Coverage for mlos_bench/mlos_bench/config/environments/apps/redis/scripts/local/process_redis_results.py: 38%

1#!/usr/bin/env python3 

2# 

3# Copyright (c) Microsoft Corporation. 

4# Licensed under the MIT License. 

5# 

6"""Script for post-processing redis-benchmark results.""" 

7 

8import argparse 

9 

10import pandas as pd 

11 

12 

13def _main(input_file: str, output_file: str) -> None: 

14 """Re-shape Redis benchmark CSV results from wide to long.""" 

15 df_wide = pd.read_csv(input_file) 

16 

17 # Format the results from wide to long 

18 # The target is columns of metric and value to act as key-value pairs. 

19 df_long = ( 

20 df_wide.melt(id_vars=["test"]) 

21 .assign(metric=lambda df: df["test"] + "_" + df["variable"]) 

22 .drop(columns=["test", "variable"]) 

23 .loc[:, ["metric", "value"]] 

24 ) 

25 

26 # Add a default `score` metric to the end of the dataframe. 

27 df_long = pd.concat( 

28 [ 

29 df_long, 

30 pd.DataFrame({"metric": ["score"], "value": [df_long.value[df_long.index.max()]]}), 

31 ] 

32 ) 

33 

34 df_long.to_csv(output_file, index=False) 

35 print(f"Converted: {input_file} -> {output_file}") 

36 # print(df_long) 

37 

38 

39if __name__ == "__main__": 

40 parser = argparse.ArgumentParser(description="Post-process Redis benchmark results.") 

41 parser.add_argument( 

42 "input", 

43 help="Redis benchmark results (downloaded from a remote VM).", 

44 ) 

45 parser.add_argument( 

46 "output", 

47 help="Converted Redis benchmark data (to be consumed by OS Autotune framework).", 

48 ) 

49 args = parser.parse_args() 

50 _main(args.input, args.output)