diff --git a/gamestonk_terminal/due_diligence/reddit_view.py b/gamestonk_terminal/due_diligence/reddit_view.py
index 5c536add200..3348e8638eb 100644
--- a/gamestonk_terminal/due_diligence/reddit_view.py
+++ b/gamestonk_terminal/due_diligence/reddit_view.py
@@ -85,6 +85,10 @@ def due_diligence(other_args: List[str], ticker: str):
"News",
"Advice",
"Chart",
+ "Charts and Setups",
+ "Fundamental Analysis",
+ "forex",
+ "Trade Idea",
]
l_sub_reddits = [
"pennystocks",
@@ -94,6 +98,8 @@ def due_diligence(other_args: List[str], ticker: str):
"stocks",
"investing",
"wallstreetbets",
+ "forex",
+ "Forexstrategy",
]
submissions = psaw_api.search_submissions(
diff --git a/gamestonk_terminal/forex/README.md b/gamestonk_terminal/forex/README.md
index 5c27d28a4fd..5e127cee0a3 100644
--- a/gamestonk_terminal/forex/README.md
+++ b/gamestonk_terminal/forex/README.md
@@ -30,6 +30,14 @@ This menu utilizes oanda to enable support for trading forex.
* Display the orderbook if Oanda provides one for the forex instrument
* [positionbook](#positionbook)
* Display the positionbook if Oanda provides one for the forex instrument
+* [news](#news)
+ * Latest news of the currency provided by [News API]
+* [reddit](#reddit)
+ * Gets due diligence from another user's post [Reddit]
+* [eda](#eda)
+ * This menu aims to perform exploratory data analysis on a pre-loaded forex instrument.
+* [ba](#ba)
+ * This menu aims to extrapolate behavioural analysis regarding a pre-loaded forex instrument.
## summary
```text
@@ -108,13 +116,21 @@ Specify the instrument to use in the format EUR_USD
## candles
```text
-usage: candles [-g GRANULARITY] [-c CANDLECOUNT]
+usage: candles [-g GRANULARITY] [-c CANDLECOUNT] [-abcCeorsv]
```
Retrieve a candlestick chart for the currently loaded instrument. Not a live chart.
* -g : Specify the granularity, which is the timeframe each candle represents. The available granularities are Seconds: S5, S10, S15, S30 Minutes: M1, M2, M4, M5, M10, M15, M30 Hours: H1, H2, H3, H4, H6, H8, H12 Day: D, Week: W Month: M. (default=D)
* -c : Specify the number of candles to retrieve. (default=180)
+* -a : Adds AD (Accumulation/Distribution Index) to the chart. AD is a cumulative indicator that uses volume and price to assess whether a stock is being accumulated or distributed. This provides insight into how strong a trend is. [Investopedia](#https://www.investopedia.com/terms/a/accumulationdistribution.asp)
+* -b : Adds Bollinger Bands to the chart. Bollinger bands are a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average of a security's price. [Investopedia](#https://www.investopedia.com/terms/b/bollingerbands.asp)
+* -C : Adds CCI (Commodity Channel Index) to the chart. CCI is a momentum-based oscillator used to help determine when an investment vehicle is reaching a condition of being overbought or oversold. (default=14) [Investopedia](#https://www.investopedia.com/terms/c/commoditychannelindex.asp)
+* -e : Adds EMA (Exponential Moving Average) to the chart. EMA is a moving average that places a greater weight and significance on the most recent data points. (default=10) [Investopedia](#https://www.investopedia.com/terms/e/ema.asp)
+* -o : Adds OBV (On Balance Volume) to the chart. OBV is a momentum indicator that uses volume flow to predict changes in price. [Investopedia](#https://www.investopedia.com/terms/o/onbalancevolume.asp)
+* -r : Adds RSI (Relative Strength Index) to the chart. RSI is a momentum indicator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. (default=14) [Investopedia](#https://www.investopedia.com/terms/r/rsi.asp)
+* -s : Adds SMA (Simple Moving Average) to the chart. SMA calculates the average of a selected range of prices, usually closing prices, by the number of periods in that range. (defaults= 20, 50) [Investopedia](#https://www.investopedia.com/terms/s/sma.asp)
+* -v : Adds VWAP (Volume Weighted Average Price) to the chart. VWAP gives the average price a security has traded at throughout the day, based on both volume and price. [Investopedia](#https://www.investopedia.com/terms/v/vwap.asp)
## price
```text
@@ -144,3 +160,38 @@ Plots the current orderbook for loaded instrument if one is provided by Oanda. N
usage: positionbook
```
Plots the current positionbook for the loaded instrument if one is provided by Oanda. Not a live chart.
+
+## news
+
+```text
+news [-n N_NUM]
+```
+
+Prints latest news about currency, including date, title and web link. [Source: News API]
+
+* -n : Number of latest news being printed. Default 10.
+
+## reddit
+
+```text
+usage: red [-l N_LIMIT] [-d N_DAYS] [-a]
+```
+
+Print top stock's due diligence from other users. [Source: Reddit]
+
+* -l : limit of posts to retrieve
+* -d : number of prior days to look for
+* -a : "search through all flairs (apart from Yolo and Meme). Default False (i.e. use flairs: DD, technical analysis, Catalyst, News, Advice, Chart, Charts and Setups, Fundamental Analysis, Forex, Trade Idea)
+
+## eda
+```text
+usage: eda
+```
+
+Access the exploratory data analysis menu.
+
+## ba
+```text
+usage: ba
+```
+Access the behavioural analysis menu.
diff --git a/gamestonk_terminal/forex/fx_controller.py b/gamestonk_terminal/forex/fx_controller.py
index b1ab4dc7c68..b796f83ff25 100644
--- a/gamestonk_terminal/forex/fx_controller.py
+++ b/gamestonk_terminal/forex/fx_controller.py
@@ -6,6 +6,11 @@ from gamestonk_terminal import feature_flags as gtff
from gamestonk_terminal.menu import session
from gamestonk_terminal.forex import fx_view
from gamestonk_terminal import config_terminal as cfg
+from gamestonk_terminal.due_diligence import news_view, reddit_view
+from gamestonk_terminal.behavioural_analysis import ba_controller
+from gamestonk_terminal.exploratory_data_analysis import eda_controller
+import pandas as pd
+
account = cfg.OANDA_ACCOUNT
@@ -31,6 +36,10 @@ class ForexController:
"candles",
"pending",
"calendar",
+ "news",
+ "reddit",
+ "eda",
+ "ba",
]
def __init__(self):
@@ -69,6 +78,16 @@ class ForexController:
print(" order place limit order -u # of units -p price")
print(" orderbook print orderbook")
print(" positionbook print positionbook")
+ print(" news print news [News API]")
+ print(
+ " reddit search reddit for posts about the loaded instrument"
+ )
+ print(
+ " eda > exploratory data analysis, e.g.: decompose, cusum, residuals analysis"
+ )
+ print(
+ " ba > behavioural analysis, from: reddit, stocktwits, twitter, google"
+ )
print("")
def switch(self, an_input: str):
@@ -152,6 +171,28 @@ class ForexController:
"""Call calendar"""
fx_view.calendar(self.instrument, other_args)
+ def call_news(self, other_args: List[str]):
+ """Call news [News API]"""
+ news_view.news(other_args, self.instrument)
+
+ def call_reddit(self, other_args: List[str]):
+ instrument = fx_view.format_instrument(self.instrument, " ")
+ reddit_view.due_diligence(other_args, instrument)
+
+ def call_eda(self, other_args):
+ df = fx_view.get_candles_dataframe(account, self.instrument, None)
+ df = df.rename(columns={"Close": "5. adjusted close"})
+ instrument = self.instrument
+ s_start = pd.to_datetime(df.index.values[0])
+ s_interval = "1440min"
+ eda_controller.menu(df, instrument, s_start, s_interval)
+
+ def call_ba(self, other_args: List[str]):
+ instrument = fx_view.format_instrument(self.instrument, " ")
+ df = fx_view.get_candles_dataframe(account, self.instrument, None)
+ s_start = pd.to_datetime(df.index.values[0])
+ ba_controller.menu(instrument, s_start)
+
def menu():
"""Oanda Menu"""
diff --git a/gamestonk_terminal/forex/fx_view.py b/gamestonk_terminal/forex/fx_view.py
index cc4f1c59842..0ac34599671 100644
--- a/gamestonk_terminal/forex/fx_view.py
+++ b/gamestonk_terminal/forex/fx_view.py
@@ -12,8 +12,13 @@ from oandapyV20.exceptions import V20Error
from gamestonk_terminal import config_terminal as cfg
from gamestonk_terminal import config_plot as cfgPlot
from gamestonk_terminal import feature_flags as gtff
-from gamestonk_terminal.helper_funcs import parse_known_args_and_warn, plot_autoscale
+from gamestonk_terminal.helper_funcs import (
+ parse_known_args_and_warn,
+ plot_autoscale,
+ check_non_negative,
+)
import pandas as pd
+import pandas_ta as ta
import mplfinance as mpf
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
@@ -236,6 +241,11 @@ def create_order(accountID, instrument, other_args: List[str]):
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
+ if "JPY" or "THB" or "HUF" in instrument:
+ ns_parser.price = round(ns_parser.price, 3)
+ else:
+ ns_parser.price = round(ns_parser.price, 5)
+ check_non_negative(ns_parser.price)
data = {
"order": {
@@ -250,37 +260,25 @@ def create_order(accountID, instrument, other_args: List[str]):
try:
request = orders.OrderCreate(accountID, data)
response = client.request(request)
+ order_data = []
+ order_data.append(
+ {
+ "Order ID": response["orderCreateTransaction"]["id"],
+ "Instrument": response["orderCreateTransaction"]["instrument"],
+ "Price": response["orderCreateTransaction"]["price"],
+ "Units": response["orderCreateTransaction"]["units"],
+ }
+ )
- if "orderFillTransaction" in response["orderCreateTransaction"]:
- order_id = response["orderCreateTransaction"]["orderFillTransaction"]["id"]
- order_instrument = response["orderCreateTransaction"][
- "orderFillTransaction"
- ]["instrument"]
- units = response["orderCreateTransaction"]["orderFillTransaction"]["units"]
- price = response["orderCreateTransaction"]["orderFillTransaction"]["price"]
- print("Order Filled:")
- print(f"ID: {order_id}")
- print(f"Instrument: {order_instrument}")
- print(f"Units: {units}")
- print(f"Price: {price}")
- print("")
- else:
- order_creation_id = response["orderCreateTransaction"]["id"]
- order_instrument = response["orderCreateTransaction"]["instrument"]
- units = response["orderCreateTransaction"]["units"]
- price = response["orderCreateTransaction"]["price"]
- print("Order created:")
- print(f"ID: {order_creation_id}")
- print(f"Instrument: {order_instrument}")
- print(f"Units: {units}")
- print(f"Price: {price}")
- print("")
+ df = pd.DataFrame.from_dict(order_data)
+ print(df.to_string(index=False))
+ print("")
- except Exception as e:
- print(e)
except V20Error as e:
d_error = eval(e.msg)
- print(d_error["message"], "\n")
+ print(d_error["errorMessage"], "\n")
+ except Exception as e:
+ print(e)
def cancel_pending_order(accountID, other_args: List[str]):
@@ -327,21 +325,28 @@ def get_pending_orders(accountID, other_args):
try:
request = orders.OrdersPending(accountID)
response = client.request(request)
+ pending_data = []
for i in range(len(response["orders"])):
- order_id = response["orders"][i]["id"]
- instrument = response["orders"][i]["instrument"]
- price = response["orders"][i]["price"]
- units = response["orders"][i]["units"]
- create_time = response["orders"][i]["createTime"]
- time_in_force = response["orders"][i]["timeInForce"]
- print(f"Order ID: {order_id}")
- print(f"Instrument: {instrument}")
- print(f"Price: {price}")
- print(f"Units: {units}")
- print(f"Time created: {create_time}")
- print(f"Time in force: {time_in_force}")
- print("-" * 30)
+ pending_data.append(
+ {
+ "Order ID": response["orders"][i]["id"],
+ "Instrument": response["orders"][i]["instrument"],
+ "Price": response["orders"][i]["price"],
+ "Units": response["orders"][i]["units"],
+ "Time Created": response["orders"][i]["createTime"][:10]
+ + " "
+ + response["orders"][i]["createTime"][11:19],
+ "Time In Force": response["orders"][i]["timeInForce"],
+ }
+ )
+
+ df = pd.DataFrame.from_dict(pending_data)
+ if not pending_data:
+ print("No pending orders")
+ else:
+ print(df.to_string(index=False))
print("")
+
except V20Error as e:
d_error = eval(e.msg)
print(d_error["errorMessage"], "\n")
@@ -359,22 +364,26 @@ def get_open_positions(accountID, other_args):
try:
request = positions.OpenPositions(accountID)
response = client.request(request)
+ position_data = []
for i in range(len(response["positions"])):
- instrument = response["positions"][i]["instrument"]
- long_units = response["positions"][i]["long"]["units"]
- long_pl = response["positions"][i]["long"]["pl"]
- long_upl = response["positions"][i]["long"]["unrealizedPL"]
- short_units = response["positions"][i]["short"]["units"]
- short_pl = response["positions"][i]["short"]["pl"]
- short_upl = response["positions"][i]["short"]["unrealizedPL"]
- print(f"Instrument: {instrument}\n")
- print(f"Long Units: {long_units}")
- print(f"Total Long P/L: {long_pl}")
- print(f"Long Unrealized P/L: {long_upl}\n")
- print(f"Short Units: {short_units}")
- print(f"Total Short P/L: {short_pl}")
- print(f"Short Unrealized P/L: {short_upl}")
- print("-" * 30 + "\n")
+ position_data.append(
+ {
+ "Instrument": response["positions"][i]["instrument"],
+ "Long Units": response["positions"][i]["long"]["units"],
+ "Total Long P/L": response["positions"][i]["long"]["units"],
+ "Unrealized Long P/L": response["positions"][i]["long"][
+ "unrealizedPL"
+ ],
+ "Short Units": response["positions"][i]["short"]["units"],
+ "Total Short P/L": response["positions"][i]["short"]["pl"],
+ "Short Unrealized P/L": response["positions"][i]["short"][
+ "unrealizedPL"
+ ],
+ }
+ )
+
+ df = pd.DataFrame.from_dict(position_data)
+ print(df.to_string(index=False))
print("")
except V20Error as e:
@@ -417,8 +426,10 @@ def get_open_trades(accountID, other_args):
"unrealizedPL": "Unrealized P/L",
}
)
- print(df)
+
+ print(df.to_string(index=False))
print("")
+
except KeyError:
print("No trades were found")
print("")
@@ -467,24 +478,25 @@ def close_trade(accountID, other_args: List[str]):
request = trades.TradeClose(accountID, ns_parser.orderID, data)
response = client.request(request)
- order_id = response["orderCreateTransaction"]["tradeClose"]["tradeID"]
- order_instrument = response["orderFillTransaction"]["instrument"]
- units = response["orderCreateTransaction"]["units"]
- price = response["orderFillTransaction"]["price"]
- pl = response["orderFillTransaction"]["pl"]
- print("Order closed:")
- print(f"ID: {order_id}")
- print(f"Instrument: {order_instrument}")
- print(f"Units: {units}")
- print(f"Price: {price}")
- print(f"P/L: {pl}")
+ close_data = []
+ close_data.append(
+ {
+ "OrderID": response["orderCreateTransaction"]["tradeClose"]["tradeID"],
+ "Instrument": response["orderFillTransaction"]["instrument"],
+ "Units": response["orderCreateTransaction"]["units"],
+ "Price": response["orderFillTransaction"]["price"],
+ "P/L": response["orderFillTransaction"]["pl"],
+ }
+ )
+ df = pd.DataFrame.from_dict(close_data)
+ print(df.to_string(index=False))
print("")
- except Exception as e:
- print(e, "\n")
except V20Error as e:
d_error = eval(e.msg)
print(d_error["errorMessage"], "\n")
+ except Exception as e:
+ print(e, "\n")
def show_candles(accountID, instrument, other_args: List[str]):
@@ -515,71 +527,164 @@ def show_candles(accountID, instrument, other_args: List[str]):
required=False,
help="The number of candles to retrieve. Default:180 ",
)
+ parser.add_argument(
+ "-a",
+ "--ad",
+ dest="ad",
+ action="store_true",
+ help="Adds ad (Accumulation/Distribution Indicator) to the chart",
+ )
+ parser.add_argument(
+ "-b",
+ "--bbands",
+ dest="bbands",
+ action="store_true",
+ help="Adds Bollinger Bands to the chart",
+ )
+ parser.add_argument(
+ "-C",
+ "--cci",
+ dest="cci",
+ action="store_true",
+ help="Adds cci (Commodity Channel Index) to the chart",
+ )
+ parser.add_argument(
+ "-e",
+ "--ema",
+ dest="ema",
+ action="store_true",
+ help="Adds ema (Exponential Moving Average) to the chart",
+ )
+ parser.add_argument(
+ "-o",
+ "--obv",
+ dest="obv",
+ action="store_true",
+ help="Adds obv (On Balance Volume) to the chart",
+ )
+ parser.add_argument(
+ "-r",
+ "--rsi",
+ dest="rsi",
+ action="store_true",
+ help="Adds rsi (Relative Strength Index) to the chart",
+ )
+ parser.add_argument(
+ "-s",
+ "--sma",
+ dest="sma",
+ action="store_true",
+ help="Adds sma (Simple Moving Average) to the chart",
+ )
+ parser.add_argument(
+ "-v",
+ "--vwap",
+ dest="vwap",
+ action="store_true",
+ help="Adds vwap (Volume Weighted Average Price) to the chart",
+ )
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
parameters = {}
- parameters["granularity"] = ns_parser.granularity
+ parameters["granularity"] = ns_parser.granularity.upper()
parameters["count"] = ns_parser.candlecount
try:
instrument = format_instrument(instrument, "_")
- request = instruments.InstrumentsCandles(instrument, params=parameters)
- response = client.request(request)
- process_candle_response(response)
- oanda_fix_date(".temp_candles.csv")
- df = pd.read_csv(".candles.csv", index_col=0)
- df.index = pd.to_datetime(df.index)
- df.columns = ["Open", "High", "Low", "Close", "Volume"]
+ df = get_candles_dataframe(accountID, instrument, parameters)
+
+ plots_to_add, legends, subplot_legends = add_plots(df, ns_parser)
+
if gtff.USE_ION:
plt.ion()
- mpf.plot(
+
+ fig, ax = mpf.plot(
df,
type="candle",
style="charles",
volume=True,
title=f"{instrument} {ns_parser.granularity}",
+ returnfig=True,
+ addplot=plots_to_add,
)
+
+ ax[0].set_title(f"{instrument} {ns_parser.granularity}")
+ ax[0].legend(legends)
+ for i in range(0, len(subplot_legends), 2):
+ ax[subplot_legends[i]].legend(subplot_legends[i + 1])
+
print("")
except V20Error as e:
d_error = eval(e.msg)
print(d_error["errorMessage"], "\n")
+ except TypeError as e:
+ print(e)
-def process_candle_response(response):
- with open(".temp_candles.csv", "w") as out:
- for i in range(len(response["candles"])):
- time = response["candles"][i]["time"]
- volume = response["candles"][i]["volume"]
- o = response["candles"][i]["mid"]["o"]
- h = response["candles"][i]["mid"]["h"]
- low = response["candles"][i]["mid"]["l"]
- c = response["candles"][i]["mid"]["c"]
- out.write(
- str(time)
- + ","
- + str(o)
- + ","
- + str(h)
- + ","
- + str(low)
- + ","
- + str(c)
- + ","
- + str(volume)
- + "\n"
- )
+def add_plots(df, ns_parser):
+ panel_number = 2
+ plots_to_add = []
+ legends = []
+ subplot_legends = []
+ if ns_parser.ad:
+ ad = ta.ad(df["High"], df["Low"], df["Close"], df["Volume"])
+ ad_plot = mpf.make_addplot(ad, panel=panel_number)
+ plots_to_add.append(ad_plot)
+ subplot_legends.extend([panel_number * 2, ["AD"]])
+ panel_number += 1
-def oanda_fix_date(file):
- with open(file) as candle_file:
- lines = candle_file.readlines()
- with open(".candles.csv", "w") as out:
- out.write("Datetime, Open, High, Low, Close, Volume\n")
- for line in lines:
- with open(".candles.csv", "a") as output:
- output.write(line[:10] + " " + line[11:19] + line[30:])
+ if ns_parser.bbands:
+ bbands = ta.bbands(df["Close"])
+ bbands = bbands.drop("BBB_5_2.0", axis=1)
+ bbands_plot = mpf.make_addplot(bbands, panel=0)
+ plots_to_add.append(bbands_plot)
+ legends.extend(["Lower BBand", "Middle BBand", "Upper BBand"])
+
+ if ns_parser.cci:
+ cci = ta.cci(df["High"], df["Low"], df["Close"])
+ cci_plot = mpf.make_addplot(cci, panel=panel_number)
+ plots_to_add.append(cci_plot)
+ subplot_legends.extend([panel_number * 2, ["CCI"]])
+ panel_number += 1
+
+ if ns_parser.ema:
+ ema = ta.ema(df["Close"])
+ ema_plot = mpf.make_addplot(ema, panel=0)
+ plots_to_add.append(ema_plot)
+ legends.append("10 EMA")
+
+ if ns_parser.rsi:
+ rsi = ta.rsi(df["Close"])
+ rsi_plot = mpf.make_addplot(rsi, panel=panel_number)
+ plots_to_add.append(rsi_plot)
+ subplot_legends.extend([panel_number * 2, ["RSI"]])
+ panel_number += 1
+
+ if ns_parser.obv:
+ obv = ta.obv(df["Close"], df["Volume"])
+ obv_plot = mpf.make_addplot(obv, panel=panel_number)
+ plots_to_add.append(obv_plot)
+ subplot_legends.extend([panel_number * 2, ["OBV"]])
+ panel_number += 1
+
+ if ns_parser.sma:
+ sma_length = [20, 50]
+ for length in sma_length:
+ sma = ta.sma(df["Close"], length=length)
+ sma_plot = mpf.make_addplot(sma, panel=0)
+ plots_to_add.append(sma_plot)
+ legends.append(f"{length} SMA")
+
+ if ns_parser.vwap:
+ vwap = ta.vwap(df["High"], df["Low"], df["Close"], df["Volume"])
+ vwap_plot = mpf.make_addplot(vwap, panel=0)
+ plots_to_add.append(vwap_plot)
+ legends.append("vwap")
+
+ return plots_to_add, legends, subplot_legends
def calendar(instrument, other_args: List[str]):
@@ -665,6 +770,38 @@ def calendar(instrument, other_args: List[str]):
print(d_error["message"], "\n")
+def get_candles_dataframe(accountID, instrument, parameters):
+ if not parameters:
+ parameters = {
+ "granularity": "D",
+ "count": "1500",
+ }
+ try:
+ request = instruments.InstrumentsCandles(instrument, params=parameters)
+ response = client.request(request)
+ candles_data = []
+ for i in range(len(response["candles"])):
+ candles_data.append(
+ {
+ "Date": response["candles"][i]["time"][:10]
+ + " "
+ + response["candles"][i]["time"][11:19],
+ "Open": float(response["candles"][i]["mid"]["o"]),
+ "High": float(response["candles"][i]["mid"]["h"]),
+ "Low": float(response["candles"][i]["mid"]["l"]),
+ "Close": float(response["candles"][i]["mid"]["c"]),
+ "Volume": response["candles"][i]["volume"],
+ }
+ )
+ df = pd.DataFrame(candles_data)
+ df.set_index("Date", inplace=True)
+ df.index = pd.to_datetime(df.index)
+ return df
+ except V20Error as e:
+ d_error = eval(e.msg)
+ print(d_error["errorMessage"], "\n")
+
+
def load(other_args: List[str]):
"""Load a forex instrument to use"""
parser = argparse.ArgumentParser(
@@ -740,9 +877,16 @@ def book_plot(df, instrument, book_type):
def format_instrument(instrument, char):
- if char not in instrument:
- instrument_list = list(instrument)
- instrument_list.pop(3)
- instrument_list.insert(3, char)
- instrument = "".join(map(str, instrument_list))
- return instrument
+ try:
+ if char not in instrument:
+ instrument_list = list(instrument)
+ instrument_list.pop(3)
+ if char == " ":
+ instrument = "".join(map(str, instrument_list))
+ else:
+ instrument_list.insert(3, char)
+ instrument = "".join(map(str, instrument_list))
+ return instrument
+ except TypeError:
+ print("Please load an instrument")
+ print("")