"""
Ashley Wu 
Creates visualizations for app
"""
import gradio as gr
from datetime import datetime
import pandas as pd
def update_dropdown(df):
    """
    Updates the dropdown with the columns of the dataframe in question 
    
    Args:
        df: dataframe
            the dataframe in question
    Returns: 
        gr.update
            Gradio update object to dropdown 

    """
    columns = df.columns.tolist()
    return gr.update(choices=columns)


def update_filter_block(df, column_title):
    """
    Chooses whick blocks to hide and show based off of column dtype
    
    Args: 
    df: dataframe
        dataframe in question 
    column_title: string 
        title of the column

    returns:
        gr.update: gr.update
            an update to the visibility of the max number textbox
        gr.update: gr.update
            an update to the visibility of the min number textbox
        gr.update: gr.update
            an update to the visibility of the category checklist
        gr.update: gr.update
            an update to the visibility of the max date selector
        gr.update: gr.update
            an update to the visibility of the min date selector
        string: string
            a string update incase use selects a dtype that does not have a filter
    """

    df = detect_categories(df)
    df = detect_dates(df)

    dtype = df[column_title].dtype

    max_num = False
    min_num = False
    category = False
    max_date = False
    min_date = False
    

    if dtype.kind == 'i' or dtype.kind == 'f' or dtype.kind == 'u' or dtype.kind == 'c':
        max_num = True
        min_num = True
    elif dtype.name == 'category':
        category = True
    elif dtype.kind == 'M' or dtype.kinda == 'm':
        max_date = True
        min_date = True
    else: 
        raise gr.Warning('selected column is not a filterable type!', duration=5)
        
    return gr.update(visible=max_num), gr.update(visible=min_num), gr.update(visible=category), gr.update(visible=max_date), gr.update(visible=min_date)



def apply_filter(df):
    """
    Docstring for apply_filter
    
    :param df: Description
    """

    return df

def detect_categories(df):
    """
    Detects whether or not there are categories in a string column

    Args: 
        df: dataframe 
    Returns:
        df: dataframe
    """
    
    for column in df.columns: 
        unique = df[column].nunique()
        if unique < 100 and df[column].dtype == 'object': 
            df[column] = df[column].astype('category')
    
    return df

def populate_categories(df, column): 
    """
    Populate categories of an element 
    
    Args: 
        df: dataframe 
        column: column to get categories for 
    Returns: 
        list of strings: list of categories in column 
    """

    list = df[column].unique().tolist()
    return gr.update(choices=list)

def change_slider(df, col):

    if df[col].dtype.name == 'object':
        raise gr.Error("The column can not be a category!")
    max_val = df[col].max()
    min_val = df[col].min()

    return gr.update(maximum=max_val, minimum=min_val, step=1)

def count_rows(df):
    """
    Return the row count of the dataframe 
    
    Args: 
        df: dataframe 
    Returns: 
        int: # of the rows of the dataframe
    """
    return df.shape[0]


def detect_dates(df):
    """
    Checks every column for date values, if a column with dates is found, then sets that column dtype to a date value
    
    Args: 
        df: dataframe
    Returns: 
        df: dataframe
    """
    formats = [
        '%Y-%m-%d',      
        '%m/%d/%Y',      
        '%d/%m/%Y',      
        '%Y/%m/%d',      
        '%d-%m-%Y',      
        '%d.%m.%Y',      
    ]
    
    for column in df.columns: 
        for fmt in formats:
            try: 
                datetime.strptime(df[column].iloc[0], fmt)
                df[column] = pd.to_datetime(df[column])
                break
            except: 
                continue
    return df 

def download_chats(fig1, fig2, fig3, fig4):
    """
    Downloads all figures, if figure hasn't been generated, doesn't download
    
    Args: 
        fig1: bar chart 
        fig2: time series 
        fig3: histogram
        fig4: scatter plot
    """
    if fig1 is not None: 
        fig1.savefig("bar_chart.png")
    if fig2 is not None:
        fig2.savefig("time_series.png")
    if fig3 is not None: 
        fig3.savefig("histogram.png")
    if fig4 is not None: 
        fig4.savefig("scatter_plot.png")
    pass