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This module provides a parser for the multipart/form-data format. It can read from a file, a socket or a WSGI environment. The parser can be used to replace cgi.FieldStorage to work around its limitations.
The Munkres module provides an implementation of the Munkres algorithm (also called the Hungarian algorithm or the Kuhn-Munkres algorithm). The algorithm models an assignment problem as an NxM cost matrix, where each element represents the cost of assigning the ith worker to the jth job, and it figures out the least-cost solution, choosing a single item from each row and column in the matrix, such that no row and no column are used more than once.
The "mypy_extensions" module defines experimental extensions to the standard "typing" module that are supported by the mypy typechecker. Python 3 version.
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NBClient, a client library for programmatic notebook execution, is a tool for running Jupyter Notebooks in different execution contexts. NBClient was spun out of nbconvert (formerly ExecutePreprocessor). NBClient lets you execute notebooks.
nbconvert Jupyter Notebook Conversion The nbconvert tool, jupyter nbconvert, converts notebooks to various other formats via Jinja templates. The nbconvert tool allows you to convert an .ipynb notebook file into various static formats including: HTML LaTeX PDF Reveal JS Markdown (md) ReStructured Text (rst) executable script Usage From the command line, use nbconvert to convert a Jupyter notebook (input) to a a different format (output). The basic command structure is: $ jupyter nbconvert --to <output format> <input notebook> where <output format> is the desired output format and <input notebook> is the filename of the Jupyter notebook. Example: Convert a notebook to HTML Convert Jupyter notebook file, mynotebook.ipynb, to HTML using: $ jupyter nbconvert --to html mynotebook.ipynb This command creates an HTML output file named mynotebook.html. Dev Install Check if pandoc is installed (pandoc --version); if needed, install: sudo apt-get install pandoc Or brew install pandoc I
This package contains the base implementation of the Jupyter Notebook format, and Python APIs for working with notebooks.
By design asyncio does not allow its event loop to be nested. This presents a practical problem: When in an environment where the event loop is already running it's impossible to run tasks and wait for the result. Trying to do so will give the error "RuntimeError: This event loop is already running". The issue pops up in various environments, such as web servers, GUI applications and in Jupyter notebooks. This module patches asyncio to allow nested use of asyncio.run and loop.run_until_complete.
A Python library for representing and manipulating network addresses. Provides support for: Layer 3 addresses IPv4 and IPv6 addresses, subnets, masks, prefixes iterating, slicing, sorting, summarizing and classifying IP networks dealing with various ranges formats (CIDR, arbitrary ranges and globs, nmap) set based operations (unions, intersections etc) over IP addresses and subnets parsing a large variety of different formats and notations looking up IANA IP block information generating DNS reverse lookups supernetting and subnetting Layer 2 addresses representation and manipulation MAC addresses and EUI-64 identifiers looking up IEEE organisational information (OUI, IAB) generating derived IPv6 addresses Documentation: https:/netaddr.readthedocs.io/en/latest/ Source code repository: https:/github.com/netaddr/netaddr/ PyPI page: https:/pypi.org/project/netaddr/ Share and enjoy!
An IPython-based shell environment for the netaddr library