def test_display_candle(mocker, use_matplotlib):
mocker.patch.object(target=stocks_helper.gtff,
attribute="USE_ION",
new=False)
mocker.patch("matplotlib.pyplot.show")
mocker.patch("plotly.basedatatypes.BaseFigure.show")
# LOAD DATA
ticker = "GME"
start = datetime.strptime("2020-12-01", "%Y-%m-%d")
interval = 1440
end = datetime.strptime("2020-12-08", "%Y-%m-%d")
prepost = False
source = "yf"
df_stock = stocks_helper.load(
ticker=ticker,
start=start,
interval=interval,
end=end,
prepost=prepost,
source=source,
)
# PROCESS DATA
df_stock = stocks_helper.process_candle(df_data=df_stock)
# DISPLAY CANDLE
s_ticker = "GME"
intraday = False
stocks_helper.display_candle(
s_ticker=s_ticker,
df_stock=df_stock,
use_matplotlib=use_matplotlib,
intraday=intraday,
)
def test_display_candle(mocker, use_matplotlib):
# MOCK VISUALIZE_OUTPUT
mocker.patch(
target="gamestonk_terminal.helper_classes.TerminalStyle.visualize_output"
)
mocker.patch("plotly.basedatatypes.BaseFigure.show")
# LOAD DATA
ticker = "GME"
start = datetime.strptime("2020-12-01", "%Y-%m-%d")
interval = 1440
end = datetime.strptime("2020-12-08", "%Y-%m-%d")
prepost = False
source = "yf"
df_stock = stocks_helper.load(
ticker=ticker,
start=start,
interval=interval,
end=end,
prepost=prepost,
source=source,
)
# PROCESS DATA
df_stock = stocks_helper.process_candle(df=df_stock)
# DISPLAY CANDLE
s_ticker = "GME"
intraday = False
stocks_helper.display_candle(
s_ticker=s_ticker,
df_stock=df_stock,
use_matplotlib=use_matplotlib,
intraday=intraday,
)
def call_candle(self, other_args: List[str]):
"""Process candle command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="candle",
description="Shows historic data for a stock",
)
parser.add_argument(
"-m",
"--matplotlib",
dest="matplotlib",
action="store_true",
default=False,
help="Flag to show matplotlib instead of interactive plot using plotly.",
)
parser.add_argument(
"--sort",
choices=[
"AdjClose",
"Open",
"Close",
"High",
"Low",
"Volume",
"Returns",
"LogRet",
],
default="",
type=str,
dest="sort",
help="Choose a column to sort by",
)
parser.add_argument(
"-d",
"--descending",
action="store_false",
dest="descending",
default=True,
help="Sort selected column descending",
)
parser.add_argument(
"--raw",
action="store_true",
dest="raw",
default=False,
help="Shows raw data instead of chart",
)
parser.add_argument(
"-n",
"--num",
type=check_positive,
help="Number to show if raw selected",
dest="num",
default=20,
)
ns_parser = parse_known_args_and_warn(
parser, other_args, EXPORT_ONLY_RAW_DATA_ALLOWED
)
if ns_parser:
if self.ticker:
export_data(
ns_parser.export,
os.path.join(
os.path.dirname(os.path.abspath(__file__)), "raw_data"
),
f"{self.ticker}",
self.stock,
)
if ns_parser.raw:
qa_view.display_raw(
df=self.stock,
sort=ns_parser.sort,
des=ns_parser.descending,
num=ns_parser.num,
)
else:
data = stocks_helper.process_candle(self.stock)
stocks_helper.display_candle(
s_ticker=self.ticker,
df_stock=data,
use_matplotlib=ns_parser.matplotlib,
intraday=self.interval != "1440min",
)
else:
print("No ticker loaded. First use `load {ticker}`\n")
def call_candle(self, other_args: List[str]):
"""Process candle command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="candle",
description="Shows historic data for a stock",
)
parser.add_argument(
"-p",
"--plotly",
dest="plotly",
action="store_false",
default=True,
help="Flag to show interactive plotly chart.",
)
parser.add_argument(
"--sort",
choices=[
"AdjClose",
"Open",
"Close",
"High",
"Low",
"Volume",
"Returns",
"LogRet",
],
default="",
type=str,
dest="sort",
help="Choose a column to sort by",
)
parser.add_argument(
"-d",
"--descending",
action="store_false",
dest="descending",
default=True,
help="Sort selected column descending",
)
parser.add_argument(
"--raw",
action="store_true",
dest="raw",
default=False,
help="Shows raw data instead of chart",
)
parser.add_argument(
"-n",
"--num",
type=check_positive,
help="Number to show if raw selected",
dest="num",
default=20,
)
parser.add_argument(
"-t",
"--trend",
action="store_true",
default=False,
help="Flag to add high and low trends to candle.",
dest="trendlines",
)
parser.add_argument(
"--ma",
dest="mov_avg",
type=str,
help=
"Add moving average in number of days to plot and separate by a comma. Example: 20,30,50",
default=None,
)
ns_parser = parse_known_args_and_warn(parser, other_args,
EXPORT_ONLY_RAW_DATA_ALLOWED)
if ns_parser:
if self.ticker:
export_data(
ns_parser.export,
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"raw_data"),
f"{self.ticker}",
self.stock,
)
if ns_parser.raw:
qa_view.display_raw(
df=self.stock,
sort=ns_parser.sort,
des=ns_parser.descending,
num=ns_parser.num,
)
else:
data = stocks_helper.process_candle(self.stock)
mov_avgs = []
if ns_parser.mov_avg:
mov_list = (num
for num in ns_parser.mov_avg.split(","))
for num in mov_list:
try:
mov_avgs.append(int(num))
except ValueError:
console.print(
f"{num} is not a valid moving average, must be integer"
)
stocks_helper.display_candle(
s_ticker=self.ticker,
df_stock=data,
use_matplotlib=ns_parser.plotly,
intraday=self.interval != "1440min",
add_trend=ns_parser.trendlines,
ma=mov_avgs,
)
else:
console.print("No ticker loaded. First use `load {ticker}`\n")
def call_candle(self, other_args: List[str]):
"""Process candle command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="candle",
description="Shows historic data for an ETF",
)
parser.add_argument(
"-p",
"--plotly",
dest="plotly",
action="store_false",
default=True,
help="Flag to show interactive plotly chart.",
)
parser.add_argument(
"--sort",
choices=[
"AdjClose",
"Open",
"Close",
"High",
"Low",
"Volume",
"Returns",
"LogRet",
],
default="",
type=str,
dest="sort",
help="Choose a column to sort by",
)
parser.add_argument(
"-d",
"--descending",
action="store_false",
dest="descending",
default=True,
help="Sort selected column descending",
)
parser.add_argument(
"--raw",
action="store_true",
dest="raw",
default=False,
help="Shows raw data instead of chart",
)
parser.add_argument(
"-n",
"--num",
type=check_positive,
help="Number to show if raw selected",
dest="num",
default=20,
)
parser.add_argument(
"-t",
"--trend",
action="store_true",
default=False,
help="Flag to add high and low trends to candle.",
dest="trendlines",
)
parser.add_argument(
"--ma",
dest="mov_avg",
type=str,
help="Add moving averaged to plot",
default="",
)
ns_parser = parse_known_args_and_warn(parser, other_args,
EXPORT_ONLY_RAW_DATA_ALLOWED)
if ns_parser:
if self.etf_name:
export_data(
ns_parser.export,
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"raw_data"),
f"{self.etf_name}",
self.etf_data,
)
if ns_parser.raw:
qa_view.display_raw(
df=self.etf_data,
sort=ns_parser.sort,
des=ns_parser.descending,
num=ns_parser.num,
)
else:
data = stocks_helper.process_candle(self.etf_data)
mov_avgs = (tuple(
int(num) for num in ns_parser.mov_avg.split(","))
if ns_parser.mov_avg else None)
stocks_helper.display_candle(
s_ticker=self.etf_name,
df_stock=data,
use_matplotlib=ns_parser.plotly,
intraday=False,
add_trend=ns_parser.trendlines,
ma=mov_avgs,
asset_type="ETF",
)
else:
console.print("No ticker loaded. First use `load {ticker}`\n")
def call_candle(self, other_args: List[str]):
"""Process candle command"""
parser = argparse.ArgumentParser(
add_help=False,
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
prog="candle",
description="Shows historic data for an ETF",
)
ns_parser = parse_known_args_and_warn(
parser, other_args, EXPORT_BOTH_RAW_DATA_AND_FIGURES)
if ns_parser:
if self.etf_name:
# TODO: Should be done in one function
data = stocks_helper.process_candle(self.etf_data)
df_etf = stocks_helper.find_trendline(data, "OC_High", "high")
df_etf = stocks_helper.find_trendline(data, "OC_Low", "low")
mc = mpf.make_marketcolors(
up="green",
down="red",
edge="black",
wick="black",
volume="in",
ohlc="i",
)
s = mpf.make_mpf_style(marketcolors=mc,
gridstyle=":",
y_on_right=True)
ap0 = []
if "OC_High_trend" in df_etf.columns:
ap0.append(
mpf.make_addplot(df_etf["OC_High_trend"], color="g"), )
if "OC_Low_trend" in df_etf.columns:
ap0.append(
mpf.make_addplot(df_etf["OC_Low_trend"], color="b"), )
if gtff.USE_ION:
plt.ion()
mpf.plot(
df_etf,
type="candle",
mav=(20, 50),
volume=True,
title=f"\nETF: {self.etf_name}",
addplot=ap0,
xrotation=10,
style=s,
figratio=(10, 7),
figscale=1.10,
figsize=(plot_autoscale()),
update_width_config=dict(candle_linewidth=1.0,
candle_width=0.8,
volume_linewidth=1.0),
)
console.print("")
export_data(
ns_parser.export,
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"candle"),
f"{self.etf_name}",
self.etf_data,
)
else:
console.print("No ticker loaded. First use `load {ticker}`\n")