spaCy v2.1 switched to the built-in re module, where v2.0 had been using
the third-party regex library. When the tokenizer was deserialized on
Python2.7, the `re.compile()` function was called with expressions that
featured escaped unicode codepoints that were not in Python2.7's unicode
database.
Problems occurred when we had a range between two of these unknown
codepoints, like this:
```
'[\\uAA77-\\uAA79]'
```
On Python2.7, the unknown codepoints are not unescaped correctly,
resulting in arbitrary out-of-range characters being matched by the
expression.
This problem does not occur if we instead have a range between two
unicode literals, rather than the escape sequences. To fix the bug, we
therefore add a new compat function that unescapes unicode sequences
using the `ast.literal_eval()` function. Care is taken to ensure we
do not also escape non-unicode sequences.
Closes#3356.
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* merging conllu/conll and conllubio scripts
* tabs to spaces
* removing conllubio2json from converters/__init__.py
* Move not-really-CLI tests to misc
* Add converter test using no-ud data
* Fix test I broke
* removing include_biluo parameter
* fixing read_conllx
* remove include_biluo from convert.py
* label in span not writable anymore
* more explicit unit test and error message for readonly label
* bit more explanation (view)
* error msg tailored to specific case
* fix None case
Closes#2091.
## Description
With the new `vocab.writing_system` property introduced in #3390 (exposed via the language defaults), I was able to finally fix this (I think!). Based on the `Doc`, dispaCy now detects whether it's a RTL or LTR language and adjusts the visualization accordingly. Wherever possible, I've also added `direction` and `lang` attributes.
Entity visualization now looks like this:
<img width="318" alt="Screenshot 2019-03-11 at 16 06 51" src="https://user-images.githubusercontent.com/13643239/54136866-d97afd80-441c-11e9-8c27-3d46994cc833.png">
And dependencies like this (ignore the most likely incorrect tags and dependencies):
<img width="621" alt="Screenshot 2019-03-11 at 16 51 59" src="https://user-images.githubusercontent.com/13643239/54137771-8b66f980-441e-11e9-8460-0682b95eef2a.png">
### Types of change
enhancement, bug fix
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Add xfail test for vocab.writing_system
* Add vocab.writing_system property
* Set Language.Defaults.writing_system
* Set default writing system
* Remove xfail on test_vocab_writing_system
Closes#2203. Closes#3268.
Lemmas set from outside the `Morphology` class were being overwritten. The result was especially confusing when deserialising, as it meant some lemmas could change when storing and retrieving a `Doc` object.
This PR applies two fixes:
1) When we go to set the lemma in the `Morphology` class, first check whether a lemma is already set. If so, don't overwrite.
2) When we load with `doc.from_array()`, take care to apply the `TAG` field first. This allows other fields to overwrite the `TAG` implied properties, if they're provided explicitly (e.g. the `LEMMA`).
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Make serialization methods consistent
exclude keyword argument instead of random named keyword arguments and deprecation handling
* Update docs and add section on serialization fields
* Use default return instead of else
* Add Doc.is_nered to indicate if entities have been set
* Add properties in Doc.to_json if they were set, not if they're available
This way, if a processed Doc exports "pos": None, it means that the tag was explicitly unset. If it exports "ents": [], it means that entity annotations are available but that this document doesn't contain any entities. Before, this would have been unclear and problematic for training.
* Improve handling of missing NER tags
GoldParse can accept missing NER tags, if entities is provided
in BILUO format (rather than as spans). Missing tags can be provided
as None values.
Fix bug that occurred when first tag was a None value. Closes#2603.
* Document specification of missing NER tags.
* Classes for Ukrainian; small fix in Russian.
* Contributor agreement
* pymorphy2 initialization split for ru and uk (#3327)
* stop-words fixed
* Unit-tests updated
<!--- Provide a general summary of your changes in the title. -->
## Description
This PR adds the abilility to override custom extension attributes during merging. This will only work for attributes that are writable, i.e. attributes registered with a default value like `default=False` or attribute that have both a getter *and* a setter implemented.
```python
Token.set_extension('is_musician', default=False)
doc = nlp("I like David Bowie.")
with doc.retokenize() as retokenizer:
attrs = {"LEMMA": "David Bowie", "_": {"is_musician": True}}
retokenizer.merge(doc[2:4], attrs=attrs)
assert doc[2].text == "David Bowie"
assert doc[2].lemma_ == "David Bowie"
assert doc[2]._.is_musician
```
### Types of change
enhancement
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* splitting up latin unicode interval
* removing hyphen as infix for French
* adding failing test for issue 1235
* test for issue #3002 which now works
* partial fix for issue #2070
* keep the hyphen as infix for French (as it was)
* restore french expressions with hyphen as infix (as it was)
* added succeeding unit test for Issue #2656
* Fix issue #2822 with custom Italian exception
* Fix issue #2926 by allowing numbers right before infix /
* splitting up latin unicode interval
* removing hyphen as infix for French
* adding failing test for issue 1235
* test for issue #3002 which now works
* partial fix for issue #2070
* keep the hyphen as infix for French (as it was)
* restore french expressions with hyphen as infix (as it was)
* added succeeding unit test for Issue #2656
* Fix issue #2822 with custom Italian exception
* Fix issue #2926 by allowing numbers right before infix /
* remove duplicate
* remove xfail for Issue #2179 fixed by Matt
* adjust documentation and remove reference to regex lib
* Fix matching on extension attrs and predicates
* Fix detection of match_id when using extension attributes. The match
ID is stored as the last entry in the pattern. We were checking for this
with nr_attr == 0, which didn't account for extension attributes.
* Fix handling of predicates. The wrong count was being passed through,
so even patterns that didn't have a predicate were being checked.
* Fix regex pattern
* Fix matcher set value test
* Change retokenize.split() API for heads
* Pass lists as values for attrs in split
* Fix test_doc_split filename
* Add error for mismatched tokens after split
* Raise error if new tokens don't match text
* Fix doc test
* Fix error
* Move deps under attrs
* Fix split tests
* Fix retokenize.split
* Add base classes for more languages
* Add test for language class initialization
Make sure language can be initialize – otherwise, it's difficult to catch serious errors in the test suite, because languages are lazy-loaded
* Add split one token into several (resolves#2838)
* Improve error message for token splitting
* Make retokenizer.split() tests use a Token object
Change retokenizer.split() to use a Token object, instead of an index.
* Pass Token into retokenize.split()
Tweak retokenize.split() API so that we pass the `Token` object, not the index.
* Fix token.idx in retokenize.split()
* Test that token.idx is correct after split
* Fix token.idx for split tokens
* Fix retokenize.split()
* Fix retokenize.split
* Fix retokenize.split() test
* Add custom MatchPatternError
* Improve validators and add validation option to Matcher
* Adjust formatting
* Never validate in Matcher within PhraseMatcher
If we do decide to make validate default to True, the PhraseMatcher's Matcher shouldn't ever validate. Here, we create the patterns automatically anyways (and it's currently unclear whether the validation has performance impacts at a very large scale).
In most cases, the PhraseMatcher will match on the verbatim token text or as of v2.1, sometimes the lowercase text. This means that we only need a tokenized Doc, without any other attributes.
If phrase patterns are created by processing large terminology lists with the full `nlp` object, this easily can make things a lot slower, because all components will be applied, even if we don't actually need the attributes they set (like part-of-speech tags, dependency labels).
The warning message also includes a suggestion to use nlp.make_doc or nlp.tokenizer.pipe for even faster processing. For now, the validation has to be enabled explicitly by setting validate=True.
* Improved stop words list
* Removed some wrong stop words form list
* Improved stop words list
* Removed some wrong stop words form list
* Improved Polish Tokenizer (#38)
* Add tests for polish tokenizer
* Add polish tokenizer exceptions
* Don't split any words containing hyphens
* Fix test case with wrong model answer
* Remove commented out line of code until better solution is found
* Add source srx' license
* Rename exception_list.py to match spaCy conventionality
* Add a brief explanation of where the exception list comes from
* Add newline after reach exception
* Rename COPYING.txt to LICENSE
* Delete old files
* Add header to the license
* Agreements signed
* Stanisław Giziński agreement
* Krzysztof Kowalczyk - signed agreement
* Mateusz Olko agreement
* Add DoomCoder's contributor agreement
* Improve like number checking in polish lang
* like num tests added
* all from SI system added
* Final licence and removed splitting exceptions
* Added polish stop words to LEX_ATTRA
* Add encoding info to pl tokenizer exceptions
## Description
1. Added the same infix rule as in French (`d'une`, `j'ai`) for Italian (`c'è`, `l'ha`), bringing F-score on `it_isdt-ud-train.txt` from 96% to 99%. Added unit test to check this behaviour.
2. Added specific Urdu punctuation character as suffix, improving F-score on `ur_udtb-ud-train.txt` from 94% to 100%. Added unit test to check this behaviour.
### Types of change
Enhancement of Italian & Urdu tokenization
## Checklist
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* replace unicode categories with raw list of code points
* simplifying ranges
* fixing variable length quotes
* removing redundant regular expression
* small cleanup of regexp notations
* quotes and alpha as ranges instead of alterations
* removed most regexp dependencies and features
* exponential backtracking - unit tests
* rewrote expression with pathological backtracking
* disabling double hyphen tests for now
* test additional variants of repeating punctuation
* remove regex and redundant backslashes from load_reddit script
* small typo fixes
* disable double punctuation test for russian
* clean up old comments
* format block code
* final cleanup
* naming consistency
* french strings as unicode for python 2 support
* french regular expression case insensitive
* Update matcher engine for regex and extensions
Add support for matching over arbitrary Python predicate functions, and
arbitrary Python attribute getters. This will allow matching over regex
patterns, and allow supporting extension attributes.
The results of the Python predicate functions are cached, so that we don't
call the same predicate function twice for the same token. The extension
attributes are fetched into an array for each token in the doc. This
should minimise the performance impact of the new features.
We still need to wire up these features to the patterns, and test it
all.
* Work on wiring up extra attributes in matcher
* Work on tests for extra matcher attrs
* Add support for extension attrs to matcher
* Test extension attribute matching
* Work on implementing predicate-based match patterns
* Get predicates working for set membership
* Add test for set membership
* Make extensions+predicates work
* Test matcher extensions
* Cache predicate results better in Matcher
* Remove print statement in matcher test
* Use srsly to get key for predicates
* Added the same punctuation rules as danish language.
* Added abbreviations and also the possibility to have capitalized abbreviations on some. Added a few specific cases too
* Added test for long texts in swedish
* Added morph rules, infixes and suffixes to __init__.py for swedish
* Added some tests for prefixes, infixes and suffixes
* Added tests for lemma
* Renamed files to follow convention
* [sv] Removed ambigious abbreviations
* Added more tests for tokenizer exceptions
* Added test for problem with punctuation in issue #2578
* Contributor agreement
* Removed faulty lemmatization of 'jag' ('I') as it was lemmatized to 'jaga' ('hunt')
This PR adds a test for an untested case of `Span.get_lca_matrix`, and fixes a bug for that scenario, which I introduced in [this PR](https://github.com/explosion/spaCy/pull/3089) (sorry!).
## Description
The previous implementation of get_lca_matrix was failing for the case `doc[j:k].get_lca_matrix()` where `j > 0`. A test has been added for this case and the bug has been fixed.
### Types of change
Bug fix
## Checklist
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
Initially span.as_doc() was designed to return a view of the span's contents, as a Doc object. This was a nice idea, but it fails due to the token.idx property, which refers to the character offset within the string. In a span, the idx of the first token might not be 0. Because this data is different, we can't have a view --- it'll be inconsistent.
This patch changes span.as_doc() to instead return a copy. The docs are updated accordingly. Closes#1537
* Update test for span.as_doc()
* Make span.as_doc() return a copy. Closes#1537
* Document change to Span.as_doc()
The doc.retokenize() context manager wasn't resizing doc.tensor, leading to a mismatch between the number of tokens in the doc and the number of rows in the tensor. We fix this by deleting rows from the tensor. Merged spans are represented by the vector of their last token.
* Add test for resizing doc.tensor when merging
* Add test for resizing doc.tensor when merging. Closes#1963
* Update get_lca_matrix test for develop
* Fix retokenize if tensor unset
<!--- Provide a general summary of your changes in the title. -->
## Description
See #3079. Here I'm merging into `develop` instead of `master`.
### Types of change
<!-- What type of change does your PR cover? Is it a bug fix, an enhancement
or new feature, or a change to the documentation? -->
Bug fix.
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Test on #2396: bug in Doc.get_lca_matrix()
* reimplementation of Doc.get_lca_matrix(), (closes#2396)
* reimplement Span.get_lca_matrix(), and call it from Doc.get_lca_matrix()
* tests Span.get_lca_matrix() as well as Doc.get_lca_matrix()
* implement _get_lca_matrix as a helper function in doc.pyx; call it from Doc.get_lca_matrix and Span.get_lca_matrix
* use memory view instead of np.ndarray in _get_lca_matrix (faster)
* fix bug when calling Span.get_lca_matrix; return lca matrix as np.array instead of memoryview
* cleaner conditional, add comment
* Test on #2396: bug in Doc.get_lca_matrix()
* reimplementation of Doc.get_lca_matrix(), (closes#2396)
* reimplement Span.get_lca_matrix(), and call it from Doc.get_lca_matrix()
* tests Span.get_lca_matrix() as well as Doc.get_lca_matrix()
* implement _get_lca_matrix as a helper function in doc.pyx; call it from Doc.get_lca_matrix and Span.get_lca_matrix
* use memory view instead of np.ndarray in _get_lca_matrix (faster)
* fix bug when calling Span.get_lca_matrix; return lca matrix as np.array instead of memoryview
* cleaner conditional, add comment
* Add failing test for matcher bug #3009
* Deduplicate matches from Matcher
* Update matcher ? quantifier test
* Fix bug with ? quantifier in Matcher
The ? quantifier indicates a token may occur zero or one times. If the
token pattern fit, the matcher would fail to consider valid matches
where the token pattern did not fit. Consider a simple regex like:
.?b
If we have the string 'b', the .? part will fit --- but then the 'b' in
the pattern will not fit, leaving us with no match. The same bug left us
with too few matches in some cases. For instance, consider:
.?.?
If we have a string of length two, like 'ab', we actually have three
possible matches here: [a, b, ab]. We were only recovering 'ab'. This
should now be fixed. Note that the fix also uncovered another bug, where
we weren't deduplicating the matches. There are actually two ways we
might match 'a' and two ways we might match 'b': as the second token of the pattern,
or as the first token of the pattern. This ambiguity is spurious, so we
need to deduplicate.
Closes#2464 and #3009
* Fix Python2
## Description
- [x] fix auto-detection of Jupyter notebooks (even if `jupyter=True` isn't set)
- [x] add `displacy.set_render_wrapper` method to define a custom function called around the HTML markup generated in all calls to `displacy.render` (can be used to allow custom integrations, callbacks and page formatting)
- [x] add option to customise host for web server
- [x] show warning if `displacy.serve` is called from within Jupyter notebooks
- [x] move error message to `spacy.errors.Errors`.
### Types of change
enhancement
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* issue #3012: add test
* add contributor aggreement
* Make test work without models and fix typos
ten.pos_ instead of ten.orth_ and comparison against "10" instead of integer 10
Fixes#3027.
* Allow Span.__init__ to take unicode values for the `label` argument.
* Allow `Span.label_` to be writeable.
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [ ] My changes don't require a change to the documentation, or if they do, I've added all required information.
See #3028. The solution in this patch is pretty debateable.
What we do is give the TokenC struct a .norm field, by repurposing the previously idle .sense attribute. It's nice to repurpose a previous field because it means the TokenC doesn't change size, so even if someone's using the internals very deeply, nothing will break.
The weird thing here is that the TokenC and the LexemeC both have an attribute named NORM. This arguably assists in backwards compatibility. On the other hand, maybe it's really bad! We're changing the semantics of the attribute subtly, so maybe it's better if someone calling lex.norm gets a breakage, and instead is told to write lex.default_norm?
Overall I believe this patch makes the NORM feature work the way we sort of expected it to work. Certainly it's much more like how the docs describe it, and more in line with how we've been directing people to use the norm attribute. We'll also be able to use token.norm to do stuff like spelling correction, which is pretty cool.
Remove hacks and wrappers, keep code in sync across our libraries and move spaCy a few steps closer to only depending on packages with binary wheels 🎉
See here: https://github.com/explosion/srsly
Serialization is hard, especially across Python versions and multiple platforms. After dealing with many subtle bugs over the years (encodings, locales, large files) our libraries like spaCy and Prodigy have steadily grown a number of utility functions to wrap the multiple serialization formats we need to support (especially json, msgpack and pickle). These wrapping functions ended up duplicated across our codebases, so we wanted to put them in one place.
At the same time, we noticed that having a lot of small dependencies was making maintainence harder, and making installation slower. To solve this, we've made srsly standalone, by including the component packages directly within it. This way we can provide all the serialization utilities we need in a single binary wheel.
srsly currently includes forks of the following packages:
ujson
msgpack
msgpack-numpy
cloudpickle
* WIP: replace json/ujson with srsly
* Replace ujson in examples
Use regular json instead of srsly to make code easier to read and follow
* Update requirements
* Fix imports
* Fix typos
* Replace msgpack with srsly
* Fix warning
* Support nowrap setting in util.prints
* Tidy up and fix whitespace
* Simplify script and use read_jsonl helper
* Add JSON schemas (see #2928)
* Deprecate Doc.print_tree
Will be replaced with Doc.to_json, which will produce a unified format
* Add Doc.to_json() method (see #2928)
Converts Doc objects to JSON using the same unified format as the training data. Method also supports serializing selected custom attributes in the doc._. space.
* Remove outdated test
* Add write_json and write_jsonl helpers
* WIP: Update spacy train
* Tidy up spacy train
* WIP: Use wasabi for formatting
* Add GoldParse helpers for JSON format
* WIP: add debug-data command
* Fix typo
* Add missing import
* Update wasabi pin
* Add missing import
* 💫 Refactor CLI (#2943)
To be merged into #2932.
## Description
- [x] refactor CLI To use [`wasabi`](https://github.com/ines/wasabi)
- [x] use [`black`](https://github.com/ambv/black) for auto-formatting
- [x] add `flake8` config
- [x] move all messy UD-related scripts to `cli.ud`
- [x] make converters function that take the opened file and return the converted data (instead of having them handle the IO)
### Types of change
enhancement
## Checklist
<!--- Before you submit the PR, go over this checklist and make sure you can
tick off all the boxes. [] -> [x] -->
- [x] I have submitted the spaCy Contributor Agreement.
- [x] I ran the tests, and all new and existing tests passed.
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Update wasabi pin
* Delete old test
* Update errors
* Fix typo
* Tidy up and format remaining code
* Fix formatting
* Improve formatting of messages
* Auto-format remaining code
* Add tok2vec stuff to spacy.train
* Fix typo
* Update wasabi pin
* Fix path checks for when train() is called as function
* Reformat and tidy up pretrain script
* Update argument annotations
* Raise error if model language doesn't match lang
* Document new train command
