semvec/pypi-packages huggingface dataset:
chebpy 0.2
Chebyshev polynomial based spectral methods of PDEs.
License: BSD

chebpy
        ======
        
        **chebpy** is a python package for spetral methods of PDEs based on
        Chebyshev series. 
        
        Quickstart
        ----------
        
        1. Install
        ^^^^^^^^^^
        
        ::
        
            $ easy_install chebpy
        
        or
        
        ::
        
            $ tar -xvf chebpy-xxx.tar.gz
            $ cd chebpy-xxx
            $ python setup.py install
        
        Required packages:
        
        * `numpy`: chebpy heavily depends on numpy.
        * `scipy`: advanced algorithms, such as scipy.fftpack.dct.
        
        2. APIs
        ^^^^^^^^
        Current available functions:
        
        **Chebyshev series construction**
        
        * cheb_polynomial_recursion
        * cheb_polynomial_trigonometric
        * cheb_polynomial_series
        
        **Fast Chebyshev transform**
        
        * cheb_fast_transform
        * cheb_inverse_fast_transform
        
        **Chebyshev differentiation**
        
        * cheb_D1_mat
        * cheb_D1_fft
        * cheb_D1_dct
        * cheb_D1_fchebt
        
        **Chebyshev interpolation**
        
        * cheb_interpolation_point
        * cheb_interpolation_1d
        * cheb_interpolation_2d
        
        **Chebyshev quadrature**
        
        * cheb_quadrature_clencurt
        * cheb_quadrature_cgl
        
        **Chebyshev applications in solution of PDEs**
        
        * cheb_mde_split
        * cheb_mde_neumann_split
        * cheb_mde_etdrk4
        * cheb_mde_neumann_etdrk4
        * cheb_mde_robin_etdrk4
        * cheb_allen_cahn_etdrk4
        
        Ask for Help
        ------------
        
        * You can directly contact me at liuyxpp@gmail.com.
        * You can join the mailinglist by sending an email to chebpy@librelist.com 
          and replying to the confirmation mail. 
          To unsubscribe, send a mail to chebpy-unsubscribe@librelist.com 
          and reply to the confirmation mail.
        
        Links
        -----
        
        * `Documentation <http://pypi.python.org/pypi/chebpy>`_
        * `Website <http://ngpy.org>`_
        * `Development version <http://bitbucket.org/liuyxpp/chebpy/>`_
pyconstraints 1.0.1
A simple constraints satisfaction solver
License: BSD

PyConstraints
===

A simple, constraints satisfaction problem solver. Used for the [YACS][] course
scheduler project.

[yacs]: http://github.com/jeffh/yacs

Usage
-----

The Problem is the primary interface:

    >>> from pyconstraints import Problem

And then specify your problem to solve with various constraints:

    >>> p = Problem()
    >>> p.add_variable('x', range(4)) # variable-name, domain
    >>> p.add_variable('y', range(4))
    # give constraint function and list of variables used
    >>> p.add_constraint(lambda x, y: x != y, ['x', 'y'])
    >>> p.add_constraint(lambda x: x % 2 == 0)

Then get your solutions:

    >>> p.get_solutions()
    # => ({'y': 0, 'x': 2},
    #     {'y': 1, 'x': 0},
    #     {'y': 1, 'x': 2},
    #     {'y': 2, 'x': 0},
    #     {'y': 3, 'x': 0},
    #     {'y': 3, 'x': 2})

Or iteratively:

    >>> p.iter_solutions().next()
    # => {'y': 0, 'x': 2}

And that's it!

Using Another Solver
--------------------

Simply pass the solver to the Problem constructor:

    >>> from pyconstraints import BruteForceSolver, BacktrackingSolver
    >>> p = Problem(BacktrackingSolver()) # BruteForceSolver is default

Because the BruteForceSolver uses itertools, there may be cases where it is
faster than the BacktrackingSolver.


Writing Your Own Solver
-----------------------

For convinence, there is a ``pyconstraints.SolverInterface`` Abstract-Base Class if you want to
implement all the features manually:

    @abstractproperty
    def solutions_seen(self):
        "Returns the number of solutions currently seen by the solver."

    @abstractproperty
    def solutions_at_points(self):
        """Returns a dictionary of {iteration_index: solution} of all known
        solutions while iterating.
        """

    @abstractmethod
    def set_conditions(self, variables, constraints):
        """Called by the Problem class to assign the variables and constraints
        for the problem.

            variables = {variable-name: list-of-domain-values}
            constraints = [(constraint_function,
                            variable-names,
                            default-variable-values)]
        """

    @abstractmethod
    def restore_point(self, starting_point=None):
        "Restores the iteration state to a given starting point."

    @abstractmethod
    def save_point(self):
        """Returns data to indicate a way to restore to the current iteration
        point.
        """

    @abstractmethod
    def __iter__(self):
        "Yields solutions."

But for convinence, you can inherit from the ``pyconstraints.SolverBase`` class
which provides a primitive implementation for all the interface methods except
for ``__iter__`` and ``set_conditions``.


Todo
-----

- Speed up backtracking solver
- Add more solvers?
collective.portlet.contentsearch 0.2
Adds content search portlet for Plone..
License: BSD

================================
collective.portlet.contentsearch
================================

collective.portlet.contentsearch provides **Content Search Portlet** for searching Plone's content types by searchable text filtered by collection.

Tested with
-----------

* Plone-4.1.6 [taito]

Further Documentation URL
-------------------------

`http://packages.python.org/collective.portlet.contentsearch/
<http://packages.python.org/collective.portlet.contentsearch/>`_

Repository URL
--------------

`https://github.com/collective/collective.portlet.contentsearch/
<https://github.com/collective/collective.portlet.contentsearch/>`_

Changelog
---------

0.2 (2012-08-20)
================

- Tested with Plone-4.1.6 and Python-2.7. [taito]

0.1.6 (2008-10-23)
==================

- Initial release. [taito]

Contributors
------------

Author
======

* Taito Horiuchi <taito.horiuchi at gmail.com>