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Fix broken links and add check_links shortcut script

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ines 2017-11-01 21:11:10 +01:00
parent f5855e539b
commit 2ba4e4fc88
10 changed files with 35 additions and 30 deletions
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2
website/api/_top-level/_util.jade
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@ -246,7 +246,7 @@ p
p
| Check if user is running spaCy from a #[+a("https://jupyter.org") Jupyter]
| notebook by detecting the IPython kernel. Mainly used for the
| #[+api("displacy") #[code displacy]] visualizer.
| #[+api("top-level#displacy") #[code displacy]] visualizer.
+aside-code("Example").
html = '<h1>Hello world!</h1>'

2
website/package.json
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@ -13,6 +13,8 @@
},
"dependencies": {},
"scripts": {
"check_links": "blc https://alpha.spacy.io -ro",
"compile": "NODE_ENV=deploy harp compile",
"rollup_js": "rollup www/assets/js/rollup.js --output.format iife --output.file www/assets/js/rollup.js",
"compile_rollup": "babel www/assets/js/rollup.js --out-file www/assets/js/rollup.js --presets=es2015",

9
website/usage/_install/_troubleshooting.jade
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@ -33,7 +33,7 @@ p
OSError: symbolic link privilege not held
p
| To create #[+a("/usage/models/#usage") shortcut links] that let you
| To create #[+a("/usage/models#usage") shortcut links] that let you
| load models by name, spaCy creates a symbolic link in the
| #[code spacy/data] directory. This means your user needs permission to do
| this. The above error mostly occurs when doing a system-wide installation,
@ -76,7 +76,7 @@ p
p
| As of spaCy v1.7, all models can be installed as Python packages. This means
| that they'll become importable modules of your application. When creating
| #[+a("/usage/models/#usage") shortcut links], spaCy will also try
| #[+a("/usage/models#usage") shortcut links], spaCy will also try
| to import the model to load its meta data. If this fails, it's usually a
| sign that the package is not installed in the current environment.
| Run #[code pip list] or #[code pip freeze] to check which model packages
@ -93,9 +93,8 @@ p
p
| This error may occur when using #[code spacy.load()] to load
| a language model – either because you haven't set up a
| #[+a("/usage/models/#usage") shortcut link] for it, or because it
| doesn't actually exist. Set up a
| #[+a("/usage/models/#usage") shortcut link] for the model
| #[+a("/usage/models#usage") shortcut link] for it, or because it
| doesn't actually exist. Set up a link for the model
| you want to load. This can either be an installed model package, or a
| local directory containing the model data. If you want to use one of the
| #[+a("/usage/models#languages") alpha tokenizers] for

8
website/usage/_linguistic-features/_dependency-parse.jade
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@ -187,8 +187,8 @@ p
| The best way to understand spaCy's dependency parser is interactively.
| To make this easier, spaCy v2.0+ comes with a visualization module. Simply
| pass a #[code Doc] or a list of #[code Doc] objects to
| displaCy and run #[+api("displacy#serve") #[code displacy.serve]] to
| run the web server, or #[+api("displacy#render") #[code displacy.render]]
| displaCy and run #[+api("top-level#displacy.serve") #[code displacy.serve]] to
| run the web server, or #[+api("top-level#displacy.render") #[code displacy.render]]
| to generate the raw markup. If you want to know how to write rules that
| hook into some type of syntactic construction, just plug the sentence into
| the visualizer and see how spaCy annotates it.
@ -209,7 +209,7 @@ p
p
| In the #[+a("/models") default models], the parser is loaded and enabled
| as part of the
| #[+a("docs/usage/language-processing-pipelines") standard processing pipeline].
| #[+a("/usage/processing-pipelines") standard processing pipeline].
| If you don't need any of the syntactic information, you should disable
| the parser. Disabling the parser will make spaCy load and run much faster.
| If you want to load the parser, but need to disable it for specific
@ -228,7 +228,7 @@ p
| #[+a("/usage/processing-pipelines") pipeline component names].
| This lets you disable both default and custom components when loading
| a model, or initialising a Language class via
| #[+api("language-from_disk") #[code from_disk]].
| #[+api("language#from_disk") #[code from_disk]].
+code-new.
nlp = spacy.load('en', disable=['parser'])
doc = nlp(u"I don't want parsed", disable=['parser'])

6
website/usage/_linguistic-features/_named-entities.jade
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@ -59,7 +59,7 @@ p
+annotation-row(["delivery", 2, "O", '""', "outside an entity"], style)
+annotation-row(["robots", 2, "O", '""', "outside an entity"], style)
+h(3, "setting") Setting entity annotations
+h(3, "setting-entities") Setting entity annotations
p
| To ensure that the sequence of token annotations remains consistent, you
@ -186,8 +186,8 @@ p
| If you're training a model, it's very useful to run the visualization
| yourself. To help you do that, spaCy v2.0+ comes with a visualization
| module. Simply pass a #[code Doc] or a list of #[code Doc] objects to
| displaCy and run #[+api("displacy#serve") #[code displacy.serve]] to
| run the web server, or #[+api("displacy#render") #[code displacy.render]]
| displaCy and run #[+api("top-level#displacy.serve") #[code displacy.serve]] to
| run the web server, or #[+api("top-level#displacy.render") #[code displacy.render]]
| to generate the raw markup.
p

6
website/usage/_processing-pipelines/_pipelines.jade
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@ -7,11 +7,11 @@ p
| functions. A pipeline component can be added to an already existing
| #[code nlp] object, specified when initialising a #[code Language] class,
| or defined within a
| #[+a("/usage/saving-loading#models-generating") model package].
| #[+a("/usage/training#saving-loading") model package].
p
| When you load a model, spaCy first consults the model's
| #[+a("/usage/saving-loading#models-generating") #[code meta.json]]. The
| #[+a("/usage/training#saving-loading") #[code meta.json]]. The
| meta typically includes the model details, the ID of a language class,
| and an optional list of pipeline components. spaCy then does the
| following:
@ -27,7 +27,7 @@ p
+list("numbers")
+item
| Load the #[strong language class and data] for the given ID via
| #[+api("util.get_lang_class") #[code get_lang_class]] and initialise
| #[+api("top-level#util.get_lang_class") #[code get_lang_class]] and initialise
| it. The #[code Language] class contains the shared vocabulary,
| tokenization rules and the language-specific annotation scheme.
+item

4
website/usage/_processing-pipelines/_serialization.jade
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@ -12,9 +12,9 @@ include ../_spacy-101/_serialization
p
| For simplicity, let's assume you've
| #[+a("/usage/entity-recognition#setting") added custom entities] to
| #[+a("/usage/linguistic-features#setting-entities") added custom entities] to
| a #[code Doc], either manually, or by using a
| #[+a("/usage/rule-based-matching#on_match") match pattern]. You can
| #[+a("/usage/linguistic-features#on_match") match pattern]. You can
| save it locally by calling #[+api("doc#to_disk") #[code Doc.to_disk()]],
| and load it again via #[+api("doc#from_disk") #[code Doc.from_disk()]].
| This will overwrite the existing object and return it.

2
website/usage/_spacy-101/_lightning-tour.jade
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@ -153,7 +153,7 @@ p
displacy.serve(doc_ent, style='ent')
+infobox
| #[+label-inline API:] #[+api("displacy") #[code displacy]]
| #[+label-inline API:] #[+api("top-level#displacy") #[code displacy]]
| #[+label-inline Usage:] #[+a("/usage/visualizers") Visualizers]
+h(3, "lightning-tour-word-vectors") Get word vectors and similarity

22
website/usage/_v2/_features.jade
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@ -164,14 +164,17 @@ p
| The improved #[code spacy.load] makes loading models easier and more
| transparent. You can load a model by supplying its
| #[+a("/usage/models#usage") shortcut link], the name of an installed
| #[+a("/usage/saving-loading#generating") model package] or a path.
| The #[code Language] class to initialise will be determined based on the
| model's settings. For a blank language, you can import the class directly,
| e.g. #[code from spacy.lang.en import English].
| #[+a("/models") model package] or a path. The #[code Language] class to
| initialise will be determined based on the model's settings. For a blank l
| anguage, you can import the class directly, e.g.
| #[code.u-break from spacy.lang.en import English] or use
| #[+api("spacy#blank") #[code spacy.blank()]].
+infobox
| #[+label-inline API:] #[+api("spacy#load") #[code spacy.load]]
| #[+label-inline Usage:] #[+a("/usage/saving-loading") Saving and loading]
| #[+label-inline API:] #[+api("spacy#load") #[code spacy.load]],
| #[+api("language#to_disk") #[code Language.to_disk]]
| #[+label-inline Usage:] #[+a("/usage/models#usage") Models],
| #[+a("/usage/training#saving-loading") Saving and loading]
+h(3, "features-displacy") displaCy visualizer with Jupyter support
@ -190,7 +193,7 @@ p
| visualizations in your notebook.
+infobox
| #[+label-inline API:] #[+api("displacy") #[code displacy]]
| #[+label-inline API:] #[+api("top-level#displacy") #[code displacy]]
| #[+label-inline Usage:] #[+a("/usage/visualizers") Visualizing spaCy]
+h(3, "features-language") Improved language data and lazy loading
@ -222,7 +225,7 @@ p
p
| Patterns can now be added to the matcher by calling
| #[+api("matcher-add") #[code matcher.add()]] with a match ID, an optional
| #[+api("matcher#add") #[code matcher.add()]] with a match ID, an optional
| callback function to be invoked on each match, and one or more patterns.
| This allows you to write powerful, pattern-specific logic using only one
| matcher. For example, you might only want to merge some entity types,
@ -234,4 +237,5 @@ p
+infobox
| #[+label-inline API:] #[+api("matcher") #[code Matcher]],
| #[+api("phrasematcher") #[code PhraseMatcher]]
| #[+label-inline Usage:] #[+a("/usage/rule-based-matching") Rule-based matching]
| #[+label-inline Usage:]
| #[+a("/usage/linguistic-features#rule-based-matching") Rule-based matching]

4
website/usage/_v2/_migrating.jade
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@ -64,7 +64,7 @@ p
p
| If you've been using custom pipeline components, check out the new
| guide on #[+a("/usage/language-processing-pipelines") processing pipelines].
| guide on #[+a("/usage/processing-pipelines") processing pipelines].
| Pipeline components are now #[code (name, func)] tuples. Appending
| them to the pipeline still works – but the
| #[+api("language#add_pipe") #[code add_pipe]] method now makes this
@ -191,7 +191,7 @@ p
| matcher now also supports string keys, which saves you an extra import.
| If you've been using #[strong acceptor functions], you'll need to move
| this logic into the
| #[+a("/usage/rule-based-matching#on_match") #[code on_match] callbacks].
| #[+a("/usage/linguistic-features#on_match") #[code on_match] callbacks].
| The callback function is invoked on every match and will give you access to
| the doc, the index of the current match and all total matches. This lets
| you both accept or reject the match, and define the actions to be