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My Data Journey with Python (SciPy 2015 Keynote)
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Director of Ursa Labs, Open Source Developer at Ursa LabsJul. 9, 2015•0 likes•7,416 views
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My Data Journey with Python (SciPy 2015 Keynote)
Jul. 9, 2015•0 likes•7,416 views
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Stories from my time as a Python programmer. Delivered July 9, 2015 in Austin at SciPy 2015.
Wes McKinneyFollow
Director of Ursa Labs, Open Source Developer at Ursa LabsAdvertisement
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My Data Journey with Python (SciPy 2015 Keynote)
- 1 © Cloudera, Inc. All rights reserved. My Data Journey with Python Wes McKinney @wesmckinn SciPy 2015 Keynote, 2015-‐07-‐09
- 2 © Cloudera, Inc. All rights reserved. Who am I?
- 3 © Cloudera, Inc. All rights reserved. This talk • 2007-‐present, from my perspecOve • CelebraOng our successes • Challenges and opportuniOes for the future
- 4 © Cloudera, Inc. All rights reserved. Why are we all here?
- 5 © Cloudera, Inc. All rights reserved. My pre-‐2007 existence • I was a mathemaOcian! • No exposure to Python, SQL, R (or any analyOcs for that maYer) • Rude awakening ahead
- 6 © Cloudera, Inc. All rights reserved. My first job: AQR (quant hedge fund) • A quant finance operaOon that lived and breathed SQL and Excel • ProducOon systems in C++, Java, Visual BASIC, and C# .NET • Some PhD-‐level researchers used MATLAB for research (as was common in finance / economics departments)
- 7 © Cloudera, Inc. All rights reserved. ProducOvity frustraOons • First year: several analyOcs and staOsOcal data analysis projects • A huge amount of SQL • Some Java • A liYle bit of R • … and TONS of Excel • Projects felt like 5% conceptualizaOon, 95% tedium
- 8 © Cloudera, Inc. All rights reserved. Python in early 2008: different Omes • A bleeding edge stack • NumPy 1.0.4 • SciPy 0.6.0 • matplotlib 0.91.2 • IPython 0.8.4, SVN history begins 2/2008 • Cython 0.9.8 • The scienOfic Python community seemed mainly focused on aYracOng MATLAB, HPC, and scienOfic lab users
- 9 © Cloudera, Inc. All rights reserved. 2008: Things SciPythonistas didn’t care too much about • RelaOonal data or SQL • Missing data handling (outside numpy.ma) • StaOsOcs and econometrics (first statsmodels release: 2011) • StaOsOcal graphics • Machine learning (scikit-‐learn 0.1: 2/2010) • AnalyOcs and business intelligence
- 10 © Cloudera, Inc. All rights reserved. Taking a gamble • Decided to give Python a shot for AQR projects aoer seeing part of MASS R package ported in scipy.stats.models by Jonathan Taylor at Stanford • proto-‐pandas first version built in April 2008 • Focused on porOng an R project to Python • May ‘08: Embedded Python interpreter in a legacy C++ system • 5/2008 – 12/2008: Skunkworks Python ports and evangelism across company
- 11 © Cloudera, Inc. All rights reserved. Why did Python work out? • BaYeries included • Interoperability with C++ • Embedding Python interpreter • Wrapping C++ in Python C extensions • ProducOve user interface • Python language • IPython + matplotlib
- 12 © Cloudera, Inc. All rights reserved.
- 13 © Cloudera, Inc. All rights reserved. Some other cool things we built • A global macro risk modeling system (using pandas + NumPy + PyTables) • A heterogeneous market data loading and cleaning system • A task-‐based cluster compuOng system (similar to Celery) • Tick data storage and analyOcs • Various GUIs with wxPython + matplotlib
- 14 © Cloudera, Inc. All rights reserved. End 2009: pandas! • AQR lets me open source pandas 0.1 on Christmas, 2009. ~/Downloads/pandas-‐0.1 $ cloc -‐-‐exclude-‐ext pandas -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ Language files blank comment code -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ Python 41 3124 2933 8225 Cython 7 418 93 1247 C/C++ Header 1 0 0 1 -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐ SUM: 49 3542 3026 9473 -‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐-‐
- 15 © Cloudera, Inc. All rights reserved. 2010 – 2011: Python’s data growing pains • pandas did not evolve much aoer its iniOal release • No consensus or momentum behind any project for analyOcs / data wrangling • AQR —> Duke StaOsOcal Science • AQR sponsors bug fixes and new features in pandas
- 16 © Cloudera, Inc. All rights reserved. May 2011: Gevng inspired • 2011-‐05-‐13: Enthought Datarray Summit • Discuss how to enable Python to become more useful staOsOcal compuOng • Me: “Library fragmentaOon is destrucOve; integraOon is beYer” • Data structures, missing data, and data wrangling tools • 2011-‐05-‐23 – 2011-‐06-‐03 : Python finance consulOng engagement • Realized that Python data tools sorely needed in industry • But not nearly mature enough yet
- 17 © Cloudera, Inc. All rights reserved. 2011-‐05-‐30
- 18 © Cloudera, Inc. All rights reserved. Tell me about your use cases
- 19 © Cloudera, Inc. All rights reserved. Making pandas a beYer tool • ConsulOng at AppNexus (NYC ad tech company) opened eyes to new problems • June 2011 – December 2012 • Fix some pandas design issues • Build out data wrangling capabiliOes (hierarchical indexes, etc.) • Create “killer apps” (Ome series capabiliOes) • Evangelize and collaborate with other projects
- 20 © Cloudera, Inc. All rights reserved. Taking advantage of temporary financial freedom
- 21 © Cloudera, Inc. All rights reserved. Making a book happen • A chicken-‐and-‐egg problem • Fernando Pérez, Brian Granger, and John Hunter had been toying with the idea of a “SciPy Book” for a couple years • Decided to forge my own path in Nov 2011 • WriOng took about 9 months • Helped moOvate me to “finish” parts of pandas • ~ 50,000 copies in circulaOon
- 22 © Cloudera, Inc. All rights reserved. Clarity and sooware engineering • Progress in sooware not just about hard work • Solving the right problems • … in the right order • … while wasOng liYle Ome/energy on non-‐impac}ul issues • … while being faced with real world concerns (80/20 rule) • Taking the Ome to develop a clear vision and scope for a project is a major factor in its success or failure
- 23 © Cloudera, Inc. All rights reserved. It took a village • Fernando Perez & Brian Granger (IPython) • Skipper Seabold & Josef Perktold (statsmodels) • Eric Jones (Enthought) • Travis Oliphant & Peter Wang (Enthought & ConOnuum) • John Hunter (matplotlib) • … and many others
- 24 © Cloudera, Inc. All rights reserved. An unlikely train ride SEA —> PDX November 18, 2011
- 25 © Cloudera, Inc. All rights reserved. Seatmate: “Are you a programmer?” (he saw my Emacs buffers)
- 26 © Cloudera, Inc. All rights reserved. Wes: “ Yeah, I do Python”
- 27 © Cloudera, Inc. All rights reserved. Seatmate: “Oh, I do a bit of Python too”
- 28 © Cloudera, Inc. All rights reserved. Wes: “Cool, well, there’s this awesome new thing called the IPython notebook”
- 29 © Cloudera, Inc. All rights reserved. My seatmate was computaOonal bio professor and 5-‐year PSF member Titus Brown
- 30 © Cloudera, Inc. All rights reserved. And he would later assist the IPython team in their Sloan FoundaOon $1mm grant in 2012
- 31 © Cloudera, Inc. All rights reserved. Some words about John Hunter (1968 – 2012)
- 32 © Cloudera, Inc. All rights reserved. Business ventures 2012 -‐ 2014 • 2012 : Lambda Foundry • Support and develop pandas • Explored creaOng a commercial Python financial toolkit • 2013 – 2014 : DataPad • “Google Drive for AnalyOcs / BI” • With Chang She (MIT —> AQR —> pandas) • Silicon Valley VC-‐backed • Acquired by Cloudera in September 2014
- 33 © Cloudera, Inc. All rights reserved. Cloudera • Sort of “the Red Hat of Big Data” • The leading open source Hadoop pla}orm • SupporOng and developing a liYle over 20 Apache-‐licensed open source projects • A dream job • Full Ome open source development • Solving hard data problems faced by the world’s largest companies • P.S. we’re hiring engineers in AusOn + Bay Area
- 34 © Cloudera, Inc. All rights reserved. What I’m interested in right now • Ways to enable collaboraOon on data tools across programming languages • Domain specific language design and compilaOon • Improving the Python-‐on-‐Hadoop experience • LLVM + Code generaOon
- 35 © Cloudera, Inc. All rights reserved. Different kinds of Big Data • Python programmers have been dealing with big scienOfic data in HPC sevngs for years • Big… • Text data • Homogeneous array data • Tabular (structured) data • JSON-‐like (semi-‐structured) data
- 36 © Cloudera, Inc. All rights reserved. The Great Data Tool Decoupling™ • Thesis: over Ome, user interfaces, data storage, and execuOon engines will decouple and specialize • In fact, you should really want this to happen • Share systems among languages • Reduce fragmentaOon and “lock-‐in” • Shio developer focus to usability • PredicOon: we’ll be there by 2025; sooner if we all get our act together
- 37 © Cloudera, Inc. All rights reserved. Thank you @wesmckinn
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