This is the continuation of the official Discogs API client for Python. It enables you to query the Discogs database for information on artists, releases, labels, users, Marketplace listings,and more. It also supports OAuth 1.0a authorization, which allows you to change user data such as profile information, collections and wantlists,inventory, and orders.

Flask-RESTX is an extension for Flask that adds support for quickly building REST APIs. Flask-RESTX encourages best practices with minimal setup. If you are familiar with Flask, Flask-RESTX should be easy to pick up. It provides a coherent collection of decorators and tools to describe your API and expose its documentation properly using Swagger.

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well. The execution units, called tasks, are executed concurrently on a single or more worker servers using multiprocessing, Eventlet, or gevent. Tasks can execute asynchronously (in the background) or synchronously (wait until ready).

Python-keystoneclient is the identity service used by OpenStack for authentication (authN) and high-level authorization (authZ). It currently supports token-based authN with user/service authZ, and is scalable to support OAuth, SAML, and OpenID in future versions. Out of the box, Keystone uses SQLite for its identity store database, with the option to connect to external LDAP.

This package provides a similar in functionality to the astropy.coordinates module, but with more of an emphasis on efficiency. Some functions are more than 100 times faster than the corresponding functionality in astropy. On the other hand, the API is somewhat more restrictive than the API used by astropy, so the appropriate module to use will depend on your needs.

The Apache HTTP Server Project is a collaborative software development effort aimed at creating a robust, commercial-grade, featureful, and freely-available source code implementation of an HTTP (Web) server. The project is jointly managed by a group of volunteers located around the world, using the Internet and the Web to communicate, plan, and develop the server and its related documentation.

This package implements the Louvain algorithm for community detection in C++ and exposes it to Python. Besides the relative flexibility of the implementation, it also scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The core function is find_partition which finds the optimal partition using the louvain algorithm for a number of different methods.

This package implements the Louvain algorithm for community detection in C++ and exposes it to Python. Besides the relative flexibility of the implementation, it also scales well, and can be run on graphs of millions of nodes (as long as they can fit in memory). The core function is find_partition which finds the optimal partition using the louvain algorithm for a number of different methods.

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.

This software allows you to verify wheel filenames and parse them into their component fields.

This package adheres strictly to the standard, with the following exceptions:

• Version components may be any sequence of the relevant set of characters; they are not verified for PEP 440 compliance.

• The .whl file extension is matched case-insensitively.

Wsgi_intercept installs a WSGI application in place of a real URI for testing. Testing a WSGI application normally involves starting a server at a local host and port, then pointing your test code to that address. Instead, this library lets you intercept calls to any specific host/port combination and redirect them into a WSGI application importable by your test program. Thus, you can avoid spawning multiple processes or threads to test your Web app.

PypeIt is a Python package for semi-automated reduction of astronomical spectroscopic data. Its algorithms build on decades-long development of previous data reduction pipelines by the developers.

It is designed to be used by both advanced spectroscopists with prior data reduction expertise and astronomers with no prior experience of data reduction. It is highly configurable and designed to be applied to any standard slit-imaging spectrograph, including long-slit, multi-slit, as well as cross-dispersed echelle spectra.

Dijitso provides a core component of the FEniCS framework, namely the just-in-time compilation of C++ code that is generated from Python modules. It is called from within a C++ library, using ctypes to import the dynamic shared library directly.

As long as the compiled code can provide a simple factory function to a class implementing a predefined C++ interface, there is no limit to the complexity of that interface. Parallel support depends on the mpi4py interface.

This library implements both server and client aspects of the the WebSocket protocol, striving for safety, correctness, and ergonomics. It is based on the wsproto project, which is a Sans-IO state machine that implements the majority of the WebSocket protocol, including framing, codecs, and events. This library handles I/O using the Trio framework.

python-beautifultable provides a class for easily printing tabular data in a visually appealing ASCII format to a terminal.

Features include, but are not limited to:

• Full customization of the look and feel of the table

• Row and column accessors.

• Full support for colors using ANSI sequences or any library.

• Plenty of predefined styles and option to create custom ones.

• Support for Unicode characters.

• Supports streaming table when data is slow to retrieve.

ndcube is a package for manipulating, inspecting and visualizing multi-dimensional contiguous and non-contiguous coordinate-aware data arrays.

It combines data, uncertainties, units, metadata, masking, and coordinate transformations into classes with unified slicing and generic coordinate transformations and plotting/animation capabilities. It is designed to handle data of any number of dimensions and axis types (e.g. spatial, temporal, spectral, etc.) whose relationship between the array elements and the real world can be described by WCS translations.

The fast-histogram mini-package aims to provide simple and fast histogram functions for regular bins that don't compromise on performance. It doesn't do anything complicated - it just implements a simple histogram algorithm in C and keeps it simple. The aim is to have functions that are fast but also robust and reliable. The result is a 1D histogram function here that is 7-15x faster than numpy.histogram, and a 2D histogram function that is 20-25x faster than numpy.histogram2d.

python-dolfin-adjoint is a solver of differential equations associated with a governing system and a functional of interest. Working from the forward model the solver automatically derives the discrete adjoint and tangent linear models. These additional models are key ingredients in many algorithms such as data assimilation, optimal control, sensitivity analysis, design optimisation and error estimation. The dolfin-adjoint project provides the necessary tools and data structures for cases where the forward model is implemented in fenics or firedrake.

The strict_rfc3339 Python module provides strict, simple, lightweight RFC3339 (Date and Time on the Internet: Timestamps) procedures.

It enables or aims to:

• Convert UNIX timestamps to and from RFC3339.

• Produce RFC3339 strings with a UTC offset (Z) or with the offset that the C time module reports is the local timezone offset.

• Be simple with minimal dependencies/libraries.

• Avoid timezones as much as possible.

• Be very strict and follow RFC3339.

Sekizai means blocks in Japanese, and that is what this app provides. A fresh look at blocks. With django-sekizai you can define placeholders where your blocks get rendered and at different places in your templates append to those blocks. This is especially useful for css and javascript. Your subtemplates can now define css and javascript files to be included, and the css will be nicely put at the top and the javascript to the bottom, just like you should. Also sekizai will ignore any duplicate content in a single block.

SpikeInterface is a Python framework designed to unify preexisting spike sorting technologies into a single code base.

It can:

• read/write many extracellular file formats.

• pre-process extracellular recordings.

• run many popular, semi-automatic spike sorters (kilosort1-4, mountainsort4-5, spykingcircus, tridesclous, ironclust, herdingspikes, yass, waveclus)

• run sorters developed in house (lupin, spkykingcicus2, tridesclous2, simple) that compete with kilosort4

• run theses polar sorters without installation using containers (Docker/Singularity).

• post-process sorted datasets using th SortingAnalyzer

• compare and benchmark spike sorting outputs.

• compute quality metrics to validate and curate spike sorting outputs.

• visualize recordings and spike sorting outputs in several ways (matplotlib, sortingview, jupyter, ephyviewer)

• export a report and/or export to phy

• curate your sorting with several strategies (ml-based, metrics based, manual, ...)

• have powerful sorting components to build your own sorter.

• have a full motion/drift correction framework.

Object annotation mechanism

Resolving paths in the object hierarchy

Documentation at https://melpa.org/#/python-docstring