from io import StringIO

import polars as pl

import data

d = data.load()

def property_capacities_weekdays(id: int, scrapeDate: str):
	extractions = d.extractions_propId_scrapeDate(id, scrapeDate).pl()
	df_calendar = pl.DataFrame()
	numWeeks = 0

	for row in extractions.rows(named=True):
		scrapeDate = row['created_at']
		df_calendar = pl.read_json(StringIO(row['calendar']))
		columnTitles = df_calendar.columns
		df_calendar = df_calendar.transpose()
		df_calendar = df_calendar.with_columns(pl.Series(name="dates", values=columnTitles))
		df_calendar = df_calendar.with_columns((pl.col("dates").str.to_date()))
		numWeeks = round((df_calendar.get_column("dates").max() - df_calendar.get_column("dates").min()).days / 7, 0)
		df_calendar = df_calendar.with_columns(pl.col("dates").dt.weekday().alias("weekday"))
		df_calendar = df_calendar.drop("dates")

	df_calendar = df_calendar.group_by("weekday").agg(pl.col("column_0").sum())
	df_calendar = df_calendar.with_columns((pl.col("column_0") / numWeeks).alias("weekday"))
	result = {"scraping-date": scrapeDate, "weekday": df_calendar['weekday'].to_list(), 'capacities': df_calendar['column_0'].to_list()}
	return result