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   / / /  \/_// / /   / / / \ \ \        \ \ \
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python-pynsee 0.1.8
Propagated dependencies: python-appdirs@1.4.4 python-openpyxl@3.1.5 python-pandas@3.0.3 python-platformdirs@4.3.6 python-pyarrow@24.0.0 python-requests@2.34.2 python-shapely@2.1.1 python-tqdm@4.67.1 python-unidecode@1.4.0 python-urllib3@2.7.0 python-xlrd@2.0.2
Channel: guix
Location: gnu/packages/python-science.scm (gnu packages python-science)
Home page: https://pynsee.readthedocs.io
Licenses: Expat
Build system: pyproject
Synopsis: Tools to Easily Search and Download French Data From INSEE and IGN APIs
Description:

This package provides tools to easily search and download French data from INSEE and IGN APIs. This data includes more than 150 000 macroeconomic series, a dozen datasets of local french data, numerous sources available on insee.fr, geographical limits of administrative areas taken from IGN as well as key metadata and SIRENE database containing data on all French compagnies.

python-peewee 3.18.2
Dependencies: sqlite@3.39.3
Channel: guix
Location: gnu/packages/databases.scm (gnu packages databases)
Home page: https://github.com/coleifer/peewee/
Licenses: Expat
Build system: pyproject
Synopsis: Small object-relational mapping utility
Description:

Peewee is a simple and small ORM (object-relation mapping) tool. Peewee handles converting between pythonic values and those used by databases, so you can use Python types in your code without having to worry. It has built-in support for sqlite, mysql and postgresql. If you already have a database, you can autogenerate peewee models using pwiz, a model generator.

python-pygmsh 7.1.17
Propagated dependencies: gmsh@4.15.2 python-meshio@5.3.5 python-numpy@2.4.6
Channel: guix
Location: gnu/packages/simulation.scm (gnu packages simulation)
Home page: https://github.com/nschloe/pygmsh
Licenses: GPL 3+
Build system: pyproject
Synopsis: Python frontend for Gmsh
Description:

The goal of pygmsh is to combine the power of Gmsh with the versatility of Python. The package generalises many of the methods and functions that comprise the Gmsh Python API. In this way the meshing of complex geometries using high-level abstractions is made possible. The package provides a Python library together with a command-line utility for mesh optimisation.

python-spisea 2.5
Propagated dependencies: python-astropy@8.0.1 python-matplotlib@3.10.9 python-numpy@2.4.6 python-pysynphot@2.0.0-1.a5e76c3 python-scipy@1.17.1
Channel: guix
Location: gnu/packages/astronomy.scm (gnu packages astronomy)
Home page: https://spisea.readthedocs.io/en/stable/index.html
Licenses: GPL 3+ Modified BSD
Build system: pyproject
Synopsis: Stellar Population Synthesis Modeling
Description:

SPISEA is an python package that generates single-age, single-metallicity populations (i.e. star clusters). It gives the user control over many parameters:

  • cluster characteristics (age, metallicity, mass, distance)

  • total extinction, differential extinction, and extinction law

  • stellar evolution and atmosphere models

  • stellar multiplicity and Initial Mass Function

  • initial-Final Mass Relation

  • photometric filters

python-sndata 1.3.0
Propagated dependencies: python-astropy@8.0.1 python-beautifulsoup4@4.14.3 python-numpy@2.4.6 python-pandas@3.0.3 python-pytz@2025.1 python-pyyaml@6.0.3 python-requests@2.34.2 python-sncosmo@2.13.0 python-tqdm@4.67.1
Channel: guix
Location: gnu/packages/astronomy.scm (gnu packages astronomy)
Home page: https://sndata.readthedocs.io/en/latest/
Licenses: GPL 3+
Build system: pyproject
Synopsis: Interface for data published by various supernova surveys
Description:

SNData provides an access to data releases published by a variety of supernova (SN) surveys. It is designed to support the development of scalable analysis pipelines that translate with minimal effort between and across data sets. A summary of accessible data is provided below. Access to additional surveys is added upon request or as needed for individual research projects undertaken by the developers.

python-meshio 5.3.5
Dependencies: python-h5py@3.16.0 python-netcdf4@1.7.4
Propagated dependencies: python-numpy@2.4.6 python-rich@15.0.0
Channel: guix
Location: gnu/packages/simulation.scm (gnu packages simulation)
Home page: https://github.com/nschloe/meshio
Licenses: Expat
Build system: pyproject
Synopsis: I/O for mesh files
Description:

There are various file formats available for representing unstructured meshes and mesh data. The meshio package is able to read and write mesh files in many formats and to convert files from one format to another. Formats such as cgns, h5m, gmsh, xdmf and vtk are supported. The package provides command-line tools and a collection of Python modules for programmatic use.

python-scvelo 0.3.3
Propagated dependencies: python-anndata@0.13.0rc3 python-loompy@3.0.8 python-matplotlib@3.10.9 python-numba@0.66.0 python-numpy@2.4.6 python-pandas@3.0.3 python-scanpy@1.12.2 python-scikit-learn@1.9.0 python-scipy@1.17.1 python-umap-learn@0.5.12 pybind11@2.13.6 python-hnswlib@0.8.0 python-igraph@0.11.8 python-louvain@0.16-0.def9179
Channel: guix
Location: gnu/packages/bioinformatics.scm (gnu packages bioinformatics)
Home page: https://scvelo.org
Licenses: Modified BSD
Build system: pyproject
Synopsis: RNA velocity generalized through dynamical modeling
Description:

ScVelo is a scalable toolkit for RNA velocity analysis in single cells. RNA velocity enables the recovery of directed dynamic information by leveraging splicing kinetics. scVelo generalizes the concept of RNA velocity by relaxing previously made assumptions with a stochastic and a dynamical model that solves the full transcriptional dynamics. It thereby adapts RNA velocity to widely varying specifications such as non-stationary populations.

python-onetbb 2023.1.0
Dependencies: onetbb@2023.1.0
Channel: guix
Location: gnu/packages/oneapi.scm (gnu packages oneapi)
Home page: https://uxlfoundation.github.io/oneTBB/
Licenses: ASL 2.0
Build system: cmake
Synopsis: Python bindings for the oneTBB parallel library
Description:

OneTBB is a C++ runtime library that abstracts the low-level threading details necessary for optimal multi-core performance. It uses common C++ templates and coding style to eliminate tedious threading implementation work. It provides parallel loop constructs, asynchronous tasks, synchronization primitives, atomic operations, and more. python-onetbb enables threading composability between two or more thread-enabled Python libraries.

python-corner 2.2.2
Propagated dependencies: python-matplotlib@3.10.9
Channel: guix
Location: gnu/packages/python-science.scm (gnu packages python-science)
Home page: http://corner.readthedocs.io/
Licenses: FreeBSD
Build system: pyproject
Synopsis: Make some beautiful corner plots
Description:

This Python module uses matplotlib to visualize multidimensional samples using a scatterplot matrix. In these visualizations, each one- and two-dimensional projection of the sample is plotted to reveal covariances. corner was originally conceived to display the results of Markov Chain Monte Carlo simulations and the defaults are chosen with this application in mind but it can be used for displaying many qualitatively different samples.

python-xarray 2026.04.0
Propagated dependencies: python-numpy@2.4.6 python-packaging@26.2 python-pandas@3.0.3 python-bottleneck@1.6.0 python-numba@0.66.0 python-scipy-minimal@1.17.1
Channel: guix
Location: gnu/packages/python-science.scm (gnu packages python-science)
Home page: https://github.com/pydata/xarray
Licenses: ASL 2.0
Build system: pyproject
Synopsis: N-D labeled arrays and datasets
Description:

Xarray (formerly xray) makes working with labelled multi-dimensional arrays simple, efficient, and fun!

Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.

python-tablib 3.9.0
Dependencies: python-tabulate@0.9.0
Propagated dependencies: python-markuppy@1.18 python-odfpy@1.4.2 python-openpyxl@3.1.5 python-pyyaml@6.0.3 python-xlrd@2.0.2 python-xlwt@1.3.0
Channel: guix
Location: gnu/packages/python-xyz.scm (gnu packages python-xyz)
Home page: https://tablib.readthedocs.io
Licenses: Expat
Build system: pyproject
Synopsis: Format agnostic tabular data library
Description:

tablib is a format-agnostic tabular dataset library, written in Python. Supported output formats are Excel (Sets + Books), JSON (Sets + Books), YAML (Sets + Books), HTML (Sets), Jira (Sets), TSV (Sets), ODS (Sets), CSV (Sets), and DBF (Sets).

tablib also supports Pandas DataFrames (Sets). Anyhow, since pandas is quite huge, this Guix package doesn't depend on pandas. In case, just also install python-pandas.

python-libcst 1.6.0
Dependencies: maturin@1.11.5
Propagated dependencies: python-pyyaml@6.0.3
Channel: guix
Location: gnu/packages/python-xyz.scm (gnu packages python-xyz)
Home page: https://github.com/Instagram/LibCST
Licenses: Expat Python Software Foundation License ASL 2.0
Build system: cargo
Synopsis: Concrete Syntax Tree (CST) parser and serializer library for Python
Description:

LibCST parses Python source code as a CST tree that keeps all formatting details (comments, whitespaces, parentheses, etc). It's useful for building automated refactoring (codemod) applications and linters. LibCST creates a compromise between an Abstract Syntax Tree (AST) and a traditional Concrete Syntax Tree (CST). By carefully reorganizing and naming node types and fields, LibCST creates a lossless CST that looks and feels like an AST.

python-debian 0.1.49
Propagated dependencies: python-six@1.17.0 python-chardet@5.2.0
Channel: guix
Location: gnu/packages/python-xyz.scm (gnu packages python-xyz)
Home page: https://salsa.debian.org/python-debian-team/python-debian
Licenses: GPL 3+
Build system: pyproject
Synopsis: Debian package related modules
Description:

This package provides Python modules that abstract many formats of Debian-related files, such as:

  • Debtags information;

  • debian/changelog files;

  • packages files, pdiffs;

  • control files of single or multiple RFC822-style paragraphs---e.g. debian/control, .changes, .dsc;

  • Raw .deb and .ar files, with (read-only) access to contained files and meta-information.

python2-numpy 1.8.2
Dependencies: bash@5.2.37 openblas@0.3.31
Channel: guix-past
Location: past/packages/python27.scm (past packages python27)
Home page: https://numpy.org
Licenses: Modified BSD
Build system: python-legacy
Synopsis: Fundamental package for scientific computing with Python
Description:

NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object, sophisticated (broadcasting) functions, tools for integrating C/C++ and Fortran code, useful linear algebra, Fourier transform, and random number capabilities. Version 1.8 is the last one to contain the numpy.oldnumeric API that includes the compatibility layer numpy.oldnumeric with NumPy's predecessor Numeric.

python-cdflib 1.3.12
Propagated dependencies: python-numpy@2.4.6
Channel: guix
Location: gnu/packages/astronomy.scm (gnu packages astronomy)
Home page: https://github.com/lasp/cdflib
Licenses: Expat
Build system: pyproject
Synopsis: Python library to deal with NASA's CDF astronmical data format
Description:

This package provides a Python CDF reader toolkit.

It provides the following functionality:

  • Ability to read variables and attributes from CDF files

  • Writes CDF version 3 files

  • Can convert between CDF time types (EPOCH/EPOCH16/TT2000) to other common time formats

  • Can convert CDF files into XArray Dataset objects and vice versa, attempting to maintain ISTP compliance

python-pyperf 2.10.0
Channel: guix
Location: gnu/packages/python-xyz.scm (gnu packages python-xyz)
Home page: https://github.com/psf/pyperf
Licenses: Expat
Build system: pyproject
Synopsis: Toolkit for running Python benchmarks
Description:

The Python pyperf module is a toolkit for writing, running and analyzing benchmarks. It features a simple API that can:

  • automatically calibrate a benchmark for a time budget;

  • spawn multiple worker processes;

  • compute the mean and standard deviation;

  • detect if a benchmark result seems unstable;

  • store benchmark results in JSON format;

  • support multiple units: seconds, bytes and integer.

python-deepmd 3.1.2
Propagated dependencies: python-array-api-compat@1.12.0 python-h5py@3.16.0 python-mendeleev@1.2.0 python-numpy@2.4.6 python-scipy@1.17.1 python-pygments@2.19.2 python-pyyaml@6.0.3 python-dargs@0.4.10 python-typing-extensions@4.15.0 python-importlib-metadata@8.7.0 python-h5py@3.16.0 python-wcmatch@10.1 python-packaging@26.2 python-ml-dtypes@0.5.4 python-mendeleev@1.2.0 python-array-api-compat@1.12.0
Channel: guix-science
Location: guix-science/packages/chemistry.scm (guix-science packages chemistry)
Home page: https://deepmodeling.com/
Licenses: LGPL 3+
Build system: pyproject
Synopsis: Deep learning package for molecular dynamics
Description:

DeePMD-kit is a package written in Python/C++, designed to minimize the effort required to build deep learning-based model of interatomic potential energy and force field and to perform molecular dynamics (MD). This brings new hopes to addressing the accuracy-versus-efficiency dilemma in molecular simulations. Applications of DeePMD-kit span from finite molecules to extended systems and from metallic systems to chemically bonded systems.

python-jaxopt 0.8.5
Propagated dependencies: python-dm-tree@0.1.9 python-jax@0.4.28 python-jaxlib@0.4.28 python-optax@0.1.5 python-numpy@2.4.6 python-scipy@1.17.1
Channel: guix-science
Location: guix-science/packages/python.scm (guix-science packages python)
Home page: https://github.com/google/jaxopt
Licenses: ASL 2.0
Build system: pyproject
Synopsis: Hardware accelerated, batchable and differentiable optimizers in JAX
Description:

JAXopt provides hardware accelerated, batchable and differentiable optimizers in JAX.

  1. Hardware accelerated: the implementations run on GPU and TPU, in addition to CPU.

  2. Batchable: multiple instances of the same optimization problem can be automatically vectorized using JAX’s vmap.

  3. Differentiable: optimization problem solutions can be differentiated with respect to their inputs either implicitly or via autodiff of unrolled algorithm iterations.

python-nbdime 4.0.2
Propagated dependencies: python-colorama@0.4.6 python-gitpython@3.1.44 python-jinja2@3.1.6 python-jupyter-server@2.17.0 python-jupyter-server-mathjax@0.2.6 python-nbformat@5.10.4 python-pygments@2.19.2 python-requests@2.34.2 python-tornado@6.4.2
Channel: guix
Location: gnu/packages/jupyter.scm (gnu packages jupyter)
Home page: https://nbdime.readthedocs.io
Licenses: Modified BSD
Build system: pyproject
Synopsis: Diff tools for Jupyter Notebooks
Description:

nbdime provides tools for diffing and merging of Jupyter Notebooks. It includes the following commands:

nbdiff compare notebooks in a terminal-friendly way
nbmerge three-way merge of notebooks with automatic conflict resolution
nbdiff-web rich rendered diff of notebooks
nbmerge-web web-based three-way merge tool for notebooks

nbshow present a single notebook in a terminal-friendly way

python-psutil 7.2.2
Channel: guix
Location: gnu/packages/python-xyz.scm (gnu packages python-xyz)
Home page: https://github.com/giampaolo/psutil
Licenses: Modified BSD
Build system: pyproject
Synopsis: Library for retrieving information on running processes
Description:

psutil (Python system and process utilities) is a library for retrieving information on running processes and system utilization (CPU, memory, disks, network) in Python. It is useful mainly for system monitoring, profiling and limiting process resources and management of running processes. It implements many functionalities offered by command line tools such as: ps, top, lsof, netstat, ifconfig, who, df, kill, free, nice, ionice, iostat, iotop, uptime, pidof, tty, taskset, pmap.

python-fitsio 1.4.2
Dependencies: curl@8.20.0 cfitsio@4.7.0 zlib@1.3.1
Propagated dependencies: python-numpy@2.4.6
Channel: guix
Location: gnu/packages/astronomy.scm (gnu packages astronomy)
Home page: https://github.com/esheldon/fitsio
Licenses: GPL 2+
Build system: pyproject
Synopsis: Python library to read from and write to FITS files
Description:

This package provides a Python library for reading from and writing to FITS files using the CFITSIO library. Among other things, it can

  • read and write image, binary, and ascii table extensions;

  • read arbitrary subsets of tables in a lazy manner;

  • query the rows and columns of a table;

  • read and write header keywords;

  • read and write Gzip files.

python-stdnum 2.1
Channel: guix
Location: gnu/packages/finance.scm (gnu packages finance)
Home page: https://arthurdejong.org/python-stdnum/
Licenses: LGPL 2.1+
Build system: pyproject
Synopsis: Python module to handle standardized number and code formats
Description:

This is a Python library that aims to provide functions to handle, parse and validate standard numbers. The module supports more than 100 different number formats amongst which a great number of VAT and other tax numbers, personal identity and company identification codes, international standard numbers (ISBN, IBAN, EAN, etc.) and various other formats. The module also includes implementations of the Verhoeff, Luhn and family of ISO/IEC 7064 check digit algorithms.

python-cobaya 3.6.2-0.b76b6fe
Propagated dependencies: python-dill@0.4.1 python-fuzzywuzzy@0.18.0 python-getdist@1.5.4 python-numpy@2.4.6 python-packaging@26.2 python-pandas@3.0.3 python-portalocker@2.7.0 python-py-bobyqa@1.5.0 python-pyyaml@6.0.3 python-requests@2.34.2 python-scipy@1.17.1 python-tqdm@4.67.1 python-typing-extensions@4.15.0 python-matplotlib@3.10.9 python-mpi4py@4.1.0 python-numba@0.66.0 python-pyside-6@6.9.2
Channel: guix
Location: gnu/packages/astronomy.scm (gnu packages astronomy)
Home page: https://github.com/CobayaSampler/cobaya
Licenses: LGPL 3+
Build system: pyproject
Synopsis: Code for Bayesian analysis in Cosmology
Description:

Cobaya, and Spanish for Guinea Pig) is a framework for sampling and statistical modelling: it allows you to explore an arbitrary prior or posterior using a range of Monte Carlo samplers (including the advanced MCMC sampler from CosmoMC, and the advanced nested sampler PolyChord). The results of the sampling can be analysed with GetDist. It supports MPI parallelization (and very soon HPC containerization with Docker/Shifter and Singularity).

python-pylint 4.0.8
Propagated dependencies: python-astroid@4.0.4 python-dill@0.4.1 python-isort@9.0.1 python-mccabe@0.7.0-0.292b5c7 python-platformdirs@4.3.6 python-tomlkit@0.15.0
Channel: guix
Location: gnu/packages/check.scm (gnu packages check)
Home page: https://github.com/pylint-dev/pylint
Licenses: GPL 2+
Build system: pyproject
Synopsis: Advanced Python code static checker
Description:

Pylint is a Python source code analyzer which looks for programming errors, helps enforcing a coding standard and sniffs for some code smells (as defined in Martin Fowler's Refactoring book).

Pylint has many rules enabled by default, way too much to silence them all on a minimally sized program. It's highly configurable and handle pragmas to control it from within your code. Additionally, it is possible to write plugins to add your own checks.

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