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removed warnings on import; added has_fast_tree_support(); release 2.0.4
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Manfred Moitzi committed Jan 9, 2016
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15 changes: 15 additions & 0 deletions .hgignore
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45 changes: 45 additions & 0 deletions LICENSE.txt
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Copyright (c) 2012, Manfred Moitzi

Permission is hereby granted, free of charge, to any person obtaining a
copy of this software and associated documentation files (the
"Software"), to deal in the Software without restriction, including
without limitation the rights to use, copy, modify, merge, publish,
distribute, sublicense, and/or sell copies of the Software, and to
permit persons to whom the Software is furnished to do so, subject to
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The above copyright notice and this permission notice shall be included
in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Deutsche Übersetzung:

Copyright (c) 2012, Manfred Moitzi

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und der zugehörigen Dokumentationen (die "Software") erhält, die
Erlaubnis erteilt, uneingeschränkt zu benutzen, inklusive und ohne
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verlegen, verbreiten, unterlizenzieren und/oder zu verkaufen, und
Personen, die diese Software erhalten, diese Rechte zu geben, unter den
folgenden Bedingungen:

Der obige Urheberrechtsvermerk und dieser Erlaubnisvermerk sind in allen
Kopien oder Teilkopien der Software beizulegen.

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ANSPRÜCHE HAFTBAR ZU MACHEN, OB INFOLGE DER ERFÜLLUNG EINES VERTRAGES,
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6 changes: 6 additions & 0 deletions MANIFEST.in
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include NEWS.rst README.rst LICENSE.txt
include tests/testkey.txt
include bintrees/ctrees.c
include bintrees/ctrees.h
recursive-include tests *.py
recursive-include bintrees *.pyx *.pxd
114 changes: 114 additions & 0 deletions NEWS.rst
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NEWS
====

Version 2.0.4 - 2015-01-09

* removed logging statements on import
* added helper function bintrees.has_fast_free_support()
* HINT: pypy runs faster than CPython with Cython extension

Version 2.0.3 - 2015-01-06

* replaced print function by logging.warning for import warning messages
* KNOWN ISSUE: unable to build Cython extension with MingW32 and CPython 3.5 & CPython 2.7.10

Version 2.0.2 - 2015-02-12

* fixed foreach cython-function by Sam Yaple

Version 2.0.1 - 2013-10-01

* removed __del__() method to avoid problems with garbage collection

Version 2.0.0 - 2013-06-01

* API change: consistent method naming with synonyms for dict/set compatibility
* code base refactoring
* removed tree walkers
* removed low level node stack implementation -> caused crashes
* optimizations for pypy: iter_items(), succ_item(), prev_item()
* tested with CPython2.7, CPython3.3, pypy-2.0 on Win7 and Linux Mint 15 x64 (pypy-1.9)

Version 1.0.3 - 2013-05-01

* extended iter_items(startkey=None, endkey=None, reverse=reverse) -> better performance for slicing
* Cython implementation of iter_items() for Fast_X_Trees()
* added key parameter *reverse* to itemslice(), keyslice(), valueslice()
* tested with CPython2.7, CPython3.3, pypy-2.0

Version 1.0.2 - 2013-04-01

* bug fix: FastRBTree data corruption on inserting existing keys
* bug fix: union & symmetric_difference - copy all values to result tree

Version 1.0.1 - 2013-02-01

* bug fixes
* refactorings by graingert
* skip useless tests for pypy
* new license: MIT License
* tested with CPython2.7, CPython3.2, CPython3.3, pypy-1.9, pypy-2.0-beta1
* unified line endings to LF
* PEP8 refactorings
* added floor_item/key, ceiling_item/key methods, thanks to Dai Mikurube

Version 1.0.0 - 2011-12-29

* bug fixes
* status: 5 - Production/Stable
* removed useless TreeIterator() class and T.treeiter() method.
* patch from Max Motovilov to use Visual Studio 2008 for building C-extensions

Version 0.4.0 - 2011-04-14

* API change!!!
* full Python 3 support, also for Cython implementations
* removed user defined compare() function - keys have to be comparable!
* removed T.has_key(), use 'key in T'
* keys(), items(), values() generating 'views'
* removed iterkeys(), itervalues(), iteritems() methods
* replaced index slicing by key slicing
* removed index() and item_at()
* repr() produces a correct representation
* installs on systems without cython (tested with pypy)
* new license: GNU Library or Lesser General Public License (LGPL)

Version 0.3.2 - 2011-04-09

* added itemslice(startkey, endkey), keyslice(startkey, endkey),
valueslice(startkey, endkey) - slicing by keys
* tested with pypy 1.4.1, damn fast
* Pure Python trees are working with Python 3
* No Cython implementation for Python 3

Version 0.3.1 - 2010-09-10

* runs with Python 2.7

Version 0.3.0 - 2010-05-11

* low level functions written as c-module only interface to python is a cython
module
* support for the pickle protocol

Version 0.2.1 - 2010-05-06

* added delslice del T[0:3] -> remove treenodes 0, 1, 2
* added discard -> remove key without KeyError if not found
* added heap methods: min, max, nlarges, nsmallest ...
* added Set methods -> intersection, differnce, union, ...
* added slicing: T[5:10] get items with position (not key!) 5, 6, 7, 8, 9
T[5] get item with key! 5
* added index: T.index(key) -> get position of item <key>
* added item_at: T.item_at(0) -> get item at position (not key!) 0
T.item_at(0) O(n)! <==> T.min_item() O(log(n))

Version 0.2.0 - 2010-05-03

* TreeMixin Class as base for Python-Trees and as Mixin for Cython-Trees

Version 0.1.0 - 2010-04-27

* Alpha status
* Initial release
191 changes: 191 additions & 0 deletions README.rst
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Binary Tree Package
===================

Abstract
========

This package provides Binary- RedBlack- and AVL-Trees written in Python and Cython/C.

This Classes are much slower than the built-in *dict* class, but all
iterators/generators yielding data in sorted key order. Trees can be
uses as drop in replacement for *dicts* in most cases.

Source of Algorithms
--------------------

AVL- and RBTree algorithms taken from Julienne Walker: http://eternallyconfuzzled.com/jsw_home.aspx

Trees written in Python
-----------------------

- *BinaryTree* -- unbalanced binary tree
- *AVLTree* -- balanced AVL-Tree
- *RBTree* -- balanced Red-Black-Tree

Trees written with C-Functions and Cython as wrapper
----------------------------------------------------

- *FastBinaryTree* -- unbalanced binary tree
- *FastAVLTree* -- balanced AVL-Tree
- *FastRBTree* -- balanced Red-Black-Tree

All trees provides the same API, the pickle protocol is supported.

Cython-Trees have C-structs as tree-nodes and C-functions for low level operations:

- insert
- remove
- get_value
- min_item
- max_item
- prev_item
- succ_item
- floor_item
- ceiling_item

Constructor
~~~~~~~~~~~

* Tree() -> new empty tree;
* Tree(mapping) -> new tree initialized from a mapping (requires only an items() method)
* Tree(seq) -> new tree initialized from seq [(k1, v1), (k2, v2), ... (kn, vn)]

Methods
~~~~~~~

* __contains__(k) -> True if T has a key k, else False, O(log(n))
* __delitem__(y) <==> del T[y], del[s:e], O(log(n))
* __getitem__(y) <==> T[y], T[s:e], O(log(n))
* __iter__() <==> iter(T)
* __len__() <==> len(T), O(1)
* __max__() <==> max(T), get max item (k,v) of T, O(log(n))
* __min__() <==> min(T), get min item (k,v) of T, O(log(n))
* __and__(other) <==> T & other, intersection
* __or__(other) <==> T | other, union
* __sub__(other) <==> T - other, difference
* __xor__(other) <==> T ^ other, symmetric_difference
* __repr__() <==> repr(T)
* __setitem__(k, v) <==> T[k] = v, O(log(n))
* clear() -> None, remove all items from T, O(n)
* copy() -> a shallow copy of T, O(n*log(n))
* discard(k) -> None, remove k from T, if k is present, O(log(n))
* get(k[,d]) -> T[k] if k in T, else d, O(log(n))
* is_empty() -> True if len(T) == 0, O(1)
* items([reverse]) -> generator for (k, v) items of T, O(n)
* keys([reverse]) -> generator for keys of T, O(n)
* values([reverse]) -> generator for values of T, O(n)
* pop(k[,d]) -> v, remove specified key and return the corresponding value, O(log(n))
* pop_item() -> (k, v), remove and return some (key, value) pair as a 2-tuple, O(log(n)) (synonym popitem() exist)
* set_default(k[,d]) -> value, T.get(k, d), also set T[k]=d if k not in T, O(log(n)) (synonym setdefault() exist)
* update(E) -> None. Update T from dict/iterable E, O(E*log(n))
* foreach(f, [order]) -> visit all nodes of tree (0 = 'inorder', -1 = 'preorder' or +1 = 'postorder') and call f(k, v) for each node, O(n)
* iter_items(s, e[, reverse]) -> generator for (k, v) items of T for s <= key < e, O(n)
* remove_items(keys) -> None, remove items by keys, O(n)

slicing by keys
~~~~~~~~~~~~~~~

* item_slice(s, e[, reverse]) -> generator for (k, v) items of T for s <= key < e, O(n), synonym for iter_items(...)
* key_slice(s, e[, reverse]) -> generator for keys of T for s <= key < e, O(n)
* value_slice(s, e[, reverse]) -> generator for values of T for s <= key < e, O(n)
* T[s:e] -> TreeSlice object, with keys in range s <= key < e, O(n)
* del T[s:e] -> remove items by key slicing, for s <= key < e, O(n)

start/end parameter:

* if 's' is None or T[:e] TreeSlice/iterator starts with value of min_key();
* if 'e' is None or T[s:] TreeSlice/iterator ends with value of max_key();
* T[:] is a TreeSlice which represents the whole tree;

The step argument of the regular slicing syntax T[s:e:step] will silently ignored.

TreeSlice is a tree wrapper with range check and contains no references
to objects, deleting objects in the associated tree also deletes the object
in the TreeSlice.

* TreeSlice[k] -> get value for key k, raises KeyError if k not exists in range s:e
* TreeSlice[s1:e1] -> TreeSlice object, with keys in range s1 <= key < e1
- new lower bound is max(s, s1)
- new upper bound is min(e, e1)

TreeSlice methods:

* items() -> generator for (k, v) items of T, O(n)
* keys() -> generator for keys of T, O(n)
* values() -> generator for values of T, O(n)
* __iter__ <==> keys()
* __repr__ <==> repr(T)
* __contains__(key)-> True if TreeSlice has a key k, else False, O(log(n))

prev/succ operations
~~~~~~~~~~~~~~~~~~~~

* prev_item(key) -> get (k, v) pair, where k is predecessor to key, O(log(n))
* prev_key(key) -> k, get the predecessor of key, O(log(n))
* succ_item(key) -> get (k,v) pair as a 2-tuple, where k is successor to key, O(log(n))
* succ_key(key) -> k, get the successor of key, O(log(n))
* floor_item(key) -> get (k, v) pair, where k is the greatest key less than or equal to key, O(log(n))
* floor_key(key) -> k, get the greatest key less than or equal to key, O(log(n))
* ceiling_item(key) -> get (k, v) pair, where k is the smallest key greater than or equal to key, O(log(n))
* ceiling_key(key) -> k, get the smallest key greater than or equal to key, O(log(n))

Heap methods
~~~~~~~~~~~~

* max_item() -> get largest (key, value) pair of T, O(log(n))
* max_key() -> get largest key of T, O(log(n))
* min_item() -> get smallest (key, value) pair of T, O(log(n))
* min_key() -> get smallest key of T, O(log(n))
* pop_min() -> (k, v), remove item with minimum key, O(log(n))
* pop_max() -> (k, v), remove item with maximum key, O(log(n))
* nlargest(i[,pop]) -> get list of i largest items (k, v), O(i*log(n))
* nsmallest(i[,pop]) -> get list of i smallest items (k, v), O(i*log(n))

Set methods (using frozenset)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

* intersection(t1, t2, ...) -> Tree with keys *common* to all trees
* union(t1, t2, ...) -> Tree with keys from *either* trees
* difference(t1, t2, ...) -> Tree with keys in T but not any of t1, t2, ...
* symmetric_difference(t1) -> Tree with keys in either T and t1 but not both
* is_subset(S) -> True if every element in T is in S (synonym issubset() exist)
* is_superset(S) -> True if every element in S is in T (synonym issuperset() exist)
* is_disjoint(S) -> True if T has a null intersection with S (synonym isdisjoint() exist)

Classmethods
~~~~~~~~~~~~

* from_keys(S[,v]) -> New tree with keys from S and values equal to v. (synonym fromkeys() exist)

Helper functions
~~~~~~~~~~~~~~~~

* bintrees.has_fast_tree_support() -> True if Cython extension is working else False (False = using pure Python implementation)

Installation
============

from source::

python setup.py install

or from PyPI::

pip install bintrees

Compiling the fast Trees requires Cython and on Windows is a C-Compiler necessary (MingW32 works fine, except for
CPython 2.7.10 & CPython 3.5).

Download Binaries for Windows
=============================

http://bitbucket.org/mozman/bintrees/downloads

Documentation
=============

this README.rst

bintrees can be found on bitbucket.org at:

http://bitbucket.org/mozman/bintrees
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