Just a generic question on who is the target user for the Symbolics.jl package.

I had a quick look on it, looking to find some alternative to the python-based SymPy (and the SymPy.jl wrapper), but I have now doubts if the two packages are for the same kind of users.

I am a low-math, lazy guy, and all I want is find simple way to avoid pen and paper for computing tedious derivatives, integral (no, by parts no!), solving a few system of equations and so on.

SymPy and the SymPy tutorial are fantastic for these kind of things. I can even say I can arrive to understand them

But then, looking at Symbolic.jl package I am pretty lostâ€¦ it is full of topics that for me are â€śadvancedâ€ť or look â€śof detailâ€ťâ€¦ ok, I can arrive to understand a bit about IR and ASL because I frequent the Julia community by a while now, but my colleagues would be completely lost.

`Sym`

, `istree`

, â€śexpressionâ€ť, `Num`

â€¦ what are these ?? (donâ€™t answer, I got it after a whileâ€¦) By comparison the SymPy tutorial is much more gently, it starts by showing how to achieve basic stuff and, for example, the â€śtreeâ€ť concept is given only at the very end of the tutorial.

So, my question is if indeed the objective of the package is to provide a sympy-alternative in native Julia or the focus is a bit different/ do more advanced stuffâ€¦

I would point that I am not â€ścomplainingâ€ť about the documentation, I am only trying to understand who is the target group of this package.

For example the API is also more elaborated than SymPy.

For a derivative:

SymPy:

```
using SymPy
@vars q
utility = 100q - 2q^2
marg_util = diff(utility,q)
```

Symbolics.jl:

```
using Symbolics
@variables q
utility = 100q - 2q^2
marg_util = expand_derivatives(Differential(q)(utility)) # doesn't feel very intuitive...
```

Perhaps to be more general and/or efficientâ€¦ but for basic things it is overwhelming :-/