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import streamlit as st | |
import json | |
from datasets import load_dataset | |
st.set_page_config(page_title="Kaggle Notebooks inspection", layout="wide") | |
st.markdown("<h1 style='text-align: center; color: #00BFFF;'>Kaggle Notebooks inspection 🔍</h1>", unsafe_allow_html=True) | |
st.markdown("Here you can inspect Kaggle notebooks that were converted to python scripts and deduplicated.") | |
def load_data(): | |
ds = load_dataset("loubnabnl/kaggle_scripts_dedup_subset", split="train") | |
return ds | |
samples = load_data() | |
#col1, _ = st.columns([2, 4]) | |
#with col1: | |
index_example = st.number_input(f"Index of the chosen sample from the existing {len(samples)}", min_value=0, max_value=len(samples)-1, value=0, step=1) | |
st.code(samples[index_example]["script"]) |