Robust way to ensure other people can run my python program

Question

I wish to place a python program on GitHub and have other people download and run it on their computers with assorted operating systems. I am relatively new to python but have u

Answer 1

The best tool I have used so far for this is Pipenv. Not only it unifies and simplifies the whole pip+virtualenv workflow for you, developer, but it also guarantees that the exact versions of all dependencies (including Python itself) are met when other people run your project with it.

The project website does a pretty good job at explaining how to use the tool, but, for completeness sake, I'll give a short explanation here.

Once you have Pipenv installed (for instance, by running pip install --user pipenv), you can go to the directory of your project and run pipenv --python 3.7, so Pipenv will create a new virtualenv for your project, create a Pipfile and a Pipfile.lock (more on them later). If you go ahead and run pipenv install -r requirements.txt it will install all your packages. Now you can do a pipenv shell to activate your new virtualenv, or a pipenv run your_main_file.py to simply run your project.

Now let's take a look at the contents of your Pipfile. It should be something resembling this:

[packages]
Django = "*"
djangorestframework = "*"
iso8601 = "*"
graypy = "*"
whitenoise = "*"

[requires]
python_version = "3.7"

This file has the human-readable specifications for the dependencies of your project (note that it specifies the Python version too). If your requirements.txt had pinned versions, your Pipfile could have them too, but you can safely wildcard them, because the exact versions are stored in the Pipfile.lock. Now you can run things like pipenv update to update your dependencies and don't forget to commit Pipfile and Pipfile.lock to your VCS.

Once people clone your project, all they have to do is run pipenv install and Pipenv will take care of the rest (it may even install the correct version of Python for them).

I hope this was useful. I'm not affiliated in any way with Pipenv, just wanted to share this awesome tool.

Answer 2

I'll give you a very brief summary of some of the existing available solutions when it comes to python packaging you may choose from (knowledge is power):

1. Follow the guidelines provided at Structuring Your Project, these conventions are widely accepted by python community and it's usually a good starting point when newcomers start coding in python. By following these guidelines pythonists watching your project/source at github or other similar places will know straightaway how to install it. Also, uploading your project to pypi as well as adding CI by following those rules will be painless.

2. Once your project is structured properly according to standard conventions, the next step might be using some of the available freezers, in case you'd like to ship to your end-users a package they can install without forcing them to have python installed on their machines. Be aware though these tools won't provide you any code protection... said otherwise, extracting the original python code from the final artifacts would be trivial in all cases

3. If you still want to ship your project to your users without forcing them to install any dev dependency and you do also care about code protection so you don't want to consider any of the existing freezers you might use tools such as nuitka, shedskin, cython or similar ones. Usually reversing code from the artifacts produced by these tools isn't trivial at all... Cracking protection on the other hand is a different matter and unless you don't provide a physical binary to your end-user you can't do much about it other than slowing them down :)

4. Also, in case you'd need to use external languages in your python project another classic link that comes to mind would be https://wiki.python.org/moin/IntegratingPythonWithOtherLanguages, adding the build systems of such tools to CI by following rules of 1 would be pretty easy.

That said, I'd suggest stick to bulletpoint 1 as I know that will be more than good enough to get you started, also that particular point should cover many of the existing use-cases for python "standard" projects.

While this is not intended to be a full guide by following those you'll be able to publish your python project to the masses in no time.