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I want to install conda python packages on all cluster machines
Check out conda-pack:
conda-pack can be used to distribute conda environments to be used with Apache Spark jobs when deploying on Apache YARN. By bundling your environment for use with Spark, you can make use of all the libraries provided by conda, and ensure that they’re consistently provided on every node. This makes use of YARN’s resource localization by distributing environments as archives, which are then automatically unarchived on every node. In this case either the tar.gz or zip formats must be used.
Source: https://conda.github.io/conda-pack/spark.html
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Some programming languages provide capability t create a self contained packages that can run on any machine.
For example, dotnet core can self-contained apps per below:
https://learn.microsoft.com/en-us/dotnet/core/deploying/#publish-self-contained
The C# self-contained apps can be single large file, or a directory of all files required to run the application. The package can target Linux, mac or Windows.
In Python, what is the closest feature to self-contained app packages described above?
PyInstaller seems to be the current go to, and it works well in my experience. However, some people have reported that it has very large file sizes, but I've personally never found that to be a major issue.
If you use that, you would also probably need some kind of UI, but that's a separate issue in itself.
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I have an external drive from my old PC and I would like to continue working on some projects there, I have set up python but on my VSCode I keep getting "workspace contains pipfile but pipenv was not found". What's the solution to this?
You should first install pipenv to your machine eg:
pip install pipenv
Create a virtual env in the folder you'll be working in. Install Django together with other dependencies you'll be using. Wallah you're ready to start working.
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I want to understand the difference between distributing a python application. The application should be used on both Windows and Mac OS platforms. I see there are two ways of doing it.
Either create a executable using py2exe / py2app etc
Distribute the application using pip.
I would like to understand the use-cases for both the solutions.
A few things. As Sam Chats mentioned, one possible use case for creating the executable is if you don't want to share your source code, while if you distribute the application using pip, you will be able to. Additionally, if you distribute using pip vs. creating an application, more users may be able to easily access your application. As an example, check out this StackOverflow answer as a reason for using pip over Anaconda
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Suppose I need to distribute a python script to other computers but I'm using modules downloaded from remote sources that need to be installed locally. Is there a standard way of doing that?
The official packaging tutorial for Python tells how to create redistributable Python packages: https://packaging.python.org/en/latest/distributing/
Specifically, the setup.py in your package can define dependencies to to third party libraries: https://packaging.python.org/en/latest/distributing/#install-requires
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I am a newbie to Web2py and Python and I am trying to add requests
(http://docs.python-requests.org) however I am unsure how to add
this to my current Web2py environment.
I am running OSX with Web2Py 2.12.3
If you are running the Mac binary version of web2py, it includes its own Python interpreter (so if you have Python installed on your system, it will ignore any libraries available in your system Python installation). To make requests available to your web2py app, you can either put the requests package in the app's /modules folder, or you can put it in the web2py /site-packages folder, which on the Mac is inside /Contents/Resources.
However, a better option is probably just to install Python on your machine and then use the source version of web2py instead of the Mac binary. Then you can use pip to install any external libraries and they will be available when running web2py.