I have some old python projects that are NOT packaged (no setup.py) I need to access them.
Till now I was using buildout where I can specify a python path in buildout.cfg.
I would like to switch to pipenv : how can I specify an arbitrary python path with pipenv so I can import my unpackaged projects ?
I finally wrote a script that creates a .pth file with all the pythonpath I wanted to add in the virtualenv:
#!/usr/bin/env python
from distutils import sysconfig
import os
site_packages_path = sysconfig.get_python_lib()
PTH_FILENAME = 'MyApp.pth'
# Change here to your project home dir
PROJECT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
relative_paths = [
'.',
'plugins',
'src/achilterm',
'src/addicted',
'src/naghelp',
'src/textops',
'src',
]
absolute_paths = [ os.path.join(PROJECT_DIR,p) for p in relative_paths ]
with open(os.path.join(site_packages_path,PTH_FILENAME),'w') as fh:
for p in absolute_paths:
print 'Installing path : %s ...' % p
fh.write('%s\n' % p)
Related
import PIL
img = PIL.Image.new("RGB", (100,100))
img.show()
The error message:
FSPathMakeRef(/Applications/Preview.app) failed with error -43.
Following from Sean True's answer, an even quicker but temporary fix is to simply make a symbolic link to Preview.app in the old location. In the terminal run
ln -s /System/Applications/Preview.app /Applications/Preview.app
This fixed the problem for me.
There's an official fix in github for Pillow 7, but I'm still on 6.
This appears to be a PIL ImageShow issue, with the PIL MacViewer using /Applications/Preview.app as an absolute path to the OSX Preview app.
It's not there in Catalina. I did a quick hack to ImageShow.py changing /Applications/Preview.app to just Preview.app and the issue went away. That might or might not still work on pre-Catalina OSX, but I don't have an easy way to test.
It has apparently moved to /System/Applications/Preview.app so a quick check at run time would probably cover both cases.
elif sys.platform == "darwin":
class MacViewer(Viewer):
format = "PNG"
options = {'compress_level': 1}
preview_locations = ["/System/Applications/Preview.app","/Applications/Preview.app"]
preview_location = None
def get_preview_application(self):
if self.preview_location is None:
for pl in self.preview_locations:
if os.path.exists(pl):
self.preview_location = pl
break
if self.preview_location is None:
raise RuntimeError("Can't find Preview.app in %s" % self.preview_locations)
return self.preview_location
def get_command(self, file, **options):
# on darwin open returns immediately resulting in the temp
# file removal while app is opening
pa = self.get_preview_application()
command = "open -a %s" % pa
command = "(%s %s; sleep 20; rm -f %s)&" % (command, quote(file),
quote(file))
return command
def show_file(self, file, **options):
"""Display given file"""
pa = self.get_preview_application()
fd, path = tempfile.mkstemp()
with os.fdopen(fd, 'w') as f:
f.write(file)
with open(path, "r") as f:
subprocess.Popen([
'im=$(cat);'
'open %s $im;'
'sleep 20;'
'rm -f $im' % pa
], shell=True, stdin=f)
os.remove(path)
return 1
I need to develop a script in gnuplot that is usable under both Windows and Linux.
To decide which OS I have, I wrote
OS=system("echo %OS%")
print "OS = ", OS
if (OS eq "Windows_NT") \
...; \
else \
...;
and it worked.
Is there an alternative way, native to gnuplot, which does not depend on environment variables?
you could use the internal variable GPVAL_SYSNAME:
gnuplot> print GPVAL_SYSNAME
Windows_NT-10.0
which is on Windows initialized in eval.c as:
ZeroMemory(&osvi, sizeof(OSVERSIONINFO));
osvi.dwOSVersionInfoSize = sizeof(OSVERSIONINFO);
GetVersionEx(&osvi);
snprintf(s, 30, "Windows_NT-%ld.%ld", osvi.dwMajorVersion, osvi.dwMinorVersion);
fill_gpval_string("GPVAL_SYSNAME", s);
In order to test if this string starts with "Windows", one could use the Gnuplot's internal strstrt function as:
if (strstrt(GPVAL_SYSNAME, "Windows") == 1) {
....
}
In addition, there is also GPVAL_MACHINE:
gnuplot> print GPVAL_MACHINE
x86_64
Anybody tried to use numba in google collaboratory? I just can not figure out how to set it up in this environment.
At the moment, I'm stuck with the error library nvvm not found.
Copy this code into cell. It works for me.
!apt-get install nvidia-cuda-toolkit
!pip3 install numba
import os
os.environ['NUMBAPRO_LIBDEVICE'] = "/usr/lib/nvidia-cuda-toolkit/libdevice"
os.environ['NUMBAPRO_NVVM'] = "/usr/lib/x86_64-linux-gnu/libnvvm.so"
from numba import cuda
import numpy as np
import time
#cuda.jit
def hello(data):
data[cuda.blockIdx.x, cuda.threadIdx.x] = cuda.blockIdx.x
numBlocks = 5
threadsPerBlock = 10
data = np.ones((numBlocks, threadsPerBlock), dtype=np.uint8)
hello[numBlocks, threadsPerBlock](data)
print(data)
I didn't have to install the packages #Algis suggested, but the paths to the drivers were different. So I had to do the following.
First determine the correct paths for the drivers
!find / -iname 'libdevice'
!find / -iname 'libnvvm.so'
# Output:
# /usr/local/cuda-9.2/nvvm/lib64/libnvvm.so
# /usr/local/cuda-9.2/nvvm/libdevice
Then set the paths as #Algis described
import os
os.environ['NUMBAPRO_LIBDEVICE'] = "/usr/local/cuda-9.2/nvvm/libdevice"
os.environ['NUMBAPRO_NVVM'] = "/usr/local/cuda-9.2/nvvm/lib64/libnvvm.so"
You can do #Stan's work in one simple sweep if you have this block at the beginning of your colab notebook (this also automatically updates as CUDA gets updated)
import os
dev_lib_path = !find / -iname 'libdevice'
nvvm_lib_path = !find / -iname 'libnvvm.so'
assert len(dev_lib_path)>0, "Device Lib Missing"
assert len(nvvm_lib_path)>0, "NVVM Missing"
os.environ['NUMBAPRO_LIBDEVICE'] = dev_lib_path[0]
os.environ['NUMBAPRO_NVVM'] = nvvm_lib_path[0]
I am looking to set up two separate system variables through python, so that both gdal_calc and gdal_translate will work properly on my computer. However, it the pathway's that I have appended and the variables that I have added don't seem to be working properly. Any suggestions?
#!/usr/bin/env python
import subprocess
from subprocess import call
import sys
import os
# make dictionary of environmental variables to set up for gdal_calc and gdal_translate
gdal_env = os.environ.copy()
# modify and add variables for environment so that GDAL runs properly
gdal_env["GDAL_DATA"] = "C:\\Program Files (x86)\\GDAL\\gdal-data"
gdal_env["GDAL_DRIVER_PATH"] = "C:\\Program Files (x86)\\GDAL\\gdalplugins"
gdal_env["PATH"] = gdal_env["PATH"] + ";C:\\Program Files (x86)\\GDAL\\bin"
# Set constants
# The pathway to the images files are nested within the '--outfile=' command
inHVFile = os.path.expanduser('~\\Desktop\\Components\\Float32\\newHV32.img')
outPlacement = os.path.expanduser('~\\Desktop\\Components\\Zeros\\newHVZeros_1.img')
outVFile = '--outfile=' + outPlacement
#calc_cmd_HV = ['gdal_calc.py', '-A', inHVFile, outVFile, '--calc=A+1']
inVHFile = os.path.expanduser('~\\Desktop\\Components\\Float32\\newVH32.img')
outPlacement_1 = os.path.expanduser('~\\Desktop\\Components\\Zeros\\newVHZeros_1.img')
outVFile_1 = '--outfile=' + outPlacement_1
#calc_cmd_VH = ['gdal_calc.py', '-A', inVHFile, outVFile_1, '--calc=A+1']
subprocess.call([sys.executable,'C:\Program Files (x86)\GDAL\gdal_calc.py', inHVFile, outVFile, '--calc=A+1'], env=gdal_env)
subprocess.call([sys.executable,'C:\Program Files (x86)\GDAL\gdal_calc.py', inVHFile, outVFile_1, '--calc=A+1'], env=gdal_env)
#subprocess.call([sys.executable, 'C:\\Program Files (x86)\\GDAL\\gdal_calc.py','-A', inHVFile, outVFile, '--calc=A+1'])
#subprocess.call([sys.executable, 'C:\\Program Files (x86)\\GDAL\\gdal_calc.py','-A', inVHFile, outVFile_1, '--calc=A+1'])
Environmental variables hold information about where files and programs can be found. When using Python to call commandline programs via subprocess.call or subprocess.Popen, you can specify a set of environmental variables at the time the subprocess is spawned. This is done by passing a dictionary to the env kwarg of call or Popen. If env is not specified, the default environmental variables will be used.
Modifications to the environmental variables stored in os.environ will not persist after the Python session has ended.
To call GDAL programs via subprocess.call, do the following:
import os
import subprocess
import sys
# make dictionary of environmental variables
gdal_env = os.environ.copy()
# modify and add variables
gdal_env["GDAL_DATA"] = "C:\\Program Files (x86)\\GDAL\gdal-data"
gdal_env["GDAL_DRIVER_PATH"] = "C:\\Program Files (x86)\\GDAL\\gdalplugins"
gdal_env["PATH"] = gdal_env["PATH"] + ";C:\\Program Files (x86)\\GDAL\\bin"
# ... do preparation ...
a = "a.tif"
b = "b.tif"
output = "output.tif"
calc_cmd = [sys.executable, 'gdal_calc.py', '-A', a, '-B', b, '--outfile='+output, '--calc=A+B']
# spawn a new subprocess
subprocess.call(calc_cmd, env=gdal_env)
For Matplotlib plots in iPython/Jupyter you can make the notebook plot plots inline with
%matplotlib inline
How can one do the same for NLTK draw() for trees? Here is the documentation http://www.nltk.org/api/nltk.draw.html
Based on this answer:
import os
from IPython.display import Image, display
from nltk.draw import TreeWidget
from nltk.draw.util import CanvasFrame
def jupyter_draw_nltk_tree(tree):
cf = CanvasFrame()
tc = TreeWidget(cf.canvas(), tree)
tc['node_font'] = 'arial 13 bold'
tc['leaf_font'] = 'arial 14'
tc['node_color'] = '#005990'
tc['leaf_color'] = '#3F8F57'
tc['line_color'] = '#175252'
cf.add_widget(tc, 10, 10)
cf.print_to_file('tmp_tree_output.ps')
cf.destroy()
os.system('convert tmp_tree_output.ps tmp_tree_output.png')
display(Image(filename='tmp_tree_output.png'))
os.system('rm tmp_tree_output.ps tmp_tree_output.png')
Little slow, but does the job. If you're doing it remotely, don't forget to run your ssh session with -X key (like ssh -X user#server.com) so that Tk could initialize itself (no display name and no $DISPLAY environment variable-kind of error)
UPD: it seems like last versions of jupyter and nltk work nicely together, so you can just do IPython.core.display.display(tree) to get a nice-looking tree-render embedded into the output.
2019 Update:
This runs on Jupyter Notebook:
from nltk.tree import Tree
from IPython.display import display
tree = Tree.fromstring('(S (NP this tree) (VP (V is) (AdjP pretty)))')
display(tree)
Requirements:
NLTK
Ghostscript