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Rename app (1).py to app .py
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import math
from dataclasses import asdict, dataclass
from typing import Dict, List, Optional, Tuple
import gradio as gr
import pandas as pd
import plotly.express as px
# External dependency:
# pip install periodictable
from periodictable import elements
# -----------------------------
# Data extraction helpers
# -----------------------------
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)"),
]
# Some curated quick facts. We'll augment with group-based facts so every element gets at least one.
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.",
}
# Map periodictable categories into the above buckets
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"
# Build a dataframe of elements
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()
# Layout positions: group (1-18) x period (1-7); f-block as two rows
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
# f-block positions (lanthanides/actinides) - show in separate rows
LAN = [z for z in DF["Z"] if 57 <= z <= 71]
ACT = [z for z in DF["Z"] if 89 <= z <= 103]
# -----------------------------
# UI callbacks
# -----------------------------
def element_info(z_or_symbol: str):
# Accept atomic number or symbol
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']
# Build facts
facts = []
facts.extend(CURATED_FACTS.get(symbol, []))
facts.append(GROUP_FACTS.get(row['category'], None))
facts = [f for f in facts if f]
# Properties text
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!\"
# Trend plot (Atomic number vs selected property)
# We'll default to electronegativity if available, else mass.
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',
)
# Highlight selected element
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]
# Create a pseudo-2D matrix for the s/p/d blocks (7x18) with property values
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
# -----------------------------
# Build UI
# -----------------------------
with gr.Blocks(title="Interactive Periodic Table", css=\"\"\"
.button-cell {min-width: 40px; height: 40px; padding: 0.25rem; font-weight: 600;}
.symbol {font-size: 0.95rem;}
.small {font-size: 0.7rem; opacity: 0.8;}
.grid {display: grid; grid-template-columns: repeat(18, 1fr); gap: 4px;}
.fgrid {display: grid; grid-template-columns: repeat(15, 1fr); gap: 4px;}
.header {text-align:center; font-weight:700; margin: 0.5rem 0;}
\"\"\") 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\")
main_buttons = []
with gr.Group():
with gr.Row():
gr.HTML('<div class=\"grid\">' + ''.join([f'<div class=\"header\">{g}</div>' for g in range(1, 19)]) + '</div>')
# Build button grid
rows = []
for r in range(MAX_PERIOD):
with gr.Row():
cells = []
for c in range(MAX_GROUP):
z = GRID[r][c]
if z is None:
btn = gr.Button(\"\", elem_classes=[\"button-cell\"])
btn.click(lambda: (gr.update(), gr.update(), gr.update()))
else:
sym = DF.loc[DF['Z'] == z, 'symbol'].values[0]
btn = gr.Button(sym, elem_classes=[\"button-cell\"])
btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)], outputs=[
gr.Textbox(interactive=False), gr.Markdown(), gr.Plot()])
cells.append(btn)
rows.append(cells)
gr.Markdown(\"### f-block (lanthanides & actinides)\")
with gr.Row():
# Lanthanides row
lan_buttons = []
for z in LAN:
sym = DF.loc[DF['Z'] == z, 'symbol'].values[0]
btn = gr.Button(sym, elem_classes=[\"button-cell\"])
btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)], outputs=[
gr.Textbox(interactive=False), gr.Markdown(), gr.Plot()])
lan_buttons.append(btn)
with gr.Row():
# Actinides row
act_buttons = []
for z in ACT:
sym = DF.loc[DF['Z'] == z, 'symbol'].values[0]
btn = gr.Button(sym, elem_classes=[\"button-cell\"])
btn.click(handle_button_click, inputs=[gr.Number(z, visible=False)], outputs=[
gr.Textbox(interactive=False), gr.Markdown(), gr.Plot()])
act_buttons.append(btn)
with gr.Column(scale=1):
gr.Markdown(\"### Inspector\")
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])
# Initialize
heat.update(heatmap(\"electronegativity\"))
gr.Markdown(\"---\\nBuilt with **Gradio** + **periodictable**. Data completeness varies by element; some values may be missing.\")
if __name__ == \"__main__\":
demo.launch()