trio
Trio provides a set of abstract base classes that define a standard interface for unidirectional and bidirectional byte streams.
Why is this useful? Because it lets you write generic protocol implementations that can work over arbitrary transports, and easily create complex transport configurations. Here's some examples:
trio.SocketStream
wraps a raw socket (like a TCP connection over the network), and converts it to the standard stream interface.trio.ssl.SSLStream
is a "stream adapter" that can take any object that implements thetrio.abc.Stream
interface, and convert it into an encrypted stream. In trio the standard way to speak SSL over the network is to wrap an~trio.ssl.SSLStream
around a~trio.SocketStream
.If you spawn a subprocess then you can get a
~trio.abc.SendStream
that lets you write to its stdin, and a~trio.abc.ReceiveStream
that lets you read from its stdout. If for some reason you wanted to speak SSL to a subprocess, you could use aStapledStream
to combine its stdin/stdout into a single bidirectional~trio.abc.Stream
, and then wrap that in an~trio.ssl.SSLStream
:ssl_context = trio.ssl.create_default_context() ssl_context.check_hostname = False s = SSLStream(StapledStream(process.stdin, process.stdout), ssl_context)
[Note: subprocess support is not implemented yet, but that's the plan. Unless it is implemented, and I forgot to remove this note.]
It sometimes happens that you want to connect to an HTTPS server, but you have to go through a web proxy... and the proxy also uses HTTPS. So you end up having to do SSL-on-top-of-SSL. In trio this is trivial – just wrap your first
~trio.ssl.SSLStream
in a second~trio.ssl.SSLStream
:# Get a raw SocketStream connection to the proxy: s0 = await open_tcp_stream("proxy", 443) # Set up SSL connection to proxy: s1 = SSLStream(s0, proxy_ssl_context, server_hostname="proxy") # Request a connection to the website await s1.send_all(b"CONNECT website:443 / HTTP/1.0\r\n") await check_CONNECT_response(s1) # Set up SSL connection to the real website. Notice that s1 is # already an SSLStream object, and here we're wrapping a second # SSLStream object around it. s2 = SSLStream(s1, website_ssl_context, server_hostname="website") # Make our request await s2.send_all("GET /index.html HTTP/1.0\r\n") ...
- The
trio.testing
module provides a set offlexible in-memory stream object implementations <testing-streams>
, so if you have a protocol implementation to test then you can can start two tasks, set up a virtual "socket" connecting them, and then do things like inject random-but-repeatable delays into the connection.
trio.abc
Abstract base class | Inherits from... | Adds these abstract methods... | And these concrete methods. | Example implementations |
---|---|---|---|---|
AsyncResource |
~AsyncResource.aclose |
__aenter__ , __aexit__ |
async-file-objects |
|
SendStream |
AsyncResource |
~SendStream.send_all , ~SendStream.wait_send_all_might_not_block |
~trio.testing.MemorySendStream |
|
ReceiveStream |
AsyncResource |
~ReceiveStream.receive_some |
~trio.testing.MemoryReceiveStream |
|
Stream |
SendStream , ReceiveStream |
~trio.ssl.SSLStream |
||
HalfCloseableStream |
Stream |
~HalfCloseableStream.send_eof |
~trio.SocketStream , ~trio.StapledStream |
|
Listener |
AsyncResource |
~Listener.accept |
~trio.SocketListener , ~trio.ssl.SSLListener |
trio.abc.AsyncResource
trio
aclose_forcefully
trio.abc
trio.abc.SendStream
trio.abc.ReceiveStream
trio.abc.Stream
trio.abc.HalfCloseableStream
trio
BrokenStreamError
trio.abc
trio.abc.Listener
trio
Trio currently provides a generic helper for writing servers that listen for connections using one or more ~trio.abc.Listener
s, and a generic utility class for working with streams. And if you want to test code that's written against the streams interface, you should also check out testing-streams
in trio.testing
.
serve_listeners
StapledStream
The high-level network interface is built on top of our stream abstraction.
open_tcp_stream
serve_tcp
open_ssl_over_tcp_stream
serve_ssl_over_tcp
open_unix_socket
SocketStream
SocketListener
open_tcp_listeners
open_ssl_over_tcp_listeners
trio.ssl
The trio.ssl
module implements SSL/TLS support for Trio, using the standard library ssl
module. It re-exports most of ssl
´s API, with the notable exception of ssl.SSLContext
, which has unsafe defaults; if you really want to use ssl.SSLContext
you can import it from ssl
, but normally you should create your contexts using trio.ssl.create_default_context <ssl.create_default_context>
.
Instead of using ssl.SSLContext.wrap_socket
, though, you create a SSLStream
:
SSLStream
And if you're implementing a server, you can use SSLListener
:
SSLListener
trio.socket
The trio.socket
module provides trio's basic low-level networking API. If you're doing ordinary things with stream-oriented connections over IPv4/IPv6/Unix domain sockets, then you probably want to stick to the high-level API described above. If you want to use UDP, or exotic address families like AF_BLUETOOTH
, or otherwise get direct access to all the quirky bits of your system's networking API, then you're in the right place.
Generally, the API exposed by trio.socket
mirrors that of the standard library socket
module. Most constants (like SOL_SOCKET
) and simple utilities (like ~socket.inet_aton
) are simply re-exported unchanged. But there are also some differences, which are described here.
First, Trio provides analogues to all the standard library functions that return socket objects; their interface is identical, except that they're modified to return trio socket objects instead:
socket
socketpair
fromfd
fromshare(data)
Like socket.fromshare
, but returns a trio socket object.
In addition, there is a new function to directly convert a standard library socket into a trio socket:
from_stdlib_socket
Unlike socket.socket
, trio.socket.socket
is a function, not a class; if you want to check whether an object is a trio socket, use isinstance(obj, trio.socket.SocketType)
.
For name lookup, Trio provides the standard functions, but with some changes:
getaddrinfo
getnameinfo
getprotobyname
Trio intentionally DOES NOT include some obsolete, redundant, or broken features:
~socket.gethostbyname
,~socket.gethostbyname_ex
,~socket.gethostbyaddr
: obsolete; use~socket.getaddrinfo
and~socket.getnameinfo
instead.~socket.getservbyport
: obsolete and buggy; instead, do:_, service_name = await getnameinfo((127.0.0.1, port), NI_NUMERICHOST))
~socket.getservbyname
: obsolete and buggy; instead, do:await getaddrinfo(None, service_name)
~socket.getfqdn
: obsolete; usegetaddrinfo
with theAI_CANONNAME
flag.~socket.getdefaulttimeout
,~socket.setdefaulttimeout
: instead, use trio's standard support forcancellation
.- On Windows,
SO_REUSEADDR
is not exported, because it's a trap: the name is the same as UnixSO_REUSEADDR
, but the semantics are different and extremely broken. In the very rare cases where you actually wantSO_REUSEADDR
on Windows, then it can still be accessed from the standard library'ssocket
module.
Note
trio.socket.SocketType
is an abstract class and cannot be instantiated directly; you get concrete socket objects by calling constructors like trio.socket.socket
. However, you can use it to check if an object is a Trio socket via isinstance(obj, trio.socket.SocketType)
.
Trio socket objects are overall very similar to the standard
library socket objects <python:socket-objects>
, with a few important differences:
First, and most obviously, everything is made "trio-style": blocking methods become async methods, and the following attributes are not supported:
~socket.socket.setblocking
: trio sockets always act like blocking sockets; if you need to read/write from multiple sockets at once, then create multiple tasks.~socket.socket.settimeout
: seecancellation
instead.~socket.socket.makefile
: Python's file-like API is synchronous, so it can't be implemented on top of an async socket.~socket.socket.sendall
: Could be supported, but you're better off using the higher-level~trio.SocketStream
, and specifically its~trio.SocketStream.send_all
method, which also does additional error checking.
In addition, the following methods are similar to the equivalents in socket.socket
, but have some trio-specific quirks:
connect
Connect the socket to a remote address.
Similar to socket.socket.connect
, except async.
Warning
Due to limitations of the underlying operating system APIs, it is not always possible to properly cancel a connection attempt once it has begun. If connect
is cancelled, and is unable to abort the connection attempt, then it will:
- forcibly close the socket to prevent accidental re-use
- raise
~trio.Cancelled
.
tl;dr: if connect
is cancelled then the socket is left in an unknown state – possibly open, and possibly closed. The only reasonable thing to do is to close it.
sendfile
We also keep track of an extra bit of state, because it turns out to be useful for trio.SocketStream
:
did_shutdown_SHUT_WR
This bool
attribute is True if you've called sock.shutdown(SHUT_WR)
or sock.shutdown(SHUT_RDWR)
, and False otherwise.
The following methods are identical to their equivalents in socket.socket
, except async, and the ones that take address arguments require pre-resolved addresses:
~socket.socket.accept
~socket.socket.recv
~socket.socket.recv_into
~socket.socket.recvfrom
~socket.socket.recvfrom_into
~socket.socket.recvmsg
(if available)~socket.socket.recvmsg_into
(if available)~socket.socket.send
~socket.socket.sendto
~socket.socket.sendmsg
(if available)
All methods and attributes not mentioned above are identical to their equivalents in socket.socket
:
~socket.socket.family
~socket.socket.type
~socket.socket.proto
~socket.socket.fileno
~socket.socket.listen
~socket.socket.getpeername
~socket.socket.getsockname
~socket.socket.close
~socket.socket.shutdown
~socket.socket.setsockopt
~socket.socket.getsockopt
~socket.socket.dup
~socket.socket.detach
~socket.socket.share
~socket.socket.set_inheritable
~socket.socket.get_inheritable
trio
Trio provides built-in facilities for performing asynchronous filesystem operations like reading or renaming a file. Generally, we recommend that you use these instead of Python's normal synchronous file APIs. But the tradeoffs here are somewhat subtle: sometimes people switch to async I/O, and then they're surprised and confused when they find it doesn't speed up their program. The next section explains the theory behind async file I/O, to help you better understand your code's behavior. Or, if you just want to get started, you can jump down to the API overview.
Many people expect that switching to from synchronous file I/O to async file I/O will always make their program faster. This is not true! If we just look at total throughput, then async file I/O might be faster, slower, or about the same, and it depends in a complicated way on things like your exact patterns of disk access, or how much RAM you have. The main motivation for async file I/O is not to improve throughput, but to reduce the frequency of latency glitches.
To understand why, you need to know two things.
First, right now no mainstream operating system offers a generic, reliable, native API for async file or filesystem operations, so we have to fake it by using threads (specifically, run_sync_in_worker_thread
). This is cheap but isn't free: on a typical PC, dispatching to a worker thread adds something like ~100 µs of overhead to each operation. ("µs" is pronounced "microseconds", and there are 1,000,000 µs in a second. Note that all the numbers here are going to be rough orders of magnitude to give you a sense of scale; if you need precise numbers for your environment, measure!)
And second, the cost of a disk operation is incredibly bimodal. Sometimes, the data you need is already cached in RAM, and then accessing it is very, very fast – calling io.FileIO
's read
method on a cached file takes on the order of ~1 µs. But when the data isn't cached, then accessing it is much, much slower: the average is ~100 µs for SSDs and ~10,000 µs for spinning disks, and if you look at tail latencies then for both types of storage you'll see cases where occasionally some operation will be 10x or 100x slower than average. And that's assuming your program is the only thing trying to use that disk – if you're on some oversold cloud VM fighting for I/O with other tenants then who knows what will happen. And some operations can require multiple disk accesses.
Putting these together: if your data is in RAM then it should be clear that using a thread is a terrible idea – if you add 100 µs of overhead to a 1 µs operation, then that's a 100x slowdown! On the other hand, if your data's on a spinning disk, then using a thread is great – instead of blocking the main thread and all tasks for 10,000 µs, we only block them for 100 µs and can spend the rest of that time running other tasks to get useful work done, which can effectively be a 100x speedup.
But here's the problem: for any individual I/O operation, there's no way to know in advance whether it's going to be one of the fast ones or one of the slow ones, so you can't pick and choose. When you switch to async file I/O, it makes all the fast operations slower, and all the slow operations faster. Is that a win? In terms of overall speed, it's hard to say: it depends what kind of disks you're using and your kernel's disk cache hit rate, which in turn depends on your file access patterns, how much spare RAM you have, the load on your service, ... all kinds of things. If the answer is important to you, then there's no substitute for measuring your code's actual behavior in your actual deployment environment. But what we can say is that async disk I/O makes performance much more predictable across a wider range of runtime conditions.
If you're not sure what to do, then we recommend that you use async disk I/O by default, because it makes your code more robust when conditions are bad, especially with regards to tail latencies; this improves the chances that what your users see matches what you saw in testing. Blocking the main thread stops all tasks from running for that time. 10,000 µs is 10 ms, and it doesn't take many 10 ms glitches to start adding up to real money; async disk I/O can help prevent those. Just don't expect it to be magic, and be aware of the tradeoffs.
If you want to perform general filesystem operations like creating and listing directories, renaming files, or checking file metadata – or if you just want a friendly way to work with filesystem paths – then you want trio.Path
. It's an asyncified replacement for the standard library's pathlib.Path
, and provides the same comprehensive set of operations.
For reading and writing to files and file-like objects, Trio also provides a mechanism for wrapping any synchronous file-like object into an asynchronous interface. If you have a trio.Path
object you can get one of these by calling its ~trio.Path.open
method; or if you know the file's name you can open it directly with trio.open_file
. Alternatively, if you already have an open file-like object, you can wrap it with trio.wrap_file
– one case where this is especially useful is to wrap io.BytesIO
or io.StringIO
when writing tests.
Path
open_file
wrap_file
Asynchronous file interface
Trio's asynchronous file objects have an interface that automatically adapts to the object being wrapped. Intuitively, you can mostly treat them like a regular file object
, except adding an await
in front of any of methods that do I/O. The definition of file object
is a little vague in Python though, so here are the details:
- Synchronous attributes/methods: if any of the following attributes or methods are present, then they're re-exported unchanged:
closed
,encoding
,errors
,fileno
,isatty
,newlines
,readable
,seekable
,writable
,buffer
,raw
,line_buffering
,closefd
,name
,mode
,getvalue
,getbuffer
. - Async methods: if any of the following methods are present, then they're re-exported as an async method:
flush
,read
,read1
,readall
,readinto
,readline
,readlines
,seek
,tell
,truncate
,write
,writelines
,readinto1
,peek
,detach
.
Special notes:
- Async file objects implement trio's
~trio.abc.AsyncResource
interface: you close them by calling~trio.abc.AsyncResource.aclose
instead ofclose
(!!), and they can be used as async context managers. Like all~trio.abc.AsyncResource.aclose
methods, theaclose
method on async file objects is guaranteed to close the file before returning, even if it is cancelled or otherwise raises an error. - Using the same async file object from multiple tasks simultaneously: because the async methods on async file objects are implemented using threads, it's only safe to call two of them at the same time from different tasks IF the underlying synchronous file object is thread-safe. You should consult the documentation for the object you're wrapping. For objects returned from
trio.open_file
ortrio.Path.open
, it depends on whether you open the file in binary mode or text mode: binary mode files are task-safe/thread-safe, text mode files are not. Async file objects can be used as async iterators to iterate over the lines of the file:
async with await trio.open_file(...) as f: async for line in f: print(line)
- The
detach
method, if present, returns an async file object.
This should include all the attributes exposed by classes in io
. But if you're wrapping an object that has other attributes that aren't on the list above, then you can access them via the .wrapped
attribute:
wrapped
The underlying synchronous file object.
trio
open_signal_receiver