158 lines
5.1 KiB
Python
158 lines
5.1 KiB
Python
import json
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from dataclasses import dataclass
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from datetime import datetime
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from datetime import date
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from datetime import timedelta
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from models.HabitTracking import HabitTracking
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from db.SQLiteClient import (create_habit, get_habit, update_habit, delete_habit, get_next_slot, get_slots, update_slot,
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get_habitTrackings, get_habitList)
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# unit will be represented by integers like this:
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# 0: day
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# 1: week (default)
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# 2: month
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# 3: year
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@dataclass
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class Habit:
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id: int
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list_id: int
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name: str
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note: str
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times: int
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unit: int
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slot: int
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percentage: int = 0
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streak: int = 0
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def __post_init__(self):
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self.fill_statistics()
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@staticmethod
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def create(list_id: int, name: str, times: int, note: str = None, unit: int = 1):
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slot = get_next_slot(list_id)
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id = create_habit(list_id, name, note, times, unit, slot)
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return Habit(id, list_id, name, note, times, unit, slot)
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@staticmethod
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def get(id: int):
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habit = get_habit(id)
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return Habit(habit[0], habit[1], habit[2], habit[3], habit[4], habit[5], habit[6]) if habit else None
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# Updates: name, note, times, unit
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def update(self):
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update_habit(self.id, self.name, self.note, self.times, self.unit)
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# Updates the slot and reorders the HabitList accordingly
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def update_slot(self, new_slot: int):
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# Fetches a list with the following structure [(id, slot), (id, slot), ...]
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slots = get_slots(self.list_id)
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# Splits the list depending on whether the new slot is higher or lower than the current one
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if new_slot > self.slot: # Example self.slot=1 new_slot=4
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slots = slots[self.slot:new_slot] # Expected list: [(id, 2), (id, 3), (id, 4)]
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for slot in slots:
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update_slot(slot[0], slot[1]-1)
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if new_slot < self.slot: # Example self.slot=4 new_slot=1
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slots = slots[new_slot-1:self.slot-1] # Expected list: [(id, 1), (id, 2), (id, 3)]
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for slot in slots:
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update_slot(slot[0], slot[1]+1)
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# Update the slot of the current habit
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update_slot(self.id, new_slot)
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# Deletes the Habit
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def delete(self):
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# Reorders the slots
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slots = get_slots(self.list_id)[self.slot+1:]
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for slot in slots:
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update_slot(slot[0], slot[1] - 1)
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# Deletes all track-records associated with the Habit
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trackings = self.get_habitTrackings()
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for tracking in trackings:
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tracking.delete()
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# Deletes the current Habit
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delete_habit(self.id)
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# Returns all track-records for a Habit
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def get_habitTrackings(self) -> list:
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trackings = []
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for rawTracking in get_habitTrackings(self.id):
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trackings.append(HabitTracking(rawTracking[0], rawTracking[1],
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datetime.strptime(rawTracking[2], "%Y-%m-%dT%H:%M:%S.%f")))
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return trackings
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# Returns the HabitList in which the Habit is located
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def habit_list(self) -> list:
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from models.HabitList import HabitList
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raw_habitLists = get_habitList(self.list_id)
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return HabitList(raw_habitLists[0], raw_habitLists[1], raw_habitLists[2]) if raw_habitLists else None
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def getStreak(self):
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trackings = []
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for rawTracking in get_habitTrackings(self.id):
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trackings.append(datetime.strptime(rawTracking[2], "%Y-%m-%d"))
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trackings.sort(reverse=True)
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current_date = date.today()
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yesterdate = date.today() - timedelta(days=1)
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if not trackings:
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return self.streak
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# bisherige streak zurückgeben, falls nicht vorhanden bei null starten
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if self.streak != 0 and (current_date == trackings[0] or yesterdate == trackings[0]):
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return self.streak
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else:
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self.streak = 0
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return self.streak
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def removeStreak(self):
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self.streak -= 1
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return
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def addStreak(self):
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self.streak += 1
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return
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# Saves the progress of the Habit in the attribute percentage
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def fill_statistics(self):
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count = 0
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self.checked = False
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for tracking in self.get_habitTrackings():
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if tracking.created_at.date() == datetime.today().date():
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self.checked = True
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# day
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if self.unit == 0:
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if tracking.created_at.date() == datetime.today().date():
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count += 1
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# week
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elif self.unit == 1:
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if tracking.created_at.isocalendar()[1] == datetime.today().isocalendar()[1]:
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count += 1
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# month
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elif self.unit == 2:
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if tracking.created_at.month == datetime.today().month:
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count += 1
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# year
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elif self.unit == 3:
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if tracking.created_at.year == datetime.today().year:
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count += 1
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self.percentage = int(count / self.times * 100)
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def to_json(self):
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return json.dumps(self, default=lambda o: o.__dict__, sort_keys=True, indent=4)
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