Where to find the required Python version for a bug is undocumented

[BaumiCoder]

I tried to compile bug 3 of project black, but got several error messages. These are the outputs of compiling the buggy / fixed version of bug 3 in the provided docker container:

• compile_buggy.log
• compile_fixed.log

Many errors have the reason that gcc is missing. Therefore, I run apt-get install gcc in the container and tried the fixed version again. This changes a lot in the compile output. For example some C compilations now fail due to missing files. The whole output here: compile_with_gcc.log (On my local machine I have gcc installed and get similar error messages.)

It seems that some versions are not fixed and therefore newer versions are used, which changes the projects compile "behavior". For example dependency version conflicts like:

Collecting mypy-extensions==0.4.3
  Using cached mypy_extensions-0.4.3-py2.py3-none-any.whl.metadata (1.2 kB)
Using cached mypy_extensions-0.4.3-py2.py3-none-any.whl (4.5 kB)
Installing collected packages: mypy-extensions
  Attempting uninstall: mypy-extensions
    Found existing installation: mypy_extensions 1.1.0
    Uninstalling mypy_extensions-1.1.0:
      Successfully uninstalled mypy_extensions-1.1.0
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
mypy 1.18.2 requires mypy_extensions>=1.0.0, but you have mypy-extensions 0.4.3 which is incompatible.
Successfully installed mypy-extensions-0.4.3

Furthermore, the container uses Python 3.12 but the bugsinpy_bug.info says python_version="3.8.3" and the Pipefile contains this dataclasses = {version = ">=0.6",python_version = "< 3.7"}. I do not know if and how this is maybe already handled by BugsInPy. Without handling this version difference this maybe also one of the reasons for the compile problems.

[BaumiCoder]

Running it with python 3.8 works. Therefore, the python version of the docker image is wrong, at least for this project:

BugsInPy/Dockerfile

Line 1 in 11c5f1e

FROM python:3.12-slim-trixie

I don't know if there is an image which contains several python versions, as they are different between the projects,
although the meaning of the bug.info file versions is not mentioned in the README.

$ find projects -name bug.info -exec grep python_version "{}" \; | sort | uniq
python_version="3.6.9"
python_version="3.7.0"
python_version="3.7.0"
python_version="3.7.3"
python_version="3.7.4"
python_version="3.7.4"
python_version="3.7.7"
python_version="3.8.1"
python_version="3.8.3"
python_version="3.8.3"

Maybe an approach like here would be an option for the container image. @agb94 How to you use your container image? Why does it have python 3.12?

[agb94]

uv is available in the Docker container, which lets you install and manage any Python version. You can then create and activate a virtual environment in the working directory.

For example:

uv python install 3.8
uv venv --python 3.8
source .venv/bin/activate

Example session:

root@33264f2d52ff:/home/workspace/youtube-dl# bugsinpy-compile
Python 3.12.11
dos2unix: converting file /home/workspace/youtube-dl/bugsinpy_requirements.txt to Unix format...

root@33264f2d52ff:/home/workspace/youtube-dl# uv python install 3.8
Installed Python 3.8.20 in 10.77s
 + cpython-3.8.20-linux-aarch64-gnu (python3.8)

root@33264f2d52ff:/home/workspace/youtube-dl# uv python find 3.8
/root/.local/share/uv/python/cpython-3.8.20-linux-aarch64-gnu/bin/python3.8

root@33264f2d52ff:/home/workspace/youtube-dl# uv venv --python 3.8
Using CPython 3.8.20
Creating virtual environment at: .venv
Activate with: source .venv/bin/activate

root@33264f2d52ff:/home/workspace/youtube-dl# source .venv/bin/activate
(youtube-dl) root@33264f2d52ff:/home/workspace/youtube-dl# bugsinpy-compile
Python 3.8.20
dos2unix: converting file /home/workspace/youtube-dl/bugsinpy_requirements.txt to Unix format...

Please try this, and let me know if it doesn't work!

[BaumiCoder]

Yes, thanks @agb94, this works also the first bugsinpy-compile fails due to the wrong python version and only these commands also work:

uv python install 3.8
uv venv --python 3.8
source .venv/bin/activate
bugsinpy-compile

If the necessary python version is installed with uv, why does the base image even provides a python version? Does uv needs this python version?

[agb94]

Well, that is a great point.. I think it is possible to install uv even on machines without a preinstalled Python interpreter, because it is a Rust-based standalone tool. However, the official Astral documentation uses the official Python base image in its Docker example (https://docs.astral.sh/uv/guides/integration/docker/#installing-uv). I was referring to that example Dockerfile snippet.

(Since your PR with the README fix is still open, it would be great to include these details as well such as how to install the appropriate Python version for each buggy program snapshot, and a clarification on why the Python 3.12 base image is used, to help avoid any confusion 🙂)

[BaumiCoder]

Well, that is a great point.. I think it is possible to install uv even on machines without a preinstalled Python interpreter, because it is a Rust-based standalone tool. However, the official Astral documentation uses the official Python base image in its Docker example (https://docs.astral.sh/uv/guides/integration/docker/#installing-uv). I was referring to that example Dockerfile snippet.

Okay, following the uv documentation looks good.

(Since your PR with the README fix is still open, it would be great to include these details as well such as how to install the appropriate Python version for each buggy program snapshot, and a clarification on why the Python 3.12 base image is used, to help avoid any confusion 🙂)

@ratnadiraw Do you prefer separate PRs in this project (i.e., one for the small README fixes and one to clarify / improve the Python version handling)?

[BaumiCoder]

Update

For improving the docker image, @cedricrupb already started a (draft) PR: #95

Furthermore, I renamed this issue, to make the title more suitable for the core problem.