# -*- coding: utf-8 -*-
__company__ = ''
__project__ = 'Observatory News - Final Project'
__author__ = 'Strauss'
__intial__ = '2023-08-07'

import sys
import os
import pandas as pd
import streamlit as st
from database.data import Data
from utils.graphs import Altair
from database.data import Data
import glob
from datasets import load_dataset

sys.path.append(os.path.dirname(os.getcwd()))

## Label Metrics Size
st.markdown("""<style>[data-testid="stMetricValue"] {font-size: 20px;}</style>""", unsafe_allow_html=True,)

data = Data()


def load_ds(media):
    dir = '{0}/{1}'.format(data.pth_data, media)
    st.info(dir)
    files = glob.glob(dir + '/*.csv')
    df_list = (pd.read_csv(file) for file in files)
    st.info(files)
    df = pd.concat(df_list, ignore_index=True)
    st.info('Loaded {0} rows and {1} columns'.format(df.shape[0], df.shape[1]))
    return df

def load_hugging_face_ds(media):

    # If the dataset is gated/private, make sure you have run huggingface-cli login
    dataset = load_dataset("strauss-oak/observatory-brazilian-news")

    dir = '{0}{1}/202101.csv'.format(data.pth_data, media)
    st.info(dir)
    dataset = load_dataset('csv', data_files=[dir], delimiter=',')
    return dataset


c1 = st.container()
with c1:
    #col1, col2 = st.columns(2)
    #df_news = load_ds('jpan')
    #st.dataframe(df_news)

    #df_news = load_ds('globo')
    #st.dataframe(df_news)

    #ds = load_hugging_face_ds('jpan')
    #st.dataframe(ds)

    #df = load_ds('jpan')
    #st.dataframe(df)

    #dataset = load_dataset("strauss-oak/observatory-brazilian-news")

    #df = pd.DataFrame.from_dict(dataset["train"])
    #st.dataframe(df)

    from huggingface_hub import login

    access_token = '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'

    login(access_token)


    dataset = load_dataset("strauss-oak/observatory-brazilian-news", token=True)

    st.dataframe(dataset)

    df = pd.DataFrame.from_dict(dataset["train"])
    st.dataframe(df)