Develop Reference

Use strings as slice indices in Python ? (TypeError: slice indices must be integers or None or have an __index__ method)

I have a sorted array:
arr = ['Alexander', 'Belman', 'Erik', 'Nicholas', ... , 'Zahir']
I would like to do something like this:
arr['B':'M'] # ['Belman', 'Erik']
How can I create a class and implement
__getitem__
__index__
in the right way to achieve this ?
I am thinking of using something like
def __getitem__(self, key):
if isinstance(key, slice):
return [self.list[i] for i in range(key.start, key.stop)]
return self.list[key]
but I don't know how to index the strings. How can I create an
__index__
method to apply a binarySearch to self.list and return the correct indices ?

I think you can get away with as simple implementation as below:
from collections import UserList
class MyList(UserList):
def __getitem__(self, key):
if isinstance(key, slice):
return [e for e in self.data if key.start <= e < key.stop]
# TODO implement the rest of the usecases and/or error handling...
# for now slicing with integers will miserably fail,
# and basic integer indexing returns None
arr = MyList(['Alexander', 'Belman', 'Erik', 'Nicholas', 'Zahir'])
print(arr['B':'M'])
which will output
['Belman', 'Erik']
likewise,
print(arr['Alex':'Er'])
will output
['Alexander', 'Belman']
Note that I used key.start <= e < key.stop to be in line with the inclusive:exclusive ([)) behavior which is used throughout python.
Also note that I implemented only the string slices usecase. You can implement the other usecases and error handling as you see fit.

I also post my solution with binary search using numpy
class Stock():
def __init__(self, name, date):
self.name = name
self.date = np.array(date)
def __getitem__(self, key):
if isinstance(key, slice):
if key.start is not None and key.stop is not None:
return self.date[np.searchsorted(self.date, key.start, side='left', sorter=None):np.searchsorted(self.date, key.stop, side='left', sorter=None)]
elif key.start is not None:
return self.date[np.searchsorted(self.date, key.start, side='left', sorter=None):]
elif key.stop is not None:
return self.date[:np.searchsorted(self.date, key.stop, side='left', sorter=None)]
else:
return self.date[:]
i = np.searchsorted(self.date, key, side='left', sorter=None)
if key != self.date[i]:
raise KeyError('key: {} was not found!'.format(key))
else:
return self.date[i]
aapl = Stock('aapl', ['2010','2012', '2014', '2016', '2018'])
print(aapl['2011':])
print(aapl['2014':'2017'])
print(aapl[:'2016'])
print(aapl['2010'])
print(aapl['2013'])
'''
['2012' '2014' '2016' '2018']
['2014' '2016']
['2010' '2012' '2014']
2010
Traceback (most recent call last):
File "C:\Users\...\Desktop\...\stock.py", line ##, in <module>
print(aapl['2013'])
File "C:\Users\...\Desktop\...\stock.py", line ##, in __getitem__
raise KeyError('key: {} was not found!'.format(key))
KeyError: 'key: 2013 was not found!'
'''

What is the most efficient data structure to build a large word-to-index-to-word dictionary?

I would like to index a very large number of strings (mapping each string to an numeric value) but also be able to retrieve each string from its numeric index.
Using hash tables or python dict is not an option because of memory issues so I decided to use a radix trie to store the strings, I can retrieve the index of any string very quickly and handle a very large number of strings.
My problem is that I also need to retrieve the strings from their numeric index, and if I maintain a "reverse index" list [string1, string2, ..., stringn] I'll loose the memory benefit of the Trie.
I thought maybe the "reverse index" could be a list of pointers to the last node of a kind-of Trie structure but first, there are no pointers in python, and second I'm not sure I can have a "node-level" access to the Trie structure I'm currently using.
Does this kind of data-structure already exists? And if not how would you do this in python?

As per What data structure to use to have O(log n) key AND value lookup? , you need two synchronized data structures for key and value lookups, each holding references to the other's leaf nodes.
The structure for the ID lookup can be anything with sufficient efficientcy -- a balanced tree, a hash table, another trie.
To be able to extract the value from a leaf node reference, a trie needs to allow 1) leaf node references themselves (not necessarily a real Python reference, anything that its API can use); 2) walking up the trie to extract the word from that reference.
Note that a reference is effectively a unique integer so if your IDs are not larger than an integer, it makes sense to reuse something as IDs -- e.g. the trie node references themselves. Then if the trie API can validate such a reference (i.e. tell if it has a used node with such a reference) this will act as the ID lookup and you don't need the 2nd structure at all! This way, the IDs will be non-persistent though 'cuz reference values (effectively memory addresses) change between processes and runs.

I'm answering to myself because I finally end up creating my own data-structure which is perfectly suited for the word-to-index-to-word problem I had, using only python3 built-in functions.
I tried to make it clean and efficient but there's obviously room for improvement and a C binding would be better.
So the final result is a indexedtrie class that looks like a python dict (or defaultdict if you invoke it with a default_factory parameter) but can also be queried like a list because a kind of "reversed index" is automatically maintained.
The keys, which are stored in an internal radix trie, can be any subscriptable object (bytes, strings, tuples, lists) and the values you want to store anything you want inside.
Also the indextrie class is pickable, and you can benefit from the advantages of radix tries regarding "prefix search" and this kind of things!
Each key in the trie is associated with a unique integer index, you can retrieve the key with the index or the index with the key and the whole thing is fast and memory safe so I personally think that's one of the best data-structure in the world and that it should be integrated in python standard library :).
Enough talking, here is the code, feel free to adapt and use it:
"""
A Python3 indexed trie class.
An indexed trie's key can be any subscriptable object.
Keys of the indexed trie are stored using a "radix trie", a space-optimized data-structure which has many advantages (see https://en.wikipedia.org/wiki/Radix_tree).
Also, each key in the indexed trie is associated to a unique index which is build dynamically.
Indexed trie is used like a python dictionary (and even a collections.defaultdict if you want to) but its values can also be accessed or updated (but not created) like a list!
Example:
>>> t = indextrie()
>>> t["abc"] = "hello"
>>> t[0]
'hello'
>>> t["abc"]
'hello'
>>> t.index2key(0)
'abc'
>>> t.key2index("abc")
0
>>> t[:]
[0]
>>> print(t)
{(0, 'abc'): hello}
"""
__author__ = "#fbparis"
_SENTINEL = object()
class _Node(object):
"""
A single node in the trie.
"""
__slots__ = "_children", "_parent", "_index", "_key"
def __init__(self, key, parent, index=None):
self._children = set()
self._key = key
self._parent = parent
self._index = index
self._parent._children.add(self)
class IndexedtrieKey(object):
"""
A pair (index, key) acting as an indexedtrie's key
"""
__slots__ = "index", "key"
def __init__(self, index, key):
self.index = index
self.key = key
def __repr__(self):
return "(%d, %s)" % (self.index, self.key)
class indexedtrie(object):
"""
The indexed trie data-structure.
"""
__slots__ = "_children", "_indexes", "_values", "_nodescount", "_default_factory"
def __init__(self, items=None, default_factory=_SENTINEL):
"""
A list of items can be passed to initialize the indexed trie.
"""
self._children = set()
self.setdefault(default_factory)
self._indexes = []
self._values = []
self._nodescount = 0 # keeping track of nodes count is purely informational
if items is not None:
for k, v in items:
if isinstance(k, IndexedtrieKey):
self.__setitem__(k.key, v)
else:
self.__setitem__(k, v)
#classmethod
def fromkeys(cls, keys, value=_SENTINEL, default_factory=_SENTINEL):
"""
Build a new indexedtrie from a list of keys.
"""
obj = cls(default_factory=default_factory)
for key in keys:
if value is _SENTINEL:
if default_factory is not _SENTINEL:
obj[key] = obj._default_factory()
else:
obj[key] = None
else:
obj[key] = value
return obj
#classmethod
def fromsplit(cls, keys, value=_SENTINEL, default_factory=_SENTINEL):
"""
Build a new indexedtrie from a splitable object.
"""
obj = cls(default_factory=default_factory)
for key in keys.split():
if value is _SENTINEL:
if default_factory is not _SENTINEL:
obj[key] = obj._default_factory()
else:
obj[key] = None
else:
obj[key] = value
return obj
def setdefault(self, factory=_SENTINEL):
"""
"""
if factory is not _SENTINEL:
# indexed trie will act like a collections.defaultdict except in some cases because the __missing__
# method is not implemented here (on purpose).
# That means that simple lookups on a non existing key will return a default value without adding
# the key, which is the more logical way to do.
# Also means that if your default_factory is for example "list", you won't be able to create new
# items with "append" or "extend" methods which are updating the list itself.
# Instead you have to do something like trie["newkey"] += [...]
try:
_ = factory()
except TypeError:
# a default value is also accepted as default_factory, even "None"
self._default_factory = lambda: factory
else:
self._default_factory = factory
else:
self._default_factory = _SENTINEL
def copy(self):
"""
Return a pseudo-shallow copy of the indexedtrie.
Keys and nodes are deepcopied, but if you store some referenced objects in values, only the references will be copied.
"""
return self.__class__(self.items(), default_factory=self._default_factory)
def __len__(self):
return len(self._indexes)
def __repr__(self):
if self._default_factory is not _SENTINEL:
default = ", default_value=%s" % self._default_factory()
else:
default = ""
return "<%s object at %s: %d items, %d nodes%s>" % (self.__class__.__name__, hex(id(self)), len(self), self._nodescount, default)
def __str__(self):
ret = ["%s: %s" % (k, v) for k, v in self.items()]
return "{%s}" % ", ".join(ret)
def __iter__(self):
return self.keys()
def __contains__(self, key_or_index):
"""
Return True if the key or index exists in the indexed trie.
"""
if isinstance(key_or_index, IndexedtrieKey):
return key_or_index.index >= 0 and key_or_index.index < len(self)
if isinstance(key_or_index, int):
return key_or_index >= 0 and key_or_index < len(self)
if self._seems_valid_key(key_or_index):
try:
node = self._get_node(key_or_index)
except KeyError:
return False
else:
return node._index is not None
raise TypeError("invalid key type")
def __getitem__(self, key_or_index):
"""
"""
if isinstance(key_or_index, IndexedtrieKey):
return self._values[key_or_index.index]
if isinstance(key_or_index, int) or isinstance(key_or_index, slice):
return self._values[key_or_index]
if self._seems_valid_key(key_or_index):
try:
node = self._get_node(key_or_index)
except KeyError:
if self._default_factory is _SENTINEL:
raise
else:
return self._default_factory()
else:
if node._index is None:
if self._default_factory is _SENTINEL:
raise KeyError
else:
return self._default_factory()
else:
return self._values[node._index]
raise TypeError("invalid key type")
def __setitem__(self, key_or_index, value):
"""
"""
if isinstance(key_or_index, IndexedtrieKey):
self._values[key_or_index.index] = value
elif isinstance(key_or_index, int):
self._values[key_or_index] = value
elif isinstance(key_or_index, slice):
raise NotImplementedError
elif self._seems_valid_key(key_or_index):
try:
node = self._get_node(key_or_index)
except KeyError:
# create a new node
self._add_node(key_or_index, value)
else:
if node._index is None:
# if node exists but not indexed, we index it and update the value
self._add_to_index(node, value)
else:
# else we update its value
self._values[node._index] = value
else:
raise TypeError("invalid key type")
def __delitem__(self, key_or_index):
"""
"""
if isinstance(key_or_index, IndexedtrieKey):
node = self._indexes[key_or_index.index]
elif isinstance(key_or_index, int):
node = self._indexes[key_or_index]
elif isinstance(key_or_index, slice):
raise NotImplementedError
elif self._seems_valid_key(key_or_index):
node = self._get_node(key_or_index)
if node._index is None:
raise KeyError
else:
raise TypeError("invalid key type")
# switch last index with deleted index (except if deleted index is last index)
last_node, last_value = self._indexes.pop(), self._values.pop()
if node._index != last_node._index:
last_node._index = node._index
self._indexes[node._index] = last_node
self._values[node._index] = last_value
if len(node._children) > 1:
#case 1: node has more than 1 child, only turn index off
node._index = None
elif len(node._children) == 1:
# case 2: node has 1 child
child = node._children.pop()
child._key = node._key + child._key
child._parent = node._parent
node._parent._children.add(child)
node._parent._children.remove(node)
del(node)
self._nodescount -= 1
else:
# case 3: node has no child, check the parent node
parent = node._parent
parent._children.remove(node)
del(node)
self._nodescount -= 1
if hasattr(parent, "_index"):
if parent._index is None and len(parent._children) == 1:
node = parent._children.pop()
node._key = parent._key + node._key
node._parent = parent._parent
parent._parent._children.add(node)
parent._parent._children.remove(parent)
del(parent)
self._nodescount -= 1
#staticmethod
def _seems_valid_key(key):
"""
Return True if "key" can be a valid key (must be subscriptable).
"""
try:
_ = key[:0]
except TypeError:
return False
return True
def keys(self, prefix=None):
"""
Yield keys stored in the indexedtrie where key is a IndexedtrieKey object.
If prefix is given, yield only keys of items with key matching the prefix.
"""
if prefix is None:
for i, node in enumerate(self._indexes):
yield IndexedtrieKey(i, self._get_key(node))
else:
if self._seems_valid_key(prefix):
empty = prefix[:0]
children = [(empty, prefix, child) for child in self._children]
while len(children):
_children = []
for key, prefix, child in children:
if prefix == child._key[:len(prefix)]:
_key = key + child._key
_children.extend([(_key, empty, _child) for _child in child._children])
if child._index is not None:
yield IndexedtrieKey(child._index, _key)
elif prefix[:len(child._key)] == child._key:
_prefix = prefix[len(child._key):]
_key = key + prefix[:len(child._key)]
_children.extend([(_key, _prefix, _child) for _child in child._children])
children = _children
else:
raise ValueError("invalid prefix type")
def values(self, prefix=None):
"""
Yield values stored in the indexedtrie.
If prefix is given, yield only values of items with key matching the prefix.
"""
if prefix is None:
for value in self._values:
yield value
else:
for key in self.keys(prefix):
yield self._values[key.index]
def items(self, prefix=None):
"""
Yield (key, value) pairs stored in the indexedtrie where key is a IndexedtrieKey object.
If prefix is given, yield only (key, value) pairs of items with key matching the prefix.
"""
for key in self.keys(prefix):
yield key, self._values[key.index]
def show_tree(self, node=None, level=0):
"""
Pretty print the internal trie (recursive function).
"""
if node is None:
node = self
for child in node._children:
print("-" * level + "<key=%s, index=%s>" % (child._key, child._index))
if len(child._children):
self.show_tree(child, level + 1)
def _get_node(self, key):
"""
Return the node associated to key or raise a KeyError.
"""
children = self._children
while len(children):
notfound = True
for child in children:
if key == child._key:
return child
if child._key == key[:len(child._key)]:
children = child._children
key = key[len(child._key):]
notfound = False
break
if notfound:
break
raise KeyError
def _add_node(self, key, value):
"""
Add a new key in the trie and updates indexes and values.
"""
children = self._children
parent = self
moved = None
done = len(children) == 0
# we want to insert key="abc"
while not done:
done = True
for child in children:
# assert child._key != key # uncomment if you don't trust me
if child._key == key[:len(child._key)]:
# case 1: child's key is "ab", insert "c" in child's children
parent = child
children = child._children
key = key[len(child._key):]
done = len(children) == 0
break
elif key == child._key[:len(key)]:
# case 2: child's key is "abcd", we insert "abc" in place of the child
# child's parent will be the inserted node and child's key is now "d"
parent = child._parent
moved = child
parent._children.remove(moved)
moved._key = moved._key[len(key):]
break
elif type(key) is type(child._key): # don't mess it up
# find longest common prefix
prefix = key[:0]
for i, c in enumerate(key):
if child._key[i] != c:
prefix = key[:i]
break
if prefix:
# case 3: child's key is abd, we spawn a new node with key "ab"
# to replace child ; child's key is now "d" and child's parent is
# the new created node.
# the new node will also be inserted as a child of this node
# with key "c"
node = _Node(prefix, child._parent)
self._nodescount += 1
child._parent._children.remove(child)
child._key = child._key[len(prefix):]
child._parent = node
node._children.add(child)
key = key[len(prefix):]
parent = node
break
# create the new node
node = _Node(key, parent)
self._nodescount += 1
if moved is not None:
# if we have moved an existing node, update it
moved._parent = node
node._children.add(moved)
self._add_to_index(node, value)
def _get_key(self, node):
"""
Rebuild key from a terminal node.
"""
key = node._key
while node._parent is not self:
node = node._parent
key = node._key + key
return key
def _add_to_index(self, node, value):
"""
Add a new node to the index.
Also record its value.
"""
node._index = len(self)
self._indexes.append(node)
self._values.append(value)
def key2index(self, key):
"""
key -> index
"""
if self._seems_valid_key(key):
node = self._get_node(key)
if node._index is not None:
return node._index
raise KeyError
raise TypeError("invalid key type")
def index2key(self, index):
"""
index or IndexedtrieKey -> key.
"""
if isinstance(index, IndexedtrieKey):
index = index.index
elif not isinstance(index, int):
raise TypeError("index must be an int")
if index < 0 or index > len(self._indexes):
raise IndexError
return self._get_key(self._indexes[index])

How to prevent key creation through d[key] = val

Suppose I have d = {'dogs': 3}. Using:
d['cats'] = 2
would create the key 'cats' and give it the value 2.
If I really intend to update a dict with a new key and value, I would use d.update(cats=2) because it feels more explicit.
Having automatic creation of a key feels error prone (especially in larger programs), e.g.:
# I decide to make a change to my dict.
d = {'puppies': 4, 'big_dogs': 2}
# Lots and lots of code.
# ....
def change_my_dogs_to_maximum_room_capacity():
# But I forgot to change this as well and there is no error to inform me.
# Instead a bug was created.
d['dogs'] = 1
Question:
Is there a way to disable the automatic creation of a key that doesn't exist through d[key] = value, and instead raise a KeyError?
Everything else should keep working though:
d = new_dict() # Works
d = new_dict(hi=1) # Works
d.update(c=5, x=2) # Works
d.setdefault('9', 'something') # Works
d['a_new_key'] = 1 # Raises KeyError

You could create a child of dict with a special __setitem__ method that refuses keys that didn't exist when it was initially created:
class StrictDict(dict):
def __setitem__(self, key, value):
if key not in self:
raise KeyError("{} is not a legal key of this StricDict".format(repr(key)))
dict.__setitem__(self, key, value)
x = StrictDict({'puppies': 4, 'big_dogs': 2})
x["puppies"] = 23 #this works
x["dogs"] = 42 #this raises an exception
It's not totally bulletproof (it will allow x.update({"cats": 99}) without complaint, for example), but it prevents the most likely case.

Inherit dict class and override __setitem__ to suits your needs.Try this
class mydict(dict):
def __init__(self, *args, **kwargs):
self.update(*args, **kwargs)
def __setitem__(self, key, value):
raise KeyError(key)
>>>a=mydict({'a':3})
>>>d
{'a': 3}
>>>d['a']
3
>>>d['b']=4
KeyError: 'b'

This will only allow new keys to be added with key=value using update:
class MyDict(dict):
def __init__(self, d):
dict.__init__(self)
self.instant = False
self.update(d)
def update(self, other=None, **kwargs):
if other is not None:
if isinstance(other, dict):
for k, v in other.items():
self[k] = v
else:
for k, v in other:
self[k] = v
else:
dict.update(self, kwargs)
self.instant = True
def __setitem__(self, key, value):
if self.instant and key not in self:
raise KeyError(key)
dict.__setitem__(self, key, value)
x = MyDict({1:2,2:3})
x[1] = 100 # works
x.update(cat=1) # works
x.update({2:200}) # works
x["bar"] = 3 # error
x.update({"foo":2}) # error
x.update([(5,2),(3,4)]) # error

How can I access a deeply nested dictionary using tuples?

I would like to expand on the autovivification example given in a previous answer from nosklo to allow dictionary access by tuple.
nosklo's solution looks like this:
class AutoVivification(dict):
"""Implementation of perl's autovivification feature."""
def __getitem__(self, item):
try:
return dict.__getitem__(self, item)
except KeyError:
value = self[item] = type(self)()
return value
Testing:
a = AutoVivification()
a[1][2][3] = 4
a[1][3][3] = 5
a[1][2]['test'] = 6
print a
Output:
{1: {2: {'test': 6, 3: 4}, 3: {3: 5}}}
I have a case where I want to set a node given some arbitrary tuple of subscripts. If I don't know how many layers deep the tuple will be, how can I design a way to set the appropriate node?
I'm thinking that perhaps I could use syntax like the following:
mytuple = (1,2,3)
a[mytuple] = 4
But I'm having trouble coming up with a working implementation.
Update
I have a fully working example based on #JCash's answer:
class NestedDict(dict):
"""
Nested dictionary of arbitrary depth with autovivification.
Allows data access via extended slice notation.
"""
def __getitem__(self, keys):
# Let's assume *keys* is a list or tuple.
if not isinstance(keys, basestring):
try:
node = self
for key in keys:
node = dict.__getitem__(node, key)
return node
except TypeError:
# *keys* is not a list or tuple.
pass
try:
return dict.__getitem__(self, keys)
except KeyError:
raise KeyError(keys)
def __setitem__(self, keys, value):
# Let's assume *keys* is a list or tuple.
if not isinstance(keys, basestring):
try:
node = self
for key in keys[:-1]:
try:
node = dict.__getitem__(node, key)
except KeyError:
node[key] = type(self)()
node = node[key]
return dict.__setitem__(node, keys[-1], value)
except TypeError:
# *keys* is not a list or tuple.
pass
dict.__setitem__(self, keys, value)
Which can achieve the same output as above using extended slice notation:
d = NestedDict()
d[1,2,3] = 4
d[1,3,3] = 5
d[1,2,'test'] = 6

This seems to work
def __setitem__(self, key, value):
if isinstance(key, tuple):
node = self
for i in key[:-1]:
try:
node = dict.__getitem__(node, i)
except KeyError:
node = node[i] = type(self)()
return dict.__setitem__(node, i, value)
return dict.__setitem__(self, key, value)

Handling IndexError exceptions with a list

I'm currently learning Python and I have this exercise where you have to handle exceptions. The goal of this one is to throw an exception when the value of the given key is not in the range of the list "self.data".
This is what I'm supposed to enter in my function to test it:
v = Vecteur(-9, -6, 2, 3, -2)
v[-1]
Now I'm supposed to get an IndexError
class Vecteur:
def __init__(self, *valeurs):
self.data = list(valeurs)
def __getitem__(self,key):
try:
erreur = self.data[key]
except IndexError:
print('indice invalide pour ce vecteur')
return self.data[key]
def __setitem__(self,key,item):
self.data[key] = item
Can one of you enlighten me on the subject?
Thanks in advance!

Your problem stems from the fact that you're catching the IndexError, and then printing, and letting execution fall through.
I'd do this instead:
class Vecteur:
def __init__(self, *valeurs):
self.data = list(valeurs)
def __getitem__(self,key):
try:
return self.data[key]
except IndexError:
raise IndexError('indice invalide pour ce vecteur')
def __setitem__(self,key,item):
self.data[key] = item
By the way, -1 is a valid index. Therefore, you might want to change your __getitem__:
def __getitem__(self, key):
if key < 0:
raise ValueError("Index has to be greater than 0")
# the rest of your __getitem__ here