Biopython VS bioconda-recipes

Compare Biopython vs bioconda-recipes and see what are their differences.

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Biopython bioconda-recipes
31 5
4,120 1,552
4.6% 0.8%
9.6 10.0
about 23 hours ago 7 days ago
Python Shell
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Biopython

Posts with mentions or reviews of Biopython. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-05-12.

bioconda-recipes

Posts with mentions or reviews of bioconda-recipes. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-24.
  • Why should academic researchers use Rust?
    3 projects | /r/rust | 24 Feb 2023
    Rust makes distribution and maintenance near trivial. My lab develops a fairly widely-used tool, salmon, for the quantification of transcript expression from RNA-seq data. This tool is written in C++14, and has a substantial number of dependencies. The process of updating the tool (e.g. bumping dependencies) and cutting a new release is painful. To maintain widespread availability, we distribute this tool using bioconda which uses it's own CI and setup to build new releases for (in our case) Linux and MacOS. Things break all the time. For example, recently, they bumped the compiler used to build packages. This changed some default "implementation defined" behavior, causing previously functioning code to fail. We didn't find this locally, because we didn't test that specific compiler version. When we tried to release a new version, we had to go back and fix things etc. This is not just because different compilers exist, but because the C++ specification is soooo complicated and the set of undefined and implementation defined behavior is sooo broad that it's very brittle and it's easy for things to "break" via bitrot. However, the stability provided by Rust has been phenomenal so far. In our code, we only use stable Rust features, and we have benefited tremendously from the empirical guarantee that valid Rust code (except in exceptional cases like latent bugs in the language) will remain valid. While not all crates follow it religiously, there is a reasonable respect for semantic versioning. Thus, cutting a new release of one of our Rust tools is often as simple as just updating the Cargo.toml (and Cargo.lock in the case of applications), tagging a new release in GitHub, and letting the bioconda CI do it's business with the tagged artifacts. The build "scripts" are almost always trivial because the builds just work, across platforms, across CIs, etc. Now, new projects like cargo dist look like they make this process even simpler.
  • Software engineers: consider working on genomics
    6 projects | news.ycombinator.com | 19 Nov 2022
    I contribute to Nextflow core (https://nf-co.re/) It's more of a collection of pipelines than traditional software, but there are users all around the world and a good community.

    Most of the packages on bioconda (https://bioconda.github.io/) are open source. But you probably want to find a sub-field that interests you most before finding a project.

    In grad school, we also had an ex-google software engineer volunteer with us one day a week. It was very impactful for many members of the lab to learn good engineering practices, and it wasn't at all like the sentiment others in this thread are expressing where engineers were "janitors".

  • How to mix separated versions of Python in the cleanest way
    4 projects | /r/devops | 25 Sep 2021
    In my world (research science) we usually use anaconda, which is just a slightly higher-level wrapper around python virtual envs. But they also maintain more repositories of various modules that scientists need. e.g. https://bioconda.github.io/
  • Seq: A programming language for high-performance computational genomics
    9 projects | news.ycombinator.com | 15 Sep 2021
    Seems like there's a conda packaging on the works: https://github.com/bioconda/bioconda-recipes/pull/29660

What are some alternatives?

When comparing Biopython and bioconda-recipes you can also consider the following projects:

RDKit - The official sources for the RDKit library

biotite - A comprehensive library for computational molecular biology

Numba - NumPy aware dynamic Python compiler using LLVM

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

PyDy - Multibody dynamics tool kit.

weblogo - WebLogo 3: Sequence Logos redrawn

statsmodels - Statsmodels: statistical modeling and econometrics in Python

bccb - Incubator for useful bioinformatics code, primarily in Python and R

bcbio-nextgen - Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

SciPy - SciPy library main repository

Dask - Parallel computing with task scheduling

PatZilla - PatZilla is a modular patent information research platform and data integration toolkit with a modern user interface and access to multiple data sources.