import matplotlib.pyplot as plt
import matplotlib, io
import plotly.express as px
import plotly
from datetime import datetime


def generate_table(headers, data, title="", bg="skyblue", border="steelblue"):
    timestamp = datetime.now().strftime("%d/%m/%Y %H:%M:%S")

    font = {"family": "monospace", "weight": "normal", "size": 12}

    matplotlib.rc("font", **font)

    title_text = title
    footer_text = timestamp
    fig_background_color = bg
    fig_border = border

    column_headers = headers

    if data:
        cell_text = []
        for row in data:
            cell_text.append([x for x in row])
    else:
        cell_text = [["No Data"] + ["" for x in range(len(headers) - 1)]]

    # Create the figure. Setting a small pad on tight_layout
    # seems to better regulate white space. Sometimes experimenting
    # with an explicit figsize here can produce better outcome.

    dpi = 160
    # image_height = (( 0.5 + ( 0.4125 * ( len(data) + 1) ) ) * dpi)
    image_height = 100 + (67 * (len(data) + 1))
    image_width = 6 * dpi

    plt.figure(
        linewidth=2,
        edgecolor=fig_border,
        facecolor=fig_background_color,
        tight_layout={"pad": 1},
        dpi=dpi,
        figsize=(image_width / dpi, image_height / dpi),
    )

    # Add a table at the bottom of the axes
    the_table = plt.table(
        cellText=cell_text, colLabels=column_headers, loc="upper center"
    )

    # Scaling is the only influence we have over top and bottom cell padding.
    # Make the rows taller (i.e., make cell y scale larger).
    the_table.scale(1, 2)

    # Hide axes
    ax = plt.gca()
    ax.get_xaxis().set_visible(False)
    ax.get_yaxis().set_visible(False)

    # Hide axes border
    plt.box(on=None)

    # Add title
    plt.suptitle(title_text, x=0.5, y=((image_height - 15) / image_height))

    # Add footer
    plt.figtext(
        ((image_width - 15) / image_width),
        1 - ((image_height - 15) / image_height),
        footer_text,
        horizontalalignment="right",
        size=12,
        weight="light",
    )

    # Force the figure to update, so backends center objects correctly within the figure.
    # Without plt.draw() here, the title will center on the axes and not the figure.
    plt.draw()

    # Create image. plt.savefig ignores figure edge and face colors, so map them.
    image_buffer = io.BytesIO()
    plt.savefig(image_buffer, format="png")
    image_buffer.seek(0)
    return image_buffer


def generate_chart(ticker, history):
    fig = px.line(
        history,
        x=history.index,
        y="Open",
        title="{} Stock Prices".format(ticker),
        labels={"Open": "Price Per Share"},
    )

    img_bytes = plotly.io.to_image(fig, format="png")
    return io.BytesIO(img_bytes)