ISO 8601 is most commonly known as a way to exchange datetimes in textual format. A lesser known aspect of the standard is the representation of durations. The state of the art of ISO 8601 duration handling in Python is more or less limited to what's offered by isodate. This package attempts to address the shortcomings of isodate.

This package provides YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order. It is a derivative of Kirill Simonov’s PyYAML 3.11. It supports YAML 1.2 and has round-trip loaders and dumpers. It supports comments. Block style and key ordering are kept, so you can diff the source.

This package provides YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order. It is a derivative of Kirill Simonov’s PyYAML 3.11. It supports YAML 1.2 and has round-trip loaders and dumpers. It supports comments. Block style and key ordering are kept, so you can diff the source.

Telomerecat is a tool for estimating the average telomere length (TL) for a paired end, whole genome sequencing (WGS) sample.

Telomerecat is adaptable, accurate and fast. The algorithm accounts for sequencing amplification artifacts, anneouploidy (common in cancer samples) and noise generated by WGS. For a high coverage WGS BAM file of around 100GB telomerecat can produce an estimate in ~1 hour.

PyTorch is a Python package that provides two high-level features:

• tensor computation (like NumPy) with strong GPU acceleration;

• deep neural networks (DNNs) built on a tape-based autograd system.

You can reuse Python packages such as NumPy, SciPy, and Cython to extend PyTorch when needed.

Note: currently this package does not provide GPU support.

This package provides a simple implementation of contracts for Python. Contracts are a debugging and verification tool. They are declarative statements about what states a program must be in to be considered "correct" at runtime. They are similar to assertions, and are verified automatically at various well-defined points in the program. Contracts can be specified on functions and on classes.

This package supports the creation of a combined header for a FITS file based on the contents of the headers of a set of input FITS images. A rules file defines what keywords will be present in the combined output header as well as how the output value will be determined from the set of values from all the input image headers.

PINT is not TEMPO3 - package providing a Pulsar Timing, written in Python from scratch. Features:

• a robust system to produce high-precision timing results that is completely independent of TEMPO and Tempo2

• a system that is easy to extend and modify due to a good design and the use of a modern programming language, techniques, and libraries

Python XMP Toolkit is a library for working with XMP metadata, as well as reading/writing XMP metadata stored in many different file formats.

Python XMP Toolkit is wrapping Exempi (using ctypes), a C/C++ XMP library based on Adobe XMP Toolkit, ensuring that future updates to the XMP standard are easily incorporated into the library with a minimum amount of work.

The proposal of this package is to provide XPath 1.0 and 2.0 selectors for Python's ElementTree XML data structures, both for the standard ElementTree library and for the lxml.etree library.

For lxml.etree this package can be useful for providing XPath 2.0 selectors, because lxml.etree already has its own implementation of XPath 1.0.

Itemloaders is a library that helps you collect data from HTML and XML sources. It comes in handy to extract data from web pages, as it supports data extraction using CSS and XPath Selectors.

It’s specially useful when you need to standardize the data from many sources. For example, it allows you to have all your casting and parsing rules in a single place.

The ItemAdapter class is a wrapper for data container objects, providing a common interface to handle objects of different types in an uniform manner, regardless of their underlying implementation.

Currently supported types are:

• scrapy.item.Item

• dict

• dataclass-based classes

• attrs-based classes

• pydantic-based classes

Additionally, interaction with arbitrary types is supported by implementing a pre-defined interface.

PickleShare is a small ‘shelve’-like datastore with concurrency support. Like shelve, a PickleShareDB object acts like a normal dictionary. Unlike shelve, many processes can access the database simultaneously. Changing a value in database is immediately visible to other processes accessing the same database. Concurrency is possible because the values are stored in separate files. Hence the “database” is a directory where all files are governed by PickleShare.

Factory_boy is a fixtures replacement based on thoughtbot’s factory_girl. As a fixtures replacement tool, it aims to replace static, hard to maintain fixtures with easy-to-use factories for complex object. Instead of building an exhaustive test setup with every possible combination of corner cases, factory_boy allows you to use objects customized for the current test, while only declaring the test-specific fields.

Macaroons, like cookies, are a form of bearer credential. Unlike opaque tokens, macaroons embed caveats that define specific authorization requirements for the target service, the service that issued the root macaroon and which is capable of verifying the integrity of macaroons it receives.

Macaroons allow for delegation and attenuation of authorization. They are simple and fast to verify, and decouple authorization policy from the enforcement of that policy.

This Python package provides high-level utilities to read and write a variety of Python types from and to HDF5 formatted files. This package also provides support for MATLAB MAT v7.3 formatted files, which are HDF5 files with a different extension and some extra metadata. Because HDF5 and MAT files might need to be read from untrusted sources, pickling is avoided in this package.

This is a implementation of immutable linked lists for Python. It contains nil (the empty linked list) and a Pair class for nodes. Since a linked list is treated as immutable, it is hashable, and its length can be retrieved in constant time. Some of the terminology is inspired by LISP. It is possible to create an improper list by creating a Pair with a non-list cdr.

Table logger using Rich, aimed at PyTorch Lightning logging.

Features

• display your training logs with pretty rich tables

• describe your fields with goal, format and name

• a field descriptor can be matched with any regex

• a field name can be computed as a regex substitution

• works in Jupyter notebooks as well as in a command line

• integrates easily with Pytorch Lightning

The fastbencode Python package implements the bencode serialization format for storing and transmitting loosely structured data, originally used by BitTorrent.

The format can encode four different types of values: byte strings, integers, lists, and dictionaries (associative arrays). It's simple and unaffected by endianness,

This package includes both a pure-Python version and an optional C extension based on Cython. Both provide the same functionality, but the C version has significantly better performance.

pytest-perf makes it easy to compare works by creating two installs, the control and the experiment, and measuring the performance of some Python code against each. Under the hood, it uses the pip-run command to install from the upstream main branch (e.g. https://github.com/jaraco/pytest-perf) for the control and from . for the experiment. It then runs each of the experiments against each of the environments.

This package provides:

• PEP 561 typing stubs packages for the Trio project packages:

  • trio (trio-stubs)

  • outcome (outcome-stubs)

  • async_generator (async_generator-stubs)

• A package trio_typing containing types that Trio programs often want to refer to (AsyncGenerator[Y, S] and TaskStatus[T]) and a mypy plugin that smooths over some limitations in the basic type hints.

Advanced Python Scheduler (APScheduler) is a Python library that lets you schedule your Python code to be executed later, either just once or periodically.

You can add new jobs or remove old ones on the fly as you please. If you store your jobs in a database, they will also survive scheduler restarts and maintain their state. When the scheduler is restarted, it will then run all the jobs it should have run while it was offline.

Advanced Python Scheduler (APScheduler) is a Python library that lets you schedule your Python code to be executed later, either just once or periodically.

You can add new jobs or remove old ones on the fly as you please. If you store your jobs in a database, they will also survive scheduler restarts and maintain their state. When the scheduler is restarted, it will then run all the jobs it should have run while it was offline.

This package implements Jupyter/IPython magic commands for interacting with the SLURM workload manager. SLURM magic simply wraps command-line executables and the commands themselves should look like their command-line counterparts. Commands are spawned via subprocess and output captured in the notebook. Whatever arguments are accepted by a SLURM command line executable are also accepted by the corresponding magic command---e.g., %salloc, %sbatch, etc.