In the last text, we ended with a loose idea of what our input and output JSONs could look like.
I went further and asked an LLM to model those requirements in JSON format, so that things were even clearer. Let's see if this helps us?
{ "nomeCampeonato": "String", "equipes": [ { "id": "Integer", "nome": "String", "localizacao": "String", "grupo": "String", "subGrupo: "String" }, ... ], "formatoCampeonato": { "divisaoPorGrupos": Integer, "grupos": [ { "id": "Integer", "nome": "String", "equipes": ["Integer"], }, ], "turnosDentroGrupo": "Integer", "turnosEntreGrupos": "Integer", "sorteioGrupos": "Boolean" }, "calendarioConfig": { "tabelaOtimizada": "Boolean", "totalJogosPorDia": "Integer", "diasDescanso": "Integer" } }
Let's understand what LLM brought us:
Well, if you've studied object orientation a little, you know that these JSON objects that we model here are great candidates for becoming classes in our code, right?
In the next text, we will analyze whether each JSON object like this is eligible to generate a class in our backend and we will also talk a little about the architecture of our Tabelão.
We continue.
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