src/pages/3_Draft_View.py

import json
import os
import pandas as pd
import requests
import streamlit as st

from config import DEFAULT_ICON, SEASON
from login_component import is_token_in_session
from shared_page import common_page_config
from streamlit_filter import filter_dataframe


HARDCODED_KEEPERS_YAHOO_ID = {
    2025: [
        "40908",
        "40168",
        "30971",
        "40899",
        "40883",
        "40993",
        "32703",
        "40196",
        "40878",
        "40881",
        "40875",
        "40118",
        "33967",
        "34007",
        "31840",
        "41048",
        "30259",
        "40063",
        "40889",
        "40059",
        "31833",
        "40905",
        "40890",
        "40877",
        "33399",
        "32685",
        "40896",
        "40041",
        "33514",
        "30994",
        "34120",
        "40084",
        "34010",
    ]
}


@st.cache_data(ttl=60 * 60 * 24)
def load_yahoo_to_fp_id_map() -> dict[str, str]:
    df = pd.read_csv(r"https://raw.githubusercontent.com/dynastyprocess/data/master/files/db_playerids.csv")
    for id_col in ["yahoo_id", "fantasypros_id"]:
        df[id_col] = df[id_col].fillna(-9999).apply(lambda x: str(int(x)))

    player_id_dict = df.set_index("yahoo_id")["fantasypros_id"].to_dict()
    # map team DST
    player_id_dict.update(
        {
            "100022": "8000",  # Arizona
            "100001": "8010",  # Atlanta
            "100033": "8020",  # Baltimore
            "100002": "8030",  # Buffalo
            "100029": "8040",  # Carolina
            "100003": "8050",  # Chicago
            "100004": "8060",  # Cincinnati
            "100005": "8070",  # Cleveland
            "100006": "8080",  # Dallas
            "100007": "8090",  # Denver
            "100008": "8100",  # Detroit
            "100009": "8110",  # Green Bay
            "100034": "8120",  # Houston
            "100011": "8130",  # Indianapolis
            "100030": "8140",  # Jacksonville
            "100012": "8150",  # Kansas City
            "100013": "8220",  # Las Vegas
            "100014": "8280",  # Los Angeles Rams
            "100024": "8250",  # Los Angeles Chargers
            "100015": "8160",  # Miami
            "100016": "8170",  # Minnesota
            "100017": "8180",  # New England
            "100018": "8190",  # New Orleans
            "100019": "8200",  # New York Giants
            "100020": "8210",  # New York Jets
            "100021": "8230",  # Philadelphia
            "100023": "8240",  # Pittsburgh
            "100025": "8270",  # San Francisco
            "100026": "8260",  # Seattle
            "100027": "8290",  # Tampa Bay
            "100010": "8300",  # Tennessee
            "100028": "8310",  # Washington
        }
    )
    return player_id_dict


def load_depth_charts():
    df = pd.read_csv(os.path.join(os.path.dirname(__file__), "../../tests/mocks/2024 Depth Charts - formatted.csv"))
    df["yahoo_id"] = df["yahoo_id"].apply(lambda x: str(int(x)))
    df["fp_id"] = df["yahoo_id"].apply(lambda x: load_yahoo_to_fp_id_map().get(x, x))
    return df


def extract_ecr_var_data(request_text_str, var_name: str):
    start_str = f"""var {var_name} = """
    end_str = """};"""
    end_offset = 1  # include closing bracket

    start_slice_pos = request_text_str.find(start_str) + len(start_str)
    first_slice = request_text_str[start_slice_pos:]
    end_slice_pos = first_slice.find(end_str) + end_offset
    dom_str = first_slice[:end_slice_pos]
    var_json = json.loads(dom_str)
    return var_json


@st.cache_data(ttl=60 * 60 * 24)
def load_ecr_data():
    request_text = get_ecr_request_text()
    ecr_data = extract_ecr_var_data(request_text, "ecrData")
    ecr_columns = [
        "player_id",
        "player_name",
        "player_position_id",
        "player_team_id",
        "player_bye_week",
        "rank_ecr",
        "pos_rank",
        "tier",
    ]
    df_ecr = pd.DataFrame(ecr_data["players"])[ecr_columns]
    df_ecr["rank_ecr"] = df_ecr["rank_ecr"].astype(int)
    df_ecr["player_id"] = df_ecr["player_id"].apply(lambda x: str(int(x)))

    # sos_data = extract_ecr_var_data(request_text, "sosData")
    # adp_data = extract_ecr_var_data(request_text, "adpData")
    return df_ecr


@st.cache_data(ttl=60 * 60 * 24)
def get_ecr_request_text():
    r = requests.get("https://www.fantasypros.com/nfl/rankings/half-point-ppr-cheatsheets.php")
    return r.text


@st.cache_resource(ttl=60 * 60 * 24)
def get_league_settings_with_cache(selected_league):
    return st.session_state.yahoo_client.parse_league_settings(selected_league)


def highlight_drafted(data_row_series):
    return ["background-color: salmon" if data_row_series.is_drafted else "" for _ in range(len(data_row_series))]


def display_formatted_tiers(df):
    st.dataframe(
        df.sort_values("rank_ecr").style.apply(highlight_drafted, axis=1),
        hide_index=True,
        height=35 * (len(df) + 1) + 5,
        column_order=[
            "rank_ecr",
            "player_name",
            # "player_position_id",
            "player_bye_week",
            # "tier",
            # "is_drafted",
            "player_team_id",
        ],
        column_config={
            "player_name": st.column_config.TextColumn(label="", help="Player's name"),
            "player_position_id": st.column_config.TextColumn(label="", help="Player's position"),
            "player_bye_week": st.column_config.NumberColumn(label="Bye", help="Player's Bye Week"),
            "rank_ecr": st.column_config.NumberColumn(label="Rank", help="Player ECR Rank"),
            "tier": st.column_config.NumberColumn(label="Tier", help="Player Tier"),
            "is_drafted": st.column_config.CheckboxColumn(label="Drafted", help="Has been drafted"),
            "player_team_id": st.column_config.TextColumn(label="Tm"),
        },
        use_container_width=True,
    )


def get_page():
    page_title = "Yahoo Draft Live Summary"
    st.set_page_config(page_title=page_title, page_icon=DEFAULT_ICON, layout="wide")
    common_page_config()
    st.title(page_title)

    if not (is_token_in_session() and st.session_state.get("user_admin")):
        st.write("Exclusive feature")

    else:
        selected_season = st.selectbox("Select Season", list(range(SEASON, 2012, -1)))
        user_leagues = st.session_state.yahoo_client.find_all_leagues_for_logged_in_user(season=selected_season)
        selected_league = st.selectbox("Select league", user_leagues)
        league_settings = get_league_settings_with_cache(selected_league)
        st.header(f"{league_settings.name} - {league_settings.season}")
        with st.expander("Show Positions"):
            st.dataframe(
                pd.DataFrame(league_settings.roster_positions).set_index("position")["count"],
            )

        draft_result = st.session_state.yahoo_client.get_draft(selected_league)
        if st.button("Load / Refresh"):
            draft_result = st.session_state.yahoo_client.get_draft(selected_league)
        if "player_key" in draft_result:
            draft_result["player_id"] = draft_result["player_key"].apply(lambda x: x.rsplit(".", 1)[-1] if x else x)
        else:
            draft_result["player_id"] = ""
        draft_result["fp_id"] = draft_result["player_id"].apply(lambda x: load_yahoo_to_fp_id_map().get(x, x))

        ecr_data = load_ecr_data()
        draft_result_merge_cols = [
            "fp_id",
            "team_key",
            "round",
            "pick",
        ]
        for col in draft_result_merge_cols:
            if col not in draft_result:
                draft_result[col] = ""
        ecr_with_draft = ecr_data.merge(
            draft_result[draft_result_merge_cols], how="outer", left_on="player_id", right_on="fp_id"
        )

        keepers_fp_id_list = [load_yahoo_to_fp_id_map().get(x, x) for x in HARDCODED_KEEPERS_YAHOO_ID.get(SEASON, [])]
        ecr_with_draft["is_drafted"] = ecr_with_draft["fp_id"].notna() | ecr_with_draft["player_id"].isin(
            keepers_fp_id_list
        )

        # depth_charts = load_depth_charts()
        # ecr_with_draft = ecr_with_draft.merge(depth_charts, how="left", left_on="player_id", right_on="fp_id")

        if ("round" in ecr_with_draft) and ("pick" in ecr_with_draft):
            draft_picks_only = ecr_with_draft[ecr_with_draft.is_drafted].sort_values(["round", "pick"])

        with st.expander("Show Draft Results"):

            pos_pivot_df = draft_picks_only.pivot_table(
                values="player_id", columns="player_position_id", index="team_key", aggfunc="count", margins=True
            )
            st.dataframe(pos_pivot_df, use_container_width=True)

            if st.checkbox("Full Results"):
                st.dataframe(draft_picks_only)

        with st.expander("Unmatched"):
            st.dataframe(ecr_with_draft[ecr_with_draft.player_name.isna()])

        st.header("ECR Tiers")
        with st.expander("Filters"):
            filtered_data = filter_dataframe(
                ecr_with_draft,
                force_on=True,
                force_on_columns=["is_drafted", "player_position_id", "player_team_id"],
            )

        position_list = [
            x for x in ["QB", "RB", "WR", "TE", "DST", "K"] if x in filtered_data.player_position_id.unique()
        ]

        if not st.checkbox("Show DST/K"):
            position_list = [x for x in position_list if x not in ["DST", "K"]]

        if st.checkbox("Show Overall"):
            position_list = ["OVERALL"]

        columns_list = st.columns(len(position_list))
        for pos, col in zip(position_list, columns_list):
            with col:
                st.header(pos)
                if pos == "OVERALL":
                    df_pos = filtered_data
                else:
                    df_pos = filtered_data[filtered_data.player_position_id == pos]
                for tier, df_tier in df_pos.groupby("tier"):
                    st.header(f"Tier {tier}")
                    display_formatted_tiers(df_tier)


if __name__ == "__main__":
    get_page()