On Mon, Sep 30, 2013 at 11:03 AM, F. B. <franz.bona...@gmail.com> wrote:
> Python is normally easier to write code than C++, but I think there is a
> main exception, i.e. cases of complex class-structure. In C++ there is the
> possibility of using IDEs with autocompletion enabled, which can any time
> tell you which type a variable is, a great advantage of statically typed
> languages. I tried for some time PyDev plugin in Eclipse, but it is not
> comparable to C++ development, static methods are correctly guessed, but in
> the case of class instances it is very poor.
>
> By the way, I feel that complex class-objects should be in any case
> rewritten to C++, for this very reason.

Yes, Python doesn't have types at compile time,
only at runtime. Which has advantages for easy prototyping etc., but based on my
experience, if I want to understand other people's code, it really helps to know
the types that go into methods/functions. As a side effect, also powerful
IDEs can be built around it, as you mentioned. Also, you don't need to
write tests just to check syntax like we have to do in SymPy, because
the compiler checks it for you.

The only problem with C++ that I have is that it takes forever (for me) to write
something in it (compared to Python) and it is a complex language overall.
But I am convinced that it is worthy for symbolic manipulation library.

> Regarding the Rubi ruleset, I think that a pattern matching improvement and
> rewriting in C++ would be needed, but one has also to improve the
> assumptions module in order to be able to perform the same checks as in
> Mathematica, besides the checks are to be inserted inside the pattern
> matching algorithm.

Exactly. CSymPy currently has no assumptions, so those would need to be added.

Based on my discussions so far, I think this should be what I should work on
next in CSymPy --- fast pattern matching and assumptions.

> It would be very nice to find an equivalent ruleset as Rubi for differential
> equations, if there are any.

Ondrej

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