update readme files

README.dev.md

@@ -32,24 +32,26 @@ install-nplinker-deps
 
 Afterwards check that the install directory is present in the `PATH` environment variable.
 
-## Running the tests
-
-There are two ways to run tests.
+You can also use [conda](https://docs.conda.io/projects/conda/en/stable/) to manage python environments.
 
-The first way requires an activated virtual environment with the development tools installed:
+## Running the tests
 
+**Run unit tests with**
 ```shell
-pytest -v
+pytest
+# or
+pytest -n auto tests/unit
 ```
+Parallel testing is supported with `pytest-xdist` plugin. To run tests in parallel, use the `-n`
+option, e.g. `-n auto` to run tests in parallel with the number of CPUs available.
 
-The second is to use `tox`, which can be installed separately (e.g. with `pip install tox`), i.e. not necessarily inside the virtual environment you use for installing `nplinker`, but then builds the necessary virtual environments itself by simply running:
-
+**Run integration tests with**
 ```shell
-tox
+pytest -n 0 tests/integration
 ```
+`-n 0` means no parallel testing.
+
 
-Testing with `tox` allows for keeping the testing environment separate from your development environment.
-The development environment will typically accumulate (old) packages during development that interfere with testing; this problem is avoided by testing with `tox`.
 
 ### Test coverage
 
@@ -117,35 +119,35 @@ For more info about static typing and mypy, see:
 - [Static typing with Python](https://typing.readthedocs.io/en/latest/index.html#)
 - [Mypy doc](https://mypy.readthedocs.io/en/stable/)
 
-## Generating the API docs
+## Docs
+We use [MkDocs](https://www.mkdocs.org/) and its theme [Material for MkDocs](https://squidfunk.github.io/mkdocs-material/)
+to generate documentations. The configurations of MkDocs are set in [mkdocs.yml](mkdocs.yml) file.
 
+To watch the changes of current doc in real time, run:
 ```shell
-cd docs
-make html
+mkdocs serve
+# or to watch src and docs directories
+mkdocs serve -w docs -w src
 ```
+Then open your browser and go to [http://127.0.0.1:8000/](http://127.0.0.1:8000/).
 
-The documentation will be in `docs/_build/html`
-
-If you do not have `make` use
+### Publishing the docs
+The docs are published on github pages. We use [mike](https://github.com/jimporter/mike)
+to deploy the docs to the `gh-pages` branch and to manage the versions of docs.
 
+For example, to deploy the version 2.0 of the docs to the `gh-pages` branch and make it the latest
+version, run:
 ```shell
-sphinx-build -b html docs docs/_build/html
+mike deploy -p -u 2.0 latest
 ```
+If you are not happy with the changes you can run `mike delete [version]`.
+All these mike operations will be recorded as git commits of branch `gh-pages`.
 
-To find undocumented Python objects run
+ `mike serve` is used to check all versions committed to branch `gh-pages`, which is for checking
+ the production website. If you have changes but not commit them yet, you should use `mkdocs serve`
+ instead of  `mike serve` to check them.
 
-```shell
-cd docs
-make coverage
-cat _build/coverage/python.txt
-```
-
-To [test snippets](https://www.sphinx-doc.org/en/master/usage/extensions/doctest.html) in documentation run
 
-```shell
-cd docs
-make doctest
-```
 
 ## Versioning
 

README.md

@@ -6,10 +6,10 @@
 | (2/5) license                      | [![github license badge](https://img.shields.io/github/license/NPLinker/nplinker)](https://github.com/NPLinker/nplinker) |
 | (3/5) community registry           | [![pypi badge](https://img.shields.io/pypi/v/nplinker.svg?color=blue)](https://pypi.python.org/project/nplinker/) ![Docker Image Version (latest by date)](https://img.shields.io/docker/v/nlesc/nplinker?arch=amd64&label=docker&sort=date)|
 | (4/5) citation                     | [![Zenodo](https://zenodo.org/badge/DOI/10.5281/zenodo.4680218.svg)](https://doi.org/10.5281/zenodo.4680218) |
-| (5/5) checklist                    | Coming soon |
+| (5/5) checklist                    | ![Static Badge](https://img.shields.io/badge/Coming_Soon-lightgrey) |
 | how FAIR is                          | [![fair-software badge](https://img.shields.io/badge/fair--software.eu-%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8F%20%20%E2%97%8B-yellow)](https://fair-software.eu) |
 | **Other best practices**           |  |
-| Documentation                      | [![Documentation Status](https://readthedocs.org/projects/nplinker/badge/?version=latest)](https://nplinker.readthedocs.io/en/latest/?badge=latest) |
+| Documentation                      | [![Static Badge](https://img.shields.io/badge/Docs_Available-lightgreen)](https://nplinker.github.io/nplinker) [🔗](https://nplinker.github.io/nplinker)|
 | Build & Test                       | [![build](https://github.com/NPLinker/nplinker/actions/workflows/build.yml/badge.svg)](https://github.com/NPLinker/nplinker/actions/workflows/build.yml) |
 | Static analysis                    | [![workflow scq badge](https://sonarcloud.io/api/project_badges/measure?project=NPLinker_nplinker&metric=alert_status)](https://sonarcloud.io/dashboard?id=NPLinker_nplinker) |
 | Coverage                           | [![workflow scc badge](https://sonarcloud.io/api/project_badges/measure?project=NPLinker_nplinker&metric=coverage)](https://sonarcloud.io/dashboard?id=NPLinker_nplinker) |
@@ -18,21 +18,21 @@
 
 
 # Natural Products Linker (NPLinker)
+NPLinker is a python framework for data mining microbial natural products by integrating genomics and metabolomics data.
 
-NPLinker aims to address the significant bottleneck that exists in the realization of the potential of genome-led metabolite discovery, namely the slow manual matching of predicted biosynthetic gene clusters (BGCs) with metabolites produced during bacterial culture; linking phenotype to genotype.
-
-NPLinker implements a new data-centric approach to alleviate this linking problem by searching for patterns of strain presence and absence between groups of similar spectra (molecular families; MF) and groups of similar BGCs (gene cluster families; GCF). Searches can be performed using a number of available analysis methods employed in isolation or together.
+Original paper: [Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions](https://doi.org/10.1371/journal.pcbi.1008920).
 
+## Setup and usage
 
-Currently available analysis methods (scoring methods):
-- **Metcalf** (standardised): see [Hjörleifsson Eldjárn G, et al. (2021)](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008920), [Doroghazi JR, et al. (2014)](https://www.nature.com/articles/nchembio.1659), and the [demo](notebooks/nplinker_demo1.ipynb).
-- **Rosetta**: see [Hjörleifsson Eldjárn G, et al. (2021)](https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008920) and [Soldatou S, et al. (2021)](https://www.mdpi.com/1660-3397/19/2/103).
-- **NPClassScore**: see the preprint [Louwen JJR, et al. (2022)](https://www.researchsquare.com/article/rs-1391827/v2), and the [demo](notebooks/npclassscore_linking/NPClassScore_demo.ipynb).
+### Requirement
+- Linux, MacOS, or Windows with WSL ([Windows Subsystem for Linux](https://learn.microsoft.com/en-us/windows/wsl/about)) enabled
+  - For Windows without WSL, please use the [docker image](https://hub.docker.com/r/nlesc/nplinker)
+- Python version ≥3.9
 
-## Setup and usage
 
+### Installation
 NPLinker is a Python package, you can install it as following:
-```
+```shell
 # create a new virtual environment
 python -m venv env
 source env/bin/activate
@@ -44,15 +44,12 @@ pip install nplinker
 install-nplinker-deps
 ```
 
-Due to hardware requirements of some non-pypi dependecies:
-- NPLinker can only be installed on `Linux` and `MacOS (Intel chip)`
-- `MacOS(Apple Silicon, M1/M2 chip)` user should execute the install commands in a [Rosseta-enabled terminal](https://support.apple.com/en-us/HT211861).
-- For `Windows` users, please use our [docker image](https://hub.docker.com/r/nlesc/nplinker).
-
+A virtual environment is *required* to install the the non-pypi dependencies. You can also use `conda`
+to manage python environments.
 
-See the example in [Jupyter notebook](notebooks/nplinker_demo1.ipynb) for a guided introduction to the NPLinker API which shows how to load and examine a dataset. Other notebooks are present showcasing other scoring methods, like for [NPClassScore](notebooks/npclassscore_linking/NPClassScore_demo.ipynb).
+### Usage
 
-If you want to visualize and manipulate NPLinker predictions, check [NPLinker Webapp](https://github.com/NPLinker/nplinker-webapp) for more info.
+See the [documentation](https://nplinker.github.io/nplinker) for more information about how to use NPLinker.
 
 ## Contributing
 

bin/install-nplinker-deps

@@ -150,8 +150,7 @@ echo "🔥 Start installing FastTree ..."
     fi
 echo -e "✅ FastTree installed successfully\n"
 
-#--- Install Hmmer (not support Windows and ARM64, required by BigScape)
-# brew hmmer not available ARM64 platform (e.g. Apple silicon)
+#--- Install Hmmer (required by BigScape)
 if ! command -v hmmpress &> /dev/null; then
     install_it hmmer
 fi

project_setup.md

@@ -7,19 +7,6 @@ text when the development of the software package takes off.
 For a quick reference on software development, we refer to [the software guide
 checklist](https://guide.esciencecenter.nl/#/best_practices/checklist).
 
-## Python versions
-
-This repository is set up with Python versions:
-
-- 3.6
-- 3.7
-- 3.8
-- 3.9
-
-
-Add or remove Python versions based on project requirements. See [the
-guide](https://guide.esciencecenter.nl/#/best_practices/language_guides/python) for more information about Python
-versions.
 
 ## Package management and dependencies
 
@@ -43,21 +30,15 @@ help you decide which tool to use for packaging.
 - The testing framework used is [PyTest](https://pytest.org)
   - [PyTest introduction](https://pythontest.com/pytest-book/)
   - PyTest is listed as a development dependency
-  - This is configured in `setup.cfg`
+  - This is configured in `pyproject.toml`
 - The project uses [GitHub action workflows](https://docs.github.com/en/actions) to automatically run tests on GitHub infrastructure against multiple Python versions
   - Workflows can be found in [`.github/workflows`](.github/workflows/)
 - [Relevant section in the guide](https://guide.esciencecenter.nl/#/best_practices/language_guides/python?id=testing)
 
 ## Documentation
 
-- Documentation should be put in the [`docs/`](docs/) directory. The contents have been generated using `sphinx-quickstart` (Sphinx version 1.6.5).
-- We recommend writing the documentation using Restructured Text (reST) and Google style docstrings.
-  - [Restructured Text (reST) and Sphinx CheatSheet](https://thomas-cokelaer.info/tutorials/sphinx/rest_syntax.html)
-  - [Google style docstring examples](http://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html).
-- The documentation is set up with the ReadTheDocs Sphinx theme.
-  - Check out its [configuration options](https://sphinx-rtd-theme.readthedocs.io/en/latest/).
-- [AutoAPI](https://sphinx-autoapi.readthedocs.io/) is used to generate documentation for the package Python objects.
-- `.readthedocs.yaml` is the ReadTheDocs configuration file. When ReadTheDocs is building the documentation this package and its development dependencies are installed so the API reference can be rendered.
+- Documentation should be put in the [`docs/`](docs/) directory.
+- We recommend writing the documentation using [MkDocs](https://www.mkdocs.org/) and [Google style docstrings](http://sphinxcontrib-napoleon.readthedocs.io/en/latest/example_google.html).
 - [Relevant section in the guide](https://guide.esciencecenter.nl/#/best_practices/language_guides/python?id=writingdocumentation)
 
 ## Coding style conventions and code quality
@@ -69,7 +50,7 @@ help you decide which tool to use for packaging.
 [Sonarcloud](https://sonarcloud.io/) is used to perform quality analysis and code coverage report
 
 - `sonar-project.properties` is the SonarCloud [configuration](https://docs.sonarqube.org/latest/analysis/analysis-parameters/) file
-- `.github/workflows/sonarcloud.yml` is the GitHub action workflow which performs the SonarCloud analysis
+- `.github/workflows/sonar-cloud.yml` is the GitHub action workflow which performs the SonarCloud analysis
 
 ## Package version number
 
@@ -80,7 +61,6 @@ help you decide which tool to use for packaging.
 ## Logging
 
 - We recommend using the logging module for getting useful information from your module (instead of using print).
-- The project is set up with a logging example.
 - [Relevant section in the guide](https://guide.esciencecenter.nl/#/best_practices/language_guides/python?id=logging)
 
 ## CHANGELOG.md