1. tutorials-day-1-2017-07-10
2. tutorials-day-2-2017-07-11
3. keynotes
4. talks
   1. 2017-07-12
   2. 2017-07-13
   3. 2017-07-14
5. lightning-talks

scipy_2017_notes

Links and notes for SciPy 2017.

What to know what happed last year?

• https://github.com/chendaniely/scipy_2016_notes

Please help mainain the list! send a PR!

Lists of tutorials: https://scipy2017.scipy.org/ehome/220975/493418/

Proceedings: http://conference.scipy.org/proceedings/scipy2017/

Videos of talks and tutorials: https://www.youtube.com/playlist?list=PLYx7XA2nY5GfdAFycPLBdUDOUtdQIVoMf

BoFs

• jupyter widget bof: https://gist.github.com/mwcraig/176560759e889a3635cbaaa1fdef8bbc

Tutorials Day 1 2017-07-10

Tutorial Repository	Video
Software Carpentry Scientific Python Course Part 1 (Beginner)	link
Cython for Data, Scientists, and Data Scientists (Intermediate/Advanced)	link
Numba: Tell Those C++ Bullies to Get Lost (Intermediate)	link
Automatic Code Generation with SymPy (Advanced)	link
Modern Optimization Methods in Python (Intermediate/Advanced)
Software Carpentry Scientific Python Course Part 2 (Beginner)
Computational Statistics (Beginner)	link
The Jupyter Interactive Widget Ecosystem (Intermediate/Advanced)	link
HDF5 take 2: h5py & PyTables (Intermediate/Advanced)	link
Interactive Data Visualization with HoloViews & Bokeh (Advanced)

Tutorials Day 2 2017-07-11

Tutorial Repository	Video
Introduction to Numerical Computing with NumPy (Beginner)	link
Pandas for Data Analysis (Beginner)	link
Machine Learning with scikit-learn Part One (Intermediate)	link
Parallelizing Scientific Python with Dask (Intermediate)	link
Parallel Data Analysis in Python (Intermediate)	link
Anatomy of Matplotlib (Beginner)	link
scikit-image: Image Processing for Python (Intermediate)	link
Network Science and Statistics: Fundamentals and Applications (Intermediate)	link
Machine Learning with scikit-learn Part Two (Intermediate)	link
Signal Processing and Communications Hands-On Using scikit-dsp-comm (Intermediate)	link

Keynotes

• https://github.com/katyhuff/2017-07-12-scipy
• https://www.slideshare.net/GaelVaroquaux/presentations

Talks

2017-07-12

• Python + Tableau: Building an Interactive and Beautiful Data Visualization with TabPy
  • Chloe Tseng
  • https://github.com/tableau/TabPy
• Dataflow Notebooks: Encoding and Using Cell Dependencies
  • David Koop
  • https://github.com/dataflownb/dfkernel
  • Working with notebook cells
  • iterermediate results
    • out dictionary, _, global variables
    • Out['13']
  • Persistent cell IDs
• bqplot - Seamless Interactive Visualizations in the Jupyter Notebook
  • Dhruv Madeka
  • https://github.com/dmadeka/SciPy2017
• nbgrader: A Tool for Creating and Grading Assignments in the Jupyter Notebook
  • https://github.com/jhamrick/nbgrader
• Berryconda : Scientific Python on the Raspberry Pi
  • https://github.com/jjhelmus/berryconda
• MatchPy: A Pattern Matching Library
  • Manuel Krebber, RWTH Aachen University
  • https://github.com/HPAC/matchpy
  • slides: http://slides.com/wheerd/matchpy#/
• MNE to see the brain at a millisecond time scale
  • Alex Gramfort
  • https://github.com/agramfort/mne_scipy2017
  • https://www.slideshare.net/agramfort/mne-scipy-conference-2017

2017-07-13

• Composable Multiprocessing and Multithreading for Numeric Libraries
  • Anton Malakhov, Anton Gorshkov, Terry Wilmarth
  • https://github.com/IntelPython/smp
• Dash - A New Framework for Buildin User Interfaces for Technical Computing
  • Chris Parmer
  • It's like Shiny for Python!
  • https://github.com/plotly/dash
  • https://plot.ly/products/dash/
  • http://flask.pocoo.org/
  • https://facebook.github.io/react/
  • 'widgets' are react components
    • https://plot.ly/dash/plugins
  • Learn react: https://academy.plot.ly/
• Diversity and Inclusion at the SciPy Conference
  • Julie Hollek
  • https://github.com/jkru/scipy_diversity
  • https://www.scientificamerican.com/article/how-diversity-makes-us-smarter/
  • http://www.laurenbacon.com/how-likely-is-an-all-male-speakers-list-statistically/
• Make it Work, Make it Right, Make it Fast - Debugging and Profiling in Dask
  • James Crist
  • http://jcrist.github.io/talks/profile_and_debug_dask/slides.html#/
  • https://github.com/jcrist/talks/tree/master/profile_and_debug_dask
  • https://github.com/dask/dask-glm
• Introducing JOSS: The Journal of Open Source Software
  • http://joss.theoj.org/
• Scientific MicroPython on Microcontrollers and IoT
  • Roberto Colistete Jr
  • https://github.com/micropython/micropython
• Creating Reproducible Experiments with ReproZip
  • Vicky Steeves (@VickySteeves)
  • Rémi Rampin (@remram44)
  • https://reprozip.org
  • https://vickysteeves.gitlab.io/2017-SciPy/
• Efficient Array Computing in C++ with xtensor and Apache Arrow
  • Johan Mabille
  • Sylvian Corlau
  • https://github.com/QuantStack/xtensor
  • http://xtensor.readthedocs.io/en/latest/numpy.html

2017-07-14

• Dask: Advanced Techniques

  • Matthew Rocklin
  • http://matthewrocklin.com/slides/scipy-2017.html#/
  • https://www.youtube.com/watch?v=ZxNPVTHQwGo
  • http://matthewrocklin.com/slides/scipy-2017.html#/

• Terabytes at Your Fingertips: Interactive Big Data Coding with PySpark

  • Sam Penrose
  • https://github.com/SamPenrose/decision-tree-coding
  • www.sampenrose.net

• Scientific Analysis at Scale: a Comparison of Five Systems

  • Jake VanderPlas
  • https://speakerdeck.com/jakevdp/image-analysis-at-scale -Comparative Evaluation of Big-Data Systems on Scientific Image Analytics Workloads
    • https://arxiv.org/pdf/1612.02485.pdf

• A Python API for Earth

  • Sam Skillman
  • http://descartes-labs-python.readthedocs.io/en/latest/
  • https://www.descarteslabs.com/beta-application

• NEXT: Machine Learning, Crowdsourcing, and Cartoons

  • Scott Sievert
  • https://speakerdeck.com/stsievert/scipy-2017-next

• ChiantiPy

  • https://github.com/wtbarnes/chiantipy-talk-scipy-2017

• python packaging

  • https://github.com/python-packaging-tutorial/python-packaging-tutorial

• Scientific Programming with the SciPy Stack

  • https://github.com/scw/scipy-devsummit-2017-talk

• Dashboards Visualizing Hundreds of Millions of Datapoints in 30 Lines of Python

  • https://github.com/philippjfr/scipy-talk-2017

Lightning talks

• modeling simulation in python: http://greenteapress.com/wp/modsimpy/

• screenlamp (toolkit for facilitating hypothesis-driven, ligand-based screening of large molecule libraries): https://github.com/psa-lab/screenlamp

• biopandas: https://github.com/rasbt/biopandas

• figurefirst: http://flyranch.github.io/figurefirst/

• synthpy (synthetic data in python): https://github.com/pambot/synthpy

• PlasmaPy: https://github.com/PlasmaPy/PlasmaPy

• PyART, The Python ARM Radar Toolkit, Atmospheric Radiation Measurement (ARM) : http://arm-doe.github.io/pyart/

• Computational Experiments Survey: http://survey.npimentel.net/en/

• ipython-unittest: https://www.google.com/search?q=ipython+unit+test&ie=utf-8&oe=utf-8

• burrito data: http://bit.ly/burritodata

• burrito review: https://docs.google.com/forms/d/e/1FAIpQLSdWAkbSKzHydtzJ-AKHp_rXKHeG80cZuUBjyEeMAUZXJsiFKQ/viewform

• burrito: https://github.com/srcole/burritos

• elegant scipy: https://github.com/elegant-scipy/elegant-scipy

  • givaway: elegant-scipy/elegant-scipy#308
  • picking the 25 people script/gist: https://gist.github.com/stefanv/87c866f3bda2a1f1f2d23380cdf4dd9f
  • html build copy: https://www.dropbox.com/s/cw49dk1gj6r389i/elegant-scipy-2017-07-13_15-18-54.zip?dl=0

• cykdtree: http://cykdtree.readthedocs.io/en/latest/

• cgal4py: http://cgal4py.readthedocs.io/en/latest/

• hi toby: https://github.com/tobsecret

• bokeh genome explorer: https://github.com/tobsecret/Bokeh_genome_explorer

• tex2ipy (beamer to jupyter notebooks): https://github.com/prabhuramachandran/tex2ipy

  • tex2ipy talk.tex talk.ipynb

• ipyaml: https://github.com/prabhuramachandran/ipyaml

  • https://github.com/aaren/notedown
  • https://github.com/rossant/ipymd

• reproducible self-publishing: pythontex: https://github.com/gpoore/pythontex

• vpython (navigable 3D displays and animations): http://vpython.org/

  • Matt Craig - MSUM Physics and Astronomy
  • http://www.glowscript.org/
  • https://github.com/BruceSherwood/vpython-jupyter

• Jupyter Lab: https://github.com/jupyterlab/jupyterlab

  • Jason Grout: http://jasongrout.org/
  • clap clap

• Data Package manaer (data retriever): http://www.data-retriever.org/

  • https://github.com/weecology/retriever

• cpDetect (Bayesian change point detection): https://github.com/choderalab/cpdetect

• BACnet: http://www.bacnet.org/

  • https://github.com/BuildingRobotics/pybacnet
  • http://bacpypes.sourceforge.net/

• script all the things: https://goo.gl/AqQd9v

• datalore

  • https://www.jetbrains.com/products.html
  • http://www.surveygizmo.com/s3/2911800/DataLore-Private-Beta-Sign-up

• opsn source sustainability:

  • https://www.numfocus.org/
  • bit.ly/nf-sustainability

• pep8speaks

  • https://pep8speaks.com/
  • https://github.com/OrkoHunter/pep8speaks
  • http://tinryurl.com/pythonjokes

• clover health

  • https://www.cloverhealth.com/en/
  • Associate Software Engineer Program
  • https://www.cloverhealth.com/en/about-us/careers
  • We miss you Matt: https://twitter.com/jiffyclub

• RDP

  • https://rdp.cme.msu.edu/
  • https://github.com/bio-miga/miga
  • http://enve-omics.ce.gatech.edu:3000/

• ipython 6.0 6.1

  • python 3 only
  • upgrade pip and setuptools
  • ending py2 compatibility: https://www.youtube.com/watch?v=2DkfPzWWC2Q
  • https://github.com/Carreau/pycon2017

• gormless

  • @dontusethiscode: https://twitter.com/dontusethiscode
  • domain modelling

• firefly

  • https://github.com/Caltech-IPAC/firefly
  • stargazer?
  • ipywidgets.readthedocs.io
  • firefly_widgets: https://github.com/Caltech-IPAC/firefly_widgets
  • cookiecutter templates for jupyter widgets

• Pwang

  • mission accomplished
  • open source won!
  • 2010 talk: https://www.youtube.com/watch?v=fK6E9tq-KjM&feature=youtu.be

• Pump up the Jams

  • https://gist.github.com/bmcfee/ab75ca0f10d0a01d4fe67035d1e65990

• Bus Factor: https://github.com/dpshelio/busfactor

• Hack your inbox: https://docs.google.com/presentation/d/1EaoHUxg3VNDqDq6LBD8ayawUVGVwMKkJMn-7SSH5ujk/edit#slide=id.p