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marketdata.py
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# -*- coding:utf-8 -*-
import pandas as pd
from pandas.compat import StringIO
import re
import json
import numpy as np
from gugu.base import Base, cf
class MarketData(Base):
def index(self):
"""
获取大盘指数行情
return
-------
DataFrame or list: [{'code':, 'name':, ...}, ...]
code:指数代码
name:指数名称
change:涨跌幅
open:开盘价
preclose:昨日收盘价
close:收盘价
high:最高价
low:最低价
volume:成交量(手)
amount:成交金额（亿元）
"""
self._data = pd.DataFrame()
# http://hq.sinajs.cn/rn=xppzh&list=sh000001,sh000002,sh000003,sh000008,sh000009,sh000010,sh000011,sh000012,sh000016,sh000017,sh000300,sh000905,sz399001,sz399002,sz399003,sz399004,sz399005,sz399006,sz399008,sz399100,sz399101,sz399106,sz399107,sz399108,sz399333,sz399606
request = self._session.get( cf.INDEX_URL, timeout=10 )
request.encoding = 'gbk'
text = request.text.replace('var hq_str_', '')
text = text.replace('";', '').replace('"', '').replace('=', ',')
text = '%s%s'%(cf.INDEX_HEADER, text)
self._data = pd.read_csv(StringIO(text), sep=',', thousands=',')
self._data['change'] = (self._data['close'] / self._data['preclose'] - 1 ) * 100
self._data['amount'] = self._data['amount'] / 100000000
self._data['change'] = self._data['change'].map(cf.FORMAT)
self._data['amount'] = self._data['amount'].map(cf.FORMAT4)
self._data = self._data[cf.INDEX_COLS]
self._data['code'] = self._data['code'].map(lambda x:str(x).zfill(6))
self._data['change'] = self._data['change'].astype(float)
self._data['amount'] = self._data['amount'].astype(float)
return self._result()
def latest(self):
"""
一次性获取最近一个日交易日所有股票的交易数据
return
-------
DataFrame or list: [{'code':, 'name':, ...}, ...]
code：代码
name:名称
changepercent:涨跌幅
trade:现价
open:开盘价
high:最高价
low:最低价
settlement:昨日收盘价
volume:成交量
turnoverratio:换手率
amount:成交量
per:市盈率
pb:市净率
mktcap:总市值
nmc:流通市值
"""
self._data = pd.DataFrame()
self._writeHead()
self._data = self.__handleLatest(1)
if self._data is not None:
for i in range(2, cf.PAGE_NUM[0]):
newData = self.__handleLatest(i)
self._data = self._data.append(newData, ignore_index=True)
return self._result()
def __handleLatest(self, pageNum=1):
"""
处理当日行情分页数据，格式为json
Parameters
------
pageNum:页码
return
-------
DataFrame 当日所有股票交易数据(DataFrame)
"""
self._writeConsole()
# http://vip.stock.finance.sina.com.cn/quotes_service/api/json_v2.php/Market_Center.getHQNodeData?num=80&sort=code&asc=0&node=hs_a&symbol=&_s_r_a=page&page=1
request = self._session.get( cf.LATEST_URL % pageNum, timeout=10 )
if self._PY3:
request.encoding = 'gbk'
text = request.text
if text == 'null':
return None
reg = re.compile(r'\,(.*?)\:')
text = reg.sub(r',"\1":', text)
text = text.replace('"{symbol', '{"symbol')
text = text.replace('{symbol', '{"symbol"')
jstr = json.dumps(text)
js = json.loads(jstr)
df = pd.DataFrame(pd.read_json(js, dtype={'code':object}), columns=cf.DAY_TRADING_COLUMNS)
df = df.drop('symbol', axis=1)
return df
def indexETF(self):
"""
获取指数ETF及其相关数据
return
------
DataFrame or List: [{'fund_id':, 'fund_nm':, ...}, ...]
fund_id: 基金代码
fund_nm: 基金名称
index_id: 跟踪指数代码
creation_unit: 最小申赎单位（万份）
amount: 份额（万份）
unit_total: 规模（亿元）
unit_incr: 规模变化（亿元）
price: 现价
volume: 成交额（万元）
increase_rt: 涨幅（%）
estimate_value: 估值
discount_rt: 溢价率（%）
fund_nav: 净值
nav_dt: 净值日期
index_nm: 指数名称
index_increase_rt: 指数涨幅（%）
pe: 市盈率
pb: 市净率
"""
self._data = pd.DataFrame()
page = 1
while(True):
try:
request = self._session.get( cf.INDEX_ETF_URL % page )
text = request.text.replace('%', '')
dataDict = json.loads(text)
if dataDict['page'] < page:
break
dataList = []
for row in dataDict['rows']:
dataList.append(row['cell'])
self._data = self._data.append(pd.DataFrame(dataList, columns = cf.INDEX_ETF_COLS), ignore_index=True)
page += 1
except Exception as e:
print(str(e))
self._data[self._data=="-"] = np.NaN
for col in ['creation_unit', 'amount', 'unit_total', 'unit_incr', 'price', 'volume', 'increase_rt',
'estimate_value', 'discount_rt', 'fund_nav', 'index_increase_rt', 'pe', 'pb']:
self._data[col] = self._data[col].astype(float)
self._data['index_id'] = self._data['index_id'].map(lambda x : x if x != "0" else None)
return self._result()