parse_contents.py

# -*- coding: utf-8 -*-
"""
Created on Thu Aug 23 10:54:31 2018
@author: Aveedibya Dey
"""
import dash_table_experiments as dte

import base64
import datetime
import io

import dash
from dash.dependencies import Input, Output
import dash_core_components as dcc
import dash_html_components as html

import pandas as pd

def parse_contents(contents, filename, date):
    content_type, content_string = contents.split(',')

    decoded = base64.b64decode(content_string)
    try:
        if 'csv' in filename:
            # Assume that the user uploaded a CSV file
            df = pd.read_csv(
                io.StringIO(decoded.decode('utf-8'))).dropna()
        elif 'xls' in filename:
            # Assume that the user uploaded an excel file
            df = pd.read_excel(io.BytesIO(decoded)).dropna()
    except Exception as e:
        print(e)
        return html.Div([
            'There was an error processing this file.'
        ])

    return html.Div([
        html.Label('File Uploaded: ' + filename + ' on: ' + str(datetime.datetime.fromtimestamp(date))),
        #html.H6(datetime.datetime.fromtimestamp(date)),

        # Use the DataTable prototype component:
        # github.com/plotly/dash-table-experiments
        dte.DataTable(rows=df.to_dict('records')),

        html.Hr(),  # horizontal line

        # For debugging, display the raw contents provided by the web browser
        html.Div('Raw Content'),
        html.Pre(contents[0:200] + '...', style={
            'whiteSpace': 'pre-wrap',
            'wordBreak': 'break-all'
        })
    ]), df.dropna().to_json(date_format='iso', orient='split')
    
def parse_contents_to_df(contents, filename, date):
    content_type, content_string = contents.split(',')
    decoded = base64.b64decode(content_string)
    try:
        if 'csv' in filename:
            # Assume that the user uploaded a CSV file
            df = pd.read_csv(
                io.StringIO(decoded.decode('utf-8')))
        elif 'xls' in filename:
            # Assume that the user uploaded an excel file
            df = pd.read_excel(io.BytesIO(decoded))
    except Exception as e:
        print(e)
    print(df.tail())
    return df