def eight_k():
eight_dic = {
'Item 1.03': 'Bankruptcy or Receivership',
'Item 1.04': 'Mine Safety - Reporting of Shutdowns and Patterns of Violations',
'Item 2.04': 'Triggering Events That Accelerate or Increase a Direct Financial Obligation or an Obligation under an Off-Balance Sheet Arrangement',
'Item 2.05': 'Costs Associated with Exit or Disposal Activities',
'Item 2.06': 'Material Impairments',
'Item 3.01': 'Notice of Delisting or Failure to Satisfy a Continued Listing Rule or Standard; Transfer of Listing',
'Item 4.02': 'Non-Reliance on Previously Issued Financial Statements or a Related Audit Report or Completed Interim Review',
'Item 5.04': 'Temporary Suspension of Trading Under Registrant"s Employee Benefit Plans',
'Item 6.04': 'Failure to Make a Required Distribution',}
a = feedparser.parse('http://www.sec.gov/cgi-bin/browse-edgar?action=getcurrent&CIK=&type=8-k&company=&dateb=&owner=include&start=0&count=100&output=atom')
time.sleep(2)
today = datetime.datetime.today()
for entry in range(0,99):
try:
company_name = a.entries[entry].title.lower()
company_summary = a.entries[entry].summary
for key in eight_dic:
if key in company_summary:
last25 = slice(-25, None)
if company_name[last25] not in stocks_sent:
day = a.entries[entry].updated
day = day.split('T')
t = day[0]
if t in str(today):
try:
cik = company_name[company_name.find("(")+1:company_name.find(")")]
stocks_sent.append(company_name[last25])
headers = {'Ocp-Apim-Subscription-Key': 'GETYOUROWNSUBSCRIPTIONKEY',}
params = urllib.parse.urlencode({})
conn = http.client.HTTPSConnection('services.last10k.com')
conn.request("GET", "/v1/company/"+cik+"/ticker?%s" % params, "{body}", headers)
responsed = conn.getresponse()
with responsed as response:
html_content = response.read()
ticker = html_content
ticker = str(ticker)
ticker = ticker.replace("b","")
ticker = ticker.replace('"','')
ticker = ticker.replace("'","")
ticker = ticker.replace(" ","")
ticker = ticker.upper()
symbol = ticker
conn.close()
desc = eight_dic.get(key)
ticker = Stock(ticker)
current_price = ticker.get_price()
message = company_name+'\n'+symbol+'\n$'+str(current_price)+'\n\n'+key+'\n'+desc
confirm(text=message, title='Short Option', buttons=['OK'])
print(key,'\n',desc,'\n~~~~~~~~~~~~~~~~~~~~')
except:
print('research fail: ',company_name)
pass
except:
print('da fuk? Re 8k')
pass
def getStock(name):
# get data from API - use the Python requests library
# process input to pull out the right values needed
# calculate the sharpe ratio
# return the sharpe ratio
stock = Stock(name)
return str(stock.get_price())
class IEXSecurity:
def __init__(self, ticker):
self.ticker = ticker
self.security = Stock(ticker)
def get_price(self):
return self.security.get_price()
def data(tickers, sector):
slist = []
print(tickers)
stocks_object = Stock(tickers)
stocks = stocks_object.get_price()
now = datetime.now()
last_year = datetime.now() - timedelta(days=365)
date = datetime.today().strftime('%Y-%m-%d')
for company in stocks:
# Create one-year graph trend for company
df = web.DataReader(company, 'robinhood', datetime(last_year.year, last_year.month, last_year.day), datetime(now.year, now.month, now.day)).reset_index()
data = [go.Scatter(x=df.begins_at, y=df.close_price)]
layout = go.Layout(title=company, xaxis={'title': 'Date'}, yaxis={'title':'Close Price'})
figure = go.Figure(data=data, layout=layout)
link = py.plot(figure, filename=company)
# Get closing price of company
price = stocks[company]
# Link to company graph
company_graph = "[{}]({})".format(company, link)
# Output company info
slist.append([date, company_graph, price])
output(slist)
def index():
form = investmentForm()
if request.method == 'POST' and form.validate():
#Get form field data
symb = form.stockSymbol.data
stock = Stock(symb)
openPrice = stock.get_open()
nowPrice = stock.get_price()
companyInfo = stock.get_company()
companyName = companyInfo['companyName']
symbol = companyInfo['symbol']
calculate = openPrice - nowPrice
calc = "{:.2f}".format(calculate)
ct = datetimeConverstion()
percentage = ((openPrice - nowPrice) / openPrice) * 100
percent = "{:.2f}".format(percentage)
new_date = ct.strftime('%A %Y-%m-%d %I:%M %p')
return render_template('price.html',
symbol=symbol,
companyName=companyName,
nowPrice=nowPrice,
new_date=new_date,
calc=calc,
percent=percent)
return render_template('home.html', form=form)
def update_header(submit, input_value):
b = Stock(input_value)
name = pd.DataFrame([b.get_company()])
name = name['companyName'].values[0]
f = str(b.get_price())
title = name + ' $' + f
return title
def price(ticker):
try:
ticker = Stock(ticker.ticker)
price = ticker.get_price()
except:
return "---"
else:
return price
def fetch_market_data(tickers):
prices = {}
for i in range(0, len(tickers), 99):
# print('{}/{}'.format(i, len(tickers)))
stock = Stock(tickers[i:i + 99])
batch_prices = {ticker: (datetime.now(), value) for ticker, value in stock.get_price().items()}
prices.update(batch_prices)
batch_prices = {ticker: (datetime.now(), value) for ticker, value in Stock(tickers[-(len(tickers) % 99):]).get_price().items()}
prices.update(batch_prices)
return prices
def main(argv):
print("name\tprice\topen\tvariation")
for n in argv:
try:
s = Stock(n)
price = s.get_price()
open = s.get_open()
variation = 100 * (price - open) / open
print("{}\t{}\t{}\t{:.3f} %".format(n, price, open, variation))
except:
sys.stderr.write("error fetching data for '{}'\n".format(n))
def chat(msg):
global dictionary,pending,pending_action,state,my_friend
print(msg)
usermessage=txt_recog(msg)
if usermessage=='quit':
my_friend.send(get_chatbotanswer('See you.'))
sys.exit()
intent=interprete(interpreter,usermessage)['intent']['name']
entities=extract_entities(nlp,usermessage)
Org=Check_Org(entities)
intent_=(check_intents(intent))
dictionary,pending,pending_action,state=bot_reply(intent_,state,pending,Org,pending_action,dictionary)
if state==END:
my_friend.send(get_chatbotanswer('See you.'))
sys.exit()
action=pending_actions()
if pending is not 0:
my_friend.send(get_chatbotanswer(action[pending_action]))
if state is not 0 and state is not 3 and state is not 5:
my_friend.send(get_chatbotanswer(state_change_action(state)))
if (dictionary['function'] is not None) and (dictionary['company']is not None):
CPN=Stock(get_ticker_symbol(dictionary['company']))
if dictionary['function']=='b':
if error_check1(CPN)==1:
p_CPN=CPN.get_price()
state=FOUND
my_friend.send(get_chatbotanswer('Ok,I have found it! The price of {0} is {1}$'.format(dictionary['company'],p_CPN) ))
else:
my_friend.send(get_chatbotanswer('Information of company not found'))
state=NOTFOUND
if dictionary['function']=='c':
if error_check2(CPN)==1:
mv_CPN=CPN.get_volume()
my_friend.send(get_chatbotanswer('Ok,I have found it!'))
state=FOUND
my_friend.send(get_chatbotanswer('The volume of {0} is {1}'.format(dictionary['company'],mv_CPN) ))
else:
my_friend.send(get_chatbotanswer('Information of company not found'))
state=NOTFOUND
if dictionary['function']=='d':
if error_check3(CPN)==1:
mc_CPN=CPN.get_market_cap()
my_friend.send(get_chatbotanswer('Ok,I have found it!'))
state=FOUND
my_friend.send(get_chatbotanswer('The market value of {0} is {1}$'.format(dictionary['company'],mc_CPN)))
else:
my_friend.send(get_chatbotanswer('Information not found'))
state=NOTFOUND
if state == FOUND or state==NOTFOUND :
my_friend.send(get_chatbotanswer('Do you have other questions? Say "quit" to quit'))
state=INIT
def get_list_price(self, code_list):
# check if there is only one code in list
if len(code_list) == 1:
return self.get_price(code_list[0])
# use list to directly query
user_stocks = IEXStock(code_list)
try:
return user_stocks.get_price()
except:
return ("No saved stock in record")
def get_prices_in_range():
with open('NDQTickers.csv') as csvfile:
reader = csv.reader(csvfile)
for row in reader:
#print(row[0])
if len(row[0]) > 4:
continue
else:
ticker = Stock(row[0])
price = ticker.get_price()
if 10 < price < 250:
tickersInRange.append(row[0])
#print(row[0] + " " + str(ticker.get_price()))
return tickersInRange
def run(self, dispatcher, tracker, domain):
company_x = tracker.get_slot('company')
symbols = get_available_symbols()
for i in range(len(symbols)):
if company_x.lower() in symbols[i]["name"].lower():
company = symbols[i]["symbol"]
companyobj = Stock(company)
price = companyobj.get_price()
response = """{} shares is {} currently.""".format(company, price)
dispatcher.utter_message(response)
return [SlotSet('company', company)]
def get_ma(ticker): stock = Stock(ticker) start = now - timedelta(days=25) try: keyStats = stock.get_key_stats() if (stock.get_price() < 5): return -1,-1,-1 df_hist = get_historical_data(ticker, start=start, end=now, output_format='pandas') dma50 = keyStats['day50MovingAvg'] dma10 = df_hist.tail(10)['close'].mean() dma20 = df_hist.tail(20)['close'].mean() except: return -1,-1,-1 return dma10, dma20, dma50
def get_price(sym):
start = time.time()
pattern = re.compile(r'^\$([0-9]+\.[0-9]+)', re.MULTILINE)
try:
symbol = Stock(sym)
price = symbol.get_price()
except:
soup = pull_website(sym)
text = soup.find('p', {'class':f'last_price'})
if not hasattr(text, 'text'):
text = soup.find('div', {'class':f'last_price_mf'})
#print(text.text)
price = re.search(pattern, text.text).group(1)
end = time.time()
#print(f'{sym} price generation took {end-start} seconds')
return float(price)
def get_ma(ticker):
stock = Stock(ticker)
start = now - timedelta(days=25)
try:
keyStats = stock.get_key_stats()
if (stock.get_price() < 5):
return -1, -1, -1
df_hist = get_historical_data(ticker,
start=start,
end=now,
output_format='pandas')
dma50 = keyStats['day50MovingAvg']
dma10 = df_hist.tail(10)['close'].mean()
dma20 = df_hist.tail(20)['close'].mean()
except:
return -1, -1, -1
return dma10, dma20, dma50
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>
class TestBatch(object):
def setup_class(self):
self.cbatch = Stock(["aapl", "tsla"])
def test_invalid_symbol_or_symbols(self):
with pytest.raises(IEXSymbolError):
Stock(["TSLA", "AAAPLPL", "fwoeiwf"])
def test_get_all_format(self):
data = self.cbatch.get_all()
assert isinstance(data, dict)
def test_get_chart_format(self):
data = self.cbatch.get_chart()
assert isinstance(data, dict)
def test_get_book_format(self):
data = self.cbatch.get_book()
assert isinstance(data, dict)
def test_get_open_close_format(self):
data = self.cbatch.get_open_close()
assert isinstance(data, dict)
def test_get_previous_format(self):
data = self.cbatch.get_previous()
assert isinstance(data, dict)
def test_get_company_format(self):
data = self.cbatch.get_company()
assert isinstance(data, dict)
def test_get_key_stats_format(self):
data = self.cbatch.get_key_stats()
assert isinstance(data, dict)
def test_get_relevant_format(self):
data = self.cbatch.get_relevant()
assert isinstance(data, dict)
def test_get_news_format(self):
data = self.cbatch.get_news()
assert isinstance(data, dict)
def test_get_financials_format(self):
data = self.cbatch.get_financials()
assert isinstance(data, dict)
def test_get_earnings_format(self):
data = self.cbatch.get_earnings()
assert isinstance(data, dict)
def test_get_logo_format(self):
data = self.cbatch.get_logo()
assert isinstance(data, dict)
def test_get_price_format(self):
data = self.cbatch.get_price()
assert isinstance(data, dict)
def test_get_delayed_quote_format(self):
data = self.cbatch.get_delayed_quote()
assert isinstance(data, dict)
def test_get_effective_spread_format(self):
data = self.cbatch.get_effective_spread()
assert isinstance(data, dict)
def test_get_volume_by_venue_format(self):
data = self.cbatch.get_volume_by_venue()
assert isinstance(data, dict)
def test_get_select_ep_bad_params(self):
with pytest.raises(ValueError):
self.cbatch.get_select_endpoints()
with pytest.raises(IEXEndpointError):
self.cbatch.get_select_endpoints("BADENDPOINT")
def test_ohlc(self):
data = self.cbatch.get_ohlc()
assert isinstance(data, dict)
def test_time_series(self):
data = self.cbatch.get_time_series()
data2 = self.cbatch.get_chart()
assert data == data2
def test_nondefault_params_1(self):
data = Stock(["AAPL", "TSLA"], _range='5y')
data2 = Stock(["AAPL", "TSLA"])
assert len(data.get_chart()["AAPL"]) > len(data2.get_chart()["AAPL"])
assert len(data.get_chart()["TSLA"]) > len(data2.get_chart()["TSLA"])
def test_nondefault_params_2(self):
data = Stock(["AAPL", "TSLA"], last=37)
assert len(data.get_news()["AAPL"]) == 37
assert len(data.get_news()["TSLA"]) == 37
def analyse_data(self, filename, coin, formatted_cryptocurrency_tweets,
j_info):
tweetsInHour = []
print("Number of unique tweets in an hour for " + coin + " is " +
str(len(formatted_cryptocurrency_tweets)))
file_exists = os.path.isfile(filename)
if sentiment_config.TYPE == "CRYPTO":
change = j_info['ticker']['change']
volume = j_info['ticker']['volume']
self.price = j_info['ticker']['price']
timestamp = j_info['timestamp']
else:
stock = Stock(sentiment_config.EXCHANGE)
change = stock.get_price() - self.price
volume = stock.get_volume()
self.price = stock.get_price()
timestamp = datetime.datetime.now().strftime("%H:%M:%S")
try:
# average compound
average_compound = float(
sum(d['sentiment']['compound']
for d in formatted_cryptocurrency_tweets)) / len(
formatted_cryptocurrency_tweets)
cryptoFeature = {
'TimeStamp': [timestamp],
'Sentiment': [average_compound],
'Volume': [volume],
'Change': [change],
'Price': [self.price],
'NoOfTweets': [len(formatted_cryptocurrency_tweets)]
}
formatted_cryptocurrency_tweets = []
pd.DataFrame.from_dict(data=cryptoFeature,
orient='columns').to_csv(
filename,
mode='a',
header=not file_exists)
# Make Predictions
linear_predict_change = predict.generate_linear_prediction_model(
cryptoFeature, filename)
multi_linear_predict_change = predict.generate_multi_linear_prediction_model(
cryptoFeature, filename)
tree_predict_change = predict.generate_tree_prediction_model(
cryptoFeature, filename)
forest_predict_change = predict.generate_forest_prediction_model(
cryptoFeature, filename)
if linear_predict_change is not None and multi_linear_predict_change is not None\
and tree_predict_change is not None and forest_predict_change is not None:
#get average prediction
average_prediction = (float(linear_predict_change) +
float(multi_linear_predict_change) +
float(tree_predict_change) +
float(forest_predict_change)) / 4
self.notify_user(str(average_prediction),
str(cryptoFeature['Sentiment'][0]))
#Plotting
self.cryptocurrency_current_price.append(self.price)
self.cryptocurrency_plot_time.append(
datetime.datetime.now().strftime("%H:%M:%S"))
print("Linear " + linear_predict_change)
print("Multi Linear" + multi_linear_predict_change)
print("Forest" + forest_predict_change)
self.plot(linear_predict_change, multi_linear_predict_change,
tree_predict_change, forest_predict_change)
else:
print("Still building set")
except Exception as e:
print("No tweets in the last hour", str(e))
def setUp(self):
stock = Stock(["GOOG", "TSLA"])
self.company = stock.get_price()
# https://pypi.org/project/iexfinance/
# Stock
from iexfinance import Stock
tsla = Stock('TSLA')
print('TSLA open: %f' % tsla.get_open())
print('TSLA price: %f' % tsla.get_price())
# Historical Data
from iexfinance import get_historical_data
from datetime import datetime
import pandas as pd
start = datetime(2014, 1, 1)
end = datetime(2018, 10, 1)
aapl_hist_df = get_historical_data("AAPL", start=start, end=end, output_format='pandas')
days_from_start = []
for x in aapl_hist_df.axes[0]:
dt = datetime.strptime(x, "%Y-%m-%d")
if start is None:
start = dt
diff = dt - start
days_from_start.append(diff.days)
aapl_hist_closing_df = pd.DataFrame({'price': aapl_hist_df['close'], 'days_from_start': days_from_start})
# Chart it
import matplotlib.pyplot as plt
end = datetime.today()
df = get_historical_data('MMM', start=start, end=end, output_format='pandas')
df['date'] = df.index
#df.drop(['date'],axis=1)
df.reset_index(level=0, inplace=True)
scipy.io.savemat('test.mat', {'struct': df.to_dict('list')})
#IES Market Data
a = get_market_tops('TSLA', output_format='pandas')
get_market_last()
get_market_deep()
get_market_book()
# IEX stats
get_stats_intraday()
get_stats_recent()[0]
get_stats_records()
get_stats_daily(last=3)
get_stats_monthly(start=datetime(2017, 2, 9), end=datetime(2017, 5, 24))[0]
b = get_stats_intraday('TSLA')
tsla = Stock(['TSLA', 'AAPL'], output_format='pandas')
tsla.get_open()
tsla.get_price()
df = get_historical_data("AAPL", start=start, end=end, output_format='pandas')
df.head()
df.tail()
df.plot()
plt.show()
def get_price(sym):
symbol = Stock(sym)
price = symbol.get_price()
return price
from iexfinance import Stock
from datetime import datetime
stockname = "GE"
stock = Stock(stockname)
lastprice = 0
while (True):
curprice = stock.get_price()
if (curprice != lastprice):
lastprice = curprice
print(str(datetime.now().time()) + " | " + str(curprice))
def quote(name):
stock = Stock(name)
return stock.get_price()
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),
'{:.2f}'.format(norm_stock_intrinsic_value)))
class TestShareDefault(object):
def setup_class(self):
self.cshare = Stock("aapl")
self.cshare2 = Stock("aapl", output_format='pandas')
self.cshare3 = Stock("svxy")
self.cshare4 = Stock("aapl",
json_parse_int=Decimal,
json_parse_float=Decimal)
self.cshare5 = Stock("gig^")
def test_invalid_symbol(self):
data = Stock("BAD SYMBOL")
with pytest.raises(IEXSymbolError):
data.get_price()
def test_get_all_format(self):
data = self.cshare.get_all()
assert isinstance(data, dict)
def test_get_all(self):
data = self.cshare.get_all()
assert len(data) == 20
def test_get_endpoints(self):
data = self.cshare.get_endpoints(["price"])
assert list(data) == ["price"]
def test_get_endpoints_bad_endpoint(self):
with pytest.raises(IEXEndpointError):
self.cshare.get_endpoints(["BAD ENDPOINT", "quote"])
with pytest.raises(IEXEndpointError):
self.cshare.get_endpoints("BAD ENDPOINT")
def test_get_book_format(self):
data = self.cshare.get_book()
assert isinstance(data, dict)
data2 = self.cshare2.get_book()
assert isinstance(data2, pd.DataFrame)
def test_get_chart_format(self):
data = self.cshare.get_chart()
assert isinstance(data, list)
data2 = self.cshare2.get_chart()
assert isinstance(data2, list)
def test_get_chart_params(self):
data = self.cshare.get_chart()
# Test chart ranges
data2 = self.cshare.get_chart(range_='1y')
assert 15 < len(data) < 35
assert 240 < len(data2) < 260
# Test chartSimplify
data4 = self.cshare.get_chart(chartSimplify=True)[0]
assert "simplifyFactor" in list(data4)
data5 = self.cshare.get_chart(range_='1y', chartInterval=5)
assert 45 < len(data5) < 55
@pytest.mark.xfail(reason="This test only runs correctly between 00:00 and"
"09:30 EST")
def test_get_chart_reset(self):
# Test chartReset
data3 = self.cshare.get_chart(range_='1d', chartReset=True)
assert data3 == []
def test_get_company_format(self):
data = self.cshare.get_company()
assert isinstance(data, dict)
data2 = self.cshare2.get_company()
assert isinstance(data2, pd.DataFrame)
def test_get_delayed_quote_format(self):
data = self.cshare.get_delayed_quote()
assert isinstance(data, dict)
data2 = self.cshare2.get_delayed_quote()
assert isinstance(data2, pd.DataFrame)
def test_get_dividends_format(self):
data = self.cshare.get_dividends()
assert isinstance(data, list)
data2 = self.cshare2.get_dividends()
assert isinstance(data2, list)
def test_get_dividends_params(self):
data = self.cshare.get_dividends()
data2 = self.cshare.get_dividends(range_='2y')
data3 = self.cshare.get_dividends(range_='5y')
assert len(data) < len(data2) < len(data3)
def test_get_earnings_format(self):
data = self.cshare.get_earnings()
assert isinstance(data, list)
data2 = self.cshare2.get_earnings()
assert isinstance(data2, pd.DataFrame)
# Ensure empty list is returned for symbol with no earnings
data3 = self.cshare5.get_earnings()
assert isinstance(data3, list)
def test_get_effective_spread_format(self):
data = self.cshare.get_effective_spread()
assert isinstance(data, list)
data2 = self.cshare2.get_effective_spread()
assert isinstance(data2, pd.DataFrame)
def test_get_financials_format(self):
data = self.cshare.get_financials()
assert isinstance(data, list)
data2 = self.cshare2.get_financials()
assert isinstance(data2, pd.DataFrame)
# Ensure empty list is returned even when ticker has no financials
data3 = self.cshare5.get_financials()
assert isinstance(data3, list)
def test_get_key_stats_format(self):
data = self.cshare.get_key_stats()
assert isinstance(data, dict)
data2 = self.cshare2.get_key_stats()
assert isinstance(data2, pd.DataFrame)
def test_get_largest_trades(self):
data = self.cshare.get_largest_trades()
assert isinstance(data, list)
data2 = self.cshare2.get_largest_trades()
assert isinstance(data2, pd.DataFrame)
def test_get_logo_format(self):
data = self.cshare.get_logo()
assert isinstance(data, dict)
data2 = self.cshare2.get_logo()
assert isinstance(data2, pd.DataFrame)
def test_get_news_format(self):
data = self.cshare.get_news()
assert isinstance(data, list)
@pytest.mark.xfail(reason="Provider error. Awaiting patch.")
def test_get_news_params(self):
data = self.cshare.get_news(last=15)
assert len(data) == 15
def test_ohlc(self):
data = self.cshare.get_ohlc()
assert isinstance(data, dict)
data2 = self.cshare2.get_ohlc()
assert isinstance(data2, pd.DataFrame)
def test_get_open_close_format(self):
data = self.cshare.get_open_close()
assert isinstance(data, dict)
data2 = self.cshare2.get_open_close()
assert isinstance(data2, pd.DataFrame)
def test_get_peers_format(self):
data = self.cshare.get_peers()
assert isinstance(data, list)
data2 = self.cshare2.get_peers()
assert isinstance(data2, list)
def test_get_previous_format(self):
data = self.cshare.get_previous()
assert isinstance(data, dict)
data2 = self.cshare2.get_previous()
assert isinstance(data2, pd.DataFrame)
def test_get_price_format(self):
data = self.cshare.get_price()
assert isinstance(data, float)
data2 = self.cshare2.get_price()
assert isinstance(data2, pd.DataFrame)
data4 = self.cshare4.get_price()
assert isinstance(data4, Decimal)
def test_get_quote_format(self):
data = self.cshare.get_quote()
assert isinstance(data, dict)
data2 = self.cshare2.get_quote()
assert isinstance(data2, pd.DataFrame)
def test_get_quote_params(self):
data = self.cshare.get_quote()
data2 = self.cshare.get_quote(displayPercent=True)
assert (abs(data2["ytdChange"]) > abs(data["ytdChange"]))
def test_get_relevant_format(self):
data = self.cshare.get_relevant()
assert isinstance(data, dict)
data2 = self.cshare2.get_relevant()
assert isinstance(data2, pd.DataFrame)
def test_get_splits_format(self):
data = self.cshare3.get_splits()
assert isinstance(data, list)
data2 = self.cshare3.get_splits(range_="1y")
assert isinstance(data2, list)
def test_get_splits_params(self):
data = self.cshare3.get_splits(range_="2y")
data2 = self.cshare3.get_splits(range_="5y")
assert len(data2) > len(data)
def test_get_time_series(self):
data = self.cshare.get_time_series()
data2 = self.cshare.get_chart()
assert data == data2
def test_get_volume_by_venue_format(self):
data = self.cshare.get_volume_by_venue()
assert isinstance(data, list)
data2 = self.cshare2.get_volume_by_venue()
assert isinstance(data2, pd.DataFrame)
def test_filter(self):
data = self.cshare.get_quote(filter_='ytdChange')
assert isinstance(data, dict)
assert isinstance(data["ytdChange"], float)
data4 = self.cshare4.get_quote(filter_='ytdChange')
assert isinstance(data4, dict)
assert isinstance(data4["ytdChange"], Decimal)
def test_invalid_symbol(self):
data = Stock("BAD SYMBOL")
with pytest.raises(IEXSymbolError):
data.get_price()
def test_invalid_symbol_or_symbols(self):
with pytest.raises(IEXSymbolError):
a = Stock(["TSLA", "BAD SYMBOL", "BAD SYMBOL"])
a.get_price()
class TestBatchDefault(object):
def setup_class(self):
self.cbatch = Stock(["aapl", "tsla"])
self.cbatch2 = Stock(["aapl", "tsla"], output_format='pandas')
self.cbatch3 = Stock(["uvxy", "svxy"])
def test_invalid_symbol_or_symbols(self):
with pytest.raises(IEXSymbolError):
a = Stock(["TSLA", "BAD SYMBOL", "BAD SYMBOL"])
a.get_price()
def test_get_endpoints(self):
data = self.cbatch.get_endpoints(["price"])["AAPL"]
assert list(data) == ["price"]
def test_get_endpoints_bad_endpoint(self):
with pytest.raises(IEXEndpointError):
self.cbatch.get_endpoints(["BAD ENDPOINT", "quote"])
with pytest.raises(IEXEndpointError):
self.cbatch.get_endpoints("BAD ENDPOINT")
def test_get_all(self):
data = self.cbatch.get_all()
assert len(data) == 2
assert len(data["AAPL"]) == 20
def test_get_all_format(self):
data = self.cbatch.get_all()
assert isinstance(data, dict)
data2 = self.cbatch2.get_all()
assert isinstance(data2["AAPL"], dict)
def test_get_book_format(self):
data = self.cbatch.get_book()
assert isinstance(data, dict)
data2 = self.cbatch2.get_book()
assert isinstance(data2, pd.DataFrame)
def test_get_chart_format(self):
data = self.cbatch.get_chart()
assert isinstance(data, dict)
data2 = self.cbatch2.get_chart()
assert isinstance(data2["AAPL"], list)
def test_get_chart_params(self):
data = self.cbatch.get_chart()["AAPL"]
# Test chart range_s
data2 = self.cbatch.get_chart(range_='1y')["AAPL"]
assert 15 < len(data) < 35
assert 240 < len(data2) < 260
# Test chartSimplify
data4 = self.cbatch.get_chart(chartSimplify=True)["AAPL"][0]
assert "simplifyFactor" in list(data4)
data5 = self.cbatch.get_chart(range_='1y', chartInterval=5)["AAPL"]
assert 45 < len(data5) < 55
@pytest.mark.xfail(reason="This test only works overnight")
def test_get_chart_reset(self):
# Test chartReset
data = self.cbatch.get_chart(range_='1d', chartReset=True)
assert data == []
def test_get_company_format(self):
data = self.cbatch.get_company()
assert isinstance(data, dict)
data2 = self.cbatch2.get_company()
assert isinstance(data2, pd.DataFrame)
def test_get_delayed_quote_format(self):
data = self.cbatch.get_delayed_quote()
assert isinstance(data, dict)
data2 = self.cbatch2.get_delayed_quote()
assert isinstance(data2, pd.DataFrame)
def test_get_dividends_format(self):
data = self.cbatch.get_dividends()
assert isinstance(data, dict)
data2 = self.cbatch2.get_dividends()
assert isinstance(data2, dict)
def test_get_dividends_params(self):
data = self.cbatch.get_dividends()["AAPL"]
data2 = self.cbatch.get_dividends(range_='2y')["AAPL"]
data3 = self.cbatch.get_dividends(range_='5y')["AAPL"]
assert len(data) < len(data2) < len(data3)
def test_get_earnings_format(self):
data = self.cbatch.get_earnings()
assert isinstance(data, dict)
data2 = self.cbatch2.get_earnings()
assert isinstance(data2, pd.DataFrame)
def test_get_effective_spread_format(self):
data = self.cbatch.get_effective_spread()
assert isinstance(data, dict)
data2 = self.cbatch2.get_effective_spread()
assert isinstance(data2, pd.DataFrame)
def test_get_financials_format(self):
data = self.cbatch.get_financials()
assert isinstance(data, dict)
data2 = self.cbatch2.get_financials()
assert isinstance(data2, pd.DataFrame)
def test_get_key_stats_format(self):
data = self.cbatch.get_key_stats()
assert isinstance(data, dict)
data2 = self.cbatch2.get_key_stats()
assert isinstance(data2, pd.DataFrame)
def test_get_logo_format(self):
data = self.cbatch.get_logo()
assert isinstance(data, dict)
data2 = self.cbatch2.get_logo()
assert isinstance(data2, pd.DataFrame)
def test_get_news_format(self):
data = self.cbatch.get_news()
assert isinstance(data, dict)
def test_ohlc(self):
data = self.cbatch.get_ohlc()
assert isinstance(data, dict)
def test_get_open_close_format(self):
data = self.cbatch.get_open_close()
assert isinstance(data, dict)
data2 = self.cbatch2.get_open_close()
assert isinstance(data2, pd.DataFrame)
def test_get_peers_format(self):
data = self.cbatch.get_peers()
assert isinstance(data, dict)
data2 = self.cbatch2.get_peers()
assert isinstance(data2, dict)
def test_get_previous_format(self):
data = self.cbatch.get_previous()
assert isinstance(data, dict)
data2 = self.cbatch2.get_previous()
assert isinstance(data2, pd.DataFrame)
def test_get_price_format(self):
data = self.cbatch.get_price()
assert isinstance(data, dict)
data2 = self.cbatch2.get_price()
assert isinstance(data2, pd.DataFrame)
def test_get_quote_format(self):
data = self.cbatch.get_quote()
assert isinstance(data, dict)
data2 = self.cbatch2.get_quote()
assert isinstance(data2, pd.DataFrame)
data3 = self.cbatch.get_quote(displayPercent=True)
assert (abs(data3["AAPL"]["ytdChange"]) > abs(
data["AAPL"]["ytdChange"]))
def test_get_relevant_format(self):
data = self.cbatch.get_relevant()
assert isinstance(data, dict)
data2 = self.cbatch2.get_relevant()
assert isinstance(data2, pd.DataFrame)
def test_get_splits(self):
data = self.cbatch.get_splits()
assert isinstance(data, dict)
data2 = self.cbatch2.get_splits()
assert isinstance(data2, pd.DataFrame)
def test_get_splits_params(self):
data = self.cbatch3.get_splits(range_="2y")["SVXY"]
data2 = self.cbatch3.get_splits(range_="5y")["SVXY"]
assert len(data2) > len(data)
def test_time_series(self):
data = self.cbatch.get_time_series()
data2 = self.cbatch.get_chart()
assert data == data2
def test_get_volume_by_venue_format(self):
data = self.cbatch.get_volume_by_venue()
assert isinstance(data, dict)
data2 = self.cbatch2.get_volume_by_venue()
assert isinstance(data2, pd.DataFrame)
def test_get_select_ep_bad_params(self):
with pytest.raises(ValueError):
self.cbatch.get_endpoints()
with pytest.raises(IEXEndpointError):
self.cbatch.get_endpoints("BADENDPOINT")
def run():
tsla = Stock('VOO')
price_open = tsla.get_open()
price_now = tsla.get_price()
print(price_open)
print(price_now)
def scrape_xml(link,company_name):
TotalValue = 0
transactionCodeList = []
DorIList = []
TitleList = []
today = datetime.datetime.today()
today = today.strftime('%m/%d/%Y %I:%M %p')
headers = {
"user-agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/48.0.2564.103 Safari/537.36",
"accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8",
"accept-charset": "ISO-8859-1,utf-8;q=0.7,*;q=0.3",
"accept-encoding": "gzip, deflate, sdch",
"accept-language": "en-US,en;q=0.8",
}
explain = {'P' : 'Open market or private purchase of non-derivative or derivative security',
'S' : 'Open market or private sale of non-derivative or derivative security',
'V' : 'Transaction voluntarily reported earlier than required',
'A' : 'Grant, award or other acquisition',
'D' : 'Disposition to the issuer of issuer equity securities',
'F' : 'Payment of exercise price or tax liability by delivering or withholding securities incident to the receipt of a security issued',
'I' : 'Discretionary transaction resulting in acquisition or disposition of issuer securities',
'M' : 'Exercise or conversion of derivative security exempted Derivative Securities Codes',
'C' : 'Conversion of derivative security',
'E' : 'Expiration of short derivative position',
'H' : 'Expiration of long derivative position with value received',
'O' : 'Exercise of out-of-the-money derivative security',
'X' : 'Exercise of in-the-money or at-the-money derivative security',
'G' : 'Bona fide gift',
'L' : 'Small acquisition',
'W' : 'Acquisition or disposition by will or the laws of descent and distribution',
'Z' : 'Deposit into or withdrawal from voting trust',
'J' : 'Other',
'K' : 'Transaction in equity swap or instrument with similar characteristics',
'U' : 'Disposition pursuant to a tender of shares in a change of control transaction',
}
res = requests.get(link, headers=headers)
soup = bs4.BeautifulSoup(res.text, 'html.parser')
for a in soup.find_all('a'):
if a.getText()[-4:] == '.xml':
address = 'http://www.sec.gov' + a['href']
res = requests.get(address, headers=headers, timeout=None)
tree = ET.fromstring(res.content)
try:
isOfficer = tree.find('reportingOwner/reportingOwnerRelationship/isOfficer').text
if not isOfficer:
isOfficer = 'I shot the Deputy'
except:
isOfficer = "0"
pass
transactionCode = tree.findall('nonDerivativeTable/nonDerivativeTransaction/transactionCoding/transactionCode')
if not transactionCode:
try:
transactionCode = tree.findall('derivativeTable/derivativeTransaction/transactionCoding/transactionCode')
except:
transactionCode = "0"
pass
tradingSymbol = tree.find('issuer/issuerTradingSymbol')
ticker = tradingSymbol.text.lower()
symbol = str(ticker.upper())
print(company_name.title() + ' (' + symbol + ') at ' + str(today))
transactionShares = tree.findall('nonDerivativeTable/nonDerivativeTransaction/transactionAmounts/transactionShares/value')
if transactionShares == None:
try:
transactionShares = tree.findall('derivativeTable/derivativeTransaction/transactionAmounts/transactionShares/value')
except:
transactionShares = []
pass
transactionPricePerShare = tree.findall('nonDerivativeTable/nonDerivativeTransaction/transactionAmounts/transactionPricePerShare/value')
if transactionShares == None:
try:
transactionShares = tree.findall('derivativeTable/derivativeTransaction/transactionAmounts/transactionPricePerShare/value')
except:
transactionShares = []
pass
DorI = tree.findall('nonDerivativeTable/nonDerivativeTransaction/ownershipNature/directOrIndirectOwnership/value')
if not DorI:
try:
DorI = tree.findall('derivativeTable/derivativeTransaction/ownershipNature/directOrIndirectOwnership/value')
except:
DorI = []
pass
for price, shares, direct, code in zip(transactionPricePerShare, transactionShares, DorI, transactionCode):
if explain[code.text]:
#direct.text == 'D' and
print('Shares: ',shares.text)
TotalValue = TotalValue + float(shares.text)*float(price.text)
print('Total value: ',TotalValue)
shares = shares.text
else:
pass
for code in transactionCode:
transactionCodeList.append(code.text)
for item in DorI:
DorIList.append(item.text)
if '2' in isOfficer:
print ('Director purchase')
elif '1' in isOfficer:
print ('Officer purchase')
elif '0' in isOfficer:
print ('Neither Officer or Director')
elif isOfficer != '1' or '2' or '0':
print('Officer overboard --- or maybe more!', isOfficer)
if 'D' in DorIList:
print('Direct Purchase')
elif 'I' in DorIList:
print('Indirect Purchase')
else:
print('D or I value fubar')
print('Transaction codes: ' + str(transactionCodeList))
for key in explain:
if key in transactionCodeList:
print(explain.get(key))
print ('~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~')
if 'P' in transactionCodeList:
#and ticker not in portfolio:
#isOfficer == str(1) and and TotalValue > 10000 and 'D' in DorIList
with open('portfolio.txt', 'a') as f:
f.write(ticker + '\n')
ticker = Stock(ticker)
current_price = str(ticker.get_price())
with open('bought_price.txt', 'a') as f:
f.write(current_price + '\n')
message = 'Buy Opportunity\n' + company_name.capitalize() + '\nTicker symbol: ' + symbol + '\n\nCurrent price: $'+ current_price + '\n\nOfficer: ' + isOfficer + '\n Total Value: '+str(TotalValue)
print(address)
print(message)
if confirm(text='Want to email with your friends?', title='Insider Buy!', buttons=['YES', 'NO']) == 'YES':
email (symbol, address, current_price, company_name, message)
print('~~~~~~~~~~~~~~~~\nemail!!!!\n~~~~~~~~~~~~~~~~~~~~~~~')
class TestShare(object):
def setup_class(self):
self.cshare = Stock("aapl")
def test_get_all_format(self):
data = self.cshare.get_all()
assert isinstance(data, dict,)
def test_get_chart_format(self):
data = self.cshare.get_chart()
assert isinstance(data, list)
def test_get_book_format(self):
data = self.cshare.get_book()
assert isinstance(data, dict)
def test_get_open_close_format(self):
data = self.cshare.get_open_close()
assert isinstance(data, dict)
def test_get_previous_format(self):
data = self.cshare.get_previous()
assert isinstance(data, dict)
def test_get_company_format(self):
data = self.cshare.get_company()
assert isinstance(data, dict)
def test_get_key_stats_format(self):
data = self.cshare.get_key_stats()
assert isinstance(data, dict)
def test_get_relevant_format(self):
data = self.cshare.get_relevant()
assert isinstance(data, dict)
def test_get_news_format(self):
data = self.cshare.get_news()
assert isinstance(data, list)
def test_get_financials_format(self):
data = self.cshare.get_financials()
assert isinstance(data, dict)
def test_get_earnings_format(self):
data = self.cshare.get_earnings()
assert isinstance(data, dict)
def test_get_logo_format(self):
data = self.cshare.get_logo()
assert isinstance(data, dict)
def test_get_price_format(self):
data = self.cshare.get_price()
assert isinstance(data, float)
def test_get_delayed_quote_format(self):
data = self.cshare.get_delayed_quote()
assert isinstance(data, dict)
def test_get_effective_spread_format(self):
data = self.cshare.get_effective_spread()
assert isinstance(data, list)
def test_get_volume_by_venue_format(self):
data = self.cshare.get_volume_by_venue()
assert isinstance(data, list)
def test_ohlc(self):
data = self.cshare.get_ohlc()
assert isinstance(data, dict)
def test_time_series(self):
data = self.cshare.get_time_series()
data2 = self.cshare.get_chart()
assert data == data2
def test_nondefault_params_1(self):
aapl = Stock("AAPL", _range='5y')
aapl2 = Stock("AAPL")
assert len(aapl.get_chart()) > len(aapl2.get_chart())
def test_nondefault_params_2(self):
aapl = Stock("AAPL", last=37)
assert len(aapl.get_news()) == 37
