Whisper is one of three components within the Graphite project. Whisper is a fixed-size database, similar in design and purpose to RRD (round-robin-database). It provides fast, reliable storage of numeric data over time. Whisper allows for higher resolution (seconds per point) of recent data to degrade into lower resolutions for long-term retention of historical data.

Baycomp is a library for Bayesian comparison of classifiers. Functions in the library compare two classifiers on one or on multiple data sets. They compute three probabilities: the probability that the first classifier has higher scores than the second, the probability that differences are within the region of practical equivalence (rope), or that the second classifier has higher scores.

TOML Kit is a 1.0.0rc1-compliant TOML library. It includes a parser that preserves all comments, indentations, whitespace and internal element ordering, and makes them accessible and editable via an intuitive API. It can also create new TOML documents from scratch using the provided helpers. Part of the implementation has been adapted, improved, and fixed from Molten.

API to query the distutils metadata written in PKG-INFO inside a source distriubtion (an sdist) or a binary distribution (e.g., created by running bdist_egg). It can also query the EGG-INFO directory of an installed distribution, and the *.egg-info stored in a "development checkout" (e.g, created by running python setup.py develop).

The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool.

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.

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.

Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays are accelerated and use less memory than doing the same calculation in Python. In addition, its multi-threaded capabilities can make use of all your cores, which may accelerate computations, most specially if they are not memory-bounded (e.g. those using transcendental functions).

Cartopy is a Python package designed to make drawing maps for data analysis and visualisation easy.

It features:

• object oriented projection definitions

• point, line, polygon and image transformations between projections

• integration to expose advanced mapping in Matplotlib with a simple and intuitive interface

• powerful vector data handling by integrating shapefile reading with Shapely capabilities

Passlib is a password hashing library for Python 2 & 3, which provides cross-platform implementations of over 30 password hashing algorithms, as well as a framework for managing existing password hashes. It's designed to be useful for a wide range of tasks, from verifying a hash found in /etc/shadow, to providing full-strength password hashing for multi-user application.

This package provides a Python implementation of the CANopen standard for CANs. The aim of the project is to support the most common parts of the CiA 301 standard in a simple Pythonic interface. It is mainly targeted for testing and automation tasks rather than a standard compliant master implementation.

msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. It includes the following features:

• High performance encoders/decoders for common protocols.

• Support for a wide variety of Python types.

• Zero-cost schema validation using familiar Python type annotations.

• A speedy Struct type for representing structured data.

Execnet provides a share-nothing model with channel-send/receive communication for distributing execution across many Python interpreters across version, platform and network barriers. It has a minimal and fast API targeting the following uses:

1. distribute tasks to (many) local or remote CPUs

2. write and deploy hybrid multi-process applications

3. write scripts to administer multiple environments

python-pymonad implements data structures typically available in purely functional or functional first programming languages such as Haskell and F#. Included are

• Monad and Monoid data types with several common monads such as Maybe and State

• Useful tools such as the @curry decorator for defining curried functions

• Type annotations to help ensure correct usage

msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. It includes the following features:

• High performance encoders/decoders for common protocols.

• Support for a wide variety of Python types.

• Zero-cost schema validation using familiar Python type annotations.

• A speedy Struct type for representing structured data.

This package provides a Python package to calculate gravitational-wave sensitivity curves for pulsar timing arrays.

Features:

• pulsar transmission functions

• inverse-noise-weighted transmission functions

• individual pulsar sensitivity curves

• pulsar timing array sensitivity curves as characteristic strain, strain sensitivity or energy density

• power-law integrated sensitivity curves

• sensitivity sky maps for pulsar timing arrays

Serpent provides ast.literal_eval()-compatible object tree serialization. It serializes an object tree into bytes (an utf-8 encoded string) that can be decoded and then passed as-is to ast.literal_eval() to rebuild the original object tree.

Because only safe literals are encoded, it is safe to send serpent data to other machines, such as over the network.

The COde-independent Organized LEns STandard (COOLEST) defines a set of conventions to be shared across the strong lensing community, in order to consistently store, share and improve lens modeling analyses. In short, this project provides tools to manipulate lens models as a single, human-readable JSON template file alongside Python routines for visualizing and comparing lens models possibly obtained from different modeling codes.

This is a backport of the standard library typing module to Python versions older than 3.5. Typing defines a standard notation for Python function and variable type annotations. The notation can be used for documenting code in a concise, standard format, and it has been designed to also be used by static and runtime type checkers, static analyzers, IDEs and other tools.

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI libraries for simplifying ML compute. These are the provided Ray AI libraries:

• Data: Scalable datasets for ML;

• Train: Distributed training;

• Tune: Scalable hyperparameter tuning;

• RLlib: Scalable reinforcement learning;

• Serve: Scalable and programmable serving.

Vulture finds unused code in Python programs. This is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python's dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused.

PyVista is...

• Pythonic VTK: a high-level API to the Visualization Toolkit (VTK);

• mesh data structures and filtering methods for spatial datasets;

• 3D plotting made simple and built for large/complex data geometries.

This package provides a Pythonic, well-documented interface exposing VTK's powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets.

This package provides CLI tool and Python library parallel file downloader using asyncio. parfive can handle downloading multiple files in parallel as well as downloading each file in a number of chunks.

asciicast demo of parfive parfive works by creating a downloader object, appending files to it and then running the download. parfive has a synchronous API, but uses asyncio to parallelise downloading the files.

SiriLic (SiriL's Interactif Companion) is a software for preparing acquisition files (raw, Biases, Flat and Dark) for processing with SiriL software.

Features:

• structuring the SiriL working directory into sub-folders

• convert Raw, Biases , Dark or Flat files into SiriL sequence

• automatically generate the SiriL script according to the files present and the options

• batch process multiple channel and sessions