Explore Jupyter Notebook integration

**The Idea**
For Data Science, computational notebooks are the main development environment. Durable Functions should have a story around this and maybe allow users to monitor their orchestrations via a nifty API that they can easily call on a notebook.

There might also be other interactions we would want customers to have with Durable when working on a notebook. I think this is really exciting and opens the door to augmentations of our programming model, now in a more interactive setting.

**Some Options**
- What if customers were able to schedule orchestrations directly from notebooks? What would that look like?
- What if customers wanted to visualize their orchestrations in a notebook? Notebooks these days allow for embedded HTML graphics, so this would be an interaction customers might expect and be familiar with.
- Since notebooks are interactive, maybe our programming model could evolve to be more interactive too. Here's an idea: what if we allowed users to define orchestrations in parts? Say, a customer implements a partial orchestrator in a cell, runs the code provided so far, and visualizes that result; as is common in DataSci. Then, looking at the data in that partial state, they can make an informed decision as to what transformations to run next and so they complete the orchestrator code in another cell, and the orchestrator resumes from there.

**Question to the community:**
If you are a Durable Functions for Python early adopter, and you are interested in using it for Data Science, what are some ways in which you would like to interface with Jupyter notebooks? Feel free to think big, and be creative, as I think there are opportunities for innovating here.

Inizia esaminando le interazioni con Jupyter Notebook proposte nell’issue: pianificare orchestrazioni, monitorarle tramite un’API, visualizzarle e definire orchestrazioni in modo interattivo. Prima dell’implementazione, determina quale singolo caso d’uso ha un criterio di successo concreto e identifica i punti di ingresso pertinenti della libreria Python e i test; l’issue attualmente non indica alcun file né obiettivo di test.

Scritto dal modello di indicizzazione a partire dal testo della issue.