Пример #1
0
def fib_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    start: str = "",
    end: str = "",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with fibonacci retracement [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta fib %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    past_days = (past_days + 1) if (interval != 1440) or (start != "") else 365

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception(f"No data found for {ticker.upper()}.")

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]

    (
        df_fib,
        min_date,
        max_date,
        min_pr,
        max_pr,
    ) = custom_indicators_model.calculate_fib_levels(df_ta, 12, bar_start,
                                                     None)

    levels = df_fib.Price

    # Output Data
    fibs = [
        "<b>0</b>",
        "<b>0.235</b>",
        "<b>0.382</b>",
        "<b>0.5</b>",
        "<b>0.618</b>",
        "<b>0.65</b>",
        "<b>1</b>",
    ]
    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        shared_xaxes=True,
        vertical_spacing=0.07,
    )
    title = f"<b>{plot['plt_title']} Fibonacci-Retracement-Levels</b>"
    lvl_text: str = "right" if min_date > max_date else "left"
    fig = plot["fig"]

    fig.add_trace(
        go.Scatter(
            x=[min_date, max_date],
            y=[min_pr, max_pr],
            opacity=1,
            mode="lines",
            line=imps.PLT_FIB_COLORWAY[8],
            showlegend=False,
        ),
        row=1,
        col=1,
        secondary_y=True,
    )

    for i in range(6):
        fig.add_trace(
            go.Scatter(
                name=fibs[i],
                x=[min_date, max_date],
                y=[levels[i], levels[i]],
                opacity=0.2,
                mode="lines",
                line_color=imps.PLT_FIB_COLORWAY[i],
                showlegend=False,
            ),
            row=1,
            col=1,
            secondary_y=True,
        )
        fig.add_trace(
            go.Scatter(
                name=fibs[i + 1],
                x=[min_date, max_date],
                y=[levels[i + 1], levels[i + 1]],
                opacity=0.2,
                mode="lines",
                fill="tonexty",
                line_color=imps.PLT_FIB_COLORWAY[i + 1],
                showlegend=False,
            ),
            row=1,
            col=1,
            secondary_y=True,
        )

    for i in range(7):
        fig.add_trace(
            go.Scatter(
                name=fibs[i],
                x=[min_date],
                y=[levels[i]],
                opacity=0.9,
                mode="text",
                text=fibs[i],
                textposition=f"middle {lvl_text}"
                if i != 5 else f"bottom {lvl_text}",
                textfont=dict(imps.PLT_FIB_COLORWAY[7],
                              color=imps.PLT_FIB_COLORWAY[i]),
                showlegend=False,
            ),
            row=1,
            col=1,
            secondary_y=True,
        )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        title=title,
        title_x=0.02,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_fib.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )
    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Fibonacci-Retracement-Levels {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #2
0
def macd_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    fast="12",
    slow="26",
    signal="9",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with moving average convergence/divergence [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta macd %s %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            fast,
            slow,
            signal,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    if not fast.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    fast = int(fast)
    if not slow.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    slow = int(slow)
    if not signal.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    signal = int(signal)

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    ta_data = momentum_model.macd(df_stock["Adj Close"], fast, slow, signal)
    df_ta = df_ta.join(ta_data)

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.4, 0.6],
        specs=[[{"secondary_y": True}], [{"secondary_y": False}]],
    )
    title = f"<b>{plot['plt_title']} MACD {fast} {slow} {signal}</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Bar(
            name="MACD Histogram",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            opacity=(plot["bar_opacity"] + 0.3),
            marker_color="#d81aea",
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            name="MACD Line",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            opacity=0.8,
            line=dict(color="#00e6c3"),
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            name="Signal Line",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 2)].values,
            opacity=1,
            line=dict(color="#9467bd"),
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.02,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_macd.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Moving-Average-Convergence-Divergence {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #3
0
def stoch_command(
    ticker: str = "",
    interval: int = 15,
    past_days: int = 0,
    fast_k="14",
    slow_d="3",
    slow_k="4",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with stochastic relative strength average [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        logger.debug(
            "ta stoch %s %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            fast_k,
            slow_k,
            slow_d,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    if not fast_k.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    fast_k = int(fast_k)
    if not slow_k.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    slow_k = int(slow_k)
    if not slow_d.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    slow_d = int(slow_d)

    # 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,
        heikin_candles=heikin_candles,
    )

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    df_ta = df_ta.join(
        momentum_model.stoch(
            df_stock["High"],
            df_stock["Low"],
            df_stock["Adj Close"],
            fast_k,
            slow_d,
            slow_k,
        ))

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.4, 0.6],
        specs=[[{
            "secondary_y": True
        }], [{
            "secondary_y": False
        }]],
    )
    title = f"<b>{plot['plt_title']} STOCH RSI</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Scatter(
            name=f"%K {fast_k}, {slow_d}, {slow_k}",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            line=dict(width=1.8),
            mode="lines",
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            name=f"%D {fast_k}, {slow_d}, {slow_k}",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            line=dict(width=1.8, dash="dash"),
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.add_hrect(
        y0=80,
        y1=100,
        fillcolor="red",
        opacity=0.2,
        layer="below",
        line_width=0,
        row=2,
        col=1,
    )
    fig.add_hrect(
        y0=0,
        y1=20,
        fillcolor="green",
        opacity=0.2,
        layer="below",
        line_width=0,
        row=2,
        col=1,
    )
    fig.add_hline(
        y=80,
        fillcolor="green",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="red", dash="dash"),
        row=2,
        col=1,
    )
    fig.add_hline(
        y=20,
        fillcolor="green",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="green", dash="dash"),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.01,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_stoch.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )
    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title":
        f"Stocks: Stochastic-Relative-Strength-Index {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #4
0
def adx_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    length="14",
    scalar="100",
    drift="1",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with average directional movement index [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta adx %s %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            length,
            scalar,
            drift,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    if not length.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    length = float(length)
    if not scalar.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    scalar = float(scalar)
    if not drift.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    drift = float(drift)

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    ta_data = trend_indicators_model.adx(
        df_stock["High"],
        df_stock["Low"],
        df_stock["Adj Close"],
        length,
        scalar,
        drift,
    )
    df_ta = df_ta.join(ta_data)

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.4, 0.6],
        specs=[[{
            "secondary_y": True
        }], [{
            "secondary_y": False
        }]],
    )
    title = f"<b>{plot['plt_title']} Average Directional Movement Index</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Scatter(
            name=f"ADX ({length})",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            opacity=1,
            line=dict(width=2),
        ),
        secondary_y=False,
        row=2,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            name=f"+DI ({length})",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            opacity=1,
            line=dict(width=1),
        ),
        secondary_y=False,
        row=2,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            name=f"-DI ({length})",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 2)].values,
            opacity=1,
            line=dict(width=1),
        ),
        secondary_y=False,
        row=2,
        col=1,
    )
    fig.add_hline(
        y=25,
        fillcolor="grey",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="grey", dash="dash"),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.01,
        title_font_size=12,
        dragmode="pan",
    )
    imagefile = "ta_adx.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title":
        f"Stocks: Average-Directional-Movement-Index {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #5
0
def aroon_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    length="25",
    scalar="100",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with aroon indicator [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        logger.debug(
            "ta aroon %s %s %s %s %s, %s, %s, %s, %s, %s",
            ticker,
            interval,
            past_days,
            length,
            scalar,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    if not length.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    length = int(length)
    if not scalar.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    scalar = float(scalar)

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
    df_ta = df_ta.join(
        trend_indicators_model.aroon(df_ta["High"], df_ta["Low"], length,
                                     scalar))

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=3,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.02,
        row_width=[0.2, 0.2, 0.3],
        specs=[
            [{
                "secondary_y": True
            }],
            [{
                "secondary_y": False
            }],
            [{
                "secondary_y": False
            }],
        ],
    )
    title = f"<b>{plot['plt_title']} Aroon ({length})</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Scatter(
            name="Aroon DOWN",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            opacity=1,
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            name="Aroon UP",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            opacity=1,
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_trace(
        go.Scatter(
            name="Aroon OSC",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 2)].values,
            opacity=1,
        ),
        row=3,
        col=1,
        secondary_y=False,
    )
    fig.add_hline(
        y=50,
        fillcolor="grey",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="grey", dash="dash"),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.1,
        title_font_size=14,
        dragmode="pan",
        yaxis=dict(nticks=10),
        yaxis2=dict(nticks=10),
    )
    imagefile = "ta_aroon.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )
    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Aroon-Indicator {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #6
0
def kc_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    length="20",
    scalar="2",
    ma_mode="sma",
    offset="0",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with keltner channel [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta kc %s %s %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            length,
            scalar,
            ma_mode,
            offset,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if not length.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    length = int(length)
    if not scalar.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    scalar = float(scalar)
    if not offset.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    offset = float(offset)

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    ta_data = volatility_model.kc(
        df_stock["High"],
        df_stock["Low"],
        df_stock["Adj Close"],
        length,
        scalar,
        ma_mode,
        offset,
    )
    df_ta = df_ta.join(ta_data)

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        shared_xaxes=True,
        vertical_spacing=0.07,
    )
    title = f"<b>{plot['plt_title']} Keltner Channels ({ma_mode.upper()})</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Scatter(
            name="upper",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 2)].values,
            opacity=1,
            mode="lines",
            line_color="indigo",
            showlegend=False,
        ),
        row=1,
        col=1,
        secondary_y=True,
    )
    fig.add_trace(
        go.Scatter(
            name="lower",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            opacity=1,
            mode="lines",
            line_color="indigo",
            fill="tonexty",
            fillcolor="rgba(74, 0, 128, 0.2)",
            showlegend=False,
        ),
        row=1,
        col=1,
        secondary_y=True,
    )
    fig.add_trace(
        go.Scatter(
            name="mid",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            opacity=1,
            line=dict(
                width=1.5,
                dash="dash",
            ),
            showlegend=False,
        ),
        row=1,
        col=1,
        secondary_y=True,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.02,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_kc.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )
    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Keltner-Channel {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #7
0
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,
    }
Пример #8
0
def rsi_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    length="14",
    scalar="100",
    drift="1",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with relative strength index [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta rsi %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            length,
            scalar,
            drift,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    if not length.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    length = int(length)
    if not scalar.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    scalar = float(scalar)
    if not drift.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    drift = int(drift)

    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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
    df_ta = df_ta.join(momentum_model.rsi(df_ta["Adj Close"], length, scalar, drift))

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.5, 0.6],
        specs=[
            [{"secondary_y": True}],
            [{"secondary_y": False}],
        ],
    )
    title = f"<b>{plot['plt_title']} RSI</b>"
    fig = plot["fig"]

    fig.add_trace(
        go.Scatter(
            name=f"RSI {length}",
            mode="lines",
            x=df_ta.index,
            y=df_ta.iloc[:, 6].values if interval != 1440 else df_ta.iloc[:, 11].values,
            opacity=1,
        ),
        row=2,
        col=1,
        secondary_y=False,
    )
    fig.add_hrect(
        y0=70,
        y1=100,
        fillcolor="red",
        opacity=0.2,
        layer="below",
        line_width=0,
        row=2,
        col=1,
    )
    fig.add_hrect(
        y0=0,
        y1=30,
        fillcolor="green",
        opacity=0.2,
        layer="below",
        line_width=0,
        row=2,
        col=1,
    )
    fig.add_hline(
        y=70,
        fillcolor="green",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="red", dash="dash"),
        row=2,
        col=1,
    )
    fig.add_hline(
        y=30,
        fillcolor="green",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="green", dash="dash"),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.1,
        title_font_size=14,
        dragmode="pan",
        yaxis=dict(nticks=15),
        yaxis2=dict(nticks=10),
    )
    imagefile = "ta_rsi.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Relative-Strength-Index {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #9
0
def bbands_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    length="20",
    n_std: float = 2.0,
    ma_mode="sma",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with bollinger bands [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta bbands %s %s %s %s %s %s %s %s %s %s",
            ticker,
            past_days,
            length,
            n_std,
            ma_mode,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    possible_ma = [
        "dema",
        "ema",
        "fwma",
        "hma",
        "linreg",
        "midpoint",
        "pwma",
        "rma",
        "sinwma",
        "sma",
        "swma",
        "t3",
        "tema",
        "trima",
        "vidya",
        "wma",
        "zlma",
    ]

    if ticker == "":
        raise Exception("Stock ticker is required")

    if not length.lstrip("-").isnumeric():
        raise Exception("Number has to be an integer")
    ta_length = float(length)
    n_std = float(n_std)

    if ma_mode not in possible_ma:
        raise Exception("Invalid ma entered")

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
    df_ta = df_ta.join(
        volatility_model.bbands(df_ta["Adj Close"], ta_length, n_std, ma_mode))

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(df_ta, ticker, interval, extended_hours,
                                  news)
    title = f"<b>{plot['plt_title']} Bollinger Bands ({ma_mode.upper()})</b>"
    fig = plot["fig"]
    idx = 6 if interval != 1440 else 11

    fig.add_trace(
        go.Scatter(
            name=f"BBU_{length}_{n_std}",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 2)].values,
            opacity=1,
            mode="lines",
            line_color="indigo",
        ),
        secondary_y=True,
        row=1,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            name=f"BBL_{length}_{n_std}",
            x=df_ta.index,
            y=df_ta.iloc[:, idx].values,
            opacity=1,
            mode="lines",
            line_color="indigo",
            fill="tonexty",
            fillcolor="rgba(74, 0, 128, 0.2)",
        ),
        secondary_y=True,
        row=1,
        col=1,
    )
    fig.add_trace(
        go.Scatter(
            name=f"BBM_{length}_{n_std}",
            x=df_ta.index,
            y=df_ta.iloc[:, (idx + 1)].values,
            opacity=1,
            line=dict(
                width=1.5,
                dash="dash",
            ),
        ),
        secondary_y=True,
        row=1,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.1,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_bbands.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Bollinger-Bands {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #10
0
def ad_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    is_open: bool = False,
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with accumulation/distribution line [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta ad %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            is_open,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]
    df_ta = df_ta.join(volume_model.ad(df_stock, is_open))

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.4, 0.6],
        specs=[
            [{
                "secondary_y": True
            }],
            [{
                "secondary_y": False
            }],
        ],
    )
    title = f"<b>{plot['plt_title']} A/D</b>"
    fig = plot["fig"]

    fig.add_trace(
        go.Scatter(
            name="A/D",
            x=df_ta.index,
            y=df_ta.iloc[:, 6].values
            if interval != 1440 else df_ta.iloc[:, 11].values,
            mode="lines",
            line=dict(width=2),
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.add_hline(
        y=0,
        fillcolor="grey",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="grey", dash="dash"),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.1,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_ad.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Accumulation/Distribution Line {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #11
0
def ma_command(
    ticker="",
    interval: int = 15,
    past_days: int = 0,
    ma_mode="ema",
    window="",
    offset: int = 0,
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with selected Moving Average  [Yahoo Finance]"""
    # Debug
    if imps.DEBUG:
        # pylint: disable=logging-too-many-args
        logger.debug(
            "ta ma %s %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            ma_mode,
            window,
            offset,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    overlap_ma = {
        "ema": overlap_model.ema,
        "hma": overlap_model.hma,
        "sma": overlap_model.sma,
        "wma": overlap_model.wma,
        "zlma": overlap_model.zlma,
    }

    if ticker == "":
        raise Exception("Stock ticker is required")

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    if window == "":
        window = [20, 50]
    else:
        window_temp = list()
        for wind in window.split(","):
            try:
                window_temp.append(int(wind))
            except Exception as e:
                raise Exception("Window needs to be a float") from e
        window = window_temp

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    for win in window:
        ema_data = overlap_ma[ma_mode](values=df_ta["Adj Close"],
                                       length=win,
                                       offset=offset)
        df_ta = df_ta.join(ema_data)

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
    )
    title = f"<b>{plot['plt_title']} Moving Average ({ma_mode.upper()})</b>"
    fig = plot["fig"]

    i2 = 6 if interval != 1440 else 11
    for i in range(i2, df_ta.shape[1]):
        fig.add_trace(
            go.Scatter(
                name=f"{df_ta.iloc[:, i].name}",
                mode="lines",
                x=df_ta.index,
                y=df_ta.iloc[:, i].values,
                opacity=1,
            ),
            secondary_y=True,
            row=1,
            col=1,
        )

    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.1,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_ma.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )
    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Moving Average {ma_mode.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }
Пример #12
0
def cci_command(
    ticker: str = "",
    interval: int = 15,
    past_days: int = 0,
    length="14",
    scalar="0.015",
    start="",
    end="",
    extended_hours: bool = False,
    heikin_candles: bool = False,
    news: bool = False,
):
    """Displays chart with commodity channel index [Yahoo Finance]"""

    # Debug
    if imps.DEBUG:
        logger.debug(
            "ta cci %s %s %s %s %s %s %s %s %s %s",
            ticker,
            interval,
            past_days,
            length,
            scalar,
            start,
            end,
            extended_hours,
            heikin_candles,
            news,
        )

    # Check for argument
    if ticker == "":
        raise Exception("Stock ticker is required")

    # 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,
        heikin_candles=heikin_candles,
    )

    if df_stock.empty:
        raise Exception("No Data Found")

    # pylint
    try:
        length = int(length)
    except ValueError as e:
        raise Exception("Length has to be an integer") from e
    try:
        scalar = float(scalar)
    except ValueError as e:
        raise Exception("Scalar has to be an integer") from e

    df_ta = df_stock.loc[(df_stock.index >= start) & (df_stock.index < end)]

    if df_ta.empty:
        raise Exception("No Data Found")

    ta_data = momentum_model.cci(
        df_ta["High"], df_ta["Low"], df_ta["Adj Close"], length, scalar
    )
    df_ta = df_ta.join(ta_data)

    # Output Data
    if interval != 1440:
        df_ta = df_ta.loc[(df_ta.index >= bar_start) & (df_ta.index < end)]
    df_ta = df_ta.fillna(0.0)

    plot = load_candle.candle_fig(
        df_ta,
        ticker,
        interval,
        extended_hours,
        news,
        bar=bar_start,
        int_bar=interval,
        rows=2,
        cols=1,
        shared_xaxes=True,
        vertical_spacing=0.07,
        row_width=[0.4, 0.6],
        specs=[[{"secondary_y": True}], [{"secondary_y": False}]],
    )
    title = f"<b>{plot['plt_title']} Commodity-Channel-Index</b>"
    fig = plot["fig"]
    ta_values = (
        df_ta.iloc[:, 6].values if interval != 1440 else df_ta.iloc[:, 11].values
    )

    dmin = ta_values.min()
    dmax = ta_values.max()

    fig.add_trace(
        go.Scatter(
            name=f"CCI  ({length})  ({scalar})",
            mode="lines",
            x=df_ta.index,
            y=ta_values,
            opacity=1,
        ),
        row=2,
        col=1,
    )
    fig.add_hrect(
        y0=100,
        y1=dmax,
        fillcolor="red",
        opacity=0.2,
        layer="below",
        line_width=0,
        row=2,
        col=1,
    )
    fig.add_hrect(
        y0=-100,
        y1=dmin,
        fillcolor="green",
        opacity=0.2,
        layer="below",
        line_width=0,
        row=2,
        col=1,
    )
    fig.add_hline(
        y=-100,
        fillcolor="green",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="green", dash="dash"),
        row=2,
        col=1,
    )
    fig.add_hline(
        y=100,
        fillcolor="red",
        opacity=1,
        layer="below",
        line_width=3,
        line=dict(color="red", dash="dash"),
        row=2,
        col=1,
    )
    fig.update_layout(
        margin=dict(l=0, r=0, t=50, b=20),
        template=imps.PLT_TA_STYLE_TEMPLATE,
        colorway=imps.PLT_TA_COLORWAY,
        title=title,
        title_x=0.02,
        title_font_size=14,
        dragmode="pan",
    )
    imagefile = "ta_cci.png"

    # Check if interactive settings are enabled
    plt_link = ""
    if imps.INTERACTIVE:
        plt_link = imps.inter_chart(fig, imagefile, callback=False)

    fig.update_layout(
        width=800,
        height=500,
    )

    imagefile = imps.image_border(imagefile, fig=fig)

    return {
        "title": f"Stocks: Commodity-Channel-Index {ticker.upper()}",
        "description": plt_link,
        "imagefile": imagefile,
    }