Python Project

import requests
from bs4 import BeautifulSoup
import csv

website_url = requests.get('https://money.cnn.com/data/hotstocks').text
soup = BeautifulSoup(website_url, 'lxml')

tickers_mostactive_long = []
tickers_mostactive = []
names_mostactive_nonetype = []
names_mostactive = []
# initizaling lists for most active table

my_table = soup.findAll('table')[0]

html_tickers_mostactive = my_table.find_all('a')

for i in html_tickers_mostactive:
     tickers_mostactive_long.append(i.get('href'))

tickers_mostactive = [i.split('=',1)[1] for i in tickers_mostactive_long]

html_names_mostactive = my_table.find_all('span')

for i in html_names_mostactive:
     names_mostactive_nonetype.append(i.get('title'))

for name in names_mostactive_nonetype:
    if name != None:
        names_mostactive.append(name)
# will non-none type values will be appended to names_mostactive
# end of most active

tickers_gainers_long = []
tickers_gainers = []
names_gainers_nonetype = []
names_gainers = []
# initizaling lists for gainers table

my_table = soup.find_all('table')[1]

html_tickers_gainers = my_table.find_all('a')

for i in html_tickers_gainers:
     tickers_gainers_long.append(i.get('href'))

tickers_gainers = [i.split('=',1)[1] for i in tickers_gainers_long]


html_names_gainers = my_table.find_all('span')

for i in html_names_gainers:
     names_gainers_nonetype.append(i.get('title'))

for name in names_gainers_nonetype:
    if name != None:
        names_gainers.append(name)
# will non-none type values will be appended to names_gainers
# end of gainers

tickers_losers_long = []
tickers_losers = []
names_losers_nonetype = []
names_losers = []
# initizaling lists for losers table

my_table = soup.findAll('table')[2]

html_tickers_losers = my_table.find_all('a')

for i in html_tickers_losers:
     tickers_losers_long.append(i.get('href'))

tickers_losers = [i.split('=',1)[1] for i in tickers_losers_long]

html_names_losers = my_table.find_all('span')

for i in html_names_losers:
     names_losers_nonetype.append(i.get('title'))

for name in names_losers_nonetype:
    if name != None:
        names_losers.append(name)
# will non-none type values will be appended to names_losers
# end of losers

print('Most Active:')
for ticker, name in zip(tickers_mostactive, names_mostactive):
    print(ticker,',',name)
print('\n')

print('Top Gainers:')
for ticker, name in zip(tickers_gainers, names_gainers):
    print(ticker,',',name)
print('\n')

print('Top Losers:')
for ticker, name in zip(tickers_losers, names_losers):
    print(ticker,',',name)
print('\n')

previousclose_mostactive = []
openprice_mostactive = []
volume_mostactive = []
marketcap_mostactive = []

url_pattern = 'https://finance.yahoo.com/quote/{}/'

for ticker in tickers_mostactive:
    url = url_pattern.format(ticker)

    url_extract = requests.get(url).text

    soup = BeautifulSoup(url_extract, 'lxml')

    td_previousclose = soup.find_all('td')[1]
    td_openprice = soup.find_all('td') [3]
    td_volume = soup.find_all('td')[13]
    td_marketcap = soup.find_all('td')[17]
    # located previous close, open price, volume, and market cap
    # consistent for all stocks

    span_previousclose = str(td_previousclose.find_all('span'))
    span_openprice = str(td_openprice.find_all('span'))
    span_volume = str(td_volume.find_all('span'))
    span_marketcap = str(td_marketcap.find_all('span'))
    # used to trim down and to convert to string for manipulation

    split_previousclose = span_previousclose.split('">')[1]
    split_openprice = span_openprice.split('">')[1]
    split_volume = span_volume.split('">')[1]
    split_marketcap = span_marketcap.split('">')[1]
    # split to trim down even more

    previousclose = (split_previousclose.split('<')[0])
    openprice = (split_openprice.split('<')[0])
    volume = (split_volume.split('<')[0])
    marketcap = (split_marketcap.split('<')[0])
    # split to trim down even to just get attributes needed

    previousclose_mostactive.append(previousclose)
    openprice_mostactive.append(openprice)
    volume_mostactive.append(volume)
    marketcap_mostactive.append(marketcap)

previousclose_gainers = []
openprice_gainers = []
volume_gainers = []
marketcap_gainers = []

for ticker in tickers_gainers:
    url = url_pattern.format(ticker)

    url_extract = requests.get(url).text

    soup = BeautifulSoup(url_extract, 'lxml')

    td_previousclose = soup.find_all('td')[1]
    td_openprice = soup.find_all('td') [3]
    td_volume = soup.find_all('td')[13]
    td_marketcap = soup.find_all('td')[17]
    # located previous close, open price, volume, and market cap
    # consistent for all stocks

    span_previousclose = str(td_previousclose.find_all('span'))
    span_openprice = str(td_openprice.find_all('span'))
    span_volume = str(td_volume.find_all('span'))
    span_marketcap = str(td_marketcap.find_all('span'))
    # used to trim down and to convert to string for manipulation

    split_previousclose = span_previousclose.split('">')[1]
    split_openprice = span_openprice.split('">')[1]
    split_volume = span_volume.split('">')[1]
    split_marketcap = span_marketcap.split('">')[1]
    # split to trim down even more

    previousclose = (split_previousclose.split('<')[0])
    openprice = (split_openprice.split('<')[0])
    volume = (split_volume.split('<')[0])
    marketcap = (split_marketcap.split('<')[0])
    # split to trim down even to just get attributes needed

    previousclose_gainers.append(previousclose)
    openprice_gainers.append(openprice)
    volume_gainers.append(volume)
    marketcap_gainers.append(marketcap)

previousclose_losers = []
openprice_losers = []
volume_losers = []
marketcap_losers = []

for ticker in tickers_losers:
    url = url_pattern.format(ticker)

    url_extract = requests.get(url).text

    soup = BeautifulSoup(url_extract, 'lxml')

    td_previousclose = soup.find_all('td')[1]
    td_openprice = soup.find_all('td') [3]
    td_volume = soup.find_all('td')[13]
    td_marketcap = soup.find_all('td')[17]
    # located previous close, open price, volume, and market cap
    # consistent for all stocks

    span_previousclose = str(td_previousclose.find_all('span'))
    span_openprice = str(td_openprice.find_all('span'))
    span_volume = str(td_volume.find_all('span'))
    span_marketcap = str(td_marketcap.find_all('span'))
    # used to trim down and to convert to string for manipulation

    split_previousclose = span_previousclose.split('">')[1]
    split_openprice = span_openprice.split('">')[1]
    split_volume = span_volume.split('">')[1]
    split_marketcap = span_marketcap.split('">')[1]
    # split to trim down even more

    previousclose = (split_previousclose.split('<')[0])
    openprice = (split_openprice.split('<')[0])
    volume = (split_volume.split('<')[0])
    marketcap = (split_marketcap.split('<')[0])
    # split to trim down even to just get attributes needed

    previousclose_losers.append(previousclose)
    openprice_losers.append(openprice)
    volume_losers.append(volume)
    marketcap_losers.append(marketcap)

column_headers = ['Ticker', 'Name', 'Previous Close', 'Open Price', 'Volume', 'Market Cap']
break_mostactive = ['Most Active']
break_gainers = ['Gainers']
break_losers = ['Losers']

rows_mostactive = zip(tickers_mostactive, names_mostactive, previousclose_mostactive, openprice_mostactive, volume_mostactive, marketcap_mostactive)
rows_gainers = zip(tickers_gainers, names_gainers, previousclose_gainers, openprice_gainers, volume_gainers, marketcap_gainers)
rows_losers = zip(tickers_losers, names_losers, previousclose_losers, openprice_losers, volume_losers, marketcap_losers)



with open('stocks.csv', 'w') as f:
    writer = csv.writer(f)
    writer.writerow(column_headers)
    writer.writerow(break_mostactive)
    for row in rows_mostactive:
        writer.writerow(row)
    writer.writerow(break_gainers)
    for row in rows_gainers:
        writer.writerow(row)
    writer.writerow(break_losers)
    for row in rows_losers:
        writer.writerow(row)

print('stocks.csv created')
print('\n')

stonks_file = 'stocks.csv'

reader = csv.reader(open('stocks.csv'))

stonks = {}

for row in reader:
    key = row[0]
    if key in stonks:
        pass
    stonks[key] = row[1:]

while True:

    stonk = input('Which stock do you want to know more about? Enter the stock ticker:').upper()

    if (stonk == 'ticker') or (stonk == 'most active') or (stonk == 'gainers') or (stonk == 'losers') or (stonk not in stonks):
        print('You did not enter a valid stock ticker!')
        break

    elif stonk in stonks:
        stonk_info = list(stonks[stonk])
        print('Ticker:', stonk)
        print('Name:', stonk_info[0])
        print('Previous Close:', stonk_info[1])
        print('Open Price:', stonk_info[2])
        print('Volume:', stonk_info[3])
        print('Market Cap:', stonk_info[4])

    restart = input('Do you want to look at another one? (yes/no)').lower()

    if (restart == 'yes'):
        continue

    elif (restart == 'no'):
        print('Goodbye!')
        break

    elif (restart != 'yes') or (restart != 'no'):
        print('You did not enter a valid answer!')
        break