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Who are thought-leaders these days on topics such as: open collaboration, open source software, social architecture, free
software economics, open science, innovation by open project groups, non zero-sum games? Please mention things to read and
study as well as more keywords!

Answers so far:

https://en.m.wikipedia.org/wiki/The_Wealth_of_Networks
https://www.amazon.com/Information-Rules-Strategic-Network-Economy/dp/087584863X
https://twitter.com/steveklabnik
https://twitter.com/cjenscook

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sudo pip install packaging
Traceback (most recent call last):
  File "/usr/local/bin/pip", line 7, in <module>
    from pip._internal.cli.main import main
  File "/usr/local/lib/python3.6/site-packages/pip/_internal/cli/main.py", line 9, in <module>
    from pip._internal.cli.autocompletion import autocomplete
  File "/usr/local/lib/python3.6/site-packages/pip/_internal/cli/autocompletion.py", line 10, in <module>
    from pip._internal.cli.main_parser import create_main_parser
  File "/usr/local/lib/python3.6/site-packages/pip/_internal/cli/main_parser.py", line 8, in <module>
    from pip._internal.cli import cmdoptions

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Numba Vision (Anarcho Utilitarianism)
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* A kick-ass Python compiler. (Money, Fame, ...)
* A tiny Numba core, barebones library, with useful
  abstractions/contracts/interfaces (Essentialism)
* A compiler library to build other compilers on top of. (Framework/Structure)
* A platform for compiler profiling and debugging research. (Creativity)
* A platform for exploring novel scientific algorithms. (Innovation)
* An ecosystem of Numba open extensions/add-ons/utilities/libraries for

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What should Numba be?

* Numba,  as in the code base, should really be an extensible toolkit for writing compilers, the default user facing front end of which is _an_ implementation of a compiler for Python and (maybe!) NumPy.
* It needs to be sufficiently extensible to cover the spectrum of use cases, including but not limited to:
    * Typical users, just wanting to @jit some numerical functions (many many users, the most common use case)
    * Those providing libraries for domain specific use (e.g.  researchers - TARDIS-SN)
    * Those providing libraries for use in scientific computing as part of the numerical python scaffold (e.g. pydata-sparse)
    * Those writing more advanced libraries containing their own data types etc (e.g. AwkwardArray)
    * Compiler extenders wanting to write and explore new compiler use cases/needing a custom compiler (e.g. Bodo, omnisci-db)
    * Hardware vendors wanting to extend Numba support to their custom silicon (e.g. NVIDIA, Intel)

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numba_cov_active:
	NUMBA_JIT_COVERAGE=1 pytest --cov=issue_9859  test_issue_9859.py

numba_cov_disable:
	NUMBA_JIT_COVERAGE=0 pytest --cov=issue_9859  test_issue_9859.py