Hello, what would be a good way to define a Julia function based on the result of symbolic calculations?

For the moment, using `lambdify`

in `SymEngine`

gives a rather slow result, as compared to “brute force” parsing of the SymEngine output:

```
using SymEngine
@vars x
# Complicated symbolic expression here
symf = x
fl = lambdify(symf, [x])
eval(Meta.parse("fm(x)="*SymEngine.toString(symf)))
```

This defines two functions `fl`

and `fm`

which evaluate the expression in `symf`

. However, the variant with parsing the output is 20 times faster than `lambdify`

:

```
@time sum(fl(y) for y in LinRange(0., 1., 10000000))
```

```
0.924081 seconds (50.00 M allocations: 762.940 MiB, 3.03% gc time)
```

```
@time sum(fm(y) for y in LinRange(0., 1., 10000000))
```

```
0.041786 seconds (7 allocations: 272 bytes)
```