交量变化量 int
long_party_name 持多单排序的当前名次会员 string(中文)
long_open_interest 该会员持多单 int
long_open_interest_chg 该会员持多单变化量 int
short_party_name 持空单排序的当前名次会员 string(中文)
short_open_interest 该会员持空单 int
short_open_interest_chg 该会员持空单变化量 int
symbol 标的合约 string
var 品种 string
date 日期 string YYYYMMDD
"""
date = cons.convert_date(date) if date is not None else datetime.date.today()
if date < datetime.date(2005, 5, 9):
print("czce数据源开始日期为20050509，跳过")
return {}
if date.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % date.strftime('%Y%m%d'))
return {}
if date <= datetime.date(2010, 8, 25):
url = cons.CZCE_VOL_RANK_URL_1 % (date.strftime('%Y%m%d'))
data = _czce_df_read(url, skip_rows=0)
r = requests_link(url, 'utf-8')
r.encoding = 'utf-8'
soup = BeautifulSoup(r.text, 'lxml', from_encoding="gb2312")
symbols = []
for link in soup.find_all('b'):
strings = (str(link).split(' '))
if len(strings) > 5:
try:
symbol = chinese_to_english(strings[4])
except:
symbol = strings[4]
symbols.append(symbol)
big_dict = {}
for i in range(len(symbols)):
symbol = symbols[i]
table_cut = data[i + 2]
table_cut.columns = rank_columns
table_cut = table_cut.iloc[:-1, :]
table_cut.loc[:, 'rank'] = table_cut.index
table_cut.loc['合计', 'rank'] = 999
table_cut.loc['合计', ['vol_party_name', 'long_party_name', 'short_party_name']] = None
table_cut.loc[:, 'symbol'] = symbol
table_cut.loc[:, 'variety'] = symbol_varieties(symbol)
table_cut[intColumns] = table_cut[intColumns].fillna(0)
table_cut[intColumns] = table_cut[intColumns].astype(str)
table_cut[intColumns] = table_cut[intColumns].applymap(lambda x: x.replace(',', ''))
table_cut = table_cut.applymap(lambda x: 0 if x == '-' else x)
table_cut[intColumns] = table_cut[intColumns].astype(float)
table_cut[intColumns] = table_cut[intColumns].astype(int)
big_dict[symbol] = table_cut.reset_index(drop=True)
return big_dict
elif date <= datetime.date(2015, 11, 11):
url = cons.CZCE_VOL_RANK_URL_2 % (date.year, date.strftime('%Y%m%d'))
data = _czce_df_read(url, skip_rows=1)[1]
elif date < datetime.date(2017, 12, 28):
url = cons.CZCE_VOL_RANK_URL_3 % (date.year, date.strftime('%Y%m%d'))
data = _czce_df_read(url, skip_rows=1)[0]
else:
url = cons.CZCE_VOL_RANK_URL_3 % (date.year, date.strftime('%Y%m%d'))
data = _czce_df_read(url, skip_rows=0)[0]
if len(data.columns) < 6:
return {}
table = pd.DataFrame(data.iloc[:, :9])
table.columns = rank_columns
table.loc[:, 'rank'] = table.index
table[intColumns] = table[intColumns].astype(str)
table[intColumns] = table[intColumns].applymap(lambda x: x.replace(',', ''))
table = table.applymap(lambda x: 0 if x == '-' else x)
indexes = [i for i in table.index if '合约' in i or '品种' in i]
indexes.insert(0, 0)
big_dict = {}
for i in range(len(indexes)):
if indexes[i] == 0:
table_cut = table.loc[:indexes[i + 1], :]
string = table_cut.index.name
elif i < len(indexes) - 1:
table_cut = table.loc[indexes[i]:indexes[i + 1], :]
string = table_cut.index[0]
else:
table_cut = table.loc[indexes[i]:, :]
string = table_cut.index[0]
if 'PTA' in string:
symbol = 'TA'
else:
try:
symbol = chinese_to_english(find_chinese(re.compile(r'：(.*) ').findall(string)[0]))
except:
symbol = re.compile(r'：(.*) ').findall(string)[0]
var = symbol_varieties(symbol)
if var in vars_list:
table_cut = table_cut.dropna(how='any').iloc[1:, :]
table_cut = table_cut.loc[[x for x in table_cut.index if x in [str(i) for i in range(21)]], :]
table_cut = _table_cut_cal(table_cut, symbol)
big_dict[symbol] = table_cut.reset_index(drop=True)
return big_dict
def get_futures_daily(start_day="20200413",
end_day="20200416",
market="CFFEX",
index_bar=False):
"""
交易所日交易数据
Parameters
------
start_day: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
end_day: 结束数据 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
market: 'CFFEX' 中金所, 'CZCE' 郑商所, 'SHFE' 上期所, 'DCE' 大商所 之一, 'INE' 上海国际能源交易中心。默认为中金所
index_bar: bool 是否合成指数K线
Return
-------
DataFrame
中金所日交易数据(DataFrame):
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或 None(给定日期没有交易数据)
"""
if market.upper() == "CFFEX":
f = get_cffex_daily
elif market.upper() == "CZCE":
f = get_czce_daily
elif market.upper() == "SHFE":
f = get_shfe_daily
elif market.upper() == "DCE":
f = get_dce_daily
elif market.upper() == "INE":
f = get_ine_daily
else:
print("Invalid Market Symbol")
return
start_day = (cons.convert_date(start_day)
if start_day is not None else datetime.date.today())
end_day = (cons.convert_date(end_day)
if end_day is not None else cons.convert_date(
cons.get_latest_data_date(datetime.datetime.now())))
df_list = list()
while start_day <= end_day:
df = f(start_day)
if df is not None:
df_list.append(df)
if index_bar:
df_list.append(get_futures_index(df))
start_day += datetime.timedelta(days=1)
if len(df_list) > 0:
return pd.concat(df_list).reset_index(drop=True)
def get_cffex_daily(date=None):
"""
获取中国金融期货交易所日交易数据
:param date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象; 为空时为当天
:return: pd.DataFrame
中国金融期货交易所日(pd.DataFrame):
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或 None(给定日期没有交易数据)
"""
day = cons.convert_date(
date) if date is not None else datetime.date.today()
if day.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % day.strftime('%Y%m%d'))
return None
try:
html = requests_link(cons.CFFEX_DAILY_URL.format(
day.strftime('%Y%m'), day.strftime('%d'), day.strftime('%Y%m%d')),
encoding="gbk",
headers=cons.headers).text
except requests.exceptions.HTTPError as reason:
if reason.response != 404:
print(
cons.CFFEX_DAILY_URL %
(day.strftime('%Y%m'), day.strftime('%d'),
day.strftime('%Y%m%d')), reason)
return
if html.find('网页错误') >= 0:
return
html = [
i.replace(' ', '').split(',') for i in html.split('\n')[:-2]
if i[0][0] != '小'
]
if html[0][0] != '合约代码':
return
dict_data = list()
day_const = day.strftime('%Y%m%d')
for row in html[1:]:
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {'date': day_const, 'symbol': row[0], 'variety': m.group(1)}
for i, field in enumerate(cons.CFFEX_COLUMNS):
if row[i + 1] == "":
row_dict[field] = 0.0
elif field in ['volume', 'open_interest', 'oi_chg']:
row_dict[field] = int(row[i + 1])
else:
try:
row_dict[field] = float(row[i + 1])
except:
pass
row_dict['pre_settle'] = row_dict['close'] - row_dict['change1']
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[cons.OUTPUT_COLUMNS]
def get_shfe_daily(date="20131016"):
"""
上海期货交易所-日频率-量价数据
:param date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象, 默认为当前交易日
:type date: str or datetime.date
:return: 上海期货交易所-日频率-量价数据
:rtype: pandas.DataFrame or None
上期所日交易数据(DataFrame):
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或 None(给定交易日没有交易数据)
"""
day = cons.convert_date(date) if date is not None else datetime.date.today()
if day.strftime("%Y%m%d") not in calendar:
warnings.warn("%s非交易日" % day.strftime("%Y%m%d"))
return None
try:
json_data = json.loads(
requests_link(
cons.SHFE_DAILY_URL % (day.strftime("%Y%m%d")),
headers=cons.shfe_headers,
).text
)
except requests.HTTPError as reason:
if reason.response != 404:
print(cons.SHFE_DAILY_URL % (day.strftime("%Y%m%d")), reason)
return
if len(json_data["o_curinstrument"]) == 0:
return
df = pd.DataFrame(
[
row
for row in json_data["o_curinstrument"]
if row["DELIVERYMONTH"] not in ["小计", "合计"] and row["DELIVERYMONTH"] != ""
]
)
df["variety"] = df.PRODUCTID.str.slice(0, -6).str.upper()
df["symbol"] = df["variety"] + df["DELIVERYMONTH"]
df["date"] = day.strftime("%Y%m%d")
v_wap_df = get_shfe_v_wap(day)
if v_wap_df is not None:
df = pd.merge(
df,
v_wap_df[v_wap_df.time_range == "9:00-15:00"],
on=["date", "symbol"],
how="left",
)
df["turnover"] = df.v_wap * df.VOLUME
else:
df["VOLUME"] = df["VOLUME"].apply(lambda x: 0 if x == "" else x)
df["turnover"] = df["VOLUME"] * df["SETTLEMENTPRICE"]
df.rename(columns=cons.SHFE_COLUMNS, inplace=True)
return df[cons.OUTPUT_COLUMNS]
def get_czce_daily(date=None):
"""
获取郑商所日交易数据
Parameters
------
date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
Return
-------
DataFrame
郑商所每日期货交易数据:
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或
DataFrame
郑商所每日期权交易数据
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
pre_settle 前结算价
settle 结算价
delta 对冲值
volume 成交量
open_interest 持仓量
oi_change 持仓变化
turnover 成交额
implied_volatility 隐含波动率
exercise_volume 行权量
variety 合约类别
None(类型错误或给定日期没有交易数据)
"""
day = cons.convert_date(
date) if date is not None else datetime.date.today()
if day.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % day.strftime('%Y%m%d'))
return None
if day > datetime.date(2010, 8, 24):
if day > datetime.date(2015, 9, 19):
u = cons.CZCE_DAILY_URL_3
url = u % (day.strftime('%Y'), day.strftime('%Y%m%d'))
elif day < datetime.date(2015, 9, 19):
u = cons.CZCE_DAILY_URL_2
url = u % (day.strftime('%Y'), day.strftime('%Y%m%d'))
listed_columns = cons.CZCE_COLUMNS
output_columns = cons.OUTPUT_COLUMNS
try:
r = requests.get(url)
html = r.text
except requests.exceptions.HTTPError as reason:
if reason.response.status_code != 404:
print(
cons.CZCE_DAILY_URL_3 %
(day.strftime('%Y'), day.strftime('%Y%m%d')), reason)
return
if html.find('您的访问出错了') >= 0 or html.find('无期权每日行情交易记录') >= 0:
return
html = [
i.replace(' ', '').split('|') for i in html.split('\n')[:-4]
if i[0][0] != u'小'
]
if day > datetime.date(2015, 9, 19):
if html[1][0] not in ['品种月份', u'品种代码']:
return
dict_data = list()
day_const = int(day.strftime('%Y%m%d'))
for row in html[2:]:
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {
'date': day_const,
'symbol': row[0],
'variety': m.group(1)
}
for i, field in enumerate(listed_columns):
if row[i + 1] == "\r":
row_dict[field] = 0.0
elif field in [
'volume', 'open_interest', 'oi_chg',
'exercise_volume'
]:
row[i + 1] = row[i + 1].replace(',', '')
row_dict[field] = int(row[i + 1])
else:
row[i + 1] = row[i + 1].replace(',', '')
row_dict[field] = float(row[i + 1])
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[output_columns]
elif day < datetime.date(2015, 9, 19):
dict_data = list()
day_const = int(day.strftime('%Y%m%d'))
for row in html[1:]:
row = row[0].split(',')
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {
'date': day_const,
'symbol': row[0],
'variety': m.group(1)
}
for i, field in enumerate(listed_columns):
if row[i + 1] == "\r":
row_dict[field] = 0.0
elif field in [
'volume', 'open_interest', 'oi_chg',
'exercise_volume'
]:
row_dict[field] = int(float(row[i + 1]))
else:
row_dict[field] = float(row[i + 1])
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[output_columns]
if day <= datetime.date(2010, 8, 24):
u = cons.CZCE_DAILY_URL_1
url = u % day.strftime('%Y%m%d')
listed_columns = cons.CZCE_COLUMNS_2
output_columns = cons.OUTPUT_COLUMNS
df = pd.read_html(url)[1].dropna(how='any')
dict_data = list()
day_const = int(day.strftime('%Y%m%d'))
for row in df.to_dict(orient='records')[1:]:
m = cons.FUTURES_SYMBOL_PATTERN.match(row[0])
if not m:
continue
row_dict = {
'date': day_const,
'symbol': row[0],
'variety': m.group(1)
}
for i, field in enumerate(listed_columns):
if row[i + 1] == "\r":
row_dict[field] = 0.0
elif field in [
'volume', 'open_interest', 'oi_chg', 'exercise_volume'
]:
row_dict[field] = int(row[i + 1])
else:
row_dict[field] = float(row[i + 1])
dict_data.append(row_dict)
return pd.DataFrame(dict_data)[output_columns]
def get_czce_rank_table(date="20201026", vars_list=cons.contract_symbols):
"""
郑州商品交易所前 20 会员持仓排名数据明细
注：该交易所既公布了品种排名, 也公布了标的排名
:param date: 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, 数据从20050509开始，每交易日16:30左右更新数据
:return: pd.DataFrame
rank 排名 int
vol_party_name 成交量排序的当前名次会员 string(中文)
vol 该会员成交量 int
vol_chg 该会员成交量变化量 int
long_party_name 持多单排序的当前名次会员 string(中文)
long_open_interest 该会员持多单 int
long_open_interest_chg 该会员持多单变化量 int
short_party_name 持空单排序的当前名次会员 string(中文)
short_open_interest 该会员持空单 int
short_open_interest_chg 该会员持空单变化量 int
symbol 标的合约 string
var 品种 string
date 日期 string YYYYMMDD
"""
date = cons.convert_date(date) if date is not None else datetime.date.today()
if date < datetime.date(2015, 10, 8):
print("CZCE可获取的数据源开始日期为 20151008, 请输入合适的日期参数")
return {}
if date.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % date.strftime('%Y%m%d'))
return {}
if date >= datetime.date(2015, 10, 8):
url = f"http://www.czce.com.cn/cn/DFSStaticFiles/Future/{date.year}/{date.isoformat().replace('-', '')}/FutureDataHolding.xls"
r = requests.get(url)
temp_df = pd.read_excel(BytesIO(r.content))
temp_pinzhong_index = [item + 1 for item in temp_df[temp_df.iloc[:, 0].str.contains("合计")].index.to_list()]
temp_pinzhong_index.insert(0, 0)
temp_pinzhong_index.pop()
temp_symbol_index = temp_df.iloc[temp_pinzhong_index, 0].str.split(" ", expand=True).iloc[:, 0]
symbol_list = [re.compile(r"[0-9a-zA-Z_]+").findall(item)[0] for item in temp_symbol_index.values]
temp_symbol_index_list = temp_symbol_index.index.to_list()
big_dict = {}
for i in range(len(temp_symbol_index_list)-1):
inner_temp_df = temp_df[temp_symbol_index_list[i]+2: temp_symbol_index_list[i+1]-1]
inner_temp_df.columns = ["rank",
"vol_party_name",
"vol",
"vol_chg",
"long_party_name",
"long_open_interest",
"long_open_interest_chg",
"short_party_name",
"short_open_interest",
"short_open_interest_chg",
]
inner_temp_df.reset_index(inplace=True, drop=True)
big_dict[symbol_list[i]] = inner_temp_df
inner_temp_df = temp_df[temp_symbol_index_list[i+1]+2:-1]
inner_temp_df.columns = ["rank",
"vol_party_name",
"vol",
"vol_chg",
"long_party_name",
"long_open_interest",
"long_open_interest_chg",
"short_party_name",
"short_open_interest",
"short_open_interest_chg",
]
inner_temp_df.reset_index(inplace=True, drop=True)
big_dict[symbol_list[-1]] = inner_temp_df
new_big_dict = {}
for key, value in big_dict.items():
value["symbol"] = key
value["variety"] = re.compile(r"[a-zA-Z_]+").findall(key)[0]
new_big_dict[key] = value
return new_big_dict
def get_cffex_daily(date="20100401"):
"""
中国金融期货交易所日交易数据
http://www.cffex.com.cn/rtj/
:param date: 日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象; 为空时为当天
:return: pandas.DataFrame
中国金融期货交易所日:
symbol 合约代码
date 日期
open 开盘价
high 最高价
low 最低价
close 收盘价
volume 成交量
open_interest 持仓量
turnover 成交额
settle 结算价
pre_settle 前结算价
variety 合约类别
或 None(给定日期没有交易数据)
"""
day = cons.convert_date(
date) if date is not None else datetime.date.today()
if day.strftime("%Y%m%d") not in calendar:
warnings.warn("%s非交易日" % day.strftime("%Y%m%d"))
return None
url = f"http://www.cffex.com.cn/sj/historysj/{date[:-2]}/zip/{date[:-2]}.zip"
r = requests.get(url)
try:
with zipfile.ZipFile(BytesIO(r.content)) as file:
with file.open(f"{date}_1.csv") as my_file:
data = my_file.read().decode("gb2312")
data_df = pd.read_csv(StringIO(data))
except:
return None
data_df = data_df[data_df["合约代码"] != "小计"]
data_df = data_df[data_df["合约代码"] != "合计"]
data_df = data_df[~data_df["合约代码"].str.contains("IO")]
data_df.reset_index(inplace=True, drop=True)
data_df["合约代码"] = data_df["合约代码"].str.strip()
symbol_list = data_df["合约代码"].to_list()
variety_list = [
re.compile(r"[a-zA-Z_]+").findall(item)[0] for item in symbol_list
]
if data_df.shape[1] == 15:
data_df.columns = [
"symbol", "open", "high", "low", "volume", "turnover",
"open_interest", "_", "close", "settle", "pre_settle", "_", "_",
"_", "_"
]
else:
data_df.columns = [
"symbol", "open", "high", "low", "volume", "turnover",
"open_interest", "_", "close", "settle", "pre_settle", "_", "_",
"_"
]
data_df["date"] = date
data_df["variety"] = variety_list
data_df = data_df[[
"symbol", "date", "open", "high", "low", "close", "volume",
"open_interest", "turnover", "settle", "pre_settle", "variety"
]]
return data_df
def futures_dce_position_rank(date: str = "20160104") -> pd.DataFrame:
"""
大连商品交易日每日持仓排名-具体合约
http://www.dce.com.cn/dalianshangpin/xqsj/tjsj26/rtj/rcjccpm/index.html
:param date: 指定交易日; e.g., "20200511"
:type date: str
:return: 指定日期的持仓排名数据
:rtype: pandas.DataFrame
"""
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('%s非交易日' % date.strftime('%Y%m%d'))
return {}
url = "http://www.dce.com.cn/publicweb/quotesdata/exportMemberDealPosiQuotesBatchData.html"
headers = {
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9",
"Accept-Encoding": "gzip, deflate",
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"Content-Length": "160",
"Content-Type": "application/x-www-form-urlencoded",
"Host": "www.dce.com.cn",
"Origin": "http://www.dce.com.cn",
"Pragma": "no-cache",
"Referer": "http://www.dce.com.cn/publicweb/quotesdata/memberDealPosiQuotes.html",
"Upgrade-Insecure-Requests": "1",
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/81.0.4044.138 Safari/537.36",
}
payload = {
"memberDealPosiQuotes.variety": "a",
"memberDealPosiQuotes.trade_type": "0",
"contract.contract_id": "a2009",
"contract.variety_id": "a",
"year": date.year,
"month": date.month - 1,
"day": date.day,
"batchExportFlag": "batch",
}
r = requests.post(url, payload, headers=headers)
big_dict = dict()
with zipfile.ZipFile(BytesIO(r.content), "r") as z:
for i in z.namelist():
file_name = i.encode('cp437').decode('GBK')
try:
data = pd.read_table(z.open(i), header=None, sep="\t").iloc[:-6]
if len(data) < 12: # 处理没有活跃合约的情况
big_dict[file_name.split("_")[1]] = pd.DataFrame()
continue
start_list = data[data.iloc[:, 0].str.find("名次") == 0].index.tolist()
data = data.iloc[start_list[0]:, data.columns[data.iloc[start_list[0], :].notnull()]]
data.reset_index(inplace=True, drop=True)
start_list = data[data.iloc[:, 0].str.find("名次") == 0].index.tolist()
end_list = data[data.iloc[:, 0].str.find("总计") == 0].index.tolist()
part_one = data[start_list[0]: end_list[0]].iloc[1:, :]
part_two = data[start_list[1]: end_list[1]].iloc[1:, :]
part_three = data[start_list[2]: end_list[2]].iloc[1:, :]
temp_df = pd.concat([part_one.reset_index(drop=True), part_two.reset_index(drop=True),
part_three.reset_index(drop=True)], axis=1, ignore_index=True)
temp_df.columns = ["名次", "会员简称", "成交量", "增减", "名次", "会员简称", "持买单量", "增减", "名次", "会员简称", "持卖单量", "增减"]
temp_df["rank"] = range(1, len(temp_df) + 1)
del temp_df["名次"]
temp_df.columns = ["vol_party_name", "vol", "vol_chg", "long_party_name", "long_open_interest",
"long_open_interest_chg", "short_party_name", "short_open_interest",
"short_open_interest_chg", "rank"]
temp_df["symbol"] = file_name.split("_")[1]
temp_df["variety"] = file_name.split("_")[1][:-4].upper()
temp_df = temp_df[["long_open_interest", "long_open_interest_chg", "long_party_name", "rank",
"short_open_interest", "short_open_interest_chg", "short_party_name",
"vol", "vol_chg", "vol_party_name", "symbol", "variety"]]
big_dict[file_name.split("_")[1]] = temp_df
except UnicodeDecodeError as e:
try:
data = pd.read_table(z.open(i), header=None, sep="\\s+", encoding="gb2312", skiprows=3)
except:
data = pd.read_table(z.open(i), header=None, sep="\\s+", encoding="gb2312", skiprows=4)
start_list = data[data.iloc[:, 0].str.find("名次") == 0].index.tolist()
end_list = data[data.iloc[:, 0].str.find("总计") == 0].index.tolist()
part_one = data[start_list[0]: end_list[0]].iloc[1:, :]
part_two = data[start_list[1]: end_list[1]].iloc[1:, :]
part_three = data[start_list[2]: end_list[2]].iloc[1:, :]
temp_df = pd.concat([part_one.reset_index(drop=True), part_two.reset_index(drop=True),
part_three.reset_index(drop=True)], axis=1, ignore_index=True)
temp_df.columns = ["名次", "会员简称", "成交量", "增减", "名次", "会员简称", "持买单量", "增减", "名次", "会员简称", "持卖单量", "增减"]
temp_df["rank"] = range(1, len(temp_df) + 1)
del temp_df["名次"]
temp_df.columns = ["vol_party_name", "vol", "vol_chg", "long_party_name", "long_open_interest",
"long_open_interest_chg", "short_party_name", "short_open_interest",
"short_open_interest_chg", "rank"]
temp_df["symbol"] = file_name.split("_")[1]
temp_df["variety"] = file_name.split("_")[1][:-4].upper()
temp_df = temp_df[["long_open_interest", "long_open_interest_chg", "long_party_name", "rank",
"short_open_interest", "short_open_interest_chg", "short_party_name",
"vol", "vol_chg", "vol_party_name", "symbol", "variety"]]
big_dict[file_name.split("_")[1]] = temp_df
return big_dict
def get_dce_rank_table(date: str = "20210302", vars_list=cons.contract_symbols):
"""
大连商品交易所前 20 会员持仓排名数据明细, 由于交易所网站问题, 需要 20200720 之后才有数据
注: 该交易所只公布标的合约排名
:param date: 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, 数据从 20060104 开始，每交易日 16:30 左右更新数据
:return: pandas.DataFrame
rank 排名 int
vol_party_name 成交量排序的当前名次会员 string(中文)
vol 该会员成交量 int
vol_chg 该会员成交量变化量 int
long_party_name 持多单排序的当前名次会员 string(中文)
long_open_interest 该会员持多单 int
long_open_interest_chg 该会员持多单变化量 int
short_party_name 持空单排序的当前名次会员 string(中文)
short_open_interest 该会员持空单 int
short_open_interest_chg 该会员持空单变化量 int
symbol 标的合约 string
var 品种 string
date 日期 string YYYYMMDD
"""
date_string = date
date = cons.convert_date(date) if date is not None else datetime.date.today()
if date < datetime.date(2006, 1, 4):
print(Exception("大连商品交易所数据源开始日期为 20060104，跳过"))
return {}
if date.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % date.strftime('%Y%m%d'))
return {}
vars_list = [i for i in vars_list if i in cons.market_exchange_symbols['dce']]
big_dict = {}
for var in vars_list:
# var = 'V'
symbol_list = _get_dce_contract_list(date, var)
for symbol in symbol_list:
url = cons.DCE_VOL_RANK_URL_1 % (var.lower(), symbol, var.lower(), date.year, date.month - 1, date.day)
temp_df = pd.read_excel(url[:-3] + 'excel', header=0, skiprows=3)
temp_df.dropna(how='any', axis=0, inplace=True)
temp_df = temp_df.applymap(lambda x: str(x).replace(',', ''))
del temp_df["名次.1"]
del temp_df["名次.2"]
temp_df.rename(columns={"名次": "rank",
"会员简称": "vol_party_name",
"成交量": "vol",
"增减": "vol_chg",
"会员简称.1": "long_party_name",
"持买单量": "long_open_interest",
"增减.1": "long_open_interest_chg",
"会员简称.2": "short_party_name",
"持卖单量": "short_open_interest",
"增减.2": "short_open_interest_chg",
}, inplace=True)
temp_df['symbol'] = symbol.upper()
temp_df['var'] = var
temp_df['date'] = date_string
temp_df = temp_df.applymap(lambda x: str(x).replace("-", "0") if x == "-" else x)
temp_df['rank'] = range(1, len(temp_df)+1)
temp_df['vol'] = temp_df['vol'].astype(float)
temp_df['vol_chg'] = temp_df['vol_chg'].astype(float)
temp_df['long_open_interest'] = temp_df['long_open_interest'].astype(float)
temp_df['long_open_interest_chg'] = temp_df['long_open_interest_chg'].astype(float)
temp_df['short_open_interest'] = temp_df['short_open_interest'].astype(float)
temp_df['short_open_interest_chg'] = temp_df['short_open_interest_chg'].astype(float)
big_dict[symbol] = temp_df
return big_dict
def get_shfe_rank_table(date=None, vars_list=cons.contract_symbols):
"""
上海期货交易所前 20 会员持仓排名数据明细
注：该交易所只公布每个品种内部的标的排名，没有公布品种的总排名
数据从20020107开始，每交易日16:30左右更新数据
:param date: 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
rank 排名 int
vol_party_name 成交量排序的当前名次会员 string(中文)
vol 该会员成交量 int
vol_chg 该会员成交量变化量 int
long_party_name 持多单排序的当前名次会员 string(中文)
long_open_interest 该会员持多单 int
long_open_interest_chg 该会员持多单变化量 int
short_party_name 持空单排序的当前名次会员 string(中文)
short_open_interest 该会员持空单 int
short_open_interest_chg 该会员持空单变化量 int
symbol 标的合约 string
var 品种 string
date 日期 string YYYYMMDD
"""
date = cons.convert_date(
date) if date is not None else datetime.date.today()
if date < datetime.date(2002, 1, 7):
print("shfe数据源开始日期为20020107，跳过")
return {}
if date.strftime('%Y%m%d') not in calendar:
warnings.warn('%s非交易日' % date.strftime('%Y%m%d'))
return {}
url = cons.SHFE_VOL_RANK_URL % (date.strftime('%Y%m%d'))
r = requests_link(url, 'utf-8')
try:
context = json.loads(r.text)
except:
return {}
df = pd.DataFrame(context['o_cursor'])
df = df.rename(
columns={
'CJ1': 'vol',
'CJ1_CHG': 'vol_chg',
'CJ2': 'long_open_interest',
'CJ2_CHG': 'long_open_interest_chg',
'CJ3': 'short_open_interest',
'CJ3_CHG': 'short_open_interest_chg',
'PARTICIPANTABBR1': 'vol_party_name',
'PARTICIPANTABBR2': 'long_party_name',
'PARTICIPANTABBR3': 'short_party_name',
'PRODUCTNAME': 'product1',
'RANK': 'rank',
'INSTRUMENTID': 'symbol',
'PRODUCTSORTNO': 'product2'
})
if len(df.columns) < 3:
return {}
df = df.applymap(lambda x: x.strip() if isinstance(x, str) else x)
df = df.applymap(lambda x: None if x == '' else x)
df['variety'] = df['symbol'].apply(lambda x: symbol_varieties(x))
df = df[df['rank'] > 0]
for col in [
'PARTICIPANTID1', 'PARTICIPANTID2', 'PARTICIPANTID3', 'product1',
'product2'
]:
try:
del df[col]
except:
pass
get_vars = [var for var in vars_list if var in df['variety'].tolist()]
big_dict = {}
for var in get_vars:
df_var = df[df['variety'] == var]
for symbol in set(df_var['symbol']):
df_symbol = df_var[df_var['symbol'] == symbol]
big_dict[symbol] = df_symbol.reset_index(drop=True)
return big_dict
def get_czce_receipt_3(
date: str = None,
vars_list: List = cons.contract_symbols) -> pd.DataFrame:
"""
郑州商品交易所-注册仓单数据
适用 20151008-至今
http://www.czce.com.cn/cn/jysj/cdrb/H770310index_1.htm
:param date: 开始日期 format：YYYY-MM-DD 或 YYYYMMDD 或 datetime.date对象 为空时为当天
:type date: str
:param vars_list: 合约品种如 CF、TA 等列表为空时为所有商品
:type vars_list: list
:return: 注册仓单数据
:rtype: pandas.DataFrame
"""
if not isinstance(vars_list, list):
return warnings.warn("vars_list: 必须是列表")
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('%s非交易日' % date.strftime('%Y%m%d'))
return None
url = f"http://www.czce.com.cn/cn/DFSStaticFiles/Future/{date[:4]}/{date}/FutureDataWhsheet.xls"
r = requests_link(url, encoding='utf-8')
temp_df = pd.read_excel(BytesIO(r.content))
temp_df = temp_df[[
bool(1 - item) for item in [
item if item is not np.NAN else False
for item in temp_df.iloc[:, 0].str.contains("非农产品")
]
]]
temp_df.reset_index(inplace=True, drop=True)
range_list_one = list(temp_df[[
item if item is not np.NAN else False
for item in temp_df.iloc[:, 0].str.contains("品种")
]].index)
range_list_two = list(temp_df[[
item if item is not np.NAN else False
for item in temp_df.iloc[:, 0].str.contains("品种")
]].index)[1:]
range_list_two.append(None)
symbol_list = []
receipt_list = []
receipt_chg_list = []
for page in range(len(range_list_one)):
inner_df = temp_df[range_list_one[page]:range_list_two[page]]
reg = re.compile(r'[A-Z]+')
try:
symbol = reg.findall(inner_df.iloc[0, 0])[0]
except:
continue
symbol_list.append(symbol)
inner_df.columns = inner_df.iloc[1, :]
inner_df = inner_df.iloc[2:, :]
inner_df = inner_df.dropna(axis=1, how='all')
if symbol == "PTA":
try:
receipt_list.append(
inner_df['仓单数量(完税)'].iloc[-1] +
inner_df['仓单数量(保税)'].iloc[-1]) # 20210316 TA 分为保税和完税
except:
receipt_list.append(0)
elif symbol == "MA":
try:
try:
receipt_list.append(
inner_df['仓单数量(完税)'].iloc[-2] +
inner_df['仓单数量(保税)'].iloc[-2]) # 20210316 MA 分为保税和完税
except:
receipt_list.append(
inner_df['仓单数量(完税)'].iloc[-2]) # 处理 MA 的特殊格式
except:
receipt_list.append(0)
else:
try:
receipt_list.append(inner_df['仓单数量'].iloc[-1])
except:
receipt_list.append(0)
if symbol == "MA":
receipt_chg_list.append(inner_df['当日增减'].iloc[-2])
else:
receipt_chg_list.append(inner_df['当日增减'].iloc[-1])
data_df = pd.DataFrame([
symbol_list, receipt_list, receipt_chg_list,
[date] * len(receipt_chg_list)
]).T
data_df.columns = ['var', 'receipt', 'receipt_chg', 'date']
temp_list = data_df['var'].tolist()
data_df['var'] = [item if item != "PTA" else "TA" for item in temp_list]
if len(data_df.index) != 0:
data_df.index = data_df['var']
vars_in_market = [i for i in vars_list if i in data_df.index]
records = data_df.loc[vars_in_market, :]
return records.reset_index(drop=True)
