Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Scale like a pro
Search
Python Porto
December 14, 2017
Programming
1
230
Scale like a pro
Distributed task processing with Python and Celery
Python Porto
December 14, 2017
Tweet
Share
More Decks by Python Porto
See All by Python Porto
Detecting phishing with Recurrent Neural Networks
pyporto
0
35
Quick and Robust API with Django Rest Framework
pyporto
1
330
Django as your data management framework
pyporto
1
1.1k
Can my computer make jokes
pyporto
0
99
Building a serverless cloud service
pyporto
0
48
Python Porto #10. Past, present and future
pyporto
0
78
Entertaining testing with pytest
pyporto
0
180
Joyful Python Web App development with Appier
pyporto
0
150
Other Decks in Programming
See All in Programming
rails statsで大解剖 🔍 “B/43流” のRailsの育て方を歴史とともに振り返ります
shoheimitani
2
950
php-conference-japan-2024
tasuku43
0
350
Scalaから始めるOpenFeature入門 / Scalaわいわい勉強会 #4
arthur1
1
340
nekko cloudにおけるProxmox VE利用事例
irumaru
3
440
CQRS+ES の力を使って効果を感じる / Feel the effects of using the power of CQRS+ES
seike460
PRO
0
150
命名をリントする
chiroruxx
1
430
PHPとAPI Platformで作る本格的なWeb APIアプリケーション(入門編) / phpcon 2024 Intro to API Platform
ttskch
0
290
fs2-io を試してたらバグを見つけて直した話
chencmd
0
240
Semantic Kernelのネイティブプラグインで知識拡張をしてみる
tomokusaba
0
180
生成AIでGitHubソースコード取得して仕様書を作成
shukob
0
500
ゆるやかにgolangci-lintのルールを強くする / Kyoto.go #56
utgwkk
2
420
「Chatwork」Android版アプリを 支える単体テストの現在
okuzawats
0
180
Featured
See All Featured
Java REST API Framework Comparison - PWX 2021
mraible
28
8.3k
Side Projects
sachag
452
42k
Sharpening the Axe: The Primacy of Toolmaking
bcantrill
38
1.9k
Designing on Purpose - Digital PM Summit 2013
jponch
116
7k
Product Roadmaps are Hard
iamctodd
PRO
49
11k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
229
52k
Building Applications with DynamoDB
mza
91
6.1k
Writing Fast Ruby
sferik
628
61k
The MySQL Ecosystem @ GitHub 2015
samlambert
250
12k
How To Stay Up To Date on Web Technology
chriscoyier
789
250k
Learning to Love Humans: Emotional Interface Design
aarron
274
40k
Building Flexible Design Systems
yeseniaperezcruz
327
38k
Transcript
Scale like a pro Distributed computing with message queues and
Python Roman Imankulov | Python Porto | December 2017
Source: https://blog.kissmetrics.com/wp-content/uploads/2011/04/loading-time.pdf
browser ./webserver.py request POST /obj/<id> obj.update()
browser ./webserver.py request POST /obj/<id> obj.update() update search indexes
browser ./webserver.py request POST /obj/<id> obj.update() update search indexes send
email “object updated” …
browser ./webserver.py request POST /obj/<id> obj.update() update search indexes update
business analytics send email “object updated” …
browser ./webserver.py request POST /obj/<id> obj.update() update search indexes update
business analytics send email “object updated” … response
None
browser ./webserver.py request POST /obj/<id> response obj.update() ./worker.py ./worker.py ./worker.py
update search indexes send email “object updated” update business analytics
Message queues
None
None
queue
frontends queue
frontends queue workers
frontends queue job 1 workers
frontends queue job 1 workers job 2
frontends queue job 1 workers job 2 job 3
frontends queue put() job 1 workers job 2 job 3
frontends queue put() job 1 workers job 2 job 3
frontends queue job 1 workers job 2 job 3
frontends queue job 1 workers put() job 2 job 3
frontends queue job 1 workers put() job 2 job 3
frontends queue job 1 workers job 2 job 3
frontends queue job 1 workers put() job 2 job 3
frontends queue job 1 workers put() job 2 job 3
frontends queue job 1 workers job 2 job 3
frontends queue job 1 get() workers job 2 job 3
frontends queue get() workers job 2 job 3 job 1
frontends queue workers job 2 job 3 job 1
frontends queue workers get() job 2 job 3 job 1
frontends queue workers get() job 3 job 1 job 2
frontends queue workers job 3 job 1 job 2
frontends queue workers job 3 job 2
frontends queue workers job 3 job 2 get()
frontends queue workers job 2 job 3 get()
frontends queue workers job 2 job 3
frontends queue workers
Queue in python
Multiprocessing
None
None
None
None
None
None
None
Celery The queue out of the box
None
None
None
None
None
Celery Workflows chains, groups and chords
Task signatures
Task signatures
Task signatures
Chains a(…) b(…) c(…)
Chains a(…) b(…) c(…)
Chains a(…) b(…) c(…)
a(…) b(…) c(…) Groups
a(…) b(…) c(…) Groups
a(…) b(…) c(…) Groups
Chords a(…) b(…) c(…) d(…)
Chords a(…) b(…) c(…) d(…)
Chords a(…) b(…) c(…) d(…)
Celery Extras out of the box
None
• Different backends
• Different backends • Different serializers
• Different backends • Different serializers • Callbacks / errbacks
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies • Time limits on task execution
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies • Time limits on task execution • Rate limits (N tasks per minute)
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies • Time limits on task execution • Rate limits (N tasks per minute) • Autoscaling
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies • Time limits on task execution • Rate limits (N tasks per minute) • Autoscaling • Multiple queues
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies • Time limits on task execution • Rate limits (N tasks per minute) • Autoscaling • Multiple queues • Introspection and statistics
• Different backends • Different serializers • Callbacks / errbacks
• Progress reports from tasks • Delayed tasks • Ignored results • Expiring results • Retry policies • Time limits on task execution • Rate limits (N tasks per minute) • Autoscaling • Multiple queues • Introspection and statistics • Periodic tasks and crontabs
None
facebook.com/pyporto