RFC: Lazier and more interface-based conversion

Rather than trying to convert and copy values between Python and Julia, I propose to:

1. Enhance `pyjlwrap` and implement most of [Python data model](https://docs.python.org/3/reference/datamodel.html) such that virtually all Julia values are usable with `pyjlwrap`. For example, we can translate `getindex` to `__getitem__` etc. such that we can use an `AbstractArray` without translating it to a Numpy array. We can also implement `__array__` in Julia side to make `numpy.asarray` fast.

2. Restrict automatic conversion to Julia types which supports ("practically") lossless round-trip (Julia -> Python -> Julia). Maybe something like:

```julia
Union{
Nothing,
Integer,
NpyNumber, # Int64, Float16, Float32, Float64, ...
Array{<: NpyNumber},
String,
Dates.AbstractTime, # or maybe only the concrete subtypes
IO, # ditto
}
```

Here is a reference implementation that shows this approach works: https://github.com/tkf/PyBase.jl

It would solve, e.g.,:
https://github.com/JuliaPy/PyCall.jl/issues/11
https://github.com/JuliaPy/PyCall.jl/issues/175
https://github.com/JuliaPy/PyCall.jl/issues/507
https://github.com/JuliaPy/PyCall.jl/issues/555
https://github.com/JuliaPy/PyCall.jl/issues/616
https://github.com/JuliaPy/PyPlot.jl/issues/391
https://github.com/JuliaPy/PyPlot.jl/issues/400
https://github.com/JuliaPy/pyjulia/issues/122
https://github.com/JuliaPy/pyjulia/issues/123
https://github.com/JuliaDiffEq/diffeqpy/issues/21

There are many details that can be refined (e.g., rather than using a single Python class, maybe define a few base class? Or even create Python class on-demand?) but first I'd like to know if it is a reasonable direction for PyCall.jl.