stocks.py

import time
import requests

symbols = [
    "ARA",
    "LN",
    "ARCH",
    "NTB",
    "TELL",
    "WINS",
    "NBEV",
    "GLBS",
    "NAK",
    "VST",
    "TECK",
    "EBR",
    "CRBP",
    "WRN",
    "CLF",
    "LEU",
    "SKY",
    "AKS",
    "GSS",
    "X",
    "AMD",
    "CC",
    "DGSE",
    "COE",
    "AXU",
    "FBK",
    "CDE",
    "AKTS",
    "DMPI",
    "SINO",
    "SID",
    "EVI",
    "USAS",
    "CYBE",
    "MTL",
    "GV",
    "DRD",
    "JAG",
    "HCLP",
    "NVDA",
    "NXE",
    "VGZ",
    "GDS",
    "NAV",
    "GPL",
    "GRVY",
    "QUAD",
    "GSV",
    "CECO",
    "BGI",
    "SPAR",
]

listed_in_target_year = []

for i in range(len(symbols)):
    symbol = symbols[i]
    print(f"Checking {symbol}...")
    api_key = "GRF31138021UY295"
    api_url = f"https://www.alphavantage.co/query?function=TIME_SERIES_MONTHLY&symbol={symbol}&apikey={api_key}"
    request = requests.get(api_url)
    response = request.json()

    if "Note" in response:
        print(response["Note"])
        exit()

    elif "Error Message" in response:
        print(f"Error fetching data for {symbol}:")
        print(response["Error Message"])

    else:
        target_year = 2016
        keys = list(response["Monthly Time Series"].keys())
        earliest_entry = keys[-1]
        parsed_date = time.strptime(earliest_entry, "%Y-%m-%d")
        earliest_year = parsed_date.tm_year

        if earliest_year == target_year:
            listed_in_target_year.append(symbol)

        most_recent_entry = keys[0]
        parsed_date = time.strptime(most_recent_entry, "%Y-%m-%d")
        most_recent_year = parsed_date.tm_year

    if i + 1 != len(symbols) and (i + 1) % 5 == 0:
        print("API limit reached. Sleeping for a minute...")
        time.sleep(60)

print(
    "The earliest data found for these stocks was in the target year, meaning it was probably an IPO:\n",
    listed_in_target_year,
)