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-# Trie implementation using nested dictionaries
-This library provides a [trie](https://en.wikipedia.org/wiki/Trie)
-implementation using nested dictionaries. Apart from the basic operations, a
-number of functions for *approximate matching* are implemented.
-
-
-## Installation
-Via [pypi](https://pypi.python.org/pypi/dict-trie):
-
-    pip install dict-trie
-
-From source:
-
-    git clone https://github.com/jfjlaros/dict-trie.git
-    cd dict-trie
-    pip install .
-
-
-## Usage
-The library provides the `Trie` class.
-
-### Basic operations
-Initialisation of the trie is done via the constructor by providing a list of
-words.
-```python
->>> from dict_trie import Trie
->>>
->>> trie = Trie(['abc', 'te', 'test'])
-```
-
-Alternatively, an empty trie can be made to which words can be added with the
-`add` function.
-```python
->>> trie = Trie()
->>> trie.add('abc')
->>> trie.add('te')
->>> trie.add('test')
-```
-
-Membership can be tested with the `in` statement.
-```python
->>> 'abc' in trie
-True
-```
-
-Test whether a prefix is present by using the `has_prefix` function.
-```python
->>> trie.has_prefix('ab')
-True
-```
-
-Remove a word from the trie with the `remove` function. This function returns
-`False` if the word was not in the trie.
-```python
->>> trie.remove('abc')
-True
->>> 'abc' in trie
-False
->>> trie.remove('abc')
-False
-```
-
-Iterate over all words in a trie.
-```python
->>> list(trie)
-['abc', 'te', 'test']
-```
-
-### Approximate matching
-A trie can be used to efficiently find a word that is similar to a query word.
-This is implemented via a number of functions that search for a word, allowing
-a given number of mismatches. These functions are divided in two families, one
-using the Hamming distance which only allows substitutions, the other using the
-Levenshtein distance which allows substitutions, insertions and deletions.
-
-To find a word that has at most Hamming distance 2 to the word 'abe', the
-`hamming` function is used.
-```python
->>> trie = Trie(['abc', 'aaa', 'ccc'])
->>> trie.hamming('abe', 2)
-'aaa'
-```
-
-To get all words that have at most Hamming distance 2 to the word 'abe', the
-`all_hamming` function is used. This function returns a generator.
-```python
->>> list(trie.all_hamming('abe', 2))
-['aaa', 'abc']
-```
-
-In order to find a word that is closest to the query word, the `best_hamming`
-function is used. In this case a word with distance 1 is returned.
-```python
->>> trie.best_hamming('abe', 2)
-'abc'
-```
-
-The functions `levenshtein`, `all_levenshtein` and `best_levenshtein` are used
-in a similar way.
-
-### Other functionalities
-A trie can be populated with all words of a fixed length over an alphabet by
-using the `fill` function.
-```python
->>> trie = Trie()
->>> trie.fill(('a', 'b'), 2)
->>> list(trie)
-['aa', 'ab', 'ba', 'bb']
-```
-
-The trie data structure can be accessed via the `root` member variable.
-```python
->>> trie.root
-{'a': {'a': {'': 1}, 'b': {'': 1}}, 'b': {'a': {'': 1}, 'b': {'': 1}}}
->>> trie.root.keys()
-['a', 'b']
-```
-
-The distance functions `all_hamming` and `all_levenshtein` also have
-counterparts that give the developer more information by returning a list of
-tuples containing not only the matched word, but also its distance to the query
-string and a [CIGAR](https://samtools.github.io/hts-specs/SAMv1.pdf)-like
-string.
-
-The following encoding is used in the CIGAR-like string:
-
-    character | meaning
-          --: | :--
-            = | match
-            X | mismatch
-            I | insertion
-            D | deletion
-
-In the following example, we search for all words with Hamming distance 1 to
-the word 'acc'. In the results we see a match with the word 'abc' having
-distance 1 and a mismatch at position 2.
-```python
->>> trie = Trie(['abc'])
->>> list(trie.all_hamming_('acc', 1))
-[('abc', 1, '=X=')]
-```
-
-Similarly, we can search for all words having Levenshtein distance 2 to the
-word 'acb'. The word 'abc' matches three times, once by deleting the 'b' on
-position 2 and inserting a 'b' after position 3, once by inserting a 'c' after
-position 1 and deleting the last character and once by introducing two
-mismatches.
-```python
->>> list(trie.all_levenshtein_('acb', 2))
-[('abc', 2, '=D=I'), ('abc', 2, '=XX'), ('abc', 2, '=I=D')]
-```