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from dataclasses import dataclass
import datetime
import re
from dataclass_defs import ProcessedRow, SheetsRow
INTERVAL_ABBREVS = {
"pv": datetime.timedelta(days=1),
"vk": datetime.timedelta(days=7),
"kk": datetime.timedelta(days=30),
"v": datetime.timedelta(days=365),
}
def _calculate_interval(interval_str: str):
match = re.search(r"(\d+)(\w+)", interval_str)
number = int(match[1])
abbrev = match[2]
try:
interval = INTERVAL_ABBREVS[abbrev]
except KeyError:
raise Exception(f'"{interval_str}" is an invalid interval string!')
total_interval = datetime.timedelta(seconds=interval.total_seconds() * number)
return total_interval
def _timestamp_to_date(timestamp: str) -> datetime.datetime:
return datetime.datetime.strptime(timestamp, "%Y-%m-%d")
def _date_to_timestamp(date: datetime.datetime) -> str:
return datetime.datetime.strftime(date, "%Y-%m-%d")
def _process_row(row: SheetsRow):
interval = _calculate_interval(row.interval)
last_done_date = _timestamp_to_date(row.last_done)
next_date = last_done_date + interval
next_date_str = _date_to_timestamp(next_date)
return ProcessedRow(
name=row.name,
next_datestamp=next_date_str,
next_date=next_date,
last_datestamp=row.last_done,
last_date=last_done_date,
interval=row.interval,
)
def process_rows(rows: list[SheetsRow]) -> list[ProcessedRow]:
return list(map(_process_row, rows))
def _is_this_week(processed_row: ProcessedRow):
next_date = processed_row.next_date
now = datetime.datetime.now()
return (next_date - now) < datetime.timedelta(weeks=1)
def filter_only_this_week(rows: list[ProcessedRow]) -> list[ProcessedRow]:
return list(filter(_is_this_week, rows))
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