conda-forge / packages

Package Name Access Summary Updated
qca public Qt Cryptographic Architecture (QCA) provides a straightforward and cross-platform crypto API, using Qt datatypes and conventions. 2019-06-25
python-lalburst public LSC Algorithm Burst Library 2019-06-25
lalburst public LSC Algorithm Burst Library 2019-06-25
paramiko public SSH2 protocol library 2019-06-25
magpylib public A simple, user friendly Python 3 toolbox for calculating magnetic fields from permanent magnets and current distributions. 2019-06-25
rpcq public The RPC framework and message specification for Rigetti QCS 2019-06-25
uproot public ROOT I/O in pure Python and Numpy. 2019-06-25
uproot-base public ROOT I/O in pure Python and Numpy. 2019-06-25
msrest public AutoRest swagger generator Python client runtime. 2019-06-25
miniwdl public A static analysis toolkit for the Workflow Description Language 2019-06-25
orange3-singlecell public Single-cell Orange 2019-06-24
botocore public Low-level, data-driven core of boto 3. 2019-06-24
conda public OS-agnostic, system-level binary package and environment manager. 2019-06-24
newrelic public New Relic Python Agent 2019-06-24
imagemagick public Software suite to create, edit, compose, or convert bitmap images. 2019-06-24
statsmodels public Statistical computations and models for use with SciPy 2019-06-24
python-dotenv public Get and set values in your .env file in local and production servers like Heroku does. 2019-06-24
wakatime public Common interface to the WakaTime api. 2019-06-24
vdom public VDOM for Python 2019-06-24
sphinx_gmt public Sphinx extensions for the Generic Mapping Tools 2019-06-24
libnl-cos6-x86_64 public (CDT) Convenience library for kernel netlink sockets 2019-06-24
r-ggstance public A 'ggplot2' extension that provides flipped components: horizontal versions of 'Stats' and 'Geoms', and vertical versions of 'Positions'. 2019-06-24
r-coop public Fast implementations of the co-operations: covariance, correlation, and cosine similarity. The implementations are fast and memory-efficient and their use is resolved automatically based on the input data, handled by R's S3 methods. Full descriptions of the algorithms and benchmarks are available in the package vignettes. 2019-06-24
r-coranking public Calculates the co-ranking matrix to assess the quality of a dimensionality reduction. 2019-06-24
r-coxme public Cox proportional hazards models containing Gaussian random effects, also known as frailty models. 2019-06-24
r-plotly public Create interactive web graphics from 'ggplot2' graphs and/or a custom interface to the (MIT-licensed) JavaScript library 'plotly.js' inspired by the grammar of graphics. 2019-06-24
xpdan public Analysis Tools for XPD 2019-06-24
pydda public Pythonic Direct Data Assimilation 2019-06-24
pylbm public A flexible Python package for lattice Boltzmann method 2019-06-24
conda-package-handling public Create and extract conda packages of various formats 2019-06-24
qgis public A free and open source Geographic Information System (GIS). 2019-06-24
ibis-framework public Productivity-centric Python Big Data Framework 2019-06-24
gsoap public The most advanced C/C++ autocoding tools for XML Web service APIs and other XML applications 2019-06-24
http3 public The next generation HTTP client. 2019-06-24
simpleeval public A simple, safe single expression evaluator library. 2019-06-24
tabulator public Consistent interface for stream reading and writing tabular data (csv/xls/json/etc) 2019-06-24
pango public Text layout and rendering engine. 2019-06-24
mypy public Optional static typing for Python 2019-06-24
climlab public Python package for process-oriented climate modeling 2019-06-24
glue-core public Multi-dimensional linked data exploration 2019-06-24
pyproj public Python interface to PROJ.4 library 2019-06-24
r-gggenes public Provides a 'ggplot2' geom and helper functions for drawing gene arrow maps. 2019-06-24
gpi public GPI - Graphical Programming Interface Development Framework 2019-06-24
glue-vispy-viewers public 3D viewers for Glue based on Vispy 2019-06-24
r-lime public When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>. 2019-06-24
harfbuzz public An OpenType text shaping engine. 2019-06-24
typing-extensions public Backported and Experimental Type Hints for Python 2019-06-24
asammdf public ASAM MDF measurement data file parser 2019-06-24
paramtools public Library for parameter processing and validation with a focus on computational modeling projects 2019-06-24
kitty public A cross-platform, fast, feature full, GPU based terminal emulator 2019-06-24
PRIVACY POLICY  |  EULA (Anaconda Cloud v2.33.29) © 2019 Anaconda, Inc. All Rights Reserved.