janaf
Python wrapper for NIST-JANAF Thermochemical Tables
Decision gist · record as of 2026-08-14
Yes, if you need reliable access to NIST-JANAF thermochemical reference data in Python. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and integrates cleanly with polars. The permissive license and low dependency count make it a straightforward addition to chemistry or materials science workflows. Not necessary if you already have direct access to NIST tables or use a different thermodynamic database.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires polars to be installed; Python 3.10 or later.
- Low install friction with a single polars dependency.
- Active maintenance with a recent release (31 days ago) and current commits; supports Python 3.10 through 3.15.
License · maintenance · safety
0BSD (permissive) — Licensed under 0BSD (permissive), allowing unrestricted use. Note that the bundled NIST-JANAF data itself carries a separate NIST disclaimer regarding accuracy and liability.
last release 2026-07-14 (31 days) · last repo commit 2026-08-10 · 11 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 531,795 downloads/mo, #6,152 on PyPI
Alternatives
Verify before relying
pip install janaf
import janaf
table = janaf.search(formula="CO2$")
df = table.df
value = df.filter(pl.col("T(K)").is_close(298.15)).item(0, "delta-f H")- Scope of data corrections applied (missing signs, missing tabs, comment lines) and whether they affect all compounds or specific subsets
- Whether search supports compound names, formulas, or both; regex support indicated but full query syntax not detailed
What it is and what it does
janaf is a Python wrapper around the NIST-JANAF Thermochemical Tables, a curated reference database of thermodynamic properties for chemical compounds. It lets you search for compounds by formula and retrieve their thermochemical data—heat capacity, entropy, Gibbs free energy, formation enthalpy, and more—across a temperature range, parsed directly into a polars DataFrame for analysis and calculation.
The package includes corrections for known data quality issues in the original NIST tables (missing signs, formatting gaps, stray comment lines) and exposes the underlying data as structured columns. It depends only on polars for data handling, making it lightweight to install. The bundled thermochemical data comes from NIST's official tables, though the wrapper itself is newly maintained.
Use it for
- Look up standard formation enthalpies and Gibbs free energies for compounds at reference temperature (298.15 K) for equilibrium calculations.
- Retrieve heat capacity and entropy data across a temperature range for thermodynamic simulations or process design.
- Search for thermochemical properties of a specific compound by chemical formula to validate or supplement experimental measurements.
- Extract tabular thermodynamic data into a DataFrame for batch analysis or integration into a larger computational chemistry workflow.
- Verify compound identifiers and available temperature ranges before performing high-temperature thermodynamic calculations.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need reliable access to NIST-JANAF thermochemical reference data in Python.
The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and integrates cleanly with polars. The permissive license and low dependency count make it a straightforward addition to chemistry or materials science workflows. Not necessary if you already have direct access to NIST tables or use a different thermodynamic database.
Install
janaf on PyPI
Before you install
Low install friction with a single polars dependency. Active maintenance with a recent release (31 days ago) and current commits; supports Python 3.10 through 3.15.
Requires polars to be installed; Python 3.10 or later.
License in practice
Licensed under 0BSD (permissive), allowing unrestricted use. Note that the bundled NIST-JANAF data itself carries a separate NIST disclaimer regarding accuracy and liability.
Quickstart
pip install janaf
import janaf
table = janaf.search(formula="CO2$")
df = table.df
value = df.filter(pl.col("T(K)").is_close(298.15)).item(0, "delta-f H")Verify before relying
- Scope of data corrections applied (missing signs, missing tabs, comment lines) and whether they affect all compounds or specific subsets
- Whether search supports compound names, formulas, or both; regex support indicated but full query syntax not detailed
Package facts
| License | 0BSD permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagepolars |
| Maintenance | Actively maintained 31 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 531,795 / month, #6,152 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Programming Language :: Python :: 3.15Programming Language :: Python :: Implementation :: CPythonTopic :: Scientific/Engineering :: ChemistryTopic :: Scientific/Engineering :: Physics |
Evidence: janaf-1.4.0-py3-none-any.whl
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