Package provides Binary-, RedBlack- and AVL-Trees in Python and Cython.
Project description
Binary Tree Package
Bintrees Development Stopped
Use sortedcontainers instead: https://pypi.python.org/pypi/sortedcontainers
see also PyCon 2016 presentation: https://www.youtube.com/watch?v=7z2Ki44Vs4E
Advantages:
pure Python no Cython/C dependencies
faster
active development
more & better testing/profiling
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))
__copy__() -> shallow copy support, copy.copy(T)
__deepcopy__() -> deep copy support, copy.deepcopy(T)
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.
Download Binaries for Windows
Documentation
this README.rst
bintrees can be found on GitHub.com at:
NEWS
Version 2.1.0 - 2020-01-02
Use sortedcontainers instead: https://pypi.python.org/pypi/sortedcontainers
Project Status: Inactive
removed official Python 2 support
Version 2.0.7 - 2017-04-28
BUGFIX: foreach (pure Python implementation) works with empty trees
acquire GIL for PyMem_Malloc() and PyMem_Free() calls
Version 2.0.6 - 2017-02-04
BUGFIX: correct deepcopy() for tree in tree
Version 2.0.5 - 2017-02-04
support for copy.deepcopy()
changed status back to Mature, there will be: bugfixes, compatibility checks and simple additions like this deep copy support, because I got feedback, that there are some special cases in which bintrees can be useful.
switched development to 64bit only & MS compilers - on Windows 7 everything works fine now with CPython 2.7/3.5/3.6
Repository moved to GitHub: https://github.com/mozman/bintrees.git
Version 2.0.4 - 2016-01-09
removed logging statements on import
added helper function bintrees.has_fast_tree_support()
HINT: pypy runs faster than CPython with Cython extension
Version 2.0.3 - 2016-01-06
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
Project details
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