pyregion is a python module to parse ds9 region files. It also supports ciao region files. Features:

• ds9 and ciao region files.

• (physical, WCS) coordinate conversion to the image coordinate.

• convert regions to matplotlib patches.

• convert regions to spatial filter (i.e., generate mask images)

Jupytext is a plugin for Jupyter that can save Jupyter notebooks as either Markdown files or scripts in many languages. Common use cases for Jupytext are:

• version control on Jupyter Notebooks

• editing, merging or refactoring notebooks in your favorite text editor

• applying Q&A checks on notebooks.

Docutils is a modular system for processing documentation into useful formats, such as HTML, XML, and LaTeX. It uses reStructuredText, an easy to use markup language, for input.

This package provides tools for converting .rst files to other formats via commands such as rst2man, as well as supporting Python code.

Docutils is a modular system for processing documentation into useful formats, such as HTML, XML, and LaTeX. It uses reStructuredText, an easy to use markup language, for input.

This package provides tools for converting .rst files to other formats via commands such as rst2man, as well as supporting Python code.

The Gurobi Optimizer is a commercial optimization solver for linear programming (LP), quadratic programming (QP), quadratically constrained programming (QCP), mixed integer linear programming (MILP), mixed-integer quadratic programming (MIQP), and mixed-integer quadratically constrained programming (MIQCP). See here for more info: https://www.gurobi.com/documentation/9.0/quickstart_linux/cs_python.html.

This package provides a small library, built on top of pyOpenSSL, which allows for creating a custom certificate authority (CA) certificate, and generating on-demand dynamic host certs using that CA certificate. It is most useful for use with a man-in-the-middle HTTPS proxy, for example, for recording or replaying web content.

Parallel Python module (PP) provides an easy and efficient way to create parallel-enabled applications for SMP computers and clusters. PP module features cross-platform portability and dynamic load balancing. Thus applications written with PP will parallelize efficiently even on heterogeneous and multi-platform clusters (including clusters running other applications with variable CPU loads).

If your code lets other people supply callback functions, it's important to specify the function signature you expect, and check that functions support that. Adding extra parameters later would break other peoples code unless you're careful. The backcall package provides a way of specifying the callback signature using a prototype function.

This Python package is a high-level wrapper for Kerberos (GSSAPI) operations. The goal is to avoid having to build a module that wraps the entire Kerberos.framework, and instead offer a limited set of functions that do what is needed for client/server Kerberos authentication based on <http://www.ietf.org/rfc/rfc4559.txt>.

This package cleans Jupyter notebooks of cell execution counts, metadata, outputs, and empty cells, preparing them for committing to version control. It provides a Git filter to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains. Some of its key distinguishing features include: clear, readable syntax; strong introspection capabilities; intuitive object orientation; natural expression of procedural code; full modularity, supporting hierarchical packages; exception-based error handling; and very high level dynamic data types.

Plots, scatter plots, histograms and heatmaps in the terminal using braille dots, and foreground and background colors - with (almost) no dependancies. Make complex figures using the Figure class or make fast and simple plots using graphing function - similar to a very small sibling to matplotlib. Or use the canvas to plot dots, lines and images yourself.

Deepdish is a Python library to load and save HDF5 files. The primary feature of deepdish is its ability to save and load all kinds of data as HDF5. It can save any Python data structure, offering the same ease of use as pickling or numpy.save, but with the language interoperability offered by HDF5.

This package provides a set of handlers for the Python standard library logging package. Some of these handlers are out-of-scope for the standard library, and so they are packaged here. Others are updated versions which have appeared in recent Python releases, but are usable with older versions of Python and so are packaged here.

python-nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Un-evaluated notebooks - i.e. notebooks without stored output cells - will be automatically executed during the Sphinx build process.

wxPython is a cross-platform GUI toolkit for the Python programming language. It is implemented as a set of Python extension modules that wrap the GUI components of the popular wxWidgets cross platform C++ library. In most cases, wxPython uses the native widgets on each platform to provide a 100% native look and feel for the application.

python-dbusmock allows for the easy creation of mock objects on D-Bus. This is useful for writing tests for software which talks to D-Bus services such as upower, systemd, logind, gnome-session or others, and it is hard (or impossible without root privileges) to set the state of the real services to what you expect in your tests.

Retrying is a general-purpose retrying library to simplify the task of adding retry behavior to just about anything.

Features:

• Generic Decorator API.

• Specify stop condition (i.e. limit by number of attempts).

• Specify wait condition (i.e. exponential backoff sleeping between attempts).

• Customize retrying on Exceptions.

• Customize retrying on expected returned result.

statmake takes a user-written Stylespace that defines OpenType STAT information for an entire font family and then (potentially subsets and) applies it to a specific variable font. This spares users from having to deal with raw TTX dumps and juggling with nameIDs.

CairoSVG is a SVG converter based on Cairo. It can export SVG files to PDF, PostScript and PNG files. The main part of CairoSVG is a SVG parser, trying to follow the SVG 1.1 recommendation from the W3C. Once parsed, the result is drawn to a Cairo surface that can be exported to qvarious formats: PDF, PostScript, PNG and even SVG.

HTTP Core provides a minimal and low-level HTTP client, which does one thing only: send HTTP requests.

Some things HTTP Core does do:

• Sending HTTP requests.

• Provides both sync and async interfaces.

• Supports HTTP/1.1 and HTTP/2.

• Async backend support for asyncio and trio.

• Automatic connection pooling.

• HTTP(S) proxy support.

This package includes Controller Area Network (CAN) related tools that can be used to:

• parse DBC, KCD, SYM, ARXML 4 and CDD files

• encode and decode CAN messages

• multiplex simple and extended signals

• diagnose DID encoding and decoding

• dump the CAN decoder output

• test CAN nodes

• generate C source code

• monitor the CAN bus

This package is a library to enable flexible and scalable operations on genomic interval dataframes in Python. Bioframe enables access to a rich set of dataframe operations. Working in Python enables rapid visualization and iteration of genomic analyses. The philosophy underlying bioframe is to enable flexible operations. Instead of creating a function for every possible use-case, we encourage users to compose functions to achieve their goals.

Liblarch is a Python library built to easily handle data structures such as lists, trees and acyclic graphs. There's also a GTK binding that will allow you to use your data structure in a Gtk.Treeview.

Liblarch support multiple views of one data structure and complex filtering. That way, you have a clear separation between your data themselves (Model) and how they are displayed (View).