Import of the watch repository from Pebble

tools/analyze_pdebug_dat.py

@@ -0,0 +1,120 @@
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# This file can be used to process output from waf's extra tool parallel_debug.py that enables
+# the profiling of tasks in a waf build.
+#
+# To use this!
+# * Grab the parallel_debug.py file from the waf repo and throw it in your waftools directory
+#   https://raw.githubusercontent.com/waf-project/waf/master/waflib/extras/parallel_debug.py
+# * Add "conf.load('parallel_debug', tooldir='waftools')" to the top of def configure in the
+#   root wscript
+# * Run your build! This should produce a pdebug.data and pdebug.svg in your root
+# * Run this script with the current directory being the root of your repo
+#
+# Output will look something like the following:
+# c                                                             5326  44.79%  251.37s   0.05s
+# .pbi                                                          2496  40.42%  226.83s   0.09s
+# run_test                                                       434  08.29%   46.55s   0.11s
+# clar_main.c,clar.h                                             434  03.68%   20.63s   0.05s
+# cprogram                                                       436  02.56%   14.39s   0.03s
+# .png                                                            40  00.14%    0.79s   0.02s
+# .pdc                                                            16  00.03%    0.18s   0.01s
+# python -m unittest discover -s /Users/brad/pebble/tintin/t       2  00.03%    0.16s   0.08s
+# .apng                                                            8  00.02%    0.13s   0.02s
+# .c                                                              68  00.02%    0.09s   0.00s
+# pbi2png.py                                                       2  00.01%    0.07s   0.03s
+# cstlib                                                           2  00.01%    0.06s   0.03s
+#
+# Columns are task name, count, total percentage, total time, average time per task
+
+tasks_by_thread = {}
+
+
+class Task(object):
+    pass
+
+# process all lines
+with open('pdebug.dat') as f:
+    import csv
+    reader = csv.reader(f, delimiter=' ')
+    for row in reader:
+        t = Task()
+        t.thread_id = int(row[0])
+        t.task_id = int(row[1])
+        t.start_time = float(row[2])
+        t.task_name = row[3]
+
+        if t.task_name.startswith("'"):
+            t.task_name = t.task_name[1:]
+        if t.task_name.endswith("'"):
+            t.task_name = t.task_name[:-1]
+
+        thread_tasks = tasks_by_thread.setdefault(t.thread_id, [])
+        thread_tasks.append(t)
+
+# assign durations
+for thread_tasks in tasks_by_thread.values():
+    for i in xrange(len(thread_tasks) - 1):
+        thread_tasks[i].duration = thread_tasks[i+1].start_time - thread_tasks[i].start_time
+
+    # Can't guess the duration for the final task because the values only have start times :(
+    thread_tasks[-1].duration = 0
+
+# Flatten the dict into a big list
+all_tasks = [item for sublist in tasks_by_thread.values() for item in sublist]
+
+tasks_by_task_type = {}
+for t in all_tasks:
+    task_type_name = t.task_name
+
+    if task_type_name.endswith('.pbi'):
+        task_type_name = '.pbi'
+    elif task_type_name.endswith('.png'):
+        task_type_name = '.png'
+    elif task_type_name.endswith('.apng'):
+        task_type_name = '.apng'
+    elif task_type_name.endswith('.pdc'):
+        task_type_name = '.pdc'
+    elif task_type_name.endswith('.c'):
+        task_type_name = '.c'
+
+    task_type_tasks = tasks_by_task_type.setdefault(task_type_name, [])
+    task_type_tasks.append(t)
+
+
+class TaskType(object):
+    pass
+
+task_types = []
+total_duration = 0.0
+for task_type_name, tasks in tasks_by_task_type.items():
+    tt = TaskType()
+
+    tt.name = task_type_name
+    tt.total_duration = reduce(lambda accumulated, x: accumulated + x.duration, tasks, 0.0)
+    tt.average_duration = tt.total_duration / len(tasks)
+    tt.count = len(tasks)
+
+    task_types.append(tt)
+
+    total_duration += tt.total_duration
+
+task_types.sort(key=lambda x: -x.total_duration)
+
+for tt in task_types:
+    percentage_of_total = (tt.total_duration / total_duration) * 100
+
+    print "%-60s %5u  %05.2f%% %7.2fs %6.2fs" % \
+        (tt.name[:58], tt.count, percentage_of_total, tt.total_duration, tt.average_duration)