import datetime
import pandas as pd
import streamlit as st
import timeago

st.set_page_config(layout="wide")
st.markdown(
    """
            <style>
                .block-container {
                    padding-top: 1rem;
                }
                #MainMenu {visibility: hidden;}
            </style>
    """,
    unsafe_allow_html=True
)

now = datetime.datetime.now()
MATCH_RESULTS_URL = "https://huggingface.co/datasets/huggingface-projects/bot-fight-data/raw/main/soccer_history.csv"


@st.cache_data(ttl=1800)
def fetch_match_history():
    """
    Fetch the match results from the last 24 hours.
    Cache the result for 30min to avoid unnecessary requests.
    Return a DataFrame.
    """
    df = pd.read_csv(MATCH_RESULTS_URL)
    df["timestamp"] = pd.to_datetime(df.timestamp, unit="s")
    df = df[df["timestamp"] >= pd.Timestamp.now() - pd.Timedelta(hours=24)]
    df.columns = ["home", "away", "timestamp", "result"]
    return df


match_df = fetch_match_history()

def num_matches_played():
    return match_df.shape[0]

teams = sorted(
    list(pd.concat([match_df["home"], match_df["away"]]).unique()), key=str.casefold
)

st.title("🤗 SoccerTwos Challenge Different Metrics - Just for Fun! - Only last 24hours of games considered")

team_results = {}
for i, row in match_df.iterrows():
    home_team = row["home"]
    away_team = row["away"]
    result = row["result"]

    if home_team not in team_results:
        team_results[home_team] = [0, 0, 0, 0]

    if away_team not in team_results:
        team_results[away_team] = [0, 0, 0, 0]

    if result == 0:
        team_results[home_team][2] += 1
        team_results[away_team][0] += 1
        team_results[home_team][3] += 1
    elif result == 1:
        team_results[home_team][0] += 1
        team_results[away_team][2] += 1
        team_results[home_team][3] += 3
    else:
        team_results[home_team][1] += 1
        team_results[away_team][1] += 1
        team_results[away_team][3] += 3

df = pd.DataFrame.from_dict(
    team_results, orient="index", columns=["wins", "draws", "losses", "points"]
).sort_values(by="points", ascending=False)
df[["owner", "team"]] = df.index.to_series().str.split("/", expand=True)
df = df[["owner", "team", "wins", "draws", "losses", "points"]]
df["win_pct"] = (df["wins"] / (df["wins"] + df["draws"] + df["losses"])) * 100

stats = df

st.header("League Table")
st.dataframe(stats)

st.subheader("Match Results")
st.write("Note: Match results are not displayed in this version of the app.")