Lasse Blaauwbroek 6d5ee1c6f2 Use cibuildwheel in ci (#309)
* Use cibuildwheel in ci

`cibuildwheel` is a system that automatically compiles and repairs wheels for
many python versions and architectures at once. This has some advantages vs the
old situation:
- Macosx wheels had inconsistent minimum versions ranging between 10.9 and
  11.0. I'm not sure why this happens, but for some users this means they have
  to build from source on macosx. With cibuildwheel, the build is
  consistent, with 10.9 as the minimum for x86 and 11.0 for arm64.
- Consolidation between the packaging tests and manylinux tests.
- Addition of musllinux targets and additional cross-compilation to ppc64le and
s390x.
- With cibuildwheel, new python versions should be automatically picked up.
- Separation of the sdist build and lint checks. There is not reason to run that
  many times.

All possible build targets succeed, except for ARM64 on Windows. The upstream
capnp build fails. I've disabled it.

The cross-compilation builds on linux are pretty slow. This could potentially be
sped up by separating the builds of manylinux and musllinux, but I'm not sure if
it's worth the extra complexity. (One can also contemplate disabling these
targets.)

Tests for macosx arm64 cannot be run (but also couldn't be run in the previous
system. This should be remedied once apple silicon becomes available on the CI.

I've also added some commented-out code that can automatically take care of
uploading a build to PyPi when a release is created. One might contemplate using this.

* Set CMAKE_OSX_ARCHITECTURES for arm64 and disable universal2
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pycapnp

Packaging Status manylinux2014 Status PyPI version

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-0.10 (>=0.7.0 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 .

If you wish to install using the latest upstream C++ Cap'n Proto:

pip install \
    --install-option "--libcapnp-url" \
    --install-option "https://github.com/capnproto/capnproto/archive/master.tar.gz" \
    --install-option "--force-bundled-libcapnp" .

To force bundled python:

pip install --install-option "--force-bundled-libcapnp" .

Slightly more prompt error messages using distutils rather than pip.

python setup.py install --force-bundled-libcapnp

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

Python Versions

Python 3.7+ 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 dumb binary distribution:

python setup.py bdist_dumb

Building a Python wheel distributiion:

python setup.py bdist_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 capnp
import socket

import test_capability_capnp


class Server(test_capability_capnp.TestInterface.Server):

    def __init__(self, val=1):
        self.val = val

    def foo(self, i, j, **kwargs):
        return str(i * 5 + self.val)


def server(write_end):
    server = capnp.TwoPartyServer(write_end, bootstrap=Server(100))


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 = remote.wait()

    assert response.x == '125'


if __name__ == '__main__':
    read_end, write_end = socket.socketpair(socket.AF_UNIX)
    # This is a toy example using socketpair.
    # In real situations, you can use any socket.

    server(write_end)
    client(read_end)
Description
fastest pycapnp on planet pending lang rewrite for minimal pytnon ™️
Readme 2.9 MiB
Languages
Cython 59.4%
Python 36.7%
Cap'n Proto 2%
C++ 1.8%
C 0.1%