Source code for pygtrie

# -*- coding: utf-8 -*-
"""Pure Python implementation of a trie data structure compatible with Python
2.x and Python 3.x.

`Trie data structure <http://en.wikipedia.org/wiki/Trie>`_, also known as radix
or prefix tree, is a tree associating keys to values where all the descendants
of a node have a common prefix (associated with that node).

The trie module contains :class:`pygtrie.Trie`, :class:`pygtrie.CharTrie` and
:class:`pygtrie.StringTrie` classes each implementing a mutable mapping
interface, i.e. :class:`dict` interface.  As such, in most circumstances,
:class:`pygtrie.Trie` could be used as a drop-in replacement for
a :class:`dict`, but the prefix nature of the data structure is trie’s real
strength.

The module also contains :class:`pygtrie.PrefixSet` class which uses a trie to
store a set of prefixes such that a key is contained in the set if it or its
prefix is stored in the set.

Features
--------

- A full mutable mapping implementation.

- Supports iterating over as well as deleting of a branch of a trie
  (i.e. subtrie)

- Supports prefix checking as well as shortest and longest prefix
  look-up.

- Extensible for any kind of user-defined keys.

- A PrefixSet supports “all keys starting with given prefix” logic.

- Can store any value including None.

For a few simple examples see ``example.py`` file.
"""

from __future__ import absolute_import, division, print_function

__author__ = 'Michal Nazarewicz <mina86@mina86.com>'
__copyright__ = ('Copyright 2014-2017 Google LLC',
                 'Copyright 2018-2020 Michal Nazarewicz <mina86@mina86.com>')
# __version__ = '' # set by setup.py sdist or build


import copy as _copy
import operator as _operator
try:
    import collections.abc as _abc
except ImportError:  # Python 2 compatibility
    import collections as _abc


[docs]class ShortKeyError(KeyError): """Raised when given key is a prefix of an existing longer key but does not have a value associated with itself."""
class _NoChildren(object): """Collection representing lack of any children. Also acts as an empty iterable and an empty iterator. This isn’t the cleanest designs but it makes various things more concise and avoids object allocations in a few places. Don’t create objects of this type directly; instead use _EMPTY singleton. """ __slots__ = () def __bool__(self): return False __nonzero__ = __bool__ def __len__(self): return 0 def __iter__(self): return self iteritems = sorted_items = __iter__ def __next__(self): raise StopIteration() next = __next__ def get(self, _step): return None def add(self, parent, step): node = _Node() parent.children = _OneChild(step, node) return node require = add def copy(self, _make_copy, _queue): return self def __deepcopy__(self, memo): return self # delete is not implemented on purpose since it should never be called on # a node with no children. _EMPTY = _NoChildren() class _OneChild(object): """Children collection representing a single child.""" __slots__ = ('step', 'node') def __init__(self, step, node): self.step = step self.node = node def __bool__(self): return True __nonzero__ = __bool__ def __len__(self): return 1 def sorted_items(self): return [(self.step, self.node)] def iteritems(self): return iter(((self.step, self.node),)) def get(self, step): return self.node if step == self.step else None def add(self, parent, step): node = _Node() parent.children = _Children((self.step, self.node), (step, node)) return node def require(self, parent, step): return self.node if self.step == step else self.add(parent, step) def delete(self, parent, _step): parent.children = _EMPTY def copy(self, make_copy, queue): cpy = _OneChild(make_copy(self.step), self.node.shallow_copy(make_copy)) queue.append((cpy.node,)) return cpy class _Children(dict): """Children collection representing more than one child.""" __slots__ = () def __init__(self, *items): super(_Children, self).__init__(items) if hasattr(dict, 'iteritems'): # Python 2 compatibility def sorted_items(self): items = self.items() items.sort() return items else: def sorted_items(self): return sorted(self.items()) def iteritems(self): return iter(self.items()) def add(self, _parent, step): self[step] = node = _Node() return node def require(self, _parent, step): return self.setdefault(step, _Node()) def delete(self, parent, step): del self[step] if len(self) == 1: parent.children = _OneChild(*self.popitem()) def copy(self, make_copy, queue): cpy = _Children() cpy.update((make_copy(step), node.shallow_copy(make_copy)) for step, node in self.items()) queue.append(cpy.values()) return cpy class _Node(object): """A single node of a trie. Stores value associated with the node and dictionary of children. """ __slots__ = ('children', 'value') def __init__(self): self.children = _EMPTY self.value = _EMPTY def iterate(self, path, shallow, iteritems): """Yields all the nodes with values associated to them in the trie. Args: path: Path leading to this node. Used to construct the key when returning value of this node and as a prefix for children. shallow: Perform a shallow traversal, i.e. do not yield nodes if their prefix has been yielded. iteritems: A callable taking ``node.children`` as sole argument and returning an iterable of children as ``(step, node)`` pair. The callable would typically call ``iteritems`` or ``sorted_items`` method on the argument depending on whether sorted output is desired. Yields: ``(path, value)`` tuples. """ # Use iterative function with stack on the heap so we don't hit Python's # recursion depth limits. node = self stack = [] while True: if node.value is not _EMPTY: yield path, node.value if (not shallow or node.value is _EMPTY) and node.children: stack.append(iter(iteritems(node.children))) path.append(None) while True: try: step, node = next(stack[-1]) path[-1] = step break except StopIteration: stack.pop() path.pop() except IndexError: return def traverse(self, node_factory, path_conv, path, iteritems): """Traverses the node and returns another type of node from factory. Args: node_factory: Callable to construct return value. path_conv: Callable to convert node path to a key. path: Current path for this node. iteritems: A callable taking ``node.children`` as sole argument and returning an iterable of children as ``(step, node)`` pair. The callable would typically call ``iteritems`` or ``sorted_items`` method on the argument depending on whether sorted output is desired. Returns: An object constructed by calling node_factory(path_conv, path, children, value=...), where children are constructed by node_factory from the children of this node. There doesn't need to be 1:1 correspondence between original nodes in the trie and constructed nodes (see make_test_node_and_compress in test.py). """ children = self.children and ( node.traverse(node_factory, path_conv, path + [step], iteritems) for step, node in iteritems(self.children)) value_maybe = () if self.value is not _EMPTY: value_maybe = (self.value,) return node_factory(path_conv, tuple(path), children, *value_maybe) def equals(self, other): """Returns whether this and other node are recursively equal.""" # Like iterate, we don't recurse so this works on deep tries. a, b = self, other stack = [] while True: if a.value != b.value or len(a.children) != len(b.children): return False if len(a.children) == 1: # We know a.children and b.children are both _OneChild objects # but pylint doesn’t recognise that: pylint: disable=no-member if a.children.step != b.children.step: return False a = a.children.node b = b.children.node continue if a.children: stack.append((a.children.iteritems(), b.children)) while True: try: key, a = next(stack[-1][0]) b = stack[-1][1][key] break except StopIteration: stack.pop() except IndexError: return True except KeyError: return False __bool__ = __nonzero__ = __hash__ = None def shallow_copy(self, make_copy): """Returns a copy of the node which shares the children property.""" cpy = _Node() cpy.children = self.children cpy.value = make_copy(self.value) return cpy def copy(self, make_copy): """Returns a copy of the node structure.""" cpy = self.shallow_copy(make_copy) queue = [(cpy,)] while queue: for node in queue.pop(): node.children = node.children.copy(make_copy, queue) return cpy def __getstate__(self): """Get state used for pickling. The state is encoded as a list of simple commands which consist of an integer and some command-dependent number of arguments. The commands modify what the current node is by navigating the trie up and down and setting node values. Possible commands are: * [n, step0, step1, ..., stepn-1, value], for n >= 0, specifies step needed to reach the next current node as well as its new value. There is no way to create a child node without setting its (or its descendant's) value. * [-n], for -n < 0, specifies to go up n steps in the trie. When encoded as a state, the commands are flattened into a single list. For example:: [ 0, 'Root', 2, 'Foo', 'Bar', 'Root/Foo/Bar Node', -1, 1, 'Baz', 'Root/Foo/Baz Node', -2, 1, 'Qux', 'Root/Qux Node' ] Creates the following hierarchy:: -* value: Root +-- Foo --* no value | +-- Bar -- * value: Root/Foo/Bar Node | +-- Baz -- * value: Root/Foo/Baz Node +-- Qux -- * value: Root/Qux Node Returns: A pickable state which can be passed to :func:`_Node.__setstate__` to reconstruct the node and its full hierarchy. """ # Like iterate, we don't recurse so pickling works on deep tries. state = [] if self.value is _EMPTY else [0] last_cmd = 0 node = self stack = [] while True: if node.value is not _EMPTY: last_cmd = 0 state.append(node.value) stack.append(node.children.iteritems()) while True: step, node = next(stack[-1], (None, None)) if node is not None: break if last_cmd < 0: state[-1] -= 1 else: last_cmd = -1 state.append(-1) stack.pop() if not stack: state.pop() # Final -n command is not necessary return state if last_cmd > 0: last_cmd += 1 state[-last_cmd] += 1 else: last_cmd = 1 state.append(1) state.append(step) def __setstate__(self, state): """Unpickles node. See :func:`_Node.__getstate__`.""" self.__init__() state = iter(state) stack = [self] for cmd in state: if cmd < 0: del stack[cmd:] else: while cmd > 0: parent = stack[-1] stack.append(parent.children.add(parent, next(state))) cmd -= 1 stack[-1].value = next(state)
[docs]class Trie(_abc.MutableMapping): """A trie implementation with dict interface plus some extensions. Keys used with the :class:`pygtrie.Trie` class must be iterable which each component being a hashable objects. In other words, for a given key, ``dict.fromkeys(key)`` must be valid expression. In particular, strings work well as trie keys, however when getting them back (for example via :func:`Trie.iterkeys` method), instead of strings, tuples of characters are produced. For that reason, :class:`pygtrie.CharTrie` or :class:`pygtrie.StringTrie` classes may be preferred when using string keys. """
[docs] def __init__(self, *args, **kwargs): """Initialises the trie. Arguments are interpreted the same way :func:`Trie.update` interprets them. """ self._root = _Node() self._sorted = False self.update(*args, **kwargs)
@property def _iteritems(self): """Returns function returning iterable over items of its argument. Returns: A function which returns an iterable over items in a dictionary passed to it as an argument. If child nodes sorting has been enabled (via :func:`Trie.enable_sorting` method), returned function will go through the items in sorted order. """ return _operator.methodcaller( 'sorted_items' if self._sorted else 'iteritems')
[docs] def enable_sorting(self, enable=True): """Enables sorting of child nodes when iterating and traversing. Normally, child nodes are not sorted when iterating or traversing over the trie (just like dict elements are not sorted). This method allows sorting to be enabled (which was the behaviour prior to pygtrie 2.0 release). For Trie class, enabling sorting of children is identical to simply sorting the list of items since Trie returns keys as tuples. However, for other implementations such as StringTrie the two may behave subtly different. For example, sorting items might produce:: root/foo-bar root/foo/baz even though foo comes before foo-bar. Args: enable: Whether to enable sorting of child nodes. """ self._sorted = bool(enable)
[docs] def clear(self): """Removes all the values from the trie.""" self._root = _Node()
[docs] def update(self, *args, **kwargs): # pylint: disable=signature-differs """Updates stored values. Works like :meth:`dict.update`.""" if len(args) > 1: raise ValueError('update() takes at most one positional argument, ' '%d given.' % len(args)) # We have this here instead of just letting MutableMapping.update() # handle things because it will iterate over keys and for each key # retrieve the value. With Trie, this may be expensive since the path # to the node would have to be walked twice. Instead, we have our own # implementation where iteritems() is used avoiding the unnecessary # value look-up. if args and isinstance(args[0], Trie): for key, value in args[0].items(): self[key] = value args = () super(Trie, self).update(*args, **kwargs)
[docs] def copy(self, __make_copy=lambda x: x): """Returns a shallow copy of the object.""" # pylint: disable=protected-access cpy = self.__class__() cpy.__dict__ = self.__dict__.copy() cpy._root = self._root.copy(__make_copy) return cpy
def __copy__(self): return self.copy() def __deepcopy__(self, memo): return self.copy(lambda x: _copy.deepcopy(x, memo))
[docs] @classmethod def fromkeys(cls, keys, value=None): """Creates a new trie with given keys set. This is roughly equivalent to calling the constructor with a ``(key, value) for key in keys`` generator. Args: keys: An iterable of keys that should be set in the new trie. value: Value to associate with given keys. Returns: A new trie where each key from ``keys`` has been set to the given value. """ trie = cls() for key in keys: trie[key] = value return trie
def _get_node(self, key): """Returns node for given key. Creates it if requested. Args: key: A key to look for. Returns: ``(node, trace)`` tuple where ``node`` is the node for given key and ``trace`` is a list specifying path to reach the node including all the encountered nodes. Each element of trace is a ``(step, node)`` tuple where ``step`` is a step from parent node to given node and ``node`` is node on the path. The first element of the path is always ``(None, self._root)``. Raises: KeyError: If there is no node for the key. """ node = self._root trace = [(None, node)] for step in self.__path_from_key(key): # pylint thinks node.children is always _NoChildren and thus that # we’re assigning None here; pylint: disable=assignment-from-none node = node.children.get(step) if node is None: raise KeyError(key) trace.append((step, node)) return node, trace def _set_node(self, key, value, only_if_missing=False): """Sets value for a given key. Args: key: Key to set value of. value: Value to set to. only_if_missing: If true, value won't be changed if the key is already associated with a value. Returns: The node. """ node = self._root for step in self.__path_from_key(key): node = node.children.require(node, step) if node.value is _EMPTY or not only_if_missing: node.value = value return node def _set_node_if_no_prefix(self, key): """Sets given key to True but only if none of its prefixes are present. If value is set, removes all ancestors of the node. This is a method for exclusive use by PrefixSet. Args: key: Key to set value of. """ steps = iter(self.__path_from_key(key)) node = self._root try: while node.value is _EMPTY: node = node.children.require(node, next(steps)) except StopIteration: node.value = True node.children = _EMPTY def __iter__(self): return self.iterkeys() # pylint: disable=arguments-differ
[docs] def iteritems(self, prefix=_EMPTY, shallow=False): """Yields all nodes with associated values with given prefix. Only nodes with values are output. For example:: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo'] = 'Foo' >>> t['foo/bar/baz'] = 'Baz' >>> t['qux'] = 'Qux' >>> sorted(t.items()) [('foo', 'Foo'), ('foo/bar/baz', 'Baz'), ('qux', 'Qux')] Items are generated in topological order (i.e. parents before child nodes) but the order of siblings is unspecified. At an expense of efficiency, :func:`Trie.enable_sorting` method can turn deterministic ordering of siblings. With ``prefix`` argument, only items with specified prefix are generated (i.e. only given subtrie is traversed) as demonstrated by:: >>> t.items(prefix='foo') [('foo', 'Foo'), ('foo/bar/baz', 'Baz')] With ``shallow`` argument, if a node has value associated with it, it's children are not traversed even if they exist which can be seen in:: >>> sorted(t.items(shallow=True)) [('foo', 'Foo'), ('qux', 'Qux')] Args: prefix: Prefix to limit iteration to. shallow: Perform a shallow traversal, i.e. do not yield items if their prefix has been yielded. Yields: ``(key, value)`` tuples. Raises: KeyError: If ``prefix`` does not match any node. """ node, _ = self._get_node(prefix) for path, value in node.iterate(list(self.__path_from_key(prefix)), shallow, self._iteritems): yield (self._key_from_path(path), value)
[docs] def iterkeys(self, prefix=_EMPTY, shallow=False): """Yields all keys having associated values with given prefix. This is equivalent to taking first element of tuples generated by :func:`Trie.iteritems` which see for more detailed documentation. Args: prefix: Prefix to limit iteration to. shallow: Perform a shallow traversal, i.e. do not yield keys if their prefix has been yielded. Yields: All the keys (with given prefix) with associated values in the trie. Raises: KeyError: If ``prefix`` does not match any node. """ for key, _ in self.iteritems(prefix=prefix, shallow=shallow): yield key
[docs] def itervalues(self, prefix=_EMPTY, shallow=False): """Yields all values associated with keys with given prefix. This is equivalent to taking second element of tuples generated by :func:`Trie.iteritems` which see for more detailed documentation. Args: prefix: Prefix to limit iteration to. shallow: Perform a shallow traversal, i.e. do not yield values if their prefix has been yielded. Yields: All the values associated with keys (with given prefix) in the trie. Raises: KeyError: If ``prefix`` does not match any node. """ node, _ = self._get_node(prefix) for _, value in node.iterate(list(self.__path_from_key(prefix)), shallow, self._iteritems): yield value
[docs] def items(self, prefix=_EMPTY, shallow=False): """Returns a list of ``(key, value)`` pairs in given subtrie. This is equivalent to constructing a list from generator returned by :func:`Trie.iteritems` which see for more detailed documentation. """ return list(self.iteritems(prefix=prefix, shallow=shallow))
[docs] def keys(self, prefix=_EMPTY, shallow=False): """Returns a list of all the keys, with given prefix, in the trie. This is equivalent to constructing a list from generator returned by :func:`Trie.iterkeys` which see for more detailed documentation. """ return list(self.iterkeys(prefix=prefix, shallow=shallow))
[docs] def values(self, prefix=_EMPTY, shallow=False): """Returns a list of values in given subtrie. This is equivalent to constructing a list from generator returned by :func:`Trie.itervalues` which see for more detailed documentation. """ return list(self.itervalues(prefix=prefix, shallow=shallow))
[docs] def __len__(self): """Returns number of values in a trie. Note that this method is expensive as it iterates over the whole trie. """ return sum(1 for _ in self.itervalues())
def __bool__(self): return self._root.value is not _EMPTY or bool(self._root.children) __nonzero__ = __bool__ __hash__ = None HAS_VALUE = 1 HAS_SUBTRIE = 2
[docs] def has_node(self, key): """Returns whether given node is in the trie. Return value is a bitwise or of ``HAS_VALUE`` and ``HAS_SUBTRIE`` constants indicating node has a value associated with it and that it is a prefix of another existing key respectively. Both of those are independent of each other and all of the four combinations are possible. For example:: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo/bar'] = 'Bar' >>> t['foo/bar/baz'] = 'Baz' >>> t.has_node('qux') == 0 True >>> t.has_node('foo/bar/baz') == pygtrie.Trie.HAS_VALUE True >>> t.has_node('foo') == pygtrie.Trie.HAS_SUBTRIE True >>> t.has_node('foo/bar') == (pygtrie.Trie.HAS_VALUE | ... pygtrie.Trie.HAS_SUBTRIE) True There are two higher level methods built on top of this one which give easier interface for the information. :func:`Trie.has_key` returns whether node has a value associated with it and :func:`Trie.has_subtrie` checks whether node is a prefix. Continuing previous example:: >>> t.has_key('qux'), t.has_subtrie('qux') (False, False) >>> t.has_key('foo/bar/baz'), t.has_subtrie('foo/bar/baz') (True, False) >>> t.has_key('foo'), t.has_subtrie('foo') (False, True) >>> t.has_key('foo/bar'), t.has_subtrie('foo/bar') (True, True) Args: key: A key to look for. Returns: Non-zero if node exists and if it does a bit-field denoting whether it has a value associated with it and whether it has a subtrie. """ try: node, _ = self._get_node(key) except KeyError: return 0 return ((self.HAS_VALUE * (node.value is not _EMPTY)) | (self.HAS_SUBTRIE * bool(node.children)))
[docs] def has_key(self, key): """Indicates whether given key has value associated with it. See :func:`Trie.has_node` for more detailed documentation. """ return bool(self.has_node(key) & self.HAS_VALUE)
[docs] def has_subtrie(self, key): """Returns whether given key is a prefix of another key in the trie. See :func:`Trie.has_node` for more detailed documentation. """ return bool(self.has_node(key) & self.HAS_SUBTRIE)
@staticmethod def _slice_maybe(key_or_slice): """Checks whether argument is a slice or a plain key. Args: key_or_slice: A key or a slice to test. Returns: ``(key, is_slice)`` tuple. ``is_slice`` indicates whether ``key_or_slice`` is a slice and ``key`` is either ``key_or_slice`` itself (if it's not a slice) or slice's start position. Raises: TypeError: If ``key_or_slice`` is a slice whose stop or step are not ``None`` In other words, only ``[key:]`` slices are valid. """ if isinstance(key_or_slice, slice): if key_or_slice.stop is not None or key_or_slice.step is not None: raise TypeError(key_or_slice) return key_or_slice.start, True return key_or_slice, False
[docs] def __getitem__(self, key_or_slice): """Returns value associated with given key or raises KeyError. When argument is a single key, value for that key is returned (or :class:`KeyError` exception is thrown if the node does not exist or has no value associated with it). When argument is a slice, it must be one with only `start` set in which case the access is identical to :func:`Trie.itervalues` invocation with prefix argument. Example: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo/bar'] = 'Bar' >>> t['foo/baz'] = 'Baz' >>> t['qux'] = 'Qux' >>> t['foo/bar'] 'Bar' >>> sorted(t['foo':]) ['Bar', 'Baz'] >>> t['foo'] # doctest: +IGNORE_EXCEPTION_DETAIL Traceback (most recent call last): ... ShortKeyError: 'foo' Args: key_or_slice: A key or a slice to look for. Returns: If a single key is passed, a value associated with given key. If a slice is passed, a generator of values in specified subtrie. Raises: ShortKeyError: If the key has no value associated with it but is a prefix of some key with a value. Note that :class:`ShortKeyError` is subclass of :class:`KeyError`. KeyError: If key has no value associated with it nor is a prefix of an existing key. TypeError: If ``key_or_slice`` is a slice but it's stop or step are not ``None``. """ if self._slice_maybe(key_or_slice)[1]: return self.itervalues(key_or_slice.start) node, _ = self._get_node(key_or_slice) if node.value is _EMPTY: raise ShortKeyError(key_or_slice) return node.value
[docs] def __setitem__(self, key_or_slice, value): """Sets value associated with given key. If `key_or_slice` is a key, simply associate it with given value. If it is a slice (which must have `start` set only), it in addition clears any subtrie that might have been attached to particular key. For example:: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo/bar'] = 'Bar' >>> t['foo/baz'] = 'Baz' >>> sorted(t.keys()) ['foo/bar', 'foo/baz'] >>> t['foo':] = 'Foo' >>> t.keys() ['foo'] Args: key_or_slice: A key to look for or a slice. If it is a slice, the whole subtrie (if present) will be replaced by a single node with given value set. value: Value to set. Raises: TypeError: If key is a slice whose stop or step are not None. """ key, is_slice = self._slice_maybe(key_or_slice) node = self._set_node(key, value) if is_slice: node.children = _EMPTY
[docs] def setdefault(self, key, default=None): """Sets value of a given node if not set already. Also returns it. In contrast to :func:`Trie.__setitem__`, this method does not accept slice as a key. """ return self._set_node(key, default, only_if_missing=True).value
@staticmethod def _pop_value(trace): """Removes value from given node and removes any empty nodes. Args: trace: Trace to the node to cleanup as returned by :func:`Trie._get_node`. The last element of the trace denotes the node to get value of. Returns: Value which was held in the node at the end of specified trace. This may be _EMPTY if the node didn’t have a value in the first place. """ i = len(trace) - 1 # len(path) >= 1 since root is always there step, node = trace[i] value, node.value = node.value, _EMPTY while i and node.value is _EMPTY and not node.children: i -= 1 parent_step, parent = trace[i] parent.children.delete(parent, step) step, node = parent_step, parent return value
[docs] def pop(self, key, default=_EMPTY): """Deletes value associated with given key and returns it. Args: key: A key to look for. default: If specified, value that will be returned if given key has no value associated with it. If not specified, method will throw KeyError in such cases. Returns: Removed value, if key had value associated with it, or ``default`` (if given). Raises: ShortKeyError: If ``default`` has not been specified and the key has no value associated with it but is a prefix of some key with a value. Note that :class:`ShortKeyError` is subclass of :class:`KeyError`. KeyError: If default has not been specified and key has no value associated with it nor is a prefix of an existing key. """ try: _, trace = self._get_node(key) except KeyError: if default is not _EMPTY: return default raise value = self._pop_value(trace) if value is not _EMPTY: return value if default is not _EMPTY: return default raise ShortKeyError()
[docs] def popitem(self): """Deletes an arbitrary value from the trie and returns it. There is no guarantee as to which item is deleted and returned. Neither in respect to its lexicographical nor topological order. Returns: ``(key, value)`` tuple indicating deleted key. Raises: KeyError: If the trie is empty. """ if not self: raise KeyError() node = self._root trace = [(None, node)] while node.value is _EMPTY: step, node = next(node.children.iteritems()) trace.append((step, node)) key = self._key_from_path((step for step, _ in trace[1:])) return key, self._pop_value(trace)
[docs] def __delitem__(self, key_or_slice): """Deletes value associated with given key or raises KeyError. If argument is a key, value associated with it is deleted. If the key is also a prefix, its descendents are not affected. On the other hand, if the argument is a slice (in which case it must have only start set), the whole subtrie is removed. For example:: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo'] = 'Foo' >>> t['foo/bar'] = 'Bar' >>> t['foo/bar/baz'] = 'Baz' >>> del t['foo/bar'] >>> t.keys() ['foo', 'foo/bar/baz'] >>> del t['foo':] >>> t.keys() [] Args: key_or_slice: A key to look for or a slice. If key is a slice, the whole subtrie will be removed. Raises: ShortKeyError: If the key has no value associated with it but is a prefix of some key with a value. This is not thrown if key_or_slice is a slice -- in such cases, the whole subtrie is removed. Note that :class:`ShortKeyError` is subclass of :class:`KeyError`. KeyError: If key has no value associated with it nor is a prefix of an existing key. TypeError: If key is a slice whose stop or step are not ``None``. """ key, is_slice = self._slice_maybe(key_or_slice) node, trace = self._get_node(key) if is_slice: node.children = _EMPTY elif node.value is _EMPTY: raise ShortKeyError(key) self._pop_value(trace)
class _NoneStep(object): """Representation of a non-existent step towards non-existent node.""" __slots__ = () def __bool__(self): return False __nonzero__ = __bool__ def get(self, default=None): return default is_set = has_subtrie = property(__bool__) key = value = property(lambda self: None) def __getitem__(self, index): """Makes object appear like a (key, value) tuple. This is deprecated and for backwards-compatibility only. Prefer using ``key`` and ``value`` properties directly. Args: index: Element index to return. Zero for key, one for value. Returns: ``self.key`` if index is ``0``, ``self.value`` if it's ``1``. Otherwise raises an IndexError exception. Raises: IndexError: if index is not 0 or 1. KeyError: if index is 1 but node has no value assigned. """ if index == 0: return self.key if index == 1: return self.value raise IndexError('index out of range') def __repr__(self): return '(None Step)' class _Step(_NoneStep): """Representation of a single step on a path towards particular node.""" __slots__ = ('_trie', '_path', '_pos', '_node', '__key') def __init__(self, trie, path, pos, node): self._trie = trie self._path = path self._pos = pos self._node = node def __bool__(self): return True __nonzero__ = __bool__ @property def is_set(self): """Returns whether the node has value assigned to it.""" return self._node.value is not _EMPTY @property def has_subtrie(self): """Returns whether the node has any children.""" return bool(self._node.children) def get(self, default=None): """Returns node's value or the default if value is not assigned.""" v = self._node.value return default if v is _EMPTY else v def set(self, value): """Deprecated. Use ``step.value = value`` instead.""" self._node.value = value def setdefault(self, value): """Assigns value to the node if one is not set then returns it.""" if self._node.value is _EMPTY: self._node.value = value return self._node.value def __repr__(self): return '(%r: %r)' % (self.key, self.value) @property def key(self): """Returns key of the node.""" if not hasattr(self, '_Step__key'): # pylint:disable=protected-access,attribute-defined-outside-init self.__key = self._trie._key_from_path(self._path[:self._pos]) return self.__key @property def value(self): """Returns node's value or raises KeyError.""" v = self._node.value if v is _EMPTY: raise ShortKeyError(self.key) return v @value.setter def value(self, value): self._node.value = value _NONE_STEP = _NoneStep()
[docs] def walk_towards(self, key): """Yields nodes on the path to given node. Args: key: Key of the node to look for. Yields: :class:`pygtrie.Trie._Step` objects which can be used to extract or set node's value as well as get node's key. When representing nodes with assigned values, the objects can be treated as ``(k, value)`` pairs denoting keys with associated values encountered on the way towards the specified key. This is deprecated, prefer using ``key`` and ``value`` properties or ``get`` method of the object. Raises: KeyError: If node with given key does not exist. It's all right if they value is not assigned to the node provided it has a child node. Because the method is a generator, the exception is raised only once a missing node is encountered. """ node = self._root path = self.__path_from_key(key) pos = 0 while True: yield self._Step(self, path, pos, node) if pos == len(path): break # pylint thinks node.children is always _NoChildren and thus that # we’re assigning None here; pylint: disable=assignment-from-none node = node.children.get(path[pos]) if node is None: raise KeyError(key) pos += 1
[docs] def prefixes(self, key): """Walks towards the node specified by key and yields all found items. Example: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo'] = 'Foo' >>> t['foo/bar/baz'] = 'Baz' >>> list(t.prefixes('foo/bar/baz/qux')) [('foo': 'Foo'), ('foo/bar/baz': 'Baz')] >>> list(t.prefixes('does/not/exist')) [] Args: key: Key to look for. Yields: :class:`pygtrie.Trie._Step` objects which can be used to extract or set node's value as well as get node's key. The objects can be treated as ``(k, value)`` pairs denoting keys with associated values encountered on the way towards the specified key. This is deprecated, prefer using ``key`` and ``value`` properties of the object. """ try: for step in self.walk_towards(key): if step.is_set: yield step except KeyError: pass
[docs] def shortest_prefix(self, key): """Finds the shortest prefix of a key with a value. This is roughly equivalent to taking the first object yielded by :func:`Trie.prefixes` with additional handling for situations when no prefixes are found. Example: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo'] = 'Foo' >>> t['foo/bar/baz'] = 'Baz' >>> t.shortest_prefix('foo/bar/baz/qux') ('foo': 'Foo') >>> t.shortest_prefix('foo/bar/baz/qux').key 'foo' >>> t.shortest_prefix('foo/bar/baz/qux').value 'Foo' >>> t.shortest_prefix('does/not/exist') (None Step) >>> bool(t.shortest_prefix('does/not/exist')) False Args: key: Key to look for. Returns: :class:`pygtrie.Trie._Step` object (which can be used to extract or set node's value as well as get node's key), or a :class:`pygtrie.Trie._NoneStep` object (which is falsy value simulating a _Step with ``None`` key and value) if no prefix is found. The object can be treated as ``(key, value)`` pair denoting key with associated value of the prefix. This is deprecated, prefer using ``key`` and ``value`` properties of the object. """ return next(self.prefixes(key), self._NONE_STEP)
[docs] def longest_prefix(self, key): """Finds the longest prefix of a key with a value. This is roughly equivalent to taking the last object yielded by :func:`Trie.prefixes` with additional handling for situations when no prefixes are found. Example: >>> import pygtrie >>> t = pygtrie.StringTrie() >>> t['foo'] = 'Foo' >>> t['foo/bar/baz'] = 'Baz' >>> t.longest_prefix('foo/bar/baz/qux') ('foo/bar/baz': 'Baz') >>> t.longest_prefix('foo/bar/baz/qux').key 'foo/bar/baz' >>> t.longest_prefix('foo/bar/baz/qux').value 'Baz' >>> t.longest_prefix('does/not/exist') (None Step) >>> bool(t.longest_prefix('does/not/exist')) False Args: key: Key to look for. Returns: :class:`pygtrie.Trie._Step` object (which can be used to extract or set node's value as well as get node's key), or a :class:`pygtrie.Trie._NoneStep` object (which is falsy value simulating a _Step with ``None`` key and value) if no prefix is found. The object can be treated as ``(key, value)`` pair denoting key with associated value of the prefix. This is deprecated, prefer using ``key`` and ``value`` properties of the object. """ ret = self._NONE_STEP for ret in self.prefixes(key): pass return ret
def __eq__(self, other): # pylint: disable=protected-access return self is other or self._root.equals(other._root) def __ne__(self, other): return not self == other def _str_items(self, fmt='%s: %s'): return ', '.join(fmt % item for item in self.iteritems()) def __str__(self): return '%s(%s)' % (type(self).__name__, self._str_items()) def __repr__(self): return '%s([%s])' % (type(self).__name__, self._str_items('(%r, %r)')) def __path_from_key(self, key): """Converts a user visible key object to internal path representation. Args: key: User supplied key or ``_EMPTY``. Returns: An empty tuple if ``key`` was ``_EMPTY``, otherwise whatever :func:`Trie._path_from_key` returns. Raises: TypeError: If ``key`` is of invalid type. """ return () if key is _EMPTY else self._path_from_key(key) def _path_from_key(self, key): """Converts a user visible key object to internal path representation. The default implementation simply returns key. Args: key: User supplied key. Returns: A path, which is an iterable of steps. Each step must be hashable. Raises: TypeError: If key is of invalid type. """ return key def _key_from_path(self, path): """Converts an internal path into a user visible key object. The default implementation creates a tuple from the path. Args: path: Internal path representation. Returns: A user visible key object. """ return tuple(path)
[docs] def traverse(self, node_factory, prefix=_EMPTY): """Traverses the tree using node_factory object. node_factory is a callable which accepts (path_conv, path, children, value=...) arguments, where path_conv is a lambda converting path representation to key, path is the path to this node, children is an iterable of children nodes constructed by node_factory, optional value is the value associated with the path. node_factory's children argument is an iterator which has a few consequences: * To traverse into node's children, the object must be iterated over. This can by accomplished by a simple ``children = list(children)`` statement. * Ignoring the argument allows node_factory to stop the traversal from going into the children of the node. In other words, whole subtries can be removed from traversal if node_factory chooses so. * If children is stored as is (i.e. as a iterator) when it is iterated over later on it may see an inconsistent state of the trie if it has changed between invocation of this method and the iteration. However, to allow constant-time determination whether the node has children or not, the iterator implements bool conversion such that ``has_children = bool(children)`` will tell whether node has children without iterating over them. (Note that ``bool(children)`` will continue returning ``True`` even if the iterator has been iterated over). :func:`Trie.traverse` has two advantages over :func:`Trie.iteritems` and similar methods: 1. it allows subtries to be skipped completely when going through the list of nodes based on the property of the parent node; and 2. it represents structure of the trie directly making it easy to convert structure into a different representation. For example, the below snippet prints all files in current directory counting how many HTML files were found but ignores hidden files and directories (i.e. those whose names start with a dot):: import os import pygtrie t = pygtrie.StringTrie(separator=os.sep) # Construct a trie with all files in current directory and all # of its sub-directories. Files get set a True value. # Directories are represented implicitly by being prefixes of # files. for root, _, files in os.walk('.'): for name in files: t[os.path.join(root, name)] = True def traverse_callback(path_conv, path, children, is_file=False): if path and path[-1] != '.' and path[-1][0] == '.': # Ignore hidden directory (but accept root node and '.') return 0 elif is_file: print path_conv(path) return int(path[-1].endswith('.html')) else: # Otherwise, it's a directory. Traverse into children. return sum(children) print t.traverse(traverse_callback) As documented, ignoring the children argument causes subtrie to be omitted and not walked into. In the next example, the trie is converted to a tree representation where child nodes include a pointer to their parent. As before, hidden files and directories are ignored:: import os import pygtrie t = pygtrie.StringTrie(separator=os.sep) for root, _, files in os.walk('.'): for name in files: t[os.path.join(root, name)] = True class File(object): def __init__(self, name): self.name = name self.parent = None class Directory(File): def __init__(self, name, children): super(Directory, self).__init__(name) self._children = children for child in children: child.parent = self def traverse_callback(path_conv, path, children, is_file=False): if not path or path[-1] == '.' or path[-1][0] != '.': if is_file: return File(path[-1]) children = filter(None, children) return Directory(path[-1] if path else '', children) root = t.traverse(traverse_callback) Note: Unlike iterators, when used on a deep trie, traverse method is prone to rising a RuntimeError exception when Python's maximum recursion depth is reached. This can be addressed by not iterating over children inside of the node_factory. For example, the below code converts a trie into an undirected graph using adjacency list representation:: def undirected_graph_from_trie(t): '''Converts trie into a graph and returns its nodes.''' Node = collections.namedtuple('Node', 'path neighbours') class Builder(object): def __init__(self, path_conv, path, children, _=None): self.node = Node(path_conv(path), []) self.children = children self.parent = None def build(self, queue): for builder in self.children: builder.parent = self.node queue.append(builder) if self.parent: self.parent.neighbours.append(self.node) self.node.neighbours.append(self.parent) return self.node nodes = [t.traverse(Builder)] i = 0 while i < len(nodes): nodes[i] = nodes[i].build(nodes) i += 1 return nodes Args: node_factory: Makes opaque objects from the keys and values of the trie. prefix: Prefix for node to start traversal, by default starts at root. Returns: Node object constructed by node_factory corresponding to the root node. """ node, _ = self._get_node(prefix) return node.traverse(node_factory, self._key_from_path, list(self.__path_from_key(prefix)), self._iteritems)
traverse.uses_bool_convertible_children = True
[docs]class CharTrie(Trie): """A variant of a :class:`pygtrie.Trie` which accepts strings as keys. The only difference between :class:`pygtrie.CharTrie` and :class:`pygtrie.Trie` is that when :class:`pygtrie.CharTrie` returns keys back to the client (for instance when :func:`Trie.keys` method is called), those keys are returned as strings. Common example where this class can be used is a dictionary of words in a natural language. For example:: >>> import pygtrie >>> t = pygtrie.CharTrie() >>> t['wombat'] = True >>> t['woman'] = True >>> t['man'] = True >>> t['manhole'] = True >>> t.has_subtrie('wo') True >>> t.has_key('man') True >>> t.has_subtrie('man') True >>> t.has_subtrie('manhole') False """ def _key_from_path(self, path): return ''.join(path)
[docs]class StringTrie(Trie): """:class:`pygtrie.Trie` variant accepting strings with a separator as keys. The trie accepts strings as keys which are split into components using a separator specified during initialisation (forward slash, i.e. ``/``, by default). Common example where this class can be used is when keys are paths. For example, it could map from a path to a request handler:: import pygtrie def handle_root(): pass def handle_admin(): pass def handle_admin_images(): pass handlers = pygtrie.StringTrie() handlers[''] = handle_root handlers['/admin'] = handle_admin handlers['/admin/images'] = handle_admin_images request_path = '/admin/images/foo' handler = handlers.longest_prefix(request_path) """
[docs] def __init__(self, *args, **kwargs): # pylint: disable=differing-param-doc """Initialises the trie. Except for a ``separator`` named argument, all other arguments are interpreted the same way :func:`Trie.update` interprets them. Args: *args: Passed to super class initialiser. **kwargs: Passed to super class initialiser. separator: A separator to use when splitting keys into paths used by the trie. "/" is used if this argument is not specified. This named argument is not specified on the function's prototype because of Python's limitations. Raises: TypeError: If ``separator`` is not a string. ValueError: If ``separator`` is empty. """ separator = kwargs.pop('separator', '/') if not isinstance(separator, getattr(__builtins__, 'basestring', str)): raise TypeError('separator must be a string') if not separator: raise ValueError('separator can not be empty') self._separator = separator super(StringTrie, self).__init__(*args, **kwargs)
[docs] @classmethod def fromkeys(cls, keys, value=None, separator='/'): # pylint: disable=arguments-differ trie = cls(separator=separator) for key in keys: trie[key] = value return trie
def __str__(self): if not self: return '%s(separator=%s)' % (type(self).__name__, self._separator) return '%s(%s, separator=%s)' % ( type(self).__name__, self._str_items(), self._separator) def __repr__(self): return '%s([%s], separator=%r)' % ( type(self).__name__, self._str_items('(%r, %r)'), self._separator) def _path_from_key(self, key): return key.split(self._separator) def _key_from_path(self, path): return self._separator.join(path)
[docs]class PrefixSet(_abc.MutableSet): """A set of prefixes. :class:`pygtrie.PrefixSet` works similar to a normal set except it is said to contain a key if the key or it's prefix is stored in the set. For instance, if "foo" is added to the set, the set contains "foo" as well as "foobar". The set supports addition of elements but does *not* support removal of elements. This is because there's no obvious consistent and intuitive behaviour for element deletion. """
[docs] def __init__(self, iterable=(), factory=Trie, **kwargs): """Initialises the prefix set. Args: iterable: A sequence of keys to add to the set. factory: A function used to create a trie used by the :class:`pygtrie.PrefixSet`. kwargs: Additional keyword arguments passed to the factory function. """ super(PrefixSet, self).__init__() self._trie = factory(**kwargs) for key in iterable: self.add(key)
[docs] def copy(self): """Returns a shallow copy of the object.""" return self.__copy__()
def __copy__(self): # pylint: disable=protected-access cpy = self.__class__() cpy.__dict__ = self.__dict__.copy() cpy._trie = self._trie.__copy__() return cpy def __deepcopy__(self, memo): # pylint: disable=protected-access cpy = self.__class__() cpy.__dict__ = self.__dict__.copy() cpy._trie = self._trie.__deepcopy__(memo) return cpy
[docs] def clear(self): """Removes all keys from the set.""" self._trie.clear()
[docs] def __contains__(self, key): """Checks whether set contains key or its prefix.""" return bool(self._trie.shortest_prefix(key)[1])
[docs] def __iter__(self): """Return iterator over all prefixes in the set. See :func:`PrefixSet.iter` method for more info. """ return self._trie.iterkeys()
[docs] def iter(self, prefix=_EMPTY): """Iterates over all keys in the set optionally starting with a prefix. Since a key does not have to be explicitly added to the set to be an element of the set, this method does not iterate over all possible keys that the set contains, but only over the shortest set of prefixes of all the keys the set contains. For example, if "foo" has been added to the set, the set contains also "foobar", but this method will *not* iterate over "foobar". If ``prefix`` argument is given, method will iterate over keys with given prefix only. The keys yielded from the function if prefix is given does not have to be a subset (in mathematical sense) of the keys yielded when there is not prefix. This happens, if the set contains a prefix of the given prefix. For example, if only "foo" has been added to the set, iter method called with no arguments will yield "foo" only. However, when called with "foobar" argument, it will yield "foobar" only. """ if prefix is _EMPTY: return iter(self) if self._trie.has_node(prefix): return self._trie.iterkeys(prefix=prefix) if prefix in self: # Make sure the type of returned keys is consistent. # pylint: disable=protected-access return ( self._trie._key_from_path(self._trie._path_from_key(prefix)),) return ()
[docs] def __len__(self): """Returns number of keys stored in the set. Since a key does not have to be explicitly added to the set to be an element of the set, this method does not count over all possible keys that the set contains (since that would be infinity), but only over the shortest set of prefixes of all the keys the set contains. For example, if "foo" has been added to the set, the set contains also "foobar", but this method will *not* count "foobar". """ return len(self._trie)
[docs] def add(self, value): """Adds given value to the set. If the set already contains prefix of the value being added, this operation has no effect. If the value being added is a prefix of some existing values in the set, those values are deleted and replaced by a single entry for the value being added. For example, if the set contains value "foo" adding a value "foobar" does not change anything. On the other hand, if the set contains values "foobar" and "foobaz", adding a value "foo" will replace those two values with a single value "foo". This makes a difference when iterating over the values or counting number of values. Counter intuitively, adding of a value can *decrease* size of the set. Args: value: Value to add. """ # We're friends with Trie; pylint: disable=protected-access self._trie._set_node_if_no_prefix(value)
[docs] def discard(self, value): """Raises NotImplementedError.""" raise NotImplementedError( 'Removing values from PrefixSet is not implemented.')
[docs] def remove(self, value): """Raises NotImplementedError.""" raise NotImplementedError( 'Removing values from PrefixSet is not implemented.')
[docs] def pop(self): """Raises NotImplementedError.""" raise NotImplementedError( 'Removing values from PrefixSet is not implemented.')