pyglenn — Thermochemical Properties Calculator

Computes Cp(T), H°(T), S°(T) from NASA polynomial coefficients stored in a SQLite database, converted from FORTRAN thermo.inp files.

Author: Dr. Reginaldo G. Leão Jr. — prof.reginaldo.leao@gmail.com

📖 Documentation: profleao.github.io/pyglenn

Features

• Parse NASA-format thermo.inp (FORTRAN Appendix C) → SQLite3 database
• Query species by name, phase, molecular weight
• Calculate Cp(T), H°(T), S°(T) at any valid temperature
• Sensible enthalpy, analytical dCp/dT and Cp/Cv (γ)
• Mixture properties (molar and mass basis) for a fixed composition
• Enthalpy of formation lookup
• Enthalpy change between two temperatures
• Command-line interface
• 2,035 species, 3,779 temperature intervals

Installation

From PyPI (pip)

pip install pyglenn

From source

git clone https://github.com/ProfLeao/pyglenn.git
cd pyglenn
pip install .

Conda

conda install conda-forge::pyglenn

Quick Start

The database is bundled with the package — no manual build step needed.

Python API

from pyglenn import ThermochemicalCalculator

# No need to specify a DB file — uses the bundled thermo.db
calc = ThermochemicalCalculator()
calc.connect()

# Find O2 (exact match — returns only O2, not Be3N2 or Al2O2)
species = calc.get_available_species('O2', exact_match=True)
o2 = species[0]

# Calculate properties at 1000 K
props = calc.calculate_properties(o2.id, 1000.0)
print(f"Cp = {props.cp:.2f} J/(mol·K)")
print(f"H° = {props.h_relative:.1f} J/mol")
print(f"S° = {props.s:.3f} J/(mol·K)")

calc.close()

Or use the context manager for automatic cleanup:

from pyglenn import ThermochemicalCalculator

with ThermochemicalCalculator() as calc:
    # exact_match=True guarantees the correct species (case-insensitive)
    species = calc.get_available_species('CH4', exact_match=True)
    props = calc.calculate_properties(species[0].id, 500.0)
    print(f"Cp = {props.cp:.2f} J/(mol·K)")

Mixtures

Compute mixture properties (e.g. dry air) from mole fractions, on both the molar and mass basis:

from pyglenn import Mixture, ThermochemicalCalculator

with ThermochemicalCalculator() as calc:
    n2 = calc.get_available_species('N2', exact_match=True)[0]
    o2 = calc.get_available_species('O2', exact_match=True)[0]

    air = Mixture(((n2.id, 0.79), (o2.id, 0.21)))  # mole fractions
    mix = calc.mixture_properties(air, 1000.0)

print(f"mean molar mass = {mix.molar_mass * 1000.0:.3f} g/mol")
print(f"cp_mass         = {mix.cp_mass:.2f} J/(kg·K)")

CLI

pyglenn query -s O2

Rebuilding the database

Only needed if the database is corrupted or you modify thermo.inp manually:

pyglenn build -i thermo.inp -o thermo.db

Database Structure

Table	Description
species	Chemical species (name, formula, phase, MW, ΔH°f)
temperature_intervals	Valid T ranges per species
coefficients	NASA-7 polynomial coefficients (a1–a7, b1, b2)
file_metadata	Global file metadata
metadata	Dataset metadata, including its reference gas constant

Gas Constants

R_UNIVERSAL = 8.31446261815324 J/(mol·K) is the universal CODATA value and remains available through the compatibility alias R. NASA Glenn/CEA polynomials in newly built databases declare their fitted reference constant as R_GLENN = 8.314510 J/(mol·K) in SQLite metadata. The calculator reads that value automatically when it connects; legacy databases fall back to R_UNIVERSAL until explicitly migrated.

Citing

If you use pyglenn in your research, please cite it as:

@software{goncalves_leao_junior_2026_21324586,
  author    = {Gonçalves Leão Junior, Reginaldo},
  title     = {pyglenn: A Python Toolkit for Thermochemical
               Properties Calculation from NASA Polynomials},
  month     = jul,
  year      = 2026,
  publisher = {Zenodo},
  doi       = {10.5281/zenodo.21324586},
  url       = {https://doi.org/10.5281/zenodo.21324586},
}

Requirements

• Python ≥ 3.9
• NumPy ≥ 1.21
• SQLite3 (stdlib)

License

MIT — see LICENSE file.