def import_yahoofinance2():
# import stock_info module from yahoo_fin
from yahoo_fin import stock_info as si
# get live price of Apple
si.get_live_price("aapl")
# or Amazon
si.get_live_price("amzn")
# or any other ticker
si.get_live_price(ticker)
# get quote table back as a data frame
si.get_quote_table("aapl", dict_result = False)
# or get it back as a dictionary (default)
si.get_quote_table("aapl")
si.get_top_crypto()
# get most active stocks on the day
si.get_day_most_active()
# get biggest gainers
si.get_day_gainers()
# get worst performers
si.get_day_losers()
def post_market(self):
root = {}
root["market"] = {}
""" Market Node """
day_gainers = si.get_day_gainers().to_dict(orient="dict")
day_losers = si.get_day_losers().to_dict(orient="dict")
top_crypto = si.get_top_crypto().to_dict(orient="dict")
most_active = si.get_day_most_active().to_dict(orient="dict")
new_node = {"Day_Gainers" : day_gainers,
"Day_Losers" : day_losers,
"Top_Crypto" : top_crypto,
"Most_Active" : most_active}
for node_key in new_node.keys():
now = str(datetime.date(datetime.now()))
key_var = now
self.post(key_var, new_node[node_key], "Market", node_key)
time.sleep(.5)
print('Sucess\n')
def topcrypto():
"""Returns: cryptocurrency with the highest price in a given day and its name
with format: 'CRYPTO': 'PRICE'."""
top_crypto = si.get_top_crypto()
output = str(top_crypto.at[0, 'Symbol']) + ': ' + str(
round(si.get_live_price(top_crypto.at[0, 'Symbol']), roundNumber))
return output
def tab_crypto():
new_tab = []
tab = si.get_top_crypto()
tab = np.array(tab)
for i in tab:
array = np.array(i)
new_tab.append([array[0], array[1]])
return new_tab
def ethereum_change():
crypt=get_top_crypto()
ethereum=crypt['Name']
ethereum_price=crypt['Price (Intraday)']
ethereum_change=crypt['% Change']
if ethereum_change[0] >=0:
result='up'
else:
result='down'
return(f"{ethereum[1]} is trading at {'${:,.2f}'.format(ethereum_price[1])}, {result} {'{:.2%}'.format(ethereum_change[1]/100)}.")
def bitcoin_change():
crypt=get_top_crypto()
bitcoin=crypt['Name']
bitcoin_price=crypt['Price (Intraday)']
bitcoin_change=crypt['% Change']
if bitcoin_change[0] >=0:
result='up'
else:
result='down'
return(f"{bitcoin[0]} is trading at {'${:,.2f}'.format(bitcoin_price[0])}, {result} {'{:.2%}'.format(bitcoin_change[0]/100)}.")
def functions_type():
#VERIF TAILLE DU TABLEAU
if var_text.get() > 0 and var_text.get() < 101:
if type_ == "stock_gainers":
tab = si.get_day_gainers()
elif type_ == "stock_losers":
tab = si.get_day_losers()
elif type_ == "crypto":
tab = si.get_top_crypto()
else:
print("error1")
#convert in table
tab = np.array(tab)
affichage_tab(tab)
def main():
# creating object of TwitterClient Class
q_word = "BTC"
api = TwitterClient()
output = []
i = 0
#Section to run in a loop
# calling function to get tweets
while (i < 480):
#print("Mining Tweets")
tweets = api.get_tweets(query=q_word, count=100)
#print("Example of a tweet")
#print(tweets[0])
#print(len(tweets))
BTC = si.get_top_crypto()
btcp = BTC["Price (Intraday)"].tolist()
btcp = btcp[0]
#print(btcp)
# picking positive tweets from tweets
ptweets = [
tweet for tweet in tweets if tweet['sentiment'] == 'positive'
]
# percentage of positive tweets
#print("Positive tweets percentage: {} %".format(100*len(ptweets)/len(tweets)))
# picking negative tweets from tweets
ntweets = [
tweet for tweet in tweets if tweet['sentiment'] == 'negative'
]
# percentage of negative tweets
#print("Negative tweets percentage: {} %".format(100*len(ntweets)/len(tweets)))
# percentage of neutral tweets
#print("Neutral tweets percentage: {} % \
# ".format(100*(len(tweets) -(len( ntweets )+len( ptweets)))/len(tweets)))
#Calculate Summary Stats to Save
ptweetp = 100 * len(ptweets) / len(tweets)
ntweetp = 100 * len(ntweets) / len(tweets)
dtg = datetime.now()
myTup = (btcp, ptweetp, ntweetp, dtg)
print(myTup)
output.append(myTup)
time.sleep(60)
i = i + 1
print("Loop Complete")
print(output)
# printing first 5 positive tweets
print("\n\nPositive tweets:")
for tweet in ntweets[:10]:
print(tweet['text'])
# printing first 5 negative tweets
print("\n\nNegative tweets:")
for tweet in ntweets[:10]:
print(tweet['text'])
#Save to a pickle
with open('outputBTC.txt', 'wb') as fp:
pickle.dump(output, fp)
def btc_price(self):
top = si.get_top_crypto()
btc = top['Symbol'][0]
price = top['Price (Intraday)'][0]
self.engine.say("The current price of Bitcoin is " + str(price))
self.engine.runAndWait()
async def on_message(message):
print(message.content)
if message.content.find("!") != -1:
content = message.content.strip('!').lower().split()
print(content)
print(content[0])
if content[0] == "day":
if content[1] == "gain":
await message.channel.send(
si.get_day_gainers().head(10).iloc[:, :3])
await message.channel.send(
"-------------------------------------------")
await message.channel.send(
si.get_day_gainers().head(10).iloc[:, 4:7])
elif content[1] == "lose":
await message.channel.send(
si.get_day_losers().head(10).iloc[:, :3])
await message.channel.send(
"-------------------------------------------")
await message.channel.send(
si.get_day_losers().head(10).iloc[:, 4:7])
elif content[1] == "active":
await message.channel.send(
si.get_day_most_active().head(10).iloc[:, :3])
await message.channel.send(
"-------------------------------------------")
await message.channel.send(
si.get_day_most_active().head(10).iloc[:, 4:7])
elif content[0] == "crypto":
await message.channel.send(si.get_top_crypto().head(10).iloc[:, :3]
)
await message.channel.send(
"-------------------------------------------")
await message.channel.send(si.get_top_crypto().head(10).iloc[:,
4:5])
elif content[0] == "help":
embedVar = discord.Embed(title="List of functioning commands",
description="",
colour=0x00ff00)
embedVar.add_field(name="\u200b",
value="!tsla\n!day gain\n!day loss",
inline=True)
embedVar.add_field(
name="\u200b",
value="!calls tlsa 03/19/2021\n!puts tlsa 03/19/2021",
inline=True)
await message.channel.send(embed=embedVar)
elif content[0] == "calls":
await message.channel.send(
op.get_calls(content[1], content[2]).iloc[:, 2:8])
elif content[0] == "puts":
await message.channel.send(
op.get_puts(content[1], content[2]).iloc[:, 2:8])
else:
temp = si.get_quote_table(content[0])
change = round(temp["Quote Price"] - temp["Previous Close"], 2)
percentage = round(change / temp["Previous Close"] * 100, 2)
displayQuote = str(round(temp["Quote Price"], 2))
displayChange = str(change)
displayPercentage = str(percentage)
displayTicker = content[0].upper()
displayClose = str(round(temp["Previous Close"], 2))
dayRange = temp["Day's Range"].replace('-', '').split()
dayLow = dayRange[0]
dayHigh = dayRange[1]
open = temp["Open"]
close = temp["Previous Close"]
volume = str(round(temp["Volume"] / 1000000, 2))
volume = volume + "M"
avgVolume = str(round(temp["Avg. Volume"] / 1000000, 2))
avgVolume = avgVolume + "M"
bid = temp["Bid"]
ask = temp["Ask"]
if change >= 0:
rgb = 0x00ff00
displayChange = "+" + displayChange
displayPercentage = "+" + displayPercentage
else:
rgb = 0xff0000
embedVar = discord.Embed(
title=
f"${displayTicker}\n${displayQuote} {displayChange} ({displayPercentage}%)",
description="",
colour=rgb)
embedVar.add_field(
name="\u200b",
value=
f"High: {dayHigh}\nLow: {dayLow}\n\nAsk: {ask}\nBid: {bid}",
inline=True)
embedVar.add_field(name="\u200b",
value=f"Open: {open}\nPrev.: {close}",
inline=True)
embedVar.add_field(
name="\u200b",
value=f"Volume: {volume}\nAvg. Vol.: {avgVolume}",
inline=True)
await message.channel.send(embed=embedVar)
def getTopCrypto(self):
#TODO
topCrypto = si.get_top_crypto()[0:10]
return topCrypto
def main():
#Initialize
userInput = ''
#Program will run until 5 is entered
while userInput != "5":
userInput = mainMenu()
#Look up Stock
if userInput == "1":
#Initialize
subSelect = ''
#Get symbol, validate, print current price, opening price, previous close
symbol = getStock()
if symbol != 'Q':
quoteTable = si.get_quote_table(symbol)
print("Current price: $", round(si.get_live_price(symbol), 3),
" as of", currentTime())
print("Opening price: $", quoteTable['Open'], \
"\nPrevious closing price: $", quoteTable['Previous Close'])
#Stay on submenu until 5 is entered
while subSelect != '5':
subSelect = subMenu()
#Get date range and plot historical price
if subSelect == '1':
selection = 'Y'
while selection == 'Y':
plot(getStockData(symbol), "index", "close",
"Price ($)")
selection = input(
"Would you like to enter a new set of dates? (Y/N) "
)
#Get date range and plot historical volume
if subSelect == '2':
selection = 'Y'
while selection == 'Y':
plot(getStockData(), "index", "volume", "Volume ")
selection = input(
"Would you like to enter a new set of dates? (Y/N) "
)
#Add stock to a watchlist
if subSelect == '3':
columns = ['Name']
#Try to open existing watchlist and add stock to it
try:
watchlist = pd.read_csv("watchlist.csv",
header=0,
delim_whitespace=True)
add = pd.DataFrame([symbol],
index=None,
columns=columns)
watchlist = watchlist.append(add, True)
watchlist.to_csv('watchlist.csv', index=False)
#Create new watchlist file and add stock to it
except:
add = pd.DataFrame([symbol],
index=None,
columns=columns)
add.to_csv('watchlist.csv', index=False)
print("This stock has been added to your watchlist\n")
#Update the live price
if subSelect == '4':
print("Current price: $",
round(si.get_live_price(symbol), 3), " as of",
currentTime())
#Print Watchlist
if userInput == "2":
#Try to open watchlist. Look up live price for each stock on the list. print the resulting Dataframe
try:
watchlist = pd.read_csv("watchlist.csv",
header=0,
delim_whitespace=True)
npWatchlist = watchlist.to_numpy()
price = []
for i in range(0, len(npWatchlist)):
price.append(round(si.get_live_price(npWatchlist[i][0]),
3))
watchlist['price'] = price
watchlist = watchlist.set_index('Name')
print(watchlist)
#Error message if watchlist does not exist
except:
print(
"Watchlist is currently empty. Feel free to add stocks to your watchlist under the Look up Stock option in the main menu"
)
#Prints top 10 gainers and losers
if userInput == "3": #Gainers Losers
gainers = si.get_day_gainers()
deleteData = [
'Change', 'Volume', 'Avg Vol (3 month)', 'Market Cap',
'PE Ratio (TTM)'
]
print("Top Gainers\n")
dfTrimmer(gainers, deleteData)
losers = si.get_day_losers()
print("\nTop Losers\n")
dfTrimmer(losers, deleteData)
#Prints top 10 crypto by market cap
if userInput == "4":
crypto = si.get_top_crypto()
delete = [
"Market Cap", "Volume in Currency (Since 0:00 UTC)",
'Volume in Currency (24Hr)',
'Total Volume All Currencies (24Hr)', 'Circulating Supply'
]
print("The top 10 Cryptocurrencies by Market Cap:")
dfTrimmer(crypto, delete)
#If user enters invalid input
elif userInput != '5' and userInput != '1' and userInput != '2' and userInput != '3' and userInput != '4':
print("Selection not recognized try again")
