Consider a web service API that returns a complex Json object. Using the stock Python tools for the job, this will read in from the web service as a dict which contains, in turn, a mixture of arrays, dicts, strings, and numbers.

I confess: this data is born in Java. In Java, there's a data model for this data. My question is, would dyed-in-the-wool Python programmers desire a Python class data model that adds some notational niceness, or would they expect to just be handed the situation described in the first paragraph.

In code terms, what's the value of:

 text.tokens[3].part_of_speech

as opposed to:

 text['tokens'][3]['part_of_speech']

?

Consider a web service API that returns a complex Json object. Using the stock Python tools for the job, this will read in from the web service as a dict which contains, in turn, a mixture of arrays, dicts, strings, and numbers.

I confess: this data is born in Java. In Java, there's a data model for this data. My question is, would dyed-in-the-wool Python programmers desire a Python class data model that adds some notational niceness, or would they expect to just be handed the situation described in the first paragraph.

In code terms, what's the value of:

 text.tokens[3].part_of_speech

as opposed to:

 text['tokens'][3]['part_of_speech']

?

Based on some comments, I want to expand this a little. What I wrote above is all about consuming a complex data structure that arrives in Python as Json, and I can see that 'sugaring' it with a pile of classes with @property markers is not very helpful.

Another side of the coin is assembling one of these. As, admittedly, a person who has spent a lot more time in Java, C++, C (and Lisp?) than in Python, I would tend to see value in some API that helps me remember the names of all the bits and pieces. So maybe that suggests simply providing constants that provide the defined keys?