DARPA gives $3M to Continuum Analytics to improve Python for big data

http://www.drdobbs.com/tools/us-defense-agency-feeds-python/240151767

by astaire • 13 years ago

216 40 13 years ago

drdobbs.com

pjscott• 13 years ago

More info from Continuum Analytics:

http://continuum.io/blog/continuum-wins-darpa-xdata-funding

The money is going to develop Blaze and Bokeh:

http://blaze.pydata.org/

https://github.com/ContinuumIO/Bokeh

gojomo2• 13 years ago

I see that Blaze is BSD-licensed... but Bokeh has no clear licensing information. Anyone know the intended Bokeh license?

(The Dr. Dobbs article doesn't mention licensing at all; the Continuum release implies the XDATA program has a focus on open source but doesn't specify more about Bokeh.)

jsrn• 13 years ago

"Bokeh will be BSD/MIT."

https://github.com/ContinuumIO/Bokeh/issues/7

gjreda• 13 years ago

I think the lack of a ggplot2 equivalent is one of the main things holding people back from fully converting from R to Python - I know it is for me. Once you really understand the ggplot2 syntax and style, making your graphics seems to come naturally. It's fantastic.

I'm extremely excited to see Bokeh develop more.

alokv28• 13 years ago

I've found matplotlib [1] to be an intuitive and customizable way to make beautiful plots with python

[1] http://matplotlib.org/

primelens• 13 years ago

Better D3 integration from within Python would be awesome.

coldtea2• 13 years ago

Why, is there ANY D3 integration with Python?

paddy_m2• 13 years ago

Bokeh has three components. BokehJS runs in the browser, the Bokeh server and the Bokeh Python client library.

BokehJS draws plots in the browser with canvas. BokehJS maintains a data model of plot models (plots, renederers of different types, tools) with Backbone JS. It has a a connection to the Bokeh server via web sockets.

The Bokeh server keeps track of plot objects and other models with redis. It keeps these persistently in documents.

The python client connects to the server and either create new plots or updates existing plots. You can create a plot with python and get a url to embed that plot in any web page. This means that your python code can just be a script that doesn't have to worry about serving up a web page.

We intend to write client libraries in other languages like java, R, and ruby to name a few.

wilfra• 13 years ago

Article calls it both a 'donation' and an 'investment' - which is it?

paddy_m2• 13 years ago

We are working to build open source software for them that meets their needs. I think they are making an investment in the sense that any customer is invested in the outcome of a project. It wasn't a VC investment.

gojomo2• 13 years ago

I'd guess 'grant' would be a better term than either for what's happening here. AFAIK, DARPA doesn't take equity, but does make grants based on intended deliverables.

('Investment' was used in the article in the general sense of "an investment in our children's future" or "investing in shared infrastructure", rather than expecting a specific liquid return like cash dividends or an appreciated exit event.)

ryguytilidie• 13 years ago

Since DARPA can't take equity in companies, it doesn't really matter. Its a donation in that the department will get nothing in return. Its an investment in that it will ideally make America a better place. Think of everything DARPA does as both a donation and an investment.

dekhn• 13 years ago

Blaze has the potential to be great. Numpy/Scipy (and previously, numarry and NumPy) are, at least to scientists, some of the most useful libraries in Python. Being able to express computation in a high level language, and having it run in native code, yet still be able to access the data in python, is often a major productivity enhancer.

I'm still a bit skeptical Blaze will catch on. It's ambitious, and the python numeric community has had to chase each new implementation (with serious issues with backwards compatibility and cost of adoption) over the years. I would actually far prefer numpy and its limited functionality, over a much more complex system that didn't have any adopters.

siddboots2• 13 years ago

Having a bit of a look at the docs^1, I don't really see it as "yet another arrays package". The API exposes generalized table/array operations, and a subset of those features can be implemented using NumPy's ndarrays. If the interface is clean, then I don't think adoption will be an issue: there simply isn't anything else that does this.

You are absolutely right that both of these projects are extremely ambitious, but, given the $3 mil grant, I can't help but be optimistic.

1 http://blaze.pydata.org/docs/overview.html#blaze-is-a-genera...

shazzdeeds• 13 years ago

DARPA is also working closely with the Blaze team on several projects to enhance its functionality and performance, so it will continue to improve. I'm not aware of any money being directly invested, but the organization has a way of encouraging projects it finds promising.

eliben• 13 years ago

This is great! Continuum Analytics are doing cool stuff for numeric / big data Python and it's great to see the language getting more and more traction in this domain.

chm• 13 years ago

Will this mean better scientific computing with Python?

hazov3• 13 years ago

Depends on what you call scientific computing, Continuum Analytics appears to have a data/stats focus (I now work as a statistician and people talks good about their products, I never used them), there I believe Python has the possibility to displace R and Octave/SciLab/MatLab as the language for light academic stuff, for CFD (Computational Fluid Dynamics) and CEM (Computational Electrodynamics) guys generally run on C, C++ and Fortran, or whatever runs Numerical Linear Algebra faster, I doubt Python will take this post anytime soon.

ahaefner• 13 years ago

I saw a presentation about Blaze at PyData. The CEO of Continuum was the author of Numpy and said they are doing everything he would have done differently in Blaze.

Also, Blaze is attempting to abstract the concept of having huge arrays distributed across multiple systems, clusters, clouds, whatever. So imagine having large distributed arrays that you can easily perform computations on. Could be very powerful if it works as planned.

qompiler• 13 years ago

All I see in these libraries are standard data types which are already available in Python. Are these libraries even being developed by mathematicians? It looks like someone hired a bunch of first grade computer science students to chunk out wrappers.

mmcnickle• 13 years ago

There are many new data types introduced by these libraries, distinct from the standard library types. The N-dimentional array is the most notable one.

toolslive• 13 years ago

"If they can learn an easy language, they won't have to rely on an external software development group to complete their analysis."

Although scientists earn more credit here than business people, allow me to make a skeptical remark:

This is exactly the same reason they had in the past regarding with SQL. "Business people can't wait for programmers to run their queries; if they can learn an easy language, they won't have to rely on programmers to do that for them..."

In the end, the business people did not do SQL; they just force developers to do it for them, using SQL.

History repeats itself, perpetuating fallacies

yummyfajitas• 13 years ago

Many business people do write SQL. Typically in a poorly administered access database, but they do write SQL.

Scientists also already use several easy languages (r, MATLAB, SAS, increasingly python) rather than relying on outside developers.

pwang3• 13 years ago

> In the end, the business people did not do SQL

False. There are literally hundreds of thousands of people using SQL every day to query and analyze their data, that would not be able to write a for-loop or tell you what a pointer is. The same goes for R.

Just because the needs of business analytics have grown to a point where developers are needed to build extremely sophisticated things with SQL, does not mean that simple SQL does not serve its original purpose beautifully.

The same is true for Python. You can do incredibly sophisticated things with Python, but there are many, many scientists and data analysts that use it to do simple things that would not quite fit into a SQL mold, but also don't require a deep knowledge of CS.

indeyets• 13 years ago

Would be really cool, if part of this money went for funding PyPy's NumPy effort (they still need $15K to be fully funded)

ateev23• 13 years ago

This will sure make me to learn python over ruby

DARPA gives $3M to Continuum Analytics to improve Python for big data

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