## Description
Fix for issue #2361 :
replace &, <, >, " with &amp; , &lt; , &gt; , &quot; in before rendering svg
## 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.
- [ ] I ran the tests, and all new and existing tests passed.
(As discussed in the comments to #2361)
- [x] My changes don't require a change to the documentation, or if they do, I've added all required information.
* Simplify is_config() and normalize_string_keys()
* Use __in__ to avoid the nested _ands_ and _ors_.
* Dict comprehension directly tracks with the doc string
* Keep more basic loop in normalize_string_keys
* Whitespace
* Go back to using requests instead of urllib (closes#2320)
Fewer dependencies are good, but this one was simply causing too many other problems around SSL verification and Python 2/3 compatibility. requests is a popular enough package that it's okay for spaCy to depend on it – and this will hopefully make model downloads less flakey.
* Only download model if not installed (see #1456)
Use #egg=model==version to allow pip to check for existing installations. The download is only started if no installation matching the package/version is found. Fixes a long-standing inconvenience.
* Pass additional options to pip when installing model (resolves#1456)
Treat all additional arguments passed to the download command as pip options to allow user to customise the command. For example:
python -m spacy download en --user
* Add CLI option to enable installing model package dependencies
* Revert "Add CLI option to enable installing model package dependencies"
This reverts commit 9336ffe695.
* Update documentation
* Add Romanian lemmatizer lookup table.
Adapted from http://www.lexiconista.com/datasets/lemmatization/
by replacing cedillas with commas (ș and ț).
The original dataset is licensed under the Open Database License.
* Fix one blatant issue in the Romanian lemmatizer
* Romanian examples file
* Add ro_tokenizer in conftest
* Add Romanian lemmatizer test
* Fix the code for FACILITIY entities
As far as I can tell, the default models all use "FAC" rather than "FACILITY"
* Added my Contributor Agreement
* Rename vishnumenon to vishnumenon.md
* Update lex_attrs.py
Fixed spelling mistakes of some numbers (according to Brazilian Portuguese).
* Update lex_attrs.py
As requested, I've included the correct spelling for both Brazilian Portuguese and Portuguese Portuguese.
I will advise however, that the two are separated in the future. Brazilian Portuguese is a very different language from the original one, although most of the writing is unified, the way people talk in both countries is radically different. Keeping both languages as one may lead to bigger issues in the future, especially when it comes to spell checking.
* Add contraction forms of some common stopwords
All the stopwords added contain the apostrophe" ' "or " ’ ".
* Adds contributor agreement mauryaland
* Update mauryaland.md
Failing to set a default, method, or getter results in a ValueError:
ValueError: [E083] Error setting extension: only one of `default`, `method`, or `getter` (plus optional `setter`) is allowed. Got: 0
* Port Japanese mecab tokenizer from v1
This brings the Mecab-based Japanese tokenization introduced in #1246 to
spaCy v2. There isn't a JapaneseTagger implementation yet, but POS tag
information from Mecab is stored in a token extension. A tag map is also
included.
As a reminder, Mecab is required because Universal Dependencies are
based on Unidic tags, and Janome doesn't support Unidic.
Things to check:
1. Is this the right way to use a token extension?
2. What's the right way to implement a JapaneseTagger? The approach in
#1246 relied on `tag_from_strings` which is just gone now. I guess the
best thing is to just try training spaCy's default Tagger?
-POLM
* Add tagging/make_doc and tests
* Fix code sample for `set_extension`
The previous sample code for `set_extension` fails the assertion at the end, because `city_getter` it checked if the whole document text matches any of the city names. Now it checks if any of the city names is contained in the document text.
* Contributor agreement
* Integrate Python kernel via Binder
* Add live model test for languages with examples
* Update docs and code examples
* Adjust margin (if not bootstrapped)
* Add binder version to global config
* Update terminal and executable code mixins
* Pass attributes through infobox and section
* Hide v-cloak
* Fix example
* Take out model comparison for now
* Add meta text for compat
* Remove chart.js dependency
* Tidy up and simplify JS and port big components over to Vue
* Remove chartjs example
* Add Twitter icon
* Add purple stylesheet option
* Add utility for hand cursor (special cases only)
* Add transition classes
* Add small option for section
* Add thumb object for small round thumbnail images
* Allow unset code block language via "none" value
(workaround to still allow unset language to default to DEFAULT_SYNTAX)
* Pass through attributes
* Add syntax highlighting definitions for Julia, R and Docker
* Add website icon
* Remove user survey from navigation
* Don't hide GitHub icon on small screens
* Make top navigation scrollable on small screens
* Remove old resources page and references to it
* Add Universe
* Add helper functions for better page URL and title
* Update site description
* Increment versions
* Update preview images
* Update mentions of resources
* Fix image
* Fix social images
* Fix problem with cover sizing and floats
* Add divider and move badges into heading
* Add docstrings
* Reference converting section
* Add section on converting word vectors
* Move converting section to custom section and fix formatting
* Remove old fastText example
* Move extensions content to own section
Keep weird ID to not break permalinks for now (we don't want to rewrite URLs if not absolutely necessary)
* Use better component example and add factories section
* Add note on larger model
* Use better example for non-vector
* Remove similarity in context section
Only works via small models with tensors so has always been kind of confusing
* Add note on init-model command
* Fix lightning tour examples and make excutable if possible
* Add spacy train CLI section to train
* Fix formatting and add video
* Fix formatting
* Fix textcat example description (resolves#2246)
* Add dummy file to try resolve conflict
* Delete dummy file
* Tidy up [ci skip]
* Ensure sufficient height of loading container
* Add loading animation to universe
* Update Thebelab build and use better startup message
* Fix asset versioning
* Fix typo [ci skip]
* Add note on project idea label
