I'm trying to install PennyBlack:
https://github.com/allink/pennyblack
I've done some reading, and it appears that "email_re" was removed from the latest version of Django.
I am VERY new. I was wondering if anyone could tell me a workaround so that I can get this older package installed?
The most correct way to behave in this situation would be not to use the module that is not maintained and doesn't support several latest django versions. Instead, find an alternative, see Django Packages.
Another possible solution would be to fork the project on github and make it work with the version of django you are currently using.
Also see the relevant compatibility issue.
Related
I want to develop python 2.7 app using Kivy library on Windows 10, but I do not know how to install it. I have tried to install Cython,Pygame and then Kivy.But it did not work. I have reinstalled all these things like Cython,Kivy,Python... And now I want to install it from the beginning. How can I install Kivy?
Your answers will be very appreciated.
Kivy changed a little bit since 1.8.0, use the new instructions if you have pdf docs, or some kind of book. So... the default provider is sdl2 now(pygame isn't necessary). Also, there's no need for compiling since there are wheels, so even cython and mingw aren't necessary(if you don't code with them). The only thing you need is python installed correctly.
At first of all you should visit main page and especially documentation where is described quite well what is needed and what you should install, yet still someone comes with missing dlls or something, therefore read it carefully. Or grab a tool.
But really, use the docs, most of the stuff is documented either in docs or here(examples, problems,...). No one's going to read it for you. :)
I installed Python 3.5 from source and broke a number of modules on Python 3.4, which unfortunately, was an essential part of Ubuntu. I've been trying to fix the system, now I'm almost there, with (hopefully) the last problem: My Python 3.4 only recognize C modules with name *.cpython-34m.so, while all packages from Ubuntu repository are named *.cpython-34m-x86_64-linux-gnu.so. It seems that the cpython-34m stuff is the full name of Python, so I need to change it in accord with Ubuntu's expectation. How can I achieve this?
What you are trying makes no sense. The name cannot be changed, for a good reason. The reason the names are different is to prevent incompatible versions from mixing up each other. You can compile a different version with different options and then the name will be different, too.
The essence of the package management is to satisfy all dependencies through the repositories. Theoretically there should be no need to install anything from the sources.
If you need a different Python version for some specifical reasons, virtual environments would be the thing to look for:
http://docs.python-guide.org/en/latest/dev/virtualenvs/
I reinstalled Python 3.4 via Ubuntu package system, and suddenly everything worked fine. I still have no clue how Ubuntu customize its own Python, since Python's configure command has no related option at all. Anyway, it works, so why bother :P. Finally, thank you for helping me with this problem.
The Question
Where can I access the documentation for legacy versions of the nose testing framework?
Why
I have to support some python code that must run against python 2.6 on a Centos 6 system. It is clear from experimentation that nosetests --failed does not work on this system. I'd like to know if I'm just missing a module or not. More generally, I need to know what capabilities of nose that I have grown used to I will have to do without, without having to check for them individually.
You could browse archive.org for the old results. Here's an example of a snapshot from 2012 (near the beginning of archive.org's records for the current site url): https://web.archive.org/web/20120731114655/http://nose.readthedocs.org/en/latest
You should be able to upgrade nosetests via pip, while still staying with python 2.6. At least, nose 1.3.4 (latest as of this writing) installs cleanly inside the py2.6 virtualenv I just threw together. I don't have any py2.6-compatible code to hand to show that it's working correctly, though.
I'm working on a GIS project, and I would like to implement and test some geo-spatial algorithms in Python. For this purpose, I will not only need sqlite, but also spatialite, in order to store and query the location data. Now I've tried to install the pyspatialite package, but no matter what Python version I tried (I tried all versions from 2.6 to 3.3), the pip keeps insisting, that none of the existing sqlite packages are compatible with my version of Python.
If I try to do this using easy_install, I get a traceback and an error:
AttributeError: MSVCCompiler instance has no attribute 'compiler'
And that also occurs, if I try to install the package manually, by executing the setup.py file.
From what I've already searched, some people suggest to connect to a spatialite database somehow using sqlite and loading extension, but frankly I have no idea how to do it, and couldn't understand any of these answers. I will be really grateful if someone here is able to propose a solution in a clear, step-by step way, as I'm not a very experienced Python programmer yet. Thanks in advance.
My program requires specific versions of several python packages. I don't want to have to require the user to specifically install the specific version, so I feel that the best solution is to simply install the package within the source repository, and to distribute it along with my package.
What is the simplest way to do this?
(Please be detailed - I'm familiar with pip and easy_install, but they don't seem to do this, at least not by default).
Go for virtualenv. Life will be much easier. MUCH easier. Basically, it allows you to create specific python environments as needed.
There are indeed two ways to get this done.
I usually use buildout (see a post by Jacob from Django: http://jacobian.org/writing/django-apps-with-buildout/) - and have everything from django up installed locally at the project's environment, with pydev and django support. It's very easy since I have projects that use latest versions of open source software and others that use specific versions of the same packages.
Another alternative is, as Charlie says, the virtualenv,which is designed to do just that. Many people recommend it, I've never used it myself as I'm happy with buildout.