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23e468b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 | """
SQLite database layer for storing and querying polymer datasheets.
"""
from __future__ import annotations
import logging
from typing import Optional
import pandas as pd
from sqlalchemy import (
Column,
String,
Text,
create_engine,
or_,
)
from sqlalchemy.orm import Session, declarative_base, sessionmaker
import config
from models import DatasheetRecord
logger = logging.getLogger(__name__)
Base = declarative_base()
# ── ORM Model ────────────────────────────────────────────────────────────────
class DatasheetRow(Base):
"""SQLAlchemy model mirroring DatasheetRecord."""
__tablename__ = "datasheets"
id = Column(String, primary_key=True)
created_at = Column(String, default="")
# General
material_name = Column(Text, default="")
trade_name = Column(Text, default="")
manufacturer = Column(Text, default="", index=True)
polymer_family = Column(Text, default="", index=True)
grade = Column(Text, default="")
description = Column(Text, default="")
processing_method = Column(Text, default="")
features = Column(Text, default="")
applications = Column(Text, default="")
source_url = Column(Text, default="")
# Mechanical
tensile_strength_mpa = Column(Text, default="")
tensile_modulus_mpa = Column(Text, default="")
elongation_at_break_pct = Column(Text, default="")
flexural_strength_mpa = Column(Text, default="")
flexural_modulus_mpa = Column(Text, default="")
impact_strength_charpy_kj_m2 = Column(Text, default="")
impact_strength_izod_j_m = Column(Text, default="")
hardness_shore_d = Column(Text, default="")
hardness_rockwell = Column(Text, default="")
compressive_strength_mpa = Column(Text, default="")
# Thermal
melting_temperature_c = Column(Text, default="")
glass_transition_temperature_c = Column(Text, default="")
heat_deflection_temperature_c = Column(Text, default="")
vicat_softening_temperature_c = Column(Text, default="")
continuous_service_temperature_c = Column(Text, default="")
thermal_conductivity_w_mk = Column(Text, default="")
coefficient_of_thermal_expansion_um_mk = Column(Text, default="")
flammability_rating = Column(Text, default="")
# Physical
density_g_cm3 = Column(Text, default="")
melt_flow_index_g_10min = Column(Text, default="")
water_absorption_pct = Column(Text, default="")
moisture_absorption_pct = Column(Text, default="")
specific_gravity = Column(Text, default="")
transparency = Column(Text, default="")
color = Column(Text, default="")
# Electrical
dielectric_strength_kv_mm = Column(Text, default="")
dielectric_constant = Column(Text, default="")
volume_resistivity_ohm_cm = Column(Text, default="")
surface_resistivity_ohm = Column(Text, default="")
dissipation_factor = Column(Text, default="")
# Chemical Resistance
acid_resistance = Column(Text, default="")
alkali_resistance = Column(Text, default="")
solvent_resistance = Column(Text, default="")
uv_resistance = Column(Text, default="")
weatherability = Column(Text, default="")
# Regulatory
fda_approved = Column(Text, default="")
rohs_compliant = Column(Text, default="")
reach_compliant = Column(Text, default="")
ul94_rating = Column(Text, default="")
# ── Database Manager ─────────────────────────────────────────────────────────
class DatasheetDB:
"""Manages all database operations for the polymer datasheet store."""
def __init__(self, db_path: str = config.DB_PATH):
self.engine = create_engine(f"sqlite:///{db_path}", echo=False)
Base.metadata.create_all(self.engine)
self.SessionLocal = sessionmaker(bind=self.engine)
# ── Write ─────────────────────────────────────────────────────────────
def upsert(self, record: DatasheetRecord) -> str:
"""Insert or update a datasheet record. Returns the record ID."""
data = record.to_flat_dict()
with self.SessionLocal() as session:
existing = session.get(DatasheetRow, data["id"])
if existing:
for key, value in data.items():
setattr(existing, key, value)
else:
row = DatasheetRow(**data)
session.add(row)
session.commit()
logger.info("Upserted record %s (%s)", data["id"], data.get("trade_name"))
return data["id"]
# ── Read ──────────────────────────────────────────────────────────────
def search(
self,
query: str = "",
manufacturer: str = "",
polymer_family: str = "",
limit: int = 50,
) -> pd.DataFrame:
"""
Search the database with optional filters.
Returns a Pandas DataFrame.
"""
with self.SessionLocal() as session:
q = session.query(DatasheetRow)
if manufacturer:
q = q.filter(
DatasheetRow.manufacturer.ilike(f"%{manufacturer}%")
)
if polymer_family:
q = q.filter(
DatasheetRow.polymer_family.ilike(f"%{polymer_family}%")
)
if query:
pattern = f"%{query}%"
q = q.filter(
or_(
DatasheetRow.material_name.ilike(pattern),
DatasheetRow.trade_name.ilike(pattern),
DatasheetRow.manufacturer.ilike(pattern),
DatasheetRow.polymer_family.ilike(pattern),
DatasheetRow.grade.ilike(pattern),
DatasheetRow.description.ilike(pattern),
DatasheetRow.applications.ilike(pattern),
DatasheetRow.features.ilike(pattern),
)
)
rows = q.limit(limit).all()
if not rows:
return pd.DataFrame()
records = []
for row in rows:
records.append(
{c.name: getattr(row, c.name) for c in DatasheetRow.__table__.columns}
)
return pd.DataFrame(records)
def get_by_id(self, record_id: str) -> Optional[DatasheetRecord]:
"""Retrieve a single record by ID."""
with self.SessionLocal() as session:
row = session.get(DatasheetRow, record_id)
if row is None:
return None
data = {c.name: getattr(row, c.name) for c in DatasheetRow.__table__.columns}
return DatasheetRecord(**data)
def get_all_dataframe(self) -> pd.DataFrame:
"""Return the entire database as a DataFrame."""
return self.search(limit=10_000)
def count(self) -> int:
"""Return total number of records."""
with self.SessionLocal() as session:
return session.query(DatasheetRow).count()
def delete(self, record_id: str) -> bool:
"""Delete a record by ID. Returns True if deleted."""
with self.SessionLocal() as session:
row = session.get(DatasheetRow, record_id)
if row:
session.delete(row)
session.commit()
return True
return False
def get_summary_dataframe(self) -> pd.DataFrame:
"""Return a summary view with key columns only."""
df = self.get_all_dataframe()
if df.empty:
return df
summary_cols = [
"id", "material_name", "trade_name", "manufacturer",
"polymer_family", "grade", "density_g_cm3",
"tensile_strength_mpa", "melting_temperature_c",
"heat_deflection_temperature_c", "applications",
"created_at",
]
available = [c for c in summary_cols if c in df.columns]
return df[available]
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