def view_vwap(
s_ticker: str,
df_stock: pd.DataFrame,
offset: int = 0,
s_interval: str = "",
export: str = "",
):
"""Plots EMA technical indicator
Parameters
----------
s_ticker : str
Ticker
df_stock : pd.DataFrame
Dataframe of prices
offset : int
Offset variable
s_interval : str
Interval of data
export : str
Format to export data
"""
df_stock.index = df_stock.index.tz_localize(None)
df_stock["Day"] = [idx.date() for idx in df_stock.index]
day_df = df_stock[df_stock.Day == df_stock.Day[-1]]
df_vwap = overlap_model.vwap(day_df, offset)
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)
addplot_result = mpf.make_addplot(df_vwap, color="k")
mpf.plot(
day_df,
style=s,
type="candle",
addplot=addplot_result,
volume=True,
title=f"\n{s_ticker} {s_interval} VWAP",
)
if gtff.USE_ION:
plt.ion()
plt.show()
console.print("")
export_data(
export,
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
"VWAP",
df_vwap,
)
def view_vwap(
s_ticker: str,
ohlc: pd.DataFrame,
offset: int = 0,
s_interval: str = "",
export: str = "",
external_axes: Optional[List[plt.Axes]] = None,
):
"""Plots EMA technical indicator
Parameters
----------
s_ticker : str
Ticker
ohlc : pd.DataFrame
Dataframe of prices
offset : int
Offset variable
s_interval : str
Interval of data
export : str
Format to export data
external_axes : Optional[List[plt.Axes]], optional
External axes (3 axes are expected in the list), by default None
"""
ohlc.index = ohlc.index.tz_localize(None)
ohlc["Day"] = [idx.date() for idx in ohlc.index]
day_df = ohlc[ohlc.Day == ohlc.Day[-1]]
df_vwap = overlap_model.vwap(day_df, offset)
candle_chart_kwargs = {
"type": "candle",
"style": theme.mpf_style,
"volume": True,
"xrotation": theme.xticks_rotation,
"scale_padding": {
"left": 0.3,
"right": 1.2,
"top": 0.8,
"bottom": 0.8
},
"update_width_config": {
"candle_linewidth": 0.6,
"candle_width": 0.8,
"volume_linewidth": 0.8,
"volume_width": 0.8,
},
"warn_too_much_data": 10000,
}
# This plot has 2 axes
if external_axes is None:
candle_chart_kwargs["returnfig"] = True
candle_chart_kwargs["figratio"] = (10, 7)
candle_chart_kwargs["figscale"] = 1.10
candle_chart_kwargs["figsize"] = plot_autoscale()
candle_chart_kwargs["addplot"] = mpf.make_addplot(
df_vwap, width=theme.line_width)
fig, _ = mpf.plot(day_df, **candle_chart_kwargs)
fig.suptitle(
f"{s_ticker} {s_interval} VWAP",
x=0.055,
y=0.965,
horizontalalignment="left",
)
theme.visualize_output(force_tight_layout=False)
else:
if len(external_axes) != 3:
console.print("[red]Expected list of 3 axis items./n[/red]")
return
(ax1, ax2, ax3) = external_axes
candle_chart_kwargs["ax"] = ax1
candle_chart_kwargs["volume"] = ax2
candle_chart_kwargs["addplot"] = mpf.make_addplot(
df_vwap, width=theme.line_width, ax=ax3)
mpf.plot(day_df, **candle_chart_kwargs)
export_data(
export,
os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
"VWAP",
df_vwap,
)
def candle_command(
ticker: str = "",
interval: int = 15,
past_days: int = 0,
extended_hours: bool = False,
start="",
end="",
news: bool = False,
heikin_candles: bool = False,
vwap: bool = False,
):
"""Shows candle plot of loaded ticker or crypto. [Source: Yahoo Finance or Binance API]
Parameters
----------
ticker : Stock Ticker
interval : Chart Minute Interval, 1440 for Daily
past_days: Past Days to Display. Default: 0(Not for Daily)
extended_hours: Display Pre/After Market Hours. Default: False
start: YYYY-MM-DD format
end: YYYY-MM-DD format
news: Display clickable news markers on interactive chart. Default: False
heikin_candles: Heikin Ashi candles. Default: False
"""
logger.info(
"candle %s %s %s %s %s %s %s %s",
ticker,
interval,
past_days,
extended_hours,
start,
end,
news,
heikin_candles,
)
# Retrieve Data
df_stock, start, end, bar_start = load_candle.stock_data(
ticker=ticker,
interval=interval,
past_days=past_days,
extended_hours=extended_hours,
start=start,
end=end,
news=news,
heikin_candles=heikin_candles,
)
df_stock = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_stock = df_stock.join(overlap_model.vwap(df_stock, 0))
# Check that loading a stock was not successful
if df_stock.empty:
raise Exception(f"No data found for {ticker.upper()}.")
# Output Data
if interval != 1440:
df_stock = df_stock.loc[(df_stock.index >= bar_start) & (df_stock.index < end)]
plot = load_candle.candle_fig(
df_stock,
ticker,
interval,
extended_hours,
news,
bar=bar_start,
int_bar=interval,
)
title = f"{plot['plt_title']} Chart"
fig = plot["fig"]
if interval != 1440 and vwap:
fig.add_trace(
go.Scatter(
name="VWAP",
x=df_stock.index,
y=df_stock["VWAP_D"],
opacity=0.65,
line=dict(color="#00e6c3", width=2),
showlegend=True,
),
secondary_y=True,
)
fig.update_layout(
margin=dict(l=0, r=0, t=40, b=20),
template=imps.PLT_CANDLE_STYLE_TEMPLATE,
title=title,
title_x=0.5,
title_font_size=14,
)
imagefile = "candle.png"
# Check if interactive settings are enabled
plt_link = ""
if imps.INTERACTIVE:
plt_link = imps.inter_chart(fig, imagefile, callback=True)
fig.update_layout(
width=800,
height=500,
)
imagefile = imps.image_border(imagefile, fig=fig)
return {
"title": title,
"description": plt_link,
"imagefile": imagefile,
}
async def candle_command(
ctx,
ticker: str = "",
interval: int = 15,
past_days: int = 1,
start="",
end="",
):
"""Shows candle plot of loaded ticker. [Source: Yahoo Finance, IEX Cloud or Alpha Vantage]
Parameters
----------
ticker: str
Ticker name
interval: int
chart mins or daily
past_days: int
Display the past * days. Default: 1(Not for Daily)
start: str
start date format YYYY-MM-DD
end: str
end date format YYYY-MM-DD
"""
try:
logger.info("candle %s %s %s %s", ticker, interval, start, end)
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
futures = "=F"
if interval == 1440:
df_stock_candidate = yf.download(
ticker,
start=start,
end=end,
progress=False,
)
# Check that loading a stock was not successful
if df_stock_candidate.empty:
raise Exception(f"No data found for {ticker.upper()}")
df_stock_candidate.index.name = "date"
else:
s_int = str(interval) + "m"
d_granularity = {
"1m": past_days,
"5m": past_days,
"15m": past_days,
"30m": past_days,
"60m": past_days,
}
s_start_dt = datetime.utcnow() - timedelta(
days=d_granularity[s_int])
s_date_start = s_start_dt.strftime("%Y-%m-%d")
df_stock_candidate = yf.download(
ticker,
start=s_date_start
if s_start_dt > start else start.strftime("%Y-%m-%d"),
progress=False,
interval=s_int,
prepost=True,
)
# Check that loading a stock was not successful
if df_stock_candidate.empty:
raise Exception(f"No data found for {ticker.upper()}.")
df_stock_candidate.index = df_stock_candidate.index.tz_localize(None)
df_stock_candidate.index.name = "date"
df_stock = df_stock_candidate
price_df = df_stock.loc[(df_stock.index >= start)
& (df_stock.index < end)]
df_vwap = overlap_model.vwap(price_df, 0)
plt_title = [f"{ticker.upper()} Intraday {interval}min", "Volume"]
title = f"Intraday {interval}min Chart for {ticker.upper()}"
if interval == 1440:
plt_title = [f"{ticker.upper()} Daily", "Volume"]
title = f"Daily Chart for {ticker.upper()}"
fig = make_subplots(
rows=2,
cols=1,
shared_xaxes=True,
vertical_spacing=0.06,
subplot_titles=plt_title,
row_width=[0.2, 0.7],
)
fig.add_trace(
go.Candlestick(
x=df_stock.index,
open=df_stock.Open,
high=df_stock.High,
low=df_stock.Low,
close=df_stock.Close,
name="OHLC",
showlegend=False,
),
row=1,
col=1,
)
colors = [
"green" if row.Open < row["Adj Close"] else "red"
for _, row in df_stock.iterrows()
]
fig.add_trace(
go.Bar(
x=df_stock.index,
y=df_stock.Volume,
name="Volume",
marker_color=colors,
showlegend=False,
),
row=2,
col=1,
)
fig.update_layout(
margin=dict(l=0, r=0, t=25, b=20),
template=cfg.PLT_CANDLE_STYLE_TEMPLATE,
yaxis_title="Stock Price ($)",
yaxis=dict(
fixedrange=False,
showspikes=True,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
showspikes=True,
),
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
dragmode="pan",
hovermode="x unified",
)
if interval != 1440:
fig.add_trace(
go.Scatter(
name="VWAP",
x=df_stock.index,
y=df_vwap["VWAP_D"],
opacity=1,
line=dict(color="#d81aea", width=2),
showlegend=True,
), )
if futures in ticker.upper():
fig.update_xaxes(rangebreaks=[
dict(bounds=["fri", "sun"]),
dict(bounds=[17, 17.5], pattern="hour"),
], )
else:
fig.update_xaxes(rangebreaks=[
dict(bounds=["sat", "mon"]),
dict(bounds=[19, 9.5], pattern="hour"),
], )
config = dict({"scrollZoom": True})
rand = random.randint(69, 69420)
imagefile = f"candle{rand}.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
fig.write_html(f"in/candle_{rand}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/candle_{rand}.html)"
fig.update_layout(
width=800,
height=500,
)
fig.write_image(imagefile)
img = Image.open(imagefile)
im_bg = Image.open(cfg.IMG_BG)
h = img.height + 240
w = img.width + 520
# Paste fig onto background img and autocrop background
img = img.resize((w, h), Image.ANTIALIAS)
x1 = int(0.5 * im_bg.size[0]) - int(0.5 * img.size[0])
y1 = int(0.5 * im_bg.size[1]) - int(0.5 * img.size[1])
x2 = int(0.5 * im_bg.size[0]) + int(0.5 * img.size[0])
y2 = int(0.5 * im_bg.size[1]) + int(0.5 * img.size[1])
img = img.convert("RGB")
im_bg.paste(img, box=(x1 - 5, y1, x2 - 5, y2))
im_bg.save(imagefile, "PNG", quality=100)
image = Image.open(imagefile)
image = autocrop_image(image, 0)
image.save(imagefile, "PNG", quality=100)
image = disnake.File(imagefile)
print(f"Image {imagefile}")
embed = disnake.Embed(title=title,
description=plt_link,
colour=cfg.COLOR)
embed.set_image(url=f"attachment://{imagefile}")
embed.set_author(
name=cfg.AUTHOR_NAME,
icon_url=cfg.AUTHOR_ICON_URL,
)
os.remove(imagefile)
await ctx.send(embed=embed, file=image)
except Exception as e:
embed = disnake.Embed(
title="ERROR Stocks: Intraday",
colour=cfg.COLOR,
description=e,
)
await ctx.send(embed=embed, delete_after=30.0)
def candle_command(
ticker: str = "",
interval: int = 15,
past_days: int = 1,
start="",
end="",
):
"""Shows candle plot of loaded ticker. [Source: Yahoo Finance, IEX Cloud or Alpha Vantage]
Parameters
----------
ticker: str
Ticker name
interval: int
chart mins or daily
past_days: int
Display the past * days. Default: 1(Not for Daily)
start: str
start date format YYYY-MM-DD
end: str
end date format YYYY-MM-DD
"""
logger.info("candle %s %s %s %s", ticker, interval, start, end)
if start == "":
start = datetime.now() - timedelta(days=365)
else:
start = datetime.strptime(start, cfg.DATE_FORMAT)
if end == "":
end = datetime.now()
else:
end = datetime.strptime(end, cfg.DATE_FORMAT)
futures = "=F" or "^"
crypto = "-USD"
if interval == 1440:
df_stock_candidate = yf.download(
ticker,
start=start,
end=end,
progress=False,
)
# Check that loading a stock was not successful
if df_stock_candidate.empty:
raise Exception(f"No data found for {ticker.upper()}")
df_stock_candidate.index.name = "date"
else:
s_int = str(interval) + "m"
d_granularity = {
"1m": past_days,
"5m": past_days,
"15m": past_days,
"30m": past_days,
"60m": past_days,
}
s_start_dt = datetime.utcnow() - timedelta(days=d_granularity[s_int])
s_date_start = s_start_dt.strftime("%Y-%m-%d")
df_stock_candidate = yf.download(
ticker,
start=s_date_start
if s_start_dt > start else start.strftime("%Y-%m-%d"),
progress=False,
interval=s_int,
prepost=True,
)
# Check that loading a stock was not successful
if df_stock_candidate.empty:
raise Exception(f"No data found for {ticker.upper()}.")
df_stock_candidate.index = df_stock_candidate.index.tz_localize(None)
df_stock_candidate.index.name = "date"
df_stock = df_stock_candidate
price_df = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
df_vwap = overlap_model.vwap(price_df, 0)
plt_title = [f"{ticker.upper()} Intraday {interval}min", "Volume"]
title = f"Intraday {interval}min Chart for {ticker.upper()}"
if interval == 1440:
plt_title = [f"{ticker.upper()} Daily", "Volume"]
title = f"Daily Chart for {ticker.upper()}"
fig = make_subplots(
shared_xaxes=True,
vertical_spacing=0.09,
subplot_titles=plt_title,
specs=[[{
"secondary_y": True
}]],
)
fig.add_trace(
go.Candlestick(
x=df_stock.index,
open=df_stock.Open,
high=df_stock.High,
low=df_stock.Low,
close=df_stock.Close,
name="OHLC",
showlegend=False,
),
secondary_y=True,
)
fig.add_trace(
go.Bar(
x=df_stock.index,
y=df_stock.Volume,
name="Volume",
yaxis="y2",
marker_color="#d81aea",
opacity=0.4,
showlegend=False,
),
secondary_y=False,
)
if interval != 1440:
fig.add_trace(
go.Scatter(
name="VWAP",
x=df_stock.index,
y=df_vwap["VWAP_D"],
opacity=0.65,
line=dict(color="#fdc708", width=2),
showlegend=True,
),
secondary_y=True,
)
fig.update_xaxes(showspikes=True, spikesnap="cursor", spikemode="across")
fig.update_yaxes(showspikes=True, spikethickness=2)
fig.update_layout(
margin=dict(l=0, r=0, t=40, b=20),
template=cfg.PLT_CANDLE_STYLE_TEMPLATE,
yaxis2_title="Price ($)",
yaxis_title="Volume",
yaxis=dict(
showgrid=False,
fixedrange=False,
side="left",
titlefont=dict(color="#d81aea"),
tickfont=dict(color="#d81aea"),
nticks=20,
),
yaxis2=dict(
side="right",
fixedrange=False,
anchor="x",
layer="above traces",
overlaying="y",
nticks=20,
),
xaxis=dict(
rangeslider=dict(visible=False),
type="date",
showspikes=True,
),
legend=dict(orientation="h",
yanchor="bottom",
y=1.02,
xanchor="right",
x=1),
dragmode="pan",
hovermode="x unified",
spikedistance=1000,
hoverdistance=100,
)
if futures in ticker.upper():
fig.update_xaxes(rangebreaks=[
dict(bounds=["sat", "sun"]),
dict(bounds=[17, 17.50], pattern="hour"),
], )
elif crypto not in ticker.upper() and interval != 1440:
fig.update_xaxes(rangebreaks=[
dict(bounds=["sat", "mon"]),
dict(bounds=[20, 9.50], pattern="hour"),
], )
config = dict({"scrollZoom": True})
imagefile = "candle.png"
# Check if interactive settings are enabled
plt_link = ""
if cfg.INTERACTIVE:
html_ran = helpers.uuid_get()
fig.write_html(f"in/candle_{html_ran}.html", config=config)
plt_link = f"[Interactive]({cfg.INTERACTIVE_URL}/candle_{html_ran}.html)"
fig.update_layout(
width=800,
height=500,
)
imagefile = helpers.image_border(imagefile, fig=fig)
return {
"title": title,
"description": plt_link,
"imagefile": imagefile,
}