"""Streamlit app"""
from os.path import join, exists, dirname, abspath
from glob import glob

import numpy as np
import pandas as pd
import streamlit as st

import warnings
warnings.simplefilter(action='ignore')

curr_filepath = abspath(__file__)
repo_path = dirname(curr_filepath)


temporal_terms = [
    "then",
    "before",
    "after",
    "followed by",
    "preceded by",
    "approach",
]


def make_grid(cols,rows):
    grid = [0]*cols
    for i in range(cols):
        with st.container():
            grid[i] = st.columns(rows)
    return grid


if __name__ == "__main__":

    # Streamlit app code
    st.set_page_config(layout="wide")
    st.title("Clips from AudioCaps (possibly of temporal nature) 🎬")
    
    # load data
    if "df" not in st.session_state:
        splits = ["train.csv", "val.csv", "test.csv"]
        dfs = [pd.read_csv(join(repo_path, "data", split)) for split in splits]
        df = pd.concat(dfs, axis=0)
        # Filter df based on whether the temporal term is in the sentence
        indices = df.caption.apply(lambda x: any([term in x for term in temporal_terms]))
        df = df[indices]
        st.session_state.df = df
    else:
        df = st.session_state.df
    st.markdown(f"**Total number of relevant clips**: {len(df)}", unsafe_allow_html=True)

    reload_button = st.button("Reload")
    NUM = 9
    indices = np.random.randint(0, len(st.session_state.df), NUM)
    if reload_button:
        indices = np.random.randint(0, len(st.session_state.df), NUM)

    grid = make_grid(3, 3)
    per_video_width = 360
    per_video_height = 240
    for i, idx in enumerate(indices):
        row = i // 3
        col = i % 3
        
        video_id = df.iloc[idx].youtube_id
        start = df.iloc[idx].start_time
        end = start + 10.

        url = f"https://www.youtube.com/embed/{video_id}?start={int(start)}&end={int(end)}"
        html_code = f"""
        <iframe height="{per_video_height}" width="{per_video_width}" src="{url}" frameborder="0" allowfullscreen></iframe>
        """
        grid[row][col].markdown(html_code, unsafe_allow_html=True)
        grid[row][col].markdown(f"**Caption**: {df.iloc[idx].caption}", unsafe_allow_html=True)