Pyan takes one or more Python source files, performs a (rather superficial) static analysis, and constructs a directed graph of the objects in the combined source, and how they define or use each other. The graph can be output for rendering by GraphViz or yEd.

This collection of utilities contains tooling and templates to assist in creating releases on GitHub and publishing them on PyPI. It is designed to be used by Robot Framework and tools and libraries in its ecosystem, but can naturally be used also by other projects.

Anvi’o is a comprehensive platform that brings together many aspects of today’s computational strategies of data-enabled microbiology, including genomics, metagenomics, metatranscriptomics, pangenomics, metapangenomics, phylogenomics, and microbial population genetics in an integrated and easy-to-use fashion through extensive interactive visualization capabilities.

The Python Satellite Data Analysis Toolkit (pysat) provides a simple and flexible interface for robust data analysis from beginning to end - including downloading, loading, cleaning, managing, processing, and analyzing data. Pysat's plug-in design allows analysis support for any data, including user provided data sets.

This plugin adds functionality to Pytest to recognise and collect Jupyter notebooks. The intended purpose of the tests is to determine whether execution of the stored inputs match the stored outputs of the .ipynb file. Whilst also ensuring that the notebooks are running without errors.

pyfma provides an implementation of fused multiply-add which computes (x*y) + z with a single rounding. This is useful for dot products, matrix multiplications, polynomial evaluations (e.g., with Horner's rule), Newton's method for evaluating functions, convolutions, artificial neural networks etc.

This package provides a self-contained and simple BIP39 implementation written in Python. It includes a bip39.py executable.

BIP39 is a standardized mapping between binary data (the entropy), and a list of words that are easier to remember for humans (the mnemonic).

Traceback serialization allows you to:

1. Pickle tracebacks and raise exceptions with pickled tracebacks in different processes. This allows better error handling when running code over multiple processes (imagine multiprocessing, billiard, futures, celery etc).

2. Parse traceback strings and raise with the parsed tracebacks.

klaus is a simple, easy-to-set-up git web viewer. It features

• Super easy to set up -- no configuration required

• Syntax highlighting

• Markdown + RestructuredText rendering support

• Pull + push support (Git Smart HTTP)

• Code navigation using Exuberant ctags

GitDB allows you to access bare Git repositories for reading and writing. It aims at allowing full access to loose objects as well as packs with performance and scalability in mind. It operates exclusively on streams, allowing to handle large objects with a small memory footprint.

PySM generates full-sky simulations of Galactic emissions in intensity and polarization relevant to Cosmic Microwave Background experiments. It is a large refactor of PySM 2 focused on reducing memory usage, improving performance and run in parallel with MPI.

Migen FHDL is a Python library that replaces the event-driven paradigm of Verilog and VHDL with the notions of combinatorial and synchronous statements, has arithmetic rules that make integers always behave like mathematical integers, and allows the design's logic to be constructed by a Python program.

Radon is a Python tool which computes various code metrics. Supported metrics are:

• raw metrics: SLOC, comment lines, blank lines, &c.

• Cyclomatic Complexity (i.e., McCabe’s Complexity)

• Halstead metrics (all of them)

• the Maintainability Index (a Visual Studio metric)

Annoy is a C++ library with Python bindings to search for points in space that are close to a given query point. It also creates large read-only file-based data structures that are mmapped into memory so that many processes may share the same data.

Ngesh is a Python library and CLI tool for simulating phylogenetic trees and data. It is intended for benchmarking phylogenetic methods, especially in historical linguistics andstemmatology. The generation of stochastic phylogenetic trees also goes by the name simulationmethods for phylogenetic trees, synthetic data generation, or just phylogenetic tree simulation.

Pyxel is a game engine inspired by retro gaming consoles. It has a fixed 16-color palette, can hold up to 3 image banks and 8 tilemaps (256x256 pixels each) and 4 sound channels with 64 definable sounds. It also comes with a built-in image and sound editor.

This package provides a way to record and replay device descriptions and events, making it possible to emulate input devices through the Linux kernel's input system. Emulated devices are for most practical purposes indistinguishable from real devices.

It provides a command line program and also a Python library.

The cliff framework allows creating multi-level commands such as those of subversion and git, where the main program handles some basic argument parsing and then invokes a sub-command to do the work. It uses plugins to define sub-commands, output formatters, and other extensions.

This tool implements quantile normalization. It properly resolves rank ties, which is important when ties happen frequently, such as when working with discrete numbers (integers) in count tables. This implementation should be relatively fast, and can use multiple cores to sort the columns and tie-resolvement is accelerated by numba.

Mock is a library for testing in Python. It allows you to replace parts of your system under test with mock objects and make assertions about how they have been used. This library is now part of Python (since Python 3.3), available via the unittest.mock module.

PyAMG is a Python library of Algebraic Multigrid (AMG) solvers. It features implementations of:

• Ruge-Stuben (RS) or Classical AMG

• AMG based on Smoothed Aggregation (SA)

• Adaptive Smoothed Aggregation (αSA)

• Compatible Relaxation (CR)

• Krylov methods such as CG, GMRES, FGMRES, BiCGStab, MINRES, etc.

This package provides tools to convert files in the format used by multiple Spanish banks (standard 43 of the Spanish Banking Council [CSB43] / Spanish Banking Association [AEB43]) to other formats.

Supported output formats are: OFX, HomeBank CSV, HTML, JSON, ODS (OpenDocument spreadsheet), CSV, TSV, XLS, XLSX (Microsoft Excel spreadsheet), and YAML.

MAPIE allows you to easily estimate prediction intervals (or prediction sets) using your favourite scikit-learn-compatible model for single-output regression or multi-class classification settings.

Prediction intervals output by MAPIE encompass both aleatoric and epistemic uncertainties and are backed by strong theoretical guarantees thanks to conformal prediction methods intervals.

Flaky is a plugin for nose or py.test that automatically reruns flaky tests.

Ideally, tests reliably pass or fail, but sometimes test fixtures must rely on components that aren't 100% reliable. With flaky, instead of removing those tests or marking them to @skip, they can be automatically retried.