* Add a `dora-python-operator` crate to hold utils functions for dora python

* Remove python serialisation and deserialisation from `dora-runtime`

* Update `python` documentation

* add `pip` release in release workflow

* add blank space

* Reduce Python verion to 3.7 for default conda support

* Split CI workflows to avoid name collusions

There is a name collusion issue within cargo. See: https://github.com/rust-lang/cargo/issues/6313
That make it impossible to build at the same time the `dora` cli binary,
and the `dora` python shared library.

To avoid the collusion, this commit split the two workflows:
- `main` workflows consists of default-members and is tested on `ci.yml`
- `python` workflow is on `ci-python.yaml` which is only run when python file changed.

* add root example package

* add python version

* Fix Minor pypi release issue

- Name is `dora-rs` and not `dora`
- maturin 0.13 does not have `extension-module` features built in.

* Use `--all` to check build of `dora`

As the cli name was changed to `dora-cli`, we don't have name collusion anymore and can use `--all` flags for building and testing `dora`

Changes the message format from raw data bytes to a higher-level `Message` struct serialized with capnproto. In addition to the raw data, which is sent as a byte array as before, the `Message` struct features `metadata` field. This metadata field can be used to pass open telemetry contexts, deadlines, etc.

Since the merge of https://github.com/PyO3/maturin/pull/605 ,
we can add features flag when maturin build the python project, removing
the need to always enabling `extension-module` flag when building.

The `extension-module` flag creates crash when building and testing outside
of maturin.

Previous fix required to disable default feature flag when building and testing which is not ideal.

Adding `next` and `send_output` requires an async threadpool as the
communication Layer defined by the Middleware Layer returns an async Future
stream.

I solve this issue by adding a tokio runtime on a separater thread that is connected with two channels.
One for sending data and one for receiving data.

Those channel are then exposed synchronously to Python. This should not be cause for
concern as channel are really fast.

Looking at Zenoh Python client, they are heavily using `pyo3-asyncio` implementation
of futures to pass Rust futures into Python.

This can be a solution as well, but, from previous experiment, I'm concerned about performance on such
solution. I have experienced that putting futures from Rust into the `asyncio` queue to be slow.

I'm concerned also by mixing `async` and `sync` code in Python, as it might be blocking. This might requires 2 threadpool in Python.
This might seem as heavy overhead for some operations.