diff --git a/experiments/aggregated_hotness/aggregated_hotness/__init__.py b/experiments/aggregated_hotness/aggregated_hotness/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3dc1f76bc69e3f559bee6253b24fc93acee9e1f9 --- /dev/null +++ b/experiments/aggregated_hotness/aggregated_hotness/__init__.py @@ -0,0 +1 @@ +__version__ = "0.1.0" diff --git a/experiments/aggregated_hotness/aggregated_hotness/hotness.py b/experiments/aggregated_hotness/aggregated_hotness/hotness.py new file mode 100644 index 0000000000000000000000000000000000000000..cb19925729e4ea8043a8feefabe30db239643ef6 --- /dev/null +++ b/experiments/aggregated_hotness/aggregated_hotness/hotness.py @@ -0,0 +1,73 @@ +from datetime import timezone +from itertools import groupby +from pathlib import Path +import numpy as np +import pandas as pd +from pytility import parse_date + + +def load_daily_hotness( + path_dir, + start_date, + end_date, + glob="*.csv", + index_col="bgg_id", +): + path_dir = Path(path_dir).resolve() + start_date = parse_date(start_date, tzinfo=timezone.utc) + end_date = parse_date(end_date, tzinfo=timezone.utc) + + for date, group in groupby( + sorted( + (date, path_file) + for path_file in path_dir.glob(glob) + if start_date + <= (date := parse_date(path_file.stem, tzinfo=timezone.utc)) + < end_date + ), + key=lambda x: x[0].date(), + ): + _, path_file = min(group) + series = pd.read_csv(path_file, index_col=index_col)["rank"] + yield series.rename(date.isoformat()) + + +def _compute_scores( + path_dir, + start_date, + end_date, + top=None, +): + result = pd.concat( + objs=load_daily_hotness( + path_dir=path_dir, + start_date=start_date, + end_date=end_date, + ), + axis=1, + ) + + if top: + return pd.Series( + { + bgg_id: np.exp2(1 - ranks.sort_values().head(top)).sum() / top + for bgg_id, ranks in result.T.items() + } + ) + + full_scores = 2 ** (1 - result) + return full_scores.sum(axis=1) / result.shape[1] + + +def aggregate_hotness( + path_dir, + start_date, + end_date, + top=None, +): + return _compute_scores( + path_dir=path_dir, + start_date=start_date, + end_date=end_date, + top=top, + ).sort_values(ascending=False) diff --git a/experiments/aggregated_hotness/aggregated_hotness/utils.py b/experiments/aggregated_hotness/aggregated_hotness/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..17ad268ac7fb3311dcbf4c52f87d19c1a035bab9 --- /dev/null +++ b/experiments/aggregated_hotness/aggregated_hotness/utils.py @@ -0,0 +1,31 @@ +from itertools import tee +from dateutil.rrule import MONTHLY, WEEKLY, YEARLY, rrule +from snaptime import snap + + +def pairwise(iterable): + it1, it2 = tee(iterable) + next(it2, None) + return zip(it1, it2) + + +def gen_start_and_end_dates(min_date, max_date, freq): + if freq == "week": + instruction = "@week1" # previous Monday + freq = WEEKLY + elif freq == "month": + instruction = "@month" # beginning of the month + freq = MONTHLY + elif freq == "year": + instruction = "@year" # beginning of the year + freq = YEARLY + else: + raise ValueError(f"Unknow frequency <{freq}>") + + return pairwise( + rrule( + dtstart=snap(min_date, instruction), + until=max_date, + freq=freq, + ) + ) diff --git a/experiments/aggregated_hotness/hotness.py b/experiments/aggregated_hotness/hotness.py new file mode 100644 index 0000000000000000000000000000000000000000..98833b40d5f843b00cf76c8d0b483e6f9994884d --- /dev/null +++ b/experiments/aggregated_hotness/hotness.py @@ -0,0 +1,59 @@ +# --- +# jupyter: +# jupytext: +# formats: ipynb,py:percent +# text_representation: +# extension: .py +# format_name: percent +# format_version: '1.3' +# jupytext_version: 1.16.1 +# kernelspec: +# display_name: Python 3 (ipykernel) +# language: python +# name: python3 +# --- + +# %% +from datetime import datetime, timedelta +from pathlib import Path +import jupyter_black +import pandas as pd +from pytility import parse_date +from aggregated_hotness.hotness import aggregate_hotness + +jupyter_black.load() + + +# %% +def hot_games( + games_path=Path("../../../board-game-data/scraped/bgg_GameItem.csv").resolve(), + hot_dir=Path("../../../board-game-data/rankings/bgg/hotness/").resolve(), + start_date=datetime.utcnow() - timedelta(days=60), + end_date=datetime.utcnow(), + top=30, +): + games = pd.read_csv( + games_path, + index_col="bgg_id", + low_memory=False, + ) + hotness = aggregate_hotness( + path_dir=hot_dir, + start_date=start_date, + end_date=end_date, + top=top, + ).rename("hotness") + return ( + games[["name"]] + .join(hotness, how="right") + .sort_values("hotness", ascending=False) + ) + + +# %% +results = hot_games( + start_date=parse_date("2024-02-01T00:00Z"), + end_date=parse_date("2024-04-01T00:00Z"), + top=30, +) +results.head(50) diff --git a/experiments/aggregated_hotness/poetry.lock b/experiments/aggregated_hotness/poetry.lock new file mode 100644 index 0000000000000000000000000000000000000000..a3657539e256160c25e849d521afff78a3fc8e6e --- /dev/null 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