def get_watchlist_symbols():
"""
Returns: the symbol for each stock in your watchlist as a list of strings
"""
my_list_names = []
symbols = []
for name in r.get_all_watchlists(info='name'):
my_list_names.append(name)
for name in my_list_names:
list = r.get_watchlist_by_name(name)
for item in list:
instrument_data = r.get_instrument_by_url(item.get('instrument'))
symbol = instrument_data['symbol']
symbols.append(symbol)
return symbols
def rh_pull_symbol_from_instrument_url(url):
obj = robinhood_traded_stocks.objects.filter(instrument_url=url)
if not obj:
obj = robinhood_traded_stocks()
symbol = r.get_instrument_by_url(url)['symbol']
name = r.get_name_by_symbol(symbol)
obj.symbol = symbol
obj.name = name
obj.instrument_url = url
obj.save()
else:
obj = obj[0]
symbol = obj.symbol
name = obj.name
return symbol, name
def import_portfolio_robinhood(access_token,
username=None,
password=None,
name="Robinhood",
free_stock=False):
"""
Accesses Robinhood account and downloads transactions
Parameters
==========
username : Robinhood username
password : Robinhood account password
name : desired portfolio name
free_stock : include a free stock not captured by transaction history (see below)
Returns
=======
df : dataframe with transactions
p : portfolio (Portfolio class object)
"""
if not access_token:
if username is None:
username = getpass("Username: "******"Password: "******"Parsing orders ...")
# pre-pull all tickers before creating order history df
Tickerset = []
for order in orders:
if len(order["executions"]):
Tickerset.append(order["instrument"])
Tickerset = list(set(Tickerset))
# make a lookup dict for ticker symbols
Tickersymbols = {}
for element in Tickerset:
Tickersymbols[element] = r.get_instrument_by_url(element)["symbol"]
for order in orders:
if len(order["executions"]):
Date.append(pd.to_datetime(order["last_transaction_at"]))
Transaction.append(order["side"])
Ticker.append(Tickersymbols[order["instrument"]])
Currency.append("USD")
Price.append(order["average_price"])
Quantity.append(order["quantity"])
# add deposits
transfers = r.get_bank_transfers()
print("Parsing bank transfers ...")
for transfer in transfers:
if transfer["cancel"] is None:
Date.append(pd.to_datetime(transfer["created_at"]))
Transaction.append(transfer["direction"])
Ticker.append(None)
Currency.append("USD")
Price.append(1.0)
Quantity.append(transfer["amount"])
# add dividends
dividends = r.get_dividends()
print("Parsing dividends ...")
for dividend in dividends:
if dividend["state"] == "paid":
Date.append(pd.to_datetime(dividend["paid_at"]))
Transaction.append("dividend")
Ticker.append(Tickersymbols[dividend["instrument"]])
Currency.append("USD")
Price.append(1.0)
Quantity.append(dividend["amount"])
if free_stock == True:
# include free stock (Robinhood promotion, not included in transaction history)
print("Adding promotional stock ...")
Date.append(pd.to_datetime("2/1/18"))
Transaction.append("buy")
Ticker.append("CHK")
Currency.append("USD")
Price.append(0.0)
Quantity.append(1.0)
# build dataframe
d = {
"Date": Date,
"Transaction": Transaction,
"Ticker": Ticker,
"Currency": Currency,
"Price": pd.to_numeric(Price),
"Quantity": pd.to_numeric(Quantity),
}
df = pd.DataFrame(data=d)
# strip time of day information
df.Date = df.Date.map(lambda x: x.strftime("%m-%d-%Y"))
df.Date = pd.to_datetime(df.Date)
# create a new portfolio object
p = Portfolio(name=name)
# parse
p = parse_portfolio(df, p)
return p
input(
"\nYour stocks and the last trade prices of each on your account?\n\n<enter> if everything looks correct.\n"
)
numSymbols = len(d)
# print(numSymbols)
positions = r.get_open_stock_positions()
numPositions = len(positions)
quantities = {}
for i in range(0, numPositions):
# print(positions[i])
# print(json.dumps(positions[i],indent=1))
quantities[r.get_instrument_by_url(
positions[i]["instrument"])["symbol"]] = float(
positions[i]["quantity"])
index = 0
check = {}
#s is symbol, d is the whole rh_stock_data json dictionary
for s in d:
try:
if s in quantities:
print("\n" + s + " stock sellable: " + str(quantities[s]))
# print("\n"+s+" last trade price: "+str(d[s]))
Ltp = d[s]
# print(s+" Ask: "+str(ask(s)))
Ask = ask(s)
# print(s+" Bid: "+str(bid(s)))
Bid = bid(s)
def import_portfolio_robinhood(username=None,
password=None,
name="Robinhood",
free_stock=False):
"""
Accesses Robinhood account and downloads transactions
Parameters
==========
username : Robinhood username
password : Robinhood account password
name : desired portfolio name
free_stock : include a free stock not captured by transaction history (see below)
Returns
=======
df : dataframe with transactions
p : portfolio (Portfolio class object)
"""
import robin_stocks as r
from getpass import getpass
if username is None: username = getpass("Username: "******"Password: "******"Parsing orders ...")
for order in orders:
if len(order['executions']):
Date.append(pd.to_datetime(order['last_transaction_at']))
Transaction.append(order['side'])
Ticker.append(
r.get_instrument_by_url(order['instrument'])['symbol'])
Currency.append('USD')
Price.append(order['average_price'])
Quantity.append(order['quantity'])
# add deposits
transfers = r.get_bank_transfers()
print("Parsing bank transfers ...")
for transfer in transfers:
if transfer['cancel'] is None:
Date.append(pd.to_datetime(transfer['created_at']))
Transaction.append('deposit')
Ticker.append(None)
Currency.append('USD')
Price.append(1.0)
Quantity.append(transfer['amount'])
# add dividends
dividends = r.get_dividends()
print("Parsing dividends ...")
for dividend in dividends:
if dividend['state'] == 'paid':
Date.append(pd.to_datetime(dividend['paid_at']))
Transaction.append('dividend')
Ticker.append(
r.get_instrument_by_url(dividend['instrument'])['symbol'])
Currency.append('USD')
Price.append(
float(dividend['amount']) / float(dividend['position']))
Quantity.append(dividend['position'])
if free_stock == True:
# include free stock (Robinhood promotion, not included in transaction history)
print("Adding promotional stock ...")
Date.append(pd.to_datetime('2/1/18'))
Transaction.append('buy')
Ticker.append('CHK')
Currency.append('USD')
Price.append(0.0)
Quantity.append(1.0)
# build dataframe
d = {
'Date': Date,
'Transaction': Transaction,
'Ticker': Ticker,
'Currency': Currency,
'Price': pd.to_numeric(Price),
'Quantity': pd.to_numeric(Quantity)
}
df = pd.DataFrame(data=d)
# strip time of day information
df.Date = df.Date.map(lambda x: x.strftime('%m-%d-%Y'))
df.Date = pd.to_datetime(df.Date)
# create a new portfolio object
p = Portfolio(name=name)
# parse
p = parse_portfolio(df, p)
return p
def load_securities(
security_ids: List[str], t: datetime, online: bool, log: bool
) -> Dict[str, SecurityInfo]:
"""
Hits the Robinhood API to pull down security information like the latest
price and the full security name.
"""
security_info_base_dir: str = os.path.join("data", "securities")
security_info_output_dir: str = os.path.join(
security_info_base_dir,
t.strftime("%Y"),
t.strftime("%m"),
t.strftime("%d"),
t.strftime("%H"),
t.strftime("%M"),
t.strftime("%S"),
)
resp: Dict[str, Any] = {}
if online:
for sec_id in security_ids:
sec_url = os.path.join(
"https://api.robinhood.com", "instruments", sec_id
)
sec_meta = r.get_instrument_by_url(sec_url)
sec_name = sec_meta["name"]
sec_sym = sec_meta["symbol"]
sec_price = r.get_latest_price(sec_sym)
resp[sec_id] = {
"name": sec_name,
"symbol": sec_sym,
"price": sec_price,
}
if log:
if not os.path.exists(security_info_output_dir):
os.makedirs(security_info_output_dir)
security_info_output_file = os.path.join(
security_info_output_dir,
"{}.json".format(t.strftime("%Y_%m_%d_%H_%M_%S")),
)
with open(security_info_output_file, "w") as f:
f.write(json.dumps(resp, indent=4))
else:
latest = datetime.strptime(
latest_ds(security_info_base_dir), "%Y/%m/%d/%H/%M/%S"
)
security_info_latest_file: str = os.path.join(
security_info_base_dir,
latest.strftime("%Y"),
latest.strftime("%m"),
latest.strftime("%d"),
latest.strftime("%H"),
latest.strftime("%M"),
latest.strftime("%S"),
"{}.json".format(latest.strftime("%Y_%m_%d_%H_%M_%S")),
)
resp = json.load(open(security_info_latest_file, "r"))
security_info: Dict[str, SecurityInfo] = {}
for (sec_id, info) in resp.items():
security_info[sec_id] = SecurityInfo(
info["name"], info["symbol"], float(info["price"][0])
)
return security_info