Beispiel #1
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def save_day(paralleled=True):
    """多进程保存日线数据
    """
    QA_SU_save_index_day('tdx', paralleled=paralleled)
    QA_SU_save_etf_list('tdx')
    QA_SU_save_etf_day('tdx', paralleled=paralleled)
    QA_SU_save_index_list('tdx')
    QA_SU_save_stock_list('tdx')
    QA_SU_save_stock_block('tdx')
    QA_SU_save_stock_day('tdx', paralleled=paralleled)
    QA_SU_save_stock_xdxr('tdx')
Beispiel #2
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 def test_save_day(self):
     from QUANTAXIS.QACmd import QA_SU_save_stock_day, QA_SU_save_index_day, QA_SU_save_etf_day, \
         QA_SU_save_stock_xdxr, QA_SU_save_etf_list, QA_SU_save_index_list, QA_SU_save_stock_list, \
         QA_SU_save_stock_block
     QA_SU_save_stock_day('tdx', paralleled=True)
     QA_SU_save_stock_xdxr('tdx')
     QA_SU_save_index_day('tdx', paralleled=True)
     QA_SU_save_etf_list('tdx')
     QA_SU_save_etf_day('tdx', paralleled=True)
     QA_SU_save_index_list('tdx')
     QA_SU_save_stock_list('tdx')
     QA_SU_save_stock_block('tdx')
    def test_QA_save_stock_xdxr_with_delete(self):
        """测试多线程QA_SU_save_stock_xdxrk
        """
        #  删除部分数据(以startStr开头的股票)
        table = DATABASE.stock_xdxr
        startStr = "0000"
        codelist = QA.QA_fetch_stock_list().code.tolist()
        codelist = [i for i in codelist if i.startswith(startStr)]
        myquery = {"code": {"$regex": "^{}".format(startStr)}}
        x = table.delete_many(myquery)
        print(x.deleted_count, " documents deleted(记录被删除).")

        with self.assertRaises(Exception) as context:
            data1 = QA.QA_fetch_stock_xdxr(codelist[:10])
        self.assertTrue('not found' in str(context.exception.args),
                        "删除后,数据应为空")

        QA_SU_save_stock_xdxr('tdx', paralleled=True)
        print('start test_QA_SU_save_xdxr')
        data1 = QA.QA_fetch_stock_xdxr(codelist[:10])
        self.assertTrue(len(data1) > 0, "未保存数据")
        print("read from DB:", data1)
        print('end test_QA_SU_save_xdxr')
Beispiel #4
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def save_xdxr(parallele=True):
    # 使用mock多进程下载xdxr数据
    QA_SU_save_stock_xdxr('tdx')