from tinydb import TinyDB, Query
import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
from datetime import datetime,date
MarketDB = TinyDB('market.json')
PlayerDB = TinyDB('player.json')
NotificationDB = TinyDB('notifications.json')
MonitorDB = TinyDB('monitor_market.json')


def getMonitor(card_name):
    data = MonitorDB.table('_default').all()
    for record in data:
        if record['name'] == card_name:
            return record['cost']
    return None

def getDF(card=None,aDate=None,pruneOutliers=True):
    """
        Supply either a card identifier or a date for filter by.

        card can be an integer, which will pull from the card-num, or a string
            which will pull from the name field.  It can also be a list of ints
            or strings, which will pull multiple cards histories.
        date can be either a datetime or string date formatted 'yyyy-mm-dd'
    """
    MarketDB = TinyDB('market.json')
    if card is not None:
        if isinstance(card,list):
            if isinstance(card[0],int):
                d=MarketDB.search(Query()['card-num'].one_of(card))
            else:
                d=MarketDB.search(Query()['name'].one_of(card))
        else:
            if isinstance(card,int):
                d=MarketDB.search(Query()['card-num']==card)
            else:
                d=MarketDB.search(Query()['name']==card)
    else:
        if isinstance(aDate,(datetime,date)):
            d=MarketDB.search(Query()['date']==aDate.strftime('%Y-%m-%d'))
        else:
            d=MarketDB.search(Query()['date']==aDate)
    df=pd.DataFrame(d)
    if pruneOutliers:
        df=df[np.abs(stats.zscore(df['cost'])) < 1.5]
    df.sort_values(by=['card-num','date'], ascending=[True,True], inplace=True)
    return df.round({'cost':2,'cost-min':0,'cost-max':0})

def _hist(card=None,date=None,columns=['date','card-num','name','cost']):
    return getDF(card,date)[columns].to_string(index=False)

def hist(card=None,date=None,columns=['date','card-num','name','cost']):
    print(_hist(card,date,columns))

def plot(card=None,columns=['cost','cost-min','cost-max'],maxCost=None):
    """must use either card or date.
        card cand be card-num or name
        date can be a datetime type or a string like 'yyy-mm-dd'
        columns must be a list of any numeric fields in the MarketDB
    """
    df=getDF(card).plot(x='date',y=columns)
    plt.title(str(card))
    plt.xticks(rotation=45)
    plt.xlabel("Date")
    plt.ylabel("Cost")
    plt.ylim(0,maxCost)
    plt.show()
    
def buyout():
    today=datetime.utcnow().strftime('%Y-%m-%d')
    PlayerDB = TinyDB('player.json')
    PlayerCards=PlayerDB.search(Query().fragment({'date':today}))
    Stock=[None]*152
    for card in PlayerCards: Stock[card['card-num']]=card['stock']
    MarketDF = getDF(aDate=today)
    MarketCards=MarketDF.to_dict('records')
    total=0
    cardCount=0
    NeededCards=[]
    print(f"Cards Needed Today:")
    print(f'    Name             Needed  Cost')
    for card in MarketCards:
        if 'CRYSTAL' not in Stock[card['card-num']]:
            card['stock']=int(Stock[card['card-num']])
            card['needed']=10-card['stock']
            card['card-num']=card['card-num']
            card['total-cost']=card['needed']*card['cost']
            NeededCards.append(card)
            total+=card['total-cost']
            cardCount+=card['needed']
            print(f"{card['card-num']: >3} {card['name']: <20} {card['needed']: >2} {round(card['total-cost']): >5}")
    
    print(f"  Remaining Cards: {cardCount}")
    print(f"Total Gems Needed: {round(total)}")