| """Write a NumPy array in parallel from multiple CPUs/processes, using shared memory.""" | |
| from contextlib import closing | |
| import multiprocessing as mp | |
| import os | |
| import numpy as np | |
| def _init(shared_arr_): |
| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """Script to facilitate the import of a Readcube Papers 3 library into Zotero | |
| __Purpose of this script__ | |
| If you export your Readcube (Mekentosj) Papers3 library as a BibTeX file, the file paths to the PDFs are not formatted | |
| correctly for Zotero to import them. |
| #!/usr/bin/env python3 | |
| """ | |
| Code from http://www.labri.fr/perso/nrougier/python-opengl/#the-hard-way | |
| """ | |
| import ctypes | |
| import logging |
| import os | |
| import os.path as op | |
| from pathlib import Path | |
| import shutil | |
| import subprocess | |
| import tempfile | |
| from IPython.lib.latextools import genelatex | |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| #include <stdint.h> | |
| #ifdef _MSC_VER | |
| #include <intrin.h> /* for rdtscp and clflush */ | |
| #pragma optimize("gt",on) | |
| #else | |
| #include <x86intrin.h> /* for rdtscp and clflush */ | |
| #endif |
Distributing Python software to non-technical users is too hard. We need to make it simpler.
I'm imagining a tool based on conda.
Ideally I'd like to have something like this:
environment.yml file with the conda/pip dependencies for my softwareinstaller.yml file that describes my installer: package name, paths to logo/images, icon shortcuts for binaries, etc.build-installer and a few files are created:mypackage.sh: for Unix systems
