diff options
Diffstat (limited to 'afdo_redaction/redact_profile.py')
| -rwxr-xr-x | afdo_redaction/redact_profile.py | 38 |
1 files changed, 22 insertions, 16 deletions
diff --git a/afdo_redaction/redact_profile.py b/afdo_redaction/redact_profile.py index 96375fee..02bae928 100755 --- a/afdo_redaction/redact_profile.py +++ b/afdo_redaction/redact_profile.py @@ -1,4 +1,4 @@ -#!/usr/bin/env python2 +#!/usr/bin/env python3 # -*- coding: utf-8 -*- # Copyright 2018 The Chromium OS Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be @@ -30,6 +30,7 @@ import collections import re import sys + def _count_samples(samples): """Count the total number of samples in a function.""" line_re = re.compile(r'^(\s*)\d+(?:\.\d+)?: (\d+)\s*$') @@ -132,7 +133,7 @@ def _read_textual_afdo_profile(stream): continue if line[0].isspace(): - assert function_line is not None, "sample exists outside of a function?" + assert function_line is not None, 'sample exists outside of a function?' samples.append(line) continue @@ -170,12 +171,13 @@ def dedup_records(profile_records, summary_file, max_repeats=100): counts[_normalize_samples(record.samples)].append(record) # Be sure that we didn't see any duplicate functions, since that's bad... - total_functions_recorded = sum(len(records) - for records in counts.itervalues()) + total_functions_recorded = sum(len(records) for records in counts.values()) - unique_function_names = set(record.function_line.split(':')[0] - for records in counts.itervalues() - for record in records) + unique_function_names = { + record.function_line.split(':')[0] + for records in counts.values() + for record in records + } assert len(unique_function_names) == total_functions_recorded, \ 'duplicate function names?' @@ -187,7 +189,7 @@ def dedup_records(profile_records, summary_file, max_repeats=100): num_samples_total = 0 num_top_samples_total = 0 - for normalized_samples, records in counts.iteritems(): + for normalized_samples, records in counts.items(): top_sample_count, all_sample_count = _count_samples(normalized_samples) top_sample_count *= len(records) all_sample_count *= len(records) @@ -205,11 +207,13 @@ def dedup_records(profile_records, summary_file, max_repeats=100): for record in records: yield record - print('Retained {:,}/{:,} functions'.format(num_kept, num_total), - file=summary_file) - print('Retained {:,}/{:,} samples, total'.format(num_samples_kept, - num_samples_total), - file=summary_file) + print( + 'Retained {:,}/{:,} functions'.format(num_kept, num_total), + file=summary_file) + print( + 'Retained {:,}/{:,} samples, total'.format(num_samples_kept, + num_samples_total), + file=summary_file) print('Retained {:,}/{:,} top-level samples' \ .format(num_top_samples_kept, num_top_samples_total), file=summary_file) @@ -220,15 +224,17 @@ def run(profile_input_file, summary_output_file, profile_output_file): # Sort this so we get deterministic output. AFDO doesn't care what order it's # in. - deduped = sorted(dedup_records(profile_records, summary_output_file), - key=lambda r: r.function_line) + deduped = sorted( + dedup_records(profile_records, summary_output_file), + key=lambda r: r.function_line) for function_line, samples in deduped: print(function_line, file=profile_output_file) print('\n'.join(samples), file=profile_output_file) def _main(): - run(profile_input_file=sys.stdin, summary_output_file=sys.stderr, + run(profile_input_file=sys.stdin, + summary_output_file=sys.stderr, profile_output_file=sys.stdout) |