Develop Reference

Are unofficial python binaries safe?

I was working a on python project in vscode in which I have need to install PyAudio but pip method isn't working so I found the method of unofficial python binaries for windows but I have a doubt are those binaries safe for my PC? Is that going to corrupt files or OS? Do they access data or hardware? or They send some data or enter viruses? or Is there any other method to install pyaudio?

No - a program from anywhere can be unsafe
Your only assurances are
ability to inspect the source code and compile the program yourself
threat of lawsuit (value of compromising your system compared with the value of the source company)
restricted environments (JavaScript, airgapped system)
If you can't guarantee at least one is true, you're very likely at risk

Preferably do not use any software from unreliable sources. It may harm your system.

How can I build an RPM for an earlier version of python?

How can I build a python distribution RPM that is only dependent on an earlier version of python?
Why? I'm trying to build a distribution RPMs for RHEL6/CentOS 6, which only includes Python 2.6, but I am building usually on machines with Python 2.7.
This is an open source project, and I have already ensured that it shouldn't be including any libraries/APIs that are not in 2.6.
I am building the RPMs with:
python setup.py bdist_rpm
setup.py file:
from distutils.core import setup
setup(name='pyresttest',
version='0.1',
description=Text',
maintainer='Not listing here',
maintainer_email='no,just no',
url='project url here',
keywords='rest web http testing',
packages=['pyresttest'],
license='Apache License, Version 2.0',
requires=['yaml','pycurl']
)
(Specifics removed for the url, maintainer, email and description).
The RPM appears to be valid, but when I try to install on RHEL6, I get this error:
python(abi) = 2.7 is needed by pyresttest-0.1-1.noarch
There should be some way to get it to override the default python version to require, or supply a custom SPEC file, but after several hours of fiddling with it, I'm stuck. Ideas?
EDIT: I suppose I should clarify why I'm doing a RPM for python code, instead of just using setuptools or pip: this will hopefully go to production at work, where all deployments are RPM-based and most VMs are still RHEL6. Asking them to adopt another packaging tool is likely to be a non-starter, since our company is closely tied to the RPM format.

Re-organized the answer.
Actually, there's no "rpm-package". There're rpm-packages for RHEL6, rpm-packages for FedoraNN, rpm-packagse for OpenSUSE-X.Y and so on. And besides there're Debian, Ubuntu, Arch and Gentoo :)
You have the following possibilities with your Python package:
You may completely avoid rpm-, deb- and other "native linux packaging systems", and may opt to use a "python-native" packaging system like PIP. Thus you completely avoid the complexity and lack of compatibility between packaging systems in various versions and various flavours of Linux. And for a package which doesn't "infiltrate" deeply into "core system", this could be the best solution.
You may continue to use RPM as an archive format for your package but completely turn off automatic dependency calculations. This can be done with AutoReqProv: no directive in the spec. To be able to work with a customized spec one may use --spec-only and --spec-file distutils options. But remember that a package built this way is even worse than a zip from p.1: without proper dependencies it contains less necessary metainformation and thus "defames" the whole idea behind Linux packaging systems which were invented to built consistent systems, to avoid problems like "DLL hell" and to be suitable for automatic maintainance and updates. Actually you may add dependency information manually, via Requires: <something> tag but this may become even more hard and bporing if you target several Linux platforms at once.
In order to take into account all those complex and boring details and nuances of a particular package system you may create "build sandboxes" with appropriate versions of necessary Linux flavours. My preferred way to create such sandboxes is to use pre-created "OpenVZ templates", but without OpenVZ per se: simply unpack a given archive into a subdirectory (being root to preserve permissions), then chroot into the subdirectory, and voila! you've got Debian, RHEL etc... Fedora people have created Mock for the same purposes and likely Mock would be a more elaborated solution. As #BobMcGee suggests in the comment one also may consider Jenkins Docker plugin
Once you have a build sandbox with python distribution specific to that system, distutils etc you may automate the build process using simple scripting, bash or python.
That's it.

I do not do very much python work but have done some RPM packaging. You probably need to somehow do what one would normally do in the RPM's spec file and specify and require a particular release of your python package like so ...
# this would be in your spec file
requires: python <= 2.6
Take a look here for more info:
http://ftp.rpm.org/max-rpm/s1-rpm-depend-manual-dependencies.html

Canonical way to install modules and app onto offline system

We have an app (a bunch of Twisted classes actually) which runs on a specific Python version and depends on quite a bit of modules. This app needs to be deployed onto a Windows Server machine which has no access to Internet.
Currently we are choosing between:
having to install Python prior to everything else, and a Python script which unpacks all modules and runs setup.py,
making an NSIS installer which installs Python, then all modules with .exe installers, then unpacks smaller modules into some other dir, then adds the dir to %PYTHONPATH%.
What is the good accepted way of dealing with such situation? Obviously we cannot use pip, easy_install.exe and other blessed tools, and our approaches are silly and inelegant.

As a third option you can consider deploing the application as an executable using PyInstaller (http://www.pyinstaller.org). You dont need to install anything on the client machine (not even python)
PyInstaller is a program that converts (packages) Python programs into stand-alone executables, under Windows, Linux, Mac OS X, Solaris and AIX. Its main advantages over similar tools are that PyInstaller works with any version of Python since 2.4, it builds smaller executables thanks to transparent compression, it is fully multi-platform, and use the OS support to load the dynamic libraries, thus ensuring full compatibility.
I have used it in a project to deploy standalone application in both Linux and Windows. Worked like a charm. My project also used Twisted.
Between your current two choices the setup.py approach is more pythonic. But beware that if any of your modules has some c implementation for faster performance that need to be compiled, you can't do that on you client's machine.

Try to use wheels. It designed to cover your case, i.e. you build wheel once, downloading all required packages. Then you just copy wheel archive to the target machine and install your application without downloading anything.

Deploying python app to Mac and Windows users

I've written an app in python that depends on wxPython and some other python libraries. I know about pyexe for making python scripts executable on Windows, but what would be the easiest way to share this with my Mac using friends who wouldn't know how to install the required dependencies? One option would be to bundle my dependencies in the same package, but that seems kind of clunky. How do people usually deploy such apps? For once I miss Java...

You could check out py2app, which is similar to py2exe

How do people usually deploy such apps?
2 choices.
With instructions.
All bundled up.
You write simple instructions like this. Folks can follow these pretty reliably, unless they don't have enough privileges. Sometimes they need to sudo in linux environments.
Download easy_install (or pip)
easy_install this, easy_install that (or pip this, pip that)
easy_install whatever package you wrote.
It works really well. If you download some Python packages you'll see this in action.
Sphinx requires docutils. Django requires docutils and PIL. It works out really well to simply document the dependencies. Other folks seem to do it without serious problems. Follow their lead.
Bundling things up means you have to
(a) provide the entire original distribution (as required by most open source licenses)
(b) provide a compatible open source license with the licenses of the things you bundled. This can be easy if you depend on things that all of the same license. Otherwise, you basically can't redistribute them and have to resort to installation instructions.

Tool (or combination of tools) for reproducible environments in Python

I used to be a java developer and we used tools like ant or maven to manage our development/testing/UAT environments in a standardized way. This allowed us to handle library dependencies, setting OS variables, compiling, deploying, running unit tests, and all the required tasks. Also, the scripts generated guaranteed that all the environments were almost equally configured, and all the task were performed in the same way by all the members of the team.
I'm starting to work in Python now and I'd like your advice in which tools should I use to accomplish the same as described for java.

virtualenv to create a contained virtual environment (prevent different versions of Python or Python packages from stomping on each other). There is increasing buzz from people moving to this tool. The author is the same as the older working-env.py mentioned by Aaron.
pip to install packages inside a virtualenv. The traditional is easy_install as answered by S. Lott, but pip works better with virtualenv. easy_install still has features not found in pip though.
scons as a build tool, although you won't need this if you stay purely Python.
Fabric paste, or paver for deployment.
buildbot for continuous integration.
Bazaar, mercurial, or git for version control.
Nose as an extension for unit testing.
PyFit for FIT testing.

I also work with both java and python.
For python development the maven equivalent is setuptools (http://peak.telecommunity.com/DevCenter/setuptools). For web application development I use this in combination with paster (http://pythonpaste.org/) for the deployment process

Other than easy_install?
For our Linux servers, we use easy_install and yum.
For our Windows development laptops, we use easy_install and a few MSI's for some projects.
Most of the Python libraries we use are source-only, so we can use the same distribution on all boxes. If we could have a network shared device, we'd put them all there. Sadly, our infrastructure is kind of scattered, so we have to either move .TAR files around or redo the installs to rebuild the environments.
In a few cases (e.g., PIL), we have to recompile and check the version numbers.

You will want easy_setup to get the eggs (roughly what Maven calls an artifact).
For setting up your environment, have a look at working-env.py
Python is not compiled but you can put all files for a project in an egg. This is done with setuptools
For CI, check this answer.

We would be remiss not to also mention Paver, which was created by Kevin Dangoor of TurboGears fame. The project is still in alpha, but it appears very promising. A snippet from the project page:
Paver is a Python-based build/distribution/deployment scripting tool along the lines of Make or Rake. What makes Paver unique is its integration with commonly used Python libraries. Common tasks that were easy before remain easy. More importantly, dealing with your applications specific needs and requirements is now much easier.

I do exactly this with a combination of setuptools and Hudson. I know Hudson is a java app, but it can run Python stuff just fine.

You might want to check our Devenv. It allows you to standardize the build environments for development, QA and UAT. It's free as in "free beer".
HTH