Package golang provides Go-like features for Python:
- gpython is Python interpreter with support for lightweight threads.
- go spawns lightweight thread.
- chan and select provide channels with Go semantic.
- func allows to define methods separate from class.
- defer allows to schedule a cleanup from the main control flow.
- error and package errors provide error chaining.
- b and u provide way to make sure an object is either bytes or unicode.
- gimport allows to import python modules by full path in a Go workspace.
Package golang.pyx provides similar features for Cython/nogil.
Additional packages and utilities are also provided to close other gaps between Python/Cython and Go environments.
Contents
Command gpython provides Python interpreter that supports lightweight threads via tight integration with gevent. The standard library of GPython is API compatible with Python standard library, but inplace of OS threads lightweight coroutines are provided, and IO is internally organized via libuv/libev-based IO scheduler. Consequently programs can spawn lots of coroutines cheaply, and modules like time, socket, ssl, subprocess etc - all could be used from all coroutines simultaneously, and in the same blocking way as if every coroutine was a full OS thread. This gives ability to scale programs without changing concurrency model and existing code.
Additionally GPython sets UTF-8 to be default encoding always, and puts go, chan, select etc into builtin namespace.
Note
GPython is optional and the rest of Pygolang can be used from under standard Python too. However without gevent integration go spawns full - not lightweight - OS thread. GPython can be also used with threads - not gevent - runtime. Please see GPython options for details.
go spawns a coroutine, or thread if gevent was not activated. It is possible to exchange data in between either threads or coroutines via channels. chan creates a new channel with Go semantic - either synchronous or buffered. Use chan.recv, chan.send and chan.close for communication. nilchan stands for nil channel. select can be used to multiplex on several channels. For example:
ch1 = chan() # synchronous channel
ch2 = chan(3) # channel with buffer of size 3
def _():
ch1.send('a')
ch2.send('b')
go(_)
ch1.recv() # will give 'a'
ch2.recv_() # will give ('b', True)
ch2 = nilchan # rebind ch2 to nil channel
_, _rx = select(
ch1.recv, # 0
ch1.recv_, # 1
(ch1.send, obj), # 2
ch2.recv, # 3
default, # 4
)
if _ == 0:
# _rx is what was received from ch1
...
if _ == 1:
# _rx is (rx, ok) of what was received from ch1
...
if _ == 2:
# we know obj was sent to ch1
...
if _ == 3:
# this case will be never selected because
# send/recv on nil channel block forever.
...
if _ == 4:
# default case
...
By default chan creates new channel that can carry arbitrary Python objects. However type of channel elements can be specified via chan(dtype=X) - for example chan(dtype='C.int') creates new channel whose elements are C integers. chan.nil(X) creates typed nil channel. Cython/nogil API explains how channels with non-Python dtypes, besides in-Python usage, can be additionally used for interaction in between Python and nogil worlds.
func decorator allows to define methods separate from class.
For example:
@func(MyClass)
def my_method(self, ...):
...
will define MyClass.my_method().
func can be also used on just functions, for example:
@func
def my_function(...):
...
defer allows to schedule a cleanup to be executed when current function returns. It is similar to try/finally but does not force the cleanup part to be far away in the end. For example:
wc = wcfs.join(zurl) │ wc = wcfs.join(zurl)
defer(wc.close) │ try:
│ ...
... │ ...
... │ ...
... │ finally:
│ wc.close()
If deferred cleanup fails, previously unhandled exception, if any, won't be lost - it will be chained with (PEP 3134) and included into traceback dump even on Python2.
For completeness there is recover and panic that allow to program with Go-style error handling, for example:
def _():
r = recover()
if r is not None:
print("recovered. error was: %s" % (r,))
defer(_)
...
panic("aaa")
But recover and panic are probably of less utility since they can be practically natively modelled with try/except.
If defer is used, the function that uses it must be wrapped with @func decorator.
In concurrent systems operational stack generally differs from execution code flow, which makes code stack traces significantly less useful to understand an error. Pygolang provides support for error chaining that gives ability to build operational error stack and to inspect resulting errors:
error is error type that can be used by itself or subclassed. By providing .Unwrap() method, an error can optionally wrap another error this way forming an error chain. errors.Is reports whether an item in error chain matches target. fmt.Errorf provides handy way to build wrapping errors. For example:
e1 = error("problem")
e2 = fmt.Errorf("doing something for %s: %w", "joe", e1)
print(e2) # prints "doing something for joe: problem"
errors.Is(e2, e1) # gives True
# OpError is example class to represents an error of operation op(path).
class OpError(error):
def __init__(e, op, path, err):
e.op = op
e.path = path
e.err = err
# .Error() should be used to define what error's string is.
# it is automatically used by error to also provide both .__str__ and .__repr__.
def Error(e):
return "%s %s: %s" % (e.op, e.path, e.err)
# provided .Unwrap() indicates that this error is chained.
def Unwrap(e):
return e.err
mye = OpError("read", "file.txt", io.ErrUnexpectedEOF)
print(mye) # prints "read file.txt: unexpected EOF"
errors.Is(mye, io.EOF) # gives False
errors.Is(mye. io.ErrUnexpectedEOF) # gives True
Both wrapped and wrapping error can be of arbitrary Python type - not necessarily of error or its subclass.
error is also used to represent at Python level an error returned by Cython/nogil call (see Cython/nogil API) and preserves Cython/nogil error chain for inspection at Python level.
Pygolang error chaining integrates with Python error chaining and takes .__cause__ attribute into account for exception created via raise X from Y (PEP 3134).
b and u provide way to make sure an object is either bytes or unicode. b(obj) converts str/unicode/bytes obj to UTF-8 encoded bytestring, while u(obj) converts str/unicode/bytes obj to unicode string. For example:
b("привет мир") # -> gives bytes corresponding to UTF-8 encoding of "привет мир".
def f(s):
s = u(s) # make sure s is unicode, decoding as UTF-8(*) if it was bytes.
... # (*) but see below about lack of decode errors.
The conversion in both encoding and decoding never fails and never looses information: b(u(·)) and u(b(·)) are always identity for bytes and unicode correspondingly, even if bytes input is not valid UTF-8.
gimport provides way to import python modules by full path in a Go workspace.
For example
lonet = gimport('lab.nexedi.com/kirr/go123/xnet/lonet')
will import either
- lab.nexedi.com/kirr/go123/xnet/lonet.py, or
- lab.nexedi.com/kirr/go123/xnet/lonet/__init__.py
located in src/ under $GOPATH.
Cython package golang provides nogil API with goroutines, channels and other features that mirror corresponding Python package. Cython API is not only faster compared to Python version, but also, due to nogil property, allows to build concurrent systems without limitations imposed by Python's GIL. All that while still programming in Python-like language. Brief description of Cython/nogil API follows:
go spawns new task - a coroutine, or thread, depending on activated runtime. chan[T] represents a channel with Go semantic and elements of type T. Use makechan[T] to create new channel, and chan[T].recv, chan[T].send, chan[T].close for communication. nil stands for nil channel. select can be used to multiplex on several channels. For example:
cdef nogil:
struct Point:
int x
int y
void worker(chan[int] chi, chan[Point] chp):
chi.send(1)
cdef Point p
p.x = 3
p.y = 4
chp.send(p)
void myfunc():
cdef chan[int] chi = makechan[int]() # synchronous channel of integers
cdef chan[Point] chp = makechan[Point](3) # channel with buffer of size 3 and Point elements
go(worker, chi, chp)
i = chi.recv() # will give 1
p = chp.recv() # will give Point(3,4)
chp = nil # rebind chp to nil channel
cdef cbool ok
cdef int j = 33
_ = select([
chi.recvs(&i), # 0
chi.recvs(&i, &ok), # 1
chi.sends(&j), # 2
chp.recvs(&p), # 3
default, # 4
])
if _ == 0:
# i is what was received from chi
...
if _ == 1:
# (i, ok) is what was received from chi
...
if _ == 2:
# we know j was sent to chi
...
if _ == 3:
# this case will be never selected because
# send/recv on nil channel block forever.
...
if _ == 4:
# default case
...
Python channels are represented by pychan cdef class. Python channels that carry non-Python elements (pychan.dtype != DTYPE_PYOBJECT) can be converted to Cython/nogil chan[T] via pychan.chan_*(). Similarly Cython/nogil chan[T] can be wrapped into pychan via pychan.from_chan_*(). This provides interaction mechanism in between nogil and Python worlds. For example:
def myfunc(pychan pych):
if pych.dtype != DTYPE_INT:
raise TypeError("expected chan[int]")
cdef chan[int] ch = pych.chan_int() # pychan -> chan[int]
with nogil:
# use ch in nogil code. Both Python and nogil parts can
# send/receive on the channel simultaneously.
...
def mytick(): # -> pychan
cdef chan[int] ch
with nogil:
# create a channel that is connected to some nogil task of the program
ch = ...
# wrap the channel into pychan. Both Python and nogil parts can
# send/receive on the channel simultaneously.
cdef pychan pych = pychan.from_chan_int(ch) # pychan <- chan[int]
return pych
error is the interface that represents errors. errors.New and fmt.errorf provide way to build errors from text. An error can optionally wrap another error by implementing errorWrapper interface and providing .Unwrap() method. errors.Is reports whether an item in error chain matches target. fmt.errorf with %w specifier provide handy way to build wrapping errors. For example:
e1 = errors.New("problem")
e2 = fmt.errorf("doing something for %s: %w", "joe", e1)
e2.Error() # gives "doing something for joe: problem"
errors.Is(e2, e1) # gives True
An error can be exposed to Python via pyerror cdef class wrapper instantiated by pyerror.from_error(). pyerror preserves Cython/nogil error chain for inspection by Python-level error.Is.
panic stops normal execution of current goroutine by throwing a C-level exception. On Python/C boundaries C-level exceptions have to be converted to Python-level exceptions with topyexc. For example:
cdef void _do_something() nogil:
...
panic("bug") # hit a bug
# do_something is called by Python code - it is thus on Python/C boundary
cdef void do_something() nogil except +topyexc:
_do_something()
def pydo_something():
with nogil:
do_something()
See libgolang.h and golang.pxd for details of the API. See also testprog/golang_pyx_user/ for demo project that uses Pygolang in Cython/nogil mode.
The following additional packages and utilities are also provided to close gaps between Python/Cython and Go environments:
In addition to go and channels, the following packages are provided to help handle concurrency in structured ways:
- golang.context (py, pyx) provides contexts to propagate deadlines, cancellation and task-scoped values among spawned goroutines [*].
- golang.sync (py, pyx) provides sync.WorkGroup to spawn group of goroutines working on a common task. It also provides low-level primitives - for example sync.Once, sync.WaitGroup, sync.Mutex and sync.RWMutex - that are sometimes useful too.
- golang.time (py, pyx) provides timers integrated with channels.
| [*] | See Go Concurrency Patterns: Context for overview. |
qq (import from golang.gcompat) provides %q functionality that quotes as Go would do. For example the following code will print name quoted in " without escaping printable UTF-8 characters:
print('hello %s' % qq(name))
qq accepts both str and bytes (unicode and str on Python2) and also any other type that can be converted to str.
Package golang.strconv provides direct access to conversion routines, for example strconv.quote and strconv.unquote.
py.bench allows to benchmark python code similarly to go test -bench and py.test. For example, running py.bench on the following code:
def bench_add(b):
x, y = 1, 2
for i in xrange(b.N):
x + y
gives something like:
$ py.bench --count=3 x.py ... pymod: bench_add.py Benchmarkadd 50000000 0.020 µs/op Benchmarkadd 50000000 0.020 µs/op Benchmarkadd 50000000 0.020 µs/op
Package golang.testing provides corresponding runtime bits, e.g. testing.B.
py.bench produces output in Go benchmark format, and so benchmark results can be analyzed and compared with standard Go tools, for example with benchstat. Additionally package golang.x.perf.benchlib can be used to load and process such benchmarking data in Python.
GPython mimics and supports most of Python command-line options, like gpython -c <commands> to run Python statements from command line, or gpython -m <module> to execute a module. Such options have the same meaning as in standard Python and are not documented here.
GPython-specific options and environment variables are listed below:
- -X gpython.runtime=(gevent|threads)
- Specify which runtime GPython should use. gevent provides lightweight coroutines, while with threads go spawns full OS thread. gevent is default. The runtime to use can be also specified via $GPYTHON_RUNTIME environment variable.