API_Session2

#API Keys
#	Why use them?
#	Monitor uses
#	How to monitor security of API keys?
#	Multi-factor authentication
	

#Environment Variables
#	Better environment variables for enhanced security so others can’t use your keys
#	.env file in separate file
#Calling Envionment Variables
#	Api_key = os.genenv()


 
##Instructor Demo: environment variables
# Import dotenv package for settin env. Variables
From dotenv import load_dotenv

# Import os package
Import os

Api_key = os.getenv()
_____


## Instructor demo 2: Alpaca demo
# Initial imports
import osimport requests
import pandas as pd
from dotenv import load_dotenv
import alpaca_trade_api as trade_api

#load .env environment variables
load_dotenv()

# set alpaca api key and secret
alpaca_api_key = os.getenv("ALPACA_API_KEY")
alpaca_secret_key = os.getenv("ALPACA_SECRET_KEY")

#Verify that Alpaca key and secret were correctly loaded
print(f"Alpaca key type: {ALPACA_API_KEY})
print(f"Alpaca Secret key type: {ALPACA_SECRET_KEY})

#Create the Alpaca API object
alpaca = tradeapi.REST(alpaca_api_key, alpaca_secret_key, api_version="v2")

#Format current date as ISO format
today = pd.Timestamp("2021-04-08", tz="America/New_York").isoformat()

#Set the tickers
tickers = ["FB", "TWTR"]

#Set timeframe to one day ('1D') for the Alpaca API
timeframe = "1D"

#Get current closing prices for FB and TWTR
df_portfolio = alpaca.get_barset(
    tickers,
    timeframe,
    start = today,
    end = today,
).df

# Display sample data
df_portfolio

#Format start and end dates as ISO format for one year period
start= _____
end=_____


#Create and empty DataFrame for closing prices
df_closing_prices = pd.dataFrame()
#Fetch the closing prices of FB and TWTR
df_closing_price["FB"] = df_portfolio_year["FB"]["close"]


# _____


# Compute daily returns
df_daily_returns