from PIL import Image
import json
import streamlit as st


def load_image_from_local(image_path, image_resize=None):
	image = Image.open(image_path)

	if isinstance(image_resize, tuple):
		image = image.resize(image_resize)
	return image


# # reading the nct_ta dictionary
# with open('asset/data/input_sentence.json') as f:
# 	data = f.read()
# sample_sentences = json.loads(data)  # load dict
# print(sample_sentences)

def unique_list(seq):
    seen = set()
    seen_add = seen.add
    return [x for x in seq if not (x in seen or seen_add(x))]


def pure_comma_separation(list_str, return_list=True):
	r = unique_list([item.strip() for item in list_str.lower().split(",") if item.strip()])
	if return_list:
		return r
	return ", ".join(r)



def local_css(css_path):
    with open(css_path) as f:
        st.markdown(f'<style>{f.read()}</style>', unsafe_allow_html=True)


def remote_css(css_url):
    st.markdown(f'<link href="{css_url}" rel="stylesheet">', unsafe_allow_html=True)
    
"""Basic utilities module"""
import requests
import csv
import re


def request_ct(url):
    """Performs a get request that provides a (somewhat) useful error message."""
    try:
        response = requests.get(url)
    except ImportError:
        raise ImportError(
            "Couldn't retrieve the data, check your search expression or try again later."
        )
    else:
        return response


def json_handler(url):
    """Returns request in JSON (dict) format"""
    return request_ct(url).json()


def csv_handler(url):
    """Returns request in CSV (list of records) format"""

    response = request_ct(url)
    decoded_content = response.content.decode("utf-8")

    split_by_blank = re.split(r"\n\s*\n", decoded_content)  # Extracts header info
    cr = csv.reader(split_by_blank[1].splitlines(), delimiter=",")
    records = list(cr)

    return records