Some tips for profiling django

1. Profiling Django

2. 1. models = MyModel.object.all()
2. filtered = models.filter( size__lte=20 )
3. fronts = filtered[:9]
4. print(fronts[0].attribute)

3. • QuerySet lazy evaluation
• https://docs.djangoproject.com/es/1.9/ref/models/
querysets/

4. •
• profile

5. Profile
•
• Profile

6. view
• django-debug-toolbar
• django-debug-toolbar-line-profiler

9. Performance

10. silk
• view benchmark
• Query

13. Demo

14. Django Command

15. cProfile
python -m cProfile -o my-profile-data.out manage.py
cprofilev -f my-profile-data.out -a 0.0.0.0 -p 4000

17. •
• function.

18. line profiler
•

19. kernprof -l manage.py <Command>
python -m line_profiler manage.py.lprof

21. • db
• django orm orz…

22. code snippet
def store_conversion(post_back, conversion_type):
time_stamp = dateutil.parser.parse(post_back['at'])
nested_data = post_back['data']
if not nested_data:
return
try:
ConversionRecord.objects.create( time_stamp=time_stamp )
except IntegrityError:
pass

23. Profile
• Python Parse

25. 60

26. •

27. for index in range(1, piece+1):
r = update_metric_task(index,
total_count,
piece,
metrics_qs,
records)
jobs.append(r)
Query task

28. benchmark
• query set…

29. Reason
Pickling QuerySets¶
If you pickle a QuerySet,
this will force all the results to be loaded into memory prior to pickling.

30. • Query Set Task
• Task QuerySet

31. • bulk create
• call save method
•

32. • Unittest Sqlite
Process
• TEST_NAME, Sqlite lock
• postgres sql

33. • Profile
• Django ORM