import requests
import pandas as pd
from datetime import date, datetime, timezone, timedelta
import numpy as np
from google.cloud import bigquery

api_token = 'token'
today = date.today()
client = bigquery.Client.from_service_account_json(r'ServiceAccount.json')
clan_tags = ["QG9UJ08","Q2JLCVLR","P09YGYU2","2YCCGY8JU"]

def import_to_gbq(df, destination_table):
    try:
        ## If you want the column and row count then
        table_id = destination_table
        job_config = bigquery.LoadJobConfig(
            schema=[
            ],
            write_disposition="WRITE_TRUNCATE",
        )

        job = client.load_table_from_dataframe(
            df, table_id, job_config=job_config
        )  # Make an API request.

        job.result()  # Wait for the job to complete.
        table = client.get_table(table_id)  # Make an API request.
        print("Loaded {} rows and {} columns to {}".format(table.num_rows, len(table.schema), table_id))
    except Exception as e:
        print(e)

def get_current_war_data(clan_tag):
    url = "https://api.clashofclans.com/v1/clans/%23{clan_tag}/currentwar".format(clan_tag=clan_tag)
    r = requests.get(url, headers={"Accept":"application/json", "authorization":"Bearer "+api_token}) #, params = {"limit":20})
    data = r.json()

    if r.status_code == 200:
        if data.get('state') == "inWar" or data.get('state') == "preparation" or data.get('state') == "warEnded":
            return data
    else:
        return None

# Define a function to calculate time left in hours and minutes (as a decimal)
def calculate_time_left(end_time, utc_offset_hours=0):
    war_end_time = datetime.strptime(end_time, "%Y%m%dT%H%M%S.%fZ").replace(tzinfo=timezone.utc)
    my_local_time_plus_UTC = datetime.now(timezone.utc) + timedelta(hours=utc_offset_hours)
    time_left = war_end_time - my_local_time_plus_UTC
    hours_left = time_left.total_seconds() / 3600  # Convert total seconds to hours
    return round(hours_left, 1)  # Round to 1 decimal place for readability

# Define a function to extract the required information and create a dictionary with clan high level info, like total stars, attacks, percent destruction.
def extract_clan_info(clan_info):
    return {
        'clanTag': clan_info.get('tag', ''),
        'clanName': clan_info.get('name', ''),
        'clanLevel': clan_info.get('clanLevel', 0),
        'attacks': clan_info.get('attacks', 0),
        'stars': clan_info.get('stars', 0),
        'destructionPercentage': clan_info.get('destructionPercentage', 0.00)
    }


# Define a function to reformat the clan info for single row representation, for both my clan and enemy clan
def reformat_for_single_row(user_clan, opponent_clan):
    combined_data = {}
    for key, value in user_clan.items():
        combined_data[f'user_{key}'] = value
    for key, value in opponent_clan.items():
        combined_data[f'opponent_{key}'] = value
    return combined_data

# Define a function to process member attack data
def process_member_attacks(member):
    # Initialize default values
    attack_details = {
        'player_tag': member.get('tag',''),
        'name': member.get('name', ''),
        'total_attacks': 0,
        # 'first_attack_stars': None,
        # 'second_attack_stars': None,
        # 'first_attack_destruction': None,
        # 'second_attack_destruction': None
        'first_attack_stars': np.nan,
        'second_attack_stars': np.nan,
        'first_attack_destruction': np.nan,
        'second_attack_destruction': np.nan
    }
    
    # Process each attack
    attacks = member.get('attacks', [])
    attack_details['total_attacks'] = len(attacks)
    for i, attack in enumerate(attacks):
        if i == 0:  # First attack
            attack_details['first_attack_stars'] = attack.get('stars', 0)
            attack_details['first_attack_destruction'] = attack.get('destructionPercentage', 0)
        elif i == 1:  # Second attack
            attack_details['second_attack_stars'] = attack.get('stars', 0)
            attack_details['second_attack_destruction'] = attack.get('destructionPercentage', 0)
    
    return attack_details