bintrees 2.2.0

• 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)]

• __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)

• 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_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))

• 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))

• 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)

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

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