Where is this project heading?

[tgoossens]

Is it the goal of this project to become like amaple or sympy (python) for clojure?

With features like

• symbolic differentiation/integration of a function
• taylor expansions
• simplify expressions

Just curious.

[mikera]

My personal view is that expresso could easily develop into something like SymPy over time. That will depend on where contributors want to take it of course!

[tgoossens]

Seems nice to me.

Was there a special motivation to start this project. i.e. a specific problem that had to be solved. Or is it more like 'let's see how well clojure does at symbolic math' ?

Personally I use maple quite often to do some quick calculations. And I was wondering whether there would be a specific advantage to using clojure. Of course clojure overrules maple as a decent programming language :)

[mikera]

Well I started it out of curiosity but @mschuene has done most of the subsequent development as part of Google Summer of Code.

My motivation was being able to solve / optimise algebraic expressions for data science related work. It ties quite closely to the work I'm doing on core.matrix (https://github.com/mikera/core.matrix)

Clojure gives quite a big advantage in the sense that Lisp expressions are already well suited to treating "code as data". And it also has the advantage of being a very strong general purpose language (which means it trumps Mathematica and Maple for practical usage)

[mschuene]

Hi,
Yes, expresso's goal is to evolve into a clojure CAS system much like sympy
etc. for python.
I worked on it during last years Google Summer of Code, with @mikera as
mentor.
I'd be very thankful for some contributors who share the vision to do
computer algebra in clojure. Core.matrix is a great unifying example, you
can use the plethora of matrix implementations that are available on the
jvm (or interfacing native code) but having a nice functional lispy api
which is great.
Expresso is meant to be the symbolic counterpart of that story.
I am studying mathematics and informatics currently, so I don't really have
time to work on expresso during course time, but I plan to move it forward
during my free time in summer.
Currently, expresso already has support for solving/optimising expressions,
symbolically differentiating and simplifying them etc, but it is still far
from a real CAS system.
The next steps planned are:

• giving core.matrix access to symbolic matrices with expresso as an
  implementation -> this is mostly done but still needs to be merged into
  core.matrix
• optimise the rule engine of expresso -> currently this is build on top of
  a expressive, but not very efficient rule engine written ontop of
  core.logic, there are some plans for a fast pure clojure term rewriting
  engine(for example https://github.com/kovasb/combinator and
  https://github.com/kovasb/term). unifying these term rewriting engines and
  building expresso on top of this is the way forward.

On Sat, Jul 12, 2014 at 1:24 PM, Mike Anderson notifications@github.com
wrote:

Well I started it out of curiosity but @mschuene
https://github.com/mschuene has done most of the subsequent development
as part of Google Summer of Code.

My motivation was being able to solve / optimise algebraic expressions for
data science related work. It ties quite closely to the work I'm doing on
core.matrix (https://github.com/mikera/core.matrix)

Clojure gives quite a big advantage in the sense that Lisp expressions are
already well suited to treating "code as data". And it also has the
advantage of being a very strong general purpose language (which means it
trumps Mathematica and Maple for practical usage)

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