When asyncio was first proposed, many people (not so much on python-ideas, where Guido first suggested it, but on external blogs) had the same reaction: Doing the core reactor loop in Python is going to be way too slow. Something based on libev, like gevent, is inherently going to be much faster.

Then, when Python 3.4 came out, people started benchmarking it. For example, this benchmark shows that handling 100000 redis connections, 50 at a time, sending 3-byte messages, takes 3.12 seconds in asyncio vs. 4.55 in gevent.

And yet, I still see people refusing to believe those benchmarks, or their own benchmarks that they run to prove them wrong.

So, why isn't it slow? Isn't Python really slow at looping? Isn't libev a tightly-optimized reactor core?

The problem is that, as is so common, people are focusing on optimizing the wrong part of the code.

Under the covers, gevent and asyncio do similar things:
  • Call a function like epoll or kqueue to wait on a whole mess of sockets and see which ones are ready for input or output.
  • For each of those sockets:
    • Read the data.
    • Look up a coroutine in some kind of map.
    • Resume that coroutine.
    • Execute the actual Python code in that coroutine up to the next yield from/implicit suspend point.
Now, which parts of that would you expect libev to be able to optimize? Iterating over hundreds of sockets may be orders of magnitude slower in Python, but it's such a tiny percentage of the total time spent that it can't possibly matter. Remember, for each socket in that loop, you're going to make an I/O-bound syscall, do a context switch, and then interpret a bunch of Python code. It's going to be one of those things that takes time, and there's no way to optimize any of them by rewriting some completely irrelevant piece of code in (even tightly optimized) C.

From my own unscientific tests, using Fantix's work-in-progress port of gevent to Python 3 vs. asyncio, there's rarely a significant difference in either direction. I more often see a difference between Python 2.7 and 3.4. If I need to deal with lots of Unicode text, 3.4 is much faster; if I don't actually need to deal with it as Unicode but 3.x makes it hard for me to avoid doing so, 2.7 is much faster; if neither of those is relevant, 3.4 is sometimes significantly faster but sometimes not noticeably so.

There are of course sometimes good reasons to use gevent instead of asyncio. If you've got a bunch of threaded code that you want to convert over to using coroutines, for example, gevent makes it trivial. But using gevent it because you're absolutely sure that asyncio must be slow because Python code is slow, that's silly.
0

Add a comment

Hybrid Programming
Hybrid Programming
5
Greenlets vs. explicit coroutines
Greenlets vs. explicit coroutines
6
ABCs: What are they good for?
ABCs: What are they good for?
1
A standard assembly format for Python bytecode
A standard assembly format for Python bytecode
6
Unified call syntax
Unified call syntax
8
Why heapq isn't a type
Why heapq isn't a type
1
Unpacked Bytecode
Unpacked Bytecode
3
Everything is dynamic
Everything is dynamic
1
Wordcode
Wordcode
1
For-each loops should define a new variable
For-each loops should define a new variable
4
Views instead of iterators
Views instead of iterators
2
How lookup _could_ work
How lookup _could_ work
2
How lookup works
How lookup works
7
How functions work
How functions work
2
Why you can't have exact decimal math
Why you can't have exact decimal math
2
Can you customize method resolution order?
Can you customize method resolution order?
1
Prototype inheritance is inheritance
Prototype inheritance is inheritance
1
Pattern matching again
Pattern matching again
The best collections library design?
The best collections library design?
1
Leaks into the Enclosing Scope
Leaks into the Enclosing Scope
2
Iterable Terminology
Iterable Terminology
8
Creating a new sequence type is easy
Creating a new sequence type is easy
2
Going faster with NumPy
Going faster with NumPy
2
Why isn't asyncio too slow?
Why isn't asyncio too slow?
Hacking Python without hacking Python
Hacking Python without hacking Python
1
How to detect a valid integer literal
How to detect a valid integer literal
2
Operator sectioning for Python
Operator sectioning for Python
1
If you don't like exceptions, you don't like Python
If you don't like exceptions, you don't like Python
2
Spam, spam, spam, gouda, spam, and tulips
Spam, spam, spam, gouda, spam, and tulips
And now for something completely stupid…
And now for something completely stupid…
How not to overuse lambda
How not to overuse lambda
1
Why following idioms matters
Why following idioms matters
1
Cloning generators
Cloning generators
5
What belongs in the stdlib?
What belongs in the stdlib?
3
Augmented Assignments (a += b)
Augmented Assignments (a += b)
11
Statements and Expressions
Statements and Expressions
3
An Abbreviated Table of binary64 Values
An Abbreviated Table of binary64 Values
1
IEEE Floats and Python
IEEE Floats and Python
Subtyping and Ducks
Subtyping and Ducks
1
Greenlets, threads, and processes
Greenlets, threads, and processes
6
Why don't you want getters and setters?
Why don't you want getters and setters?
8
The (Updated) Truth About Unicode in Python
The (Updated) Truth About Unicode in Python
1
How do I make a recursive function iterative?
How do I make a recursive function iterative?
1
Sockets and multiprocessing
Sockets and multiprocessing
Micro-optimization and Python
Micro-optimization and Python
3
Why does my 100MB file take 1GB of memory?
Why does my 100MB file take 1GB of memory?
1
How to edit a file in-place
How to edit a file in-place
ADTs for Python
ADTs for Python
5
A pattern-matching case statement for Python
A pattern-matching case statement for Python
2
How strongly typed is Python?
How strongly typed is Python?
How do comprehensions work?
How do comprehensions work?
1
Reverse dictionary lookup and more, on beyond z
Reverse dictionary lookup and more, on beyond z
2
How to handle exceptions
How to handle exceptions
2
Three ways to read files
Three ways to read files
2
Lazy Python lists
Lazy Python lists
2
Lazy cons lists
Lazy cons lists
1
Lazy tuple unpacking
Lazy tuple unpacking
3
Getting atomic writes right
Getting atomic writes right
Suites, scopes, and lifetimes
Suites, scopes, and lifetimes
1
Swift-style map and filter views
Swift-style map and filter views
1
Inline (bytecode) assembly
Inline (bytecode) assembly
Why Python (or any decent language) doesn't need blocks
Why Python (or any decent language) doesn't need blocks
18
SortedContainers
SortedContainers
1
Fixing lambda
Fixing lambda
2
Arguments and parameters, under the covers
Arguments and parameters, under the covers
pip, extension modules, and distro packages
pip, extension modules, and distro packages
Python doesn't have encapsulation?
Python doesn't have encapsulation?
3
Grouping into runs of adjacent values
Grouping into runs of adjacent values
dbm: not just for Unix
dbm: not just for Unix
How to use your self
How to use your self
1
Tkinter validation
Tkinter validation
7
What's the deal with ttk.Frame.__init__(self, parent)
What's the deal with ttk.Frame.__init__(self, parent)
1
Does Python pass by value, or by reference?
Does Python pass by value, or by reference?
9
"if not exists" definitions
"if not exists" definitions
repr + eval = bad idea
repr + eval = bad idea
1
Solving callbacks for Python GUIs
Solving callbacks for Python GUIs
Why your GUI app freezes
Why your GUI app freezes
21
Using python.org binary installations with Xcode 5
Using python.org binary installations with Xcode 5
defaultdict vs. setdefault
defaultdict vs. setdefault
1
Lazy restartable iteration
Lazy restartable iteration
2
Arguments and parameters
Arguments and parameters
3
How grouper works
How grouper works
1
Comprehensions vs. map
Comprehensions vs. map
2
Basic thread pools
Basic thread pools
Sorted collections in the stdlib
Sorted collections in the stdlib
4
Mac environment variables
Mac environment variables
Syntactic takewhile?
Syntactic takewhile?
4
Can you optimize list(genexp)
Can you optimize list(genexp)
MISRA-C and Python
MISRA-C and Python
1
How to split your program in two
How to split your program in two
How methods work
How methods work
3
readlines considered silly
readlines considered silly
6
Comprehensions for dummies
Comprehensions for dummies
Sockets are byte streams, not message streams
Sockets are byte streams, not message streams
9
Why you don't want to dynamically create variables
Why you don't want to dynamically create variables
7
Why eval/exec is bad
Why eval/exec is bad
Iterator Pipelines
Iterator Pipelines
2
Why are non-mutating algorithms simpler to write in Python?
Why are non-mutating algorithms simpler to write in Python?
2
Sticking with Apple's Python 2.7
Sticking with Apple's Python 2.7
Blog Archive
About Me
About Me
Loading
Dynamic Views theme. Powered by Blogger. Report Abuse.