Educational ipython source code for applied thermodynamics.



Prior work

We would like to acknowledge some prior work that inspire us

nrthermo’s pvdiagram < >

“Numerical recipes applied to thermodynamics This is a bunch of old C programs based on the good ol’ Numerical Recipes There are three computational physics problems proposed:”

Here in Pytherm we plan on including some examples similar to the ones presented there: van der Waals equation of state, the p-v diagram, the Binodal Curve, the Boyle temperature, and the Compressibility diagram. However in python with numpy/scipy/sympy and matplotlib, while they did in c with numerical recipes and independent plotting tools.

Taylor’ thermodynamics with maple

“We consider the use of a computer algebra system to carry out the symbolic computations needed in thermodynamics. A package for Maple is described and illustrated with several examples involving the creation and manipulation of thermodynamic derivatives.”

“A computer algebra system (Maple) is used for the construction, display, and analysis of residue curve maps. This problem from engineering thermodynamics presents an interesting array of computational problems ranging from symbolic (for deriving the equations), through numerical (solving systems of nonlinear algebraic equations, systems of ordinary differential equations (ODEs) and systems of differential algebraic equations (DAEs), to graphical (for displaying the results).”

Castier’ thermodynamics with mathematica – THERMATH


Gibbs live

“By Thomas Cool1, R. Edwin García1, Alex Bartol1

  1. Purdue University

Python-based libraries for the calculation of phase diagrams and thermodynamic properties” < tool on a live executable environment by nanohub >” < publication>


A fortran+pýthon open source project for thermodynamic models and algorithms for phase equilibria - See also pyther -


an open source chemical engineering process simulator - - and its Standalone thermodynamics library

CalebBell’ thermo

“Thermodynamics, phase equilibria, transport properties and chemical database component of Chemical Engineering Design Library (ChEDL) -

FOSSEE’ textbook companion project

(in python:)

MIT open courseware

“The idea is simple: to publish all of our course materials online and make them widely available to everyone.” - Dick K.P. Yue, Professor, MIT School of Engineering

“a free, open source interactive text that introduces readers to core concepts of bioinformatics in the context of their implementation and application.”


GNU GPL3 : Free as in Freedom

The tools with which we build our project and their licenses or terms of service

Learn about open source licences here.

Git (GNU GPL 2.0)

The Git project chose to use GPLv2 to guarantee your freedom to share and change free software—to make sure the software is free for all its users.


GitHub Terms of Service

Anaconda (BSD license)

All rights reserved under the 3-clause BSD License.

Python (BSD license)

Python, its standard libraries, and Jython, are distributed under the Python License. The intellectual property rights behind Python and Jython are held and managed by the Python Software Foundation.

numpy (BSD license)

NumPy License (BSD Style)

sympy (BSD license)

Unless stated otherwise, all files in the SymPy project, SymPy’s webpage (and wiki), all images and all documentation including this User’s Guide are licensed using the new BSD license.

matplotlib (BSD license)

Matplotlib only uses BSD compatible code, and its license is based on the PSF license. See the Open Source Initiative licenses page for details on individual licenses. Non-BSD compatible licenses (e.g., LGPL) are acceptable in matplotlib toolkits.

Jupyter notebook (BSD license)

Jupyter uses a shared copyright model that enables all contributors to maintain the copyright on their contributions. All code is licensed under the terms of the revised BSD license.

Ipython (BSD license)

Several of the authors of IPython are connected with academic and scientific research, so it is important for us to be able to show the impact of our work in other projects and fields. If IPython contributes to a project that leads to a scientific publication, please acknowledge this fact by citing the project. You can use this ready-made citation entry.


Automated static conversion of ipynb to html


Automated conversion on markdown to css and html


remote executable environment for jupyter notebooks

Python Tutor, by Philip Guo

Helps people overcome a fundamental barrier to learning programming: understanding what happens as the computer executes each line of a program’s source code.