├── .gitignore
├── .readthedocs.yaml
├── COPYING
├── COPYING.LESSER
├── MANIFEST.in
├── README
├── README.rst
├── docs
├── conf.py
├── index.rst
├── intro.rst
├── ngram.rst
├── releasenotes.rst
└── tutorial.rst
├── ngram.py
├── pyproject.toml
├── scripts
└── csvjoin.py
├── setup.cfg
├── setup.py
├── tests
├── __init__.py
├── test_csvjoin.py
└── test_ngram.py
└── tox.ini
/.gitignore:
--------------------------------------------------------------------------------
1 | __pycache__
2 | .cache
3 | *.egg-info
4 | *.pyc
5 | *.wpu
6 | /.tox
7 | /.vscode
8 | /build
9 | /dist
10 | /docs/build
11 |
--------------------------------------------------------------------------------
/.readthedocs.yaml:
--------------------------------------------------------------------------------
1 | # .readthedocs.yaml
2 | # Read the Docs configuration file
3 | # See https://docs.readthedocs.io/en/stable/config-file/v2.html for details
4 |
5 | # Required
6 | version: 2
7 |
8 | # Build documentation in the docs/ directory with Sphinx
9 | sphinx:
10 | configuration: docs/conf.py
11 |
--------------------------------------------------------------------------------
/COPYING:
--------------------------------------------------------------------------------
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/MANIFEST.in:
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1 | include COPYING
2 | include COPYING.LESSER
3 | include tox.ini
4 | graft docs
5 | prune docs/build
6 | graft tests
7 | global-exclude *.pyc
8 |
--------------------------------------------------------------------------------
/README:
--------------------------------------------------------------------------------
1 | The NGram class extends the Python 'set' class with efficient
2 | fuzzy search for members by means of an N-gram similarity measure.
3 | It also has static methods to compare a pair of strings.
4 |
5 | The N-grams are character based not word-based, and the class does not
6 | implement a language model, merely searching for members by string similarity.
7 |
8 | See the `documentation`_, which includes a tutorial and release notes.
9 |
10 | Use the `GitHub issue tracker`_ to report issues.
11 |
12 | Installation
13 | ============
14 |
15 | To install python-ngram from `PyPI`_::
16 |
17 | pip install ngram
18 |
19 | How does it work?
20 | =================
21 |
22 | The set stores arbitrary items, but for non-string items a `key` function
23 | (such as `str`) must be specified to provide a string represenation. The key
24 | function can also be used to normalise string items (e.g. lower-casing) prior
25 | to N-gram indexing.
26 |
27 | To index a string it pads the string with a specified dummy character, then
28 | splits it into overlapping substrings of N (default N=3) characters in length
29 | and associates each N-gram to the items that use it.
30 |
31 | To find items similar to a query string, it splits the query into N-grams,
32 | collects all items sharing at least one N-gram with the query,
33 | and ranks the items by score based on the ratio of shared to unshared
34 | N-grams between strings.
35 |
36 | History
37 | =======
38 |
39 | In 2007, Michel Albert (exhuma) wrote the python-ngram module based on Perl's
40 | `String::Trigram`_ module by Tarek Ahmed, and committed the code for 2.0.0b2 to
41 | a now-disused `Sourceforge`_ subversion repo.
42 |
43 | Since late 2008, Graham Poulter has maintained python-ngram, initially refactoring
44 | it to build on the `set` class, and also adding features, documentation, tests,
45 | performance improvements and Python 3 support.
46 |
47 | Development
48 | ===========
49 |
50 | Development takes place on `Github`_. On checking out the repo run `tox` to build
51 | the Sphinx documentation and run tests. Run `pip install -e .` to install the module
52 | in editable mode, inside a virtualenv.
53 |
54 | .. _documentation: https://python-ngram.readthedocs.io/en/latest/
55 | .. _GitHub: http://github.com/gpoulter/python-ngram
56 | .. _GitHub issue tracker: https://github.com/gpoulter/python-ngram/issues
57 | .. _PyPI: http://pypi.python.org/pypi/ngram
58 | .. _String::Trigram: http://search.cpan.org/dist/String-Trigram/
59 | .. _Sourceforge: https://sourceforge.net/projects/python-ngram/
60 |
--------------------------------------------------------------------------------
/README.rst:
--------------------------------------------------------------------------------
1 | README
--------------------------------------------------------------------------------
/docs/conf.py:
--------------------------------------------------------------------------------
1 | # NGram documentation build configuration file.
2 |
3 | # Add any Sphinx extension module names here, as strings. They can be extensions
4 | # coming with Sphinx (named 'sphinx.ext.*') or your custom ones.
5 | extensions = ['sphinx.ext.autodoc', 'sphinx.ext.doctest']
6 |
7 | # The suffix of source filenames.
8 | source_suffix = '.rst'
9 |
10 | # The human-readable project name
11 | project = u'Python NGram'
12 |
13 | # The short X.Y version.
14 | version = '4.0'
15 |
16 | # The full version, including alpha/beta/rc tags.
17 | release = '4.0.3'
18 |
19 | # Language the docs are written in.
20 | language = 'en'
21 |
22 | # Copyright byline.
23 | copyright = 'Graham Poulter, Michel Albert 2008-2021'
24 |
25 | # List of directories, relative to source directory, that shouldn't be searched
26 | # for source files.
27 | exclude_trees = ['build']
28 |
29 | # The name of the Pygments (syntax highlighting) style to use.
30 | pygments_style = 'sphinx'
31 |
32 | # Name (excluding extension) of root document.
33 | root_doc = 'index'
--------------------------------------------------------------------------------
/docs/index.rst:
--------------------------------------------------------------------------------
1 | Python NGram documentation
2 | ++++++++++++++++++++++++++
3 |
4 | .. toctree::
5 | :maxdepth: 3
6 |
7 | intro
8 | tutorial
9 | ngram
10 | releasenotes
11 |
12 |
--------------------------------------------------------------------------------
/docs/intro.rst:
--------------------------------------------------------------------------------
1 | ==============
2 | Introduction
3 | ==============
4 |
5 | .. include:: ../README
6 |
7 | License
8 | =======
9 |
10 | This program is free software: you can redistribute it and/or modify
11 | it under the terms of the GNU Lesser General Public License as published
12 | by the Free Software Foundation, either version 3 of the License, or
13 | (at your option) any later version.
14 |
15 | This program is distributed in the hope that it will be useful,
16 | but WITHOUT ANY WARRANTY; without even the implied warranty of
17 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
18 | GNU General Public License for more details.
19 |
20 | You should have received a copy of the GNU General Public License
21 | along with this program. If not, see
22 |
23 | * :download:`Text of GPLv3 <../COPYING>`
24 | * :download:`Text of LGPLv3 <../COPYING.LESSER>`
25 |
26 | Indices and tables
27 | ==================
28 |
29 | * :ref:`genindex`
30 | * :ref:`modindex`
31 | * :ref:`search`
32 |
33 |
--------------------------------------------------------------------------------
/docs/ngram.rst:
--------------------------------------------------------------------------------
1 | ============================
2 | NGram Module Documentation
3 | ============================
4 |
5 | .. automodule:: ngram
6 | :members:
7 |
8 |
--------------------------------------------------------------------------------
/docs/releasenotes.rst:
--------------------------------------------------------------------------------
1 | Release Notes
2 | =============
3 |
4 | Version 4.0.3
5 | -------------
6 | Released 2021-09-15
7 |
8 | * Fixed the setup.cfg
9 |
10 | Version 4.0.1
11 | -------------
12 | Released 2021-09-10
13 |
14 | * Switched documentation host to ReadTheDocs because sphinx_upload stopped working.
15 |
16 | Version 4.0.0
17 | -------------
18 | Released 2021-09-10
19 |
20 | * Removed Python 2.7 support since 2to3 support is removed from recent setuptools.
21 |
22 | Version 3.3.2
23 | -------------
24 | Released 2017-06-20
25 |
26 | * Fixed bug in remove and pop attempting to delete an ngram multiple times.
27 | * Add DeprecationWarning for use of iconv param, ngrams method, ngrams_pad method.
28 | * Fixed csvjoin_test to run on Windows.
29 | * Fixed doctests to support dictionary random iteration order.
30 |
31 | Version 3.3.0
32 | -------------
33 | Released 2012-06-29
34 |
35 | NEW FEATURES
36 | * Correct support for remaining set methods: `pop`, `clear`, `union`, `intersection`, `difference`, `symmetric_difference`
37 | * Can provide alternate `items` to the `copy` method
38 |
39 | IMPROVEMENTS
40 | * Update license from LGPL to LGPL version 3
41 | * Revised readme to work with GitHub, PyPI and generated docs.
42 | * Tox to run all doctests, pass under 2.7 and 3.2
43 |
44 | BUG FIXES
45 | * Fix unused threshold param in `searchitem` method
46 | * Fix intersection_update to accept multiple other iterables
47 |
48 | Version 3.2.1
49 | -------------
50 | Released 2012-06-28
51 |
52 | * Fix bug in symmetric_difference_update method
53 | * Update release notes / changelog
54 | * Update tutorial
55 |
56 | Version 3.2.0
57 | -------------
58 | Released 2012-06-25
59 |
60 | NEW FEATURES
61 | * "csvjoin" script performs SQL-like join between CSV tables based on string similarity.
62 | * NGram instances can now be pickled/unpickled (added __reduce__)
63 | * Add searchitem method to search by item (search method takes a string)
64 | * Add find and finditem methods to return 1 result instead of a list.
65 |
66 | BREAKING CHANGES
67 | * iconv parameter is now the "key" parameter (matches the sorted() builtin)
68 | * qconv parameter no longer exists: use searchitem method to query by item
69 | * the `ngrams_pad` method is deprecated for new `split` and `splititem` methods
70 | * the `ngrams` method is deprecated (equivalent `_split` is for internal use)
71 |
72 | OTHER IMPROVEMENTS
73 | * Converted Mercurial repo to Git
74 | * Corrected indentation from 3 to 4 spaces
75 | * Added tox to run tests on Python 2.7 and 3.2
76 |
77 | Version 3.1.0
78 | -------------
79 | Released 2009-12-07
80 |
81 | NEW FEATURES
82 | * Python 3 support via 2to3
83 | * Sphinx documentation generation
84 | * Tutorial documentation
85 |
86 | BREAKING CHANGES
87 | * str_item and str_query params are now iconv and qconv
88 |
89 | BUG FIXES
90 | * Integer division bug (e.g. arises when warp is 2 not 2.0)
91 |
92 | MINOR CHANGES
93 | * Setuptools replaced by Distribute (for Python 3)
94 | * Docstrings now reStructuredText for Sphinx
95 |
96 | Version 3.0.0
97 | -------------
98 | Released 2009-07-03.
99 |
100 | This was a major refactoring without back-compatibility.
101 |
102 | NEW FEATURES
103 | * Accepts any hashable item - no longer limited to strings.
104 | * Re-written as subclass of set, gaining all set operations.
105 | * Docstrings added. Using Epydoc API doc generator.
106 |
107 | IMPROVEMENTS
108 | * Eliminated innermost level of dictionaries, reducing memory usage.
109 | * Revised to use Python 2.6 idioms. Losing Python 2.2 compatibility.
110 | * Renamed things to follow PEP 8
111 | * Refactored the NGram class (new method decomposition)
112 |
113 |
114 | Version 2.0.0b2
115 | ---------------
116 | Released 2007-10-23.
117 |
118 | This was the code committed to Subversion by Exhuma.
119 |
120 |
121 |
--------------------------------------------------------------------------------
/docs/tutorial.rst:
--------------------------------------------------------------------------------
1 | ==========
2 | Tutorial
3 | ==========
4 |
5 | Comparing and searching strings
6 | ===============================
7 |
8 | Compare two strings using :meth:`~ngram.NGram.compare`:
9 |
10 | .. doctest::
11 |
12 | >>> import ngram
13 | >>> ngram.NGram.compare('Ham','Spam',N=1)
14 | 0.4
15 |
16 | The :class:`~ngram.NGram` class extends the builtin `set` class with the
17 | ability to search for members by n-gram similarity.
18 |
19 | Use :meth:`~ngram.NGram.search` to return similar items in a set,
20 | and :meth:`~ngram.NGram.find` to only return the most similar item:
21 |
22 | .. doctest::
23 |
24 | >>> G = ngram.NGram(['joe','joseph','jon','john','sally'])
25 | >>> G.search('jon')
26 | [('jon', 1.0), ('john', 0.375), ('joe', 0.25), ('joseph', 0.18181818181818182)]
27 | >>> G.search('jon', threshold=0.3)
28 | [('jon', 1.0), ('john', 0.375)]
29 | >>> G.find('jose')
30 | 'joseph'
31 |
32 | Transforming items
33 | ==================
34 |
35 | By default no transformation is done, so items must be strings. By passing a `key` function,
36 | similar to the `key` parameter of the `sorted` builtin, arbitrary items can be indexed.
37 | For non-string items, generally pass `str` or `unicode` as the key function.
38 |
39 | Below, we define a key function to index the lower-case version of a string, and use
40 | the key, pad and ngrams methods to examine the internal representations:
41 |
42 | .. doctest::
43 |
44 | >>> def lower(s):
45 | ... return s.lower()
46 | >>> G = ngram.NGram(key=lower)
47 | >>> G.key('AbC')
48 | 'abc'
49 | >>> G.pad('abc')
50 | '$$abc$$'
51 | >>> list(G.split('abc'))
52 | ['$$a', '$ab', 'abc', 'bc$', 'c$$']
53 |
54 | Searching with a lowercase query returns results, but there is no match if the
55 | query contains capitals:
56 |
57 | .. doctest::
58 |
59 | >>> G.add('AbC')
60 | >>> G.search('abcd')
61 | [('AbC', 0.375)]
62 | >>> G.find('abcd')
63 | 'AbC'
64 | >>> G.search('AbC') == []
65 | True
66 | >>> G.find('AbC') == None
67 | True
68 |
69 | We can either lowercase the query, or use the "searchitem" or "finditem"
70 | methods that apply the key function to the query before searching:
71 |
72 | .. doctest::
73 |
74 | >>> G.search('AbCD'.lower())
75 | [('AbC', 0.375)]
76 | >>> G.find(lower('AbCD'))
77 | 'AbC'
78 | >>> G.searchitem('AbCD')
79 | [('AbC', 0.375)]
80 | >>> G.finditem('AbCD')
81 | 'AbC'
82 |
83 | So long as the function can be found in `__main__` or imported, NGram instances can be pickled:
84 |
85 | .. doctest::
86 |
87 | >>> import pickle
88 | >>> pickle.dumps(G) #doctest: +IGNORE_EXCEPTION_DETAIL
89 | Traceback (most recent call last):
90 | ...
91 | PicklingError: Can't pickle : it's not found as __main__.lower
92 | >>> import string
93 | >>> H1 = ngram.NGram(['ab cd'], key=string.capwords)
94 | >>> text = pickle.dumps(H1)
95 | >>> H2 = pickle.loads(text)
96 | >>> list(H1)
97 | ['ab cd']
98 | >>> list(H2)
99 | ['ab cd']
100 |
101 | The key function can perform complex transformations:
102 |
103 | .. doctest::
104 |
105 | >>> G = ngram.NGram(key=lambda x:(" ".join(x)).lower())
106 | >>> G.add(("Joe","Bloggs"))
107 | >>> G.search("jeo blogger")
108 | [(('Joe', 'Bloggs'), 0.25)]
109 | >>> G.searchitem(("Jeo", "Blogger"))
110 | [(('Joe', 'Bloggs'), 0.25)]
111 |
112 |
113 | Set Operations
114 | ==============
115 |
116 | The `update`, `discard`, `difference_update`, `intersection_update` and `symmetric_difference` update
117 | methods from the builtin `set` class have been overridden to maintain the integrity of the
118 | NGram index when performing them. These take any iterable as argument, including another
119 | NGram instance.
120 |
121 | .. doctest::
122 |
123 | >>> G = ngram.NGram(['joe','joseph','jon','john','sally'])
124 | >>> G.update(['jonathan'])
125 | >>> sorted(list(G))
126 | ['joe', 'john', 'jon', 'jonathan', 'joseph', 'sally']
127 | >>> G.discard('sally')
128 | >>> sorted(list(G))
129 | ['joe', 'john', 'jon', 'jonathan', 'joseph']
130 | >>> G.difference_update(ngram.NGram(['joe']))
131 | >>> sorted(list(G))
132 | ['john', 'jon', 'jonathan', 'joseph']
133 | >>> G.intersection_update(['james', 'joseph', 'joe', 'jon'])
134 | >>> sorted(list(G))
135 | ['jon', 'joseph']
136 | >>> G.symmetric_difference_update(ngram.NGram(['jimmy', 'jon']))
137 | >>> sorted(list(G))
138 | ['jimmy', 'joseph']
139 |
140 |
141 | Multi-byte characters
142 | =====================
143 |
144 | Use Python 3 strings (unicode) where possible.
145 |
146 | It is possible to use NGram with bytes, but only with single-byte
147 | encodings, and you must also use a byte string as the padding
148 | character:
149 |
150 | .. doctest::
151 |
152 | >>> index = ngram.NGram(N=3, pad_char=b'$', pad_len=2)
153 | >>> list(index.split(b'abc'))
154 | [b'$$a', b'$ab', b'abc', b'bc$', b'c$$']
155 |
156 | NGram will not work correctly with UTF-8 encoded bytes, because
157 | characters like é (code point 0xE9) will encode to multiple bytes as
158 | ``b'\xc3\xa9'`` and be treated as 2 separate characters.
159 |
160 | A unicode string ``'\xe9'`` will be treated correctly as a single
161 | character.
--------------------------------------------------------------------------------
/ngram.py:
--------------------------------------------------------------------------------
1 | """
2 | :mod:`ngram` -- A set class that supports lookup by N-gram string similarity
3 | ============================================================================
4 | """
5 |
6 | # This program is free software: you can redistribute it and/or modify
7 | # it under the terms of the GNU Lesser General Public License as published
8 | # by the Free Software Foundation, either version 3 of the License, or
9 | # (at your option) any later version.
10 | #
11 | # This program is distributed in the hope that it will be useful,
12 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
13 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
14 | # GNU General Public License for more details.
15 | #
16 | # You should have received a copy of the GNU Lesser General Public License
17 | # along with this program. If not, see
18 |
19 | import warnings
20 |
21 | class NGram(set):
22 | """A set that supports searching for members by N-gram string similarity.
23 |
24 | In Python 2, items should be `unicode` string or a plain ASCII `str`
25 | (bytestring) - do not use UTF-8 or other multi-byte encodings, because
26 | multi-byte characters will be split up.
27 |
28 | :type threshold: float in 0.0 ... 1.0
29 |
30 | :param threshold: minimum similarity for a string to be considered a match.
31 |
32 | :type warp: float in 1.0 ... 3.0
33 |
34 | :param warp: use warp greater than 1.0 to increase the similarity of \
35 | shorter string pairs.
36 |
37 | :type items: [item, ...]
38 |
39 | :param items: iteration of items to index for N-gram search.
40 |
41 | :type N: int >= 2
42 |
43 | :param N: number of characters per n-gram.
44 |
45 | :type pad_len: int in 0 ... N-1
46 |
47 | :param pad_len: how many characters padding to add (defaults to N-1).
48 |
49 | :type pad_char: str or unicode
50 |
51 | :param pad_char: character to use for padding. Default is '$', but \
52 | consider using the\\ non-breaking space character, ``u'\\xa0'`` \
53 | (``u"\\u00A0"``).
54 |
55 | :type key: function(item) -> str/unicode
56 |
57 | :param key: Function to convert items into string, default is no \
58 | conversion. Recommended to use `str` or `unicode` for non-string items. \
59 | Using anonymous function prevents NGram class from being pickled.
60 |
61 | Instance variables:
62 |
63 | :ivar _grams: For each n-gram, the items containing it and the number of \
64 | times\\ the n-gram occurs in the item as ``{str:{item:int, ...}, ...}``.
65 |
66 | :ivar length: maps items to length of the padded string representations \
67 | as ``{item:int, ...}``.
68 | """
69 |
70 | def __init__(self, items=None, threshold=0.0, warp=1.0, key=None,
71 | N=3, pad_len=None, pad_char='$', **kwargs):
72 | super(NGram, self).__init__()
73 | if not (0 <= threshold <= 1):
74 | raise ValueError("threshold out of range 0.0 to 1.0: "
75 | + repr(threshold))
76 | if not (1.0 <= warp <= 3.0):
77 | raise ValueError(
78 | "warp out of range 1.0 to 3.0: " + repr(warp))
79 | if not N >= 1:
80 | raise ValueError("N out of range (should be N >= 1): " + repr(N))
81 | if pad_len is None:
82 | pad_len = N - 1
83 | if not (0 <= pad_len < N):
84 | raise ValueError("pad_len out of range: " + repr(pad_len))
85 | if not len(pad_char) == 1:
86 | raise ValueError(
87 | "pad_char is not single character: " + repr(pad_char))
88 | if key is not None and not callable(key):
89 | raise ValueError("key is not a function: " + repr(key))
90 | self.threshold = threshold
91 | self.warp = warp
92 | self.N = N
93 | self._pad_len = pad_len
94 | self._pad_char = pad_char
95 | self._padding = pad_char * pad_len # derive a padding string
96 | # compatibility shim for 3.1 iconv parameter
97 | if 'iconv' in kwargs:
98 | self._key = kwargs.pop('iconv')
99 | warnings.warn('"iconv" parameter deprecated, use "key" instead.', DeprecationWarning)
100 | # no longer support 3.1 qconv parameter
101 | if 'qconv' in kwargs:
102 | raise ValueError('qconv query conversion parameter unsupported. '
103 | 'Please process query to a string before calling .search')
104 | self._key = key
105 | self._grams = {}
106 | self.length = {}
107 | if items:
108 | self.update(items)
109 |
110 | def __reduce__(self):
111 | """Return state information for pickling, no references to this
112 | instance. The key function must be None, a builtin function, or
113 | a named module-level function.
114 |
115 | >>> from ngram import NGram
116 | >>> n = NGram([0xDEAD, 0xBEEF], key=hex)
117 | >>> import pickle
118 | >>> p = pickle.dumps(n)
119 | >>> m = pickle.loads(p)
120 | >>> sorted(list(m))
121 | [48879, 57005]
122 | """
123 | return NGram, (list(self), self.threshold, self.warp, self._key,
124 | self.N, self._pad_len, self._pad_char)
125 |
126 | def copy(self, items=None):
127 | """Return a new NGram object with the same settings, and
128 | referencing the same items. Copy is shallow in that
129 | each item is not recursively copied. Optionally specify
130 | alternate items to populate the copy.
131 |
132 | >>> from ngram import NGram
133 | >>> from copy import deepcopy
134 | >>> n = NGram(['eggs', 'spam'])
135 | >>> m = n.copy()
136 | >>> m.add('ham')
137 | >>> sorted(list(n))
138 | ['eggs', 'spam']
139 | >>> sorted(list(m))
140 | ['eggs', 'ham', 'spam']
141 | >>> p = n.copy(['foo', 'bar'])
142 | >>> sorted(list(p))
143 | ['bar', 'foo']
144 | """
145 | return NGram(items if items is not None else self,
146 | self.threshold, self.warp, self._key,
147 | self.N, self._pad_len, self._pad_char)
148 |
149 | def key(self, item):
150 | """Get the key string for the item.
151 |
152 | >>> from ngram import NGram
153 | >>> n = NGram(key=lambda x:x[1])
154 | >>> n.key((3,"ham"))
155 | 'ham'
156 | """
157 | return self._key(item) if self._key else item
158 |
159 | def pad(self, string):
160 | """Pad a string in preparation for splitting into ngrams.
161 |
162 | >>> from ngram import NGram
163 | >>> n = NGram()
164 | >>> n.pad('ham')
165 | '$$ham$$'
166 | """
167 | return self._padding + string + self._padding
168 |
169 | def _split(self, string):
170 | """Iterates over the ngrams of a string (no padding).
171 |
172 | >>> from ngram import NGram
173 | >>> n = NGram()
174 | >>> list(n._split("hamegg"))
175 | ['ham', 'ame', 'meg', 'egg']
176 | """
177 | for i in range(len(string) - self.N + 1):
178 | yield string[i:i + self.N]
179 |
180 | def split(self, string):
181 | """Pads a string and iterates over its ngrams.
182 |
183 | >>> from ngram import NGram
184 | >>> n = NGram()
185 | >>> list(n.split("ham"))
186 | ['$$h', '$ha', 'ham', 'am$', 'm$$']
187 | """
188 | return self._split(self.pad(string))
189 |
190 | def ngrams(self, string):
191 | """Alias for 3.1 compatibility, please set pad_len=0 and use split."""
192 | warnings.warn('Method ngram deprecated, use method split with pad_len=0 instead.', DeprecationWarning)
193 | return self._split(string)
194 |
195 | def ngrams_pad(self, string):
196 | """Alias for 3.1 compatibility, please use split instead."""
197 | warnings.warn('Method ngrams_pad deprecated, use method split instead.', DeprecationWarning)
198 | return self.split(string)
199 |
200 | def splititem(self, item):
201 | """Pads the string key of an item and iterates over its ngrams.
202 |
203 | >>> from ngram import NGram
204 | >>> n = NGram(key=lambda x:x[1])
205 | >>> item = (3,"ham")
206 | >>> list(n.splititem(item))
207 | ['$$h', '$ha', 'ham', 'am$', 'm$$']
208 | """
209 | return self.split(self.key(item))
210 |
211 | def add(self, item):
212 | """Add an item to the N-gram index (if it has not already been added).
213 |
214 | >>> from ngram import NGram
215 | >>> n = NGram()
216 | >>> n.add("ham")
217 | >>> list(n)
218 | ['ham']
219 | >>> n.add("spam")
220 | >>> sorted(list(n))
221 | ['ham', 'spam']
222 | """
223 | if item not in self:
224 | # Add the item to the base set
225 | super(NGram, self).add(item)
226 | # Record length of padded string
227 | padded_item = self.pad(self.key(item))
228 | self.length[item] = len(padded_item)
229 | for ngram in self._split(padded_item):
230 | # Add a new n-gram and string to index if necessary
231 | self._grams.setdefault(ngram, {}).setdefault(item, 0)
232 | # Increment number of times the n-gram appears in the string
233 | self._grams[ngram][item] += 1
234 |
235 | def remove(self, item):
236 | """Remove an item from the set. Inverts the add operation.
237 |
238 | >>> from ngram import NGram
239 | >>> n = NGram(['spam', 'eggs'])
240 | >>> n.remove('spam')
241 | >>> list(n)
242 | ['eggs']
243 | """
244 | if item in self:
245 | super(NGram, self).remove(item)
246 | del self.length[item]
247 | for ngram in set(self.splititem(item)):
248 | del self._grams[ngram][item]
249 |
250 | def pop(self):
251 | """Remove and return an arbitrary set element.
252 | Raises KeyError if the set is empty.
253 |
254 | >>> from ngram import NGram
255 | >>> n = NGram(['spam', 'eggs'])
256 | >>> x = n.pop()
257 | >>> len(n)
258 | 1
259 | """
260 | item = super(NGram, self).pop()
261 | del self.length[item]
262 | for ngram in set(self.splititem(item)):
263 | del self._grams[ngram][item]
264 | return item
265 |
266 | def items_sharing_ngrams(self, query):
267 | """Retrieve the subset of items that share n-grams the query string.
268 |
269 | :param query: look up items that share N-grams with this string.
270 | :return: mapping from matched string to the number of shared N-grams.
271 |
272 | >>> from ngram import NGram
273 | >>> n = NGram(["ham","spam","eggs"])
274 | >>> sorted(n.items_sharing_ngrams("mam").items())
275 | [('ham', 2), ('spam', 2)]
276 | """
277 | # From matched string to number of N-grams shared with query string
278 | shared = {}
279 | # Dictionary mapping n-gram to string to number of occurrences of that
280 | # ngram in the string that remain to be matched.
281 | remaining = {}
282 | for ngram in self.split(query):
283 | try:
284 | for match, count in self._grams[ngram].items():
285 | remaining.setdefault(ngram, {}).setdefault(match, count)
286 | # match as many occurrences as exist in matched string
287 | if remaining[ngram][match] > 0:
288 | remaining[ngram][match] -= 1
289 | shared.setdefault(match, 0)
290 | shared[match] += 1
291 | except KeyError:
292 | pass
293 | return shared
294 |
295 | def searchitem(self, item, threshold=None):
296 | """Search the index for items whose key exceeds the threshold
297 | similarity to the key of the given item.
298 |
299 | :return: list of pairs of (item, similarity) by decreasing similarity.
300 |
301 | >>> from ngram import NGram
302 | >>> n = NGram([(0, "SPAM"), (1, "SPAN"), (2, "EG"),
303 | ... (3, "SPANN")], key=lambda x:x[1])
304 | >>> sorted(n.searchitem((2, "SPA"), 0.35))
305 | [((0, 'SPAM'), 0.375), ((1, 'SPAN'), 0.375)]
306 | """
307 | return self.search(self.key(item), threshold)
308 |
309 | def search(self, query, threshold=None):
310 | """Search the index for items whose key exceeds threshold
311 | similarity to the query string.
312 |
313 | :param query: returned items will have at least `threshold` \
314 | similarity to the query string.
315 |
316 | :return: list of pairs of (item, similarity) by decreasing similarity.
317 |
318 | >>> from ngram import NGram
319 | >>> n = NGram([(0, "SPAM"), (1, "SPAN"), (2, "EG")], key=lambda x:x[1])
320 | >>> sorted(n.search("SPA"))
321 | [((0, 'SPAM'), 0.375), ((1, 'SPAN'), 0.375)]
322 | >>> n.search("M")
323 | [((0, 'SPAM'), 0.125)]
324 | >>> n.search("EG")
325 | [((2, 'EG'), 1.0)]
326 | """
327 | threshold = threshold if threshold is not None else self.threshold
328 | results = []
329 | # Identify possible results
330 | for match, samegrams in self.items_sharing_ngrams(query).items():
331 | allgrams = (len(self.pad(query))
332 | + self.length[match] - (2 * self.N) - samegrams + 2)
333 | similarity = self.ngram_similarity(samegrams, allgrams, self.warp)
334 | if similarity >= threshold:
335 | results.append((match, similarity))
336 | # Sort results by decreasing similarity
337 | results.sort(key=lambda x: x[1], reverse=True)
338 | return results
339 |
340 | def finditem(self, item, threshold=None):
341 | """Return most similar item to the provided one, or None if
342 | nothing exceeds the threshold.
343 |
344 | >>> from ngram import NGram
345 | >>> n = NGram([(0, "Spam"), (1, "Ham"), (2, "Eggsy"), (3, "Egggsy")],
346 | ... key=lambda x:x[1].lower())
347 | >>> n.finditem((3, 'Hom'))
348 | (1, 'Ham')
349 | >>> n.finditem((4, "Oggsy"))
350 | (2, 'Eggsy')
351 | >>> n.finditem((4, "Oggsy"), 0.8)
352 | """
353 | results = self.searchitem(item, threshold)
354 | if results:
355 | return results[0][0]
356 | else:
357 | return None
358 |
359 | def find(self, query, threshold=None):
360 | """Simply return the best match to the query, None on no match.
361 |
362 | >>> from ngram import NGram
363 | >>> n = NGram(["Spam","Eggs","Ham"], key=lambda x:x.lower(), N=1)
364 | >>> n.find('Hom')
365 | 'Ham'
366 | >>> n.find("Spom")
367 | 'Spam'
368 | >>> n.find("Spom", 0.8)
369 | """
370 | results = self.search(query, threshold)
371 | if results:
372 | return results[0][0]
373 | else:
374 | return None
375 |
376 | @staticmethod
377 | def ngram_similarity(samegrams, allgrams, warp=1.0):
378 | """Similarity for two sets of n-grams.
379 |
380 | :note: ``similarity = (a**e - d**e)/a**e`` where `a` is \
381 | "all n-grams", `d` is "different n-grams" and `e` is the warp.
382 |
383 | :param samegrams: number of n-grams shared by the two strings.
384 |
385 | :param allgrams: total of the distinct n-grams across the two strings.
386 | :return: similarity in the range 0.0 to 1.0.
387 |
388 | >>> from ngram import NGram
389 | >>> NGram.ngram_similarity(5, 10)
390 | 0.5
391 | >>> NGram.ngram_similarity(5, 10, warp=2)
392 | 0.75
393 | >>> NGram.ngram_similarity(5, 10, warp=3)
394 | 0.875
395 | >>> NGram.ngram_similarity(2, 4, warp=2)
396 | 0.75
397 | >>> NGram.ngram_similarity(3, 4)
398 | 0.75
399 | """
400 | if abs(warp - 1.0) < 1e-9:
401 | similarity = float(samegrams) / allgrams
402 | else:
403 | diffgrams = float(allgrams - samegrams)
404 | similarity = ((allgrams ** warp - diffgrams ** warp)
405 | / (allgrams ** warp))
406 | return similarity
407 |
408 | @staticmethod
409 | def compare(s1, s2, **kwargs):
410 | """Compares two strings and returns their similarity.
411 |
412 | :param s1: first string
413 | :param s2: second string
414 | :param kwargs: additional keyword arguments passed to __init__.
415 | :return: similarity between 0.0 and 1.0.
416 |
417 | >>> from ngram import NGram
418 | >>> NGram.compare('spa', 'spam')
419 | 0.375
420 | >>> NGram.compare('ham', 'bam')
421 | 0.25
422 | >>> NGram.compare('spam', 'pam') #N=2
423 | 0.375
424 | >>> NGram.compare('ham', 'ams', N=1)
425 | 0.5
426 | """
427 | if s1 is None or s2 is None:
428 | if s1 == s2:
429 | return 1.0
430 | return 0.0
431 | try:
432 | return NGram([s1], **kwargs).search(s2)[0][1]
433 | except IndexError:
434 | return 0.0
435 |
436 | ### Set operations implemented on top of NGram add/remove
437 |
438 | def update(self, items):
439 | """Update the set with new items.
440 |
441 | >>> from ngram import NGram
442 | >>> n = NGram(["spam"])
443 | >>> n.update(["eggs"])
444 | >>> sorted(list(n))
445 | ['eggs', 'spam']
446 | """
447 | for item in items:
448 | self.add(item)
449 |
450 | def discard(self, item):
451 | """Remove an element from a set if it is a member.
452 |
453 | If the element is not a member, do nothing.
454 |
455 | >>> from ngram import NGram
456 | >>> n = NGram(['spam', 'eggs'])
457 | >>> n.discard('spam')
458 | >>> n.discard('ham')
459 | >>> list(n)
460 | ['eggs']
461 | """
462 | if item in self:
463 | self.remove(item)
464 |
465 | def clear(self):
466 | """Remove all elements from this set.
467 |
468 | >>> from ngram import NGram
469 | >>> n = NGram(['spam', 'eggs'])
470 | >>> sorted(list(n))
471 | ['eggs', 'spam']
472 | >>> n.clear()
473 | >>> list(n)
474 | []
475 | """
476 | super(NGram, self).clear()
477 | self._grams = {}
478 | self.length = {}
479 |
480 | def union(self, *others):
481 | """Return the union of two or more sets as a new set.
482 |
483 | >>> from ngram import NGram
484 | >>> a = NGram(['spam', 'eggs'])
485 | >>> b = NGram(['spam', 'ham'])
486 | >>> sorted(list(a.union(b)))
487 | ['eggs', 'ham', 'spam']
488 | """
489 | return self.copy(super(NGram, self).union(*others))
490 |
491 | def difference(self, *others):
492 | """Return the difference of two or more sets as a new set.
493 |
494 | >>> from ngram import NGram
495 | >>> a = NGram(['spam', 'eggs'])
496 | >>> b = NGram(['spam', 'ham'])
497 | >>> list(a.difference(b))
498 | ['eggs']
499 | """
500 | return self.copy(super(NGram, self).difference(*others))
501 |
502 | def difference_update(self, other):
503 | """Remove from this set all elements from `other` set.
504 |
505 | >>> from ngram import NGram
506 | >>> n = NGram(['spam', 'eggs'])
507 | >>> other = set(['spam'])
508 | >>> n.difference_update(other)
509 | >>> list(n)
510 | ['eggs']
511 | """
512 | for item in other:
513 | self.discard(item)
514 |
515 | def intersection(self, *others):
516 | """Return the intersection of two or more sets as a new set.
517 |
518 | >>> from ngram import NGram
519 | >>> a = NGram(['spam', 'eggs'])
520 | >>> b = NGram(['spam', 'ham'])
521 | >>> list(a.intersection(b))
522 | ['spam']
523 | """
524 | return self.copy(super(NGram, self).intersection(*others))
525 |
526 | def intersection_update(self, *others):
527 | """Update the set with the intersection of itself and other sets.
528 |
529 | >>> from ngram import NGram
530 | >>> n = NGram(['spam', 'eggs'])
531 | >>> other = set(['spam', 'ham'])
532 | >>> n.intersection_update(other)
533 | >>> list(n)
534 | ['spam']
535 | """
536 | self.difference_update(super(NGram, self).difference(*others))
537 |
538 | def symmetric_difference(self, other):
539 | """Return the symmetric difference of two sets as a new set.
540 |
541 | >>> from ngram import NGram
542 | >>> a = NGram(['spam', 'eggs'])
543 | >>> b = NGram(['spam', 'ham'])
544 | >>> sorted(list(a.symmetric_difference(b)))
545 | ['eggs', 'ham']
546 | """
547 | return self.copy(super(NGram, self).symmetric_difference(other))
548 |
549 | def symmetric_difference_update(self, other):
550 | """Update the set with the symmetric difference of itself and `other`.
551 |
552 | >>> from ngram import NGram
553 | >>> n = NGram(['spam', 'eggs'])
554 | >>> other = set(['spam', 'ham'])
555 | >>> n.symmetric_difference_update(other)
556 | >>> sorted(list(n))
557 | ['eggs', 'ham']
558 | """
559 | intersection = super(NGram, self).intersection(other)
560 | self.update(other) # add items present in other
561 | self.difference_update(intersection) # remove items present in both
562 |
--------------------------------------------------------------------------------
/pyproject.toml:
--------------------------------------------------------------------------------
1 | [build-system]
2 | requires = [
3 | "setuptools>=42",
4 | "wheel"
5 | ]
6 | build-backend = "setuptools.build_meta"
--------------------------------------------------------------------------------
/scripts/csvjoin.py:
--------------------------------------------------------------------------------
1 | #!/usr/bin/python
2 | """
3 | Left similarity join between two CSV files.
4 |
5 | For each row in the first file, take the specified join column and find
6 | similar rows in the second file based on ngram similarity to a specified
7 | column in the second file. For each resulting pair of rows, output a row
8 | consisting of the fields from the first file, a column with the similarity
9 | value, and then the fields from the second file.
10 | """
11 | from __future__ import print_function
12 |
13 | import csv, os, re
14 | from ngram import NGram
15 |
16 | def lowstrip(term):
17 | """Convert to lowercase and strip spaces"""
18 | term = re.sub(r'\s+', ' ', term)
19 | term = term.lower()
20 | return term
21 |
22 | def main(left_path, left_column, right_path, right_column,
23 | outfile, titles, join, minscore, count, warp):
24 | """Perform the similarity join"""
25 | right_file = csv.reader(open(right_path, 'r'))
26 | if titles:
27 | right_header = next(right_file)
28 | index = NGram((tuple(r) for r in right_file),
29 | threshold=minscore,
30 | warp=warp, key=lambda x: lowstrip(x[right_column]))
31 | left_file = csv.reader(open(left_path, 'r'))
32 | out = csv.writer(open(outfile, 'w'), lineterminator='\n')
33 | if titles:
34 | left_header = next(left_file)
35 | out.writerow(left_header + ["Rank", "Similarity"] + right_header)
36 | for row in left_file:
37 | if not row: continue # skip blank lines
38 | row = tuple(row)
39 | results = index.search(lowstrip(row[left_column]), threshold=minscore)
40 | if results:
41 | if count > 0:
42 | results = results[:count]
43 | for rank, result in enumerate(results, 1):
44 | out.writerow(row + (rank, result[1]) + result[0])
45 | elif join == "outer":
46 | out.writerow(row)
47 |
48 | def console_main():
49 | """Process command-line arguments."""
50 | from argparse import ArgumentParser
51 | parser = ArgumentParser(description=__doc__)
52 | parser.add_argument('-t', '--titles', action='store_true',
53 | help='input files have column titles')
54 | parser.add_argument(
55 | '-j', '--join', choices=['inner', 'outer'],
56 | help=('The kind of left join to perform. Outer join outputs left-hand '
57 | 'rows which have no right hand match, while inner join discards '
58 | 'such rows. Default: %(default)s'))
59 | parser.add_argument('-m', '--minscore', type=float,
60 | help='Minimum match score: %(default)s')
61 | parser.add_argument('-c', '--count', type=int,
62 | help='Max number of rows to match (0 for all): %(default)s')
63 | parser.add_argument('-w', '--warp', type=float,
64 | help='N-gram warp, higher helps short strings: %(default)s')
65 | parser.add_argument('left', nargs=1, help='First CSV file')
66 | parser.add_argument('leftcolumn', nargs=1, type=int, help='Column in first CSV file')
67 | parser.add_argument('right', nargs=1, help='Second CSV file')
68 | parser.add_argument('rightcolumn', nargs=1, type=int, help='Column in second CSV file')
69 | parser.add_argument('outfile', nargs=1, help='Output CSV file')
70 | parser.set_defaults(
71 | titles=False, join='outer', minscore=0.24, count=0, warp=1.0)
72 | args = parser.parse_args()
73 | for path in [args.left[0], args.right[0]]:
74 | if not os.path.isfile(path):
75 | parser.error('File "%s" does not exist.' % path)
76 | if not (0 <= args.minscore <= 1.0):
77 | parser.error("Minimum score must be between 0 and 1")
78 | if not args.count >= 0:
79 | parser.error("Maximum number of matches per row must be non-negative.")
80 | if args.count == 0:
81 | args.count = None # to return all results
82 | main(args.left[0], args.leftcolumn[0], args.right[0], args.rightcolumn[0],
83 | args.outfile[0], args.titles, args.join, args.minscore, args.count,
84 | args.warp)
85 |
86 |
87 | if __name__ == '__main__':
88 | console_main()
89 |
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/setup.cfg:
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1 | [metadata]
2 | name = ngram
3 | version = 4.0.3
4 | description = A `set` subclass providing fuzzy search based on N-grams.
5 | long_description = file: README
6 | long_description_content_type = text/x-rst
7 | author = Graham Poulter, Michel Albert
8 | maintainer = Graham Poulter
9 | license = LGPL3
10 | url = https://github.com/gpoulter/python-ngram
11 | download_url = http://pypi.python.org/pypi/ngram
12 | keywords = ngram set string text similarity
13 | platforms = any
14 | project_urls =
15 | Documentation = https://python-ngram.readthedocs.io/en/latest/
16 | classifiers =
17 | Development Status :: 5 - Production/Stable
18 | Intended Audience :: Developers
19 | License :: OSI Approved :: GNU Lesser General Public License v3 or later (LGPLv3+)
20 | License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
21 | License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
22 | Natural Language :: English
23 | Topic :: Text Processing
24 | Topic :: Text Processing :: Indexing
25 | Topic :: Text Processing :: Linguistic
26 | Operating System :: OS Independent
27 | Programming Language :: Python
28 | Programming Language :: Python :: 3
29 |
30 | [build_sphinx]
31 | source-dir = docs
32 | build-dir = docs/build
33 | all_files = 1
34 |
35 | [upload_sphinx]
36 | upload-dir = docs/build/html
37 |
38 | [nosetests]
39 | exe = 1
40 |
41 | [options]
42 | py_modules =
43 | ngram
44 | python_requires = >=3.0
45 | scripts =
46 | scripts/csvjoin.py
47 |
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/setup.py:
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1 | import setuptools
2 | setuptools.setup()
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/tests/__init__.py:
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https://raw.githubusercontent.com/gpoulter/python-ngram/2896d63f366b8d111fdd1d24e5b24ae25474aa6c/tests/__init__.py
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/tests/test_csvjoin.py:
--------------------------------------------------------------------------------
1 | #!/usr/bin/python
2 |
3 | import os
4 | import os.path
5 | import subprocess
6 | import sys
7 | import tempfile
8 | import textwrap
9 | import unittest
10 |
11 | class CsvjoinTests(unittest.TestCase):
12 |
13 | def setUp(self):
14 | self.tmpdir = tempfile.mkdtemp(prefix="csvjoin_test_")
15 | self.leftpath = os.path.join(self.tmpdir, 'left')
16 | self.rightpath = os.path.join(self.tmpdir, 'right')
17 | self.outpath = os.path.join(self.tmpdir, 'output')
18 | with open(self.leftpath, 'w') as left:
19 | left.write('''ID,NAME\n1,Joe\n2,Kin\n3,ZAS''')
20 | with open(self.rightpath, 'w') as right:
21 | right.write('''ID,NAME\nID,NAME\nA,Joe\nB,Jon\nC,Job\nD,Kim''')
22 |
23 | def tearDown(self):
24 | os.remove(self.leftpath)
25 | os.remove(self.rightpath)
26 | os.remove(self.outpath)
27 | os.rmdir(self.tmpdir)
28 |
29 | def test_csvjoin(self):
30 | args = [
31 | sys.executable,
32 | 'scripts/csvjoin.py', '--titles', '-j', 'outer', '--minscore=0.24',
33 | '--count=5', '--warp=1.0',
34 | self.leftpath, '1', self.rightpath, '1', self.outpath
35 | ]
36 | print(args)
37 | subprocess.call(args)
38 | with open(self.outpath, 'r') as out:
39 | result = '\n'.join(s.strip() for s in out.readlines())
40 | correct = textwrap.dedent("""\
41 | ID,NAME,Rank,Similarity,ID,NAME
42 | 1,Joe,1,1.0,A,Joe
43 | 1,Joe,2,0.25,B,Jon
44 | 1,Joe,3,0.25,C,Job
45 | 2,Kin,1,0.25,D,Kim
46 | 3,ZAS""")
47 | self.assertEqual(result, correct)
48 |
49 | if __name__ == "__main__":
50 | unittest.main()
51 |
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/tests/test_ngram.py:
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1 | #!/usr/bin/env python
2 | # -*- coding: utf-8 -*-
3 |
4 | """Unit tests for the ngram module."""
5 |
6 | import unittest
7 | from ngram import NGram
8 |
9 |
10 | class NgramTests(unittest.TestCase):
11 | """Tests of the ngram class"""
12 |
13 | items = ['sdafaf', 'asfwef', 'asdfawe', 'adfwe', 'askfjwehiuasdfji']
14 |
15 | def test_ngram_search(self):
16 | """Tests from the original ngram.py, to check that the
17 | rewrite still uses the same underlying algorithm"""
18 |
19 | # Basic searching of the index
20 | idx = NGram(self.items)
21 | self.assertEqual(idx.search('askfjwehiuasdfji'), [
22 | ('askfjwehiuasdfji', 1.0),
23 | ('asdfawe', 0.17391304347826086),
24 | ('asfwef', 0.083333333333333329),
25 | ('adfwe', 0.041666666666666664)])
26 | self.assertEqual(idx.search('afadfwe')[:2],
27 | [('adfwe', 0.59999999999999998),
28 | ('asdfawe', 0.20000000000000001)])
29 |
30 | # Pairwise comparison of strings
31 | self.assertEqual(NGram.compare('sdfeff', 'sdfeff'), 1.0)
32 | self.assertEqual(NGram.compare('sdfeff', 'zzzzzz'), 0.0)
33 |
34 | def test_set_operations(self):
35 | """Test advanced set operations"""
36 | items1 = set(["abcde", "cdefg", "fghijk", "ijklm"])
37 | items2 = set(["cdefg", "lmnop"])
38 | idx1 = NGram(items1)
39 | idx2 = NGram(items2)
40 | results = lambda L: sorted(x[0] for x in L)
41 | # Item removal
42 | self.assertEqual(results(idx1.search('cde')), ["abcde", "cdefg"])
43 | idx1.remove('abcde')
44 | self.assertEqual(results(idx1.search('cde')), ["cdefg"])
45 | # Set intersection operation
46 | items1.remove('abcde')
47 | idx1.intersection_update(idx2)
48 | self.assertEqual(idx1, items1.intersection(items2))
49 | self.assertEqual(results(idx1.search('lmn')), [])
50 | self.assertEqual(results(idx1.search('ijk')), [])
51 | self.assertEqual(results(idx1.search('def')), ['cdefg'])
52 |
53 |
54 | if __name__ == "__main__":
55 | unittest.main()
56 |
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/tox.ini:
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1 | [tox]
2 | envlist=py3
3 |
4 | [testenv]
5 | deps=
6 | pytest
7 | sphinx
8 | commands=
9 | py.test \
10 | --ignore=setup.py \
11 | --ignore=docs/conf.py \
12 | --doctest-modules \
13 | --doctest-glob=*.rst \
14 | []
15 |
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