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_czce_rank_table(date="20081015", 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"))
r = requests.get(url)
r.encoding = "utf-8"
soup = BeautifulSoup(r.text, "lxml")
data = _czce_df_read(url, skip_rows=0)
r = requests_link(url, "utf-8")
r.encoding = "utf-8"
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]
if symbol == "SR905日期:":
symbol = "SR905"
symbols.append(symbol)
big_dict = {}
for i in range(len(symbols)):
symbol = symbols[i]
table_cut = data[i + 1]
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): # 20200311 格式修正
url = cons.CZCE_VOL_RANK_URL_2 % (date.year, date.strftime("%Y%m%d"))
data = _czce_df_read(url, skip_rows=0, header=None)[3:]
big_df = pd.DataFrame()
for item in data:
big_df = pd.concat([big_df, item], axis=0, ignore_index=False)
big_df.columns = big_df.iloc[0, :].tolist()
data = big_df.iloc[1:, :]
elif date < datetime.date(2017, 12, 28): # 20200311 格式修正
url = cons.CZCE_VOL_RANK_URL_3 % (date.year, date.strftime("%Y%m%d"))
data = _czce_df_read(url, skip_rows=0, header=0)[1]
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.index.name = table.columns[0]
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.strip()] = table_cut.reset_index(drop=True)
return big_dict
