How can I use Symbolics.jl to simplify divisions assuming a variable is not zero?

For example, I would like to get `1`

from

```
julia> using Symbolics
julia> @variables x
1-element Vector{Num}:
x
julia> simplify(x / x) # How can this be simplified to 1 assuming that `x` is not zero?
x / x
```

For something as simple as the example above, I can use a custom rule such as

```
julia> div_rule = @rule ~x / ~x => one(~x)
~x / ~x => one(~x)
julia> simplify(x/ x, Rewriters.Prewalk(Rewriters.PassThrough(div_rule)))
1
```

However, if I have more complicated expressions, this doesn’t work anymore, e.g.

```
julia> @variables x y
2-element Vector{Num}:
x
y
julia> simplify(x * y/ x, Rewriters.Prewalk(Rewriters.PassThrough(div_rule)))
(x*y) / x
```

Something such as

```
julia> simplify(sin(y) * x/ x, Rewriters.Prewalk(Rewriters.Chain((
@rule(~a1 * ~x * ~a2 / ~x => ~a1 * ~a2),
@rule(~a1 * ~x / ~x => ~a1),
@rule( ~x * ~a2 / ~x => ~a2),
@rule( ~x / ~x => one(~x),
)))))
sin(y)
```

seems to do the job, but it’s rather complicated and applies to all variables. Moreover, it doesn’t scale to more complicated expressions such as `(x + y) / x`

.

- How can this be generalized to all forms of divisions mixed with other operations?
- Is there an easier way to achieve this?
- How can I restrict the simplification to some specific variables?