While looking at #333, I hypothesized that upgrading Cython might solve the issue. It didn't. But upgrading should still happen at some point. This is my work in progress on that. The tests pass, but there are two main things missing: Problem (1): Starting with Cython 3, you can only do `except+` or `except +reraise_kj_exception` on `extern` functions coming from C++. (This makes sense, and the way things were declared in Pycapnp wasn't too good.) As a result, I had to remove a lot of these declaration. This results in some segmentation faults, because Cython no longer detects C++ exceptions and converts them to Python exceptions in some places. To solve this, all `extern` declarations in `.pxd` files have to be examined and `except +reraise_kj_exception` clauses need to be added to anything that might throw. Previously, this was done really inconsistently. The lazy solution would be to just add the clause everywhere, but I'm not sure what the performance implications are. Problem (2): The compilation output of `python setup.py build_ext --inplace` is now full of messages like these: ``` capnp/lib/capnp.cpp: In function ‘PyObject* __pyx_f_5capnp_3lib_5capnp_18_DynamicListReader__get(__pyx_obj_5capnp_3lib_5capnp__DynamicListReader*, int64_t, int)’: capnp/lib/capnp.cpp:4871:51: warning: moving a temporary object prevents copy elision [-Wpessimizing-move] 4871 | #define __PYX_STD_MOVE_IF_SUPPORTED(x) std::move(x) | ~~~~~~~~~^~~ capnp/lib/capnp.cpp:20944:59: note: in expansion of macro ‘__PYX_STD_MOVE_IF_SUPPORTED’ 20944 | __pyx_t_2 = __pyx_f_5capnp_3lib_5capnp_to_python_reader(__PYX_STD_MOVE_IF_SUPPORTED((( ::capnp::DynamicValue::Reader)__pyx_t_7)), __pyx_t_1); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 419, __pyx_L1_error) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ capnp/lib/capnp.cpp:4871:51: note: remove ‘std::move’ call 4871 | #define __PYX_STD_MOVE_IF_SUPPORTED(x) std::move(x) | ~~~~~~~~~^~~ capnp/lib/capnp.cpp:20944:59: note: in expansion of macro ‘__PYX_STD_MOVE_IF_SUPPORTED’ 20944 | __pyx_t_2 = __pyx_f_5capnp_3lib_5capnp_to_python_reader(__PYX_STD_MOVE_IF_SUPPORTED((( ::capnp::DynamicValue::Reader)__pyx_t_7)), __pyx_t_1); if (unlikely(!__pyx_t_2)) __PYX_ERR(0, 419, __pyx_L1_error) | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ ``` There are to many `move` calls inserted. I'm not sure if this is a Cython issue, or if we are somehow annotating things wrong. Might be worth asking the Cython people. I'm not planning on working on this further in the short term. If someone wants to take over on this, feel free.
pycapnp
Cap'n'proto Mailing List Documentation
Requirements
- C++14 supported compiler
- gcc 6.1+ (5+ may work)
- clang 6 (3.4+ may work)
- Visual Studio 2017+
- cmake (needed for bundled capnproto)
- ninja (macOS + Linux)
- Visual Studio 2017+
- capnproto-1.0 (>=0.8.0 will also work if linking to system libraries)
- Not necessary if using bundled capnproto
- Python development headers (i.e. Python.h)
- Distributables from python.org include these, however they are usually in a separate package on Linux distributions
32-bit Linux requires that capnproto be compiled with -fPIC. This is usually set correctly unless you are compiling canproto yourself. This is also called -DCMAKE_POSITION_INDEPENDENT_CODE=1 for cmake.
pycapnp has additional development dependencies, including cython and pytest. See requirements.txt for them all.
Building and installation
Install with pip install pycapnp. You can set the CC environment variable to control which compiler is used, ie CC=gcc-8.2 pip install pycapnp.
Or you can clone the repo like so:
git clone https://github.com/capnproto/pycapnp.git
cd pycapnp
pip install .
By default, the setup script will automatically use the locally installed Cap'n Proto. If Cap'n Proto is not installed, it will bundle and build the matching Cap'n Proto library.
To enforce bundling, the Cap'n Proto library:
pip install . -C force-bundled-libcapnp=True
If you wish to install using the latest upstream C++ Cap'n Proto:
pip install . \
-C force-bundled-libcapnp=True \
-C libcapnp-url="https://github.com/capnproto/capnproto/archive/master.tar.gz"
To enforce using the installed Cap'n Proto from the system:
pip install . -C force-system-libcapnp=True
The bundling system isn't that smart so it might be necessary to clean up the bundled build when changing versions:
python setup.py clean
Stub-file generation
While not directly supported by pycapnp, a tool has been created to help generate pycapnp stubfile to assist with development (this is very helpful if you're new to pypcapnp!). See #289 for more details.
Python Versions
Python 3.8+ is supported.
Development
Git flow has been abandoned, use master.
To test, use a pipenv (or install requirements.txt and run pytest manually).
pip install pipenv
pipenv install
pipenv run pytest
Binary Packages
Building a Python wheel distributiion
pip wheel .
Documentation/Example
There is some basic documentation here.
Make sure to look at the examples. The examples are generally kept up to date with the recommended usage of the library.
The examples directory has one example that shows off pycapnp quite nicely. Here it is, reproduced:
import os
import capnp
import addressbook_capnp
def writeAddressBook(file):
addresses = addressbook_capnp.AddressBook.new_message()
people = addresses.init('people', 2)
alice = people[0]
alice.id = 123
alice.name = 'Alice'
alice.email = 'alice@example.com'
alicePhones = alice.init('phones', 1)
alicePhones[0].number = "555-1212"
alicePhones[0].type = 'mobile'
alice.employment.school = "MIT"
bob = people[1]
bob.id = 456
bob.name = 'Bob'
bob.email = 'bob@example.com'
bobPhones = bob.init('phones', 2)
bobPhones[0].number = "555-4567"
bobPhones[0].type = 'home'
bobPhones[1].number = "555-7654"
bobPhones[1].type = 'work'
bob.employment.unemployed = None
addresses.write(file)
def printAddressBook(file):
addresses = addressbook_capnp.AddressBook.read(file)
for person in addresses.people:
print(person.name, ':', person.email)
for phone in person.phones:
print(phone.type, ':', phone.number)
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()
if __name__ == '__main__':
f = open('example', 'w')
writeAddressBook(f)
f = open('example', 'r')
printAddressBook(f)
Also, pycapnp has gained RPC features that include pipelining and a promise style API. Refer to the calculator example in the examples directory for a much better demonstration:
import asyncio
import capnp
import socket
import test_capability_capnp
class Server(test_capability_capnp.TestInterface.Server):
def __init__(self, val=1):
self.val = val
async def foo(self, i, j, **kwargs):
return str(i * 5 + self.val)
async def client(read_end):
client = capnp.TwoPartyClient(read_end)
cap = client.bootstrap()
cap = cap.cast_as(test_capability_capnp.TestInterface)
remote = cap.foo(i=5)
response = await remote
assert response.x == '125'
async def main():
client_end, server_end = socket.socketpair(socket.AF_UNIX)
# This is a toy example using socketpair.
# In real situations, you can use any socket.
client_end = await capnp.AsyncIoStream.create_connection(sock=client_end)
server_end = await capnp.AsyncIoStream.create_connection(sock=server_end)
_ = capnp.TwoPartyServer(server_end, bootstrap=Server(100))
await client(client_end)
if __name__ == '__main__':
asyncio.run(capnp.run(main()))