If a function is very extensive, is it advisable to divide it into smaller ones?

Hello,

Splitting a function or not is not always tied to its size, but usually to the processing steps it has.

In your example, we clearly have repetitive code and can be separated into smaller specialized functions.

A simplified modification proposal follows:

def get_dataframe(site, search):
    try:
        if site == 'pichau':
            product, price_boleto, price_cartao = pichau(search)
        elif site == 'chipart':
            product, price_boleto, price_cartao = chipart(search)
        else:
            # Se for possivel ter outro valor para site

        data = {'Produto': product, 'Preço à vista': price_boleto, 'Preço cartão': price_cartao}
        product_df = DataFrame(data)
        return product_df

    except Exception as e:
        return 'Problema com a conexão entre o site!'

def pichau(search):
    soup = get_page(f'https://www.pchau.com.br/catalogsearch/result/?q={search}')
    assert soup

    price_cartao = [i.getText() for i in soup.select('.other .valor')]
    price_boleto = [i.getText().replace('à vista', '') for i in soup.select('.boleto .valor')]
    product = [i.get('title').upper() for i in soup.select('.title a')][:len(price_cartao)]

    return product, price_boleto, price_cartao

def chipart(search):
    soup = get_page(f'https://www.chipart.com.br/produtos/{search}')
    assert soup

    price_boleto = [i.getText() for i in soup.select('.products__list__item .product-card__price__final .price')]
    price_cartao1 = [i.getText().strip().replace('\t', '').replace('\n', '').replace('em', '') for i in soup.select('.products__list__item .installments')]
    price_cartao2 = [i.getText() for i in soup.select('.products__list__item .price-installments .price')]
    product = [i.getText().strip().replace('\t', '').replace('\n', '') for i in soup.select('.product-card__title .title')][:len(price_boleto)]
    price_cartao = [f'{price_cartao1[i]} de {price_cartao2[i]}' for i in range(len(price_boleto))]

    return product, price_boleto, price_cartao

Note that the get_dataframe function is much simpler and more readable. What, depending on the size of the project, makes it infinitely easier to maintain and improve.

The return part of the subfunctions pichau and chipart is at your discretion. Here I preferred to return the separated objects to avoid repetition of code. If you prefer, you can either return a dataframe or a dictionary.

Separate them into modules. The good part of python is that you can instantiate them only in import.

Depending on the case, extend the parameters and reuse a function for different tasks.