diff --git a/README.md b/README.md index 69b1778..2aff888 100644 --- a/README.md +++ b/README.md @@ -37,6 +37,11 @@ The GUI of AlphaMap is a completely stand-alone tool that requires no knowledge AlphaMap can be installed in an existing Python 3.8 environment with a single `bash` command. *This `bash` command can also be run directly from within a Jupyter notebook by prepending it with a `!`*. +```bash +pip install alphamap[stable] +``` +The [stable] tag ensures you get the latest stable release with fixed dependencies. However, it can be omitted if you prefer more flexible dependency versions: + ```bash pip install alphamap ``` @@ -44,7 +49,7 @@ pip install alphamap When a new version of AlphaMap becomes available, the old version can easily be upgraded by running e.g. the command again with an additional `--upgrade` flag: ```bash -pip install alphamap --upgrade +pip install --upgrade alphamap[stable] ``` NOTE: When installing with `pip`, UniProt information is not included. Upon first usage of a specific Organism, its information will be automatically downloaded from UniProt. @@ -71,11 +76,13 @@ For any Python package, it is highly recommended to use a [conda virtual environ ```bash conda create -n alphamap python=3.8 -y conda activate alphamap -pip install -e . +pip install -e ".[stable]" ``` * By using the editable flag `-e`, all modifications to the AlphaMap [source code folder](alphamap) are directly reflected when running AlphaMap. Note that the AlphaMap folder cannot be moved and/or renamed if an editable version is installed. +* The [stable] tag ensures you get the latest stable release with fixed dependencies. However, it can be omitted if you prefer more flexible dependency versions. + * When using Jupyter notebooks and multiple conda environments direcly from the terminal, it is recommended to `conda install nb_conda_kernels` in the conda base environment. Hereafter, running a `jupyter notebook` from the conda base environment should have a `python [conda env: alphamap]` kernel available, in addition to all other conda kernels in which the command `conda install ipykernel` was run.