improve printout

import pandas as pd

import argparse

import sys

import pathlib

# set positive threshold for "lower is better" metrics, negative for "higher is better"

def main(args):

    df_curr = pd.read_csv(args.csv_current, sep=";").sort_values(by="testcase")

    df_prev = pd.read_csv(args.csv_previous, sep=";").sort_values(by="testcase")

    df_curr = pd.read_csv(args.csv_current, sep=";")

    df_prev = pd.read_csv(args.csv_previous, sep=";")

    df_merged = pd.merge(df_curr, df_prev, on="testcase", suffixes=["-curr", "-prev"])

    # remove leading path from testcase names for better readability

    df_merged["testcase"] = [pathlib.Path(tc).name for tc in df_merged["testcase"]]

    pd.options.display.max_colwidth = 200

    regressions_found = False

    for col, thresh in COLS_2_THRESHOLDS.items():

        diff = df_curr[col] - df_prev[col]

        col_curr = f"{col}-curr"

        col_prev = f"{col}-prev"

        diff = df_merged[col_curr] - df_merged[col_prev]

        # invert sign of difference for "higher is better" metrics

        if thresh < 0:

        mask_worse = diff > thresh

        mask_better = diff < -thresh

        display_cols = ["testcase", col_curr, col_prev]

        if sum(mask_worse) > 0:

            regressions_found = True

            print(f"Testcases that got worse wrt to {col}:")

            print(df_curr[mask_worse]["testcase"])

            print(

                f"---------------Testcases that got worse wrt to {col}---------------"

            )

            print(df_merged[mask_worse][display_cols].reset_index(drop=True))

            print()

        if sum(mask_better) > 0:

            print(f"Testcases that got better wrt to {col}:")

            print(df_curr[mask_better]["testcase"])

            print(

                f"---------------Testcases that got better wrt to {col}---------------"

            )

            print(df_merged[mask_better][display_cols].reset_index(drop=True))

            print()

    return int(regressions_found)