Quickstart¶
This assumes you already have the capnp library installed. If you don’t, please follow the instructions at Installation first.
In general, this library is a very light wrapping of the Cap’n Proto C++ library. You can refer to its docs for more advanced concepts, or just to get a basic idea of how the python library is structured.
Load a Cap’n Proto Schema¶
First you need to import the library:
import capnp
Then you can load the Cap’n Proto schema with:
import addressbook_capnp
This will look all through all the directories in your sys.path/PYTHONPATH, and try to find a file of the form ‘addressbook.capnp’. If you want to disable the import hook magic that import capnp adds, and load manually, here’s how:
capnp.remove_import_hook()
addressbook_capnp = capnp.load('addressbook.capnp')
For future reference, here is the Cap’n Proto schema. Also available in the github repository under examples/addressbook.capnp:
# addressbook.capnp
@0x934efea7f017fff0;
const qux :UInt32 = 123;
struct Person {
id @0 :UInt32;
name @1 :Text;
email @2 :Text;
phones @3 :List(PhoneNumber);
struct PhoneNumber {
number @0 :Text;
type @1 :Type;
enum Type {
mobile @0;
home @1;
work @2;
}
}
employment :union {
unemployed @4 :Void;
employer @5 :Text;
school @6 :Text;
selfEmployed @7 :Void;
# We assume that a person is only one of these.
}
}
struct AddressBook {
people @0 :List(Person);
}
Const values¶
Const values show up just as you’d expect under the loaded schema. For example:
print(addressbook_capnp.qux)
# 123
Build a message¶
Initialize a New Cap’n Proto Object¶
Now that you’ve imported your schema, you need to allocate an actual struct from that schema. In this case, we will allocate an AddressBook:
addresses = addressbook_capnp.AddressBook.new_message()
Notice that we used addressbook_capnp from the previous section: Load a Cap’n Proto Schema.
Also as a shortcut, you can pass keyword arguments to the new_message function, and those fields will be set in the new message:
person = addressbook_capnp.Person.new_message(name='alice')
# is equivalent to:
person = addressbook_capnp.Person.new_message()
person.name = 'alice'
List¶
Allocating a list inside of an object requires use of the init function:
people = addresses.init('people', 2)
For now, let’s grab the first element out of this list and assign it to a variable named alice:
alice = people[0]
Note
It is a very bad idea to call init more than once on a single field. Every call to init allocates new memory inside your Cap’n Proto message, and if you call it more than once, the previous memory is left as dead space in the message. See Tips and Best Practices for more details.
Primitive Types¶
For all primitive types, from the Cap’n Proto docs:
Boolean: Bool
Integers: Int8, Int16, Int32, Int64
Unsigned integers: UInt8, UInt16, UInt32, UInt64
Floating-point: Float32, Float64
Blobs: Text, Data
You can assign straight to the variable with the corresponding Python type. For Blobs, you use strings. Assignment happens just by using the . syntax on the object you contstructed above:
alice.id = 123
alice.name = 'Alice'
alice.email = 'alice@example.com'
Note
Text fields will behave differently depending on your version of Python. In Python 2.x, Text fields will expect and return a bytes string, while in Python 3.x, they will expect and return a unicode string. Data fields will always a return bytes string.
Enums¶
First we’ll allocate a length one list of phonenumbers for alice:
alicePhone = alice.init('phones', 1)[0]
Note that even though it was a length 1 list, it was still a list that was returned, and we extracted the first (and only) element with [0].
Enums are treated like strings, and you assign to them like they were a Text field:
alicePhone.type = 'mobile'
If you assign an invalid value to one, you will get a ValueError:
alicePhone.type = 'foo'
---------------------------------------------------------------------------
KjException Traceback (most recent call last)
...
AttributeError: capnp/schema.c++:566: failed: enum has no such enumerant; name = foo
Unions¶
For the most part, you just treat them like structs:
alice.employment.school = "MIT"
Now the school field is the active part of the union, and we’ve assigned ‘MIT’ to it. You can query which field is set in a union with which(), shown in Reading Unions
Also, one weird case is for Void types in Unions (and in general, but Void is really only used in Unions). For these, you will have to assign None to them:
bob.employment.unemployed = None
Note
One caveat for unions is having structs as union members. Let us assume employment.school was actually a struct with a field of type Text called name
alice.employment.school.name = “MIT” # Raises a KjException
The problem is that a struct within a union isn’t initialized automatically. You have to do the following:
school = alice.employment.init('school')
school.name = "MIT"
Note that this is similar to init for lists, but you don’t pass a size. Requiring the init makes it more clear that a memory allocation is occurring, and will hopefully make you mindful that you shouldn’t set more than 1 field inside of a union, else you risk a memory leak
Writing to a File¶
Once you’re done assigning to all the fields in a message, you can write it to a file like so:
with open('example.bin', 'wb') as f:
addresses.write(f)
There is also a write_packed function, that writes out the message more space-efficientally. If you use write_packed, make sure to use read_packed when reading the message.
Writing to a socket¶
Alternatively, you can write to a socket. This is useful if you want to send the message over the network or to another process. A full example of this is available on GitHub examples/async_socket_message_client.py.:
stream = await capnp.AsyncIoStream.create_connection(host="localhost", port=6000)
await addresses.write_async(stream)
Important
Writing to a socket is implemented using asyncio and requires a running event loop both for the python part (asyncio) and the C++ part (KJ). See RPC for more information.
Read a message¶
Reading from a file¶
Much like before, you will have to de-serialize the message from a file descriptor:
with open('example.bin', 'rb') as f:
addresses = addressbook_capnp.AddressBook.read(f)
Note that this very much needs to match the type you wrote out. In general, you will always be sending the same message types out over a given channel or you should wrap all your types in an unnamed union. Unnamed unions are defined in the .capnp file like so:
struct Message {
union {
person @0 :Person;
addressbook @1 :AddressBook;
}
}
Reading from a socket¶
The same as for writing, you can read from a socket. This is useful if you want to receive the message over the network or from another process. A full example of this is available on GitHub examples/async_socket_message_client.py.:
stream = await capnp.AsyncIoStream.create_connection(host="localhost", port=6000)
message = await addressbook_capnp.AddressBook.read_async(stream)
Important
Reading from a socket is implemented using asyncio and requires a running event loop both for the python part (asyncio) and the C++ part (KJ). See RPC for more information.
Reading Fields¶
Fields are very easy to read. You just use the . syntax as before. Lists behave just like normal Python lists:
for person in addresses.people:
print(person.name, ':', person.email)
for phone in person.phones:
print(phone.type, ':', phone.number)
Reading Unions¶
The only tricky one is unions, where you need to call .which() to determine the union type. The .which() call returns an enum, ie. a string, corresponding to the field name:
which = person.employment.which()
print(which)
if which == 'unemployed':
print('unemployed')
elif which == 'employer':
print('employer:', person.employment.employer)
elif which == 'school':
print('student at:', person.employment.school)
elif which == 'selfEmployed':
print('self employed')
print()
Serializing/Deserializing¶
Files¶
As shown in the examples above, there is file serialization with write():
addresses = addressbook_capnp.AddressBook.new_message()
...
with open('example.bin', 'wb') as f:
addresses.write(f)
And similarly for reading:
with open('example.bin', 'rb') as f:
addresses = addressbook_capnp.AddressBook.read(f)
There are packed versions as well:
with open('example.bin', 'wb') as f:
addresses.write_packed(f)
...
with open('example.bin', 'rb') as f:
addresses = addressbook_capnp.AddressBook.read_packed(f)
Multi-message files¶
The above methods only guaranteed to work if your file contains a single message. If you have more than 1 message serialized sequentially in your file, then you need to use these convenience functions:
addresses = addressbook_capnp.AddressBook.new_message()
...
with open('example.bin', 'wb') as f:
addresses.write(f)
addresses.write(f)
addresses.write(f) # write 3 messages
with open('example.bin', 'rb') as f:
for addresses in addressbook_capnp.AddressBook.read_multiple(f):
print(addresses)
There is also a packed version:
for addresses in addressbook_capnp.AddressBook.read_multiple_packed(f):
print addresses
Dictionaries¶
There is a convenience method for converting Cap’n Proto messages to a dictionary. This works for both Builder and Reader type messages:
alice.to_dict()
For the reverse, all you have to do is pass keyword arguments to the new_message constructor:
my_dict = {'name' : 'alice'}
alice = addressbook_capnp.Person.new_message(**my_dict)
# equivalent to: alice = addressbook_capnp.Person.new_message(name='alice')
It’s also worth noting, you can use python lists/dictionaries interchangably with their Cap’n Proto equivalent types:
book = addressbook_capnp.AddressBook.new_message(people=[{'name': 'Alice'}])
...
book = addressbook_capnp.AddressBook.new_message()
book.init('people', 1)
book.people[0] = {'name': 'Bob'}
Byte Strings/Buffers¶
There is serialization to a byte string available:
encoded_message = alice.to_bytes()
And a corresponding from_bytes function:
with addressbook_capnp.Person.from_bytes(encoded_message) as alice:
# something with alice
There are also packed versions:
alice2 = addressbook_capnp.Person.from_bytes_packed(alice.to_bytes_packed())
Byte Segments¶
Note
This feature is not supported in PyPy at the moment, pending investigation.
Cap’n Proto supports a serialization mode which minimizes object copies. In the C++ interface, capnp::MessageBuilder::getSegmentsForOutput() returns an array of pointers to segments of the message’s content without copying. capnp::SegmentArrayMessageReader performs the reverse operation, i.e., takes an array of pointers to segments and uses the underlying data, again without copying. This produces a different wire serialization format from to_bytes() serialization, which uses capnp::messageToFlatArray() and capnp::FlatArrayMessageReader (both of which use segments internally, but write them in an incompatible way).
For compatibility on the Python side, use the to_segments() and from_segments() functions:
segments = alice.to_segments()
This returns a list of segments, each a byte buffer. Each segment can be, e.g., turned into a ZeroMQ message frame. The list of segments can also be turned back into an object:
alice = addressbook_capnp.Person.from_segments(segments)
For more information, please refer to the following links:
Advice on minimizing copies from Cap’n Proto (from the author of Cap’n Proto)
Advice on using Cap’n Proto over ZeroMQ (from the author of Cap’n Proto)
Discussion about sending and reassembling Cap’n Proto message segments in C++ (from the Cap’n Proto mailing list; includes sample code)
RPC¶
Cap’n Proto has a rich RPC protocol. You should read the RPC specification as well as the C++ RPC documentation before using pycapnp’s RPC features. As with the serialization part of this library, the RPC component tries to be a very thin wrapper on top of the C++ API.
The examples below will be using calculator.capnp. Please refer to it to understand the interfaces that will be used.
Asyncio support was added to pycapnp in v1.0.0. Since v2.0.0, the usage of asyncio is mandatory for all RPC calls. This guarantees a more robust and flexible RPC implementation.
KJ Event Loop¶
Cap’n Proto uses the KJ event loop for its RPC implementation. Pycapnp handles all the required mapping between the asyncio event loop and the KJ event loop.
To ensure proper creation, usage, and cleanup of the KJ event loop, a context manager called capnp.kj_loop() is exposed by pycapnp . All RPC calls must be made within this context:
import capnp
import asyncio
async def main():
async with capnp.kj_loop():
# RPC calls here
asyncio.run(main())
To simplify the usage, the helper function:py:meth:capnp.run can execute a asyncio coroutine within the capnp.kj_loop() context manager:
import capnp
import asyncio
async def main():
# RPC calls here
asyncio.run(capnp.run(main()))
Client¶
Thanks to the integration into the asyncio library, most of the boiler plate code is handled by pycapnp directly. The only thing that needs to be done is to create a client object and bootstrap the server capability.
Starting a Client¶
The first step is to open a socket to the server. For now this needs to be done
through create_connection(). A thin wrapper around asyncio.get_running_loop().create_connection()
that adds all required Protocol handling:
async def main():
host = 'localhost'
port = '6000'
connection = await capnp.AsyncIoStream.create_connection(host=host, port=port)
asyncio.run(capnp.run(main()))
Note
create_connection() forwards all calls to the underlying asyncio create_connection function.
In the next step, this created connection can be passed to capnp.TwoPartyClient() to create the client object:
async def main():
host = 'localhost'
port = '6000'
connection = await capnp.AsyncIoStream.create_connection(host=host, port=port)
client = capnp.TwoPartyClient(connection)
## Bootstrap Here ##
asyncio.run(capnp.run(main()))
SSL/TLS Client¶
SSL/TLS setup effectively wraps the socket transport. You’ll need an SSL certificate, for this example, we’ll use a self-signed certificate. Since we wrap around the asyncio connection interface, the SSL/TLS setup is done through the ssl` parameter of create_connection():
async def main():
host = 'localhost'
port = '6000'
# Setup SSL context
ctx = ssl.create_default_context(ssl.Purpose.SERVER_AUTH, cafile=os.path.join(this_dir, "selfsigned.cert"))
connection = await capnp.AsyncIoStream.create_connection(host=host, port=port, ssl=ctx, family=socket.AF_INET)
client = capnp.TwoPartyClient(connection)
## Bootstrap Here ##
asyncio.run(capnp.run(main()))
Due to a bug in Python 3.8 asyncio client needs to be initialized in a slightly different way:
if __name__ == '__main__':
loop = asyncio.get_event_loop()
loop.run_until_complete(capnp.run(main(parse_args().host)))
Bootstrap¶
Before calling any methods you’ll need to bootstrap the Calculator interface:
calculator = client.bootstrap().cast_as(calculator_capnp.Calculator)
There’s two things worth noting here. First, we are asking for the server capability. Secondly, you see that we are casting the capability that we receive. This is because capabilities are intrinsically dynamic, and they hold no run time type information, so we need to pick what interface to interpret them as.
Calling methods¶
There are 2 ways to call RPC methods. First the more verbose request syntax:
request = calculator.evaluate_request()
request.expression.literal = 123
eval_promise = request.send()
This creates a request for the method named ‘evaluate’, sets expression.literal in that call’s parameters to 123, and then sends the request and returns a promise (all non-blocking).
The shorter syntax for calling methods is:
eval_promise = calculator.evaluate({"literal": 123})
The major shortcoming with this method is that expressing complex fields with many nested sub-structs can become very tedious.
The returned promise can be handled like any other asyncio promise:
result = await eval_promise()
Pipelining¶
If a method returns values that are themselves capabilites, then you can access these fields before awaiting the promise. Doing this is called pipelining, and it allows Cap’n Proto to chain the calls without a round-trip occurring to the server:
# evaluate returns `value` which is itself an interface.
# You can call a new method on `value` without having to call wait first
read_promise = eval_promise.value.read()
read_result = await read_promise # only 1 await call
Server¶
Starting a Server¶
Like the client, the server uses an asyncio server that can be created with create_server().
Note
create_server(), similar to create_connection(), forwards all arguments to the underlying asyncio create_connection function (with the exception of the first argument).
The first argument to create_server() must be a callback
used by the pycapnp protocol implementation. The callback parameter will be called
whenever a new connection is made. It receives a py:obj:AsyncIoStream instance as its
only argument. If the result of py:obj:callback is a coroutine, it will be scheduled as a
task. At minimum, the callback should create a capnp.TwoPartyServer for the
passed stream. capnp.TwoPartyServer also exposes a
on_disconnect() function, which can be used as a task to handle
the lifetime properly:
async def new_connection(stream):
await capnp.TwoPartyServer(stream, bootstrap=CalculatorImpl()).on_disconnect()
async def main():
host = 'localhost'
port = '6000'
server = await capnp.AsyncIoStream.create_server(new_connection, host, port)
async with server:
await server.serve_forever()
if __name__ == "__main__":
asyncio.run(capnp.run(main()))
Note
On systems that have both IPv4 and IPv6 addresses, IPv6 is often resolved first and needs to be handled separately. If you’re certain IPv6 won’t be used, you can remove it (you should also avoid localhost, and stick to something like 127.0.0.1). If you’re broadcasting in general, you’ll probably want to use 0.0.0.0 (IPv4) or ::/0 (IPv6).
SSL/TLS Server¶
Adding SSL/TLS support for a pycapnp asyncio server is fairly straight-forward. Just create an SSL context before starting the asyncio server:
async def new_connection(stream):
await capnp.TwoPartyServer(stream, bootstrap=CalculatorImpl()).on_disconnect()
async def main():
host = 'localhost'
port = '6000'
# Setup SSL context
ctx = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
ctx.load_cert_chain(
os.path.join(this_dir, "selfsigned.cert"),
os.path.join(this_dir, "selfsigned.key"),
)
server = await capnp.AsyncIoStream.create_server(
new_connection, host, port, ssl=ctx, family=socket.AF_INET
)
async with server:
await server.serve_forever()
if __name__ == "__main__":
asyncio.run(capnp.run(main()))
Implementing a Server¶
Here’s a part of how you would implement a Calculator server:
class CalculatorImpl(calculator_capnp.Calculator.Server):
"Implementation of the Calculator Cap'n Proto interface."
def evaluate(self, expression, _context, **kwargs):
return evaluate_impl(expression).then(lambda value: setattr(_context.results, 'value', ValueImpl(value)))
def defFunction_context(self, context):
params = context.params
context.results.func = FunctionImpl(params.paramCount, params.body)
def getOperator(self, op, **kwargs):
return OperatorImpl(op)
Some major things worth noting.
You must inherit from your_module_capnp.YourInterface.Server, but don’t worry about calling __super__ in your __init__
Method names of your class must either match the interface exactly, or have ‘_context’ appended to it
If your method name is exactly the same as the interface, then you will be passed all the arguments from the interface as keyword arguments, so your argument names must match the interface spec exactly. You will also receive a _context parameter which is equivalent to the C++ API’s Context. I highly recommend having **kwargs as well, so that even if your interface spec is upgraded and arguments were added, your server will still operate fine.
Returns work with a bit of magic as well. If you return a promise, then it will be handled the same as if you returned a promise from a server method in the C++ API. Otherwise, your return statement will be filled into the results struct following the ordering in your spec, for example:
# capability.capnp file interface TestInterface { foo @0 (i :UInt32, j :Bool) -> (x: Text, i:UInt32); } # python code class TestInterface(capability_capnp.TestInterface.Server): def foo(self, i, j, **kwargs): return str(j), i
If your method ends in _context, then you will only be passed a context parameter. You will have to access params and set results yourself manually. Returning promises still works as above, but you can’t return anything else from a method.
Full Examples¶
Full examples are available on github. There is also an example of a very simplistic RPC available in test_rpc.py.