utils

"""
@authors: Lorenzo, Christopher
"""

import json

# FOR BACKTESTING IN 2015 HIDE COMPANIES: HLT, FCAU, QSR, BAH
DATA_DIR = "data"

companies = [
    
    "AAPL",
    "ADP",
    "CMG",
    #"HLT",
    "LOW",
    "DIS",
    "NFLX",
    "MSFT",
    "GE",
    #"FCAU",
    "LULU",
    "GS",
    "CVS",
    "MSI",
    "SBUX",
    "QSR",
    "PNC",
    "WFC",
    "T",
    "TMUS", 
    "AXP", 
    "KO",
    "COP",
    "PKX",
    "PG",
    "SNY",
    "USB",
    "WMT",
    "MCO",
    "GOOGL",
    "CRM",
    "COST",
    "CSCO",
    "ADBE",
    "AFL",
    "KMX",
    "INTU",
    #"BAH",
    "NS",
    "DVN",
    "NTP",
    "PFG",
    "UMPQ",
    "MAT",
    "TXN",
    
]


#FUNCTIONS THAT GRAB ALL THE DATA WE NEED FROM THE COMPANY PROFILES, CASH FLOW STATEMENTS, BALANCE SHEET, AND INCOME STATEMENT

def read_company_profile(company):
    file = open(f"{DATA_DIR}/company-profile-{company}.txt")
    data = json.load(file)
    price = float(data["profile"]["price"])
    file.close()
    return {"price": price}


def read_cash_flow(company, year_start, year_end):
    file = open(f"{DATA_DIR}/cash-flow-{company}.txt")
    data = json.load(file)
    cash_flow = {}
    for ent in data["financials"]:
        y = int(ent["date"][0:4])
        if year_start < y <= year_end:
            cash_flow[y] = {
                "dna": float(ent["Depreciation & Amortization"]),
                "capex": float(ent["Capital Expenditure"]),
            }
    file.close()
    return cash_flow


def read_balance_sheet(company, year_start, year_end):
    file = open(f"{DATA_DIR}/balance-sheet-{company}.txt")
    data = json.load(file)
    balance_sheet = {}
    for ent in data["financials"]:
        y = int(ent["date"][0:4])
        if year_start < y <= year_end:
            balance_sheet[y] = {
                "cash": float(ent["Cash and cash equivalents"]),
                "ar": float(ent["Receivables"]),
                "inv": float(ent["Inventories"]),
                "ap": float(ent["Payables"]),
                "debt": float(ent["Total debt"]),
            }
    file.close()
    return balance_sheet


def read_income_statement(company, year_start, year_end):
    file = open(f"{DATA_DIR}/income-statement-{company}.txt")
    data = json.load(file)
    income_statement = {}
    for ent in data["financials"]:
        y = int(ent["date"][0:4])
        if year_start < y <= year_end:
            income_statement[y] = {
                "rv": float(ent["Revenue"]),
                "rvgr": float(ent["Revenue Growth"]),
                "ebit%": float(ent["EBIT Margin"]),
                "shares": float(ent["Weighted Average Shs Out"])
            }
    file.close()
    return income_statement