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© 2017 Continuum Analytics - Confidential & Proprietary© 2018 Quansight - Confidential & Proprietary
SciPy/PyData/NumFOCUS Communities:
Past, Present, and Future
travis@quansight.com
@quansightai
@teoliphant
SciPy LATAM
Bogotá Colombia, Universidad de Los Andes
October 9, 2019
https://www.quansight.com
My Passions
Started my career in computational science
Satellites Measure Backscatter
Computer Algorithms Produce
Estimate of Earth Features
• Wind Speed
• Ice Cover
• Vegetation
• (and more)
1996 - 2001
Analyze 12.0
https://analyzedirect.com/
Richard Robb
Retired in 2015
Bringing “SciFi”
Medicine to Life
since 1971
Professor at BYU
Scanning Impedance Imaging
My little “side projects” became my life
1998 20182001
2015
2009 20122005
…
2001
2006
Python Data and ML/AI Time-Line
1991
2003
2014
2008
2010 2016
2009
Where I started
Started as my graduate student
“procrastination project” (as Multipack)
in 1998 and became SciPy in 2001 with
the help of Eric Jones and Pearu Peterson.
108 releases, 766 contributors
Used by: 128,495
SciPy
“Distribution of Python Numerical Tools masquerading as one Library”
Name Description
cluster KMeans and Vector Quantization
fftpack Discrete Fourier Transform
integrate Numerical Integration
interpolate Interpolation routines
io Data Input and Output
linalg Fast Linear algebra
misc Utilities
ndimage N-dimensional Image processing
Name Description
odr Orthogonal Distance Regression
optimize
Constrained and Unconstrained
Optimization
signal Signal Processing Tools
sparse Sparse Matrices and Algebra
spatial Spatial Data Structures and Algorithms
special Special functions (e.g. Bessel)
stats Statistical Functions and Distributions
SciPy 1.0 — finally reached 1.0 in late 2017
• 2001: the first SciPy release
• 2005: transition to NumPy
• 2007: creation of scikits
• 2008: scipy.spatial module and first Cython code added
• 2010: moving to a 6-monthly release cycle
• 2011: SciPy development moves to GitHub
• 2011: Python 3 support
• 2012: adding a sparse graph module and unified optimization interface
• 2012: removal of scipy.maxentropy
• 2013: continuous integration with TravisCI
• 2015: adding Cython interface for BLAS/LAPACK and a benchmark suite
• 2017: adding a unified C API with scipy.LowLevelCallable; removal of scipy.weave
• 2017: SciPy 1.0 release
My active involvement
Others led
Where it led for me
Gave up my chance at a tenured academic
position in 2005-2006 to bring together the
diverging array community in Python and unify
Numeric and Numarray.
159 releases, 827 contributors
Used by: 254,856
NumPy: an Array Extension of Python
• Data: the array object
– slicing and shaping
– data-type map to bytes
• Fast Math (ufuncs):
– vectorization
– broadcasting
– aggregations
https://pydata.org/event-schedule/
Python’s Scientific Ecosystem
Bokeh
Jake Vanderplas PyCon 2017 Keynote
Bokeh — Data Visualization
• Interactive viz, widgets, and tools
• Versatile high level graphics
• Streaming, dynamic, large data
• Optimized for the browser
• No Javascript
• With or without a server
Rapid Prototyping Visual Apps
• Python interface
• R interface
• Smart plotting
Bokeh — Data Visualization
Datashader: Rendering a Billion Points of Data
•datashader provides a fast,
configurable visualization pipeline
for faithfully revealing even very
large datasets
• Each of these visualizations
requires just a few lines of code
and no magic numbers to adjust
by trial and error.
Easy
Dashboards!
Exploring Data in Jupyter Notebooks ——> easy Web Applications!
http://panel.pyviz.org
Compile (Numerical) Python
to Native code for CPU and GPU
an open source JIT compiler that
translates a subset of Python and
NumPy code into fast machine code.
http://numba.pydata.org
Before you try to optimize speed!
Stan Seibert, “How to Accelerate an Existing Codebase with Numba” SciPy 2019
Dask provides advanced parallelism for analytics, enabling
performance at scale for the tools you love
Dask natively scales Python.
SciPy Latin America 2019
Huge Impact (from diverse efforts of 1000s)
LIGO : Gravitional Waves
Higgs Boson
Discovery
Black Hole
Imaging
Python and in particular PyData keeps Growing
Java
JavaScript
Python
Google Search Trends
Jun 2019
Several Deep Learning Libraries to choose
Built on NumPy/SciPy
Recommended
Recommended
Key Features Needed for any ML Library
• Ability to create chains of functions on n-dimensional arrays
• Ability to derive the derivative of the Loss-Function quickly (Automatic
Differentiation)
• Key Loss Functions implemented
• Cross-validation methods
• An Optimization library with several useful methods
• Ability to compute functions on n-dimensional arrays on multiple
hardware with highly parallel-execution
• Ability to create chains of functions on n-dimensional arrays
• Ability to compute functions on n-dimensional arrays on multiple hardware
For Training
For Inference
Missing from NumPy / SciPy and
Scikit-Learn, but added by CuPy
and Autograd
Most Libraries (other than Chainer) chose
to re-implement NumPy and SciPy as they
needed.
• Started with a legacy code in another language
• Had to work with other languages too (Node, Java, C++, Lua, etc.)
• Needed only a subset of functionality of NumPy / SciPy to build ML
• Needed GPU support
• Lacked familiarity with the NumPy / SciPy communities and how to engage
with them
Reasons:
Result: Many competing similar choices for Deep Learning
Working on this!
SciPy Conference Early History
• First SciPy Conference held at CalTech in
Summer of 2001 (~50 attendees)
• The first nine conferences were held in
Pasadena, CA until the US conference site
moved to Austin in 2010
• EuroSciPy started in 2008 in Leipzig
• SciPy.India started in 2009 in Trivandrum
• SciPy Latin America started in 2013
• SciPy Japan started in 2019
SciPy India 2009
Non-profits an important part of fabric
We founded in 2012 to unite
communities from Jupyter,
Numarray, Matplotlib, and the
scikits together.
Board Members selected for 2018
2019
Staff
https://pydata.org/past-events/
• 2012: Workshop at Google
• 2012: New York
• 2013: Silicon Valley, Boston, New York
• 2014: London, Berlin, Silicon Valley, New York
• 2015: Paris, Dallas, Berlin, London, Seattle, New York
• 2016: Amsterdam, Madrid, Florence, London, Berlin, Paris, Spain, San Francisco,
Chicago, Carolinas
• 2017: Florence, Amsterdam, London, Barcelona, Luxembourg, Paris, Virginia, Berlin,
Seattle, Rimini (Italy), Ossa (Poland), New York, New Delhi, Warsaw, Berlin, London,
Budapest, San Luis, New York
• 2018: Oxford, Florence, London, New York, Lithuania, Seattle, Amsterdam, Berlin,
Edinburgh, London, Delhi, New York, Cordoba, South Africa, New York, Los Angeles,
Karlsruhe, Washington DC, Warsaw,
• 2019: Miami, Bogota, Florence, Amsterdam, Lithuania, Czech Republic, Basel,
London, New Delhi, Cordoba, Berlin, New York, Budapest, Cambridge, Eindhoven, Los
Angeles, Austin, Warsaw
https://pydata.org/event-schedule/
A big part of my life is family!
My wife, Amy, and I have
six children who are looking to
us for support (emotional,
logistical, financial, etc.)
I love participating in OSS but I
have to do it sustainably and I
am driven to help others
participate sustainably as well.
Decided to start companies to sustain OSS
renamed
~17 million Anaconda users
Peter Wang
Building new solutions
Replaced by
Spin Out
Spin Out
2012
2018
?
Key members of the original management team at
Continuum created Quansight. We view NumFOCUS and
Anaconda as our first (spin-out) organizations.
2015
LABS
Sustaining the Future
Open-source innovation and
maintenance around the entire data-
science and AI workflow.
• NumPy ecosystem maintenance (PyData Core Team)
• Improve connection of NumPy to ML Frameworks
• GPU Support for NumPy Ecosystem
• Improve foundations of Array computing
• JupyterLab and JupyterHub
• Data Catalog standards
• Packaging (conda-forge, PyPA, etc.)
uarray — unified array interface for SciPy refactor
xnd — re-factored NumPy (low-level cross-language
libraries for N-D (tensor) computing)
Partnering with NumFOCUS
and Ursa Labs (supporting
Apache Arrow)
Bokeh
Adapted from Jake Vanderplas
PyCon 2017 Keynote
An early stage venture
capital firm investing in
startups that build on
open-source technology
and support the
communities they
depend on.
Bradden Blair
supporting
FairOSS
How to get more Community!
CULTIVATION OF COMMUNITY
Great works are started by a small
group usually 1-3 people).
SciPy Latin America 2019
CULTIVATION OF COMMUNITY
Some of the
Conda and
Anaconda Team
Crystal Soja Ilan Schnell Ray Donnelly
Kale Franz Michael Sarahan
Michael Grant
Maggie Mari
Bryan Van de Ven
Jonathan Helmus
Nehal Wani
CULTIVATION OF COMMUNITY Currently 8,093 pre-built packages!
Over 1200 contributors!
There are better ways to do things. There is a good.
What is the good :
can unite theists, agnostics and atheists in common efforts.
Ideas and actions that lead to lasting, self-
consistent, and sustaining peace, happiness, self-
direction, and prosperity — as decided by all
participants.
??? Excellent book:
Possible working statement:
You can only really think locally:
How do I serve the current and future users and
developers of this project?
Neuroscience
Matters
• The brain is a complicated mix
of many sub-systems and
processes.
• We all share in a spectrum of
“mental-illness” called the
human experience.
• Learning to manage your
particular experience (using all
available resources: cognitive
therapy, medication, improved
eating, exercise, sleeping, etc.)
is critical.
Neuroscience Really Matters
Understanding the
cognitive biases that
emerged in our sub-
systems from evolution
helps us manage them.
• File:Cognitive Bias Codex - 180+ biases, designed by John Manoogian III (jm3).jpg
Anchoring bias
Confirmation bias
Negativity bias
Bandwagon effect
Stereotypical bias
Blind Spot bias
Not invented here
…
We all must be open to
recognizing our current ideas
and thinking patterns
need to change or at least
adjust.
None of us have all the answers,
but some people do have better
answers and ways of thinking.
How and what you think
determines what you do and who
you are.
Life is a scientific experiment for you
Software communities are an intersection
of humanity and technology.
But, they are affected more by who we are
than what technology is.
It matters deeply:
• how we think about each other
• how we talk to and about each other,
• how we act towards each other.
CULTIVATION OF COMMUNITY
How we treat each other starts with how we treat ourselves
Individual habits matter
— your brain and body are all you have:
• good sleep patterns, good diet patterns, good exercise patterns
• repeated reflections on the positive things in your life and
expressions of gratitude. This will train your feeling-brain to
(remember the good things) and your life is what you remember
• objectively learn from the negative experiences with your
thinking-brain but don’t give them feeling-brain attention. Forgive
and let go of any hard feelings — they just poison you.
Understand Dunbar numbers
“the bigger their brains, the larger their social groups”
Humans have “layers” of social groups
(limited by our brain capacity) — I think it’s
about the complexity of the model we can
keep in our head about the people in our
group. Group Size Description
5 Best Friends
15 Working Group
50 Larger Group
150 Tribe
Robin Dunbar
Different interactions and communications
are required at each of these levels —need
for communication APIs
COMMUNITY PRINCIPLES
Philia
φιλíα
Greek word for “sisterly and brotherly love” — the
fellowship that should exist between members of the
same community.
“the central idea of φιλíα is that of doing well by someone for her own sake,
out of concern for her (and not, or not merely, out of concern for oneself).
[... Thus] the different forms of φιλíα [as listed above] could be viewed just
as different contexts and circumstances in which this kind of mutual well-
doing can arise"
— John M. Cooper
COMMUNITY PRINCIPLES
A Sanskrit word meaning selfless sacrifice, volunteering for
the community
Seva
(Sewa)
“Helping out is not some special skill. It is not the domain of rare individuals. It is
not confined to a single part of our lives.We simply heed the call of that natural
impulse within and follow it where it leads us.”
— Ram Dass
COMMUNITY PRINCIPLES
Arabic word for trust, belief, and confidence.
Thiqa
(‫)الثقة‬
"The highest form a civilization can reach is a seamless web of
deserved trust.” “The right culture, the highest and best culture, is
a seamless web of deserved trust.” “Not much procedure, just
totally reliable people correctly trusting one another. That’s the way
an operating room works at the Mayo Clinic.”
— Charles T. Munger
COMMUNITY PRINCIPLES
Transparency
• Tools facilitate this (GitHub, Slack, Gitter, Discourse, mailing-lists)
• Often a need to over-rotate to overcome negativity biases and
confirmation biases of participants
a : free from pretense or deceit : frank
b : easily detected or seen through : obvious
c : readily understood
d : characterized by visibility or accessibility of information especially concernin
business practices
COMMUNITY PRINCIPLES
Governance
• Avoiding common pitfalls
• Tyranny of the one
• Back-room decision making
• Exclusionary tendencies (unintentional or not, under-represented groups
usually have something you don’t understand holding them back from full
participation)
• Scape-Goating
• Good community governance takes time and requires maintenance —
it’s slower and often does not mix with other time-scales (enterprise,
other software, etc.)
• Facilitation, and advocacy are often needed (face-time helpful)
How are decisions made?
Who are the people involved?
How do these evolve?
COMMUNITY PRINCIPLES
The property of biological systems to remain diverse and
productive indefinitely
Sustainability
Open Source is so important that it must be connected to a bustling
marketplace of actors and agents.
All of the principles participate.
Trade is the foundation of peace and prosperity.
Connecting Business to Open Source is critical to sustainability.
Something we are working
on to try and help.
Problem
Commercial Organizations need commercial commitments and support
Open Source Projects need autonomy and independence
Open Source Contributors need credit and careers in OSS
Works to ensure open-source contributors thrive professionally
and financially.
Solution
An online marketplace where companies connect with the people who write and lead open source
Open Source
contributors
Find funding
for projects
Commercial
Find and fund
projects to meet
their needs
Copyright OpenTeams 2019. All rights reserved.
STARTUP X
Developers showcase their work
STARTUP X Projects show their development roadmap 
STARTUP X
Organizations find and fund projects they depend on
So what can you do?
1) Sign up on openteams.com and thank contributors and show how you
use the tools.
2) Build your profile by making contributions to projects you care about,
or creating a project you think is missing.
3) Contribute to the conversation about where your favorite open-
source projects should develop (what features or integrations do you
see missing).
4) Get in touch @teoliphant or travis@quansight.com especially if you
are a C++ or Python or Javascript developer, or a technical writer.

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SciPy Latin America 2019

  • 1. © 2017 Continuum Analytics - Confidential & Proprietary© 2018 Quansight - Confidential & Proprietary SciPy/PyData/NumFOCUS Communities: Past, Present, and Future travis@quansight.com @quansightai @teoliphant SciPy LATAM Bogotá Colombia, Universidad de Los Andes October 9, 2019 https://www.quansight.com
  • 3. Started my career in computational science Satellites Measure Backscatter Computer Algorithms Produce Estimate of Earth Features • Wind Speed • Ice Cover • Vegetation • (and more)
  • 4. 1996 - 2001 Analyze 12.0 https://analyzedirect.com/ Richard Robb Retired in 2015 Bringing “SciFi” Medicine to Life since 1971
  • 5. Professor at BYU Scanning Impedance Imaging
  • 6. My little “side projects” became my life
  • 7. 1998 20182001 2015 2009 20122005 … 2001 2006 Python Data and ML/AI Time-Line 1991 2003 2014 2008 2010 2016 2009
  • 8. Where I started Started as my graduate student “procrastination project” (as Multipack) in 1998 and became SciPy in 2001 with the help of Eric Jones and Pearu Peterson. 108 releases, 766 contributors Used by: 128,495
  • 9. SciPy “Distribution of Python Numerical Tools masquerading as one Library” Name Description cluster KMeans and Vector Quantization fftpack Discrete Fourier Transform integrate Numerical Integration interpolate Interpolation routines io Data Input and Output linalg Fast Linear algebra misc Utilities ndimage N-dimensional Image processing Name Description odr Orthogonal Distance Regression optimize Constrained and Unconstrained Optimization signal Signal Processing Tools sparse Sparse Matrices and Algebra spatial Spatial Data Structures and Algorithms special Special functions (e.g. Bessel) stats Statistical Functions and Distributions
  • 10. SciPy 1.0 — finally reached 1.0 in late 2017 • 2001: the first SciPy release • 2005: transition to NumPy • 2007: creation of scikits • 2008: scipy.spatial module and first Cython code added • 2010: moving to a 6-monthly release cycle • 2011: SciPy development moves to GitHub • 2011: Python 3 support • 2012: adding a sparse graph module and unified optimization interface • 2012: removal of scipy.maxentropy • 2013: continuous integration with TravisCI • 2015: adding Cython interface for BLAS/LAPACK and a benchmark suite • 2017: adding a unified C API with scipy.LowLevelCallable; removal of scipy.weave • 2017: SciPy 1.0 release My active involvement Others led
  • 11. Where it led for me Gave up my chance at a tenured academic position in 2005-2006 to bring together the diverging array community in Python and unify Numeric and Numarray. 159 releases, 827 contributors Used by: 254,856
  • 12. NumPy: an Array Extension of Python • Data: the array object – slicing and shaping – data-type map to bytes • Fast Math (ufuncs): – vectorization – broadcasting – aggregations https://pydata.org/event-schedule/
  • 13. Python’s Scientific Ecosystem Bokeh Jake Vanderplas PyCon 2017 Keynote
  • 14. Bokeh — Data Visualization • Interactive viz, widgets, and tools • Versatile high level graphics • Streaming, dynamic, large data • Optimized for the browser • No Javascript • With or without a server
  • 15. Rapid Prototyping Visual Apps • Python interface • R interface • Smart plotting Bokeh — Data Visualization
  • 16. Datashader: Rendering a Billion Points of Data •datashader provides a fast, configurable visualization pipeline for faithfully revealing even very large datasets • Each of these visualizations requires just a few lines of code and no magic numbers to adjust by trial and error.
  • 18. Exploring Data in Jupyter Notebooks ——> easy Web Applications! http://panel.pyviz.org
  • 19. Compile (Numerical) Python to Native code for CPU and GPU an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. http://numba.pydata.org
  • 20. Before you try to optimize speed! Stan Seibert, “How to Accelerate an Existing Codebase with Numba” SciPy 2019
  • 21. Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love Dask natively scales Python.
  • 23. Huge Impact (from diverse efforts of 1000s) LIGO : Gravitional Waves Higgs Boson Discovery Black Hole Imaging
  • 24. Python and in particular PyData keeps Growing
  • 26. Several Deep Learning Libraries to choose Built on NumPy/SciPy Recommended Recommended
  • 27. Key Features Needed for any ML Library • Ability to create chains of functions on n-dimensional arrays • Ability to derive the derivative of the Loss-Function quickly (Automatic Differentiation) • Key Loss Functions implemented • Cross-validation methods • An Optimization library with several useful methods • Ability to compute functions on n-dimensional arrays on multiple hardware with highly parallel-execution • Ability to create chains of functions on n-dimensional arrays • Ability to compute functions on n-dimensional arrays on multiple hardware For Training For Inference Missing from NumPy / SciPy and Scikit-Learn, but added by CuPy and Autograd
  • 28. Most Libraries (other than Chainer) chose to re-implement NumPy and SciPy as they needed. • Started with a legacy code in another language • Had to work with other languages too (Node, Java, C++, Lua, etc.) • Needed only a subset of functionality of NumPy / SciPy to build ML • Needed GPU support • Lacked familiarity with the NumPy / SciPy communities and how to engage with them Reasons: Result: Many competing similar choices for Deep Learning Working on this!
  • 29. SciPy Conference Early History • First SciPy Conference held at CalTech in Summer of 2001 (~50 attendees) • The first nine conferences were held in Pasadena, CA until the US conference site moved to Austin in 2010 • EuroSciPy started in 2008 in Leipzig • SciPy.India started in 2009 in Trivandrum • SciPy Latin America started in 2013 • SciPy Japan started in 2019 SciPy India 2009
  • 30. Non-profits an important part of fabric We founded in 2012 to unite communities from Jupyter, Numarray, Matplotlib, and the scikits together. Board Members selected for 2018 2019 Staff
  • 31. https://pydata.org/past-events/ • 2012: Workshop at Google • 2012: New York • 2013: Silicon Valley, Boston, New York • 2014: London, Berlin, Silicon Valley, New York • 2015: Paris, Dallas, Berlin, London, Seattle, New York • 2016: Amsterdam, Madrid, Florence, London, Berlin, Paris, Spain, San Francisco, Chicago, Carolinas • 2017: Florence, Amsterdam, London, Barcelona, Luxembourg, Paris, Virginia, Berlin, Seattle, Rimini (Italy), Ossa (Poland), New York, New Delhi, Warsaw, Berlin, London, Budapest, San Luis, New York • 2018: Oxford, Florence, London, New York, Lithuania, Seattle, Amsterdam, Berlin, Edinburgh, London, Delhi, New York, Cordoba, South Africa, New York, Los Angeles, Karlsruhe, Washington DC, Warsaw, • 2019: Miami, Bogota, Florence, Amsterdam, Lithuania, Czech Republic, Basel, London, New Delhi, Cordoba, Berlin, New York, Budapest, Cambridge, Eindhoven, Los Angeles, Austin, Warsaw https://pydata.org/event-schedule/
  • 32. A big part of my life is family! My wife, Amy, and I have six children who are looking to us for support (emotional, logistical, financial, etc.) I love participating in OSS but I have to do it sustainably and I am driven to help others participate sustainably as well.
  • 33. Decided to start companies to sustain OSS renamed ~17 million Anaconda users Peter Wang
  • 34. Building new solutions Replaced by Spin Out Spin Out 2012 2018 ? Key members of the original management team at Continuum created Quansight. We view NumFOCUS and Anaconda as our first (spin-out) organizations. 2015
  • 35. LABS Sustaining the Future Open-source innovation and maintenance around the entire data- science and AI workflow. • NumPy ecosystem maintenance (PyData Core Team) • Improve connection of NumPy to ML Frameworks • GPU Support for NumPy Ecosystem • Improve foundations of Array computing • JupyterLab and JupyterHub • Data Catalog standards • Packaging (conda-forge, PyPA, etc.) uarray — unified array interface for SciPy refactor xnd — re-factored NumPy (low-level cross-language libraries for N-D (tensor) computing) Partnering with NumFOCUS and Ursa Labs (supporting Apache Arrow) Bokeh Adapted from Jake Vanderplas PyCon 2017 Keynote
  • 36. An early stage venture capital firm investing in startups that build on open-source technology and support the communities they depend on. Bradden Blair supporting FairOSS
  • 37. How to get more Community!
  • 38. CULTIVATION OF COMMUNITY Great works are started by a small group usually 1-3 people).
  • 40. CULTIVATION OF COMMUNITY Some of the Conda and Anaconda Team Crystal Soja Ilan Schnell Ray Donnelly Kale Franz Michael Sarahan Michael Grant Maggie Mari Bryan Van de Ven Jonathan Helmus Nehal Wani
  • 41. CULTIVATION OF COMMUNITY Currently 8,093 pre-built packages! Over 1200 contributors!
  • 42. There are better ways to do things. There is a good. What is the good : can unite theists, agnostics and atheists in common efforts. Ideas and actions that lead to lasting, self- consistent, and sustaining peace, happiness, self- direction, and prosperity — as decided by all participants. ??? Excellent book: Possible working statement: You can only really think locally: How do I serve the current and future users and developers of this project?
  • 43. Neuroscience Matters • The brain is a complicated mix of many sub-systems and processes. • We all share in a spectrum of “mental-illness” called the human experience. • Learning to manage your particular experience (using all available resources: cognitive therapy, medication, improved eating, exercise, sleeping, etc.) is critical.
  • 44. Neuroscience Really Matters Understanding the cognitive biases that emerged in our sub- systems from evolution helps us manage them. • File:Cognitive Bias Codex - 180+ biases, designed by John Manoogian III (jm3).jpg Anchoring bias Confirmation bias Negativity bias Bandwagon effect Stereotypical bias Blind Spot bias Not invented here …
  • 45. We all must be open to recognizing our current ideas and thinking patterns need to change or at least adjust. None of us have all the answers, but some people do have better answers and ways of thinking. How and what you think determines what you do and who you are. Life is a scientific experiment for you
  • 46. Software communities are an intersection of humanity and technology. But, they are affected more by who we are than what technology is. It matters deeply: • how we think about each other • how we talk to and about each other, • how we act towards each other. CULTIVATION OF COMMUNITY
  • 47. How we treat each other starts with how we treat ourselves Individual habits matter — your brain and body are all you have: • good sleep patterns, good diet patterns, good exercise patterns • repeated reflections on the positive things in your life and expressions of gratitude. This will train your feeling-brain to (remember the good things) and your life is what you remember • objectively learn from the negative experiences with your thinking-brain but don’t give them feeling-brain attention. Forgive and let go of any hard feelings — they just poison you.
  • 48. Understand Dunbar numbers “the bigger their brains, the larger their social groups” Humans have “layers” of social groups (limited by our brain capacity) — I think it’s about the complexity of the model we can keep in our head about the people in our group. Group Size Description 5 Best Friends 15 Working Group 50 Larger Group 150 Tribe Robin Dunbar Different interactions and communications are required at each of these levels —need for communication APIs
  • 49. COMMUNITY PRINCIPLES Philia φιλíα Greek word for “sisterly and brotherly love” — the fellowship that should exist between members of the same community. “the central idea of φιλíα is that of doing well by someone for her own sake, out of concern for her (and not, or not merely, out of concern for oneself). [... Thus] the different forms of φιλíα [as listed above] could be viewed just as different contexts and circumstances in which this kind of mutual well- doing can arise" — John M. Cooper
  • 50. COMMUNITY PRINCIPLES A Sanskrit word meaning selfless sacrifice, volunteering for the community Seva (Sewa) “Helping out is not some special skill. It is not the domain of rare individuals. It is not confined to a single part of our lives.We simply heed the call of that natural impulse within and follow it where it leads us.” — Ram Dass
  • 51. COMMUNITY PRINCIPLES Arabic word for trust, belief, and confidence. Thiqa (‫)الثقة‬ "The highest form a civilization can reach is a seamless web of deserved trust.” “The right culture, the highest and best culture, is a seamless web of deserved trust.” “Not much procedure, just totally reliable people correctly trusting one another. That’s the way an operating room works at the Mayo Clinic.” — Charles T. Munger
  • 52. COMMUNITY PRINCIPLES Transparency • Tools facilitate this (GitHub, Slack, Gitter, Discourse, mailing-lists) • Often a need to over-rotate to overcome negativity biases and confirmation biases of participants a : free from pretense or deceit : frank b : easily detected or seen through : obvious c : readily understood d : characterized by visibility or accessibility of information especially concernin business practices
  • 53. COMMUNITY PRINCIPLES Governance • Avoiding common pitfalls • Tyranny of the one • Back-room decision making • Exclusionary tendencies (unintentional or not, under-represented groups usually have something you don’t understand holding them back from full participation) • Scape-Goating • Good community governance takes time and requires maintenance — it’s slower and often does not mix with other time-scales (enterprise, other software, etc.) • Facilitation, and advocacy are often needed (face-time helpful) How are decisions made? Who are the people involved? How do these evolve?
  • 54. COMMUNITY PRINCIPLES The property of biological systems to remain diverse and productive indefinitely Sustainability Open Source is so important that it must be connected to a bustling marketplace of actors and agents. All of the principles participate. Trade is the foundation of peace and prosperity. Connecting Business to Open Source is critical to sustainability.
  • 55. Something we are working on to try and help.
  • 56. Problem Commercial Organizations need commercial commitments and support Open Source Projects need autonomy and independence Open Source Contributors need credit and careers in OSS Works to ensure open-source contributors thrive professionally and financially.
  • 57. Solution An online marketplace where companies connect with the people who write and lead open source Open Source contributors Find funding for projects Commercial Find and fund projects to meet their needs Copyright OpenTeams 2019. All rights reserved.
  • 59. STARTUP X Projects show their development roadmap 
  • 60. STARTUP X Organizations find and fund projects they depend on
  • 61. So what can you do? 1) Sign up on openteams.com and thank contributors and show how you use the tools. 2) Build your profile by making contributions to projects you care about, or creating a project you think is missing. 3) Contribute to the conversation about where your favorite open- source projects should develop (what features or integrations do you see missing). 4) Get in touch @teoliphant or travis@quansight.com especially if you are a C++ or Python or Javascript developer, or a technical writer.