conda-forge / packages

Package Name Access Summary Updated
libcdms public Climate Data Management System library 2019-09-19
pystan public Python interface to Stan, a package for Bayesian inference 2019-09-19
pyccl public DESC Core Cosmology Library: cosmology routines with validated numerical accuracy 2019-09-19
libdrs public Data Retrieval and Storage DRS software Fortran library 2019-09-19
ldas-tools-ldasgen public Filters library used by ldas-tools 2019-09-19
jdatetime public Jalali datetime binding for python 2019-09-19
celery-eternal public Celery task subclass for jobs that should run forever 2019-09-19
snuggs public Snuggs are s-expressions for NumPy 2019-09-19
dash-core-components public Dash UI core component suite 2019-09-19
fsspec public A specification for pythonic filesystems 2019-09-19
python-pegasus-wms public This package contains the Python APIs for Pegasus WMS 2019-09-19
pygcn public Anonymous VOEvent client for receiving GCN/TAN notices in XML format 2019-09-19
python-nds2-client public Python extensions for NDS2 2019-09-19
nds2-client-swig public NDS2 Client interface SWIG wrappings 2019-09-19
weasyprint public WeasyPrint converts web documents (HTML with CSS, SVG, …) to PDF 2019-09-19
packaging public Core utilities for Python packages 2019-09-19
multinest public MultiNest is a Bayesian inference tool which calculates the evidence and explores the parameter space which may contain multiple posterior modes and pronounced (curving) degeneracies in moderately high dimensions. 2019-09-19
triangle public A Two-Dimensional Quality Mesh Generator and Delaunay Triangulator. 2019-09-19
gst-orc public Optimized Inner Loop Runtime Compiler 2019-09-19
piranha public The Piranha computer algebra system. 2019-09-19
lscsoft-glue public Grid LSC User Engine 2019-09-19
ligo-segments public Representations of semi-open intervals 2019-09-19
ligo-common public Base package for `ligo` python namespace 2019-09-19
cpnest public CPNest: Parallel nested sampling 2019-09-19
dakota public The Dakota project delivers software for optimization and uncertainty quantification. 2019-09-19
gstlal public GSTLAL 2019-09-19
plyfile public NumPy-based text/binary PLY file reader/writer for Python 2019-09-19
r-swagger public A collection of 'HTML', 'JavaScript', and 'CSS' assets that dynamically generate beautiful documentation from a 'Swagger' compliant API: <https://swagger.io/specification/>. 2019-09-19
flask-rest-api public DB agnostic framework to build auto-documented REST APIs with Flask and marshmallow 2019-09-19
celery-singleton public Prevent duplicate celery tasks 2019-09-19
hyperion-fortran public Hyperion Radiation Transfer Code 2019-09-19
mpich-mpifort public A high performance widely portable implementation of the MPI standard. 2019-09-19
mpich-mpicxx public A high performance widely portable implementation of the MPI standard. 2019-09-19
mpich-mpicc public A high performance widely portable implementation of the MPI standard. 2019-09-19
mpich public A high performance widely portable implementation of the MPI standard. 2019-09-19
keras public Deep Learning for Python 2019-09-19
tqdm public A Fast, Extensible Progress Meter 2019-09-19
mplleaflet public Convert Matplotlib plots into Leaflet web maps 2019-09-19
koalas public pandas API on Apache Spark 2019-09-19
momepy public Urban Morphology Measuring Toolkit for Python 2019-09-19
fsleyes-props public [wx]Python event programming framework 2019-09-19
ripgrep public ripgrep recursively searches directories for a regex pattern 2019-09-19
pygeos public Wraps GEOS geometry functions in numpy ufuncs 2019-09-19
progressbar2 public A Python Progressbar library to provide visual (yet text based) progress to long running operations. 2019-09-19
r-mlrmbo public Flexible and comprehensive R toolbox for model-based optimization ('MBO'), also known as Bayesian optimization. It implements the Efficient Global Optimization Algorithm and is designed for both single- and multi- objective optimization with mixed continuous, categorical and conditional parameters. The machine learning toolbox 'mlr' provide dozens of regression learners to model the performance of the target algorithm with respect to the parameter settings. It provides many different infill criteria to guide the search process. Additional features include multi-point batch proposal, parallel execution as well as visualization and sophisticated logging mechanisms, which is especially useful for teaching and understanding of algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that single components can be easily replaced or adapted by the user for specific use cases. 2019-09-19
r-catboost public CatBoost is a machine learning algorithm that uses gradient boosting on decision trees. It is available as an open source library. 2019-09-19
pyxrf public X-ray Fluorescence Fitting GUI 2019-09-19
git-secret public git-secret stores your private data inside a git repo 2019-09-19
terragrunt public Terragrunt is a thin wrapper for Terraform that provides extra tools for working with multiple Terraform modules. 2019-09-19
catboost public Gradient boosting on decision trees library 2019-09-19
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