reapxdev/pypi-scraper huggingface dataset:
multipledispatch 1.0.0 — Multiple dispatch
Author: Matthew Rocklin
License: BSD 
Keywords: dispatch

Multiple Dispatch
=================

|Build Status| |Coverage Status| |Version Status|

A relatively sane approach to multiple dispatch in Python.

This implementation of multiple dispatch is efficient, mostly complete,
performs static analysis to avoid conflicts, and provides optional namespace
support.  It looks good too.

See the documentation at https://multiple-dispatch.readthedocs.io/


Example
-------

.. code-block:: python

   >>> from multipledispatch import dispatch

   >>> @dispatch(int, int)
   ... def add(x, y):
   ...     return x + y

   >>> @dispatch(object, object)
   ... def add(x, y):
   ...     return "%s + %s" % (x, y)

   >>> add(1, 2)
   3

   >>> add(1, 'hello')
   '1 + hello'

What this does
--------------

-  Dispatches on all non-keyword arguments

-  Supports inheritance

-  Supports instance methods

-  Supports union types, e.g. ``(int, float)``

-  Supports builtin abstract classes, e.g. ``Iterator, Number, ...``

-  Caches for fast repeated lookup

-  Identifies possible ambiguities at function definition time

-  Provides hints to resolve ambiguities when they occur

-  Supports namespaces with optional keyword arguments

-  Supports variadic dispatch

What this doesn't do
--------------------

-  Diagonal dispatch

.. code-block:: python

   a = arbitrary_type()
   @dispatch(a, a)
   def are_same_type(x, y):
       return True

-  Efficient update: The addition of a new signature requires a full resolve of
   the whole function.  This becomes troublesome after you get to a few hundred
   type signatures.


Installation and Dependencies
-----------------------------

``multipledispatch`` is on the Python Package Index (PyPI):

::

    pip install multipledispatch

It is Pure-Python and depends only on the standard library.
It is a light weight dependency.


License
-------

New BSD. See `License file`_.


Links
-----

-  `Five-minute Multimethods in Python by Guido`_
-  `multimethods package on PyPI`_
-  `singledispatch in Python 3.
memory-profiler 0.61.0 — A module for monitoring memory usage of a python program
Author: Fabian Pedregosa
License: BSD 
Requires Python: >=3.5
Dependencies: psutil

.. image:: https://travis-ci.org/pythonprofilers/memory_profiler.svg?branch=master
    :target: https://travis-ci.org/pythonprofilers/memory_profiler

=================
 Memory Profiler
=================


**Note:** This package is no longer actively maintained. I won't be actively responding to issues. If you'd like to volunteer to maintain it, please drop me a line at f@bianp.net

This is a python module for monitoring memory consumption of a process
as well as line-by-line analysis of memory consumption for python
programs. It is a pure python module which depends on the `psutil
<http://pypi.python.org/pypi/psutil>`_ module.


==============
 Installation
==============
Install via pip::

    $ pip install -U memory_profiler

The package is also available on `conda-forge
<https://github.com/conda-forge/memory_profiler-feedstock>`_.

To install from source, download the package, extract and type::

    $ pip install .

===========
Quick Start
===========

Use `mprof` to generate a full memory usage report of your executable and to plot it.

.. code-block:: bash

    mprof run executable
    mprof plot

The plot would be something like this:

.. image:: https://i.stack.imgur.com/ixCH4.png

=======
 Usage
=======


line-by-line memory usage
=========================

The line-by-line memory usage mode is used much in the same way of the
`line_profiler <https://pypi.python.org/pypi/line_profiler/>`_: first
decorate the function you would like to profile with ``@profile`` and
then run the script with a special script (in this case with specific
arguments to the Python interpreter).

In the following example, we create a simple function ``my_func`` that
allocates lists ``a``, ``b`` and then deletes ``b``::


    @profile
    def my_func():
        a = [1] * (10 ** 6)
        b = [2] * (2 * 10 ** 7)
        del b
        return a

    if __name__ == '__main__':
        my_func()


Execute the code passing the option ``-m memory_profiler`` to the
python interpreter to lo
sympy 1.14.0 — Computer algebra system (CAS) in Python
Author: SymPy development team
License: BSD 
Keywords: Math CAS
Requires Python: >=3.9
Dependencies: mpmath<1.4,>=1.1.0, pytest>=7.1.0; extra == "dev", hypothesis>=6.70.0; extra == "dev"

# SymPy

[![pypi version](https://img.shields.io/pypi/v/sympy.svg)](https://pypi.python.org/pypi/sympy)
[![Join the chat at https://gitter.im/sympy/sympy](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/sympy/sympy?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
[![Zenodo Badge](https://zenodo.org/badge/18918/sympy/sympy.svg)](https://zenodo.org/badge/latestdoi/18918/sympy/sympy)
[![Downloads](https://pepy.tech/badge/sympy/month)](https://pepy.tech/project/sympy)
[![GitHub Issues](https://img.shields.io/badge/issue_tracking-github-blue.svg)](https://github.com/sympy/sympy/issues)
[![Git Tutorial](https://img.shields.io/badge/PR-Welcome-%23FF8300.svg?)](https://git-scm.com/book/en/v2/GitHub-Contributing-to-a-Project)
[![Powered by NumFocus](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](https://numfocus.org)
[![Commits since last release](https://img.shields.io/github/commits-since/sympy/sympy/latest.svg?longCache=true&style=flat-square&logo=git&logoColor=fff)](https://github.com/sympy/sympy/releases)

[![SymPy Banner](https://github.com/sympy/sympy/raw/master/banner.svg)](https://sympy.org/)


See the [AUTHORS](AUTHORS) file for the list of authors.

And many more people helped on the SymPy mailing list, reported bugs,
helped organize SymPy's participation in the Google Summer of Code, the
Google Highly Open Participation Contest, Google Code-In, wrote and
blogged about SymPy...

License: New BSD License (see the [LICENSE](LICENSE) file for details) covers all
files in the sympy repository unless stated otherwise.

Our mailing list is at
<https://groups.google.com/forum/?fromgroups#!forum/sympy>.

We have a community chat at [Gitter](https://gitter.im/sympy/sympy). Feel
free to ask us anything there. We have a very welcoming and helpful
community.

## Download

The recommended installation method is through Anaconda,
<https://www.anaconda.com/products/distribution>

You c