Prepared Day-ahead prices request for use in Async Frameworks

[JrtPec]

As proposed in #315.

This PR introduces a method that Prepares the day-ahead prices request, without sending it. This allows you to defer the handling of that request to another system.
Next, I have isolated the parsing of the pricing response, so it can also be used in a stand-alone way.

Here's an example of how you could use this to request data using aiohttp:

import aiohttp
import pandas as pd

from entsoe import EntsoePandasClient
from entsoe.mappings import lookup_area
from entsoe.parsers import parse_prices

from settings import api_key

client = EntsoePandasClient(api_key=api_key)

start = pd.Timestamp('2024-01-01', tz='Europe/Brussels')
end = pd.Timestamp('2024-01-02', tz='Europe/Brussels')
area = lookup_area('BE')

prepared_request = client.prepare_query_day_ahead_prices(country_code=area, start=start, end=end)

async with aiohttp.ClientSession() as session:
    response = await session._request(
        method='GET',
        str_or_url=prepared_request.url
    )
    response.raise_for_status()
    text = await response.text()

series = parse_prices(
    xml_text=text,
    tz=area.tz,
    resolution='60min',
    start=start,
    end=end
)

[fleimgruber]

How much context does the parse_prices need from the user in this scenario and what parts could be inferred? I am looking at resolution='60min' specifically. Would having a matching client.parse_query_day_ahead_prices(xml_plus_metadata_from_async) be an option? That would again introduce more API surface, but might be better if some of the query functions require different contexts?

In any case, I would be happy to contribute tests for this, following along #131.

[fboerman]

interesting idea! thanks for the work. I have added a design question to discuss