59 lines
1.9 KiB
Python
59 lines
1.9 KiB
Python
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#!/usr/bin/env python3
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import pandas as pd
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def parse_block(lines, run_format, run_date):
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# Future reference: output benchmark results in a format
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# that doesn't require extra code to read
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return {
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'run_date': run_date,
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'run_format' : run_format,
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'protocol' : lines[0].split(' total')[0],
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'total_secs' : int(lines[0].split('=')[1][:-2]),
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'serialize_50_nanos' : int(lines[2].split('=')[1][:-3]),
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'serialize_99_nanos' : int(lines[3].split('=')[1][:-3]),
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'serialize_999_nanos' : int(lines[4].split('=')[1][:-3]),
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'deserialize_50_nanos' : int(lines[5].split('=')[1][:-3]),
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'deserialize_99_nanos' : int(lines[6].split('=')[1][:-3]),
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'deserialize_999_nanos' : int(lines[7].split('=')[1][:-3]),
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'serialize_total_nanos' : int(lines[8].split('=')[1][:-3]),
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'deserialize_total_nanos' : int(lines[9].split('=')[1][:-3]),
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}
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def main(filename: str, run_format: str):
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records = []
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run_count = 10
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with open(filename, 'r') as handle:
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lines = handle.readlines()
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for i in range(run_count):
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num_blocks = 4
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block_len = 12
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run_date = lines[i * num_blocks * block_len + i].split('_')[2]
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for block in range(num_blocks):
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lower_block = i * block_len * num_blocks + block * block_len + i + 1
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upper_block = i * block_len * num_blocks + block * block_len + block_len + i + 1
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inner_lines = lines[lower_block:upper_block]
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rec = parse_block(inner_lines, run_format, run_date)
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records.append(rec)
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return records
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if __name__ == '__main__':
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all_records = []
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runs = [
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('shootout_normal.txt', ''),
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('shootout_taskset.txt', ''),
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('shootout_nice.txt', '')
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]
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for fname, run_format in runs:
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for record in main(fname, run_format):
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all_records.append(record)
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pd.DataFrame.from_records(all_records).to_csv('shootout.csv')
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