I wouldn't trust pip to install anything into my system. It's not a
reliable program that I'd recommend anyone to use for things that they
might depend on.
My typical course of action is to create a virtual environment for the
package I need. Install the package into that virtual environment
using pip or w/e the package wants to be installed with. Investigate
and refine the dependencies I need (It's very common in the Python
world to incorrectly specify dependencies, to require a lot of
unnecessary dependencies, to depend on packages in the wrong way). And
after I've figured out what exactly I need to get the package to work,
copy the dependencies together with the package to the platlib
directory of Python I'm using for this task.
If platlib happens to be in the system directories or anywhere else: I
wouldn't care about that. In the process of installing the program, I
would've learned about the nature and the layout of dependencies, so
that I could make informed decisions about what goes where and whether
anything is needed or is in danger of being affected by system updates
or endangers system updates.
So far, this has worked every time. This worked for me personally,
for small companies that do internal deployments and for big companies
that distribute Python together with the entire Linux distribution in
this way. The key ingredient is to know what you are doing and to be
able to anticipate the bad things. Tools like pip take away from the
users the need to know what they are doing in hopes of reducing
complexity on the part of the users' knowledge necessary to accomplish
program installation. However, there's no free lunch, and tools like
pip bring an extra layer of complexity in trying to do what they
claim. This layer of complexity is usually revealed when these tools
fail to do what they claim, and users are forced to learn what they
actually need to know and, on top of that, how to troubleshoot
programs like pip.
From working in infra / automation, I get the knowledge about program
/ package installation "free" on the job, so, I don't see a point in
using a tool that automates that for me beyond what I already
described. I'm probably also biased because of that, but I still think
that learning to do the thing is more important than learning how to
use the tool that does the thing.
On Tue, Jan 14, 2025 at 4:42 PM Chris Green via Python-list
I have a (relatively) clean Debian 12 installation running on my two
workhorse systems, a desktop server at home and my laptop that travels
around with me.
I moved from Xubuntu to Debian on both these systems a few months ago.
I ran Xubuntu for many years and acquired a whole lot of python
packages installed with pip, as root. For the last couple of years I
had to use the --break-system-packages option to get things installed.
As far as I'm aware I never hit any dependency problems doing this.
It's probably because things I installed with pip were mostly quite
small, specialised, packages that I used in just one or two utility
programs that I had written myself. In quite a few cases these were
realated to image processing and such things.
So far I've managed to keep my Debian 12 installations 'pip free', I
haven't even got pip installed. However I may have just come across
something that would at least be very useful and it comes from PyPi.
(It's tkintertable if that's of any interest or relevance)
What are my options?
Just install it using pip as root and --break-system-packages,
what's likely to break?
Use a virtual environment, what do I have to do then to make using
my program (that uses tkintertable) 'transparent', i.e. I just
want to be able to run the program from the command prompt like
any other program.
Download tkintertable from git into my development environment and
use that. My PYTHONPATH will need to point to it but I can't see
any further issues with doing this.
Anything else? As far as I can see using pipx doesn't help me at
all (see recent thread here).
--
Chris Green
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