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

# Set page title and favicon
st.set_page_config(page_title="24 Hours Form Table", page_icon=":soccer:",layout="wide")


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

# Set title and create a new tab for league history
st.title("24 Hours Form Table!")
tab_team, tab_history = st.tabs(["Form Table", "Next"])

# Fetch the match results from the last 24 hours
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()

# Define a function to calculate the total number of matches played
def num_matches_played():
    return match_df.shape[0]

# Get a list of all teams that have played in the last 24 hours
teams = sorted(
    list(pd.concat([match_df["home"], match_df["away"]]).unique()), key=str.casefold
)

# Create the form table, which shows the win percentage for each team
st.header("Form Table")
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]

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

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

# Create a DataFrame from the results dictionary and calculate the win percentage
df = pd.DataFrame.from_dict(
    team_results, orient="index", columns=["wins", "draws", "losses"]
).sort_index()
df[["owner", "team"]] = df.index.to_series().str.split("/", expand=True)
df = df[["owner", "team", "wins", "draws", "losses"]]
df["win_pct"] = (df["wins"] / (df["wins"] + df["draws"] + df["losses"])) * 100

# Display the DataFrame as a table, sorted by win percentage
stats = df.sort_values(by="win_pct", ascending=False)
styled_stats = stats.style.set_table_attributes("style='font-size: 20px'").set_table_styles([dict(selector='th', props=[('max-width', '200px')])])
styled_stats = styled_stats.set_table_attributes("style='max-height: 1200px; overflow: auto'")
st.dataframe(styled_stats)

# Create a new tab for league history over time
with tab_history:
    st.write("Coming soon!")