87 lines
2.4 KiB
Python
87 lines
2.4 KiB
Python
# -*- coding:utf-8 -*-
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import tushare as ts
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import pandas as pd
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import random
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from multiprocessing.dummy import Pool as ThreadPool
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class TsData(object):
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def __init__(self):
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self.url = 'http://file.tushare.org/tsdata/symbols.csv'
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self.stocks = self._get_data()
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self.cons = None #self._get_cons()
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self.data = pd.DataFrame()
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def _get_data(self):
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df = pd.read_csv(self.url,
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dtype={'symbol': object})
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return list(df['symbol'].values)
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def _get_cons(self):
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con1 = ts.get_apis()
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con2 = ts.get_apis()
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con3 = ts.get_apis()
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con4 = ts.get_apis()
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con5 = ts.get_apis()
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return [con1, con2, con3, con4, con5]
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def _get_server(self):
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random.shuffle(self.cons)
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return self.cons[0]
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def _data(self, symbol, start_date='', end_date=''):
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try:
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conn = self._get_server()
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df = ts.bar(symbol, conn=conn, freq='5min')
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df = df.reset_index(inplace=True)
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df = df[['datetime', 'open', 'close', 'high', 'low', 'volume', 'code']]
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self.data = self.data.append(df, ignore_index=True)
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return df
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except:
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return None
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def _get_k_data(self, symbol):
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try:
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df = ts.get_k_data(symbol, ktype='5')
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df = df[['date', 'open', 'close', 'high', 'low', 'volume', 'code']]
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df.columns = ['datetime', 'open', 'close', 'high', 'low', 'volume', 'code']
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return df
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except:
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return None
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def get_m_data(self, symbols):
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print(symbols)
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df = self._get_k_data(symbols)
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if df is None:
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if self.cons is None:
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self.cons = self._get_cons()
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df = self._data(symbols)
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self.data = self.data.append(df, ignore_index=True)
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def get_data(self, symbols=None):
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if symbols is None:
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stocks = self._get_data()
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pool = ThreadPool(600)
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pool.map(self.get_m_data, stocks)
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if self.cons is not None:
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for con in self.cons:
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ts.close_apis(con)
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return self.data
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if __name__ == '__main__':
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api = TsData()
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df = api.get_data()
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print(df)
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