stonks.py

################################################################################################################################################################

#Command Line Arguments Python
#sys.argv[1] - Day1
#sys.argv[2] - open/close
#sys.argv[3] - Day2
#sys.argv[4] - open/close
#sys.argv[5] - Options Value
#sys.argv[6] - Stock Name

#USAGE
#	python3 stonks.py m o f c 2500 AMZN
#	python3 stonks.py <day1> <open/close> <day2> <open/close> <options_val> <company_symbol>

################################################################################################################################################################

import sys
import os
import csv
import heapq
import datetime
from datetime import date
import requests
import json
import pandas as pd

################################################################################

#PARSE EARNINGS REPORT FROM YAHOO

################################################################################

### Get Earnings Webpage for the specific Stonk
link = "https://finance.yahoo.com/calendar/earnings/?symbol=" + sys.argv[6]
f = requests.get(link)
### Once you get it, get the block of page which has ONLY the earnings Table and load in Json
x = json.loads(f.text.split("\"results\":")[1].split(",\"columns\":")[0] + "}")

### Get the value of the key i.e. all the earnings report
y = x["rows"]

### This is a table, so parse using DataFrame, its basically like a SQL table
pd.set_option("display.max_rows", None, "display.max_columns", None)
df = pd.DataFrame(y)

### Once parsed, make 'date' format more in tune with the rest of the program
df["startdatetime"] = df["startdatetime"].str.split('T', expand = True)

### Get 2 columns from the DataFrame, it has many more as shown on Yahoo website
l = df[["startdatetime", "epssurprisepct"]]

### Convert to dictionary i.e. [ key - value ] => [ date of earnings - estimate beat or not ]
dic = l.set_index('startdatetime').T.to_dict('list')

### Below uses Simfin i.e. website that has LOADS of Stonk data like Kaggle but updated daily, Costs money so we using Yahoo
"""

import simfin as sf

# if you haven't installed requests, get it via 'pip install requests'
import requests
# if you haven't installed pandas, get it via 'pip install pandas'
import xlsxwriter

import pandas as pd

# here you have to enter your actual API key from SimFin
api_key = "pYXo4gt2Q2AbwQD08k4qMa8SWwQVQJVs"

# list of tickers we want to get data for
tickers = ["AAPL"]

# define the periods that we want to retrieve
periods = ["q1", "q2", "q3", "q4"]
year_start = 2019
year_end = 2020

# request url for all financial statements
request_url = 'https://simfin.com/api/v2/companies/statements'

# variable to store the names of the columns
columns = []
# variable to store our data
output = []

# if you don't have a SimFin+ subscription, you can only request data for single companies and one period at a time (with SimFin+, you can request multiple tickers and periods at once)
for ticker in tickers:
    # loop through years:
    for year in range(year_start, year_end + 1):
        # loop through periods
        for period in periods:

            # define the parameters for the query
            parameters = {"statement": "pl", "ticker": ticker, "period": period, "fyear": year, "api-key": api_key}
            # make the request
            request = requests.get(request_url, parameters)

            # convert response to json and take 0th index as we only requested one ticker (if more than one ticker is requested, the data for the nth ticker will be at the nth position in the result returned from the API)
            print(request.json())
            data = request.json()[0]

            # make sure that data was found
            if data['found'] and len(data['data']) > 0:
                # add the column descriptions once only
                if len(columns) == 0:
                    columns = data['columns']
                # add the data
                output += data['data']

# make dataframe from output
df = pd.DataFrame(output, columns=columns)

# save to XLSX
# set up the XLSX writer
writer = pd.ExcelWriter("simfin_data.xlsx", engine='xlsxwriter')
# write data and close file
df.to_excel(writer)
writer.save()
writer.close()

"""

###########################################################################################################################################################################

#Usage:
#	python3 stonks.py m o f c 2500 AMZN
#	Lookup AMZN.csv etc. from https://finance.yahoo.com/quote/AMZN/history?period1=1609632000&period2=1619049600&interval=1d&filter=history&frequency=1d&includeAdjustedClose=true
#	Download AMZN.csv etc. from https://query1.finance.yahoo.com/v7/finance/download/AMZN?period1=1609632000&period2=1619049600&interval=1d&events=history&includeAdjustedClose=true

GLOBAL_LIST = []

class bcolors:
    HEADER = '\033[95m'
    OKBLUE = '\033[94m'
    OKCYAN = '\033[96m'
    OKGREEN = '\033[92m'
    WARNING = '\033[93m'
    FAIL = '\033[91m'
    ENDC = '\033[0m'
    BOLD = '\033[1m'
    UNDERLINE = '\033[4m'

################################################################################

def map_day_to_integer(arg):
    if arg == 'm':
        return 0
    if arg == 't':
        return 1
    if arg == 'w':
        return 2
    if arg == 'th':
        return 3
    if arg == 'f':
        return 4

def map_time_to_str(arg):
    if arg == 'o':
        return 'Open'
    else:
        return 'Close'

def map_integer_to_weekday(arg):
    if(arg == 0):
        return 'Mon'
    if(arg == 1):
        return 'Tue'
    if(arg == 2):
        return 'Wed'
    if(arg == 3):
        return 'Thu'
    else:
        return 'Fri'

################################################################################

def pretty_print(day1, day2, date, diff):
    if(diff < 0):
        print(map_integer_to_weekday(day1) + " -> " + map_integer_to_weekday(day2) + " " + date + " = " + bcolors.BOLD + bcolors.FAIL + str(diff) + bcolors.ENDC + "\n")
    else:
        print(map_integer_to_weekday(day1) + " -> " + map_integer_to_weekday(day2) + " " + date + " = " + bcolors.OKBLUE + str(diff) + bcolors.ENDC + "\n")

    file1 = open("STONKS_DATASET.h", "a")
#Playing safe and trying to maximize loss
    if(diff < 0):
        diff = diff - 1
    file1.write(str(int(diff)) + ",\n")
    file1.close()

################################################################################

company_data = os.getcwd() + "/" + sys.argv[6] + ".csv"
try:
    os.remove(company_data)
except:
    print("...")
url = "https://query1.finance.yahoo.com/v7/finance/download/" + sys.argv[6] + "?period1=863654400&period2=1619913600&interval=1d&events=history&includeAdjustedClose=true"
r = requests.get(url, allow_redirects=True)
open(company_data, 'wb').write(r.content)

with open(company_data, newline='') as csvfile:
    print("\n")

    try:
        os.remove(os.getcwd() + "/STONKS_DATASET.h")
    except:
        print("...")

    reader = csv.DictReader(csvfile)

    day1 = map_day_to_integer(sys.argv[1]);
    day1_time = map_time_to_str(sys.argv[2]);

    day2 = map_day_to_integer(sys.argv[3]);
    day2_time = map_time_to_str(sys.argv[4]);

    options_val = float(sys.argv[5])

    gross = 0

    file1 = open("STONKS_DATASET.h", "a")
    file1.write("#ifndef __STONKS_DATASET_H__\n")
    file1.write("#define __STONKS_DATASET_H__\n")
    file1.write("\nconst int STONKS_DATA[] = {\n")
    file1.close()

    begin = False

### Caveat: If ANY day is a Holiday, that week will NOT show up

#Calculate
    for row in reader:
        date_time_str = row['Date']
        date_time_obj = datetime.datetime.strptime(date_time_str, '%Y-%m-%d')

        if date_time_str in dic:
            print("................................EARNINGS : " + date_time_str + " => " + bcolors.BOLD + bcolors.OKGREEN + str(dic[date_time_str]) + bcolors.ENDC + "\n")

        if(date_time_obj.weekday() == day1):
            day1_price = row[day1_time]
            begin = True

        if((date_time_obj.weekday() == day2) and (begin == True)):
            day2_price = row[day2_time]
            diff = float(day2_price) - float(day1_price)
            GLOBAL_LIST.append(diff)	#Do data analysis on this list

            if(diff < 0):
                gross = gross - options_val
            else:
                gross = gross + 100*(diff) - options_val

            pretty_print(day1, day2, date_time_str, diff)
            begin = False

    #Footers in the file
    file1 = open("STONKS_DATASET.h", "a")
    file1.write("};")
    file1.write("\n\n#endif")
    file1.close()

    print("\nNET GROSS: " + str(gross) + "\n")

################################################################################

#DATA ANALYSIS ON THE LIST

################################################################################

total_pos = 0
total_neg = 0
max_contig_pos = 0
max_contig_neg = 0
max_pos = 0
max_neg = 0

if GLOBAL_LIST[0] < 0:
    contig_pos = 0
    max_neg = GLOBAL_LIST[0]    
else:
    contig_pos = 1
    max_pos = GLOBAL_LIST[0]

tmp = 0

for val in GLOBAL_LIST:
    if val < 0:
        #Logic to calculate max contiguous surges and plummets
        if(contig_pos == 1):
            if(max_contig_pos < tmp):
                max_contig_pos = tmp
            contig_pos = 0
            tmp = 0

        total_neg += 1
        tmp  += 1
        if (val < max_neg):
            max_neg = val
    else:
        #Logic to calculate max contiguous surges and plummets
        if(contig_pos == 0):
            if(max_contig_neg < tmp):
                max_contig_neg = tmp
            contig_pos = 1
            tmp = 0

        total_pos += 1
        tmp += 1
        if (val > max_pos):
            max_pos = val

print("Total Surges: " + str(total_pos) + 
      "\nTotal Plummets: " + str(total_neg) + 
      "\nMax Continuous Surges: " + str(max_contig_pos) + 
      "\nMax Continuous Plummets: " + str(max_contig_neg) +
      "\nMax Positive Jump: " + str(max_pos) +
      "\nMax Negative Jump: " + str(max_neg))
print("\n")

################# HEAP EXPERIMENT #################
"""
li = [9, 5, 4, 3, 2, 1]
heapq.heapify(li)
print(li)
heapq.heappush(li, 0)
print(li)
heapq.heapreplace(li, -1)
print(heapq.nlargest(3,li))
print(li)
"""