Python best practice: figure out the correct directory structure by reading docs and looking at GitHub repositories, learn how to write setup.py & setup.cfg & requirements.txt & MANIFEST.in files, setup py.test and tox (because Python 2 still lives), write your README in RST format (as used by nothing else ever), and for bonus points: write your own Makefile. Get depressed when you realize that target platforms either don't have Python or have the wrong version.
Rust: type "cargo new", README and doc comments in Markdown, type "cargo test" and "cargo build".
I'm being deliberately snarky, but you get the point: there has been a slow accretion of complexity over a very long time, and most of it is not the language itself.
The Python best practice: you do not need "correct directory structure" to start programming in Python--there is no boilerplate structure to create (and that would require a tool): REPL, Jupyter notebook in a browser, a single file (module) is enough in a simple case.
There is no single "correct directory structure" for more complex cases either e.g., a Django web app and Ubuntu's Appindicator would probably have different structures and it is likely that there are tools that create corresponding project skeletons such as "django-admin startproject mysite".
Usually, the packaging/deploying are not nice & neat and differ depending on your project, chosen platform--either you follow an example or you have to study a never ending list of incomplete/contradicting standards/semi-documented rules & conventions--it is unrelated to Python (even if tools such as Ansible, Salt are implemented in Python). Naturally, there are things that can be improved.
btw, reStructuredText is a great text format for documenting Python projects (it scales from a simple README.rst to a whole book). You can always convert README.md written in your favorite Markdown flavour using pandoc or a similar tool. Markdown is great for a short human-generated plaintext content common on Github, Stack Overflow.
> there is no boilerplate structure to create (and that would require a tool): REPL, Jupyter notebook in a browser, a single file (module) is enough in a simple case.
Rhetorical question: is Python a scripting language or an applications language?
If it's a scripting language, then yes, a single file is all that you need. Otherwise, you need a directory structure with various support files to be able to create and build your CLI tool or library, and you need to follow conventions if you are going to publish your work as Open Source. Which in turn requires you to know which tools to use, and what they require.
Go raised the bar here, I think. Rust and .NET Core both follow the Go idea of having one top level tool that gives you what you need to test and package your library or CLI application. That means that new users can get success with at least two basic use cases very rapidly and with little effort. Which in turn means that the previous status quo is no longer so tolerable.
> btw, reStructuredText is a great text format for documenting Python projects (it scales from a simple README.rst to a whole book).
Sure, the big problem with RST is that it lost the fight. Every developer who uses GitHub has to know a little Markdown, not RST or something else. For larger documents, AsciiDoc is probably the thing. I used to be a Textile loyalist, myself, but stopped fighting against the tide and switched to Markdown some years ago.
Python is a general -purpose programming language. No size fits all.
You've ignored "in a simple case" and ignored the next paragraph that discussed "more complex cases." If I have a task: publish Ubuntu PPA with a package that does X, or deploy a web app on a PaaS, or add a component that massages some data for a numerical simulation on a cluster or something else. I do not see what Go, Rust, .NET do here that Python can't.
Obviously, there could be specific use-cases where some language/framework has advantages over other languages/frameworks and (as I said) there may be use-cases that can be improved that why they should be named explicitly -- that is why I've asked in the first place -- so far I don't see "shoking difference" in the general case (I don't doubt that you had experienced the shoking difference for your specific (unnamed) task).
My original comment was specifically about building a CLI tool, which I did as a learning exercise to practice writing a multi-file Python project that could act as a library as well as a CLI, and be packaged as a wheel for PyPI.
Please bear in mind here that I did this because I wanted to learn and follow current best practices, with a project that I specifically picked because it would not require 3rd-party libraries or big frameworks to muddle things.
I don't think that it was dissatisfying because Python is a general-purpose programming language, but because the process currently happens to involve an assortment of different tools, piecing together scattered information, and being willing to suffer a few paper cuts like Python versions and multiple old file formats. That was my experience building a simple Python 3 application, and it didn't leave me eager to do it again.
We can discuss how Go-style tooling and packaging can also help with the cases that you mentioned, but I didn't really want to stray off into an extended analysis. My original points were just that the overall developer experience that new Python users currently get compares poorly to some other languages, and that is totally fixable. I hope that things do improve, and feel that Pipenv is a very welcome move in that direction.
Rust: type "cargo new", README and doc comments in Markdown, type "cargo test" and "cargo build".
I'm being deliberately snarky, but you get the point: there has been a slow accretion of complexity over a very long time, and most of it is not the language itself.