Python——量化分析介绍（八）

├── README
├── MyQuant_v1 #量化分析程序目录
   ├── __init__.py
   ├── data #数据处理目录
   │   ├── __init__.py

   │   ├── basic_crawler.py# 爬取股票基础信息存入MongoDB数据库.

   │   ├── data_crawler.py  #爬取指数、股票数据

   │   └── data_module.py  #从数据集中获取股票数据

   ├──util # 公用程序
   │   ├── __init__.py

   │   ├── stock_util.py#获取股票交易日期、前一交易日日期、股票代码

   │   └── database.py #链接数据库

   ├── backtest #回测
   │   ├── __init__.py

   │   └── _backtest_ #计划写一下回测走势图

   ├── factor #因子
   │   ├── __init__.py

   │   └── pe_factor.py#计算各股票的止盈率，用于后面的股票池策略

   ├── strategy #策略
   │   ├── __init__.py   │  

   └── _strategy_ #计划简单写个，主要用于回测
   ├── trading #交易
   │   ├── __init__.py

   │   └── _trading_ #不准备开发

   └── log #日志目录
          ├── __init__.py
          ├── backtest.log #不准备开发

           └── transactions.log#不准备开发

其中get_trading_date_before(date,days)是新加的，而get_all_codes(date)函数是进行了改进，更简洁明了。

#!/usr/bin/env python3.6
# -*- coding: utf-8 -*-
# @Time    : 2019-07-13 18:19
# @Author  : Ed Frey
# @File    : stock_util.py
# @Software: PyCharm

from pymongo import ASCENDING,DESCENDING
from util.database import DB_CONN
from datetime import datetime, timedelta

def get_trading_dates(begin_date=None, end_date=None):
    """
    to get the list of trading dates.
    if the begin_date is none, then get the date one year ago'
    :param begin_date: beginning date
    :param end_date: ending date
    :return: a trading dates' list
    """
    now = datetime.now()
    if begin_date is None:
        one_year_ago = now - timedelta(days=365)
        begin_date = one_year_ago.strftime('%Y-%m-%d')

    if end_date is None:
        end_date = now.strftime('%Y-%m-%d')

    daily_cursor = DB_CONN.daily.find(
        {'code': '000001', 'date': {'$gte': begin_date, '$lte': end_date}, 'index': True},
        sort=[('date', ASCENDING)],
        projection={'date': True, '_id': False})

    dates = [x['date'] for x in daily_cursor]

    return dates

def get_trading_date_before(date, days):
    '''
    to get the trading date before,if days==1,means getting the last trading date；if days == 2,means getting the last second trading date

    :param date:
    :param days:
    :return:
    '''
    count = days + 1
    daily_cursor = DB_CONN.daily.find(
        {'code': '000001', 'date': {'$lte': date}, 'index': True},
        sort=[('date', DESCENDING)],
        projection={'date': True, '_id': False},
        limit=count
    )

    dates = [daily['date'] for daily in daily_cursor]

    if len(dates) == count:
        return dates[days]

    return None

def get_all_codes(date=None):
    """
    to get the list of stocks.
    if there's no date, then get the last day's.
    if the last day is not a trading day(can't get any code), then get the next last day's, and then on.
    :param date: date
    :return: a list of stocks' codes
    """
    datetime_obj = datetime.now()
    if date is None:
        date = datetime_obj.strftime('%Y-%m-%d')
    if date not in get_trading_dates(date,date):
        date = get_trading_date_before(date, 1)

    codes = []
    code_cursor = DB_CONN.daily.find(
        {'date': date},
        projection={'code': True, '_id': False})

    codes = [x['code'] for x in code_cursor]

    return codes


if __name__ == "__main__":

    # dates = get_trading_dates(begin_date='2018-01-01', end_date='2019-07-28')
    # print(dates,flush=True)
    code = get_all_codes("2019-07-28")
    print(len(code),code,flush=True)

#!/usr/bin/env python3.6
# -*- coding: utf-8 -*-
# @Time    : 2019-08-04 09:51
# @Author  : Ed Frey
# @File    : data_module.py
# @Software: PyCharm
from util.database import DB_CONN
from datetime import datetime
from pandas import DataFrame

class DataModule:

    def __init__(self):
        pass
    def get_all_stock_k_data_at_date(self, autype=None, date=None):

        if date is None:
            date = datetime.now().strftime('%Y-%m-%d')

        if autype is None:
            collection = "daily"
        elif autype == 'qfq':
            collection = "qfq_daily"
        elif autype == 'hfq':
            collection = "hfq_daily"
        else:
            return []

        daily_cursor = DB_CONN[collection].find(
            {'date': date, 'index': False},
            projection={'_id': False, 'index': False})

        df_daily = DataFrame([daily for daily in daily_cursor])

        if df_daily.index.size > 0:
            df_daily.set_index(['code'], 1, inplace=True)

        return df_daily


    def get_stocks_at_date(self, codes=None, autype=None, date=None):

        if codes is None:
            return self.get_all_stock_k_data_at_date(
                autype=autype, date=date)

        if date is None:
            date = datetime.now().strftime('%Y-%m-%d')

        collection = 'daily' if autype is None or autype == '' else 'daily_' + autype

        daily_cursor = DB_CONN[collection].find(
            {'code': {'$in': codes}, 'date': date, 'index': False},
            projection={'_id': False, 'index': False})

        df_daily = DataFrame([daily for daily in daily_cursor])

        if df_daily.index.size > 0:
            df_daily.set_index(['code'], 1, inplace=True)

        return df_daily

if __name__ == '__main__':
    dm = DataModule()
    df_daily = dm.get_all_stock_k_data_at_date(date='2019-07-25')
    print(df_daily, flush=True)

运行结果这个样子：