from os.path import dirname, join

import numpy as np
import pandas.io.sql as psql
import sqlite3 as sql

from bokeh.plotting import Figure
from bokeh.models import ColumnDataSource, HoverTool, HBox, VBoxForm
from bokeh.models.widgets import Slider, Select, TextInput
from bokeh.io import curdoc
from bokeh.sampledata.movies_data import movie_path

conn = sql.connect(movie_path)
query = open(join(dirname(__file__), 'query.sql')).read()
movies = psql.read_sql(query, conn)

movies["color"] = np.where(movies["Oscars"] > 0, "orange", "grey")
movies["alpha"] = np.where(movies["Oscars"] > 0, 0.9, 0.25)
movies.fillna(0, inplace=True)  # just replace missing values with zero
movies["revenue"] = movies.BoxOffice.apply(lambda x: '{:,d}'.format(int(x)))

with open(join(dirname(__file__), "razzies-clean.csv")) as f:
    razzies = f.read().splitlines()
movies.loc[movies.imdbID.isin(razzies), "color"] = "purple"
movies.loc[movies.imdbID.isin(razzies), "alpha"] = 0.9

axis_map = {
    "Tomato Meter": "Meter",
    "Numeric Rating": "numericRating",
    "Number of Reviews": "Reviews",
    "Box Office (dollars)": "BoxOffice",
    "Length (minutes)": "Runtime",
    "Year": "Year",
}

# Create Input controls
reviews = Slider(title="Minimum number of reviews", value=80, start=10, end=300, step=10)
min_year = Slider(title="Year released", start=1940, end=2014, value=1970, step=1)
max_year = Slider(title="End Year released", start=1940, end=2014, value=2014, step=1)
oscars = Slider(title="Minimum number of Oscar wins", start=0, end=4, value=0, step=1)
boxoffice = Slider(title="Dollars at Box Office (millions)", start=0, end=800, value=0, step=1)
genre = Select(title="Genre", value="All",
               options=open(join(dirname(__file__), 'genres.txt')).read().split())
director = TextInput(title="Director name contains")
cast = TextInput(title="Cast names contains")
x_axis = Select(title="X Axis", options=sorted(axis_map.keys()), value="Tomato Meter")
y_axis = Select(title="Y Axis", options=sorted(axis_map.keys()), value="Number of Reviews")

# Create Column Data Source that will be used by the plot
source = ColumnDataSource(data=dict(x=[], y=[], color=[], title=[], year=[], revenue=[]))

hover = HoverTool(tooltips=[
    ("Title","@title"),
    ("Year", "@year"),
    ("$", "@revenue")
])

p = Figure(plot_height=600, plot_width=800, title="", toolbar_location=None, tools=[hover])
p.circle(x="x", y="y", source=source, size=7, color="color", line_color=None, fill_alpha="alpha")

def select_movies():
    genre_val = genre.value
    director_val = director.value.strip()
    cast_val = cast.value.strip()
    selected = movies[
        (movies.Reviews >= reviews.value) &
        (movies.BoxOffice >= (boxoffice.value * 1e6)) &
        (movies.Year >= min_year.value) &
        (movies.Year <= max_year.value) &
        (movies.Oscars >= oscars.value)
    ]
    if (genre_val != "All"):
        selected = selected[selected.Genre.str.contains(genre_val)==True]
    if (director_val != ""):
        selected = selected[selected.Director.str.contains(director_val)==True]
    if (cast_val != ""):
        selected = selected[selected.Cast.str.contains(cast_val)==True]
    return selected

def update(attrname, old, new):
    df = select_movies()
    x_name = axis_map[x_axis.value]
    y_name = axis_map[y_axis.value]

    p.xaxis.axis_label = x_axis.value
    p.yaxis.axis_label = y_axis.value
    p.title = "%d movies selected" % len(df)
    source.data = dict(
        x=df[x_name],
        y=df[y_name],
        color=df["color"],
        title=df["Title"],
        year=df["Year"],
        revenue=df["revenue"],
        alpha=df["alpha"],
    )

controls = [reviews, boxoffice, genre, min_year, max_year, oscars, director, cast, x_axis, y_axis]
for control in controls:
    control.on_change('value', update)

inputs = HBox(VBoxForm(*controls), width=300)

update(None, None, None) # initial load of the data

curdoc().add_root(HBox(inputs, p, width=1100))
