parallel

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What happened + What you expected to happen

When calling an asynchronus map function (map, starmap) on a Pool from ray.util.multiprocessing, the callback is, in contrast to python.multiprocessing.Poo.map_asyn(), not called once

Summary

mypy shows some issues in LightGBM's Python package.

mypy \
    --exclude='python-package/compile/|python-package/build' \
    --ignore-missing-imports \
    python-package/

python-package/lightgbm/compat.py:12: error: Name 'Series' already defined (possibly by an import)
python-package

I see comments suggesting adding this to understand how loops are being handled by numba, and in the their own FAQ (https://numba.pydata.org/numba-doc/latest/user/faq.html)

from llvmlite import binding as llvm
llvm.set_option('','--debug-only=loop-vectorize')

You would then create your njit function and run it, and I believe the idea is that it prints debug information about whether

Motivation

Since scikit-learn 1.0.0, the Boston housing prices dataset has been deprecated due to the ethical problem. The dataset will be removed at scikit-learn 1.2.0. Please see also the scikit-learn's page.

The scikit-learn documentation suggesting using [California housing dataset](https://scikit-l

Version of Singularity:

3.0.3

Expected behavior

Some progress or update information during the creation of the SIF file.

Actual behavior

During "Creating SIF file..." step, the console does not produce any visible output for the user - but does create the resulting file eventually.

Steps to reproduce behavior

I was executing a few “larger” builds through the bui

• I have searched issues for similar feature requests

What is this feature about (1 sentence)

Expose link to CI build for a run

Why is it needed? What is the value? For whom do we build it?

Be able to access the build on CI from the run

High-level feature overview

Add a link that points to CI build. The data is in run.meta.ci.

1. The rf204_extrangefit.py should be translated also to C++
2. The rf204b_extendedLikelihood_rangedFit.C tutorial should also be translated to C++
3. The [rf204b_extendedLikelihood_rangedFit.C](https://root.cern.ch/doc/master/rf204b__extendedLikelihood_