Skip to content
Projects
Groups
Snippets
Help
Loading...
Help
Support
Submit feedback
Contribute to GitLab
Sign in
Toggle navigation
D
dicttrie
Project overview
Project overview
Details
Activity
Releases
Cycle Analytics
Repository
Repository
Files
Commits
Branches
Tags
Contributors
Graph
Compare
Charts
Issues
0
Issues
0
List
Boards
Labels
Milestones
Merge Requests
0
Merge Requests
0
CI / CD
CI / CD
Pipelines
Jobs
Schedules
Charts
Wiki
Wiki
Snippets
Snippets
Members
Members
Collapse sidebar
Close sidebar
Activity
Graph
Charts
Create a new issue
Jobs
Commits
Issue Boards
Open sidebar
Jeroen F.J. Laros
dicttrie
Commits
8258d45c
Commit
8258d45c
authored
Apr 27, 2017
by
Jeroen F.J. Laros
Browse files
Options
Browse Files
Download
Email Patches
Plain Diff
Added iterable trie searching.
parent
fd053c81
Changes
1
Hide whitespace changes
Inline
Sidebyside
Showing
1 changed file
with
36 additions
and
27 deletions
+36
27
dict_trie/dict_trie.py
dict_trie/dict_trie.py
+36
27
No files found.
dict_trie/dict_trie.py
View file @
8258d45c
def
_hamming
(
path
,
node
,
word
,
distance
):
"""Find the first path in the trie that is within a certain hamming
distance of {word}. Note that this does not necessarily the one with the
smallest distance.
"""Find all paths in the trie that are within a certain hamming distance of
{word}.
:arg str path: Path taken so far to reach the current node.
:arg dict node: Current node.
:arg str word: Query word.
:arg int distance: Amount of errors we can still make.
:returns
str: A word in the trie that has
Hamming distance of at most
:returns
iter: All word in the trie that have
Hamming distance of at most
{distance} to {word}.
"""
if
distance
<
0
:
return
''
return
if
not
word
:
return
path
if
''
in
node
else
''
if
''
in
node
:
yield
path
return
car
,
cdr
=
word
[
0
],
word
[
1
:]
for
char
in
node
:
result
=
_hamming
(
path
+
char
,
node
[
char
],
cdr
,
distance

int
(
char
!=
car
))
if
result
:
return
result
return
''
for
result
in
_hamming
(
path
+
char
,
node
[
char
],
cdr
,
distance

int
(
char
!=
car
)):
yield
result
def
_levenshtein
(
path
,
node
,
word
,
distance
):
"""
"""
if
distance
<
0
:
return
''
return
if
not
word
:
return
path
if
''
in
node
else
''
if
''
in
node
:
yield
path
return
car
,
cdr
=
word
[
0
],
word
[
1
:]
# Deletion.
result
=
_levenshtein
(
path
,
node
,
cdr
,
distance

1
)
if
result
:
return
result
for
result
in
_levenshtein
(
path
,
node
,
cdr
,
distance

1
):
yield
result
for
char
in
node
:
# Substitution and insertion.
result
=
(
_levenshtein
(
path
+
char
,
node
[
char
],
cdr
,
distance

int
(
char
!=
car
))
or
_levenshtein
(
path
+
char
,
node
[
char
],
word
,
distance

1
))
if
result
:
return
result
return
''
for
result
in
_levenshtein
(
path
+
char
,
node
[
char
],
cdr
,
distance

int
(
char
!=
car
)):
yield
result
for
result
in
_levenshtein
(
path
+
char
,
node
[
char
],
word
,
distance

1
):
yield
result
class
Trie
(
object
):
...
...
@@ 107,9 +104,15 @@ class Trie(object):
def
has_prefix
(
self
,
word
):
return
self
.
_find
(
word
)
!=
{}
def
hamming
(
self
,
word
,
distance
):
def
all_
hamming
(
self
,
word
,
distance
):
return
_hamming
(
''
,
self
.
root
,
word
,
distance
)
def
hamming
(
self
,
word
,
distance
):
try
:
return
self
.
all_hamming
(
word
,
distance
)
.
next
()
except
StopIteration
:
return
''
def
best_hamming
(
self
,
word
,
distance
):
"""Find the best match with {word} in the trie.
...
...
@@ 128,9 +131,15 @@ class Trie(object):
return
''
def
levenshtein
(
self
,
word
,
distance
):
def
all_
levenshtein
(
self
,
word
,
distance
):
return
_levenshtein
(
''
,
self
.
root
,
word
,
distance
)
def
levenshtein
(
self
,
word
,
distance
):
try
:
return
self
.
all_levenshtein
(
word
,
distance
)
.
next
()
except
StopIteration
:
return
''
def
best_levenshtein
(
self
,
word
,
distance
):
"""Find the best match with {word} in the trie.
...
...
Write
Preview
Markdown
is supported
0%
Try again
or
attach a new file
Attach a file
Cancel
You are about to add
0
people
to the discussion. Proceed with caution.
Finish editing this message first!
Cancel
Please
register
or
sign in
to comment