QuTiP is a library for simulating the dynamics of closed and open quantum systems. It aims to provide numerical simulations of a wide variety of quantum mechanical problems, including those with Hamiltonians and/or collapse operators with arbitrary time-dependence, commonly found in a wide range of physics applications.

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.

pyABF is a Python package for reading electrophysiology data from ABF files. It was created with the goal of providing a Pythonic API to access the content of ABF files which is so intuitive to use (with a predictive IDE) that documentation is largely unnecessary.

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.

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.

Galpy is a Python package for galactic dynamics. It supports orbit integration in a variety of potentials, evaluating and sampling various distribution functions, and the calculation of action-angle coordinates for all static potentials. Galpy is an Astropy affiliated package and provides full support for Astropy’s Quantity framework for variables with units.

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.

Yapsy, or Yet Another Plugin SYstem, is a small library implementing the core mechanisms needed to build a plugin system into a wider application.

The main purpose is to depend only on Python's standard libraries and to implement only the basic functionalities needed to detect, load and keep track of several plugins.

ObsPy is a project dedicated to provide a Python framework for processing seismological data. It provides parsers for common file formats, clients to access data centers and seismological signal processing routines which allow the manipulation of seismological time series.

The goal of the ObsPy project is to facilitate rapid application development for seismology.

This module provides an xopen function that works like Python's built-in open function, but can also deal with compressed files. Supported compression formats are gzip, bzip2 and, xz, and are automatically recognized by their file extensions. The focus is on being as efficient as possible on all supported Python versions.

Surfa is a collection of Python utilities for medical image analysis and mesh-based surface processing. It provides tools that operate on 3D image arrays and triangular meshes with consideration of their representation in a world (or scanner) coordinate system. While broad in scope, surfa is developed with particular emphasis on neuroimaging applications.

MMTK is a library for molecular simulations with an emphasis on biomolecules. It provides widely used methods such as Molecular Dynamics and normal mode analysis, but also basic routines for implementing new methods for simulation and analysis. The library is currently not actively maintained and works only with Python 2 and NumPy < 1.9.

PyDMD is a Python package designed for Dynamic Mode Decomposition (DMD), a data-driven method used for analyzing and extracting spatiotemporal coherent structures from time-varying datasets. It provides a comprehensive and user-friendly interface for performing DMD analysis, making it a valuable tool for researchers, engineers, and data scientists working in various fields.

This is an easy-to-use implementation of ECDSA cryptography (Elliptic Curve Digital Signature Algorithm), implemented purely in Python. With this library, you can quickly create key pairs (signing key and verifying key), sign messages, and verify the signatures. The keys and signatures are very short, making them easy to handle and incorporate into other protocols.

This is a minimum version for checking the input argument dict. It would examine argument's type, as well as keys and types of its sub-arguments. A special case called variant is also handled, where you can determine the items of a dict based the value of on one of its flag_name key.

This package is a Python-based command line interface for processing .bam files with mitochondrial reads and generating high-quality heteroplasmy estimation from sequencing data. The mgatk package places a special emphasis on mitochondrial genotypes generated from single-cell genomics data, primarily mtscATAC-seq, but is generally applicable across other assays.

SimPy is a process-based discrete-event simulation framework based on standard Python. Processes in SimPy are defined by Python generator functions and can, for example, be used to model active components like customers, vehicles or agents. SimPy also provides various types of shared resources to model limited capacity congestion points (like servers, checkout counters and tunnels).

python-pysox is a wrapper around the sox command line tool. The API offers Transformer and Combiner classes that allow the user to incrementally build up effects and audio manipulations. python-pysox also provides methods for querying audio information such as sample rate, determining whether an audio file is silent, and much more.

Param is a library for handling all the user-modifiable parameters, arguments, and attributes that control your code. It provides automatic, robust error-checking while dramatically reducing boilerplate code, letting you focus on what you want your code to do rather than on checking for all the possible ways users could supply inappropriate values to a function or class.

Scapy is a Python library and executable for interactively manipulating network packets. It can forge or decode packets of a number of protocols, send them on the wire, capture them, store or read them using pcap files, match requests and replies, and so on. It can handle tasks such as scanning, tracerouting, probing, unit tests, attacks or network discovery.

Lmfit provides a high-level interface to non-linear optimization and curve fitting problems for Python. It builds on and extends many of the optimization methods of scipy.optimize. Initially inspired by (and named for) extending the Levenberg-Marquardt method from scipy.optimize.leastsq, lmfit now provides a number of useful enhancements to optimization and data fitting problems.