Added section on using uv (Astral's fast Python package manager) to
install and work with CoolProp. Includes examples for:
- Installing in current environment
- Creating new projects with CoolProp
- Running scripts with automatic environment management
- Development installations from source
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Changes:
- Updated documentation to show modern pip-based installation
- Updated manylinux build script to use pip wheel instead of setup.py
- Updated conda metadata generator to use pip install
- Removed deprecated PyPI preparation script (replaced by `python -m build --sdist`)
All build infrastructure now uses the new scikit-build-core build system.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
* Add ability to get at the ideal-gas properties directly
Also through the python interface
* And python interface files
* Fixes the missing reference to ideal gas notebook
* Expansions are fully wrapped, looking good. Next step is the set of expansions that is the 1D approximation
* Get 1D approx working via cython
* Count solutions
* SuperAncillary class is working
>1000x speedup for water
Time for C++!
* Superancillaries are working!
In C++, speedup is more than 2000x. In Python, more like 150x because of Python <-> C++ overhead
* Add pmax check for PQ superancillary calls
* Update tests
* Allow T limits to be obtained
* Implement get_fluid_parameter_double for getting superanc value
* Add tests for getting parameters from superanc
* Script for testing superancillaries for sphinx
* Microoptimizations; don't help speed
The limiting factor remains the clear function, which takes about 30 ns
* Add R125 superancillary
* Use the release from fastchebpure for the files
* Drop a .gitignore in the unzipped folder
* Update superancillary injection script
* Turn on superancillaries by default
* Missing header
* Many int conversions in superancillary
* Another int cast
* More annoying solution for boost iter max
* Fix warnings
* One more warning
* Clear up the calculation of rho
* Update docs_docker-build.yml
Use arm64 since the containers were built on mac
* Superfluous ;
* Update backend.py
* Get the critical points working for superancillaries
* Fix wrapping changes of xmin&xmax methods
* squelch warnings
* Version 0 of jupyter notebook for docs
* Try to add the notebook to the docs
* Add jupyter notebook for superancillary
* Lots of updates to superancillary notebook
* More updates to docs
* Skip pseudo-pure for superancillary docs
* Fix output of superancillary figures
* Add superancillary plots to docs for the page for each fluid
* Make a placeholder figure for fluids without superancillary
* Add superancillary plots to task list
* Bump to release fixing m-xylene
* Relax the location of the REFPROP stuff
* Change default name for R-1336mzz(E)
* No need for figures to be so large
* Don't need REFPROP setting
* Bump to fastchebpure release with methanol
* Benchmark caching options
* Benchmark more granularly
* Add the fast methods to public API for HEOS class
* Back to memset - can memset with 0 but no other value
* Fix how caching is managed in Helmholtz class
* Close to final implementation
Perhaps a tiny bit more optimization possible?
* Update function name
* Make message more accurate
* Fix init order
* Expose update_QT_pure_superanc to Python
* Fix when _reducing is set for pures
* Fix the post_update
* Indent
* Notebook
* Notebook
* Make ln(p) construction lazy
Only really matters for debug builds
* Also make reference non-const
* Inject superancillary for methanol
* Make the superancillary loading entirely lazy in debug
* Fix PH bug for Nitrogen
Closes#2470
* Force the clear to be called on SatL and SatV
To invalidate them at start
* Default is non-lazy superancillary loading
* Add CMake option to have lazy-loading superancillaries [skip ci]
Not a good idea unless doing very narrow testing
