import streamlit as st
import pandas as pd
import wandb
import datetime


def get_all_competition_summary(api, projects):
    
    number_of_competitions = 0
    number_of_runs = 0
    
    for project in projects:
        entity = projects[project]["entity"]
        project_name = projects[project]["project"]
        runs = api.runs(f"{entity}/{project_name}")
        number_of_competitions += 1
        number_of_runs += len(runs)
        
    return number_of_competitions,number_of_runs

def fetch_competition_summary(api, projects, selected_project):
    data = []
        
    entity = projects[selected_project]["entity"]
    project = projects[selected_project]["project"]
    
    runs = api.runs(f"{entity}/{project}")
    
    for run in runs:
        try:
            summary = run.summary
            if summary.get("validator_id") and summary.get("winning_hotkey"):
                data.append({
                    "ID": run.id,
                    "Validator ID": summary.get("validator_id"),
                    "Winning Hotkey": summary.get("winning_hotkey"),
                    "Run Time (s)": summary.get("run_time_s"),
                    "Created At": run.created_at,
                })
        except Exception as e:
            st.write(f"Error processing run {run.id}: {str(e)}")
    
    df = pd.DataFrame(data)
    if not df.empty:
        df['Created At'] = pd.to_datetime(df['Created At'])
        df = df.sort_values(by="Created At", ascending=False)
    
    return df

def fetch_models_evaluation(api, projects, selected_project):
    data = []
    
    entity = projects[selected_project]["entity"]
    project = projects[selected_project]["project"]
    
    runs = api.runs(f"{entity}/{project}")
    
    for run in runs:
        try:
            summary = run.summary
            if summary.get("accuracy") is not None:  # Assuming runs with accuracy are model evaluations
                data.append({
                    "ID": run.id,
                    "Username": run.user.username,
                    "Model Name": summary.get("model_name", "N/A"),
                    "Hotkey": summary.get("hotkey", "N/A"),
                    "Score": summary.get("score"),
                    "F1-beta": summary.get("f1-beta"),
                    "Accuracy": summary.get("accuracy"),
                    "Recall": summary.get("recall"),
                    "ROC AUC": summary.get("roc_auc"),
                    "Created At": run.created_at,
                })
        except Exception as e:
            st.write(f"Error processing run {run.id}: {str(e)}")
    
    df = pd.DataFrame(data)
    if not df.empty:
        df['Created At'] = pd.to_datetime(df['Created At'])
        df = df.sort_values(by="Created At", ascending=False)
    
    return df

def update_leader_info(leader_info, competition, best_model):
    current_date = datetime.now().strftime("%Y-%m-%d")
    if leader_info.get(competition) is None:
        leader_info[competition] = {
            "Username": best_model["Username"],
            "Model Name": best_model["Model Name"],
            "Hotkey": best_model["Hotkey"],
            "Date": current_date,
            "UID": best_model["ID"],
            "Days on Top": 1
        }
    else:
        if leader_info[competition]["UID"] == best_model["ID"]:
            leader_info[competition]["Days on Top"] += 1
        else:
            leader_info[competition] = {
                "Username": best_model["Username"],
                "Model Name": best_model["Model Name"],
                "Hotkey": best_model["Hotkey"],
                "Date": current_date,
                "UID": best_model["ID"],
                "Days on Top": 1
            }
    return leader_info[competition]