src/queries/nflverse/github_data.py

import duckdb
import pandas as pd
import os
import streamlit as st
from typing import Callable

from domain.constants import SEASON


duckdb.default_connection.execute("SET GLOBAL pandas_analyze_sample=100000")

BASE_URL = "https://github.com/nflverse/nflverse-data/releases/download/"


FANTASY_POSITIONS = [
    "QB",
    "RB",
    "WR",
    "TE",
    "FB",
    "K",
]


def get_weekly_rosters(season_int: int | str = SEASON) -> pd.DataFrame:
    df = duckdb.sql(
        f"""
                    with grouped_stats as (
                    select player_id, sum(fantasy_points) as fantasy_points
                    from player_stats_player_stats_{season_int}
                    group by player_id
                    )
                    SELECT 
                    team
                    , wr.position
                    , wr.jersey_number
                    , wr.status
                    , wr.full_name
                    , wr.headshot_url
                    , wr.week
                    , wr.gsis_id
                    , gs.fantasy_points
                    from weekly_rosters_roster_weekly_{season_int} wr
                    left join grouped_stats gs
                    on wr.gsis_id = gs.player_id
"""
    ).df()
    return df


def get_player_stats(season_int: int | str = SEASON) -> pd.DataFrame:
    df = duckdb.sql(
        f"""SELECT 
                    player_id
                    , recent_team as team
                    , week
                    , passing_tds
                    , passing_yards
                    , passing_2pt_conversions
                    , sack_fumbles_lost
                    , interceptions
                    , rushing_tds
                    , rushing_yards
                    , rushing_2pt_conversions
                    , rushing_fumbles_lost
                    , receptions
                    , receiving_tds
                    , receiving_yards
                    , receiving_2pt_conversions
                    , receiving_fumbles_lost
                    , special_teams_tds 
                    from player_stats_player_stats_{season_int}"""
    ).df()
    return df


def get_player_kicking_stats(season_int: int | str = SEASON) -> pd.DataFrame:
    df = duckdb.sql(
        f"""SELECT
                    player_id
                    , week
                    , pat_made
                    , fg_made_0_19
                    , fg_made_20_29
                    , fg_made_30_39
                    , fg_made_40_49
                    , fg_made_50_59
                    , fg_made_60_
                    from player_stats_player_stats_kicking_{season_int}"""
    ).df()
    return df.fillna(0.0)


def get_team_defense_stats(season_int: int | str = SEASON) -> pd.DataFrame:
    df = duckdb.sql(
        f"""
        select
            week
            , team
            , sum(def_sacks) as def_sacks
            , sum(def_interceptions) as def_interceptions
            , sum(def_tds) as def_tds
            , sum(def_fumble_recovery_opp) as def_fumble_recovery_opp
            , sum(def_safety) as def_safety
        from player_stats_player_stats_def_{season_int}
        group by week, team
        """
    ).df()
    return df


NFLVERSE_ASSETS = [
    ("weekly_rosters", f"roster_weekly_{SEASON}.parquet"),
    ("player_stats", f"player_stats_{SEASON}.parquet"),
    ("player_stats", f"player_stats_kicking_{SEASON}.parquet"),
    ("player_stats", f"player_stats_def_{SEASON}.parquet"),
]


class NflVerseDataAsset:
    def __init__(
        self,
        release_tag: str,
        asset_name: str,
        dataframe_mutation_fxn: Callable[[pd.DataFrame], pd.DataFrame] = lambda x: x,
    ):
        self.release_tag = release_tag
        self.asset_name = asset_name
        self.dataframe_mutation_fxn = dataframe_mutation_fxn
        self.table_name = f"{release_tag}_{asset_name.rsplit('.', 1)[0]}"

    def load_parquet_asset_to_df(self) -> pd.DataFrame:
        location = os.path.join(BASE_URL, self.release_tag, self.asset_name)
        df = pd.read_parquet(location)
        return df

    def register_asset_to_duckdb(self) -> None:
        df = self.load_parquet_asset_to_df()
        df = self.dataframe_mutation_fxn(df)
        duckdb.register(self.table_name, df)


@st.cache_data(ttl=60 * 60 * 24)
def load_assets():
    for tag, asset in NFLVERSE_ASSETS:
        asset = NflVerseDataAsset(tag, asset)
        asset.register_asset_to_duckdb()


def get_current_tables() -> list[str]:
    current_tables_df = duckdb.sql("SHOW TABLES").df()
    return current_tables_df["name"].tolist()