import argparse
from collections.abc import Iterator
import datetime
import urllib.parse
from pathlib import Path

from personal_data.util import load_csv_file

from ..data import WorkSample

def iterate_samples_from_dicts(rows: list[dict]) -> Iterator[WorkSample]:
    max_title_parts = 2

    for event_data in rows:

        # Select data
        possible_time_keys = [
            k for k, v in event_data.items() if isinstance(v, datetime.date)
        ]
        possible_name_keys = [k for k, v in event_data.items() if isinstance(v, str)]
        possible_image_keys = [
            k for k, v in event_data.items() if isinstance(v, urllib.parse.ParseResult)
        ]

        possible_misc_keys = list(event_data.keys())
        for k in possible_image_keys:
            if k in possible_misc_keys:
                possible_misc_keys.remove(k)
            del k
        for k in possible_time_keys :
            if k in possible_misc_keys:
                possible_misc_keys.remove(k)
            del k

        date = event_data[possible_time_keys[0]] if possible_time_keys else None
        image = event_data[possible_image_keys[0]] if possible_image_keys else None

        if date is None:
            continue

        title = ': '.join(event_data[k] for k in possible_name_keys[:max_title_parts])
        description = '\n\n'.join(event_data[k] for k in possible_name_keys[max_title_parts:])

        labels = [f'{k}:{event_data[k]}' for k in possible_misc_keys]

        # Create event
        yield WorkSample(
            labels=tuple(labels),
            start_at=None,
            end_at=date,
        )

        del event_data

def iterate_samples_from_csv_file(file_path: Path) -> Iterator[WorkSample]:
    dicts = load_csv_file(file_path)
    yield from iterate_samples_from_dicts(dicts)