Created timeline statistic

src/classes/statistic_classes.py

@@ -1,15 +1,21 @@
 from pydantic import BaseModel
-from typing import Union
+from typing import Union, Dict
+from datetime import date
 
 from src.classes import boardgame_classes
 
-class NumberStatistic(BaseModel):
+class StatisticBase(BaseModel):
     name: str
+
+class NumberStatistic(StatisticBase):
     result: float
 
-class GameOrderStatistic(BaseModel):
-    name: str
+class GameOrderStatistic(StatisticBase):
     result: list[Union[
         boardgame_classes.BoardGame, boardgame_classes.BoardGameExpansion,
         boardgame_classes.OwnedBoardGame, boardgame_classes.OwnedBoardGameExpansion,
         boardgame_classes.WishlistBoardGame, boardgame_classes.WishlistBoardGameExpansion]]
+
+
+class TimeLineStatistic(StatisticBase):
+    result: Dict[date, int]

src/main.py

@@ -1,4 +1,5 @@
 from typing import Union
+from datetime import date, timedelta
 
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
@@ -76,6 +77,32 @@ def get_amount_of_games():
 
     return statistic_to_return
 
+@app.get('/statistics/amount_of_games_over_time', response_model=statistic_classes.TimeLineStatistic)
+def get_amount_of_games_over_time():
+
+    def daterange(start_date: date, end_date: date):
+        days = int((end_date - start_date).days)
+        for n in range(days):
+            yield start_date + timedelta(n)
+
+    games_in_owned_collection = data_connection.get_user_owned_collection()
+    games_in_owned_collection.sort(key=lambda x: x.acquisition_date)
+
+    timeline_dict = {}
+
+    for current_date in daterange(games_in_owned_collection[0].acquisition_date, date.today()):
+        games_in_collection_at_date = list(filter(lambda game: game.acquisition_date <= current_date, games_in_owned_collection))
+        timeline_dict[current_date] = len(games_in_collection_at_date)
+    
+    statistic_dict = {
+        "name":"Amount of games in owned collection over time",
+        "result":timeline_dict
+    }
+
+    statistic_to_return = statistic_classes.TimeLineStatistic(**statistic_dict)
+
+    return statistic_to_return
+
 
 @app.get('/statistics/most_expensive_games', response_model=statistic_classes.GameOrderStatistic)
 def get_most_expensive_game(top_amount: int = 10):