This package implements a functionality to work with Nested sampling, a popular numerical method for Bayesian computation, which simultaneously generates samples from the posterior distribution and an estimate of the Bayesian evidence for a given likelihood and prior. nestcheck provides Python utilities for analysing samples produced by nested sampling, and estimating uncertainties on nested sampling calculations (which have different statistical properties to calculations using other numerical methods).

This package is a stand-alone implementation of several NumPy dtype extensions used in machine learning libraries, including:

• bfloat16: an alternative to the standard float16 format

• float8_*: several experimental 8-bit floating point representations including:

  • float8_e4m3b11fnuz

  • float8_e4m3fn

  • float8_e4m3fnuz

  • float8_e5m2

  • float8_e5m2fnuz

• int4 and uint4: low precision integer types.

Codespell fixes common misspellings in text files. It's designed primarily for checking misspelled words in source code, but it can be used with other files as well. It does not check for word membership in a complete dictionary, but instead looks for a set of common misspellings. Therefore it should catch errors like "adn", but it will not catch "adnasdfasdf". This also means it shouldn't generate false-positives when you use a niche term it doesn't know about.

NbClassic provides a backwards compatible Jupyter Notebook interface that you can install side-by-side with the latest versions: That way, you can fearlessly upgrade without worrying about your classic extensions and customizations breaking. Because NbClassic provides the classic interface on top of the new Jupyter Server backend, it can coexist with other frontends like JupyterLab and Notebook 7 in the same installation. NbClassic preserves the custom classic notebook experience under a new set of URL endpoints, under the namespace /nbclassic/.

Pairtools is a simple and fast command-line framework to process sequencing data from a Hi-C experiment. Process pair-end sequence alignments and perform the following operations:

• detect ligation junctions (a.k.a. Hi-C pairs) in aligned paired-end sequences of Hi-C DNA molecules

• sort .pairs files for downstream analyses

• detect, tag and remove PCR/optical duplicates

• generate extensive statistics of Hi-C datasets

• select Hi-C pairs given flexibly defined criteria

• restore .sam alignments from Hi-C pairs.

This package is a tiny, zero-dependencies library that makes it easy to add function (or object) registries to your code. Function registries are helpful when you have objects that need to be both easily serializable and fully customizable. Instead of passing a function into your object, you pass in an identifier name, which the object can use to lookup the function from the registry. This makes the object easy to serialize, because the name is a simple string. If you instead saved the function, you'd have to use Pickle for serialization, which has many drawbacks.

This package provides a flexible toolbox for observation planning and scheduling. When complete, the goal is to be easy for Python beginners and new observers to to pick up, but powerful enough for observatories preparing nightly and long-term schedules.

Features:

• calculate rise/set/meridian transit times, alt/az positions for targets at observatories anywhere on Earth

• built-in plotting convenience functions for standard observation planning plots (airmass, parallactic angle, sky maps)

• determining observability of sets of targets given an arbitrary set of constraints (i.e., altitude, airmass, moon separation/illumination, etc.)

This package provides a Python library for working with and comparing language codes.

python-langcodes implements BCP 47, the IETF Best Current Practices on Tags for Identifying Languages. BCP 47 is also known as RFC 5646. It subsumes ISO 639 and is backward compatible with it, and it also implements recommendations from the Unicode CLDR.

python-langcodes can also refer to a database of language properties and names, built from Unicode CLDR and the IANA subtag registry, if you install python-language-data.

This library handles the low-level details of NTLM authentication for use in authenticating with a service that uses NTLM. It will create and parse the 3 different message types in the order required and produce a base64 encoded value that can be attached to the HTTP header.

The goal of this library is to offer full NTLM support including signing and sealing of messages as well as supporting MIC for message integrity and the ability to customise and set limits on the messages sent. Please see Features and Backlog for a list of what is and is not currently supported.

The goal of pathlib2 is to provide a backport of standard pathlib module which tracks the standard library module, so all the newest features of the standard pathlib can be used also on older Python versions.

Pathlib offers a set of classes to handle file system paths. It offers the following advantages over using string objects:

1. No more cumbersome use of os and os.path functions. Everything can be done easily through operators, attribute accesses, and method calls.

2. Embodies the semantics of different path types. For example, comparing Windows paths ignores casing.

3. Well-defined semantics, eliminating any inconsistencies or ambiguities (forward vs. backward slashes, etc.).

astrodata is a package for managing astronomical data through a uniform interface. It is designed to be used with the Astropy package. astrodata was created for use as part of the DRAGONS data reduction pipeline, but it is now implemented to be useful for any astronomical data reduction or analysis project.

Unlike managing files using the astropy.io.fits package alone, astrodata is designed to be extendible to any data format, and to parse, respond to, and store metadata in a consistent, intentional way. This makes it especially useful for managing data from multiple instruments, telescopes, and data generation utilities.

The library classeval is developed to evaluate the models performance of any kind of two-class or multi-class model. classeval computes many scoring measures in case of a two-class clasification model. Some measures are utilized from sklearn, among them AUC, MCC, Cohen kappa score, matthews correlation coefficient, whereas others are custom. This library can help to consistenly compare the output of various models. In addition, it can also give insights in tuning the models performance as the the threshold being used can be adjusted and evaluated. The output of classeval can subsequently plotted in terms of ROC curves, confusion matrices, class distributions, and probability plots. Such plots can help in better understanding of the results.

The Python FTP server library provides a high-level interface to write efficient, scalable and asynchronous FTP servers with Python. It is the most complete RFC-959 FTP server implementation available for Python, and has the following traits:

• It is lightweight, fast and scalable.

• It uses the sendfile(2) system call for uploads.

• It uses epoll, kqueue and select to handle concurrency asynchronously.

• It supports FTPS (RFC-4217), IPv6 (RFC-2428), Unicode file names (RFC-2640) and MLSD/MLST commands (RFC-3659).

• It has a flexible system of authorizers able to manage both virtual and real users.

todo.

Core Schema.

Dash table.

Dash table.

Software Heritage lister

Typing stubs for mock

Dask backend for Deisa.

Lezer-based Python grammar

Lezer-based Python grammar

This package provides Cython bindings for MurmurHash2.

Base ArviZ features and converters.