#
"""
This is a pre-processing step that generates Plotly figure templates for the
Bootstrap/Bootswatch themes that are available in the dash-bootstrap-components
library.  It's based on the dash-labs figure templates here:  https://github.com/plotly/dash-labs v0.4.0

This will be run periodically to refresh the templates if there are changes to Bootstrap themes.

Note: The Vizro Plotly templates are manually created and are not generated by this script.
They are directly sourced from: https://github.com/mckinsey/vizro/tree/main/vizro-core/src/vizro/_themes

"""

import pathlib
import json
import plotly.graph_objects as go
from plotly.utils import PlotlyJSONEncoder
import copy
import plotly.io as pio
import numpy as np
import dash_bootstrap_components as dbc


def patch_asscalar(a):
    """
    workaround for using deprecated asscalar in colormath
    https://github.com/gtaylor/python-colormath/issues/104
    """
    return a.item()

setattr(np, "asscalar", patch_asscalar)


# The following Bootstrap themes will be generated:
dbc_themes_url = {
    "BOOTSTRAP": dbc.themes.BOOTSTRAP,
    "CERULEAN": dbc.themes.CERULEAN,
    "COSMO": dbc.themes.COSMO,
    "FLATLY": dbc.themes.FLATLY,
    "JOURNAL": dbc.themes.JOURNAL,
    "LITERA": dbc.themes.LITERA,
    "LUMEN": dbc.themes.LUMEN,
    "LUX": dbc.themes.LUX,
    "MATERIA": dbc.themes.MATERIA,
    "MINTY": dbc.themes.MINTY,
    "PULSE": dbc.themes.PULSE,
    "SANDSTONE": dbc.themes.SANDSTONE,
    "SIMPLEX": dbc.themes.SIMPLEX,
    "SKETCHY": dbc.themes.SKETCHY,
    "SPACELAB": dbc.themes.SPACELAB,
    "UNITED": dbc.themes.UNITED,
    "YETI": dbc.themes.YETI,
    "CYBORG": dbc.themes.CYBORG,
    "DARKLY": dbc.themes.DARKLY,
    "SLATE": dbc.themes.SLATE,
    "SOLAR": dbc.themes.SOLAR,
    "SUPERHERO": dbc.themes.SUPERHERO,
    "QUARTZ": dbc.themes.QUARTZ,
    "MORPH": dbc.themes.MORPH,
    "VAPOR": dbc.themes.VAPOR,
    "ZEPHYR": dbc.themes.ZEPHYR,
}


"""
=====================================================================
_colors.py
"""


try:
    import spectra
    from colormath.density import auto_density
    from colormath.color_objects import LabColor as LabColor
    from colormath.color_diff import delta_e_cie1994
except ImportError:
    msg = (
        "Generating plotly.py figure templates from bootstrap theme files requires\n"
        "the optional spectra package, which can be installed using pip...\n"
        "    $ pip install spectra\n"
        "or conda...\n"
        "    $ conda install -c conda-forge spectra"
    )
    raise ValueError(msg)


white = spectra.lab(100, 0, 0)
black = spectra.lab(0, 0, 0)


def to_colormath(spectra_color):
    lab_values = spectra.html(spectra_color.hexcode).to("lab").values
    return LabColor(*lab_values)


def color_distance(clr1, clr2):
    return delta_e_cie1994(to_colormath(clr1), to_colormath(clr2))


# Distance matric
def color_distance_matrix(colors):
    return np.array(
        [
            [color_distance(c1, c2) for i, c1 in enumerate(colors)]
            for j, c2 in enumerate(colors)
        ],
        dtype="float32",
    )


def get_darkened_colors(colors, darkening_list):
    return [c.darken(d) for c, d in zip(colors, darkening_list)]


def best_darkening(c1, c2, c1_step=(1, 1), c2_step=(1, 1)):
    d = color_distance(c1, c2)
    d1 = color_distance(c1.darken(c1_step[1]), c2)
    dm1 = color_distance(c1.darken(c1_step[0]), c2)
    d2 = color_distance(c1, c2.darken(c2_step[1]))
    dm2 = color_distance(c1, c2.darken(c2_step[0]))

    # Return step with sign that increases distance most
    # Return 0 if either step lower distance
    return sorted(
        [
            (d, (0, 0)),
            (d1, (c1_step[1], 0)),
            (dm1, (c1_step[0], 0)),
            (d2, (0, c2_step[1])),
            (dm2, (0, c2_step[0])),
        ]
    )[-1]


def separate_colorway(html_colors):

    try:
        raw_colors = [
            spectra.rgb(*[c / 255 for c in to_rgb_tuple(clr)]) for clr in html_colors
        ]
    except ValueError:
        # Unable to parse colors as hex or rgb, return as-is
        return html_colors

    test_colors = [white] + raw_colors + [black]

    darkenings = list(np.zeros(len(test_colors)))
    threshold = 36

    max_shift = 16
    max_step = 16
    max_iterations = 4
    max_step_factor = 0.9

    iterations = 0
    distances = np.ones((len(html_colors) + 2, len(html_colors) + 2)) * np.nan

    while iterations < max_iterations:
        for i in range(len(test_colors) - 1):
            c1 = test_colors[i].darken(darkenings[i])
            for j in range(i + 1, len(test_colors)):
                c2 = test_colors[j].darken(darkenings[j])
                distance = color_distance(c1, c2)
                distances[i, j] = distance

                # When comparing to black and white,
                # skip if at least threshold units away
                if distance > threshold:
                    continue

                # Compute max step based on how close colors are
                this_step = max_step * ((100 - distance) / 100) ** 2

                # Clamp max steps based on how close we are to max shift allowances
                c1_step_up = max(0, min(this_step, max_shift - darkenings[i]))
                c2_step_up = max(0, min(this_step, max_shift - darkenings[j]))
                c1_step_down = min(0, max(-this_step, -darkenings[i] - max_shift))
                c2_step_down = min(0, max(-this_step, -darkenings[j] - max_shift))

                # Compute best way to lighten or darken ONE of the colors (not both)
                distance, (delta1, delta2) = best_darkening(
                    c1,
                    c2,
                    c1_step=(c1_step_down, c1_step_up),
                    c2_step=(c2_step_down, c2_step_up),
                )
                distances[i, j] = distance

                darkenings[i] += delta1
                darkenings[j] += delta2

        iterations += 1
        max_step *= max_step_factor

    result = [clr.hexcode for clr in get_darkened_colors(test_colors, darkenings)[1:-1]]

    return result


def hex_to_rgb(clr):
    clr = clr.lstrip("#")
    if len(clr) == 3:
        clr = "".join(c[0] * 2 for c in clr)
    return tuple(int(clr[i : i + 2], 16) for i in (0, 2, 4))


def to_rgb_tuple(color):
    from plotly.colors import unlabel_rgb

    if isinstance(color, tuple):
        pass
    elif color.startswith("#"):
        color = hex_to_rgb(color)
    else:
        color = unlabel_rgb(color)

    return tuple(int(c) for c in color)


def make_grid_color(bg_color, font_color, weight=0.1):
    bg_color = to_rgb_tuple(bg_color)
    font_color = to_rgb_tuple(font_color)

    s_bg_color = spectra.rgb(*[c / 255 for c in bg_color])
    s_font_color = spectra.rgb(*[c / 255 for c in font_color])
    return s_bg_color.blend(s_font_color, weight).hexcode


def maybe_blend(base_color, overlay_color):
    """
    Try to blend semi transparent overlay color on opaque
    base color. Return None if not successful
    """
    import re

    try:
        bc = spectra.html(base_color).to("rgb")
    except ValueError:
        return None

    try:
        # If overlay color is hex code or named color, it's
        # opaque, return as is
        return spectra.html(overlay_color).hexcode
    except ValueError:
        # Otherwise, it might be rgba
        pass

    rgba_match = re.match(r"rgba\(([^,]+),([^,]+),([^,]+),([^,]+)\)", overlay_color)
    if rgba_match is None:
        return None

    r, g, b, a = [float(n) for n in rgba_match.groups()]
    overlay_rgb = spectra.rgb(r / 255, g / 255, b / 255)
    blended = overlay_rgb.blend(bc, 1 - a)
    return blended.hexcode


"""
=====================================================================
From /templates/dbc.py
"""


def parse_rules_from_bootstrap_css(css_text, color_mode):
    import tinycss2

    tinycss_parsed = tinycss2.parse_stylesheet(css_text)

    # Build dict from css selectors to dict of css prop-values
    rule_props = {}
    for token in tinycss_parsed:
        if token.type != "qualified-rule":
            continue
        rule = token
        selector_str = "".join([t.serialize() for t in rule.prelude])
        selectors = tuple(s.strip() for s in selector_str.split(","))
        property_strings = [
            entry
            for entry in "".join([c.serialize().strip() for c in rule.content]).split(
                ";"
            )
            if entry
        ]

        property_pairs = [prop_str.split(":") for prop_str in property_strings]
        for selector in selectors:
            for prop_pair in property_pairs:
                if len(prop_pair) != 2:
                    continue
                rule_props.setdefault(selector, {})
                prop_key = prop_pair[0]
                prop_value = prop_pair[1].replace("!important", "").strip()
                rule_props[selector][prop_key] = prop_value

    if color_mode == "dark":
        try:
            rule_props[":root"].update(rule_props["[data-bs-theme=dark]"])
        except KeyError:
            pass

    return rule_props


# Get title font color
def get_font(rule_props):
    color = rule_props.get(":root", {}).get("--bs-body-color", "#000")
    family = rule_props.get(":root", {}).get("--bs-font-sans-serif", "sans-serif")
    return color, family


def get_role_colors(rule_props):
    # Initialize role_colors with default values
    role_colors = {
        "primary": "#007bff",
        "secondary": "#6c757d",
        "success": "#28a745",
        "info": "#17a2b8",
        "warning": "#ffc107",
        "danger": "#dc3545",
        "light": "#f8f9fa",
        "dark": "#343a40",
    }

    # Override with role colors for current theme
    for prop, val in rule_props[":root"].items():
        if prop.startswith("--bs-"):
            maybe_color = prop[5:]
            if maybe_color in role_colors:
                role_colors[maybe_color] = val

    return role_colors


def get_colorscale(color_a, color_b):

   # A range between 'primary' and 'warning'
    color1=spectra.html(color_a)
    color2=spectra.html(color_b).brighten(20)


    # A range of primary colors
    # color1 = spectra.html(color_a).brighten(-20)
    # color2 = spectra.html(color_a).brighten(40)

    scale = np.linspace(0, 1, 11)
    theme_swatches = spectra.range([color1, color2], 11)
    return [[k,v.hexcode] for k,v in zip(scale,theme_swatches)]


def get_template(bg_color):
    # spectra.lab(L, a, b)   L is lightness from 0 to 100
    lightness =spectra.html(bg_color).to("lab").values[0]
    if lightness < 50:
        return copy.deepcopy(pio.templates["plotly_dark"])
    else:
        return copy.deepcopy(pio.templates["plotly_white"])


def build_plotly_template_from_bootstrap_css_text(css_text, color_mode):

    # Parse css text
    rule_props = parse_rules_from_bootstrap_css(css_text, color_mode)

    # Initialize role_colors with default values
    role_colors = get_role_colors(rule_props)

    # Get font info
    font_color, font_family = get_font(rule_props)

    # Get background color
    plot_bgcolor = rule_props[":root"].get("--bs-body-bg", "#fff")
    paper_bgcolor = rule_props[".card"].get("--bs-card-bg", plot_bgcolor)

    # The morph theme's card background color does not look good as the paper_bgcolor in dark mode
    if "Theme: morph" in css_text:
        paper_bgcolor = plot_bgcolor

    blended = maybe_blend(plot_bgcolor, paper_bgcolor)
    if blended is None:
        # Can't blend, use background color for everything
        paper_bgcolor = plot_bgcolor
    else:
        paper_bgcolor = blended

    # Build colorway
    colorway_roles = [
        "primary",
        "danger",
        "success",
        "warning",
        "info",
    ]
    colorway = [role_colors[r] for r in colorway_roles]
    colorway = separate_colorway(colorway)


    colorscale = get_colorscale(role_colors["primary"], role_colors["danger"])

    # Build grid color
    gridcolor = make_grid_color(plot_bgcolor, font_color, 0.08)

    # Make template
    template = get_template(paper_bgcolor)

    layout = template.layout
    layout.colorway = colorway
    layout.colorscale.sequential = colorscale
    layout.piecolorway = colorway
    layout.paper_bgcolor = paper_bgcolor
    layout.plot_bgcolor = plot_bgcolor
    layout.font.color = font_color
    layout.font.family = font_family
    layout.xaxis.gridcolor = gridcolor
    layout.yaxis.gridcolor = gridcolor
    layout.xaxis.gridwidth = 0.5
    layout.yaxis.gridwidth = 0.5
    layout.xaxis.zerolinecolor = gridcolor
    layout.yaxis.zerolinecolor = gridcolor
    layout.geo.bgcolor = plot_bgcolor
    layout.geo.lakecolor = plot_bgcolor
    layout.geo.landcolor = plot_bgcolor
    layout.hoverlabel.font.family = font_family
    layout.annotationdefaults.font.color = font_color

    template.data.scatter = (go.Scatter(marker_line_color=plot_bgcolor),)
    template.data.scattergl = (go.Scattergl(marker_line_color=plot_bgcolor),)

    return template


def try_build_plotly_template_from_bootstrap_css_path(css_url, color_mode="light"):
    import requests
    from urllib.parse import urlparse

    parse_result = urlparse(css_url)
    if parse_result.scheme:
        # URL
        response = requests.get(css_url)
        if response.status_code != 200:
            return None
        css_text = response.content.decode("utf8")
    elif parse_result.path:
        # Local file
        with open(parse_result.path, "rt") as f:
            css_text = f.read()

    return build_plotly_template_from_bootstrap_css_text(css_text, color_mode)


"""
==========================================================
Generate Templates
"""

# set relative path
PATH = pathlib.Path(__file__).parent
TEMPLATES_PATH = PATH.joinpath("./src/dash_bootstrap_templates/templates").resolve()


# Creates all templates and save them as json files
print("Generating light templates...")

# light color mode
for theme, url in dbc_themes_url.items():
    dbc_template = try_build_plotly_template_from_bootstrap_css_path(url)
    with open(TEMPLATES_PATH.joinpath(f"{theme.lower()}.json"), "w") as f:
        json.dump(dbc_template, f, cls=PlotlyJSONEncoder)

print("Light Bootstrap figure templates saved as json files")
print("Generating dark templates...")


# dark color mode
for theme, url in dbc_themes_url.items():
    dbc_template = try_build_plotly_template_from_bootstrap_css_path(url, color_mode="dark")
    template_name = theme.lower() + "_dark.json"
    with open(TEMPLATES_PATH.joinpath(template_name), "w") as f:
        json.dump(dbc_template, f, cls=PlotlyJSONEncoder)

print("Dark Bootstrap figure templates saved as json files")