This package provides a Python framework for building reactive web-apps. Developed by Plotly.
This package provides a Python port of the fzy fuzzy string matching algorithm.
This package provides a Python framework for building reactive web-apps. Developed by Plotly.
The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt.
Provides an abstraction layer on top of the various Qt bindings (PyQt5, PyQt4 and PySide) and additional custom QWidgets.
This is a Python package for rendering rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal.
This is a Python package for rendering rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal.
Toil is a scalable, efficient, cross-platform pipeline management system, written entirely in Python, and designed around the principles of functional programming.
The Advanced Scientific Data Format (ASDF) is a next-generation interchange format for scientific data. This package contains the Python implementation of the ASDF Standard.
This Python package provides a collection of object-oriented and procedural interfaces for working with matrices, quaternions, vectors and plane/line/ray objects for 3D graphics.
rpy2 is a redesign and rewrite of rpy. It is providing a low-level interface to R from Python, a proposed high-level interface, including wrappers to graphical libraries, as well as R-like structures and functions.
Jedi is a static analysis tool for Python that can be used in Integrated Development Environments (IDEs) and text editors. It understands Python on a deeper level than many other static analysis frameworks for Python.
Jedi understands docstrings and you can use Jedi autocompletion in your REPL as well.
The h5py package provides both a high- and low-level interface to the HDF5 library from Python. The low-level interface is intended to be a complete wrapping of the HDF5 API, while the high-level component supports access to HDF5 files, datasets and groups using established Python and NumPy concepts.
The h5py package provides both a high- and low-level interface to the HDF5 library from Python. The low-level interface is intended to be a complete wrapping of the HDF5 API, while the high-level component supports access to HDF5 files, datasets and groups using established Python and NumPy concepts.
pixy is a command-line tool for painlessly estimating average nucleotide diversity within (π) and between (dxy) populations from a VCF. In particular, pixy facilitates the use of VCFs containing invariant (monomorphic) sites, which are essential for the correct computation of π and dxy in the face of missing data (i.e. always).
Python implementation of the Tensor Train (TT) toolbox. It contains several important packages for working with the TT-format in Python. It is able to do TT-interpolation, solve linear systems, eigenproblems, solve dynamical problems. Several computational routines are done in Fortran (which can be used separately), and are wrapped with the f2py tool.
Chex is a library of utilities for helping to write reliable JAX code. This includes utils to help:
Instrument your code (e.g. assertions)
Debug (e.g. transforming
pmapsinvmapswithin a context manager).Test JAX code across many
variants(e.g. jitted vs non-jitted).
Generalized World Coordinate System (GWCS) is an Astropy affiliated package providing tools for managing the World Coordinate System of astronomical data.
GWCS takes a general approach to the problem of expressing transformations between pixel and world coordinates. It supports a data model which includes the entire transformation pipeline from input coordinates (detector by default) to world coordinates.
Dask is a flexible parallel computing library for analytics. It consists of two components: dynamic task scheduling optimized for computation, and large data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers.
Dask is a flexible parallel computing library for analytics. It consists of two components: dynamic task scheduling optimized for computation, and large data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers.
Six is a Python 2 and 3 compatibility library. It provides utility functions for smoothing over the differences between the Python versions with the goal of writing Python code that is compatible on both Python versions. Six supports every Python version since 2.5. It is contained in only one Python file, so it can be easily copied into your project.
gcvb (generate compute validate benchmark) is a Python 3 module aiming at facilitating non-regression, validation and benchmarking of simulation codes. gcvb is not a complete tool of continuous integration (CI). It is rather a component of the testing part of a CI workflow. It can compare the different metrics of your computation with references that can be a file, depends of the 'configuration' or are absolute.
To prevent Python from decoding and canonicalizing line endings and thus preventing detection, binary mode is used for opening, which means that byte strings are read instead of normal strings. Currently read is used and a loop. This doesn't hide the underlying workings and is hence useful to explain the workings of, but nicer code could probably be written using iterator based operations like drop_while.
Fypp is a Python powered preprocessor. It can be used for any programming languages but its primary aim is to offer a Fortran preprocessor, which helps to extend Fortran with condititional compiling and template metaprogramming capabilities. Instead of introducing its own expression syntax, it uses Python expressions in its preprocessor directives, offering the consistency and versatility of Python when formulating metaprogramming tasks. It puts strong emphasis on robustness and on neat integration into developing toolchains.