recipe python-edlib

Lightweight, super fast C/C++ (& Python) library for sequence alignment using edit (Levenshtein) distance.

Homepage:

https://github.com/Martinsos/edlib

License:

MIT / MIT License

Recipe:

/python-edlib/meta.yaml

package python-edlib

(downloads) docker_python-edlib

versions:
1.3.9-4,  1.3.9-3,  1.3.9-2,  1.3.9-1,  1.3.9-0,  1.3.8.post2-1,  1.3.8.post2-0,  1.3.8.post1-2,  1.3.8.post1-1, 

1.3.9-4,  1.3.9-3,  1.3.9-2,  1.3.9-1,  1.3.9-0,  1.3.8.post2-1,  1.3.8.post2-0,  1.3.8.post1-2,  1.3.8.post1-1,  1.3.8.post1-0,  1.3.7-0,  1.3.6-0,  1.3.5-0,  1.3.4-0,  1.2.4.post1-0,  1.2.4-0,  1.2.3.post1-0,  1.2.3-1,  1.2.3-0

depends libgcc-ng:

>=12

depends libstdcxx-ng:

>=12

depends python:

>=3.10,<3.11.0a0

depends python_abi:

3.10.* *_cp310

requirements:

Installation

You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install python-edlib

and update with::

   mamba update python-edlib

To create a new environment, run:

mamba create --name myenvname python-edlib

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull quay.io/biocontainers/python-edlib:<tag>

(see `python-edlib/tags`_ for valid values for ``<tag>``)

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Link to this page

Render an install-with-bioconda badge with the following MarkDown:

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