"""
Ashley Wu 
Processes data for app
"""

import pandas as pd
import numpy as np
import gradio as gr
import datetime
import utils


#TODO: Add data preview and also do some output shenanigans, but that can wait for a little bit 
def process_csv(file):
    """
    Create and clean dataframe 
    
    Args:
        file: The uploaded file object from Gradio
    
    Returns:
        A pandas DataFrame to display in Gradio
    """

    if file is None:
        return "No file uploaded"
    
    try:
        # Read the CSV file
        df = pd.read_csv(file.name)

        # Detect Null values
        null_data = df.isnull().sum()
        if df.isnull().values.any():
            gr.Warning("Null data detected! Removing rows with null values", duration=5)
            df = df.dropna()
        df_basics = f"The shape of this dataframe is {str(df.shape)} \n {df.describe()} \n Null data: \n {null_data}"
        
        # Return the dataframe for display
        return df, df_basics 
    except Exception as e:
        raise gr.Error(f"Error reading CSV: {str(e)}", duration=10)



def save_csv(dataframe):
    """
    Save the modified dataframe to a CSV file.
    
    Args:
        dataframe: The modified pandas DataFrame
    
    Returns:
        Path to the saved CSV file
    """
    if dataframe is None:
        return None
    
    output_path = "modified_data.csv"
    dataframe.to_csv(output_path, index=False)
    return output_path


def set_max(max_value, df, column):
    """
    Docstring for update_max
    
    :param df: Description
    :param max_value: Description
    """
    filtered_df = df[df[column] < max_value]
    
    return filtered_df

def set_min(min_value, df, column):
    """
    Docstring for update_max
    
    :param df: Description
    :param max_value: Description
    """
    filtered_df = df[df[column] > min_value]
    
    return filtered_df


def set_categories(removals, df, column):
    """
    Removes the selected element's row from the dataframe 
    
    Args: 
        removals: list of elements to be removed
        df: dataframe
        column: selected column to find values of
    """
    df = utils.detect_categories(df) 

    for row in removals: 
        df = df[df[column] != row]

    return df

def submit_dates(df, max_date, min_date, column):
    """
    Filters all dates larger than the max_date and lower than the min_date
    
    Args: 
        max_date: maximum date
        df: dataframe 
        column: column of dataframe to filter

    Returns: 
        filtered_df: filtered dataframe
    """ 
    df = utils.detect_dates(df)
    filtered_df = df

    try:
        if max_date is not None: 
            filtered_df = filtered_df[filtered_df[column] <= max_date]
        if min_date is not None:
            filtered_df = filtered_df[filtered_df[column] >= min_date]
    except:
        raise gr.Error("The max date is not in the correct format", duration=1) 
    
    return filtered_df