app.py

import math
from typing import Dict, List, Optional

import gradio as gr
import pandas as pd
import plotly.express as px
from periodictable import elements

NUMERIC_PROPS = [
    ("mass", "Atomic mass (u)"),
    ("density", "Density (g/cm^3)"),
    ("electronegativity", "Pauling electronegativity"),
    ("boiling_point", "Boiling point (K)"),
    ("melting_point", "Melting point (K)"),
    ("vdw_radius", "van der Waals radius (pm)"),
    ("covalent_radius", "Covalent radius (pm)"),
]

CURATED_FACTS: Dict[str, List[str]] = {
    "H": ["Lightest element; ~74% of the visible universe by mass is hydrogen in stars."],
    "He": ["Inert, used in cryogenics and balloons; second lightest element."],
    "Li": ["Batteries MVP: lithium-ion cells power phones and EVs."],
    "C": ["Backbone of life; diamond and graphite are pure carbon with wildly different properties."],
    "N": ["~78% of Earth's atmosphere is nitrogen (mostly N₂)."],
    "O": ["Essential for respiration; ~21% of Earth's atmosphere."],
    "Na": ["Sodium metal reacts violently with water—handle only under oil or inert gas."],
    "Mg": ["Burns with a bright white flame; used in flares and fireworks."],
    "Al": ["Light and strong; forms a protective oxide layer that resists corrosion."],
    "Si": ["Silicon is the basis of modern electronics—hello, semiconductors."],
    "Cl": ["Powerful disinfectant; elemental chlorine is toxic, compounds are widely useful."],
    "Ar": ["Argon is used to provide inert atmospheres for welding and 3D printing."],
    "Fe": ["Core of steel; iron is essential in hemoglobin for oxygen transport."],
    "Cu": ["Excellent electrical conductor; iconic blue-green patina (verdigris)."],
    "Ag": ["Highest electrical conductivity of all metals; historically used as currency."],
    "Au": ["Very unreactive ('noble'); prized for electronics and jewelry."],
    "Hg": ["Only metal that's liquid at room temperature; toxic—use with care."],
    "Pb": ["Dense and malleable; toxicity led to phase-out from gasoline and paints."],
    "U": ["Radioactive; used as nuclear reactor fuel (U-235)."],
    "Pu": ["Man-made in quantity; key in certain nuclear technologies."],
    "F": ["Most electronegative element; extremely reactive."],
    "Ne": ["Neon glows striking red-orange in discharge tubes—classic signs."],
    "Xe": ["Xenon makes bright camera flashes and high-intensity lamps."],
}

GROUP_FACTS = {
    "alkali": "Alkali metal: very reactive soft metal; forms +1 cations and reacts with water.",
    "alkaline-earth": "Alkaline earth metal: reactive (less than Group 1); forms +2 cations.",
    "transition": "Transition metal: often good catalysts, colorful compounds, multiple oxidation states.",
    "post-transition": "Post-transition metal: softer metals with lower melting points than transition metals.",
    "metalloid": "Metalloid: properties between metals and nonmetals; often semiconductors.",
    "nonmetal": "Nonmetal: tends to form covalent compounds; wide range of roles in biology and materials.",
    "halogen": "Halogen: very reactive nonmetals; form salts with metals and −1 oxidation state.",
    "noble-gas": "Noble gas: chemically inert under most conditions; monatomic gases.",
    "lanthanide": "Lanthanide: f-block rare earths; notable for magnets, lasers, and phosphors.",
    "actinide": "Actinide: radioactive f-block; includes nuclear fuel materials.",
}

def classify_category(el) -> str:
    try:
        if el.block == "s" and el.group == 1 and el.number != 1:
            return "alkali"
        if el.block == "s" and el.group == 2:
            return "alkaline-earth"
        if el.block == "p" and el.group in (13, 14, 15, 16) and el.metallic:
            return "post-transition"
        if el.block == "d":
            return "transition"
        if el.block == "p" and el.group == 17:
            return "halogen"
        if el.block == "p" and el.group == 18:
            return "noble-gas"
        if el.block == "p" and not el.metallic:
            return "nonmetal"
        if el.block == "f" and 57 <= el.number <= 71:
            return "lanthanide"
        if el.block == "f" and 89 <= el.number <= 103:
            return "actinide"
    except Exception:
        pass
    return "nonmetal" if not getattr(el, "metallic", False) else "post-transition"

def build_elements_df() -> pd.DataFrame:
    rows = []
    for Z in range(1, 119):
        el = elements[Z]
        if el is None:
            continue
        data = {
            "Z": el.number,
            "symbol": el.symbol,
            "name": el.name.title(),
            "period": getattr(el, "period", None),
            "group": getattr(el, "group", None),
            "block": getattr(el, "block", None),
            "mass": getattr(el, "mass", None),
            "density": getattr(el, "density", None),
            "electronegativity": getattr(el, "electronegativity", None),
            "boiling_point": getattr(el, "boiling_point", None),
            "melting_point": getattr(el, "melting_point", None),
            "vdw_radius": getattr(el, "vdw_radius", None),
            "covalent_radius": getattr(el, "covalent_radius", None),
            "category": classify_category(el),
            "is_radioactive": bool(getattr(el, "radioactive", False)),
        }
        rows.append(data)
    df = pd.DataFrame(rows).sort_values("Z").reset_index(drop=True)
    return df

DF = build_elements_df()
MAX_GROUP = 18
MAX_PERIOD = 7

GRID: List[List[Optional[int]]] = [[None for _ in range(MAX_GROUP)] for _ in range(MAX_PERIOD)]
for _, row in DF.iterrows():
    period, group, Z = int(row["period"]), row["group"], int(row["Z"])
    if group is None:
        continue
    GRID[period-1][group-1] = Z

LAN = [z for z in DF["Z"] if 57 <= z <= 71]
ACT = [z for z in DF["Z"] if 89 <= z <= 103]

def element_info(z_or_symbol: str):
    try:
        if z_or_symbol.isdigit():
            Z = int(z_or_symbol)
            el = elements[Z]
        else:
            el = elements.symbol(z_or_symbol)
            Z = el.number
    except Exception:
        return f"Unknown element: {z_or_symbol}", None, None

    row = DF.loc[DF['Z'] == Z].iloc[0].to_dict()
    symbol = row['symbol']

    facts = []
    facts.extend(CURATED_FACTS.get(symbol, []))
    facts.append(GROUP_FACTS.get(row['category'], None))
    facts = [f for f in facts if f]

    props_lines = [
        f"{row['name']} ({symbol}), Z = {Z}",
        f"Period {int(row['period'])}, Group {row['group']}, Block {row['block']} | Category: {row['category'].replace('-', ' ').title()}",
        f"Atomic mass: {row['mass'] if row['mass'] else '—'} u",
        f"Density: {row['density'] if row['density'] else '—'} g/cm³",
        f"Electronegativity: {row['electronegativity'] if row['electronegativity'] else '—'} (Pauling)",
        f"Melting point: {row['melting_point'] if row['melting_point'] else '—'} K | Boiling point: {row['boiling_point'] if row['boiling_point'] else '—'} K",
        f"vdW radius: {row['vdw_radius'] if row['vdw_radius'] else '—'} pm | Covalent radius: {row['covalent_radius'] if row['covalent_radius'] else '—'} pm",
        f"Radioactive: {'Yes' if row['is_radioactive'] else 'No'}",
    ]
    info_text = "\n".join(props_lines)
    facts_text = "\n• ".join(["Interesting facts:"] + facts) if facts else "No fact on file—still cool though!"

    prop_key = 'electronegativity' if not pd.isna(row['electronegativity']) else 'mass'
    label = dict(NUMERIC_PROPS)[prop_key]
    trend_df = DF[['Z', 'symbol', prop_key]].dropna()
    fig = px.scatter(
        trend_df, x='Z', y=prop_key, hover_name='symbol', title=f'{label} across the periodic table',
    )
    fig.add_scatter(x=[Z], y=[row[prop_key]] if row[prop_key] else [None],
                    mode='markers+text', text=[symbol], textposition='top center')

    return info_text, facts_text, fig

def handle_button_click(z: int):
    return element_info(str(z))

def search_element(query: str):
    query = (query or '').strip()
    if not query:
        return gr.update(), gr.update(), gr.update()
    return element_info(query)

def heatmap(property_key: str):
    prop_label = dict(NUMERIC_PROPS)[property_key]
    import numpy as np
    grid_vals = np.full((MAX_PERIOD, MAX_GROUP), None, dtype=object)
    for r in range(MAX_PERIOD):
        for c in range(MAX_GROUP):
            z = GRID[r][c]
            if z is None:
                continue
            val = DF.loc[DF['Z'] == z, property_key].values[0]
            grid_vals[r, c] = val if not pd.isna(val) else None

    fig = px.imshow(
        grid_vals.astype(float),
        origin='upper',
        labels=dict(color=prop_label, x='Group', y='Period'),
        x=list(range(1, MAX_GROUP+1)),
        y=list(range(1, MAX_PERIOD+1)),
        title=f'Periodic heatmap: {prop_label}',
        aspect='auto',
        color_continuous_scale='Viridis'
    )
    return fig

with gr.Blocks(title="Interactive Periodic Table") as demo:
    gr.Markdown("# 🧪 Interactive Periodic Table\nClick an element or search by symbol/name/atomic number.")

    with gr.Row():
        with gr.Column(scale=2):
            gr.Markdown("### Main Table")
            with gr.Row():
                for g in range(1, 19):
                    gr.Markdown(f"**{g}**")
            for r in range(MAX_PERIOD):
                with gr.Row():
                    for c in range(MAX_GROUP):
                        z = GRID[r][c]
                        if z is None:
                            gr.Button("", interactive=False)
                        else:
                            sym = DF.loc[DF['Z'] == z, 'symbol'].values[0]
                            btn = gr.Button(sym)
                            btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)], outputs=[
                                gr.Textbox(interactive=False), gr.Markdown(), gr.Plot()])

            gr.Markdown("### f-block (lanthanides & actinides)")
            with gr.Row():
                for z in LAN:
                    sym = DF.loc[DF['Z'] == z, 'symbol'].values[0]
                    btn = gr.Button(sym)
                    btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)], outputs=[
                        gr.Textbox(interactive=False), gr.Markdown(), gr.Plot()])
            with gr.Row():
                for z in ACT:
                    sym = DF.loc[DF['Z'] == z, 'symbol'].values[0]
                    btn = gr.Button(sym)
                    btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)], outputs=[
                        gr.Textbox(interactive=False), gr.Markdown(), gr.Plot()])

        with gr.Column(scale=1):
            search = gr.Textbox(label="Search (symbol/name/Z)", placeholder="e.g., C, Iron, 79")
            info = gr.Textbox(label="Properties", lines=10, interactive=False)
            facts = gr.Markdown("Select an element to see fun facts.")
            trend = gr.Plot()

            search.submit(search_element, inputs=[search], outputs=[info, facts, trend])

            gr.Markdown("### Trend heatmap")
            prop = gr.Dropdown(choices=[k for k, _ in NUMERIC_PROPS], value="electronegativity", label="Property")
            heat = gr.Plot()
            prop.change(heatmap, inputs=[prop], outputs=[heat])
            heat.update(heatmap("electronegativity"))

if __name__ == "__main__":
    demo.launch()