Prepare 2.3.1 (#378)

* reformat the rst readme as md

* update setup.py

* address comments

CHANGES

@@ -13,7 +13,8 @@ The rules for this file:
   * release numbers follow "Semantic Versioning" https://semver.org
 
 ------------------------------------------------------------------------------
-??/??/2024 orbeckst
+
+08/07/2024 orbeckst, xiki-tempula
 
   * 2.3.1
 

MANIFEST.in

@@ -1,6 +1,6 @@
 include *.rst
 recursive-include src/alchemlyb *.gz *.bz2 *.zip *.rst *.txt
-include README.rst
+include README.md
 include LICENSE
 include versioneer.py
 include src/alchemlyb/_version.py

README.md

@@ -0,0 +1,54 @@
+# alchemlyb: the simple alchemistry library
+
+[![Zenodo DOI](https://zenodo.org/badge/68669096.svg)](https://zenodo.org/badge/latestdoi/68669096) [![Documentation](https://readthedocs.org/projects/alchemlyb/badge/?version=latest)](http://alchemlyb.readthedocs.io/en/latest/) [![Build Status](https://github.com/alchemistry/alchemlyb/actions/workflows/ci.yaml/badge.svg?branch=master)](https://github.com/alchemistry/alchemlyb/actions/workflows/ci.yaml) [![Code coverage](https://codecov.io/gh/alchemistry/alchemlyb/branch/master/graph/badge.svg)](https://codecov.io/gh/alchemistry/alchemlyb) [![anaconda package](https://anaconda.org/conda-forge/alchemlyb/badges/version.svg)](https://anaconda.org/conda-forge/alchemlyb)
+
+**alchemlyb** makes alchemical free energy calculations easier to do by leveraging the full power and flexibility of the PyData stack. It includes:
+
+1. Parsers for extracting raw data from output files of common molecular dynamics engines such as [GROMACS](http://www.gromacs.org/), [AMBER](http://ambermd.org/), [NAMD](http://www.ks.uiuc.edu/Research/namd/) and [other simulation codes](https://alchemlyb.readthedocs.io/en/latest/parsing.html).
+
+2. Subsamplers for obtaining uncorrelated samples from timeseries data (including extracting independent, equilibrated samples [Chodera2016](#chodera2016) as implemented in the [pymbar](http://pymbar.readthedocs.io/) package).
+
+3. Estimators for obtaining free energies directly from this data, using best-practices approaches for multistate Bennett acceptance ratio (MBAR) [Shirts2008](#shirts2008) and BAR (from [pymbar](http://pymbar.readthedocs.io/)) and thermodynamic integration (TI).
+
+## Installation
+
+**Install** via `pip` from [PyPi (alchemlyb)](https://pypi.org/project/alchemlyb):
+
+```bash
+pip install alchemlyb
+```
+
+or as a `conda` package from the [conda-forge (alchemlyb)](https://anaconda.org/conda-forge/alchemlyb) channel:
+
+```bash
+conda install -c conda-forge alchemlyb
+```
+
+**Update** with `pip`:
+
+```bash
+pip install --update alchemlyb
+```
+
+or with `conda` run:
+
+```bash
+conda update -c conda-forge alchemlyb
+```
+
+to get the latest released version.
+
+## Getting involved
+
+Contributions of all kinds are very welcome.
+
+If you have questions or want to discuss alchemlyb please post in the [alchemlyb Discussions](https://github.com/alchemistry/alchemlyb/discussions).
+
+If you have bug reports or feature requests then please get in touch with us through the [Issue Tracker](https://github.com/alchemistry/alchemlyb/issues).
+
+We also welcome code contributions: have a look at our [Developer Guide](https://github.com/alchemistry/alchemlyb/wiki/Developer-Guide). Open an issue with the proposed fix or change in the [Issue Tracker](https://github.com/alchemistry/alchemlyb/issues) and submit a pull request against the [alchemistry/alchemlyb](https://github.com/alchemistry/alchemlyb) GitHub repository.
+
+## References
+
+- <a name="shirts2008"></a> Shirts, M.R., and Chodera, J.D. (2008). Statistically optimal analysis of samples from multiple equilibrium states. The Journal of Chemical Physics 129, 124105.
+- <a name="chodera2016"></a> Chodera, J.D. (2016). A Simple Method for Automated Equilibration Detection in Molecular Simulations. Journal of Chemical Theory and Computation 12, 1799–1805.

setup.py

@@ -41,8 +41,8 @@
     packages=find_packages("src"),
     package_dir={"": "src"},
     license="BSD",
-    long_description=open("README.rst").read(),
-    long_description_content_type="text/x-rst",
+    long_description=open("README.md").read(),
+    long_description_content_type="text/markdown",
     python_requires=">=3.9",
     tests_require=["pytest", "alchemtest"],
     install_requires=[