Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Speaker Deck
PRO
Sign in
Sign up for free
Greenlet-based concurrency
Goran Peretin
July 03, 2013
Programming
2
420
Greenlet-based concurrency
Slides from EuroPython 2013 talk Greenlet-based concurrency.
Goran Peretin
July 03, 2013
Tweet
Share
More Decks by Goran Peretin
See All by Goran Peretin
Webcamp Zagreb 2013
gperetin
1
150
On Concurrency
gperetin
1
210
WebcampZG 2012
gperetin
1
270
Other Decks in Programming
See All in Programming
Modern Web Apps with Spring Boot, Angular & TypeScript
toedter
12
14k
SRE NEXT 2022: Sensible Incident Management for Software Startups
takanabe
1
200
Kotlin 最新動向2022 #tfcon #techfeed
ntaro
1
650
Improve Build Times in Less Time
zacsweers
6
2.7k
ebpfとWASMに思いを馳せる2022 / techfeed-conference-2022-ebpf-wasm-amsy810
masayaaoyama
0
300
Becoming an Android Librarian
skydoves
2
380
脱オブジェクト指向講座(5分LT資料)
kishida
8
10k
LOWYAの信頼性向上とNew Relic
kazumax55
4
290
よりUXに近いSLI・SLOの運用による可用性の再設計
kazumanagano
3
400
확장 가능한 테라폼 코드 관리 (Scalable Terraform Code Management)
posquit0
1
290
From Java 11 to 17 and beyond
josepaumard
0
280
코드 품질 1% 올리기
pluu
0
760
Featured
See All Featured
Web Components: a chance to create the future
zenorocha
303
40k
The Web Native Designer (August 2011)
paulrobertlloyd
74
1.9k
XXLCSS - How to scale CSS and keep your sanity
sugarenia
236
1M
Fireside Chat
paigeccino
11
1.2k
Building Better People: How to give real-time feedback that sticks.
wjessup
343
17k
Docker and Python
trallard
27
1.5k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
119
28k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
655
120k
The Art of Programming - Codeland 2020
erikaheidi
31
5.8k
Debugging Ruby Performance
tmm1
65
10k
Why You Should Never Use an ORM
jnunemaker
PRO
47
5.5k
A Tale of Four Properties
chriscoyier
149
20k
Transcript
Greenlet-based concurrency Goran Peretin @gperetin
Who am I? ✤ Freelancer ✤ Interested in concurrent, parallel
and distributed systems
What is this about? ✤ understand what <buzzword> is ✤
when should you use <buzzword> ✤ concurrency as execution model (as opposed to composition model)
There will be no... ✤ Turnkey solutions ✤ GIL ✤
Details
Buzzwords ahead!
✤ concurrent vs parallel execution ✤ cooperative vs preemptive multitasking
✤ CPU bound vs IO bound task ✤ thread-based vs event-based concurrency
Mandatory definitions
Parallel execution ✤ Simultaneous execution of multiple tasks ✤ Must
have multiple CPUs
Concurrent execution ✤ Executing multiple tasks in the same time
frame ✤ ... but not necessarily at the same time ✤ Doesn’t require multiple CPU cores
Why do we want concurrent execution? ✤ We need it
- more tasks than CPUs ✤ CPU is much faster than anything else
Thread-based concurrecy ✤ Executing multiple threads in the same time
frame ✤ OS scheduler decides which thread runs when
How OS scheduler switches tasks? ✤ When current thread does
IO operation ✤ When current thread used up it’s time slice
How OS scheduler switches tasks? ✤ When current thread does
IO operation ✤ When current thread used up it’s time slice Preemptive multitasking
None
Mandatory GIL slide ✤ Global Interpreter Lock ✤ One Python
interpreter can run just one thread at any point in time ✤ Only problem for CPU bound tasks
CPU bound vs IO bound ✤ CPU bound - time
to complete a task is determined by CPU speed ✤ calculating Fibonacci sequence, video processing... ✤ IO bound - does a lot of IO, eg. reading from disk, network requests... ✤ URL crawler, most web applications...
Python anyone? ✤ import threading ✤ Python threads - real
OS threads
Houston, we have a...
Problem? ✤ Lots of threads ✤ Thousands
Benchmarks!
Sample programs ✤ Prog 1: spawn some number of threads
- each sleeps 200ms ✤ Prog 2: spawn some number of threads - each sleeps 90s
Prog 1 ✤ Sleep 200ms # of threads 100 1K
10K 100K Time 207 ms 327 ms 2.55 s 25.42 s
Prog 2 ✤ Sleep 90s # of threads 100 1K
10K 100K RAM ~4.9 GB ~11.8 GB ~82GB ? (256GB)
... and more ✤ Number of threads is limited ✤
Preemptive multitasking
We need ✤ Fast to create ✤ Low memory footprint
✤ We decide when to switch
Green threads!
Green threads ✤ Not managed by OS ✤ 1:N with
OS threads ✤ User threads, light-weight processes
Greenlets ✤ “...more primitive notion of micro- thread with no
implicit scheduling; coroutines, in other words.” ✤ C extension
Greenlets ✤ Micro-thread ✤ No implicit scheduling ✤ Coroutines
Coroutine ✤ Function that can suspend it’s execution and then
later resume ✤ Can also be implemented in pure Python (PEP 342) ✤ Coroutines decide when they want to switch
Coroutine ✤ Function that can suspend it’s execution and then
later resume ✤ Can also be implemented in pure Python (PEP 342) ✤ Coroutines decide when they want to switch Cooperative multitasking
Cooperative multitasking ✤ Each task decides when to give others
a chance to run ✤ Ideal for I/O bound tasks ✤ Not so good for CPU bound tasks
Using greenlets ✤ We need something that will know which
greenlet should run next ✤ Our calls must not block ✤ We need something to notify us when our call is done
Using greenlets ✤ We need something that will know which
greenlet should run next ✤ Our calls must not block ✤ We need something to notify us when our call is done Scheduler
Using greenlets ✤ We need something that will know which
greenlet should run next ✤ Our calls must not block ✤ We need something to notify us when our call is done Scheduler Event loop
Event loop ✤ Listens for events from OS and notifies
your app ✤ Asynchronous
None
✤ Scheduler ✤ Event loop Greenlets + ...
Gevent
Gevent ✤ “...coroutine-based Python networking library that uses greenlet to
provide a high-level synchronous API on top of the libevent event loop.”
None
Prog 1 ✤ Sleep 200ms # of threads 100 1K
10K 100K Time 207 ms 327 ms 2.55 s 25.42 s # of Greenlets 100 1K 10K 100K Time 204 ms 223 ms 421 ms 3.06 s
Prog 2 ✤ Sleep 90s # of threads 100 1K
10K 100K RAM 4.9 GB 11.8 GB 82GB ? (256GB) # of Greenlets 100 1K 10K 100K Time 33 MB 41 MB 114 MB 858 MB
Gevent ✤ Monkey-patching ✤ Event loop
Disadvantages ✤ Monkey-patching ✤ Doesn’t work with C extensions ✤
Greenlet implementation details ✤ Hard to debug
Alternatives ✤ Twisted ✤ Tornado ✤ Callback based
PEP 3156 & Tulip ✤ Attempt to standardize event loop
API in Python ✤ Tulip is an implementation
Recap ✤ Concurrent execution helps with IO bound applications ✤
Use threads if it works for you ✤ Use async library if you have lots of connections
Thank you! ✤ Questions?
Resources ✤ http:/ /dabeaz.com/coroutines/Coroutines.pdf ✤ http:/ /www.gevent.org/ ✤ http:/ /greenlet.readthedocs.org/en/latest/