def get_holdings():
my_stocks = r.build_holdings()
my_options = r.options.get_open_option_positions()
dicts = []
for option in my_options:
link = option['option']
value = requests.get(link).json()
option.update(value)
dicts.append(option)
for option_position in dicts:
underlying = option_position['chain_symbol']
strike = option_position['strike_price']
expiration = option_position['expiration_date']
contract_type = option_position['type']
quantity = option_position['quantity']
average_price = option_position['average_price']
mark = ((float(option_position['min_ticks']['above_tick']) +
float(option_position['min_ticks']['above_tick'])) / 2) * 100
month = expiration.split("-")[1]
day = expiration.split("-")[2]
year = expiration.split("-")[0]
symbol = underlying + "_" + month + day + year[2:] + contract_type[
0].upper() + format_number(strike)
name = look_up[month] + " " + day + " " + year + " " + format_number(
strike) + " " + contract_type
my_stocks[symbol] = {
"type": "option",
"quantity": quantity,
"average_buy_price": average_price,
"name": name,
"equity": mark
}
return my_stocks
def rs_current_price(tick):
my_stocks = rs.build_holdings()
value = my_stocks[tick]
rs_price_dict.update({tick: float(value["price"])})
print(value["price"], "\n")
return
def tickers():
my_tickers_list = []
my_stocks = rs.build_holdings()
for key, value in my_stocks.items():
my_tickers_list.append(key)
print(my_tickers_list, "\n")
return my_tickers_list
def get_equity_data():
"""Displays a pie chart of your portfolio holdings
"""
holdings_data = r.build_holdings()
equity_data = {}
for key, value in holdings_data.items():
equity_data[key] = {}
equity_data[key][name] = value.get('name')
equity_data[key][percentage] = value.get("percentage")
equity_data[key][type]
fig1, ax1 = plt.subplots()
ax1.pie(equities, labels=labels, autopct='%1.1f%%',
shadow=True, startangle=90)
ax1.axis('equal')
plt.show()
def modified_holdings():
""" Retrieves the same dictionary as robinhood.build_holdings, but includes data about
when the stock was purchased, which is useful for the read_trade_history() method
in tradingstats.py
Returns:
the same dict from robinhood.build_holdings, but with an extra key-value pair for each
position you have, which is 'bought_at': (the time the stock was purchased)
"""
holdings = robinhood.build_holdings()
holdings_data = robinhood.open_stock_positions()
for symbol, _ in holdings.items():
bought_at = position_creation_date(symbol, holdings_data)
bought_at = str(pandas.to_datetime(bought_at))
holdings[symbol].update({'bought_at': bought_at})
return holdings
def create_holdings_table():
print("Getting holdings data...")
holdings = r.build_holdings() # get the holdings
data = [] # list to hold stock data
print("Transforming data...")
# Loop through stocks
for name, stats in holdings.items():
stock = {"name": name} # initialize name/value
stock = {**stock, **stats} # merge stats dict with stocks
data.append(stock) # append to data list
# Write to Excel
helper.create_excel(data, 'holdings')
def build_portfolio():
# Get my portfolio info
my_stocks = rb.build_holdings()
myStocks = my_stocks.items()
return myStocks
def get_holdings():
my_stocks = r.build_holdings()
for key, value in my_stocks.items():
print(key, value)
def get_profile_data(username):
holdings = rh.build_holdings()
return get_stocks_as_percent(holdings)
def returnHoldings(self):
return rs.build_holdings()
