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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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In win10 Qt environment, C++ program calls Python program how to package and distribute, can run this program on another machine without Python environment
You can use pyinstaller to make a .exe file out of your .py. And a .exe file can run on every windows Pc.
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I need to extract news article headlines from Google alerts using Python 3.7, I tried to use "galerts" library, but I couldn't install it because it doesn't have a newer release which is supported by Python 3.7. Is there any alternative way with which I can scrape the headlines?
From the README of the galerts library, there is a link to a google-alerts library - this supports Python 3.
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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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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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I'm using Blender and Python and want to give the .py file to other users to use my script... My script uses external modules (like NumPy) which will rise the errors (like can't find module xxxx).
Not all people can install NumPy (or even Python :D) as many Blender users are just artists.
Another note is that NumPy doesn't work with Blender (I install it in the system's Python, then delete Blender Python so it relies on the system Python).
If you want to distribute your code with external dependencies then you should build a Python egg. The .egg format was created to solve the issue you are dealing with. It is a self-contained release of your code with dependencies and meta-data. Here is some information on how create Python eggs.