def add_stock(self, stock_code):
# check if record already exist
try:
Stock.objects.get(code=stock_code)
except Stock.DoesNotExist:
# check if insertion is valid
try:
user_stock = IEXStock(stock_code)
new_stock = Stock()
new_stock.name = user_stock.get_company_name()
new_stock.code = stock_code
new_stock.save()
except:
return False
return True
def index():
if request.method == 'POST': #this block is only entered when the form is submitted
stock = request.form['symbol']
symbol = Stock(stock)
name = symbol.get_company_name() + " (" + str(stock) + ")\n\n"
curr_time = now
price = str(symbol.get_price()) + " " + str(
symbol.get_quote().get('change')) + " (" + str(
symbol.get_quote().get('changePercent')) + ")"
return '''<title>Python Finance Info</title>
<form method="POST">
<h3>Python Finance Info</h3><br/>
<i>Input:</i><br/><br/>
Enter a symbol <input type="text" name="symbol">
<input type="submit" value="Submit"><br/><br/>
</form>
<i>Output: </i><br/><br/> {} <br/> {} <br/> {} </h5>'''.format(
name, curr_time, price)
return '''<title>Python Finance Info</title>
def on_message(message):
global last_activity_timer #global variable, variable, etc is required to pull 'globals' between coroutines
tab="\t"
newline = "\n"
time = "%s:%s" % (datetime.now().hour,datetime.now().minute)
if message.author == client.user: #ignore messages from ourselves (the bot)
return
elif message.server.id =="317462567532625944":
Capture_Message(message,tab,newline,time)
if message.content.upper().startswith('!TODAYSEARNINGS'):
last_activity_timer = datetime.now()
page = urlopen("https://www.nasdaq.com/earnings/earnings-calendar.aspx").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find('table')
#print(table)
table_body = table.find('tbody')
rows = table_body.find_all('tr')
data = prettytable.PrettyTable(["PM/AH","Ticker","Consensus","# of est","#Last Yr EPS"])
columns_to_grab = [0,1,4,5,7]
new_rows = []
for row in rows:
cols = row.find_all('td')
if "Pre-market" in str(cols[0]): #turn cols[0] to a string - .text gives us nothing
cols[0].clear() #clear the existing data
cols[0].append("PM") #add in PM
new_rows.insert(0,cols)
else:
cols[0].clear()
cols[0].append("AH")
new_rows.append(cols) #end of list = append
Name = str(cols[1]).split() #Shorten the name to just the Ticker to save space
for word in Name:
if '(' in word:
Half_Ticker = word.replace('(','')
Ticker = Half_Ticker.replace(')','')
cols[1].clear()
cols[1].append(Ticker)
for row in new_rows:
cols = [ele.text.strip() for ele in (row[x] for x in columns_to_grab)]
data.add_row(cols)
if len(data.get_string()) > 1800:
yield from client.send_message(message.channel, "```" + data.get_string(sortby='PM/AH', reversesort=True) + "```")
data.clear_rows()
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
#End !upcomingearnings
elif message.content.upper().startswith('!BUY') or message.content.upper().startswith('!SELL'):
split_message = message.content.upper().split(' ')
if len(split_message) > 1:
Ticker = split_message[1]
else:
Ticker = 'HMNY'
Number = random.uniform(0,100)
List = ['#'+Ticker+'? Sure, why not?','BEEP BOOP what the f**k do I know?',"According to my probability back-testing algorithm, you have a " + str(round(Number,4)) + "% chance of successfully doing your ass in with " + Ticker, "Seems like a shitty idea, go for it", "I've seen better ideas on Wall Street Bets","You're going to make StockTwits Proud buying "+Ticker,'#'+Ticker+' will blow up again tomorrow... feel sorry for those of you that panicked','#'+Ticker+' got in at 6.22 with 1k shares. Your best trades just go.','#'+Ticker+' 60 mullion shares traded and UP big. What else do you need to know! ','#'+Ticker+ ' I was gonna short this but then I got high','In 4 weeks #'+Ticker+' will be in a $110.9 Billion Market. Cheap Here', Ticker + '? far from worried lol',Ticker + ' has to go eventually, right?']
String = random.choice(List)
yield from client.send_message(message.channel, "```" + String + "```")
#End !buy or !sell
elif message.content.upper().startswith('!BLOOMBERG'):
#DRIVER = 'chromedriver'
chrome_options = Options()
chrome_options.add_argument('--headless')
chrome_options.add_argument('--no-sandbox')
chrome_options.add_argument('--disable-dev-shm-usage')
driver = webdriver.Chrome(executable_path="C:/Users/Liquid Trading LLC/Desktop/le_stock_bot/chromedriver.exe")
#driver = webdriver.Chrome(DRIVER)
#print("driver")
driver.get('https://finviz.com/')
#maximize_window()
#print("google'd")
screenshot = driver.get_screenshot_as_file('C:/Users/Liquid Trading LLC/Desktop/finviz.png')
yield from client.send_file(message.channel, "C:/Users/Liquid Trading LLC/Desktop/finviz.png", content='', filename= "finviz.png")
#print("screenshot")
driver.quit()
#print("quit")
#yield from client.send_file(message.channel, screenshot, content="", filename="bloomberg.png")
elif message.content.upper().startswith('!UPGRADE') or message.content.upper().startswith('!DOWNGRADE'):
split_message = message.content.split(' ')
Ticker = split_message[1]
driver = webdriver.Chrome()
driver.get("https://finviz.com/quote.ashx?t="+ Ticker + "&ty=c&ta=0&p=d")
table = driver.find_element_by_xpath('//div[@class="fullview-ratings-outer"]/table//table/..')
table_html = table.get_attribute('innerHTML')
page = urlopen("https://finviz.com/quote.ashx?t="+ Ticker + "&ty=c&ta=0&p=d").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find_all('table')
for i in range(len(table)):
print(table[i].text)
table_body = table[7].find('tbody') #is the ?th table on the page afaik
Date = ''
Up_Down = ''
Company = ''
Weight = ''
Price = ''
data = prettytable.PrettyTable(["Date","Type","Company","Weight","Price"])
i = 0
cells = table_body.find_all('td')
while i < len(rows):
Date = cells[0+i].text
Up_Down = cells[1+i].text
Company = cells[2+i].text
Weight = cells[3+i].text
Price = cells[4+i].text
data.add_row([Date, Up_Down, Weight, Price])
i+=5
if len(data.get_string()) > 1500:
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
data.clear_rows()
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
#End Upgrade
elif message.content.upper().startswith("!HALT"):
page = urlopen("https://www.nasdaqtrader.com/trader.aspx?id=TradeHalts").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find(id='divTradeHaltResults').find_all('table') #//*[@id="divTradeHaltResults"] comes up empty for some reason
print(table)
rows = soup.find_all('td')
print(rows)
elif message.content.upper().startswith('!DATA'):
#!newdata cbrp
#For CBRP Price is : 6.59 || Volume : 257,671 || Float : 42.42M || Short Float : 15.76% || Avg Volume : 1.22M || Change : 4.56% || Earnings: October 9 AMC
split_message = message.content.split(' ')
k=1
while (k) < len(split_message):
Ticker= split_message[k]
page = urlopen("https://finviz.com/quote.ashx?t="+ Ticker + "&ty=c&ta=0&p=d").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find_all('table')
table_body = table[3].find('tbody') #is the 4th table on the page afaik
cells = table_body.find_all('td')
Shares_Outstanding = ''
Earnings = ''
Float = ''
Short_Float = ''
Rel_Vol = ''
Average_Volume = ''
Volume_Today =''
Price =''
Change = ''
Beta = ''
Volume =''
i=0
while i < (len(cells)):
#may have to str() everything to get it to work
if 'Shs Outstand' in cells[i]:
Shares_Outstanding = cells[i+1].text
if 'Earnings' in cells[i]:
Earnings = cells[i+1].text
if 'Shs Float' in cells[i]:
Float = cells[i+1].text
if 'Short Float' in cells[i]:
Short_Float = cells[i+1].text
if 'Rel Volume' in cells[i]:
Rel_Vol = cells[i+1].text
if 'Avg Vol' in cells[i]:
Average_Volume = cells[i+1].text
if 'Volume' == cells[i].text:
Volume_Today = cells[i+1].text
if "Price" in cells[i]:
Price = cells[i+1].text
if "Change" in cells[i]:
Change = cells[i+1].text
if "Beta" in cells[i]:
Beta = cells[i+1].text
i+=1
Columns = '||'
Price_String = '%s Price : %s' % (Ticker, Price)
Volume_String = 'Volume : %s' % Volume_Today # Volume_Today, Shares_Outstanding, Float, Short_Float, Rel_Vol, Beta, Change, Earnings
Shares_String = 'Shares : %s' % Shares_Outstanding
Float_String = 'Float : %s' % Float
Short_String = 'Short Float : %s' % Short_Float
Rel_String = 'Rel Volume : %s' % Rel_Vol
Beta_String = 'Beta : %s' % Beta
Change_String = 'Change : %s' % Change
Earnings_String = 'Earnings : %s' % Earnings
All_Data_In_Strings = [Price_String, Volume_String, Shares_String,Short_String,Rel_String,Beta_String,Change_String,Earnings_String]
padding = max(map(len,All_Data_In_Strings))
print(padding)
New_String = '{0} {1} {2} {3} {4}\n{5} {6} {7} {8} {9}\n{10} {11} {12} {13} {14}'.format(Price_String.ljust(padding),Columns, Volume_String.ljust(padding),Columns, Shares_String.ljust(padding),Float_String.ljust(padding), Columns, Short_String.ljust(padding),Columns,Rel_String.ljust(padding),Beta_String.ljust(padding),Columns,Change_String.ljust(padding),Columns,Earnings_String.ljust(padding))
print(New_String)
String = "```%s Price : %s \t\t|| Volume : %s \t\t|| Shares : %s\n\t Float : %s \t\t|| Short Float : %s \t\t|| Rel Volume : %s\n\t Beta : %s \t\t\t|| Change : %s \t\t|| Earnings : %s ```" % (Ticker, Price, Volume_Today, Shares_Outstanding, Float, Short_Float, Rel_Vol, Beta, Change, Earnings)
yield from client.send_message(message.channel, "`"+New_String+"`")
k+=1
# end !data
# elif message.content.upper().startswith('!DATA'):
# last_activity_timer = datetime.now()
# #For crbp Price is : 6.59 || Volume : 257,671 || Float : 42.42M || Short Float : 15.76% || Avg Volume : 1.22M || Prev Close : 6.45
# stock_name = message.content[6:] #cut out !data *space* (will it get multiple if we do STOCK, STOCK1, STOCK2 ?)
# doForLoop = False
# if "," in stock_name:
# stock_name = stock_name.replace(" ", "").split(",")
# doForLoop = True
# try:
# if doForLoop:
# the_message = ""
# for x in stock_name:
# x = x.upper()
# stock_data = Stock(stock_name)
# the_message = the_message + "{} - {} || Price : ${:,.2f} || Volume : {} || Float : {} || Short Float : {:.3%} || Avg Volume : {} || Prev Close : ${:,.2f}\n\n".format(
# stock_data.get_company_name()[x], stock_data.get_company()[x]["symbol"], stock_data.get_price()[x], human_format(stock_data.get_volume()[x]), human_format(stock_data.get_float()[x]),
# (stock_data.get_short_interest()[x]/stock_data.get_float()[x]), human_format(stock_data.get_quote()[x]['avgTotalVolume']), stock_data.get_previous()[x]['close']
# )
# yield from client.send_message(message.channel, the_message.rstrip('\n')) #rstrip last \n out
# else:
# stock_data = Stock(stock_name)
# yield from client.send_message(message.channel, "{} - {} || Price : ${:,.2f} || Volume : {} || Float : {} || Short Float : {:.3%} || Avg Volume : {} || Prev Close : ${:,.2f}".format(
# stock_data.get_company_name(), stock_data.get_company()["symbol"], stock_data.get_price(), human_format(stock_data.get_volume()), human_format(stock_data.get_float()),
# (stock_data.get_short_interest()/stock_data.get_float()), human_format(stock_data.get_quote()['avgTotalVolume']), stock_data.get_previous()['close']
# ))
# except iexfinance.utils.exceptions.IEXSymbolError as error:
# yield from client.send_message(message.channel, "Error: {0}".format(error))
# except ValueError as error:
# yield from client.send_message(message.channel, "Error: {0}".format(error))
#end !data
elif message.content.lower().startswith("!join"):
pyautogui.click(1220,400)
elif message.content.lower().startswith("!leave"):
yield from client.disconnect()
elif message.content.startswith('!news'):
last_activity_timer = datetime.now()
stock_name = message.content[6:]
try:
stock_data = Stock(stock_name)
message_to_send = "News for: {} - {}".format(stock_data.get_company_name(), stock_data.get_company()["symbol"])
for x in stock_data.get_news(last=5):
message_to_send += "\n{} - {}".format(unescape(x["headline"]), x["url"])
yield from client.send_message(message.channel, message_to_send)
except iexfinance.utils.exceptions.IEXSymbolError as error:
yield from client.send_message(message.channel, "Error: {0}".format(error))
except ValueError as error:
yield from client.send_message(message.channel, "Error: {0}".format(error))
#end !news
elif message.content.upper().startswith('!EARNINGS'):
last_activity_timer = datetime.now()
stock_name = message.content[10:]
try:
stock_data = Stock(stock_name)
page = urlopen("https://finviz.com/quote.ashx?t="+ stock_name + "&ty=c&ta=0&p=d").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find_all('table')
table_body = table[3].find('tbody') #is the 4th table on the page afaik
cells = table_body.find_all('td')
i=0
Future_Earnings = ''
EPS_Next = ''
TTM = ''
while i < (len(cells)):
if 'EPS next Q' in cells[i]:
EPS_Next = cells[i+1].text
elif 'Earnings' in cells[i]:
Future_Earnings = cells[i+1].text
elif 'EPS (ttm)' in cells[i]:
TTM = cells[i+1].text
i+=1
stock_data_earnings = stock_data.get_earnings()[0]
stock_data_earnings_two = stock_data.get_earnings()[1]
stock_data_earnings_three = stock_data.get_earnings()[2]
stock_data_earnings_four = stock_data.get_earnings()[3]
yield from client.send_message(message.channel, "{} - {}```\nReport Date: {}\t Expected : {} \tEPS(ttm) : {}\nReport Date : {}\tConsensus : {}\tActual : {}\nReport Date : {}\tConsensus : {}\tActual : {} \
\nReport Date : {}\tConsensus : {}\tActual : {}\nReport Date : {}\tConsensus : {}\tActual : {}```".format(
stock_data.get_company_name(), stock_data.get_company()["symbol"],Future_Earnings,EPS_Next,TTM, stock_data_earnings["EPSReportDate"], stock_data_earnings["consensusEPS"], stock_data_earnings["actualEPS"],
stock_data_earnings_two["EPSReportDate"], stock_data_earnings_two["consensusEPS"], stock_data_earnings_two["actualEPS"],
stock_data_earnings_three["EPSReportDate"], stock_data_earnings_three["consensusEPS"], stock_data_earnings_three["actualEPS"],
stock_data_earnings_four["EPSReportDate"], stock_data_earnings_four["consensusEPS"], stock_data_earnings_four["actualEPS"]
))
except iexfinance.utils.exceptions.IEXSymbolError as error:
yield from client.send_message(message.channel, "Error: {0}".format(error))
except ValueError as error:
yield from client.send_message(message.channel, "Error: {0}".format(error))
#end !earnings
elif message.content.startswith('!heatmap'):
urllib.request.urlretrieve('https://finviz.com/grp_image.ashx?bar_sector_t.png', "heatmap.png")
yield from client.send_file(message.channel, 'heatmap.png')
#end !heatmap
elif message.content.upper().startswith('!TREEMAP'):
last_activity_timer = datetime.now()
e = discord.Embed()
e.set_image(url="https://finviz.com/map.ashx?t=sec")
#e.set_thumbnail(url=""https://finviz.com/map.ashx?t=sec")
yield from client.send_message(message.channel, embed=e)
# end !treemap
elif message.content.lower().startswith("!shout"):
f = open("TickersAndTimes.txt","r")
lines = f.readlines()
Alerts = []
test = False
for line in lines:
alert = line.split("\t")
for shout in Alerts:
test = False
if alert[1] == shout.ticker:
print(alert[1],shout.ticker)
test = True
if test is False:
print("appending %s" % alert[1])
try:
Alerts.append(Shout(alert[0],alert[1],alert[2],alert[3],alert[4],alert[5])) #mention ticker time price currentprice sentiment
except:
print("failure to append")
alertString = ''
space = ' '
tab = '\t'
newline = '\n'
for alert in Alerts:
page = urlopen("https://www.nasdaq.com/market-activity/stocks/"+str(alert.ticker)).read()
print("page")
soup = BeautifulSoup(page, "html5lib")
print("soup")
tr = soup.find_all("tr","summary-data__row")
for i in tr:
td = i.find_all("td","summary-data__cell")
c = 0
while c < len(td):
print(td[c])
if td[c] == "Today's High/Low":
print("Found it!")
string = td[c+1].split("/")
high = string[0]
low = string[1]
highdiff = (high - alert.price)/alert.price
lowdiff = (alert.price-low)/low
if lowdiff > highdiff:
change = "decreased"
highlow = low
difference = lowdiff
else:
change = "increased"
highlow = high
difference = highdiff
c+=1
else:
highlow = "f**k"
difference = "can't find it"
change = "dunno"
stringToAdd=alert.mention+" alerted us of " + alert.ticker + " at " + alert.time + " and $"+alert.price+". It then went from $" +alert.currentprice + " to $" + highlow + " giving us a " + difference + "% " + change + "." + newline
if (len(alertString) + len(stringToAdd)) < 2000:
alertString += stringToAdd
else:
if (len(alertString)) < 2000:
yield from client.send_message(message.channel,alertString)
yield from client.send_message(message.channel,alertString)
elif message.content.upper().startswith('!HOTSTOCKS'):
f = open("pprint.txt","w")
last_activity_timer = datetime.now()
page = urlopen("https://finviz.com/").read()
soup = BeautifulSoup(page, "html5lib")
tables = soup.find_all('table',class_='t-home-table')
for i in tables:
table_rows = i.find_all('tr', onmouseout="this.className='table-light-cp-row';")
print(i.text)
f.write(str(pprint(i)))
print("NEXT TABLE")
for j in table_rows:
print(j.text)
print("NEXT ROW")
f.close()
elif message.content.upper().startswith('!CHART'):
#!chart d amzn
split_message = message.content.upper().split(' ')
if 'D' in split_message[1]:
time = 'd'
#daily
elif '1M' in split_message[1]:
time = '1m'
#intraday is premium? not sure what the timeframe is set as
elif 'W' in split_message[1]:
time = 'w'
#week
elif 'MO' in split_message[1]:
time = 'm'
#month
else:
time = 'd'
ticker = split_message[2]
e = discord.Embed()
e.set_image(url="https://finviz.com/chart.ashx?t="+ticker+"&ty=c&ta=0&p="+time+"&s=l")
yield from client.send_message(message.channel, embed=e)
#end !chart
elif message.content.upper().startswith('!IPOLIST'):
last_activity_timer = datetime.now()
page = urlopen("https://www.nasdaq.com/markets/ipos/activity.aspx?tab=upcoming").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find('table')
#print(table)
table_body = table.find('tbody')
rows = table_body.find_all('tr')
if len(rows) == 3 and 'NASDAQ' in rows[0].text:
yield from client.send_message(message.channel, "```ain't none of them IPO sum bitches left dis here month```")
else:
data = prettytable.PrettyTable(["Company Name","Symbol","Market","Price","Shares","Offer Amount","Expected IPO Date"])
for row in rows:
cols = row.find_all('td')
cols = [ele.text.strip() for ele in cols]
data.add_row(cols)
if len(data.get_string()) > 1500:
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
data.clear_rows()
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
#print(data.get_string())
#end !ipolist
elif message.content.startswith('!calendar'):
last_activity_timer = datetime.now()
page = urlopen("https://anasdaq.econoday.com/byday.asp").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find_all('table')
#print(table[6])
table_body = table[6].find('tbody')
rows = table_body.find_all('tr')
data = prettytable.PrettyTable(["Time","For","Event","Value Name","Consensus","Actual"])
#data.vrules = prettytable.ALL
#data.hrules = prettytable.ALL
for row in rows[3:]:
cols = row.find_all('td')
cols = [ele.text.strip() for ele in cols]
if len(cols) == 6:
data.add_row(cols)
if len(data.get_string()) > 1500: #if our string is big, send and reset
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
data = prettytable.PrettyTable(["Time","For","Event","Value Name","Consensus","Actual"])
#data.vrules = prettytable.ALL
#data.hrules = prettytable.ALL
yield from client.send_message(message.channel, "```" + data.get_string() + "```") #send after we're 'really' done
#end !calendar
elif message.content.startswith('!fda'):
last_activity_timer = datetime.now()
page = urlopen("https://www.biopharmcatalyst.com/calendars/fda-calendar").read()
soup = BeautifulSoup(page, "html5lib")
table = soup.find('table')
#print(table)
table_body = table.find('tbody')
rows = table_body.find_all('tr')
data = prettytable.PrettyTable(["TICKER","DRUG","STAGE","CATALYST"])
count = 1
columns_to_grab = [0,2,3,4]
for row in rows:
cols = row.find_all('td')
cols = [ele.text.strip() for ele in (cols[x] for x in columns_to_grab)]
cols[1] = cols[1].splitlines()[0] #split off the drug stuff
cols[3] = cols[3].splitlines()[0] #split off the catalyst notes
#print(cols)
if len(data.get_string()) > 1000:
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
data = prettytable.PrettyTable(["TICKER","DRUG","STAGE","CATALYST"])
count = count + 1
data.add_row(cols)
if count > 2:
break
#end !fda
elif message.content.startswith('!ta'):
last_activity_timer = datetime.now()
stock_name = message.content[4:]
data = prettytable.PrettyTable(["Levels","Price"])
try:
stock_data = Stock(stock_name)
key_stats = stock_data.get_key_stats()
recent_data = stock_data.get_chart()
recent_data_input = []
for ele in recent_data:
recent_data_input.append(ele["high"])
#print(recent_data_input)
sup_res_data = gentrends(recent_data_input)
sup_res_data.seek(0) #return to 0, otherwise we get an empty file?
data.add_row(["52-Week High",key_stats["week52high"]])
data.add_row(["52-Week Low",key_stats["week52low"]])
yield from client.send_message(message.channel, "```" + data.get_string() + "```")
yield from client.send_file(message.channel, sup_res_data, content="", filename="daschart.png")
except iexfinance.utils.exceptions.IEXSymbolError as error:
yield from client.send_message(message.channel, "Error: {0}".format(error))
except ValueError as error:
yield from client.send_message(message.channel, "Error: {0}".format(error))
#end !ta
elif message.content.startswith('!command'):
list_of_commands = ['ta [stock]','todaysearnings','data [stock]','news [stock]','earnings [stock]','fda','calendar','ipolist','heatmap','chart [timeframe (D,W,M)] [stock]','buy [stock]','sell [stock]','bloomberg (in development)','upgrades/downgrades (in development)']
text = ''
for command in list_of_commands:
text += '!' + command + '\n'
yield from client.send_message(message.channel, text)
def format_result_string(*args):
return ' | '.join(args)
default_ticker = 'KO'
if len(sys.argv) == 1:
print(f"No ticker passed in as an arguement, default to {default_ticker}")
ticker = default_ticker
else:
ticker = sys.argv[1]
stock = Stock(ticker, output_format='pandas')
stock_name = stock.get_company_name()['companyName'].to_string()
stock_price = stock.get_price()['price'][ticker]
stock_eps = stock.get_key_stats()[ticker]['latestEPS']
flat_growth_estimate = 5
aaa_corporate_bond_yield = 3.56
stock_intrinsic_value = (stock_eps * (8.5 + (2 * flat_growth_estimate)) *
4.4) / aaa_corporate_bond_yield
norm_stock_intrinsic_value = stock_intrinsic_value / stock_price
print(
format_result_string(stock_name, ticker.upper(),
format_num_to_currency(stock_price),
float_to_percentage_string(flat_growth_estimate),
float_to_percentage_string(aaa_corporate_bond_yield),
format_num_to_currency(stock_eps),
format_num_to_currency(stock_intrinsic_value),
class TestFieldMethodsBatch(object):
def setup_class(self):
self.batch = Stock(["AAPL", "TSLA"])
self.batch2 = Stock(["AAPL", "TSLA"], output_format='pandas')
self.batch4 = Stock(["AAPL", "TSLA"],
json_parse_int=Decimal,
json_parse_float=Decimal)
def test_get_company_name(self):
data = self.batch.get_company_name()
assert isinstance(data, dict)
assert data["AAPL"] == "Apple Inc."
data2 = self.batch2.get_company_name()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
def test_get_primary_exchange(self):
data = self.batch.get_primary_exchange()
assert isinstance(data, dict)
assert data["AAPL"] == "Nasdaq Global Select"
data2 = self.batch2.get_primary_exchange()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
def test_get_sector(self):
data = self.batch.get_sector()
assert isinstance(data, dict)
assert data["AAPL"] == "Technology"
data2 = self.batch2.get_sector()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
def test_get_open(self):
data = self.batch.get_open()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_open()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_close(self):
data = self.batch.get_close()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_close()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_years_high(self):
data = self.batch.get_years_high()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_years_high()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_years_low(self):
data = self.batch.get_years_low()
assert isinstance(data, dict)
assert data["AAPL"] > 0
data2 = self.batch2.get_years_low()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_ytd_change(self):
data = self.batch.get_ytd_change()
assert isinstance(data, dict)
data2 = self.batch2.get_ytd_change()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
def test_get_volume(self):
data = self.batch.get_volume()
assert isinstance(data, dict)
assert data["AAPL"] > 50000
data2 = self.batch2.get_volume()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_market_cap(self):
data = self.batch.get_market_cap()
assert isinstance(data, dict)
assert data["AAPL"] > 1000000
data2 = self.batch2.get_market_cap()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_beta(self):
data = self.batch.get_beta()
assert isinstance(data, dict)
assert isinstance(data["AAPL"], float)
data2 = self.batch2.get_beta()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.batch4.get_beta()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
def test_get_short_interest(self):
data = self.batch.get_short_interest()
assert isinstance(data, dict)
assert data["AAPL"] > 50000
data2 = self.batch2.get_short_interest()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_short_ratio(self):
data = self.batch.get_short_ratio()
assert isinstance(data, dict)
assert isinstance(data["AAPL"], float)
data2 = self.batch2.get_short_ratio()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.batch4.get_short_ratio()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
def test_get_latest_eps(self):
data = self.batch.get_latest_eps()
assert isinstance(data, dict)
assert isinstance(data["TSLA"], float)
data2 = self.batch2.get_latest_eps()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["TSLA"].dtype == "float64"
data4 = self.batch4.get_latest_eps()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
def test_get_shares_outstanding(self):
data = self.batch.get_shares_outstanding()
assert isinstance(data, dict)
assert data["AAPL"] > 100000
data2 = self.batch2.get_shares_outstanding()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_float(self):
data = self.batch.get_float()
assert isinstance(data, dict)
assert data["AAPL"] > 1000000
data2 = self.batch2.get_float()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "int64"
def test_get_eps_consensus(self):
data = self.batch.get_eps_consensus()
assert isinstance(data, dict)
assert isinstance(data["AAPL"], float)
data2 = self.batch2.get_eps_consensus()
assert isinstance(data2, pd.DataFrame)
assert_index_equal(data2.index, pd.Index(self.batch2.symbols))
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.batch4.get_eps_consensus()
assert isinstance(data4, dict)
assert isinstance(data4["AAPL"], Decimal)
class TestFieldMethodsShare(object):
def setup_class(self):
self.share = Stock("AAPL")
self.share2 = Stock("AAPL", output_format='pandas')
self.share4 = Stock("AAPL",
json_parse_int=Decimal,
json_parse_float=Decimal)
self.share5 = Stock("TSLA")
def test_get_company_name(self):
data = self.share.get_company_name()
print(type(data))
assert isinstance(data, six.string_types)
assert data == "Apple Inc."
data2 = self.share2.get_company_name()
assert isinstance(data2, pd.DataFrame)
def test_get_primary_exchange(self):
data = self.share.get_primary_exchange()
assert isinstance(data, six.string_types)
assert data == "Nasdaq Global Select"
data2 = self.share2.get_primary_exchange()
assert isinstance(data2, pd.DataFrame)
def test_get_sector(self):
data = self.share.get_sector()
assert isinstance(data, six.string_types)
assert data == "Technology"
data2 = self.share2.get_sector()
assert isinstance(data2, pd.DataFrame)
def test_get_open(self):
data = self.share.get_open()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_open()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_open()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_close(self):
data = self.share.get_close()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_close()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_close()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_years_high(self):
data = self.share.get_years_high()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_years_high()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_years_high()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_years_low(self):
data = self.share.get_years_low()
assert isinstance(data, float)
assert data > 0
data2 = self.share2.get_years_low()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_years_low()
assert isinstance(data4, Decimal)
assert data4 > 0
def test_get_ytd_change(self):
data = self.share.get_ytd_change()
assert isinstance(data, float)
data2 = self.share2.get_ytd_change()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_ytd_change()
assert isinstance(data4, Decimal)
def test_get_volume(self):
data = self.share.get_volume()
assert isinstance(data, int)
assert data > 1000
data2 = self.share2.get_volume()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_volume()
assert isinstance(data4, Decimal)
assert data4 > 1000
def test_get_market_cap(self):
data = self.share.get_market_cap()
assert isinstance(data, int)
data2 = self.share2.get_market_cap()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_market_cap()
assert isinstance(data4, Decimal)
def test_get_beta(self):
data = self.share.get_beta()
assert isinstance(data, float)
data2 = self.share2.get_beta()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_beta()
assert isinstance(data4, Decimal)
def test_get_short_interest(self):
data = self.share.get_short_interest()
assert isinstance(data, int)
data2 = self.share2.get_short_interest()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_short_interest()
assert isinstance(data4, Decimal)
def test_get_short_ratio(self):
data = self.share.get_short_ratio()
assert isinstance(data, float)
data2 = self.share2.get_short_ratio()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_short_ratio()
assert isinstance(data4, Decimal)
def test_get_latest_eps(self):
data = self.share5.get_latest_eps()
assert isinstance(data, float)
data4 = self.share4.get_latest_eps()
assert isinstance(data4, Decimal)
def test_get_shares_outstanding(self):
data = self.share.get_shares_outstanding()
assert isinstance(data, int)
data2 = self.share2.get_shares_outstanding()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_shares_outstanding()
assert isinstance(data4, Decimal)
def test_get_float(self):
data = self.share.get_float()
assert isinstance(data, int)
data2 = self.share2.get_float()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "int64"
data4 = self.share4.get_float()
assert isinstance(data4, Decimal)
def test_get_eps_consensus(self):
data = self.share.get_eps_consensus()
assert isinstance(data, float)
data2 = self.share2.get_eps_consensus()
assert isinstance(data2, pd.DataFrame)
assert data2.loc["AAPL"].dtype == "float64"
data4 = self.share4.get_eps_consensus()
assert isinstance(data4, Decimal)
ticker = sheet['B' + str(row)].value
CompanyNameList.append(company_name)
TickerList.append(ticker)
wb.save('stock_screenv2.xlsx')
print('Adding biotech tickers ...')
res = requests.get('https://www.biopharmcatalyst.com/calendars/fda-calendar')
soup = bs4.BeautifulSoup(res.text, 'lxml')
for symbol in soup.find_all('td', class_= 'js-td--ticker'):
symbol = symbol.get_text().replace('\n','')
try:
if symbol not in symbols:
symbols.append(symbol)
ticker = Stock(symbol)
company_name = ticker.get_company_name()
CompanyNameList.append(company_name)
TickerList.append(ticker)
except:
print('Investigating :',company_name)
pass
lower = [x.lower() for x in CompanyNameList]
lower = [x.replace('.com', ' com') for x in lower]
lower = [x.replace('.', '') for x in lower]
lower = [x.replace(',', '') for x in lower]
lower = [x.replace('-', ' ') for x in lower]
lower = [x.replace('\xa0', ' ') for x in lower]
if '&' in lower:
lower = lower.replace('&', '&')
if ''' in lower: