DAY REFACTORY - TS PYTHON RECURUTISIVE AND TYPES

In this article, we explore an elegant and efficient Python solution to convert empty strings to an arbitrary value within nestled data structures (dictionaries and lists). The original TypeScript solution, although functional, inspired a more concise and "pythonica" approach using recursion and comprehension .

Initially, the need came when dealing with three distinct files containing different python nestled data structures. The search for a generic solution has led to the development of a recursive function that runs through the data structure, replacing empty strings with a standard value ("unconstrated" in the example).

The first version of the Python function used explicit loops to iterate about dictionaries and lists. However, the evolution to dictionary Comphension and List Comprahension resulted in a significantly more compact and readable code, maintaining the same recursive logic.

The final solution in Python:

<code class="language-python">def substituir_strings_vazias(dados):
    if isinstance(dados, dict):
        return {k: substituir_strings_vazias(v) for k, v in dados.items()}
    elif isinstance(dados, list):
        return [substituir_strings_vazias(item) for item in dados]
    elif isinstance(dados, str) and dados == "":
        return "NAO_ENCONTRADO"
    return dados

dados = {
    "nome": "",
    "idade": 25,
    "endereco": {
        "rua": "",
        "cidade": "São Paulo",
        "estado": ""
    },
    "contatos": ["", "email@example.com"]
}

dados_convertidos = substituir_strings_vazias(dados)
print(dados_convertidos)</code>

How it works:

The function

is recursive. She checks the type of data received: substituir_strings_vazias

1. Dictionary: If it is a dictionary, it uses dictionary comprehension to create a new dictionary where each value is recursively processed by the same function.

2. List:

   If it is a list, it uses List Composition to create a new list where each item is recursively processed. >

3. Empty string:

   If it is an empty string, it returns "unconstrated".

4. Other types:

   For any other type of data, it returns the original data without modifications.

   Recursion ensures that the function processes all nestled levels of the data structure. Python code conciseness, thanks to
Comphension

, highlights the elegance and efficiency of the solution compared to the original TypeScript version. The function becomes highly reusable for the normalization of datasets with null or empty values. The difference between final python approaches and the initial TypeScript is remarkable, demonstrating the power of the tools available in Python to deal with this type of problem.

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