hikyuu2/hikyuu/data/common.py

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# coding:utf-8
#
# The MIT License (MIT)
#
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# Copyright (c) 2010-2019 fasiondog/hikyuu
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#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
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import requests
import re
import akshare as ak
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import pandas as pd
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import datetime
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from hikyuu.util import *
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class MARKET:
SH = 'SH'
SZ = 'SZ'
BJ = 'BJ'
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g_market_list = [MARKET.SH, MARKET.SZ, MARKET.BJ]
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class MARKETID:
SH = 1
SZ = 2
BJ = 3
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class STOCKTYPE:
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BLOCK = 0 # 板块
A = 1 # A股
INDEX = 2 # 指数
B = 3 # B股
FUND = 4 # 基金非ETF
ETF = 5 # ETF
ND = 6 # 国债
BOND = 7 # 其他债券
GEM = 8 # 创业板
START = 9 # 科创板
A_BJ = 11 # 北交所A股
def get_a_stktype_list():
"""获取A股市场证券类型元组含B股"""
return (STOCKTYPE.A, STOCKTYPE.INDEX, STOCKTYPE.B, STOCKTYPE.GEM, STOCKTYPE.START, STOCKTYPE.A_BJ)
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def get_stktype_list(quotations=None):
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"""
根据行情类别获取股票类别元组
:param quotations: 'stock'股票 | 'fund'基金 | 'bond'债券
:rtype: tuple
:return: 股票类别元组
"""
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if not quotations:
return (1, 2, 3, 4, 5, 6, 7, 8, 9, 11)
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result = []
for quotation in quotations:
new_quotation = quotation.lower()
if new_quotation == 'stock':
result += list(get_a_stktype_list())
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elif new_quotation == 'fund':
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result += [STOCKTYPE.FUND, STOCKTYPE.ETF]
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elif new_quotation == 'bond':
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result += [STOCKTYPE.ND, STOCKTYPE.BOND]
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else:
print('Unknow quotation: {}'.format(quotation))
return tuple(result)
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@hku_catch(ret=[], trace=True)
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@timeout(30)
def get_stk_code_name_list(market: str) -> list:
"""
获取指定证券交易所股票代码与名称列表
:return: 代码名称对组成的列表[{'code': 'code1': 'name': 'name1'}, ...]
"""
# 获取深圳股票代码表
if market == MARKET.SZ:
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ind_list = ["A股列表", "B股列表"]
df = None
for ind in ind_list:
tmp_df = ak.stock_info_sz_name_code(ind)
tmp_df.rename(columns={'A股代码': 'code', 'A股简称': 'name'}, inplace=True)
df = pd.concat([df, tmp_df]) if df is not None else tmp_df
hku_info("获取深圳证券交易所股票数量: {}", len(df) if df is not None else 0)
return df[['code', 'name']].to_dict(orient='records') if df is not None else []
# 获取上证股票代码表
if market == MARKET.SH:
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ind_list = ["主板A股", "主板B股", "科创板"]
df = None
for ind in ind_list:
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tmp_df = ak.stock_info_sh_name_code(ind)
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tmp_df.rename(columns={'证券代码': 'code', '证券简称': 'name'}, inplace=True)
df = pd.concat([df, tmp_df]) if df is not None else tmp_df
hku_info("获取上海证券交易所股票数量: {}", len(df) if df is not None else 0)
return df[['code', 'name']].to_dict(orient='records') if df is not None else []
# 获取北京股票代码表
if market == MARKET.BJ:
df = ak.stock_info_bj_name_code()
df.rename(columns={'证券代码': 'code', '证券简称': 'name'}, inplace=True)
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hku_info("获取北京证券交易所股票数量: {}", len(df) if df is not None else 0)
return df[['code', 'name']].to_dict(orient='records') if df is not None else []
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@hku_catch(ret=[], trace=True)
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@timeout(60)
def get_index_code_name_list() -> list:
"""
获取所有股票指数代码名称列表
从新浪获取多次频繁调用会被封禁IP需10分钟后再试
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:return: [{'market_code': 'SHxxx'}, ...]
"""
if hasattr(ak, 'stock_zh_index_spot_sina'):
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df = ak.stock_zh_index_spot_sina()
elif hasattr(ak, 'stock_zh_index_spot_em'):
df = ak.stock_zh_index_spot_em()
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else:
df = ak.stock_zh_index_spot()
res = [{'market_code': df.loc[i]['代码'].upper(), 'name': df.loc[i]['名称']} for i in range(len(df))]
ret = [v for v in res if len(v['market_code']) == 8]
return ret
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g_fund_code_name_list = {}
for market in g_market_list:
g_fund_code_name_list[market] = []
g_last_get_fund_code_name_list_date = datetime.date(1990, 12, 9)
@hku_catch(ret=[], trace=True)
@timeout(60)
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def get_fund_code_name_list(market: str) -> list:
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"""
获取基金代码名称列表 (来源: sina)
"""
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# 保证一天只获取一次基金股票代码表,防止对 sina 的频繁访问
global g_last_get_fund_code_name_list_date
now = datetime.date.today()
if now <= g_last_get_fund_code_name_list_date:
return g_fund_code_name_list[market]
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ind_list = "封闭式基金", "ETF基金", "LOF基金"
for ind in ind_list:
df = ak.fund_etf_category_sina(ind)
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for i in range(len(df)):
loc = df.loc[i]
try:
code, name = str(loc['代码']), str(loc['名称'])
g_fund_code_name_list[code[:2].upper()].append(dict(code=code[2:], name=name))
except Exception as e:
hku_error("{}! {}", str(e), loc)
hku_info("获取基金列表数量: {}", len(g_fund_code_name_list[market]))
g_last_get_fund_code_name_list_date = now
return g_fund_code_name_list[market]
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@hku_catch(ret=[], trace=True)
def get_new_holidays():
"""获取新的交易所休假日历"""
res = requests.get('https://www.tdx.com.cn/url/holiday/', timeout=60)
res.encoding = res.apparent_encoding
ret = re.findall(r'<textarea id="data" style="display:none;">([\s\w\d\W]+)</textarea>', res.text, re.M)[0].strip()
day = [d.split('|')[:4] for d in ret.split('\n')]
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return [v[0] for v in day if len(v) >= 3 and v[2] == '中国']
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@hku_catch(ret=[], trace=True)
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@timeout(60)
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def get_china_bond10_rate(start_date="19901219"):
"""获取中国国债收益率10年"""
bond_zh_us_rate_df = ak.bond_zh_us_rate(start_date)
df = bond_zh_us_rate_df[['中国国债收益率10年', '日期']].dropna()
return [(v[1].strftime('%Y%m%d'), int(v[0]*10000)) for v in df.values]
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def modifiy_code(code):
if code.startswith(('0', '3')):
return 'SZ' + code
if code.startswith(('4', '8', '92')):
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return 'BJ' + code
if code.startswith('6'):
return 'SH' + code
else:
hku_warn("Unknow code: {}", code)
return None
def historyfinancialreader(filepath):
"""
读取解析通达信目录的历史财务数据来源: onefish, 公众号一鱼策略
:param filepath: 字符串类型传入文件路径
:return: DataFrame格式返回解析出的财务文件内容
"""
import struct
cw_file = open(filepath, 'rb')
header_pack_format = '<1hI1H3L'
header_size = struct.calcsize(header_pack_format)
stock_item_size = struct.calcsize("<6s1c1L")
data_header = cw_file.read(header_size)
stock_header = struct.unpack(header_pack_format, data_header)
max_count = stock_header[2]
file_date = stock_header[1]
print(file_date)
report_size = stock_header[4]
report_fields_count = int(report_size / 4)
report_pack_format = '<{}f'.format(report_fields_count)
results = []
for stock_idx in range(0, max_count):
cw_file.seek(header_size + stock_idx * struct.calcsize("<6s1c1L"))
si = cw_file.read(stock_item_size)
stock_item = struct.unpack("<6s1c1L", si)
code = stock_item[0].decode("utf-8")
foa = stock_item[2]
cw_file.seek(foa)
info_data = cw_file.read(struct.calcsize(report_pack_format))
cw_info = list(struct.unpack(report_pack_format, info_data))
report_date = int(cw_info[313]) # 财务公告日期
report_date = 19000000 + report_date if report_date > 800000 else 20000000 + report_date
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results.append((file_date, modifiy_code(code), report_date, info_data))
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cw_file.close()
return results