# coding: utf-8
import os
import pickle
import json
import requests
import warnings
from collections import OrderedDict
import pandas as pd
from datetime import datetime, timedelta
from typing import List
from urllib.parse import quote
from ..objects import RawBar, Freq
from ..utils.bar_generator import freq_end_time, BarGenerator
from .base import freq_cn2jq
url = "https://dataapi.joinquant.com/apis"
home_path = os.path.expanduser("~")
file_token = os.path.join(home_path, "jq.token")
dt_fmt = "%Y-%m-%d %H:%M:%S"
date_fmt = "%Y-%m-%d"
# 1m, 5m, 15m, 30m, 60m, 120m, 1d, 1w, 1M
freq_convert = {"1min": "1m", "5min": '5m', '15min': '15m',
"30min": "30m", "60min": '60m', "D": "1d", "W": '1w', "M": "1M"}
freq_map = {'1min': Freq.F1, '5min': Freq.F5, '15min': Freq.F15, '30min': Freq.F30,
'60min': Freq.F60, 'D': Freq.D, 'W': Freq.W, 'M': Freq.M}
[docs]def set_token(jq_mob, jq_pwd):
"""
:param jq_mob: str
mob是申请JQData时所填写的手机号
:param jq_pwd: str
Password为聚宽官网登录密码，新申请用户默认为手机号后6位
:return: None
"""
with open(file_token, 'wb') as f:
pickle.dump([jq_mob, jq_pwd], f)
[docs]def get_token():
"""获取调用凭证"""
if not os.path.exists(file_token):
raise ValueError(f"{file_token} 文件不存在，请先调用 set_token 进行设置")
with open(file_token, 'rb') as f:
jq_mob, jq_pwd = pickle.load(f)
body = {
"method": "get_current_token",
"mob": jq_mob, # mob是申请JQData时所填写的手机号
"pwd": quote(jq_pwd), # Password为聚宽官网登录密码，新申请用户默认为手机号后6位
}
response = requests.post(url, data=json.dumps(body))
token = response.text
return token
to_jq_symbol = lambda x: x[:6] + ".XSHG" if x[0] == '6' else x[:6] + ".XSHE"
[docs]def text2df(text):
rows = [x.split(",") for x in text.strip().split('\n')]
df = pd.DataFrame(rows[1:], columns=rows[0])
return df
[docs]def get_query_count() -> int:
"""获取查询剩余条数
https://dataapi.joinquant.com/docs#get_query_count---%E8%8E%B7%E5%8F%96%E6%9F%A5%E8%AF%A2%E5%89%A9%E4%BD%99%E6%9D%A1%E6%95%B0
:return: int
"""
data = {
"method": "get_query_count",
"token": get_token(),
}
r = requests.post(url, data=json.dumps(data))
return int(r.text)
[docs]def get_concepts():
"""获取概念列表
https://dataapi.joinquant.com/docs#get_concepts---%E8%8E%B7%E5%8F%96%E6%A6%82%E5%BF%B5%E5%88%97%E8%A1%A8
:return: df
"""
data = {
"method": "get_concepts",
"token": get_token(),
}
r = requests.post(url, data=json.dumps(data))
df = text2df(r.text)
return df
[docs]def get_concept_stocks(symbol, date=None):
"""获取概念成份股
https://dataapi.joinquant.com/docs#get_concept_stocks---%E8%8E%B7%E5%8F%96%E6%A6%82%E5%BF%B5%E6%88%90%E4%BB%BD%E8%82%A1
:param symbol: str
如 GN036
:param date: str or datetime
日期，如 2020-08-08
:return: list
examples:
-------
>>> symbols1 = get_concept_stocks("GN036", date="2020-07-08")
>>> symbols2 = get_concept_stocks("GN036", date=datetime.now())
"""
if not date:
date = str(datetime.now().date())
else:
date = pd.to_datetime(date)
if isinstance(date, datetime):
date = str(date.date())
data = {
"method": "get_concept_stocks",
"token": get_token(),
"code": symbol,
"date": date
}
r = requests.post(url, data=json.dumps(data))
return r.text.split('\n')
[docs]def get_index_stocks(symbol, date=None):
"""获取指数成份股
https://dataapi.joinquant.com/docs#get_index_stocks---%E8%8E%B7%E5%8F%96%E6%8C%87%E6%95%B0%E6%88%90%E4%BB%BD%E8%82%A1
:param symbol: str
如 000300.XSHG
:param date: str or datetime
日期，如 2020-08-08
:return: list
examples:
-------
>>> symbols1 = get_index_stocks("000300.XSHG", date="2020-07-08")
>>> symbols2 = get_index_stocks("000300.XSHG", date=datetime.now())
"""
if not date:
date = str(datetime.now().date())
if isinstance(date, datetime):
date = str(date.date())
data = {
"method": "get_index_stocks",
"token": get_token(),
"code": symbol,
"date": date
}
r = requests.post(url, data=json.dumps(data))
return r.text.split('\n')
[docs]def get_industry(symbol):
"""
https://www.joinquant.com/help/api/help#JQDataHttp:get_industry-%E6%9F%A5%E8%AF%A2%E8%82%A1%E7%A5%A8%E6%89%80%E5%B1%9E%E8%A1%8C%E4%B8%9A
:param symbol:
:return:
"""
data = {
"method": "get_industry",
"token": get_token(),
"code": symbol,
"date": str(datetime.now().date())
}
r = requests.post(url, data=json.dumps(data))
df = text2df(r.text)
res = {
"股票代码": symbol,
"证监会行业代码": df[df['industry'] == 'zjw']['industry_code'].iloc[0],
"证监会行业名称": df[df['industry'] == 'zjw']['industry_name'].iloc[0],
"聚宽一级行业代码": df[df['industry'] == 'jq_l1']['industry_code'].iloc[0],
"聚宽一级行业名称": df[df['industry'] == 'jq_l1']['industry_name'].iloc[0],
"聚宽二级行业代码": df[df['industry'] == 'jq_l2']['industry_code'].iloc[0],
"聚宽二级行业名称": df[df['industry'] == 'jq_l2']['industry_name'].iloc[0],
"申万一级行业代码": df[df['industry'] == 'sw_l1']['industry_code'].iloc[0],
"申万一级行业名称": df[df['industry'] == 'sw_l1']['industry_name'].iloc[0],
"申万二级行业代码": df[df['industry'] == 'sw_l2']['industry_code'].iloc[0],
"申万二级行业名称": df[df['industry'] == 'sw_l2']['industry_name'].iloc[0],
"申万三级行业代码": df[df['industry'] == 'sw_l3']['industry_code'].iloc[0],
"申万三级行业名称": df[df['industry'] == 'sw_l3']['industry_name'].iloc[0],
}
return res
[docs]def get_all_securities(code, date=None) -> pd.DataFrame:
"""
https://dataapi.joinquant.com/docs#get_all_securities---%E8%8E%B7%E5%8F%96%E6%89%80%E6%9C%89%E6%A0%87%E7%9A%84%E4%BF%A1%E6%81%AF
获取平台支持的所有股票、基金、指数、期货信息
参数：
code: 证券类型,可选: stock, fund, index, futures, etf, lof, fja, fjb, QDII_fund,
open_fund, bond_fund, stock_fund, money_market_fund, mixture_fund, options
date: 日期，用于获取某日期还在上市的证券信息，date为空时表示获取所有日期的标的信息
:return:
"""
if not date:
date = str(datetime.now().date())
if isinstance(date, datetime):
date = str(date.date())
data = {
"method": "get_all_securities",
"token": get_token(),
"code": code,
"date": date
}
r = requests.post(url, data=json.dumps(data))
return text2df(r.text)
[docs]def get_kline(symbol: str, end_date: [datetime, str], freq: str,
start_date: [datetime, str] = None, count=None, fq: bool = True) -> List[RawBar]:
"""获取K线数据
https://www.joinquant.com/help/api/help#JQDataHttp:get_priceget_bars-%E8%8E%B7%E5%8F%96%E6%8C%87%E5%AE%9A%E6%97%B6%E9%97%B4%E5%91%A8%E6%9C%9F%E7%9A%84%E8%A1%8C%E6%83%85%E6%95%B0%E6%8D%AE
:param symbol: 聚宽标的代码
:param start_date: 开始日期
:param end_date: 截止日期
:param freq: K线级别，可选值 ['1min', '5min', '30min', '60min', 'D', 'W', 'M']
:param count: K线数量，最大值为 5000
:param fq: 是否进行复权
:return: pd.DataFrame
>>> start_date = datetime.strptime("20200701", "%Y%m%d")
>>> end_date = datetime.strptime("20200719", "%Y%m%d")
>>> df1 = get_kline(symbol="000001.XSHG", start_date=start_date, end_date=end_date, freq="1min")
>>> df2 = get_kline(symbol="000001.XSHG", end_date=end_date, freq="1min", count=1000)
>>> df3 = get_kline(symbol="000001.XSHG", start_date='20200701', end_date='20200719', freq="1min", fq=True)
>>> df4 = get_kline(symbol="000001.XSHG", end_date='20200719', freq="1min", count=1000)
"""
if count and count > 5000:
warnings.warn(f"count={count}, 超过5000的最大值限制，仅返回最后5000条记录")
end_date = pd.to_datetime(end_date)
if start_date:
start_date = pd.to_datetime(start_date)
data = {
"method": "get_price_period",
"token": get_token(),
"code": symbol,
"unit": freq_convert[freq],
"date": start_date.strftime("%Y-%m-%d"),
"end_date": end_date.strftime("%Y-%m-%d"),
}
elif count:
data = {
"method": "get_price",
"token": get_token(),
"code": symbol,
"count": count,
"unit": freq_convert[freq],
"end_date": end_date.strftime("%Y-%m-%d"),
}
else:
raise ValueError("start_date 和 count 不能同时为空")
if fq:
data.update({"fq_ref_date": end_date.strftime("%Y-%m-%d")})
r = requests.post(url, data=json.dumps(data))
rows = [x.split(",") for x in r.text.strip().split('\n')][1:]
bars = []
i = -1
for row in rows:
# row = ['date', 'open', 'close', 'high', 'low', 'volume', 'money']
dt = pd.to_datetime(row[0])
if freq == "D":
dt = dt.replace(hour=0, minute=0, second=0, microsecond=0)
if int(row[5]) > 0:
i += 1
bars.append(RawBar(symbol=symbol, dt=dt, id=i, freq=freq_map[freq],
open=round(float(row[1]), 2),
close=round(float(row[2]), 2),
high=round(float(row[3]), 2),
low=round(float(row[4]), 2),
vol=int(row[5]), amount=int(float(row[6]))))
# amount 单位：元
if start_date:
bars = [x for x in bars if x.dt >= start_date]
if "min" in freq:
bars[-1].dt = freq_end_time(bars[-1].dt, freq=freq_map[freq])
bars = [x for x in bars if x.dt <= end_date]
return bars
[docs]def get_kline_period(symbol: str, start_date: [datetime, str],
end_date: [datetime, str], freq: str, fq=True) -> List[RawBar]:
"""获取指定时间段的行情数据
https://www.joinquant.com/help/api/help#JQDataHttp:get_price_periodget_bars_period-%E8%8E%B7%E5%8F%96%E6%8C%87%E5%AE%9A%E6%97%B6%E9%97%B4%E6%AE%B5%E7%9A%84%E8%A1%8C%E6%83%85%E6%95%B0%E6%8D%AE
:param symbol: 聚宽标的代码
:param start_date: 开始日期
:param end_date: 截止日期
:param freq: K线级别，可选值 ['1min', '5min', '30min', '60min', 'D', 'W', 'M']
:param fq: 是否进行复权
:return:
"""
start_date = pd.to_datetime(start_date)
end_date = pd.to_datetime(end_date)
if (end_date - start_date).days * 5 / 7 > 1000:
warnings.warn(f"{end_date.date()} - {start_date.date()} 超过1000个交易日，K线获取可能失败，返回为0")
data = {
"method": "get_price_period",
"token": get_token(),
"code": symbol,
"unit": freq_convert[freq],
"date": start_date.strftime("%Y-%m-%d"),
"end_date": end_date.strftime("%Y-%m-%d"),
}
if fq:
data.update({"fq_ref_date": end_date.strftime("%Y-%m-%d")})
r = requests.post(url, data=json.dumps(data))
rows = [x.split(",") for x in r.text.strip().split('\n')][1:]
bars = []
i = -1
for row in rows:
# row = ['date', 'open', 'close', 'high', 'low', 'volume', 'money']
dt = pd.to_datetime(row[0])
if freq == "D":
dt = dt.replace(hour=0, minute=0, second=0, microsecond=0)
if int(row[5]) > 0:
i += 1
bars.append(RawBar(symbol=symbol, dt=dt, id=i, freq=freq_map[freq],
open=round(float(row[1]), 2),
close=round(float(row[2]), 2),
high=round(float(row[3]), 2),
low=round(float(row[4]), 2),
vol=int(row[5]), amount=int(float(row[6]))))
# amount 单位：元
if start_date:
bars = [x for x in bars if x.dt >= start_date]
if "min" in freq and bars:
bars[-1].dt = freq_end_time(bars[-1].dt, freq=freq_map[freq])
bars = [x for x in bars if x.dt <= end_date]
return bars
[docs]def get_init_bg(symbol: str,
end_dt: [str, datetime],
base_freq: str,
freqs: List[str],
max_count=1000,
fq=True):
"""获取 symbol 的初始化 bar generator"""
if isinstance(end_dt, str):
end_dt = pd.to_datetime(end_dt, utc=False)
delta_days = 180
last_day = (end_dt - timedelta(days=delta_days)).replace(hour=16, minute=0)
bg = BarGenerator(base_freq, freqs, max_count)
for freq in bg.bars.keys():
bars_ = get_kline(symbol=symbol, end_date=last_day, freq=freq_cn2jq[freq], count=max_count, fq=fq)
bg.init_freq_bars(freq, bars_)
print(f"{symbol} - {freq} - {len(bg.bars[freq])} - last_dt: {bg.bars[freq][-1].dt} - last_day: {last_day}")
bars2 = get_kline_period(symbol, last_day, end_dt, freq=freq_cn2jq[base_freq], fq=fq)
data = [x for x in bars2 if x.dt > last_day]
assert len(data) > 0
print(f"{symbol}: bar generator 最新时间 {bg.bars[base_freq][-1].dt.strftime(dt_fmt)}，还有{len(data)}行数据需要update")
return bg, data
[docs]def get_fundamental(table: str, symbol: str, date: str, columns: str = "") -> dict:
"""
https://dataapi.joinquant.com/docs#get_fundamentals---%E8%8E%B7%E5%8F%96%E5%9F%BA%E6%9C%AC%E8%B4%A2%E5%8A%A1%E6%95%B0%E6%8D%AE
财务数据列表：
https://www.joinquant.com/help/api/help?name=Stock#%E8%B4%A2%E5%8A%A1%E6%95%B0%E6%8D%AE%E5%88%97%E8%A1%A8
:param table:
:param symbol:
:param date: str
查询日期2019-03-04或者年度2018或者季度2018q1 2018q2 2018q3 2018q4
:param columns:
:return: df
example:
============
>>>> x1 = get_fundamental(table="indicator", symbol="300803.XSHE", date="2020-11-12")
>>>> x2 = get_fundamental(table="indicator", symbol="300803.XSHE", date="2020")
>>>> x3 = get_fundamental(table="indicator", symbol="300803.XSHE", date="2020q3")
"""
data = {
"method": "get_fundamentals",
"token": get_token(),
"table": table,
"columns": columns,
"code": symbol,
"date": date,
"count": 1
}
r = requests.post(url, data=json.dumps(data))
df = text2df(r.text)
try:
return df.iloc[0].to_dict()
except:
return {}
[docs]def run_query(table: str, conditions: str, columns=None, count=1):
"""模拟JQDataSDK的run_query方法
https://www.joinquant.com/help/api/help#JQDataHttp:run_query-%E6%A8%A1%E6%8B%9FJQDataSDK%E7%9A%84run_query%E6%96%B9%E6%B3%95
:param table: 要查询的数据库和表名，格式为 database + . + tablename 如finance.STK_XR_XD
:param conditions: 查询条件，可以为空
格式为report_date#>=#2006-12-01&report_date#<=#2006-12-31，
条件内部#号分隔，格式： column # 判断符 # value，
多个条件使用&号分隔，表示and，conditions不能有空格等特殊字符
:param columns: 所查字段，为空时则查询所有字段，多个字段中间用,分隔。如id,company_id，columns不能有空格等特殊字符
:param count: 数量
:return:
"""
data = {
"method": "run_query",
"token": get_token(),
"table": table,
"conditions": conditions,
"count": count
}
if columns:
data['columns'] = columns
r = requests.post(url, data=json.dumps(data))
df = text2df(r.text)
return df
[docs]def get_share_basic(symbol):
"""获取单个标的的基本面基础数据
:param symbol:
:return:
"""
basic_info = run_query(table="finance.STK_COMPANY_INFO", conditions="code#=#{}".format(symbol), count=1)
basic_info = basic_info.iloc[0].to_dict()
f10 = OrderedDict()
f10['股票代码'] = basic_info['code']
f10['股票名称'] = basic_info['short_name']
f10['行业'] = "{}-{}".format(basic_info['industry_1'], basic_info['industry_2'])
f10['地域'] = "{}{}".format(basic_info['province'], basic_info['city'])
f10['主营'] = basic_info['main_business']
f10['同花顺F10'] = "http://basic.10jqka.com.cn/{}".format(basic_info['code'][:6])
# 市盈率，总市值，流通市值，流通比
# ------------------------------------------------------------------------------------------------------------------
last_date = datetime.now() - timedelta(days=1)
res = get_fundamental(table="valuation", symbol=symbol, date=last_date.strftime("%Y-%m-%d"))
f10['总市值（亿）'] = float(res['market_cap'])
f10['流通市值（亿）'] = float(res['circulating_market_cap'])
f10['流通比（%）'] = round(float(res['circulating_market_cap']) / float(res['market_cap']) * 100, 2)
f10['PE_TTM'] = float(res['pe_ratio'])
f10['PE'] = float(res['pe_ratio_lyr'])
f10['PB'] = float(res['pb_ratio'])
# 净资产收益率
# ------------------------------------------------------------------------------------------------------------------
for year in ['2017', '2018', '2019', '2020']:
indicator = get_fundamental(table="indicator", symbol=symbol, date=year)
f10['{}EPS'.format(year)] = float(indicator.get('eps', 0)) if indicator.get('eps', 0) else 0
f10['{}ROA'.format(year)] = float(indicator.get('roa', 0)) if indicator.get('roa', 0) else 0
f10['{}ROE'.format(year)] = float(indicator.get('roe', 0)) if indicator.get('roe', 0) else 0
f10['{}销售净利率(%)'.format(year)] = float(indicator.get('net_profit_margin', 0)) if indicator.get('net_profit_margin', 0) else 0
f10['{}销售毛利率(%)'.format(year)] = float(indicator.get('gross_profit_margin', 0)) if indicator.get('gross_profit_margin', 0) else 0
f10['{}营业收入同比增长率(%)'.format(year)] = float(indicator.get('inc_revenue_year_on_year', 0)) if indicator.get('inc_revenue_year_on_year', 0) else 0
f10['{}营业收入环比增长率(%)'.format(year)] = float(indicator.get('inc_revenue_annual', 0)) if indicator.get('inc_revenue_annual', 0) else 0
f10['{}营业利润同比增长率(%)'.format(year)] = float(indicator.get('inc_operation_profit_year_on_year', 0)) if indicator.get('inc_operation_profit_year_on_year', 0) else 0
f10['{}经营活动产生的现金流量净额/营业收入(%)'.format(year)] = float(indicator.get('ocf_to_revenue', 0)) if indicator.get('ocf_to_revenue', 0) else 0
# 组合成可以用来推送的文本
msg = "{}（{}）@{}\n".format(f10['股票代码'], f10['股票名称'], f10['地域'])
msg += "\n{}\n".format("*" * 30)
for k in ['行业', '主营', 'PE_TTM', 'PE', 'PB', '总市值（亿）', '流通市值（亿）', '流通比（%）', '同花顺F10']:
msg += "{}：{}\n".format(k, f10[k])
msg += "\n{}\n".format("*" * 30)
cols = ['EPS', 'ROA', 'ROE', '销售净利率(%)', '销售毛利率(%)', '营业收入同比增长率(%)', '营业利润同比增长率(%)', '经营活动产生的现金流量净额/营业收入(%)']
msg += "2017~2020 财务变化\n\n"
for k in cols:
msg += k + "：{} | {} | {} | {}\n".format(*[f10['{}{}'.format(year, k)] for year in ['2017', '2018', '2019', '2020']])
f10['msg'] = msg
return f10