Package Recipe 'pridepy'

recipe pridepy

Python Client library for PRIDE Rest API

Homepage:: https://github.com/PRIDE-Archive/pridepy
License:: APACHE / Apache-2.0
Recipe:: /pridepy/meta.yaml

pridepy is a Python client library that enables users to download and search proteomics data from the PRIDE database. It supports multiple download protocols including FTP, Aspera, Globus, and S3.

package pridepy¶

Versions:

0.0.12-0

Depends:

on boto3 >=1.34.0,<2.0.0
on botocore >=1.34.0,<2.0.0
on click >=8.1.7,<9.0.0
on httpx >=0.27.0,<0.28.0
on python >=3.9
on ratelimit >=2.2.1,<3.0.0
on requests >=2.31.0,<3.0.0
on tqdm >=4.66.1,<5.0.0

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install pridepy

to add into an existing workspace instead, run:

pixi add pridepy

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install pridepy

Alternatively, to install into a new environment, run:

conda create -n envname pridepy

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/pridepy:<tag>

(see pridepy/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/pridepy/README.html)