def call_ta(self, _):
"""Process ta command"""
if not self.current_coin:
print("Please load a coin through either load or select", "\n")
elif self.current_df.empty:
print("Price dataframe is empty")
else:
# Coingecko does not provide candles so we can only provide close data.
if self.source == "CG":
self.current_df = self.current_df[["Price"]].rename(
columns={"Price": "Close"}
)
self.current_df.index.name = "date"
ta_controller.menu(
self.current_coin,
self.current_df.index[0],
"",
self.current_df,
"crypto",
)
print("")
def call_ta(self, other_args):
"""Process ta command"""
if self.current_coin:
self.current_df, self.current_currency = pycoingecko_view.ta(
self.current_coin, other_args)
if self.current_df is not None:
try:
self.current_df = self.current_df[[
"price"
]].rename(columns={"price": "Close"})
self.current_df.index.name = "date"
quit = ta_controller.menu(
stock=self.current_df,
ticker=self.current_coin.coin_symbol,
start=self.current_df.index[0],
interval="",
context="(crypto)>(cg)",
)
print("")
if quit is not None:
if quit is True:
return quit
except (ValueError, KeyError) as e:
print(e)
else:
return
else:
print("Please load a coin through either load - coin", "\n")
return
def call_ta(self, _):
"""Process ta command"""
if not self.current_coin:
print("Please load a coin through either load -c ", "\n")
elif self.current_df.empty:
print("Price dataframe is empty")
else:
try:
quit = ta_controller.menu(
stock=self.current_df,
ticker=self.current_coin,
start=self.current_df.index[0],
interval="",
context="(crypto)>(bin)",
)
print("")
if quit is not None:
if quit is True:
return quit
except (ValueError, KeyError) as e:
print(e)
def call_ta(self, _):
"""Process ta command"""
return ta_controller.menu(
self.ticker,
self.start,
self.interval,
self.stock,
)
def call_ta(self, _):
"""Process ta command"""
if not self.current_coin:
print("Please load a coin through either load or select", "\n")
if self.current_df.empty:
print("Price dataframe is empty")
else:
# Need to make the columns in df be compatible. Also since there are no splits or dividends, there is no
# adj close. To tell ta to use Close, we can just set the interval to anything but 1440.
# Binance provides candles so we just need to rename:
if self.source == "BIN":
self.current_df = self.current_df.rename(
columns={
"Open": "1. open",
"High": "2. high",
"Low": "3. low",
"Close": "4. close",
"Volume": "6. volume",
}
)
self.current_df.index.name = "date"
# Coingecko does not provide candles so we can only provide close data.
elif self.source == "CG":
self.current_df = self.current_df[["Price"]].rename(
columns={"Price": "4. close"}
)
self.current_df.index.name = "date"
return ta_controller.menu(
self.current_df,
self.current_coin,
self.current_df.index[0],
"",
)
def main():
"""
Gamestonk Terminal is an awesome stock market terminal that has been developed for fun,
while I saw my GME shares tanking. But hey, I like the stock.
"""
# Enable VT100 Escape Sequence for WINDOWS 10 Ver. 1607
if sys.platform == "win32":
os.system("")
s_ticker = ""
s_start = ""
df_stock = pd.DataFrame()
s_interval = "1440min"
# Set stock by default to speed up testing
# s_ticker = "BB"
# ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE, output_format='pandas')
# df_stock, d_stock_metadata = ts.get_daily_adjusted(symbol=s_ticker, outputsize='full')
# df_stock.sort_index(ascending=True, inplace=True)
# s_start = datetime.strptime("2020-06-04", "%Y-%m-%d")
# df_stock = df_stock[s_start:]
# Add list of arguments that the main parser accepts
menu_parser = argparse.ArgumentParser(add_help=False,
prog="gamestonk_terminal")
choices = [
"help",
"quit",
"q",
"clear",
"load",
"candle",
"view",
"export",
"disc",
"scr",
"mill",
"ba",
"res",
"fa",
"ta",
"dd",
"eda",
"pred",
"ca",
"op",
"fred",
"pa",
"crypto",
"ra",
"po",
]
menu_parser.add_argument("opt", choices=choices)
completer = NestedCompleter.from_nested_dict({c: None for c in choices})
# Print first welcome message and help
print("\nWelcome to Gamestonk Terminal 🚀\n")
should_print_help = True
parsed_stdin = False
if gtff.ENABLE_THOUGHTS_DAY:
print("-------------------")
try:
thought.get_thought_of_the_day()
except Exception as e:
print(e)
print("")
# Loop forever and ever
while True:
main_cmd = False
if should_print_help:
print_help(s_ticker, s_start, s_interval, b_is_stock_market_open())
should_print_help = False
# Get input command from stdin or user
if not parsed_stdin and len(sys.argv) > 1:
as_input = " ".join(sys.argv[1:])
parsed_stdin = True
print(f"{get_flair()}> {as_input}")
elif session and gtff.USE_PROMPT_TOOLKIT:
as_input = session.prompt(f"{get_flair()}> ", completer=completer)
else:
as_input = input(f"{get_flair()}> ")
# Is command empty
if not as_input:
print("")
continue
# Parse main command of the list of possible commands
try:
(ns_known_args,
l_args) = menu_parser.parse_known_args(as_input.split())
except SystemExit:
print("The command selected doesn't exist\n")
continue
b_quit = False
if ns_known_args.opt == "help":
should_print_help = True
elif (ns_known_args.opt == "quit") or (ns_known_args.opt == "q"):
break
elif ns_known_args.opt == "clear":
s_ticker, s_start, s_interval, df_stock = clear(
l_args, s_ticker, s_start, s_interval, df_stock)
main_cmd = True
elif ns_known_args.opt == "load":
s_ticker, s_start, s_interval, df_stock = load(
l_args, s_ticker, s_start, s_interval, df_stock)
main_cmd = True
elif ns_known_args.opt == "candle":
if s_ticker:
candle(
s_ticker,
(datetime.now() -
timedelta(days=180)).strftime("%Y-%m-%d"),
)
else:
print(
"No ticker selected. Use 'load ticker' to load the ticker you want to look at.",
"\n",
)
main_cmd = True
elif ns_known_args.opt == "view":
if s_ticker:
view(l_args, s_ticker, s_start, s_interval, df_stock)
else:
print(
"No ticker selected. Use 'load ticker' to load the ticker you want to look at.",
"\n",
)
main_cmd = True
elif ns_known_args.opt == "export":
export(l_args, df_stock)
main_cmd = True
elif ns_known_args.opt == "disc":
b_quit = disc_controller.menu()
elif ns_known_args.opt == "mill":
b_quit = mill.papermill_menu()
elif ns_known_args.opt == "ba":
b_quit = ba_controller.menu(s_ticker, s_start)
elif ns_known_args.opt == "res":
b_quit = rm.res_menu(s_ticker, s_start, s_interval)
elif ns_known_args.opt == "ca":
b_quit = ca_controller.menu(df_stock, s_ticker, s_start,
s_interval)
elif ns_known_args.opt == "fa":
b_quit = fam.fa_menu(s_ticker, s_start, s_interval)
elif ns_known_args.opt == "ta":
b_quit = ta_controller.menu(df_stock, s_ticker, s_start,
s_interval)
elif ns_known_args.opt == "dd":
b_quit = dd_controller.menu(df_stock, s_ticker, s_start,
s_interval)
elif ns_known_args.opt == "eda":
if s_interval == "1440min":
b_quit = eda_controller.menu(df_stock, s_ticker, s_start,
s_interval)
else:
df_stock = yf.download(s_ticker, start=s_start, progress=False)
df_stock = df_stock.rename(
columns={
"Open": "1. open",
"High": "2. high",
"Low": "3. low",
"Close": "4. close",
"Adj Close": "5. adjusted close",
"Volume": "6. volume",
})
df_stock.index.name = "date"
s_interval = "1440min"
b_quit = eda_controller.menu(df_stock, s_ticker, s_start,
s_interval)
elif ns_known_args.opt == "op":
b_quit = op_controller.menu(s_ticker)
elif ns_known_args.opt == "fred":
b_quit = fred_controller.menu()
elif ns_known_args.opt == "pa":
b_quit = port_controller.menu()
elif ns_known_args.opt == "crypto":
b_quit = crypto_controller.menu()
elif ns_known_args.opt == "po":
b_quit = po_controller.menu([s_ticker])
elif ns_known_args.opt == "pred":
if not gtff.ENABLE_PREDICT:
print("Predict is not enabled in feature_flags.py")
print("Prediction menu is disabled")
print("")
continue
try:
# pylint: disable=import-outside-toplevel
from gamestonk_terminal.prediction_techniques import pred_controller
except ModuleNotFoundError as e:
print("One of the optional packages seems to be missing")
print("Optional packages need to be installed")
print(e)
print("")
continue
except Exception as e:
print(e)
print("")
continue
if s_interval == "1440min":
b_quit = pred_controller.menu(df_stock, s_ticker, s_start,
s_interval)
# If stock data is intradaily, we need to get data again as prediction
# techniques work on daily adjusted data. By default we load data from
# Alpha Vantage because the historical data loaded gives a larger
# dataset than the one provided by quandl
else:
try:
ts = TimeSeries(key=cfg.API_KEY_ALPHAVANTAGE,
output_format="pandas")
# pylint: disable=unbalanced-tuple-unpacking
df_stock_pred, _ = ts.get_daily_adjusted(symbol=s_ticker,
outputsize="full")
# pylint: disable=no-member
df_stock_pred = df_stock_pred.sort_index(ascending=True)
df_stock_pred = df_stock_pred[s_start:]
b_quit = pred_controller.menu(df_stock_pred,
s_ticker,
s_start,
s_interval="1440min")
except Exception as e:
print(e)
print(
"Either the ticker or the API_KEY are invalids. Try again!"
)
return
elif ns_known_args.opt == "ra":
b_quit = ra_controller.menu(df_stock, s_ticker, s_start,
s_interval)
elif ns_known_args.opt == "scr":
b_quit = screener_controller.menu()
else:
print("Shouldn't see this command!")
continue
if b_quit:
break
else:
if not main_cmd:
should_print_help = True
print(
"Hope you enjoyed the terminal. Remember that stonks only go up. Diamond hands.\n"
)
