import argparse
import webbrowser
from bs4 import BeautifulSoup
import requests
import pandas as pd
import re
from helper_funcs import *


# ------------------------------------------------ HIGH_SHORT_INTEREST -------------------------------------------------
def high_short_interest(l_args):
    parser = argparse.ArgumentParser(prog='high_short', 
                                    description='''Print top stocks being more heavily shorted. HighShortInterest.com provides 
                                                   a convenient sorted database of stocks which have a short interest of over 
                                                   20 percent. Additional key data such as the float, number of outstanding shares, 
                                                   and company industry is displayed. Data is presented for the Nasdaq Stock Market, 
                                                   the New York Stock Exchange, and the American Stock Exchange. 
                                                   [Source: www.highshortinterest.com]''')
    
    parser.add_argument('-n', "--num", action="store", dest="n_num", type=check_positive, default=10, 
                        help='Number of top stocks to print.')

    try:
        (ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
    except SystemExit:
        print("")
        return
    
    if l_unknown_args:
        print(f"The following args couldn't be interpreted: {l_unknown_args}")

    url_high_short_interested_stocks = f"https://www.highshortinterest.com"
    text_soup_high_short_interested_stocks = BeautifulSoup(requests.get(url_high_short_interested_stocks).text, "lxml")

    a_high_short_interest_header = list()
    for high_short_interest_header in text_soup_high_short_interested_stocks.findAll('td',  {'class': 'tblhdr'}):
        a_high_short_interest_header.append(high_short_interest_header.text.strip('\n').split('\n')[0])
    df_high_short_interest = pd.DataFrame(columns=a_high_short_interest_header)
    df_high_short_interest.loc[0] = ['', '', '', '', '', '', '']

    a_high_short_interested_stocks = re.sub('<!--.*?//-->','', text_soup_high_short_interested_stocks.find_all('td')[3].text, flags=re.DOTALL).split('\n')[2:]
    a_high_short_interested_stocks[0] = a_high_short_interested_stocks[0].replace('TickerCompanyExchangeShortIntFloatOutstdIndustry','')

    l_stock_info = list()
    for elem in a_high_short_interested_stocks:
        if elem is '':
            continue
            
        l_stock_info.append(elem)
            
        if len(l_stock_info) == 7:
            df_high_short_interest.loc[len(df_high_short_interest.index)] = l_stock_info
            l_stock_info = list()
        
    pd.set_option('display.max_colwidth', -1)
    print(df_high_short_interest.head(n=ns_parser.n_num).to_string(index=False))
    print("")


# ---------------------------------------------------- LOW_FLOAT -----------------------------------------------------
def low_float(l_args):
    parser = argparse.ArgumentParser(prog='low_float', 
                                     description='''Print top stocks with lowest float. LowFloat.com provides a convenient 
                                     sorted database of stocks which have a float of under 10 million shares. Additional key 
                                     data such as the number of outstanding shares, short interest, and company industry is 
                                     displayed. Data is presented for the Nasdaq Stock Market, the New York Stock Exchange, 
                                     the American Stock Exchange, and the Over the Counter Bulletin Board. 
                                     [Source: www.lowfloat.com]''')
    
    parser.add_argument('-n', "--num", action="store", dest="n_num", type=check_positive, default=10, help='Number of top stocks to print.')

    try:
        (ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
    except SystemExit:
        print("")
        return
    
    if l_unknown_args:
        print(f"The following args couldn't be interpreted: {l_unknown_args}")

    url_high_short_interested_stocks = f"https://www.lowfloat.com"
    text_soup_low_float_stocks = BeautifulSoup(requests.get(url_high_short_interested_stocks).text, "lxml")

    a_low_float_header = list()
    for low_float_header in text_soup_low_float_stocks.findAll('td',  {'class': 'tblhdr'}):
        a_low_float_header.append(low_float_header.text.strip('\n').split('\n')[0])
    df_low_float = pd.DataFrame(columns=a_low_float_header)
    df_low_float.loc[0] = ['', '', '', '', '', '', '']

    a_low_float_stocks = re.sub('<!--.*?//-->','', text_soup_low_float_stocks.find_all('td')[3].text, flags=re.DOTALL).split('\n')[2:]
    a_low_float_stocks[0] = a_low_float_stocks[0].replace('TickerCompanyExchangeFloatOutstdShortIntIndustry','')

    l_stock_info = list()
    for elem in a_low_float_stocks:
        if elem is '':
            continue
            
        l_stock_info.append(elem)
            
        if len(l_stock_info) == 7:
            df_low_float.loc[len(df_low_float.index)] = l_stock_info
            l_stock_info = list()
        
    pd.set_option('display.max_colwidth', -1)
    print(df_low_float.head(n=ns_parser.n_num).to_string(index=False))
    print("")