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How to use print_tb method in Slash

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main.py

Source:main.py

...73        end = datetime(2016, 6, 12)74        df = web.DataReader("078930.KS", "yahoo", start, end)75        con = sqlite3.connect("./kospi.db")76        df.to_sql('078930', con, if_exists='replace')77        self.print_tb(" db is writed ", str(df))78        con.close()79    @clear_textbrowser_decorator80    def on_clicked_read_sql_test(self):81        con = sqlite3.connect("./kospi.db")82        readed_df = pd.read_sql("SELECT * FROM '078930'", con, index_col='Date')83        self.print_tb(" db is readed ", str(readed_df))84        con.close()85    @clear_textbrowser_decorator86    def on_clicked_stategy_1_btn(self):87        strategy1.strategy1(self)88    @clear_textbrowser_decorator89    def on_clicked_stategy_2_btn(self):90        strategy2.strategy2(self)91    @clear_textbrowser_decorator92    def on_clicked_stategy_3_btn(self):93        strategy3.strategy3(self)94    @clear_textbrowser_decorator95    def on_clicked_df_multiple_btn(self):96        a = pd.DataFrame([[1, 2], [3, np.nan, ], [5, 6]], columns=["a", "b"])97        b = pd.DataFrame([[1, 2], [3, 4, ], [5, 6]], columns=["a", "b"]) * 1098        self.print_tb("a is ", str(a))99        self.print_tb("b is ", str(b))100        self.print_tb("a*b ", str(a*b))101        a = pd.DataFrame([[1, 2], [3, np.nan, ], [5, 6]], columns=["a", "b"])102        b = pd.DataFrame([[1, 2, 3], [3, 4, 5], [5, 6, 7]], columns=["c", "b", "d"]) * 10103        self.print_tb(" new a is ", str(a))104        self.print_tb(" new b is ", str(b))105        self.print_tb(" a*b ", str(a*b))106        return_df = pd.DataFrame(107            [108                [np.nan, np.nan, 2],109                [3, np.nan, 3],110                [5, 6, np.nan],111            ],112            columns=["ì¼ì±", "íë", "SK"]113        )114        asset_on_df = pd.DataFrame(115            [116                [0, 1],117                [0, 1],118                [1, 0],119            ],120            columns=["ì¼ì±", "SK"]121        )122        return_df123        asset_on_df124    @clear_textbrowser_decorator125    def on_clicked_make_ana_data_btn(self):126        make_ana_data(self)127        """128        # using datareader129        # samsung_df = fdr.DataReader('005390', '2017-01-01', '2017-12-31')130        # self.print_tb("8", str(samsung_df))131        df_005930 = marcap_data('2021-01-21', code='005930')132        df_005930 = df_005930.assign(Amount=df_005930['Amount'].astype('int64'),133                                     Marcap=df_005930['Marcap'].astype('int64'))134        self.print_tb(" df_005930 ", str(df_005930))135        """136    @clear_textbrowser_decorator137    def on_clicked_load_data_btn(self):138        """139        ë°ì´í° ë¡ë140        """141        df = pd.read_csv("data/fin_statement_new.csv")142        self.print_tb("0", str(df))143        """144        ë°ì´í° ì ë¦¬145        """146        # ìì¥ì¼ ì´ ì ê±°147        df = df.drop(["ìì¥ì¼"], axis=1)148        # rename ì´149        df = df.rename(columns={150            "DPS(ë³´íµì£¼, íê¸+ì£¼ì, ì°ê°)": "DPS",151            "P/E(Adj., FY End)": "PER",152            "P/B(Adj., FY End)": "PBR",153            "P/S(Adj., FY End)": "PSR",154        })155        """156        ì ë ¬ ë° ë°ì´í° ë¶ì157        """158        # ëëë¡ ì ë ¬íê³  ì´ë¦ì´ ëª ê°ì¸ì§ ì¹´ì´í¸159        self.print_tb("1", str(df.groupby(['year'])['Name'].count()))160        # ì´ë¦ì¼ë¡ ì ë ¬íê³  ëª ëëì ììëì§ ì¹´ì´í¸161        self.print_tb("2", str(df.groupby(['Name'])['year'].count()))162        # code or nameì ì¤ë³µ ì²´í¹ ë°©ë²1163        self.print_tb("3", str(df.groupby(['year'])['Name'].nunique().equals(df.groupby(['year'])['Code'].nunique())))164        # code or nameì ì¤ë³µ ì²´í¹ ë°©ë²2165        self.print_tb("4", str(df.groupby(['year', 'Name'])['Code'].nunique()))166        self.print_tb("5", str(df.groupby(['year', 'Name'])['Code'].nunique().nunique()))167        # indexë¥¼ dfì yearë¡ íê³  / columnì dfì Name / ê°ì dfì ìì ì£¼ê°ë¡ ì¤ì 168        yearly_price_df = df.pivot(index="year", columns="Name", values="ìì ì£¼ê°")169        self.print_tb("6", str(yearly_price_df))170        # í í´ ììµë¥  êµ¬íê¸°171        yearly_rtn_df = yearly_price_df.pct_change(fill_method=None).shift(-1)172        self.print_tb("7", str(yearly_rtn_df))173        # ìì¥íì§ ì¢ëª© ì²ë¦¬174        self.print_tb("8", str(yearly_price_df['ADëª¨í°ì¤']))175        self.print_tb("9", str(yearly_price_df['ADëª¨í°ì¤'].pct_change(fill_method=None).shift(-1)))176        # self.load_data_btn.setDisabled(True)177    def print_tb(self, print_log_name="0",  msg=""):178        self.log_textBrowser.moveCursor(QtGui.QTextCursor.End)179        if print_log_name == "0":180            self.log_textBrowser.insertPlainText("\n" + msg)181        else:182            self.log_textBrowser.insertPlainText("***************" + print_log_name + " *************** : \n")183            self.log_textBrowser.insertPlainText("\n" + msg)184            self.log_textBrowser.insertPlainText("\n\n *************** " + print_log_name + " *************** - end : \n\n")185        QApplication.processEvents(QEventLoop.ExcludeUserInputEvents)186    def on_clicked_clear_tb_btn(self):187        self.log_textBrowser.clear()188app = QApplication(sys.argv)189mw = MainWindow()190mw.show()191app.exec_()

strategy1.py

Source:strategy1.py

...10    def start(self):11        """12        Load data13        """14        self.parent.print_tb(" origin df", str(self.df))15        """16        Filter17        """18        market_cap_quantile_series = self.df.groupby("year")['ìê°ì´ì¡'].quantile(.2)19        self.parent.print_tb(" ëëë³ ìê° ì´ì¡ íì 20%", str(market_cap_quantile_series))20        filtered_df = self.df.join(market_cap_quantile_series, on="year", how="left", rsuffix="20%_quantile")21        filtered_df = filtered_df[filtered_df['ìê°ì´ì¡'] <= filtered_df['ìê°ì´ì¡20%_quantile']]22        self.parent.print_tb(" ìê° ì´ì¡ íì 20%ë§ ë¨ê¸°ê³  íí°ë§", str(filtered_df))23        """24        Selector25        """26        # Selector - 127        filtered_df = filtered_df[filtered_df['PBR'] >= 0.2]28        self.parent.print_tb(" PBR 0.2 ì´ì íí°ë§", str(filtered_df))29        # Selector - 230        smallest_pbr_series = filtered_df.groupby("year")['PBR'].nsmallest(15)31        self.parent.print_tb(" ëëë³ íì 15ê° íí°ë§", str(smallest_pbr_series))32        # Selector - 333            # ìê° ì´ì¡ íì 20% + PBR 0.2 ì´ì + ëëë³ íì 15ê°ì indexë¥¼ ëê¸´ë¤34        selected_index = smallest_pbr_series.index.get_level_values(1)35        selector_df = filtered_df.loc[selected_index].pivot(36            index='year', columns="Name", values="PBR"37        )38        # íí°ë§ë ë°ì´í°ë pbrì´ ë¤ì´ê°ê³  ëë¨¸ì§ë nanê° ë¤ì´ê°ë¤39        self.parent.print_tb(" selector_df", str(selector_df))40        # pbrì´ ììê²½ì° ë§¤ìíë¤ê³  ê°ì í´ì 1ë¡ ì²ë¦¬ + pbrì´ 0ì¸ ë°ì´í°ë nanë¡ ì²ë¦¬41        asset_on_df = selector_df.notna().astype(int).replace(0, np.nan)42        self.parent.print_tb(" asset_on_df", str(asset_on_df))43        selected_return_df = self.yearly_rtn_df * asset_on_df44        rtn_series, cum_rtn_series = plothelper.get_return_series(selected_return_df)...

dtest.py

Source:dtest.py

...7    lumberjack()8except IndexError:9    exc_type, exc_value, exc_traceback = sys.exc_info()10    # print("*** print_tb:")11    # dtraceback.print_tb(exc_traceback, file=sys.stdout)12    print("*** print_tb verbose 1:")13    dtraceback.print_tb(exc_traceback, file=sys.stdout, verbosity=1)14    print("*** print_tb verbose 2:")15    dtraceback.print_tb(exc_traceback, file=sys.stdout, verbosity=2)...

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