Develop Reference

What does it mean to "initialize the Julia runtime" when exporting compiled .dll or .so files for use in other langauges?

I'm trying to compile a usable .dll file from Julia to be used in Python as I've already written a large GUI in Python and need some fast optimization work done. Normally I would just call PyJulia or some "live" call, however this program needs to be compiled to distribute within my research team, so whatever solution I end up with needs to be able to run on its own (without Julia or Python actually installed).
Right now I'm able to create .dll files via PackageCompiler.jl, something I learned from previous posts on StackOverflow, however when trying to run these files in Python via the following code
Julia mock package
module JuliaFunctions
# Pkg.add("BlackBoxOptim")
Base.#ccallable function my_main_function(x::Cfloat,y::Cfloat)::Cfloat
z = 0
for i in 1:x
z += i ^ y
end
return z
end
# function julia_main()
# print("Hello from a compiled executable!")
# end
export my_main_function
end # module
Julia script to use PackageCompiler
# using PackageCompiler
using Pkg
# Pkg.develop(path="JuliaFunctions") # This is how you add a local package
# include("JuliaFunctions/src/JuliaFunctions.jl") # this is how you add a local module
using PackageCompiler
# Pkg.add(path="JuliaFunctions")
#time create_sysimage(:JuliaFunctions, sysimage_path="JuliaFunctions.dll")
Trying to use the resulting .dll in CTypes in Python
import ctypes
from ctypes.util import find_library
from ctypes import *
path = os.path.dirname(os.path.realpath(__file__)) + '\\JuliaFunctions.dll'
# _lib = cdll.LoadLibrary(ctypes.util.find_library(path)) # same error
# hllDll = ctypes.WinDLL(path, winmode=0) # same error
with os.add_dll_directory(os.path.dirname(os.path.realpath(__file__))):
_lib = ctypes.CDLL(path, winmode=0)
I get
OSError: [WinError 127] The specified procedure could not be found
With my current understanding, this means that CTypes found the dll and imported it, but didn't find.. something? I've yet to fully grasp how this behaves.
I've verified the function my_main_function is exported in the .dll file via Nirsoft's DLL Export Viewer. Users from previous similar issues have noted that this sysimage is already callable and should work, but they always add at the end something along the lines of "Note that you will also in general need to initialize the Julia runtime."
What does this mean? Is this even something that can be done independently from the Julia installation? The dev docs in PackageCompiler mention this, however they just mention that julia_main is automatically included in the .dll file and gets called as a sort of launch point. This function is also being exported correctly into the .dll file the above code creates. Below is an image of the Nirsoft export viewer output for reference.
Edit 1
Inexplicably, I've rebuilt this .dll on another machine and made progress. Now, the dll is imported correctly. I'm not sure yet why this worked on a fresh Julia install + Python venv, but I'm going to reinstall them on the other one and update this if anything changes. For anyone encountering this, also note you need to specify the expected output, whatever it may be. In my case this is done by adding (after the import):
_lib.testmethod1.restype = c_double # switched from Cfloat earlier, a lot has changed.
_lib.testmethod1.argtypes = [c_double, c_double] # (defined by ctypes)
The current error is now OSError: exception: access violation writing 0x0000000000000024 when trying to actually use the function, which is specific to Python. Any help on this would also be appreciated.

How to get a list of warnings from sphinx compilation

I am developing a sphinx based collaborative writing tool. Users access the web application (developed in python/Flask) to write a book in sphinx and compile it to pdf.
I have learned that in order to compile a sphinx documentation from within python I should use
import sphinx
result = sphinx.build_main(['-c', 'path/to/conf',
'path/to/source/', 'path/to/out'])
So far so good.
Now my users want the app to show them their syntax mistakes. But the output (result in the example above) only gives me the exit code.
So, how do I get a list of warnings from the build process?
Perhaps I am being too ambitious, but since sphinx is a python tool, I was expecting to have a nice pythonic interface with the tool. For example, the output of sphinx.build_main could be a very rich object with warnings, line numbers...
On a related note, the argument to the method sphinx.build_main looks just like a wrapper to the command line interface.

sphinx.build_main() calls sphinx.cmdline.main(), which in turn creates a sphinx.application.Sphinx object. You could create such an object directly (instead of "making system calls within python"). Use something like this:
import os
from sphinx.application import Sphinx
# Main arguments
srcdir = "/path/to/source"
confdir = srcdir
builddir = os.path.join(srcdir, "_build")
doctreedir = os.path.join(builddir, "doctrees")
builder = "html"
# Write warning messages to a file (instead of stderr)
warning = open("/path/to/warnings.txt", "w")
# Create the Sphinx application object
app = Sphinx(srcdir, confdir, builddir, doctreedir, builder,
warning=warning)
# Run the build
app.build()

Assuming you used sphinx-quickstart to generate your initial Sphinx documentation set with a makefile, then you can use make to build docs, which in turn uses the Sphinx tool sphinx-build. You can pass the -w <file> option to sphinx-build to write warnings and errors to a file as well as stderr.
Note that options passed through the command line override any other options set in the makefile and conf.py.

How to use PyCharm for GIMP plugin development?

I need to develop a plugin for GIMP and would like to stay with PyCharm for Python editing, etc.
FYI, I'm on Windows.
After directing PyCharm to use the Python interpreter included with GIMP:
I also added a path to gimpfu.py to get rid of the error on from gimpfu import *:
This fixes the error on the import, even when set to Excluded.
I experimented with setting this directory to Sources, Resources and Excluded and still get errors for constants such as RGBA-IMAGE, TRANSPARENT_FILL, NORMAL_MODE, etc.
Any idea on how to contort PyCharm into playing nice for GIMP plugin development?
Not really running any code from PyCharm, it's really just being used as a nice code editor, facilitate revisions control, etc.

As you find this variables are part of .pyd files (dll files for Python). PyCharm can't get signatures for content of this files.
For Python builtins (like abs, all, any, etc.) PyCharm has it's own .py files that uses only for signatures and docs. You can see it if you'll click on some of this funcs and go to it's declaration:
PyCharm will open builtins.py file in it's folder with following content:
def abs(*args, **kwargs): # real signature unknown
""" Return the absolute value of the argument. """
pass
def all(*args, **kwargs): # real signature unknown
"""
Return True if bool(x) is True for all values x in the iterable.
If the iterable is empty, return True.
"""
pass
def any(*args, **kwargs): # real signature unknown
"""
Return True if bool(x) is True for any x in the iterable.
If the iterable is empty, return False.
"""
pass
As you see functions are defined and documented, but have no implementation, because their implementation created with C and placed somewhere in binary file.
Pycharm can't provide such wrapper for every library. Usually people who created .pyd files provide their .py wrappers (for example, PyQt module: no native python implementation, just signatures).
Looks like Gimp doesn't have such wrapper for some of variables. Only way I see is to create some sort of own wrapper manually. For example, create gimpfu_signatures.py with following content:
RGBA_IMAGE = 1
TRANSPARENT_FILL = 2
NORMAL_MODE = 3
And import it while you're creating plugin:
from gimpfu import *
from gimpfu_signatures import * # comment on release
Not elegant, but better then nothing.
...
One more note about gimpfu.py's path. If I understand correctly, you just added this path to project. It may work, but correct way is to add it to project's PYTHONPATH (in project preferences). See this link for detailed manual.

In setup.py, how to test if PyCapsule_New is defined?

setup.py has a feature for testing if functions are defined:
compiler = distutils.ccompiler.new_compiler ()
if compiler.has_function ('foo_new', libraries=("foo",)):
define_macros.append (('HAVE_FOO_NEW', '1'))
However I can't seem to use this for Python extension functions (specifically PyCapsule_New). The following does not define anything:
if compiler.has_function ('PyCapsule_New'):
define_macros.append (('HAVE_PYCAPSULE_NEW', '1'))
I seem to need to put something in the libraries argument, but what? The name of the Python library changes, and is not available in distutils.sysconfig except as a gcc parameter (eg. BLDLIBRARY is defined as something like -L. -lpython2.7).
It seems like such an obvious/common thing to want to do so the code will work on multiple versions of Python, but no setup.py scripts I can find use has_function in this way.

Instead of doing configure checks for Python features, you could do some compile-time testing. Ideally you could check against the Python version (PY_MAJOR_VERSION, PY_MINOR_VERSION), but you could also rely on macros defined inside the headers.
For your specific feature, note that the Py_CAPSULE_H macro is defined once the header pycapsule.h is included (via Python.h).

Best way to specify path to binary for a wrapper module

I write a module that wraps functionality of an external binary.
For example, I wrap ls program into a python module my_wrapper.py
import my_wrapper
print my_wrapper.ls('some_directory/')
# list files in some_directory
and in my_wrapper.py I do:
# my_wrapper.py
PATH_TO_LS = '/bin/ls'
def ls(path):
proc = subprocess.Popen([PATH_TO_LS, path], ...)
...
return paths
(of course, I do not wrap ls but some other binary)
The binary might be installed with an arbitrary location, like /usr/bin/, /opt/ or even at the same place as the python script (./binaries/)
Question:
What would be the cleanest (from the user perspective) way to set the path to the binary?
Should the user specify my_wrapper.PATH_TO_LS = ... or invoke some my_wrapper.set_binary_path(path) at the beginning of his script?
Maybe it would be better to specify it in env, and the wrapper would find it with os.environ?
If the wrapper is distributed as egg, can I require during the installation, that the executable is already present in the system (see below)?
egg example:
# setup.py
setup(
name='my_wrapper',
requires_binaries=['the_binary'] # <--- require that the binary is already
# installed and on visible
# on execution path
)
or
easy_install my_wrapper BINARY_PATH=/usr/local/bin/the_binary

Create a "configuration object" with sane defaults. Allow the consumer to modify the values as appropriate. Accept a configuration object instance to your functions, taking the one you created by default.