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https://github.com/dabeaz/curio

Good Curio!
https://github.com/dabeaz/curio

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README 

        
Curio

=====



Curio is a coroutine-based library for concurrent Python systems

programming using async/await.  It provides standard programming

abstractions such as tasks, sockets, files, locks, and queues as

well as some advanced features such as support for structured

concurrency. It works on Unix and Windows and has zero dependencies.

You'll find it to be familiar, small, fast, and fun.



Important Notice: October 25, 2022

----------------------------------

The Curio project is no longer making package releases.  I'm more than

happy to accept bug reports and may continue to work on it from time

to time as the mood strikes.  If you want the absolute latest version, you

should vendor the source code from here. Curio has no dependencies

other than the Python standard library.  --Dave



Curio is Different

------------------

One of the most important ideas from software architecture is the

"separation of concerns."  This can take many forms such as utilizing

abstraction layers, object oriented programming, aspects, higher-order

functions, and so forth.  However, another effective form of it exists

in the idea of separating execution environments.  For example, "user

mode" versus "kernel mode" in operating systems.  This is the

underlying idea in Curio, but applied to "asynchronous" versus

"synchronous" execution.



A fundamental problem with asynchronous code is that it involves a

completely different evaluation model that doesn't compose well with

ordinary applications or with other approaches to concurrency such as

thread programing.  Although the addition of "async/await" to Python

helps clarify such code, "async" libraries still tend to be a confused

mess of functionality that mix asynchronous and synchronous

functionality together in the same environment--often bolting it all

together with an assortment of hacks that try to sort out all of

associated API confusion.



Curio strictly separates asynchronous code from synchronous code.

Specifically, *all* functionality related to the asynchronous

environment utilizes "async/await" features and syntax--without

exception.  Moreover, interactions between async and sync code is

carefully managed through a small set of simple mechanisms such as

events and queues.  As a result, Curio is small, fast, and

significantly easier to reason about.



A Simple Example

-----------------



Here is a concurrent TCP echo server directly implemented using sockets:



.. code:: python



    # echoserv.py

    

    from curio import run, spawn

    from curio.socket import *

    

    async def echo_server(address):

        sock = socket(AF_INET, SOCK_STREAM)

        sock.setsockopt(SOL_SOCKET, SO_REUSEADDR, 1)

        sock.bind(address)

        sock.listen(5)

        print('Server listening at', address)

        async with sock:

            while True:

                client, addr = await sock.accept()

                await spawn(echo_client, client, addr, daemon=True)

    

    async def echo_client(client, addr):

        print('Connection from', addr)

        async with client:

             while True:

                 data = await client.recv(100000)

                 if not data:

                     break

                 await client.sendall(data)

        print('Connection closed')



    if __name__ == '__main__':

        run(echo_server, ('',25000))



If you've done network programming with threads, it looks almost

identical. Moreover, it can handle thousands of clients even though no

threads are being used inside.



Core Features

-------------



Curio supports standard synchronization primitives (events, locks,

recursive locks, semaphores, and condition variables), queues,

subprocesses, as well as running tasks in threads and processes.  The

task model fully supports cancellation, task groups, timeouts,

monitoring, and other features critical to writing reliable code.



Read the `official documentation `_ for

more in-depth coverage.  The `tutorial

`_ is a good

starting point.  The `howto

`_ describes how to

carry out common programming tasks.



Talks Related to Curio

----------------------



Concepts related to Curio's design and general issues related to async

programming have been described by Curio's creator, `David Beazley `_, in

various conference talks and tutorials:



* `Build Your Own Async `_, Workshop talk by David Beazley at PyCon India, 2019.



* `The Other Async (Threads + Asyncio = Love) `_, Keynote talk by David Beazley at PyGotham, 2017.



* `Fear and Awaiting in Async `_, Keynote talk by David Beazley at PyOhio 2016.



* `Topics of Interest (Async) `_, Keynote talk by David Beazley at Python Brasil 2015.



* `Python Concurrency from the Ground Up (LIVE) `_, talk by David Beazley at PyCon 2015.



Questions and Answers

---------------------



**Q: What is the point of the Curio project?**



A: Curio is async programming, reimagined as something smaller, faster, and easier 

to reason about. It is meant to be both educational and practical.



**Q: Is Curio implemented using asyncio?**



A: No. Curio is a standalone library directly created from low-level I/O primitives.



**Q: Is Curio meant to be a clone of asyncio?**



A: No. Although Curio provides a significant amount of overlapping

functionality, the API is different.  Compatibility with other

libaries is not a goal.



**Q: Is Curio meant to be compatible with other async libraries?**



A: No. Curio is a stand-alone project that emphasizes a certain

software architecture based on separation of environments.  Other

libraries have largely ignored this concept, preferring to simply

provide variations on the existing approach found in asyncio.



**Q: Can Curio interoperate with other event loops?**



A: It depends on what you mean by the word "interoperate."  Curio's

preferred mechanism of communication with the external world is a

queue.  It is possible to communicate between Curio, threads, and

other event loops using queues.  



**Q: How fast is Curio?**



A: Curio's primary goal is to be an async library that is minimal and

understandable. Performance is not the primary concern.  That said, in

rough benchmarking of a simple echo server, Curio is more than twice

as fast as comparable code using coroutines in ``asyncio`` or

``trio``.  This was last measured on OS-X using Python 3.9.  Keep in

mind there is a lot more to overall application performance than the

performance of a simple echo server so your mileage might

vary. However, as a runtime environment, Curio doesn't introduce a lot of

extra overhead. See the ``examples/benchmark`` directory for various

testing programs.



**Q: What is the future of Curio?**



A: Curio should be viewed as a library of basic programming

primitives.  At this time, it is considered to be

feature-complete--meaning that it is not expected to sprout many new

capabilities.  It may be updated from time to time to fix bugs or

support new versions of Python.



**Q: Can I contribute?**



A: Curio is not a community-based project seeking developers

or maintainers.  However, having it work reliably is important. If you've

found a bug or have an idea for making it better, please 

file an `issue `_. 



Contributors

------------



The following people contributed ideas to early stages of the Curio project:

Brett Cannon, Nathaniel Smith, Alexander Zhukov, Laura Dickinson, and Sandeep Gupta.



Who

---

Curio is the creation of David Beazley (@dabeaz) who is also

responsible for its maintenance.  http://www.dabeaz.com



P.S.

----

If you want to learn more about concurrent programming more generally, you should

come take a `course `_!



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