Curio - A Tutorial Introduction¶
Curio is a library for performing concurrent I/O using Python coroutines and the async/await syntax introduced in Python 3.5. Its programming model is based on existing system programming abstractions such as threads, sockets, files, locks, and queues. Under the hood, it’s based on a task model that provides for advanced handling of cancellation, interesting interactions between threads and processes, and much more. It’s fun.
This tutorial will take you through the basics of creating and managing tasks in curio as well as some useful debugging features.
A Small Taste¶
Curio allows you to write concurrent I/O handling code that looks a lot like threads. For example, here is a simple echo server:
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(1000)
if not data:
break
await client.sendall(data)
print('Connection closed')
if __name__ == '__main__':
run(echo_server, ('',25000))
This server can handle thousands of concurrent clients. It does not use threads. However, this example really doesn’t do Curio justice. In the rest of this tutorial, we’ll start with the basics and work our way back to this before jumping off the deep end into something more advanced.
Getting Started¶
Here is a simple curio hello world program–a task that prints a simple countdown as you wait for your kid to put their shoes on:
# hello.py
import curio
async def countdown(n):
while n > 0:
print('T-minus', n)
await curio.sleep(1)
n -= 1
if __name__ == '__main__':
curio.run(countdown, 10)
Run it and you’ll see a countdown. Yes, some jolly fun to be
sure. Curio is based around the idea of tasks. Tasks are
defined as coroutines using async functions. To make a task
execute, it must run inside the curio kernel. The run() function
starts the kernel with an initial task. The kernel runs until there
are no more tasks to complete.
Tasks¶
Let’s add a few more tasks into the mix:
# hello.py
import curio
async def countdown(n):
while n > 0:
print('T-minus', n)
await curio.sleep(1)
n -= 1
async def kid():
print('Building the Millenium Falcon in Minecraft')
await curio.sleep(1000)
async def parent():
kid_task = await curio.spawn(kid)
await curio.sleep(5)
print("Let's go")
count_task = await curio.spawn(countdown, 10)
await count_task.join()
print("We're leaving!")
await kid_task.join()
print('Leaving')
if __name__ == '__main__':
curio.run(parent)
This program illustrates the process of creating and joining with
tasks. Here, the parent() task uses the curio.spawn()
coroutine to launch a new child task. After sleeping briefly, it then
launches the countdown() task. The join() method is used to
wait for a task to finish. In this example, the parent first joins
with countdown() and then with kid() before trying to
leave. If you run this program, you’ll see it produce the following
output:
bash % python3 hello.py
Building the Millenium Falcon in Minecraft
Let's go
T-minus 10
T-minus 9
T-minus 8
T-minus 7
T-minus 6
T-minus 5
T-minus 4
T-minus 3
T-minus 2
T-minus 1
We're leaving!
.... hangs ....
At this point, the program appears hung. The child is busy for
the next 1000 seconds, the parent is blocked on join() and nothing
much seems to be happening–this is the mark of all good concurrent
programs (hanging that is). Change the last part of the program to
run the kernel with the monitor enabled:
...
if __name__ == '__main__':
curio.run(parent, with_monitor=True)
Run the program again. You’d really like to know what’s happening? Yes? Open up another terminal window and connect to the monitor as follows:
bash % python3 -m curio.monitor
Curio Monitor: 4 tasks running
Type help for commands
curio >
See what’s happening by typing ps:
curio > ps
Task State Cycles Timeout Sleep Task
------ ------------ ---------- ------- ------- --------------------------------------------------
1 FUTURE_WAIT 1 None None Monitor.monitor_task
2 READ_WAIT 1 None None Kernel._run_coro.<locals>._kernel_task
3 TASK_JOIN 3 None None parent
4 TIME_SLEEP 1 None 962.830 kid
curio >
In the monitor, you can see a list of the active tasks. You can see
that the parent is waiting to join and that the kid is sleeping.
Actually, you’d like to know more about what’s happening. You can get
the stack trace of any task using the where command:
curio > w 3
Stack for Task(id=3, name='parent', state='TASK_JOIN') (most recent call last):
File "hello.py", line 23, in parent
await kid_task.join()
curio > w 4
Stack for Task(id=4, name='kid', state='TIME_SLEEP') (most recent call last):
File "hello.py", line 12, in kid
await curio.sleep(1000)
curio >
Actually, that kid is just being super annoying. Let’s cancel their world:
curio > cancel 4
Cancelling task 4
*** Connection closed by remote host ***
This causes the whole program to die with a rather nasty traceback message like this:
Traceback (most recent call last):
File "/Users/beazley/Desktop/Projects/curio/curio/kernel.py", line 828, in _run_coro
trap = current._throw(current.next_exc)
File "/Users/beazley/Desktop/Projects/curio/curio/task.py", line 95, in _task_runner
return await coro
File "hello.py", line 12, in kid
await curio.sleep(1000)
File "/Users/beazley/Desktop/Projects/curio/curio/task.py", line 440, in sleep
return await _sleep(seconds, False)
File "/Users/beazley/Desktop/Projects/curio/curio/traps.py", line 80, in _sleep
return (yield (_trap_sleep, clock, absolute))
curio.errors.TaskCancelled: TaskCancelled
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "hello.py", line 27, in <module>
curio.run(parent, with_monitor=True, debug=())
File "/Users/beazley/Desktop/Projects/curio/curio/kernel.py", line 872, in run
return kernel.run(corofunc, *args, timeout=timeout)
File "/Users/beazley/Desktop/Projects/curio/curio/kernel.py", line 212, in run
raise ret_exc
File "/Users/beazley/Desktop/Projects/curio/curio/kernel.py", line 825, in _run_coro
trap = current._send(current.next_value)
File "/Users/beazley/Desktop/Projects/curio/curio/task.py", line 95, in _task_runner
return await coro
File "hello.py", line 23, in parent
await kid_task.join()
File "/Users/beazley/Desktop/Projects/curio/curio/task.py", line 108, in join
raise TaskError('Task crash') from self.next_exc
curio.errors.TaskError: Task crash
Not surprisingly, the parent sure didn’t like having their child
process abrubtly killed out of nowhere like that. The join()
method returned with a TaskError exception to indicate that some
kind of problem occurred in the child.
Debugging is an important feature of curio and by using the monitor, you see what’s happening as tasks run. You can find out where tasks are blocked and you can cancel any task that you want. However, it’s not necessary to do this in the monitor. Change the parent task to include a timeout and some debugging print statements like this:
async def parent():
kid_task = await curio.spawn(kid)
await curio.sleep(5)
print("Let's go")
count_task = await curio.spawn(countdown, 10)
await count_task.join()
print("We're leaving!")
try:
await curio.timeout_after(10, kid_task.join)
except curio.TaskTimeout:
print('Where are you???')
print(kid_task.traceback())
raise SystemExit()
print('Leaving!')
If you run this version, the parent will wait 10 seconds for the child
to join. If not, a debugging traceback for the child task is printed
and the program quits. Use the traceback() method to see a
traceback. Raising SystemExit() causes Curio to quit in the same
manner as normal Python programs.
The parent could also elect to forcefully cancel the child. Change the program so that it looks like this:
async def parent():
kid_task = await curio.spawn(kid)
await curio.sleep(5)
print("Let's go")
count_task = await curio.spawn(countdown, 10)
await count_task.join()
print("We're leaving!")
try:
await curio.timeout_after(10, kid_task.join)
except curio.TaskTimeout:
print('I warned you!')
await kid_task.cancel()
print('Leaving!')
Of course, all is not lost in the child. If desired, they can catch the cancellation request and cleanup. For example:
async def kid():
try:
print('Building the Millenium Falcon in Minecraft')
await curio.sleep(1000)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
Now your program should produce output like this:
bash % python3 hello.py
Building the Millenium Falcon in Minecraft
Let's go
T-minus 10
T-minus 9
T-minus 8
T-minus 7
T-minus 6
T-minus 5
T-minus 4
T-minus 3
T-minus 2
T-minus 1
We're leaving!
I warned you!
Fine. Saving my work.
Leaving!
By now, you have the basic gist of the curio task model. You can create tasks, join tasks, and cancel tasks. Even if a task appears to be blocked for a long time, it can be cancelled by another task or a timeout. You have a lot of control over the environment.
Task Groups¶
What kind of kid plays Minecraft alone? Of course, they’re going to invite
all of their school friends over. Change the kid() function like this:
async def friend(name):
print('Hi, my name is', name)
print('Playing Minecraft')
try:
await curio.sleep(1000)
except curio.CancelledError:
print(name, 'going home')
raise
async def kid():
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
await curio.sleep(1000)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
In this code, the kid creates a task group and spawns a collection of tasks into it. Now you’ve got a four-fold problem of tasks sitting around doing nothing useful. You’d think the parent might have a problem with a motley crew like this, but no. If you run the code again, you’ll get output like this:
Building the Millenium Falcon in Minecraft
Hi, my name is Max
Playing Minecraft
Hi, my name is Lillian
Playing Minecraft
Hi, my name is Thomas
Playing Minecraft
Let's go
T-minus 10
T-minus 9
T-minus 8
T-minus 7
T-minus 6
T-minus 5
T-minus 4
T-minus 3
T-minus 2
T-minus 1
We're leaving!
I warned you!
Fine. Saving my work.
Max going home
Lillian going home
Thomas going home
Leaving!
Carefully observe how all of those friends just magically went away. That’s
the defining feature of a TaskGroup. You can spawn tasks into a group and
they will either all complete or they’ll all get cancelled if any kind of error
occurs. Either way, none of those tasks are executing when control-flow leaves the
with-block. In this case, the cancellation of child() causes a cancellation
to propagate to all of those friend tasks who promptly leave. Again, problem solved.
Task Synchronization¶
Although threads are not used to implement curio, you still might have
to worry about task synchronization issues (e.g., if more than one
task is working with mutable state). For this purpose, curio provides
Event, Lock, Semaphore, and Condition objects. For
example, let’s introduce an event that makes the child wait for the
parent’s permission to start playing:
start_evt = curio.Event()
async def kid():
print('Can I play?')
await start_evt.wait()
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
await curio.sleep(1000)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
async def parent():
kid_task = await curio.spawn(kid)
await curio.sleep(5)
print('Yes, go play')
await start_evt.set()
await curio.sleep(5)
print("Let's go")
count_task = await curio.spawn(countdown, 10)
await count_task.join()
print("We're leaving!")
try:
await curio.timeout_after(10, kid_task.join)
except curio.TaskTimeout:
print('I warned you!')
await kid_task.cancel()
print('Leaving!')
All of the synchronization primitives work the same way that they do
in the threading module. The main difference is that all operations
must be prefaced by await. Thus, to set an event you use await
start_evt.set() and to wait for an event you use await
start_evt.wait().
All of the synchronization methods also support timeouts. So, if the kid wanted to be rather annoying, they could use a timeout to repeatedly nag like this:
async def kid():
while True:
try:
print('Can I play?')
await curio.timeout_after(1, start_evt.wait)
break
except curio.TaskTimeout:
print('Wha!?!')
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
await curio.sleep(1000)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
Signals¶
What kind of screen-time obsessed helicopter parent lets their child
and friends play Minecraft for a measly 5 seconds? Instead, let’s
have the parent allow the child to play as much as they want until a
Unix signal arrives, indicating that it’s time to go. Modify the code
to wait for Control-C or a SIGTERM using a SignalEvent like
this:
import signal
async def parent():
goodbye = curio.SignalEvent(signal.SIGINT, signal.SIGTERM)
kid_task = await curio.spawn(kid)
await curio.sleep(5)
print('Yes, go play')
await start_evt.set()
await goodbye.wait()
print("Let's go")
count_task = await curio.spawn(countdown, 10)
await count_task.join()
print("We're leaving!")
try:
await curio.timeout_after(10, kid_task.join)
except curio.TaskTimeout:
print('I warned you!')
await kid_task.cancel()
print('Leaving!')
If you run this program, you’ll get output like this:
Building the Millenium Falcon in Minecraft
Hi, my name is Max
Playing Minecraft
Hi, my name is Lillian
Playing Minecraft
Hi, my name is Thomas
Playing Minecraft
At this point, nothing is going to happen for awhile. The kids will play for the next 1000 seconds. However, if you press Control-C, you’ll see the program initiate it’s usual shutdown sequence:
^C (Control-C)
Let's go
T-minus 10
T-minus 9
T-minus 8
T-minus 7
T-minus 6
T-minus 5
T-minus 4
T-minus 3
T-minus 2
T-minus 1
We're leaving!
I warned you!
Fine. Saving my work.
Max going home
Lillian going home
Thomas going home
Leaving!
In either case, you’ll see the parent wake up, do the countdown and proceed to cancel the child. All the friends go home. Very good.
Signals are a weird affair though. Suppose that the parent discovers
that the house is on fire and wants to get the kids out of there fast. As
written, a SignalEvent captures the appropriate signal and sets
a sticky flag. If the same signal comes in again, nothing much happens.
In this code, the shutdown sequence would run to completion no matter
how many times you hit Control-C. Everyone dies. Sadness.
This problem is easily solved–just delete the event after you’re done with it. Like this:
async def parent():
goodbye = curio.SignalEvent(signal.SIGINT, signal.SIGTERM)
kid_task = await curio.spawn(kid)
await curio.sleep(5)
print('Yes, go play')
await start_evt.set()
await goodbye.wait()
del goodbye # Removes the Control-C handler
print("Let's go")
count_task = await curio.spawn(countdown, 10)
await count_task.join()
print("We're leaving!")
try:
await curio.timeout_after(10, kid_task.join)
except curio.TaskTimeout:
print('I warned you!')
await kid_task.cancel()
print('Leaving!')
Run the program again. Now, quickly hit Control-C twice in a row. Boom! Minecraft dies instantly and everyone hurries their way out of there. You’ll see the friends, the child, and the parent all making a hasty exit.
Number Crunching and Blocking Operations¶
Now, suppose for a moment that the kid has discovered that the shape of the Millenium Falcon is based on the Golden Ratio and that building it now requires computing a sum of larger and larger Fibonacci numbers using an exponential algorithm like this:
def fib(n):
if n < 2:
return 1
else:
return fib(n-1) + fib(n-2)
async def kid():
while True:
try:
print('Can I play?')
await curio.timeout_after(1, start_evt.wait)
break
except curio.TaskTimeout:
print('Wha!?!')
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
total = 0
for n in range(50):
total += fib(n)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
If you run this version, you’ll find that the entire kernel becomes unresponsive. For example, signals aren’t caught and there appears to be no way to get control back. The problem here is that the kid is hogging the CPU and never yields. Important lesson: curio DOES NOT provide preemptive scheduling. If a task decides to compute large Fibonacci numbers or mine bitcoins, everything will block until it’s done. Don’t do that.
If you’re trying to debug a situation like this, the good news is that you can still use the Curio monitor to find out what’s happening. For example, you could start a separate terminal window and type this:
bash % python3 -m curio.monitor
Curio Monitor: 7 tasks running
Type help for commands
curio > ps
Task State Cycles Timeout Sleep Task
------ ------------ ---------- ------- ------- --------------------------------------------------
1 FUTURE_WAIT 1 None None Monitor.monitor_task
2 READ_WAIT 1 None None Kernel._run_coro.<locals>._kernel_task
3 FUTURE_WAIT 2 None None parent
4 RUNNING 6 None None kid
5 READY 0 None None friend
6 READY 0 None None friend
7 READY 0 None None friend
curio > w 4
Stack for Task(id=4, name='kid', state='RUNNING') (most recent call last):
File "hello.py", line 44, in kid
total += fib(n)
curio > signal SIGKILL
*** Connection closed by remote host ***
bash %
The bad news is that if you want other tasks to run, you’ll have to
figure out some other way to carry out computationally intensive work.
If you know that the work might take awhile, you can have it execute
in a separate process. Change the code to use
curio.run_in_process() like this:
async def kid():
while True:
try:
print('Can I play?')
await curio.timeout_after(1, start_evt.wait)
break
except curio.TaskTimeout:
print('Wha!?!')
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
total = 0
for n in range(50):
total += await curio.run_in_process(fib, n)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
In this version, the kernel remains fully responsive because the CPU intensive work is being carried out in a subprocess. You should be able to run the monitor, send the signal, and see the shutdown occur as before.
The problem of blocking might also apply to operations involving
I/O. For example, suppose your kid starts hanging out with a bunch of
savvy 5th graders who are into microservices. Suddenly, the
kid() task morphs into something that’s making HTTP requests and
decoding JSON:
import requests
async def kid():
while True:
try:
print('Can I play?')
await curio.timeout_after(1, start_evt.wait)
break
except curio.TaskTimeout:
print('Wha!?!')
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
total = 0
for n in range(50):
r = requests.get(f'http://www.dabeaz.com/cgi-bin/fib.py?n={n}')
resp = r.json()
total += int(resp['value'])
except curio.CancelledError:
print('Fine. Saving my work.')
raise
That’s great except that the popular requests library knows
nothing of Curio and it blocks the internal event loop while waiting
for a response. This essential the same problem as before except
that requests.get() mainly spends its time waiting. For this,
you can use curio.run_in_thread() to offload work to a separate thread.
Modify the code like this:
import requests
async def kid():
while True:
try:
print('Can I play?')
await curio.timeout_after(1, start_evt.wait)
break
except curio.TaskTimeout:
print('Wha!?!')
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
total = 0
for n in range(50):
r = await curio.run_in_thread(requests.get,
f'http://www.dabeaz.com/cgi-bin/fib.py?n={n}')
resp = r.json()
total += int(resp['value'])
except curio.CancelledError:
print('Fine. Saving my work.')
raise
You’ll find that this version works. All of the tasks run, you can send signals, and it’s responsive.
Curiouser and Curiouser¶
Like actual kids, as much as you tell tasks to be responsible, you can
never be quite sure that they’re going to do the right thing in all
circumstances. The previous section on blocking operations illustrates
a problem that lurks in the shadows of any async program–-namely the
lack of task preemption and the risk of blocking the interval event
loop without even knowing it. Potentially any operation not involving
an explict await is suspect. However, it’s really up to you to
know more about the nature of what’s being done and to explicitly use
calls such as run_in_thread() or run_in_process() as
appropriate.
There is another approach however. Rewrite the fib() function and
kid() task as follows:
@curio.async_thread
def fib(n):
r = requests.get(f'http://www.dabeaz.com/cgi-bin/fib.py?n={n}')
resp = r.json()
return int(resp['value'])
async def kid():
while True:
try:
print('Can I play?')
await curio.timeout_after(1, start_evt.wait)
break
except curio.TaskTimeout:
print('Wha!?!')
print('Building the Millenium Falcon in Minecraft')
async with curio.TaskGroup() as f:
await f.spawn(friend, 'Max')
await f.spawn(friend, 'Lillian')
await f.spawn(friend, 'Thomas')
try:
total = 0
for n in range(50):
total += await fib(n)
except curio.CancelledError:
print('Fine. Saving my work.')
raise
In this code, the kid() task uses await fib() to call the
fib() function. It looks like you’re calling a coroutine, but in
reality, it’s launching a background thread and running the function
in that. Since it’s a separate thread, blocking operations aren’t
going to block the rest of Curio. In fact, you’ll find that the example
works the same as it did before.
Functions marked with @async_thread are also unusual in that they
can be called from normal synchronous code as well. For example, you could
launch an interactive interpreter and do this:
>>> fib(5)
8
>>>
In this case, there is no need to launch a background thread–the function simply runs as it normally would.
There’s more than meets the eye when it comes to Curio and threads. However, Curio provides a number of features for making coroutines and threads play nicely together. This is only a small taste.
A Simple Echo Server¶
Now that you’ve got the basics down, let’s look at some I/O. Perhaps the main use of Curio is in network programming. Here is a simple echo server written directly with sockets using curio:
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(1000)
if not data:
break
await client.sendall(data)
print('Connection closed')
if __name__ == '__main__':
run(echo_server, ('',25000))
Run this program and try connecting to it using a command such as nc
or telnet. You’ll see the program echoing back data to you. Open
up multiple connections and see that it handles multiple client
connections perfectly well:
bash % nc localhost 25000
Hello (you type)
Hello (response)
Is anyone there? (you type)
Is anyone there? (response)
^C
bash %
If you’ve written a similar program using sockets and threads, you’ll
find that this program looks nearly identical except for the use of
async and await. Any operation that involves I/O, blocking, or
the services of Curio is prefaced by await.
Carefully notice that we are using the module curio.socket instead
of the built-in socket module here. curio.socket
is a wrapper around the existing socket module. All
of the existing functionality of socket is available, but all of the
operations that might block have been replaced by coroutines and must be
preceded by an explicit await.
The use of an asynchronous context manager might be something new. For example, you’ll notice the code uses this:
async with sock:
...
Normally, a context manager takes care of closing a socket when you’re
done using it. The same thing happens here. However, because you’re
operating in an environment of cooperative multitasking, you should
use the asynchronous variant instead. As a general rule, all I/O
related operations in curio will use the async form.
A lot of the above code involving sockets is fairly repetitive. Instead
of writing the part that sets up the server, you can simplify the above example
using tcp_server() like this:
from curio import run, spawn, tcp_server
async def echo_client(client, addr):
print('Connection from', addr)
while True:
data = await client.recv(1000)
if not data:
break
await client.sendall(data)
print('Connection closed')
if __name__ == '__main__':
run(tcp_server, '', 25000, echo_client)
The tcp_server() coroutine takes care of a few low-level details
such as creating the server socket and binding it to an address. It
also takes care of properly closing the client socket so you no longer
need the extra async with client statement from before. Clients
are also launched into a proper task group so cancellation of the
server shuts everything down just like the kid’s friends in the
earlier example.
A Stream-Based Echo Server¶
In certain cases, it might be easier to work with a socket connection using a file-like stream interface. Here is an example:
from curio import run, spawn, tcp_server
async def echo_client(client, addr):
print('Connection from', addr)
s = client.as_stream()
while True:
data = await s.read(1000)
if not data:
break
await s.write(data)
print('Connection closed')
if __name__ == '__main__':
run(tcp_server, '', 25000, echo_client)
The socket.as_stream() method can be used to wrap the socket in a
file-like object for reading and writing. On this object, you would
now use standard file methods such as read(), readline(), and
write(). One feature of a stream is that you can easily read data
line-by-line using an async for statement like this:
from curio import run, spawn, tcp_server
async def echo_client(client, addr):
print('Connection from', addr)
s = client.as_stream()
async for line in s:
await s.write(line)
print('Connection closed')
if __name__ == '__main__':
run(tcp_server, '', 25000, echo_client)
This is potentially useful if you’re writing code to read HTTP headers or some similar task.
A Managed Echo Server¶
Let’s make a slightly more sophisticated echo server that responds to a Unix signal and gracefully restarts:
import signal
from curio import run, spawn, SignalQueue, CancelledError, tcp_server
from curio.socket import *
async def echo_client(client, addr):
print('Connection from', addr)
s = client.as_stream()
try:
async for line in s:
await s.write(line)
except CancelledError:
await s.write(b'SERVER IS GOING AWAY!\n')
raise
print('Connection closed')
async def main(host, port):
async with SignalQueue(signal.SIGHUP) as restart:
while True:
print('Starting the server')
serv_task = await spawn(tcp_server, host, port, echo_client)
await restart.get()
print('Server shutting down')
await serv_task.cancel()
if __name__ == '__main__':
run(main('', 25000))
In this code, the main() coroutine launches the server, but then
waits for the arrival of a SIGHUP signal. When received, it
cancels the server. Behinds the scenes, the server has spawned all children into
a task group, all active children also get cancelled and print a
“server is going away” message back to their clients. Just to be clear,
if there were a 1000 connected clients at the time the restart occurs,
the server would drop all 1000 clients at once and start fresh with no
active connections.
The use of a SignalQueue here is useful if you want to respond to
a signal more than once. Instead of merely setting a flag like an event,
each occurrence of a signal is queued. Use the get() method to get the
signals as they arrive.
Intertask Communication¶
If you have multiple tasks and want them to communicate, use a Queue.
For example, here’s a program that builds a little publish-subscribe service
out of a queue, a dispatcher task, and publish function:
from curio import run, TaskGroup, Queue, sleep
messages = Queue()
subscribers = set()
# Dispatch task that forwards incoming messages to subscribers
async def dispatcher():
async for msg in messages:
for q in list(subscribers):
await q.put(msg)
# Publish a message
async def publish(msg):
await messages.put(msg)
# A sample subscriber task
async def subscriber(name):
queue = Queue()
subscribers.add(queue)
try:
async for msg in queue:
print(name, 'got', msg)
finally:
subscribers.discard(queue)
# A sample producer task
async def producer():
for i in range(10):
await publish(i)
await sleep(0.1)
async def main():
async with TaskGroup() as g:
await g.spawn(dispatcher)
await g.spawn(subscriber, 'child1')
await g.spawn(subscriber, 'child2')
await g.spawn(subscriber, 'child3')
ptask = await g.spawn(producer)
await ptask.join()
await g.cancel_remaining()
if __name__ == '__main__':
run(main)
Curio provides the same synchronization primitives as found in the built-in
threading module. The same techniques used by threads can be used with
curio. All things equal though, prefer to use queues if you can.
A Chat Server¶
Let’s put more of our tools into practice and implement a chat server. This server combines a bit of network programming with the publish-subscribe system you just built. Here it is:
# chat.py
import signal
from curio import run, spawn, SignalQueue, TaskGroup, Queue, tcp_server, CancelledError
from curio.socket import *
messages = Queue()
subscribers = set()
async def dispatcher():
async for msg in messages:
for q in subscribers:
await q.put(msg)
async def publish(msg):
await messages.put(msg)
# Task that writes chat messages to clients
async def outgoing(client_stream):
queue = Queue()
try:
subscribers.add(queue)
async for name, msg in queue:
await client_stream.write(name + b':' + msg)
finally:
subscribers.discard(queue)
# Task that reads chat messages and publishes them
async def incoming(client_stream, name):
try:
async for line in client_stream:
await publish((name, line))
except CancelledError:
await client_stream.write(b'SERVER IS GOING AWAY!\n')
raise
# Supervisor task for each connection
async def chat_handler(client, addr):
print('Connection from', addr)
async with client:
client_stream = client.as_stream()
await client_stream.write(b'Your name: ')
name = (await client_stream.readline()).strip()
await publish((name, b'joined\n'))
async with TaskGroup(wait=any) as workers:
await workers.spawn(outgoing, client_stream)
await workers.spawn(incoming, client_stream, name)
await publish((name, b'has gone away\n'))
print('Connection closed')
async def chat_server(host, port):
async with TaskGroup() as g:
await g.spawn(dispatcher)
await g.spawn(tcp_server, host, port, chat_handler)
async def main(host, port):
async with SignalQueue(signal.SIGHUP) as restart:
while True:
print('Starting the server')
serv_task = await spawn(chat_server, host, port)
await restart.get()
print('Server shutting down')
await serv_task.cancel()
if __name__ == '__main__':
run(main('', 25000))
This code might take a bit to digest, but here are some important bits.
Each connection results into two tasks being spawned (incoming and
outgoing). The incoming task reads incoming lines and publishes
them. The outgoing task subscribes to the feed and sends outgoing
messages. The workers task group supervises these two tasks. If any
one of them terminates, the other task is cancelled right away.
The chat_server task launches both the dispatcher and a tcp_server
task and watches them. If cancelled, both of those tasks will be shut down.
This includes all active client connections (each of which will get a
“server is going away” message).
Spend some time to play with this code. Allow clients to come and go.
Send the server a SIGHUP and watch it drop all of its clients.
It’s neat.
Programming Advice¶
At this point, you should have enough of the core concepts to get going. Here are a few programming tips to keep in mind:
When writing code, think thread programming and synchronous code. Tasks execute like threads and would need to be synchronized in much the same way. However, unlike threads, tasks can only be preempted on statements that explicitly use
awaitorasync.Curio uses the same I/O abstractions that you would use in normal synchronous code (e.g., sockets, files, etc.). Methods have the same names and perform the same functions. However, all operations that potentially involve I/O or blocking will always be prefaced by an explicit
awaitkeyword.Be extra wary of any library calls that do not use an explicit
await. Although these calls will work, they could potentially block the kernel on I/O or long-running calculations. If you know that either of these are possible, consider the use of therun_in_process()orrun_in_thread()functions to execute the work.
Debugging Tips¶
A common programming mistake is to forget to use await. For example:
async def countdown(n):
while n > 0:
print('T-minus', n)
curio.sleep(5) # Missing await
n -= 1
This will usually result in a warning message:
example.py:8: RuntimeWarning: coroutine 'sleep' was never awaited
For debugging a program that is otherwise running, but you’re not exactly sure what it might be doing (perhaps it’s hung or deadlocked), consider the use of the curio monitor. For example:
import curio
...
run(..., with_monitor=True)
The monitor can show you the state of each task and you can get stack
traces. Remember that you enter the monitor by running python3 -m curio.monitor
in a separate window.
You can also turn on scheduler tracing with code like this:
from curio.debug import schedtrace
import logging
logging.basicConfig(level=logging.DEBUG)
run(..., debug=schedtrace)
This will write log information about the scheduling of tasks. If you want even more fine-grained information, you can enable trap tracing using this:
from curio.debug import traptrace
import logging
logging.basicConfig(level=logging.DEBUG)
run(..., debug=traptrace)
This will write a log of every low-level operation being performed by the kernel.
More Information¶
The official Github page at https://github.com/dabeaz/curio should be used for bug reports, pull requests, and other activities.
A reference manual can be found at https://curio.readthedocs.io/en/latest/reference.html.
A more detailed developer’s guide can be found at https://curio.readthedocs.io/en/latest/devel.html.
See the HowTo guide at https://curio.readthedocs.io/en/latest/howto.html for more tips and techniques.