TelegramAktienBot/api/app/blueprints/portfolio.py

__author__ = "Florian Kaiser"
__copyright__ = "Copyright 2022, Project Aktienbot"
__credits__ = ["Florian Kaiser", "Florian Kellermann", "Linus Eickhof", "Kevin Pauer"]
__license__ = "GPL 3.0"
__version__ = "1.0.1"

import os

from apiflask import APIBlueprint
from app.auth import auth
from app.db import database as db
from app.helper_functions import make_response, get_email_or_abort_401
from app.models import SharePrice
from app.schema import PortfolioResponseSchema

portfolio_blueprint = APIBlueprint('portfolio', __name__, url_prefix='/api')
__location__ = os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__)))


@portfolio_blueprint.route('/portfolio', methods=['GET'])
@portfolio_blueprint.output(PortfolioResponseSchema(many=True), 200)
@portfolio_blueprint.auth_required(auth)
@portfolio_blueprint.doc(summary="Returns portfolio", description="Returns all shares of current user")
def get_portfolio():
    email = get_email_or_abort_401()

    return_portfolio = []

    # Get all transactions of current user
    transactions = db.session.execute("SELECT isin, comment, SUM(count), SUM(price), MAX(time) FROM `transactions` WHERE email = '" + email + "' GROUP BY isin, comment;").all()

    # If there are no transactions, return empty portfolio
    # Otherwise calculate portfolio
    if transactions is not None:
        for row in transactions:
            if row[2] == 0:
                continue
            else:
                data = {
                    "isin": row[0],
                    "comment": row[1],
                    "count": row[2],
                    # "calculated_price": row[3],
                    "last_transaction": row[4],
                    'current_price': 0
                }

                # Add current share value to portfolio
                query_share_price = db.session.query(SharePrice).filter_by(isin=row[0]).order_by(SharePrice.date.desc()).first()
                if query_share_price is not None:
                    data['current_price'] = query_share_price.as_dict()['price']

                return_portfolio.append(data)

    return make_response(return_portfolio, 200, "Successfully loaded symbols")