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get_realtime_feature.py
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get_realtime_feature.py
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import easyquotation
import tushare as ts
import os
from tqdm import tqdm
import pandas as pd
import numpy as np
def get_feature(stock_info, df):
"""
stock_info:字典形式输入
df:股票历史信息 dataframe
"""
feature = []
# 计算20日收盘价 ma
tmp_list = list(df.iloc[-19:]['close'])
tmp_list.append(stock_info['now'])
feature.append(np.mean(tmp_list))
return feature
# 涨跌停统计
def count_limit(tmp_dict):
up = 0
down = 0
for tmp_keys in tqdm(tmp_dict.keys()):
stock_info = tmp_dict[tmp_keys]
if 'ST' in stock_info['name']:
if stock_info['now'] >= round(stock_info['close'] * 1.05, 2):
up += 1
elif stock_info['now'] <= round(stock_info['close'] * 0.95, 2):
down += 1
else:
if stock_info['now'] >= round(stock_info['close'] * 1.1, 2):
up += 1
elif stock_info['now'] <= round(stock_info['close'] * 0.9, 2):
down += 1
return up, down
def handle_history(base_path, tmp_dict):
company_info = pd.read_csv(os.path.join(base_path, 'company_info.csv'), encoding='gbk')
company_info['is_ST'] = company_info['name'].apply(JudgeST)
col = ['trade_date', 'ts_code', 'open', 'high', 'low', 'close',
'change', 'pct_chg', 'vol', 'amount', 'turnover_rate', 'volume_ratio']
df_list = []
features = []
ts_codes = []
for tmp_name in tqdm(company_info['ts_code']):
file_path = os.path.join(base_path, 'OldData', tmp_name + '_NormalData.csv')
df = pd.read_csv(file_path)
df = df.sort_values('trade_date', ascending=True).reset_index(drop=True)
try:
if 'SH' in tmp_name:
stock_info = tmp_dict['sh' + tmp_name[:6]]
elif 'SZ' in tmp_name:
stock_info = tmp_dict['sz' + tmp_name[:6]]
else:
print(tmp_name)
except:
# 可能有一些停牌企业
continue
feature = get_feature(stock_info, df)
features.append(feature)
ts_codes.append(tmp_name)
# break
return features, ts_codes
quotation = easyquotation.use('tencent') # 新浪 ['sina'] 腾讯 ['tencent', 'qq']
tmp_dict = quotation.market_snapshot(prefix=True) # prefix 参数指定返回的行情字典中的股票代码 key 是否带 sz/sh 前缀
base_path = 'stock'
features, ts_codes = handle_history(base_path, tmp_dict)
up, down = count_limit(tmp_dict)