import pandas as pd
import streamlit as st

from functions import do_login, generate_pdf_download


def open_csv_file(file_path):
    """Apre un file CSV e restituisce una connessione DuckDB in-memory."""
    import duckdb
    con = duckdb.connect(database=":memory:")
    con.execute(f"CREATE TABLE index AS SELECT * FROM read_csv_auto('{file_path}')")
    return con


def search_cas_inci(input, type="cas"):
    """Cerca un numero CAS o INCI nel file CSV. Ritorna lista di tuple (casNo, inciName)."""
    con = open_csv_file("streamlit\data.csv")
    if type == "cas":
        query = f"SELECT * FROM index WHERE casNo LIKE '%{input}%'"
    else:
        query = f"SELECT * FROM index WHERE inciName ILIKE '%{input}%'"
    results = con.execute(query).fetchdf()
    if not results.empty:
        return list(zip(results["casNo"].tolist(), results["inciName"].tolist()))
    return []


def search_cir(input_text: str) -> list[tuple]:
    """Cerca nel CIR database per nome ingrediente o INCI. Ritorna lista di (name, inci, url)."""
    con = open_csv_file("streamlit\cir-reports.csv")
    query = f"""
        SELECT
            "tablescraper-selected-row"   AS ingredient_name,
            "tablescraper-selected-row 2" AS inci_name,
            "tablescraper-selected-row href" AS url
        FROM index
        WHERE (
            "tablescraper-selected-row"   ILIKE '%{input_text}%'
            OR "tablescraper-selected-row 2" ILIKE '%{input_text}%'
        )
        AND "tablescraper-selected-row" != 'Ingredient Name as Used:'
        AND "tablescraper-selected-row href" != ''
        LIMIT 20
    """
    results = con.execute(query).fetchdf()
    if not results.empty:
        return list(zip(
            results["ingredient_name"].tolist(),
            results["inci_name"].tolist(),
            results["url"].tolist(),
        ))
    return []


def download_pdf(casNo, origin, link):
    """Mostra i pulsanti per generare e scaricare un PDF dall'API."""
    if st.button("Generate PDF", key=f"gen_{casNo}_{origin}"):
        with st.spinner("Fetching PDF..."):
            pdf_data = generate_pdf_download(cas=casNo, origin=origin, link=link)
        st.download_button(
            label="Download PDF",
            data=pdf_data,
            file_name=f"{casNo}_{origin}.pdf",
            mime="application/pdf",
            key=f"dl_{casNo}_{origin}",
        )


def show_login_page():
    """Mostra il form di login."""
    _, col, _ = st.columns([1, 1, 1])
    with col:
        st.title("LMB App")
        st.caption("Accedi per continuare")
        with st.form("login_form"):
            email = st.text_input("Email", placeholder="utente@esempio.it")
            password = st.text_input("Password", type="password")
            submitted = st.form_submit_button("Accedi", use_container_width=True, type="primary")
        if submitted:
            if not email or not password:
                st.warning("Inserisci email e password.")
            else:
                with st.spinner("Autenticazione in corso..."):
                    if do_login(email, password):
                        st.rerun()


def display_orderData(order_data: dict):
    """Mostra un riepilogo leggibile dell'ordine (non JSON)."""
    st.markdown("### Riepilogo Ordine")

    col1, col2, col3 = st.columns(3)
    with col1:
        st.metric("Cliente", order_data["client_name"])
    with col2:
        st.metric("Prodotto", order_data["product_name"])
    with col3:
        st.metric("Preset Esposizione", order_data["preset_esposizione"])

    ingredients = order_data.get("ingredients", [])
    total_pct = sum(i["percentage"] for i in ingredients)

    col4, col5, col6 = st.columns(3)
    with col4:
        st.metric("Numero ingredienti", len(ingredients))
    with col5:
        st.metric("Percentuale totale", f"{total_pct:.6f}%")
    with col6:
        n_col = sum(1 for i in ingredients if i["is_colorante"])
        n_skip = sum(1 for i in ingredients if i["skip_tox"])
        parts = []
        if n_col > 0:
            parts.append(f"{n_col} colorante/i")
        if n_skip > 0:
            parts.append(f"{n_skip} senza tox")
        st.metric("Flag attivi", ", ".join(parts) if parts else "Nessuno")

    st.markdown("**Ingredienti:**")
    display_rows = [
        {
            "INCI": i["inci"] if i["inci"] else "-",
            "CAS": i["cas"] if i["cas"] else "-",
            "Percentuale (%)": f"{i['percentage']:.6f}",
            "Colorante": "Si" if i["is_colorante"] else "-",
            "Salta Tox": "Si" if i["skip_tox"] else "-",
        }
        for i in ingredients
    ]
    st.dataframe(pd.DataFrame(display_rows), width="stretch", hide_index=True)


if __name__ == "__main__":
    data = search_cas_inci("102242-62-6")
    print(data)