npc-drops/data.py

import database
import psycopg2.extras
import stocks
from dotenv import load_dotenv
import os
import sys
from pprint import pprint
from datetime import datetime
from urllib.parse import urlencode
# from urllib.request import Request, urlopen
import requests


def broadcast(name, timestamp, price, quantity, this_drop):
    # development only
    load_dotenv()
    url = os.environ["BROADCAST_URL"]
    # Create the string
    time = datetime.utcfromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
    print(time)
    this_drop_decimal = float(this_drop / 1e9)
    string = "{}: {} dropped {} shares at ${:.2f} for a grand total of ${:.1f}B".format(
        time, name, quantity, price, this_drop_decimal)
    json = {'content': string}
    print(urlencode(json).encode())
    response = requests.post(url, json=json)
    if response.status_code in [200, 204]:
        print("Webhook executed")
    else:
        print("status code {}: {}".format(response.status_code, response.content.decode("utf-8")))


# Retrieve last and second to last timestamp from the serverS
db = database.db
cursor = db.cursor(cursor_factory=psycopg2.extras.NamedTupleCursor)
query = """SELECT DISTINCT timestamp FROM stocks ORDER BY stocks.timestamp DESC LIMIT 1 OFFSET 1;"""
cursor.execute(query)
res = cursor.fetchone()
timestamp_previous = res.timestamp
query = """SELECT DISTINCT timestamp FROM stocks ORDER BY stocks.timestamp DESC LIMIT 1;"""
cursor.execute(query)
res = cursor.fetchone()
timestamp_latest = res.timestamp

with open('timestamp.txt', 'w+') as f:
    timestamp_stored = f.read() or 0
    if timestamp_latest != timestamp_stored:
        f.write("{}".format(timestamp_latest))
    else:
        # Exit when there is nothing to do
        sys.exit()

print(timestamp_previous)
print(timestamp_latest)

for stock in stocks.stocks:
    query = """SELECT current_price, available_shares FROM stocks WHERE stock_id = %s AND timestamp = %s"""
    cursor.execute(query, (stock[1], timestamp_latest))
    data_latest = cursor.fetchone()
    cursor.execute(query, (stock[1], timestamp_previous))
    data_previous = cursor.fetchone()

    pprint(data_latest)
    pprint(data_previous)
    # Calculations

    available_latest = int(data_latest.available_shares * data_latest.current_price)
    available_previous = int(data_previous.available_shares * data_previous.current_price)
    print(available_latest)
    print(available_previous)

    drop = available_latest - available_previous
    # broadcast(stock[0], timestamp_latest, data_latest.current_price, data_latest.available_shares, drop)
    if drop > stock[3] * 1e9:
        broadcast(stock[0], timestamp_latest, data_latest.current_price, data_latest.available_shares, drop)

cursor.close()
db.close()