Saturday, January 7, 2012

Transition to Continuum

Our lives are punctuated by transformational events:  the birth of a child, finishing school, the passing of a loved one, meeting someone special.   Even without the regular beating of celestial rhythms to provide opportunities for renewal we would have these moments to measure our lives by.   Once in a while, the rhythmic and asynchronous coincide providing a particularly poignant opportunity for change.   Jan 1, 2012 was just such a time for me as I left my position as President of Enthought to start a new venture with Peter Wang (author of Chaco) and others.    Our new company is Continuum Analytics, Inc. (or just Continuum).  Our nascent website initially targeted only to the Python initiate is  

While I am ecstatic about the new venture, I will definitely miss the team that we've built around the world that has delivered Enthought's second consecutive record year.   This team of exceptional individuals has been very successful at improving and expanding the Python story in a few targeted companies inside of the Fortune 50 as well as making it easy to install Python for the masses.    Those who have taken the time to first install and then learn Traits, TraitsUI, Chaco, MayaVi, and the rest of the Enthought Tool Suite have had their efforts rewarded with increased productivity in the creation of rich client UIs and improved pluggable, scriptable, and component-based architecture.     It has been a highly educational experience to participate with Enthought.  There is much you learn about business, people, and the world when a software consulting company grows from 1 office with fewer than 17 people to 4 offices around the world and nearly 50 people.   I will always be grateful to the Enthought founders, employees (past and present), and customers (past and present) for the relationships, the trust, and the thoughtful times we shared in learning, growing, and serving each other.

My heart, however, has always been and continues to be with NumPy and SciPy which need more support than Enthought can currently provide --- so I must move on.   It took a lot of trust from my wife when (with 3 small children at home) she patiently waited for me while I spent all of 1999 writing Multipack (which in 2001 formed the bulk of SciPy).  It also took trust when in 2005 (with now 5 children at home) she watched me sacrifice my tenure-track position by writing NumPy instead of more papers.   In 2012 (with now 6 children at home), I'm asking her to trust me one more time while I leave a comfortable salary with a good company to put more effort full time in helping take NumPy and SciPy to the next level.

Over the past 4 1/2 years consulting with large companies I have learned a great deal about what NumPy (and SciPy) can and should be.  These and related tools in the Python ecosystem need to become significant pieces to real solutions to the data analytics challenges that face us.   R, Hadoop, and other (proprietary) solutions are already staking their claim on the space that Python should be dominating.   Python has significant traction in science and analysis but too little publicity in the nascent nomenclature of data analytics.    In order to accelerate the processing capabilities of Python and related tools, much progress needs to be made.   My New Year's resolution this year is to begin to contribute more substantially to that progress by organizing a new company that will hopefully allow many people to spend significant time directly on NumPy and SciPy during working hours.  I also hope to assist any public, non-profit efforts towards that mutual goal as well.   I also hope to be able to spend more time myself on NumPy and SciPy.

To realize my hopes long term, the company must succeed.   For the company to succeed it must find customers --- people willing to buy something that it sells.   People are appropriately particular about what they buy.  Making products that delight will require a lot of work from Continuum, but I am excited to help organize and work alongside the best team we can put together to do it.   This may also mean different business models and licensing around some of the NumPy-related code that the company writes.   I recognize this may cause some raised eye-brows.   I deeply value making code freely available.    I'm a Jeffersonian at heart and believe that ideas (including code) should be shared freely.   Six years ago I experimented by selling my "Guide to NumPy" long enough to make sufficient money to justify the effort.   The book ended up in the public domain and contributed substantially to the current NumPy documentation.   This is an illustration of how resources can be allocated to full-time attention and then later made available for all to enjoy.   Of course there are other models that also work to accomplish similar ends and we will be actively exploring a few of them.

Despite my ideals, my wife thanks me that I'm a pragmatist with children to provide for.   In addition, I have watched wearily as it's been difficult to find volunteer labor (including my own) to turn NumPy into the data-management and data-analytics substrate that it should already be.   All of this happens while huge sums of money are wasted at companies large and small inefficiently transforming raw, but inaccessible data into something closer to information that can be used for decisions by the domain experts.    The information available is not what it can be.  The amount of effort it takes to transform the data to actionable information is not where it can be.  The wide-spread understanding about how to program parallel and distributed machines is not where it can be.  We can and must do better in figuring out how to get full-time attention on NumPy and related tools while still making them widely available.

At Continuum, we have a vision for significantly changing how people manipulate, transform, and uncover their data.   We also have customer-driven plans to achieve it, and we are going to put our full energy into it.   So far, the development team consists of Peter Wang, me, Mark Wiebe, Francesc Alted (PyTables), and Bryan Van de Ven.   We will also be getting part-time but important development help from Hugo Shi and Andy Terrel.  In addition, we are building an initial support/business staff to help us build and grow the business.     We plan to continue to collaborate with others in the community both commercial (e.g. Wes McKinney in his new startup: Lambda Foundry) and open (e.g. Fernando Perez, Brian Granger, Min Ragan-Kelley of IPython fame). If you are interested in either joining us or collaborating with us, please send us an email at  Also, please follow us on Twitter @ContinuumIO or Like us on Facebook.  

We are actively looking for customer partners, as well.  If you are interested in learning more about where we are heading and how that might help you, please drop us a line, or come see us at PyCon this year.   We will also be at Strata, and afterwords we will be hosting a Python Data Workshop ("PyData") at the Googleplex.   Please sign up for the PyData workshop wait-list at (we could only find room for 50 people at the Googleplex).  However, given that the event is free of charge, I'm expecting some people who have reserved their spot may not actually be able to attend.  So, signing up on the wait-list is still worthwhile.

This year will be an exciting one for us.  When I get a spare moment, I still hope to finish a few of the blogs that I've started and possibly include some more that describe more of what I've learned over the past several years as a scientist/engineer-turned-software developer, lessons about running a software company, more of where we are headed at Continuum, reflections on open source, and other more technical ramblings.


  1. Great Post Travis, I met you at 2011 at Enthought during the Scipy Conference. Maybe you will remember me since I was the only guy from Brazil in the conference. I'd like to say my best wishes and success at your new company. I believe you and your staff will make scipy numpy get the real value that they both deserve. They are really amazing packages and needs a stronger commitment to evolute in the required speed. By the way in Brazil I also started lecturing about Scipy and Numpy starting a course about Scientific Computing with Python. My first class will be this month :D ( Thanks for the tips and the excelent conference the Enthought team organized in 2011. I expect to join this year again!
    Regards, Marcel

  2. I don't know how to thank you enough for all your time and effort for Numpy/Scipy, which my past and current work heavily depends on.

    I thought Dave ( is the only one who sacrificed his tenure-track position for the love of and dedication to Python in specific and Scientific Computing in general, but just realized you did as well; as an academic now in the UK who worked in the US Industry for more than 10 years, I could understand how your feeling had been for all those years.

    Please, however, be assured that your sacrifice was not in vain and more than worthwhile for the whole in Scientific & Engineering community as we all know now.

    As your moving from Academia to Industry (i.e., Enthought) was a great benefit to all using Python, this move to your own startup will be even greater benefit for the community of not only Python and Scientific Computing but also Business Computing and beyond.

    Best Wishes,
    From Wales UK,

  3. Thanks for all your incredible contributions, Travis, and here's to many more years of productive and fun collaboration! I'm sure things are only going to get better :)

    There's definitely massive room for improvement and interesting ideas in terms of data structures and tools for data analysis, so I'm very excited to see resources being put into that problem. Fun days ahead...

  4. Yes, you've always been a fantastic asset to the python community Travis and we look forward to the next step. I'm a bit worried for your wife though; it seems that every time you develop another unit of code, children result at the same time.

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  6. LOL Jon! Travis does like to leave his mark on the world. Thanks for thinking of me.

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  10. I like your forward looking (and deep) thinking. I hope that you succeed in reclaiming hearts and minds now being lost to R and Hadoop so that we can remain close to core Python. Are you going to focus on application areas-we are looking to support customers in seismic, cyber security and climate modeling and we want to stay as pythonic as possible.