explosion/spaCy
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Merge remote-tracking branch 'origin/develop' into feature/parser-history-model

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This commit is contained in:
Matthew Honnibal 2017-10-04 20:00:36 -05:00
commit bfabc333be
268 changed files with 9045 additions and 9472 deletions
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11
.buildkite/sdist.yml Normal file
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@ -0,0 +1,11 @@
steps:
-
command: "fab env clean make test sdist"
label: ":dizzy: :python:"
artifact_paths: "dist/*.tar.gz"
- wait
- trigger: "spacy-sdist-against-models"
label: ":dizzy: :hammer:"
build:
env:
SPACY_VERSION: "{$SPACY_VERSION}"

4
.gitignore vendored
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@ -1,14 +1,12 @@
# spaCy
spacy/data/
corpora/
models/
/models/
keys/
# Website
website/www/
website/_deploy.sh
website/package.json
website/announcement.jade
website/.gitignore
# Cython / C extensions

23
examples/training/train_textcat.py
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@ -1,3 +1,7 @@
'''Train a multi-label convolutional neural network text classifier,
using the spacy.pipeline.TextCategorizer component. The model is then added
to spacy.pipeline, and predictions are available at `doc.cats`.
'''
from __future__ import unicode_literals
import plac
import random
@ -12,6 +16,11 @@ from spacy.gold import GoldParse, minibatch
from spacy.util import compounding
from spacy.pipeline import TextCategorizer
# TODO: Remove this once we're not supporting models trained with thinc <6.9.0
import thinc.neural._classes.layernorm
thinc.neural._classes.layernorm.set_compat_six_eight(False)
def train_textcat(tokenizer, textcat,
train_texts, train_cats, dev_texts, dev_cats,
@ -24,14 +33,15 @@ def train_textcat(tokenizer, textcat,
train_docs = [tokenizer(text) for text in train_texts]
train_gold = [GoldParse(doc, cats=cats) for doc, cats in
zip(train_docs, train_cats)]
train_data = zip(train_docs, train_gold)
train_data = list(zip(train_docs, train_gold))
batch_sizes = compounding(4., 128., 1.001)
for i in range(n_iter):
losses = {}
train_data = tqdm.tqdm(train_data, leave=False) # Progress bar
for batch in minibatch(train_data, size=batch_sizes):
# Progress bar and minibatching
batches = minibatch(tqdm.tqdm(train_data, leave=False), size=batch_sizes)
for batch in batches:
docs, golds = zip(*batch)
textcat.update((docs, None), golds, sgd=optimizer, drop=0.2,
textcat.update(docs, golds, sgd=optimizer, drop=0.2,
losses=losses)
with textcat.model.use_params(optimizer.averages):
scores = evaluate(tokenizer, textcat, dev_texts, dev_cats)
@ -61,12 +71,13 @@ def evaluate(tokenizer, textcat, texts, cats):
return {'textcat_p': precis, 'textcat_r': recall, 'textcat_f': fscore}
def load_data():
def load_data(limit=0):
# Partition off part of the train data --- avoid running experiments
# against test.
train_data, _ = thinc.extra.datasets.imdb()
random.shuffle(train_data)
train_data = train_data[-limit:]
texts, labels = zip(*train_data)
cats = [(['POSITIVE'] if y else []) for y in labels]
@ -86,7 +97,7 @@ def main(model_loc=None):
textcat = TextCategorizer(tokenizer.vocab, labels=['POSITIVE'])
print("Load IMDB data")
(train_texts, train_cats), (dev_texts, dev_cats) = load_data()
(train_texts, train_cats), (dev_texts, dev_cats) = load_data(limit=1000)
print("Itn.\tLoss\tP\tR\tF")
progress = '{i:d} {loss:.3f} {textcat_p:.3f} {textcat_r:.3f} {textcat_f:.3f}'

23
spacy/_ml.py
View File

@ -631,6 +631,7 @@ def foreach(layer, drop_factor=1.0):
def build_text_classifier(nr_class, width=64, **cfg):
nr_vector = cfg.get('nr_vector', 5000)
pretrained_dims = cfg.get('pretrained_dims', 0)
with Model.define_operators({'>>': chain, '+': add, '|': concatenate,
'**': clone}):
if cfg.get('low_data'):
@ -638,7 +639,7 @@ def build_text_classifier(nr_class, width=64, **cfg):
SpacyVectors
>> flatten_add_lengths
>> with_getitem(0,
Affine(width, 300)
Affine(width, pretrained_dims)
)
>> ParametricAttention(width)
>> Pooling(sum_pool)
@ -665,18 +666,24 @@ def build_text_classifier(nr_class, width=64, **cfg):
)
)
if pretrained_dims:
static_vectors = (
SpacyVectors
>> with_flatten(Affine(width, 300))
>> with_flatten(Affine(width, pretrained_dims))
)
cnn_model = (
# TODO Make concatenate support lists
concatenate_lists(trained_vectors, static_vectors)
vectors = concatenate_lists(trained_vectors, static_vectors)
vectors_width = width*2
else:
vectors = trained_vectors
vectors_width = width
static_vectors = None
cnn_model = (
vectors
>> with_flatten(
LN(Maxout(width, width*2))
LN(Maxout(width, vectors_width))
>> Residual(
(ExtractWindow(nW=1) >> zero_init(Maxout(width, width*3)))
(ExtractWindow(nW=1) >> LN(Maxout(width, width*3)))
) ** 2, pad=2
)
>> flatten_add_lengths
@ -696,7 +703,7 @@ def build_text_classifier(nr_class, width=64, **cfg):
>> zero_init(Affine(nr_class, nr_class*2, drop_factor=0.0))
>> logistic
)
model.nO = nr_class
model.lsuv = False
return model

6
spacy/about.py
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@ -3,15 +3,15 @@
# https://github.com/pypa/warehouse/blob/master/warehouse/__about__.py
__title__ = 'spacy-nightly'
__version__ = '2.0.0a15'
__version__ = '2.0.0a16'
__summary__ = 'Industrial-strength Natural Language Processing (NLP) with Python and Cython'
__uri__ = 'https://spacy.io'
__author__ = 'Explosion AI'
__email__ = 'contact@explosion.ai'
__license__ = 'MIT'
__release__ = False
__release__ = True
__docs_models__ = 'https://spacy.io/docs/usage/models'
__docs_models__ = 'https://alpha.spacy.io/usage/models'
__download_url__ = 'https://github.com/explosion/spacy-models/releases/download'
__compatibility__ = 'https://raw.githubusercontent.com/explosion/spacy-models/master/compatibility.json'
__shortcuts__ = 'https://raw.githubusercontent.com/explosion/spacy-models/master/shortcuts.json'

41
spacy/cli/evaluate.py
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@ -33,16 +33,23 @@ numpy.random.seed(0)
data_path=("Location of JSON-formatted evaluation data", "positional", None, str),
gold_preproc=("Use gold preprocessing", "flag", "G", bool),
gpu_id=("Use GPU", "option", "g", int),
displacy_path=("Directory to output rendered parses as HTML", "option", "dp", str),
displacy_limit=("Limit of parses to render as HTML", "option", "dl", int)
)
def evaluate(cmd, model, data_path, gpu_id=-1, gold_preproc=False):
def evaluate(cmd, model, data_path, gpu_id=-1, gold_preproc=False,
displacy_path=None, displacy_limit=25):
"""
Train a model. Expects data in spaCy's JSON format.
Evaluate a model. To render a sample of parses in a HTML file, set an output
directory as the displacy_path argument.
"""
util.use_gpu(gpu_id)
util.set_env_log(False)
data_path = util.ensure_path(data_path)
displacy_path = util.ensure_path(displacy_path)
if not data_path.exists():
prints(data_path, title="Evaluation data not found", exits=1)
if displacy_path and not displacy_path.exists():
prints(displacy_path, title="Visualization output directory not found", exits=1)
corpus = GoldCorpus(data_path, data_path)
nlp = util.load_model(model)
dev_docs = list(corpus.dev_docs(nlp, gold_preproc=gold_preproc))
@ -50,17 +57,26 @@ def evaluate(cmd, model, data_path, gpu_id=-1, gold_preproc=False):
scorer = nlp.evaluate(dev_docs, verbose=False)
end = timer()
nwords = sum(len(doc_gold[0]) for doc_gold in dev_docs)
print('Time', end-begin, 'words', nwords, 'w.p.s', nwords/(end-begin))
print_results(scorer)
print_results(scorer, time=end - begin, words=nwords,
wps=nwords / (end - begin))
if displacy_path:
docs, golds = zip(*dev_docs)
render_deps = 'parser' in nlp.meta.get('pipeline', [])
render_ents = 'ner' in nlp.meta.get('pipeline', [])
render_parses(docs, displacy_path, model_name=model, limit=displacy_limit,
deps=render_deps, ents=render_ents)
prints(displacy_path, title="Generated %s parses as HTML" % displacy_limit)
def _render_parses(i, to_render):
to_render[0].user_data['title'] = "Batch %d" % i
with Path('/tmp/entities.html').open('w') as file_:
html = displacy.render(to_render[:5], style='ent', page=True)
def render_parses(docs, output_path, model_name='', limit=250, deps=True, ents=True):
docs[0].user_data['title'] = model_name
if ents:
with (output_path / 'entities.html').open('w') as file_:
html = displacy.render(docs[:limit], style='ent', page=True)
file_.write(html)
with Path('/tmp/parses.html').open('w') as file_:
html = displacy.render(to_render[:5], style='dep', page=True)
if deps:
with (output_path / 'parses.html').open('w') as file_:
html = displacy.render(docs[:limit], style='dep', page=True, options={'compact': True})
file_.write(html)
@ -88,8 +104,11 @@ def print_progress(itn, losses, dev_scores, wps=0.0):
print(tpl.format(itn, **scores))
def print_results(scorer):
def print_results(scorer, time, words, wps):
results = {
'Time': '%.2f s' % time,
'Words': words,
'Words/s': '%.0f' % wps,
'TOK': '%.2f' % scorer.token_acc,
'POS': '%.2f' % scorer.tags_acc,
'UAS': '%.2f' % scorer.uas,

14
spacy/tests/regression/test_issue1380.py Normal file
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@ -0,0 +1,14 @@
from __future__ import unicode_literals
import pytest
from ...language import Language
def test_issue1380_empty_string():
nlp = Language()
doc = nlp('')
assert len(doc) == 0
@pytest.mark.models('en')
def test_issue1380_en(EN):
doc = EN('')
assert len(doc) == 0

3
website/404.jade
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@ -8,4 +8,5 @@ include _includes/_mixins
| does not exist!
h2.c-landing__title.u-heading-3.u-padding-small
a(href="javascript:history.go(-1)") Click here to go back.
+button(false, true, "secondary-light")(href="javascript:history.go(-1)")
| Click here to go back

49
website/_data.json
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@ -3,24 +3,22 @@
"landing": true,
"logos": [
{
"quora": [ "https://www.quora.com", 150 ],
"chartbeat": [ "https://chartbeat.com", 200 ],
"duedil": [ "https://www.duedil.com", 150 ],
"stitchfix": [ "https://www.stitchfix.com", 190 ]
"airbnb": [ "https://www.airbnb.com", 150, 45],
"quora": [ "https://www.quora.com", 120, 34 ],
"retriever": [ "https://www.retriever.no", 150, 33 ],
"stitchfix": [ "https://www.stitchfix.com", 150, 18 ]
},
{
"wayblazer": [ "http://wayblazer.com", 200 ],
"indico": [ "https://indico.io", 150 ],
"chattermill": [ "https://chattermill.io", 175 ],
"turi": [ "https://turi.com", 150 ],
"kip": [ "http://kipthis.com", 70 ]
},
"chartbeat": [ "https://chartbeat.com", 180, 25 ],
"allenai": [ "https://allenai.org", 220, 37 ]
}
],
"features": [
{
"socrata": [ "https://www.socrata.com", 150 ],
"cytora": [ "http://www.cytora.com", 125 ],
"signaln": [ "http://signaln.com", 150 ],
"wonderflow": [ "http://www.wonderflow.co", 200 ],
"synapsify": [ "http://www.gosynapsify.com", 150 ]
"thoughtworks": ["https://www.thoughtworks.com/radar/tools", 150, 28],
"wapo": ["https://www.washingtonpost.com/news/wonk/wp/2016/05/18/googles-new-artificial-intelligence-cant-understand-these-sentences-can-you/", 100, 77],
"venturebeat": ["https://venturebeat.com/2017/01/27/4-ai-startups-that-analyze-customer-reviews/", 150, 19],
"microsoft": ["https://www.microsoft.com/developerblog/2016/09/13/training-a-classifier-for-relation-extraction-from-medical-literature/", 130, 28]
}
]
},
@ -34,7 +32,24 @@
"landing": true
},
"announcement" : {
"title": "Important Announcement"
"styleguide": {
"title": "Styleguide",
"sidebar": {
"Styleguide": { "": "styleguide" },
"Resources": {
"Website Source": "https://github.com/explosion/spacy/tree/master/website",
"Contributing Guide": "https://github.com/explosion/spaCy/blob/master/CONTRIBUTING.md"
}
},
"menu": {
"Introduction": "intro",
"Logo": "logo",
"Colors": "colors",
"Typography": "typography",
"Elements": "elements",
"Components": "components",
"Embeds": "embeds",
"Markup Reference": "markup"
}
}
}

80
website/_harp.json
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@ -11,12 +11,9 @@
"COMPANY": "Explosion AI",
"COMPANY_URL": "https://explosion.ai",
"DEMOS_URL": "https://demos.explosion.ai",
"MODELS_REPO": "explosion/spacy-models",
"SPACY_VERSION": "1.8",
"LATEST_NEWS": {
"url": "https://github.com/explosion/spaCy/releases/tag/v2.0.0-alpha",
"title": "Test spaCy v2.0.0 alpha!"
},
"SPACY_VERSION": "2.0",
"SOCIAL": {
"twitter": "spacy_io",
@ -27,25 +24,23 @@
},
"NAVIGATION": {
"Home": "/",
"Usage": "/docs/usage",
"Reference": "/docs/api",
"Demos": "/docs/usage/showcase",
"Blog": "https://explosion.ai/blog"
"Usage": "/usage",
"Models": "/models",
"API": "/api"
},
"FOOTER": {
"spaCy": {
"Usage": "/docs/usage",
"API Reference": "/docs/api",
"Tutorials": "/docs/usage/tutorials",
"Showcase": "/docs/usage/showcase"
"Usage": "/usage",
"Models": "/models",
"API Reference": "/api",
"Resources": "/usage/resources"
},
"Support": {
"Issue Tracker": "https://github.com/explosion/spaCy/issues",
"StackOverflow": "http://stackoverflow.com/questions/tagged/spacy",
"Reddit usergroup": "https://www.reddit.com/r/spacynlp/",
"Gitter chat": "https://gitter.im/explosion/spaCy"
"Reddit Usergroup": "https://www.reddit.com/r/spacynlp/",
"Gitter Chat": "https://gitter.im/explosion/spaCy"
},
"Connect": {
"Twitter": "https://twitter.com/spacy_io",
@ -74,21 +69,11 @@
{"id": "venv", "title": "virtualenv", "help": "Use a virtual environment and install spaCy into a user directory" },
{"id": "gpu", "title": "GPU", "help": "Run spaCy on GPU to make it faster. Requires an NVDIA graphics card with CUDA 2+. See section below for more info."}]
},
{ "id": "model", "title": "Models", "multiple": true, "options": [
{ "id": "en", "title": "English", "meta": "50MB" },
{ "id": "de", "title": "German", "meta": "645MB" },
{ "id": "fr", "title": "French", "meta": "1.33GB" },
{ "id": "es", "title": "Spanish", "meta": "377MB"}]
}
{ "id": "model", "title": "Models", "multiple": true }
],
"QUICKSTART_MODELS": [
{ "id": "lang", "title": "Language", "options": [
{ "id": "en", "title": "English", "checked": true },
{ "id": "de", "title": "German" },
{ "id": "fr", "title": "French" },
{ "id": "es", "title": "Spanish" }]
},
{ "id": "lang", "title": "Language"},
{ "id": "load", "title": "Loading style", "options": [
{ "id": "spacy", "title": "Use spacy.load()", "checked": true, "help": "Use spaCy's built-in loader to load the model by name." },
{ "id": "module", "title": "Import as module", "help": "Import the model explicitly as a Python module." }]
@ -98,50 +83,15 @@
}
],
"MODELS": {
"en": [
{ "id": "en_core_web_sm", "lang": "English", "feats": [1, 1, 1, 1], "size": "50 MB", "license": "CC BY-SA", "def": true },
{ "id": "en_core_web_md", "lang": "English", "feats": [1, 1, 1, 1], "size": "1 GB", "license": "CC BY-SA" },
{ "id": "en_depent_web_md", "lang": "English", "feats": [1, 1, 1, 0], "size": "328 MB", "license": "CC BY-SA" },
{ "id": "en_vectors_glove_md", "lang": "English", "feats": [1, 0, 0, 1], "size": "727 MB", "license": "CC BY-SA" }
],
"de": [
{ "id": "de_core_news_md", "lang": "German", "feats": [1, 1, 1, 1], "size": "645 MB", "license": "CC BY-SA" }
],
"fr": [
{ "id": "fr_depvec_web_lg", "lang": "French", "feats": [1, 1, 0, 1], "size": "1.33 GB", "license": "CC BY-NC" }
],
"es": [
{ "id": "es_core_web_md", "lang": "Spanish", "feats": [1, 1, 1, 1], "size": "377 MB", "license": "CC BY-SA"}
]
},
"EXAMPLE_SENTENCES": {
"en": "This is a sentence.",
"de": "Dies ist ein Satz.",
"fr": "C'est une phrase.",
"es": "Esto es una frase."
},
"ALPHA": true,
"V_CSS": "1.6",
"V_JS": "1.2",
"V_CSS": "2.0",
"V_JS": "2.0",
"DEFAULT_SYNTAX": "python",
"ANALYTICS": "UA-58931649-1",
"MAILCHIMP": {
"user": "spacy.us12",
"id": "83b0498b1e7fa3c91ce68c3f1",
"list": "89ad33e698"
},
"BADGES": {
"pipy": {
"badge": "https://img.shields.io/pypi/v/spacy.svg?style=flat-square",
"link": "https://pypi.python.org/pypi/spacy"
},
"conda": {
"badge": "https://anaconda.org/conda-forge/spacy/badges/version.svg",
"link": "https://anaconda.org/conda-forge/spacy"
}
}
}
}

12
website/_includes/_footer.jade
View File

@ -1,8 +1,6 @@
//- 💫 INCLUDES > FOOTER
include _mixins
footer.o-footer.u-text.u-border-dotted
footer.o-footer.u-text
+grid.o-content
each group, label in FOOTER
+grid-col("quarter")
@ -13,18 +11,18 @@ footer.o-footer.u-text.u-border-dotted
li
+a(url)=item
if SECTION != "docs"
if SECTION == "index"
+grid-col("quarter")
include _newsletter
if SECTION == "docs"
if SECTION != "index"
.o-content.o-block.u-border-dotted
include _newsletter
.o-inline-list.u-text-center.u-text-tiny.u-color-subtle
span &copy; 2016-#{new Date().getFullYear()} #[+a(COMPANY_URL, true)=COMPANY]
+a(COMPANY_URL, true)
+svg("graphics", "explosion", 45).o-icon.u-color-theme.u-grayscale
+a(COMPANY_URL, true)(aria-label="Explosion AI")
+icon("explosion", 45).o-icon.u-color-theme.u-grayscale
+a(COMPANY_URL + "/legal", true) Legal / Imprint

70
website/_includes/_functions.jade
View File

@ -1,35 +1,71 @@
//- 💫 INCLUDES > FUNCTIONS
//- More descriptive variables for current.path and current.source
//- Descriptive variables, available in the global scope
- CURRENT = current.source
- SECTION = current.path[0]
- SUBSECTION = current.path[1]
- LANGUAGES = public.models._data.LANGUAGES
- MODELS = public.models._data.MODELS
- CURRENT_MODELS = MODELS[current.source] || []
- MODEL_COUNT = Object.keys(MODELS).map(m => Object.keys(MODELS[m]).length).reduce((a, b) => a + b)
- MODEL_LANG_COUNT = Object.keys(MODELS).length
- LANG_COUNT = Object.keys(LANGUAGES).length
- MODEL_META = public.models._data.MODEL_META
- MODEL_LICENSES = public.models._data.MODEL_LICENSES
- MODEL_ACCURACY = public.models._data.MODEL_ACCURACY
- EXAMPLE_SENTENCES = public.models._data.EXAMPLE_SENTENCES
- IS_PAGE = (SECTION != "index") && !landing
- IS_MODELS = (SECTION == "models" && LANGUAGES[current.source])
- HAS_MODELS = IS_MODELS && CURRENT_MODELS.length
//- Add prefixes to items of an array (for modifier CSS classes)
array - [array] list of class names or options, e.g. ["foot"]
prefix - [string] prefix to add to each class, e.g. "c-table__row"
RETURNS - [array] list of modified class names
- function prefixArgs(array, prefix) {
- return array.map(function(arg) {
- return prefix + '--' + arg;
- }).join(' ');
- return array.map(arg => prefix + '--' + arg).join(' ');
- }
//- Convert API paths (semi-temporary fix for renamed sections)
path - [string] link path supplied to +api mixin
RETURNS - [string] new link path to correct location
- function convertAPIPath(path) {
- if (path.startsWith('spacy#') || path.startsWith('displacy#') || path.startsWith('util#')) {
- var comps = path.split('#');
- return "top-level#" + comps[0] + '.' + comps[1];
- }
- else if (path.startsWith('cli#')) {
- return "top-level#" + path.split('#')[1];
- }
- return path;
- }
//- Get model components from ID. Components can then be looked up in LANGUAGES
and MODEL_META respectively, to get their human-readable form.
id - [string] model ID, e.g. "en_core_web_sm"
RETURNS - [object] object keyed by components lang, type, genre and size
- function getModelComponents(id) {
- var comps = id.split('_');
- return {'lang': comps[0], 'type': comps[1], 'genre': comps[2], 'size': comps[3]}
- }
//- Generate GitHub links
repo - [string] name of repo owned by explosion
filepath - [string] logical path to file relative to repository root
branch - [string] optional branch, defaults to "master"
RETURNS - [string] the correct link to the file on GitHub
- function gh(repo, filepath, branch) {
- var branch = ALPHA ? 'develop' : branch
- return 'https://github.com/' + SOCIAL.github + '/' + repo + (filepath ? '/blob/' + (branch || 'master') + '/' + filepath : '' );
- }
//- Get social images
- function getSocialImg() {
- var base = SITE_URL + '/assets/img/social/preview_'
- var image = ALPHA ? 'alpha' : 'default'
- if (preview) image = preview
- else if (SECTION == 'docs' && !ALPHA) image = 'docs'
- return base + image + '.jpg'
- return 'https://github.com/' + SOCIAL.github + '/' + (repo || '') + (filepath ? '/blob/' + (branch || 'master') + '/' + filepath : '' );
- }

124
website/_includes/_mixins-base.jade
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@ -1,5 +1,13 @@
//- 💫 MIXINS > BASE
//- Section
id - [string] anchor assigned to section (used for breadcrumb navigation)
mixin section(id)
section.o-section(id="section-" + id data-section=id)
block
//- Aside wrapper
label - [string] aside label
@ -11,34 +19,26 @@ mixin aside-wrapper(label)
block
//- Date
input - [string] date in the format YYYY-MM-DD
mixin date(input)
- var date = new Date(input)
- var months = [ 'January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December' ]
time(datetime=JSON.parse(JSON.stringify(date)))&attributes(attributes)=months[date.getMonth()] + ' ' + date.getDate() + ', ' + date.getFullYear()
//- SVG from map
file - [string] SVG file name in /assets/img/
//- SVG from map (uses embedded SVG sprite)
name - [string] SVG symbol id
width - [integer] width in px
height - [integer] height in px (default: same as width)
mixin svg(file, name, width, height)
mixin svg(name, width, height)
svg(aria-hidden="true" viewBox="0 0 #{width} #{height || width}" width=width height=(height || width))&attributes(attributes)
use(xlink:href="/assets/img/#{file}.svg##{name}")
use(xlink:href="#svg_#{name}")
//- Icon
name - [string] icon name, should be SVG symbol ID
size - [integer] icon width and height (default: 20)
name - [string] icon name (will be used as symbol id: #svg_{name})
width - [integer] icon width (default: 20)
height - [integer] icon height (defaults to width)
mixin icon(name, size)
- var size = size || 20
+svg("icons", name, size).o-icon(style="min-width: #{size}px")&attributes(attributes)
mixin icon(name, width, height)
- var width = width || 20
- var height = height || width
+svg(name, width, height).o-icon(style="min-width: #{width}px")&attributes(attributes)
//- Pro/Con/Neutral icon
@ -46,8 +46,8 @@ mixin icon(name, size)
size - [integer] icon size (optional)
mixin procon(icon, size)
- colors = { pro: "green", con: "red", neutral: "yellow" }
+icon(icon, size)(class="u-color-#{colors[icon] || 'subtle'}" aria-label=icon)&attributes(attributes)
- colors = { pro: "green", con: "red", neutral: "subtle" }
+icon("circle", size || 16)(class="u-color-#{colors[icon] || 'subtle'}" aria-label=icon)&attributes(attributes)
//- Headlines Helper Mixin
@ -80,8 +80,7 @@ mixin headline(level)
mixin permalink(id)
if id
a.u-permalink(id=id href="##{id}")
+icon("anchor").u-permalink__icon
a.u-permalink(href="##{id}")
block
else
@ -109,7 +108,7 @@ mixin quickstart(groups, headline, description, hide_results)
.c-quickstart__fields
for option in group.options
input.c-quickstart__input(class="c-quickstart__input--" + (group.input_style ? group.input_style : group.multiple ? "check" : "radio") type=group.multiple ? "checkbox" : "radio" name=group.id id="qs-#{option.id}" value=option.id checked=option.checked)
label.c-quickstart__label(for="qs-#{option.id}")!=option.title
label.c-quickstart__label.u-text-tiny(for="qs-#{option.id}")!=option.title
if option.meta
| #[span.c-quickstart__label__meta (#{option.meta})]
if option.help
@ -122,12 +121,10 @@ mixin quickstart(groups, headline, description, hide_results)
code.c-code-block__content.c-quickstart__code(data-qs-results="")
block
.c-quickstart__info.u-text-tiny.o-block.u-text-right
| Like this widget? Check out #[+a("https://github.com/ines/quickstart").u-link quickstart.js]!
//- Quickstart code item
data [object] - Rendering conditions (keyed by option group ID, value: option)
data - [object] Rendering conditions (keyed by option group ID, value: option)
style - [string] modifier ID for line style
mixin qs(data, style)
- args = {}
@ -148,6 +145,13 @@ mixin terminal(label)
+code.x-terminal__code
block
//- Chart.js
id - [string] chart ID, will be assigned as #chart_{id}
mixin chart(id)
figure.o-block&attributes(attributes)
canvas(id="chart_#{id}" width="800" height="400" style="max-width: 100%")
//- Gitter chat button and widget
button - [string] text shown on button
@ -156,26 +160,24 @@ mixin terminal(label)
mixin gitter(button, label)
aside.js-gitter.c-chat.is-collapsed(data-title=(label || button))
button.js-gitter-button.c-chat__button.u-text-small
+icon("chat").o-icon--inline
button.js-gitter-button.c-chat__button.u-text-tag
+icon("chat", 16).o-icon--inline
!=button
//- Badge
name - [string] "pipy" or "conda"
image - [string] path to badge image
url - [string] badge link
mixin badge(name)
- site = BADGES[name]
if site
+a(site.link).u-padding-small
img(src=site.badge alt="{name} version" height="20")
mixin badge(image, url)
+a(url).u-padding-small.u-hide-link&attributes(attributes)
img.o-badge(src=image alt=url height="20")
//- Logo
//- spaCy logo
mixin logo()
+svg("graphics", "spacy", 675, 215).o-logo&attributes(attributes)
+svg("spacy", 675, 215).o-logo&attributes(attributes)
//- Landing
@ -186,18 +188,56 @@ mixin landing-header()
.c-landing__content
block
mixin landing-banner(headline, label)
.c-landing__banner.u-padding.o-block.u-color-light
+grid.c-landing__banner__content.o-no-block
+grid-col("third")
h3.u-heading.u-heading-1
if label
div
span.u-text-label.u-text-label--light=label
!=headline
mixin landing-badge(url, graphic, alt, size)
+a(url)(aria-label=alt title=alt).c-landing__badge
+svg("graphics", graphic, size || 225)
+grid-col("two-thirds").c-landing__banner__text
block
mixin landing-logos(title, logos)
.o-content.u-text-center&attributes(attributes)
h3.u-heading.u-text-label.u-color-dark=title
each row, i in logos
- var is_last = i == logos.length - 1
+grid("center").o-inline-list.o-no-block(class=is_last ? "o-no-block" : null)
each details, name in row
+a(details[0]).u-padding-medium
+icon(name, details[1], details[2])
if is_last
block
//- Under construction (temporary)
Marks sections that still need to be completed for the v2.0 release.
mixin under-construction()
+infobox("🚧 Under construction")
+infobox("Under construction", "🚧")
| This section is still being written and will be updated for the v2.0
| release. Is there anything that you think should definitely mentioned or
| explained here? Any examples you'd like to see? #[strong Let us know]
| on the #[+a(gh("spacy") + "/issues/1105") v2.0 alpha thread] on GitHub!
//- Alpha infobox (temporary)
Added in the templates to notify user that they're visiting the alpha site.
mixin alpha-info()
+infobox("You are viewing the spaCy v2.0.0 alpha docs", "⚠️")
strong This page is part of the alpha documentation for spaCy v2.0.
| It does not reflect the state of the latest stable release.
| Because v2.0 is still under development, the implementation
| may differ from the intended state described here. See the
| #[+a(gh("spaCy") + "/releases/tag/v2.0.0-alpha") release notes]
| for details on how to install and test the new version. To
| read the official docs for spaCy v1.x,
| #[+a("https://spacy.io/docs") go here].

231
website/_includes/_mixins.jade
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@ -8,11 +8,15 @@ include _mixins-base
level - [integer] headline level, corresponds to h1, h2, h3 etc.
id - [string] unique identifier, creates permalink (optional)
mixin h(level, id)
+headline(level).u-heading&attributes(attributes)
mixin h(level, id, source)
+headline(level).u-heading(id=id)&attributes(attributes)
+permalink(id)
block
if source
+button(gh("spacy", source), false, "secondary", "small").u-nowrap.u-float-right
span Source #[+icon("code", 14).o-icon--inline]
//- External links
url - [string] link href
@ -38,21 +42,23 @@ mixin src(url)
//- API link (with added tag and automatically generated path)
path - [string] path to API docs page relative to /docs/api/
path - [string] path to API docs page relative to /api/
mixin api(path)
+a("/docs/api/" + path, true)(target="_self").u-no-border.u-inline-block.u-nowrap
- path = convertAPIPath(path)
+a("/api/" + path, true)(target="_self").u-no-border.u-inline-block.u-nowrap
block
| #[+icon("book", 18).o-icon--inline.u-color-theme]
| #[+icon("book", 16).o-icon--inline.u-color-theme]
//- Help icon with tooltip
tooltip - [string] Tooltip text
icon_size - [integer] Optional size of help icon in px.
mixin help(tooltip)
mixin help(tooltip, icon_size)
span(data-tooltip=tooltip)&attributes(attributes)
+icon("help", 16).i-icon--inline
+icon("help", icon_size || 16).o-icon--inline
//- Aside for text
@ -68,24 +74,43 @@ mixin aside(label)
label - [string] aside title (optional or false for no label)
language - [string] language for syntax highlighting (default: "python")
supports basic relevant languages available for PrismJS
prompt - [string] prompt displayed before first line, e.g. "$"
mixin aside-code(label, language)
mixin aside-code(label, language, prompt)
+aside-wrapper(label)
+code(false, language).o-no-block
+code(false, language, prompt).o-no-block
block
//- Infobox
label - [string] infobox title (optional or false for no title)
emoji - [string] optional emoji displayed before the title, necessary as
argument to be able to wrap it for spacing
mixin infobox(label)
mixin infobox(label, emoji)
aside.o-box.o-block.u-text-small
if label
h3.u-text-label.u-color-theme=label
h3.u-heading.u-text-label.u-color-theme
if emoji
span.o-emoji=emoji
| #{label}
block
//- Logos displayed in the top corner of some infoboxes
logos - [array] List of icon ID, width, height and link.
mixin infobox-logos(...logos)
.o-box__logos.u-text-right.u-float-right
for logo in logos
if logo[3]
| #[+a(logo[3]).u-inline-block.u-hide-link.u-padding-small #[+icon(logo[0], logo[1], logo[2]).u-color-dark]]
else
| #[+icon(logo[0], logo[1], logo[2]).u-color-dark]
//- Link button
url - [string] link href
trusted - [boolean] if not set / false, rel="noopener nofollow" is added
@ -94,7 +119,7 @@ mixin infobox(label)
see assets/css/_components/_buttons.sass
mixin button(url, trusted, ...style)
- external = url.includes("http")
- external = url && url.includes("http")
a.c-button.u-text-label(href=url class=prefixArgs(style, "c-button") role="button" target=external ? "_blank" : null rel=external && !trusted ? "noopener nofollow" : null)&attributes(attributes)
block
@ -103,31 +128,33 @@ mixin button(url, trusted, ...style)
label - [string] aside title (optional or false for no label)
language - [string] language for syntax highlighting (default: "python")
supports basic relevant languages available for PrismJS
prompt - [string] prompt or icon to display next to code block, (mostly used for old/new)
prompt - [string] prompt displayed before first line, e.g. "$"
height - [integer] optional height to clip code block to
icon - [string] icon displayed next to code block (e.g. "accept" for new code)
wrap - [boolean] wrap text and disable horizontal scrolling
mixin code(label, language, prompt, height)
mixin code(label, language, prompt, height, icon, wrap)
pre.c-code-block.o-block(class="lang-#{(language || DEFAULT_SYNTAX)}" class=icon ? "c-code-block--has-icon" : null style=height ? "height: #{height}px" : null)&attributes(attributes)
if label
h4.u-text-label.u-text-label--dark=label
- var icon = (prompt == 'accept' || prompt == 'reject')
- var icon = icon || (prompt == 'accept' || prompt == 'reject')
if icon
- var classes = {'accept': 'u-color-green', 'reject': 'u-color-red'}
.c-code-block__icon(class=classes[icon] || null class=classes[icon] ? "c-code-block__icon--border" : null)
+icon(icon, 18)
code.c-code-block__content(data-prompt=icon ? null : prompt)
code.c-code-block__content(class=wrap ? "u-wrap" : null data-prompt=icon ? null : prompt)
block
//- Code blocks to display old/new versions
mixin code-old()
+code(false, false, "reject").o-block-small
+code(false, false, false, false, "reject").o-block-small
block
mixin code-new()
+code(false, false, "accept").o-block-small
+code(false, false, false, false, "accept").o-block-small
block
@ -138,12 +165,33 @@ mixin code-new()
mixin codepen(slug, height, default_tab)
figure.o-block(style="min-height: #{height}px")&attributes(attributes)
.codepen(data-height=height data-theme-id="26467" data-slug-hash=slug data-default-tab=(default_tab || "result") data-embed-version="2" data-user=SOCIAL.codepen)
.codepen(data-height=height data-theme-id="31335" data-slug-hash=slug data-default-tab=(default_tab || "result") data-embed-version="2" data-user=SOCIAL.codepen)
+a("https://codepen.io/" + SOCIAL.codepen + "/" + slug) View on CodePen
script(async src="https://assets.codepen.io/assets/embed/ei.js")
//- GitHub embed
repo - [string] repository owned by explosion organization
file - [string] logical path to file, relative to repository root
alt_file - [string] alternative file path used in footer and link button
height - [integer] height of code preview in px
mixin github(repo, file, alt_file, height)
- var branch = ALPHA ? "develop" : "master"
- var height = height || 250
figure.o-block
pre.c-code-block.o-block-small(class="lang-#{(language || DEFAULT_SYNTAX)}" style="height: #{height}px; min-height: #{height}px")
code.c-code-block__content(data-gh-embed="#{repo}/#{branch}/#{file}")
footer.o-grid.u-text
.o-block-small.u-flex-full #[+icon("github")] #[code=repo + '/' + (alt_file || file)]
div
+button(gh(repo, alt_file || file), false, "primary", "small") View on GitHub
//- Images / figures
url - [string] url or path to image
width - [integer] image width in px, for better rendering (default: 500)
@ -168,10 +216,26 @@ mixin image-caption()
block
//- Label
//- Graphic or illustration with button
original - [string] Path to original image
mixin graphic(original)
+image
block
if original
.u-text-right
+button(original, false, "secondary", "small") View large graphic
//- Labels
mixin label()
.u-text-label.u-color-subtle&attributes(attributes)
.u-text-label.u-color-dark&attributes(attributes)
block
mixin label-inline()
strong.u-text-label.u-color-dark&attributes(attributes)
block
@ -188,7 +252,9 @@ mixin tag()
mixin tag-model(...capabs)
- var intro = "To use this functionality, spaCy needs a model to be installed"
- var ext = capabs.length ? " that supports the following capabilities: " + capabs.join(', ') : ""
+tag Requires model
span.u-nowrap
+tag Needs model
+help(intro + ext + ".").u-color-theme
@ -219,13 +285,7 @@ mixin list(type, start)
//- List item (only used within +list)
mixin item(procon)
if procon
li&attributes(attributes)
+procon(procon).c-list__icon
block
else
mixin item()
li.c-list__item&attributes(attributes)
block
@ -237,9 +297,9 @@ mixin table(head)
table.c-table.o-block&attributes(attributes)
if head
+row
+row("head")
each column in head
th.c-table__head-cell.u-text-label=column
+head-cell=column
block
@ -251,10 +311,11 @@ mixin row(...style)
block
//- Footer table row (only ued within +table)
mixin footrow()
tr.c-table__row.c-table__row--foot&attributes(attributes)
//- Header table cell (only used within +row)
mixin head-cell()
th.c-table__head-cell.u-text-label&attributes(attributes)
block
@ -285,70 +346,57 @@ mixin grid-col(width)
//- Card (only used within +grid)
title - [string] card title
details - [object] url, image, author, description, tags etc.
(see /docs/usage/_data.json)
mixin card(title, details)
+grid-col("half").o-card.u-text&attributes(attributes)
if details.image
+a(details.url).o-block-small
img(src=details.image alt=title width="300" role="presentation")
url - [string] link for card
author - [string] optional author, displayed as byline at the bottom
icon - [string] optional ID of icon displayed with card
width - [string] optional width of grid column, defaults to "half"
mixin card(title, url, author, icon, width)
+grid-col(width || "half").o-box.o-grid.o-grid--space.u-text&attributes(attributes)
+a(url)
h4.u-heading.u-text-label
if icon
+icon(icon, 25).u-float-right
if title
+a(details.url)
+h(3)=title
span.u-color-dark=title
.o-block-small.u-text-small
block
if author
.u-color-subtle.u-text-tiny by #{author}
if details.author
.u-text-small.u-color-subtle by #{details.author}
if details.description || details.tags
ul
if details.description
li=details.description
if details.tags
li
each tag in details.tags
span.u-text-tag #{tag}
| &nbsp;
//- Table of contents, to be used with +item mixins for links
col - [string] width of column (see +grid-col)
mixin table-of-contents(col)
+grid-col(col || "half")
+infobox
+label.o-block-small Table of contents
+list("numbers").u-text-small.o-no-block
block
//- Simpler card list item (only used within +list)
title - [string] card title
details - [object] url, image, author, description, tags etc.
(see /docs/usage/_data.json)
//- Bibliography
id - [string] ID of bibliography component, for anchor links. Can be used if
there's more than one bibliography on one page.
mixin card-item(title, details)
+item&attributes(attributes)
+a(details.url)=title
if details.description
br
span=details.description
if details.author
br
span.u-text-small.u-color-subtle by #{details.author}
mixin bibliography(id)
section(id=id || "bibliography")
+infobox
+label.o-block-small Bibliography
+list("numbers").u-text-small.o-no-block
block
//- Table row for models table
//- Footnote
id - [string / integer] ID of footnote.
bib_id - [string] ID of bibliography component, defaults to "bibliography".
tooltip - [string] optional text displayed as tooltip
mixin model-row(name, lang, procon, size, license, default_model, divider)
- var licenses = { "CC BY-SA": "https://creativecommons.org/licenses/by-sa/3.0/", "CC BY-NC": "https://creativecommons.org/licenses/by-nc/3.0/" }
+row(divider ? "divider": null)
+cell #[code=name]
if default_model
| #[span.u-color-theme(title="default model") #[+icon("star", 16)]]
+cell=lang
each icon in procon
+cell.u-text-center #[+procon(icon ? "pro" : "con")]
+cell.u-text-right=size
+cell
if license in licenses
+a(licenses[license])=license
mixin fn(id, bib_id, tooltip)
sup.u-padding-small(id="bib" + id data-tooltip=tooltip)
span.u-text-tag
+a("#" + (bib_id || "bibliography")).u-hide-link #{id}
//- Table rows for annotation specs
@ -383,14 +431,3 @@ mixin annotation-row(annots, style)
else
+cell=cell
block
//- Table of contents, to be used with +item mixins for links
col - [string] width of column (see +grid-col)
mixin table-of-contents(col)
+grid-col(col || "half")
+infobox
+label.o-block-small Table of contents
+list("numbers").u-text-small.o-no-block
block

20
website/_includes/_navigation.jade
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@ -1,19 +1,15 @@
//- 💫 INCLUDES > TOP NAVIGATION
include _mixins
nav.c-nav.u-text.js-nav(class=landing ? "c-nav--theme" : null)
a(href='/') #[+logo]
if SUBSECTION != "index"
.u-text-label.u-padding-small.u-hidden-xs=SUBSECTION
a(href="/" aria-label=SITENAME) #[+logo]
ul.c-nav__menu
- var NAV = ALPHA ? { "Usage": "/docs/usage", "Reference": "/docs/api" } : NAVIGATION
each url, item in NAV
li.c-nav__menu__item(class=(url == "/") ? "u-hidden-xs" : null)
- var current_url = '/' + current.path[0]
each url, item in NAVIGATION
li.c-nav__menu__item(class=(current_url == url) ? "is-active" : null)
+a(url)=item
li.c-nav__menu__item
+a(gh("spaCy"))(aria-label="GitHub").u-hidden-xs #[+icon("github", 20)]
li.c-nav__menu__item.u-hidden-xs
+a(gh("spaCy"))(aria-label="GitHub") #[+icon("github", 20)]
progress.c-progress.js-progress(value="0" max="1")

9
website/_includes/_newsletter.jade
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@ -1,6 +1,6 @@
//- 💫 INCLUDES > NEWSLETTER
ul.o-block
ul.o-block-small
li.u-text-label.u-color-subtle Stay in the loop!
li Receive updates about new releases, tutorials and more.
@ -10,7 +10,6 @@ form.o-grid#mc-embedded-subscribe-form(action="//#{MAILCHIMP.user}.list-manage.c
div(style="position: absolute; left: -5000px;" aria-hidden="true")
input(type="text" name="b_#{MAILCHIMP.id}_#{MAILCHIMP.list}" tabindex="-1" value="")
.o-grid-col.u-border.u-padding-small
input#mce-EMAIL.u-text(type="email" name="EMAIL" placeholder="Your email")
button#mc-embedded-subscribe.u-text-label.u-color-theme(type="submit" name="subscribe") Sign up
.o-grid-col.o-grid.o-grid--nowrap.o-field.u-padding-small
input#mce-EMAIL.o-field__input.u-text(type="email" name="EMAIL" placeholder="Your email" aria-label="Your email")
button#mc-embedded-subscribe.o-field__button.u-text-label.u-color-theme.u-nowrap(type="submit" name="subscribe") Sign up

55
website/_includes/_page-docs.jade
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@ -1,47 +1,56 @@
//- 💫 INCLUDES > DOCS PAGE TEMPLATE
- sidebar_content = (SUBSECTION != "index") ? public.docs[SUBSECTION]._data.sidebar : public.docs._data.sidebar || FOOTER
- sidebar_content = (public[SECTION] ? public[SECTION]._data.sidebar : public._data[SECTION] ? public._data[SECTION].sidebar : false) || FOOTER
include _sidebar
main.o-main.o-main--sidebar.o-main--aside
article.o-content
+grid.o-no-block
+grid-col(source ? "two-thirds" : "full")
+h(1)=title
+h(1).u-heading--title=title.replace("'", "’")
if tag
+tag=tag
if tag_new
+tag-new(tag_new)
if teaser
.u-heading__teaser.u-text-small.u-color-dark=teaser
else if IS_MODELS
.u-heading__teaser.u-text-small.u-color-dark
| Available statistical models for
| #[code=current.source] (#{LANGUAGES[current.source]}).
if source
+grid-col("third").u-text-right
.o-inline-list
+button(gh("spacy", source), false, "secondary").u-text-tag Source #[+icon("code", 14)]
.o-block.u-text-right
+button(gh("spacy", source), false, "secondary", "small").u-nowrap
| Source #[+icon("code", 14)]
//-if ALPHA
//- +alpha-info
if ALPHA
+infobox("⚠️ You are viewing the spaCy v2.0.0 alpha docs")
strong This page is part of the alpha documentation for spaCy v2.0.
| It does not reflect the state of the latest stable release.
| Because v2.0 is still under development, the implementation
| may differ from the intended state described here. See the
| #[+a(gh("spaCy") + "/releases/tag/v2.0.0-alpha") release notes]
| for details on how to install and test the new version. To
| read the official docs for spaCy v1.x,
| #[+a("https://spacy.io/docs") go here].
if IS_MODELS
include _page_models
else
!=yield
+grid.o-content.u-text
+grid-col("half")
if next && public.docs[SUBSECTION]._data[next]
- data = public.docs[SUBSECTION]._data[next]
if !IS_MODELS
.o-inline-list
span #[strong.u-text-label Read next:] #[+a(next).u-link=data.title]
+button(gh("spacy", "website/" + current.path.join('/') + ".jade"), false, "secondary", "small")
| #[span.o-icon Suggest edits] #[+icon("code", 14)]
+grid-col("half").u-text-right
.o-inline-list
+button(gh("spacy", "website/" + current.path.join('/') + ".jade"), false, "secondary").u-text-tag Suggest edits #[+icon("code", 14)]
if next && public[SECTION]._data[next]
- data = public[SECTION]._data[next]
+grid("vcenter")
+a(next).u-text-small.u-flex-full
h4.u-text-label.u-color-dark Read next
| #{data.title}
+a(next).c-icon-button.c-icon-button--right(aria-hidden="true")
+icon("arrow-right", 24)
+gitter("spaCy chat")

77
website/_includes/_page_models.jade Normal file
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@ -0,0 +1,77 @@
//- 💫 INCLUDES > MODELS PAGE TEMPLATE
for id in CURRENT_MODELS
+section(id)
+grid("vcenter").o-no-block(id=id)
+grid-col("two-thirds")
+h(2)
+a("#" + id).u-permalink=id
+grid-col("third").u-text-right
.u-color-subtle.u-text-tiny
+button(gh("spacy-models") + "/releases", true, "secondary", "small")(data-tpl=id data-tpl-key="download")
| Release details
.u-padding-small Latest: #[code(data-tpl=id data-tpl-key="version") n/a]
+aside-code("Installation", "bash", "$").
spacy download #{id}
- var comps = getModelComponents(id)
p(data-tpl=id data-tpl-key="description")
div(data-tpl=id data-tpl-key="error" style="display: none")
+infobox
| Unable to load model details from GitHub. To find out more
| about this model, see the overview of the
| #[+a(gh("spacy-models") + "/releases") latest model releases].
+table(data-tpl=id data-tpl-key="table")
+row
+cell #[+label Language]
+cell #[+tag=comps.lang] #{LANGUAGES[comps.lang]}
for comp, label in {"Type": comps.type, "Genre": comps.genre}
+row
+cell #[+label=label]
+cell #[+tag=comp] #{MODEL_META[comp]}
+row
+cell #[+label Size]
+cell #[+tag=comps.size] #[span(data-tpl=id data-tpl-key="size") #[em n/a]]
each label in ["Pipeline", "Sources", "Author", "License"]
- var field = label.toLowerCase()
+row
+cell.u-nowrap
+label=label
if MODEL_META[field]
| #[+help(MODEL_META[field]).u-color-subtle]
+cell
span(data-tpl=id data-tpl-key=field) #[em n/a]
+row(data-tpl=id data-tpl-key="compat-wrapper" style="display: none")
+cell
+label Compat #[+help("Latest compatible model version for your spaCy installation").u-color-subtle]
+cell
.o-field.u-float-left
select.o-field__select.u-text-small(data-tpl=id data-tpl-key="compat")
.o-empty(data-tpl=id data-tpl-key="compat-versions") &nbsp;
section(data-tpl=id data-tpl-key="accuracy-wrapper" style="display: none")
+grid.o-no-block
+grid-col("third")
+h(4) Accuracy
+table.o-block-small
for label, field in MODEL_ACCURACY
+row(style="display: none")
+cell.u-nowrap
+label=label
if MODEL_META[field]
| #[+help(MODEL_META[field]).u-color-subtle]
+cell.u-text-right(data-tpl=id data-tpl-key=field)
| n/a
+grid-col("two-thirds")
+h(4) Comparison
+chart(id).u-padding-small
p.u-text-small.u-color-dark(data-tpl=id data-tpl-key="notes")

53
website/_includes/_scripts.jade
View File

@ -1,27 +1,46 @@
//- 💫 INCLUDES > SCRIPTS
script(src="/assets/js/main.js?v#{V_JS}")
script(src="/assets/js/prism.js")
if quickstart
script(src="/assets/js/quickstart.min.js")
if SECTION == "docs"
if quickstart
script(src="/assets/js/quickstart.js")
script var qs = new Quickstart("#qs")
if IS_PAGE
script(src="/assets/js/in-view.min.js")
script.
((window.gitter = {}).chat = {}).options = {
useStyles: false,
activationElement: '.js-gitter-button',
targetElement: '.js-gitter',
room: '!{SOCIAL.gitter}'
};
script(src="https://sidecar.gitter.im/dist/sidecar.v1.js" async defer)
if HAS_MODELS
script(src="/assets/js/chart.min.js")
if environment == "deploy"
script
script(async src="https://www.google-analytics.com/analytics.js")
script(src="/assets/js/prism.min.js")
script(src="/assets/js/main.js?v#{V_JS}")
script
| new ProgressBar('.js-progress');
if changelog
| new Changelog('!{SOCIAL.github}', 'spacy');
if quickstart
| new Quickstart("#qs");
if IS_PAGE
| new SectionHighlighter('data-section', 'data-nav');
| new GitHubEmbed('!{SOCIAL.github}', 'data-gh-embed');
| ((window.gitter = {}).chat = {}).options = {
| useStyles: false,
| activationElement: '.js-gitter-button',
| targetElement: '.js-gitter',
| room: '!{SOCIAL.gitter}'
| };
if HAS_MODELS
| new ModelLoader('!{MODELS_REPO}', !{JSON.stringify(CURRENT_MODELS)}, !{JSON.stringify(MODEL_LICENSES)}, !{JSON.stringify(MODEL_ACCURACY)});
if environment == "deploy"
| window.ga=window.ga||function(){
| (ga.q=ga.q||[]).push(arguments)}; ga.l=+new Date;
| ga('create', '#{ANALYTICS}', 'auto'); ga('send', 'pageview');
script(async src="https://www.google-analytics.com/analytics.js")
if IS_PAGE
script(src="https://sidecar.gitter.im/dist/sidecar.v1.js" async defer)

24
website/_includes/_sidebar.jade
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@ -1,13 +1,23 @@
//- 💫 INCLUDES > SIDEBAR
include _mixins
menu.c-sidebar.js-sidebar.u-text
if sidebar_content
each items, menu in sidebar_content
ul.c-sidebar__section.o-block
li.u-text-label.u-color-subtle=menu
each items, sectiontitle in sidebar_content
ul.c-sidebar__section.o-block-small
li.u-text-label.u-color-dark=sectiontitle
each url, item in items
li(class=(CURRENT == url || (CURRENT == "index" && url == "./")) ? "is-active" : null)
+a(url)=item
- var is_current = CURRENT == url || (CURRENT == "index" && url == "./")
li.c-sidebar__item
+a(url)(class=is_current ? "is-active" : null)=item
if is_current
if IS_MODELS && CURRENT_MODELS.length
- menu = Object.assign({}, ...CURRENT_MODELS.map(id => ({ [id]: id })))
if menu
ul.c-sidebar__crumb.u-hidden-sm
- var counter = 0
for id, title in menu
- counter++
li.c-sidebar__crumb__item(data-nav=id class=(counter == 1) ? "is-active" : null)
+a("#section-" + id)=title

157
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25
website/_layout.jade
View File

@ -2,11 +2,16 @@
include _includes/_mixins
- title = IS_MODELS ? LANGUAGES[current.source] || title : title
- social_title = (SECTION == "index") ? SITENAME + " - " + SLOGAN : title + " - " + SITENAME
- social_img = SITE_URL + "/assets/img/social/preview_" + (preview || ALPHA ? "alpha" : "default") + ".jpg"
doctype html
html(lang="en")
title
if SECTION == "docs" && SUBSECTION && SUBSECTION != "index"
| #{title} | #{SITENAME} #{SUBSECTION == "api" ? "API" : "Usage"} Documentation
if SECTION == "api" || SECTION == "usage" || SECTION == "models"
- var title_section = (SECTION == "api") ? "API" : SECTION.charAt(0).toUpperCase() + SECTION.slice(1)
| #{title} | #{SITENAME} #{title_section} Documentation
else if SECTION != "index"
| #{title} | #{SITENAME}
@ -22,32 +27,30 @@ html(lang="en")
meta(property="og:type" content="website")
meta(property="og:site_name" content=sitename)
meta(property="og:url" content="#{SITE_URL}/#{current.path.join('/')}")
meta(property="og:title" content="#{title} - spaCy")
meta(property="og:title" content=social_title)
meta(property="og:description" content=description)
meta(property="og:image" content=getSocialImg())
meta(property="og:image" content=social_img)
meta(name="twitter:card" content="summary_large_image")
meta(name="twitter:site" content="@" + SOCIAL.twitter)
meta(name="twitter:title" content="#{title} - spaCy")
meta(name="twitter:title" content=social_title)
meta(name="twitter:description" content=description)
meta(name="twitter:image" content=getSocialImg())
meta(name="twitter:image" content=social_img)
link(rel="shortcut icon" href="/assets/img/favicon.ico")
link(rel="icon" type="image/x-icon" href="/assets/img/favicon.ico")
if ALPHA && SECTION == "docs"
if SECTION == "api"
link(href="/assets/css/style_green.css?v#{V_CSS}" rel="stylesheet")
else if SUBSECTION == "usage"
link(href="/assets/css/style_red.css?v#{V_CSS}" rel="stylesheet")
else
link(href="/assets/css/style.css?v#{V_CSS}" rel="stylesheet")
body
include _includes/_svg
include _includes/_navigation
if SECTION == "docs"
if !landing
include _includes/_page-docs
else

43
website/api/_annotation/_biluo.jade Normal file
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@ -0,0 +1,43 @@
//- 💫 DOCS > API > ANNOTATION > BILUO
+table([ "Tag", "Description" ])
+row
+cell #[code #[span.u-color-theme B] EGIN]
+cell The first token of a multi-token entity.
+row
+cell #[code #[span.u-color-theme I] N]
+cell An inner token of a multi-token entity.
+row
+cell #[code #[span.u-color-theme L] AST]
+cell The final token of a multi-token entity.
+row
+cell #[code #[span.u-color-theme U] NIT]
+cell A single-token entity.
+row
+cell #[code #[span.u-color-theme O] UT]
+cell A non-entity token.
+aside("Why BILUO, not IOB?")
| There are several coding schemes for encoding entity annotations as
| token tags. These coding schemes are equally expressive, but not
| necessarily equally learnable.
| #[+a("http://www.aclweb.org/anthology/W09-1119") Ratinov and Roth]
| showed that the minimal #[strong Begin], #[strong In], #[strong Out]
| scheme was more difficult to learn than the #[strong BILUO] scheme that
| we use, which explicitly marks boundary tokens.
p
| spaCy translates the character offsets into this scheme, in order to
| decide the cost of each action given the current state of the entity
| recogniser. The costs are then used to calculate the gradient of the
| loss, to train the model. The exact algorithm is a pastiche of
| well-known methods, and is not currently described in any single
| publication. The model is a greedy transition-based parser guided by a
| linear model whose weights are learned using the averaged perceptron
| loss, via the #[+a("http://www.aclweb.org/anthology/C12-1059") dynamic oracle]
| imitation learning strategy. The transition system is equivalent to the
| BILOU tagging scheme.

0
website/docs/api/_annotation/_dep-labels.jade → website/api/_annotation/_dep-labels.jade
View File

0
website/docs/api/_annotation/_named-entities.jade → website/api/_annotation/_named-entities.jade
View File

0
website/docs/api/_annotation/_pos-tags.jade → website/api/_annotation/_pos-tags.jade
View File

115
website/api/_architecture/_cython.jade Normal file
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@ -0,0 +1,115 @@
//- 💫 DOCS > API > ARCHITECTURE > CYTHON
+aside("What's Cython?")
| #[+a("http://cython.org/") Cython] is a language for writing
| C extensions for Python. Most Python code is also valid Cython, but
| you can add type declarations to get efficient memory-managed code
| just like C or C++.
p
| spaCy's core data structures are implemented as
| #[+a("http://cython.org/") Cython] #[code cdef] classes. Memory is
| managed through the #[+a(gh("cymem")) #[code cymem]]
| #[code cymem.Pool] class, which allows you
| to allocate memory which will be freed when the #[code Pool] object
| is garbage collected. This means you usually don't have to worry
| about freeing memory. You just have to decide which Python object
| owns the memory, and make it own the #[code Pool]. When that object
| goes out of scope, the memory will be freed. You do have to take
| care that no pointers outlive the object that owns them — but this
| is generally quite easy.
p
| All Cython modules should have the #[code # cython: infer_types=True]
| compiler directive at the top of the file. This makes the code much
| cleaner, as it avoids the need for many type declarations. If
| possible, you should prefer to declare your functions #[code nogil],
| even if you don't especially care about multi-threading. The reason
| is that #[code nogil] functions help the Cython compiler reason about
| your code quite a lot — you're telling the compiler that no Python
| dynamics are possible. This lets many errors be raised, and ensures
| your function will run at C speed.
p
| Cython gives you many choices of sequences: you could have a Python
| list, a numpy array, a memory view, a C++ vector, or a pointer.
| Pointers are preferred, because they are fastest, have the most
| explicit semantics, and let the compiler check your code more
| strictly. C++ vectors are also great — but you should only use them
| internally in functions. It's less friendly to accept a vector as an
| argument, because that asks the user to do much more work. Here's
| how to get a pointer from a numpy array, memory view or vector:
+code.
cdef void get_pointers(np.ndarray[int, mode='c'] numpy_array, vector[int] cpp_vector, int[::1] memory_view) nogil:
pointer1 = &lt;int*&gt;numpy_array.data
pointer2 = cpp_vector.data()
pointer3 = &memory_view[0]
p
| Both C arrays and C++ vectors reassure the compiler that no Python
| operations are possible on your variable. This is a big advantage:
| it lets the Cython compiler raise many more errors for you.
p
| When getting a pointer from a numpy array or memoryview, take care
| that the data is actually stored in C-contiguous order — otherwise
| you'll get a pointer to nonsense. The type-declarations in the code
| above should generate runtime errors if buffers with incorrect
| memory layouts are passed in. To iterate over the array, the
| following style is preferred:
+code.
cdef int c_total(const int* int_array, int length) nogil:
total = 0
for item in int_array[:length]:
total += item
return total
p
| If this is confusing, consider that the compiler couldn't deal with
| #[code for item in int_array:] — there's no length attached to a raw
| pointer, so how could we figure out where to stop? The length is
| provided in the slice notation as a solution to this. Note that we
| don't have to declare the type of #[code item] in the code above —
| the compiler can easily infer it. This gives us tidy code that looks
| quite like Python, but is exactly as fast as C — because we've made
| sure the compilation to C is trivial.
p
| Your functions cannot be declared #[code nogil] if they need to
| create Python objects or call Python functions. This is perfectly
| okay — you shouldn't torture your code just to get #[code nogil]
| functions. However, if your function isn't #[code nogil], you should
| compile your module with #[code cython -a --cplus my_module.pyx] and
| open the resulting #[code my_module.html] file in a browser. This
| will let you see how Cython is compiling your code. Calls into the
| Python run-time will be in bright yellow. This lets you easily see
| whether Cython is able to correctly type your code, or whether there
| are unexpected problems.
p
| Working in Cython is very rewarding once you're over the initial
| learning curve. As with C and C++, the first way you write something
| in Cython will often be the performance-optimal approach. In
| contrast, Python optimisation generally requires a lot of
| experimentation. Is it faster to have an #[code if item in my_dict]
| check, or to use #[code .get()]? What about
| #[code try]/#[code except]? Does this numpy operation create a copy?
| There's no way to guess the answers to these questions, and you'll
| usually be dissatisfied with your results — so there's no way to
| know when to stop this process. In the worst case, you'll make a
| mess that invites the next reader to try their luck too. This is
| like one of those
| #[+a("http://www.wemjournal.org/article/S1080-6032%2809%2970088-2/abstract") volcanic gas-traps],
| where the rescuers keep passing out from low oxygen, causing
| another rescuer to follow — only to succumb themselves. In short,
| just say no to optimizing your Python. If it's not fast enough the
| first time, just switch to Cython.
+infobox("Resources")
+list.o-no-block
+item #[+a("http://docs.cython.org/en/latest/") Official Cython documentation] (cython.org)
+item #[+a("https://explosion.ai/blog/writing-c-in-cython", true) Writing C in Cython] (explosion.ai)
+item #[+a("https://explosion.ai/blog/multithreading-with-cython") Multi-threading spaCy’s parser and named entity recogniser] (explosion.ai)

141
website/api/_architecture/_nn-model.jade Normal file
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@ -0,0 +1,141 @@
//- 💫 DOCS > API > ARCHITECTURE > NN MODEL ARCHITECTURE
p
| The parsing model is a blend of recent results. The two recent
| inspirations have been the work of Eli Klipperwasser and Yoav Goldberg at
| Bar Ilan#[+fn(1)], and the SyntaxNet team from Google. The foundation of
| the parser is still based on the work of Joakim Nivre#[+fn(2)], who
| introduced the transition-based framework#[+fn(3)], the arc-eager
| transition system, and the imitation learning objective. The model is
| implemented using #[+a(gh("thinc")) Thinc], spaCy's machine learning
| library. We first predict context-sensitive vectors for each word in the
| input:
+code.
(embed_lower | embed_prefix | embed_suffix | embed_shape)
&gt;&gt; Maxout(token_width)
&gt;&gt; convolution ** 4
p
| This convolutional layer is shared between the tagger, parser and NER,
| and will also be shared by the future neural lemmatizer. Because the
| parser shares these layers with the tagger, the parser does not require
| tag features. I got this trick from David Weiss's "Stack Combination"
| paper#[+fn(4)].
p
| To boost the representation, the tagger actually predicts a "super tag"
| with POS, morphology and dependency label#[+fn(5)]. The tagger predicts
| these supertags by adding a softmax layer onto the convolutional layer –
| so, we're teaching the convolutional layer to give us a representation
| that's one affine transform from this informative lexical information.
| This is obviously good for the parser (which backprops to the
| convolutions too). The parser model makes a state vector by concatenating
| the vector representations for its context tokens. The current context
| tokens:
+table
+row
+cell #[code S0], #[code S1], #[code S2]
+cell Top three words on the stack.
+row
+cell #[code B0], #[code B1]
+cell First two words of the buffer.
+row
+cell.u-nowrap
| #[code S0L1], #[code S1L1], #[code S2L1], #[code B0L1],
| #[code B1L1]#[br]
| #[code S0L2], #[code S1L2], #[code S2L2], #[code B0L2],
| #[code B1L2]
+cell
| Leftmost and second leftmost children of #[code S0], #[code S1],
| #[code S2], #[code B0] and #[code B1].
+row
+cell.u-nowrap
| #[code S0R1], #[code S1R1], #[code S2R1], #[code B0R1],
| #[code B1R1]#[br]
| #[code S0R2], #[code S1R2], #[code S2R2], #[code B0R2],
| #[code B1R2]
+cell
| Rightmost and second rightmost children of #[code S0], #[code S1],
| #[code S2], #[code B0] and #[code B1].
p
| This makes the state vector quite long: #[code 13*T], where #[code T] is
| the token vector width (128 is working well). Fortunately, there's a way
| to structure the computation to save some expense (and make it more
| GPU-friendly).
p
| The parser typically visits #[code 2*N] states for a sentence of length
| #[code N] (although it may visit more, if it back-tracks with a
| non-monotonic transition#[+fn(4)]). A naive implementation would require
| #[code 2*N (B, 13*T) @ (13*T, H)] matrix multiplications for a batch of
| size #[code B]. We can instead perform one #[code (B*N, T) @ (T, 13*H)]
| multiplication, to pre-compute the hidden weights for each positional
| feature with respect to the words in the batch. (Note that our token
| vectors come from the CNN — so we can't play this trick over the
| vocabulary. That's how Stanford's NN parser#[+fn(3)] works — and why its
| model is so big.)
p
| This pre-computation strategy allows a nice compromise between
| GPU-friendliness and implementation simplicity. The CNN and the wide
| lower layer are computed on the GPU, and then the precomputed hidden
| weights are moved to the CPU, before we start the transition-based
| parsing process. This makes a lot of things much easier. We don't have to
| worry about variable-length batch sizes, and we don't have to implement
| the dynamic oracle in CUDA to train.
p
| Currently the parser's loss function is multilabel log loss#[+fn(6)], as
| the dynamic oracle allows multiple states to be 0 cost. This is defined
| as follows, where #[code gZ] is the sum of the scores assigned to gold
| classes:
+code.
(exp(score) / Z) - (exp(score) / gZ)
+bibliography
+item
| #[+a("https://www.semanticscholar.org/paper/Simple-and-Accurate-Dependency-Parsing-Using-Bidir-Kiperwasser-Goldberg/3cf31ecb2724b5088783d7c96a5fc0d5604cbf41") Simple and Accurate Dependency Parsing Using Bidirectional LSTM Feature Representations]
br
| Eliyahu Kiperwasser, Yoav Goldberg. (2016)
+item
| #[+a("https://www.semanticscholar.org/paper/A-Dynamic-Oracle-for-Arc-Eager-Dependency-Parsing-Goldberg-Nivre/22697256ec19ecc3e14fcfc63624a44cf9c22df4") A Dynamic Oracle for Arc-Eager Dependency Parsing]
br
| Yoav Goldberg, Joakim Nivre (2012)
+item
| #[+a("https://explosion.ai/blog/parsing-english-in-python") Parsing English in 500 Lines of Python]
br
| Matthew Honnibal (2013)
+item
| #[+a("https://www.semanticscholar.org/paper/Stack-propagation-Improved-Representation-Learning-Zhang-Weiss/0c133f79b23e8c680891d2e49a66f0e3d37f1466") Stack-propagation: Improved Representation Learning for Syntax]
br
| Yuan Zhang, David Weiss (2016)
+item
| #[+a("https://www.semanticscholar.org/paper/Deep-multi-task-learning-with-low-level-tasks-supe-S%C3%B8gaard-Goldberg/03ad06583c9721855ccd82c3d969a01360218d86") Deep multi-task learning with low level tasks supervised at lower layers]
br
| Anders Søgaard, Yoav Goldberg (2016)
+item
| #[+a("https://www.semanticscholar.org/paper/An-Improved-Non-monotonic-Transition-System-for-De-Honnibal-Johnson/4094cee47ade13b77b5ab4d2e6cb9dd2b8a2917c") An Improved Non-monotonic Transition System for Dependency Parsing]
br
| Matthew Honnibal, Mark Johnson (2015)
+item
| #[+a("http://cs.stanford.edu/people/danqi/papers/emnlp2014.pdf") A Fast and Accurate Dependency Parser using Neural Networks]
br
| Danqi Cheng, Christopher D. Manning (2014)
+item
| #[+a("https://www.semanticscholar.org/paper/Parsing-the-Wall-Street-Journal-using-a-Lexical-Fu-Riezler-King/0ad07862a91cd59b7eb5de38267e47725a62b8b2") Parsing the Wall Street Journal using a Lexical-Functional Grammar and Discriminative Estimation Techniques]
br
| Stefan Riezler et al. (2002)

127
website/docs/api/_data.json → website/api/_data.json
View File

@ -1,29 +1,32 @@
{
"sidebar": {
"Introduction": {
"Facts & Figures": "./",
"Languages": "language-models",
"Annotation Specs": "annotation"
"Overview": {
"Architecture": "./",
"Annotation Specs": "annotation",
"Functions": "top-level"
},
"Top-level": {
"spacy": "spacy",
"displacy": "displacy",
"Utility Functions": "util",
"Command line": "cli"
},
"Classes": {
"Containers": {
"Doc": "doc",
"Token": "token",
"Span": "span",
"Lexeme": "lexeme"
},
"Pipeline": {
"Language": "language",
"Tokenizer": "tokenizer",
"Pipe": "pipe",
"Tensorizer": "tensorizer",
"Tagger": "tagger",
"DependencyParser": "dependencyparser",
"EntityRecognizer": "entityrecognizer",
"TextCategorizer": "textcategorizer",
"Tokenizer": "tokenizer",
"Lemmatizer": "lemmatizer",
"Matcher": "matcher",
"Lexeme": "lexeme",
"PhraseMatcher": "phrasematcher"
},
"Other": {
"Vocab": "vocab",
"StringStore": "stringstore",
"Vectors": "vectors",
@ -34,52 +37,37 @@
},
"index": {
"title": "Facts & Figures",
"next": "language-models"
"title": "Architecture",
"next": "annotation",
"menu": {
"Basics": "basics",
"Neural Network Model": "nn-model",
"Cython Conventions": "cython"
}
},
"language-models": {
"title": "Languages",
"next": "philosophy"
},
"philosophy": {
"title": "Philosophy"
},
"spacy": {
"title": "spaCy top-level functions",
"source": "spacy/__init__.py",
"next": "displacy"
},
"displacy": {
"title": "displaCy",
"tag": "module",
"source": "spacy/displacy",
"next": "util"
},
"util": {
"title": "Utility Functions",
"source": "spacy/util.py",
"next": "cli"
},
"cli": {
"title": "Command Line Interface",
"source": "spacy/cli"
"top-level": {
"title": "Top-level Functions",
"menu": {
"spacy": "spacy",
"displacy": "displacy",
"Utility Functions": "util",
"Compatibility": "compat",
"Command Line": "cli"
}
},
"language": {
"title": "Language",
"tag": "class",
"teaser": "A text-processing pipeline.",
"source": "spacy/language.py"
},
"doc": {
"title": "Doc",
"tag": "class",
"teaser": "A container for accessing linguistic annotations.",
"source": "spacy/tokens/doc.pyx"
},
@ -103,6 +91,7 @@
"vocab": {
"title": "Vocab",
"teaser": "A storage class for vocabulary and other data shared across a language.",
"tag": "class",
"source": "spacy/vocab.pyx"
},
@ -115,10 +104,27 @@
"matcher": {
"title": "Matcher",
"teaser": "Match sequences of tokens, based on pattern rules.",
"tag": "class",
"source": "spacy/matcher.pyx"
},
"phrasematcher": {
"title": "PhraseMatcher",
"teaser": "Match sequences of tokens, based on documents.",
"tag": "class",
"tag_new": 2,
"source": "spacy/matcher.pyx"
},
"pipe": {
"title": "Pipe",
"teaser": "Abstract base class defining the API for pipeline components.",
"tag": "class",
"tag_new": 2,
"source": "spacy/pipeline.pyx"
},
"dependenyparser": {
"title": "DependencyParser",
"tag": "class",
@ -127,18 +133,22 @@
"entityrecognizer": {
"title": "EntityRecognizer",
"teaser": "Annotate named entities on documents.",
"tag": "class",
"source": "spacy/pipeline.pyx"
},
"textcategorizer": {
"title": "TextCategorizer",
"teaser": "Add text categorization models to spaCy pipelines.",
"tag": "class",
"tag_new": 2,
"source": "spacy/pipeline.pyx"
},
"dependencyparser": {
"title": "DependencyParser",
"teaser": "Annotate syntactic dependencies on documents.",
"tag": "class",
"source": "spacy/pipeline.pyx"
},
@ -149,15 +159,23 @@
"source": "spacy/tokenizer.pyx"
},
"lemmatizer": {
"title": "Lemmatizer",
"tag": "class"
},
"tagger": {
"title": "Tagger",
"teaser": "Annotate part-of-speech tags on documents.",
"tag": "class",
"source": "spacy/pipeline.pyx"
},
"tensorizer": {
"title": "Tensorizer",
"teaser": "Add a tensor with position-sensitive meaning representations to a document.",
"tag": "class",
"tag_new": 2,
"source": "spacy/pipeline.pyx"
},
@ -169,23 +187,38 @@
"goldcorpus": {
"title": "GoldCorpus",
"teaser": "An annotated corpus, using the JSON file format.",
"tag": "class",
"tag_new": 2,
"source": "spacy/gold.pyx"
},
"binder": {
"title": "Binder",
"tag": "class",
"tag_new": 2,
"source": "spacy/tokens/binder.pyx"
},
"vectors": {
"title": "Vectors",
"teaser": "Store, save and load word vectors.",
"tag": "class",
"tag_new": 2,
"source": "spacy/vectors.pyx"
},
"annotation": {
"title": "Annotation Specifications"
"title": "Annotation Specifications",
"teaser": "Schemes used for labels, tags and training data.",
"menu": {
"Tokenization": "tokenization",
"Sentence Boundaries": "sbd",
"POS Tagging": "pos-tagging",
"Lemmatization": "lemmatization",
"Dependencies": "dependency-parsing",
"Named Entities": "named-entities",
"Training Data": "training"
}
}
}

175
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@ -1,26 +1,17 @@
//- 💫 DOCS > USAGE > COMMAND LINE INTERFACE
include ../../_includes/_mixins
//- 💫 DOCS > API > TOP-LEVEL > COMMAND LINE INTERFACE
p
| As of v1.7.0, spaCy comes with new command line helpers to download and
| link models and show useful debugging information. For a list of available
| commands, type #[code spacy --help].
+infobox("⚠️ Deprecation note")
| As of spaCy 2.0, the #[code model] command to initialise a model data
| directory is deprecated. The command was only necessary because previous
| versions of spaCy expected a model directory to already be set up. This
| has since been changed, so you can use the #[+api("cli#train") #[code train]]
| command straight away.
+h(2, "download") Download
+h(3, "download") Download
p
| Download #[+a("/docs/usage/models") models] for spaCy. The downloader finds the
| Download #[+a("/usage/models") models] for spaCy. The downloader finds the
| best-matching compatible version, uses pip to download the model as a
| package and automatically creates a
| #[+a("/docs/usage/models#usage") shortcut link] to load the model by name.
| #[+a("/usage/models#usage") shortcut link] to load the model by name.
| Direct downloads don't perform any compatibility checks and require the
| model name to be specified with its version (e.g., #[code en_core_web_sm-1.2.0]).
@ -49,15 +40,15 @@ p
| detailed messages in case things go wrong. It's #[strong not recommended]
| to use this command as part of an automated process. If you know which
| model your project needs, you should consider a
| #[+a("/docs/usage/models#download-pip") direct download via pip], or
| #[+a("/usage/models#download-pip") direct download via pip], or
| uploading the model to a local PyPi installation and fetching it straight
| from there. This will also allow you to add it as a versioned package
| dependency to your project.
+h(2, "link") Link
+h(3, "link") Link
p
| Create a #[+a("/docs/usage/models#usage") shortcut link] for a model,
| Create a #[+a("/usage/models#usage") shortcut link] for a model,
| either a Python package or a local directory. This will let you load
| models from any location using a custom name via
| #[+api("spacy#load") #[code spacy.load()]].
@ -95,7 +86,7 @@ p
+cell flag
+cell Show help message and available arguments.
+h(2, "info") Info
+h(3, "info") Info
p
| Print information about your spaCy installation, models and local setup,
@ -122,15 +113,15 @@ p
+cell flag
+cell Show help message and available arguments.
+h(2, "convert") Convert
+h(3, "convert") Convert
p
| Convert files into spaCy's #[+a("/docs/api/annotation#json-input") JSON format]
| Convert files into spaCy's #[+a("/api/annotation#json-input") JSON format]
| for use with the #[code train] command and other experiment management
| functions. The right converter is chosen based on the file extension of
| the input file. Currently only supports #[code .conllu].
+code(false, "bash", "$").
+code(false, "bash", "$", false, false, true).
spacy convert [input_file] [output_dir] [--n-sents] [--morphology]
+table(["Argument", "Type", "Description"])
@ -159,14 +150,18 @@ p
+cell flag
+cell Show help message and available arguments.
+h(2, "train") Train
+h(3, "train") Train
p
| Train a model. Expects data in spaCy's
| #[+a("/docs/api/annotation#json-input") JSON format].
| #[+a("/api/annotation#json-input") JSON format]. On each epoch, a model
| will be saved out to the directory. Accuracy scores and model details
| will be added to a #[+a("/usage/training#models-generating") #[code meta.json]]
| to allow packaging the model using the
| #[+api("cli#package") #[code package]] command.
+code(false, "bash", "$").
spacy train [lang] [output_dir] [train_data] [dev_data] [--n-iter] [--n-sents] [--use-gpu] [--no-tagger] [--no-parser] [--no-entities]
+code(false, "bash", "$", false, false, true).
spacy train [lang] [output_dir] [train_data] [dev_data] [--n-iter] [--n-sents] [--use-gpu] [--meta-path] [--vectors] [--no-tagger] [--no-parser] [--no-entities] [--gold-preproc]
+table(["Argument", "Type", "Description"])
+row
@ -204,6 +199,27 @@ p
+cell option
+cell Use GPU.
+row
+cell #[code --vectors], #[code -v]
+cell option
+cell Model to load vectors from.
+row
+cell #[code --meta-path], #[code -m]
+cell option
+cell
| #[+tag-new(2)] Optional path to model
| #[+a("/usage/training#models-generating") #[code meta.json]].
| All relevant properties like #[code lang], #[code pipeline] and
| #[code spacy_version] will be overwritten.
+row
+cell #[code --version], #[code -V]
+cell option
+cell
| Model version. Will be written out to the model's
| #[code meta.json] after training.
+row
+cell #[code --no-tagger], #[code -T]
+cell flag
@ -219,12 +235,18 @@ p
+cell flag
+cell Don't train NER.
+row
+cell #[code --gold-preproc], #[code -G]
+cell flag
+cell Use gold preprocessing.
+row
+cell #[code --help], #[code -h]
+cell flag
+cell Show help message and available arguments.
+h(3, "train-hyperparams") Environment variables for hyperparameters
+h(4, "train-hyperparams") Environment variables for hyperparameters
+tag-new(2)
p
| spaCy lets you set hyperparameters for training via environment variables.
@ -236,98 +258,149 @@ p
+code(false, "bash").
parser_hidden_depth=2 parser_maxout_pieces=1 train-parser
+under-construction
+table(["Name", "Description", "Default"])
+row
+cell #[code dropout_from]
+cell
+cell Initial dropout rate.
+cell #[code 0.2]
+row
+cell #[code dropout_to]
+cell
+cell Final dropout rate.
+cell #[code 0.2]
+row
+cell #[code dropout_decay]
+cell
+cell Rate of dropout change.
+cell #[code 0.0]
+row
+cell #[code batch_from]
+cell
+cell Initial batch size.
+cell #[code 1]
+row
+cell #[code batch_to]
+cell
+cell Final batch size.
+cell #[code 64]
+row
+cell #[code batch_compound]
+cell
+cell Rate of batch size acceleration.
+cell #[code 1.001]
+row
+cell #[code token_vector_width]
+cell
+cell Width of embedding tables and convolutional layers.
+cell #[code 128]
+row
+cell #[code embed_size]
+cell
+cell Number of rows in embedding tables.
+cell #[code 7500]
+row
+cell #[code parser_maxout_pieces]
+cell
+cell Number of pieces in the parser's and NER's first maxout layer.
+cell #[code 2]
+row
+cell #[code parser_hidden_depth]
+cell
+cell Number of hidden layers in the parser and NER.
+cell #[code 1]
+row
+cell #[code hidden_width]
+cell
+cell Size of the parser's and NER's hidden layers.
+cell #[code 128]
+row
+cell #[code learn_rate]
+cell
+cell Learning rate.
+cell #[code 0.001]
+row
+cell #[code optimizer_B1]
+cell
+cell Momentum for the Adam solver.
+cell #[code 0.9]
+row
+cell #[code optimizer_B2]
+cell
+cell Adagrad-momentum for the Adam solver.
+cell #[code 0.999]
+row
+cell #[code optimizer_eps]
+cell
+cell Epsylon value for the Adam solver.
+cell #[code 1e-08]
+row
+cell #[code L2_penalty]
+cell
+cell L2 regularisation penalty.
+cell #[code 1e-06]
+row
+cell #[code grad_norm_clip]
+cell
+cell Gradient L2 norm constraint.
+cell #[code 1.0]
+h(2, "package") Package
+h(3, "evaluate") Evaluate
+tag-new(2)
p
| Generate a #[+a("/docs/usage/saving-loading#generating") model Python package]
| Evaluate a model's accuracy and speed on JSON-formatted annotated data.
| Will print the results and optionally export
| #[+a("/usage/visualizers") displaCy visualizations] of a sample set of
| parses to #[code .html] files. Visualizations for the dependency parse
| and NER will be exported as separate files if the respective component
| is present in the model's pipeline.
+code(false, "bash", "$", false, false, true).
spacy evaluate [model] [data_path] [--displacy-path] [--displacy-limit] [--gpu-id] [--gold-preproc]
+table(["Argument", "Type", "Description"])
+row
+cell #[code model]
+cell positional
+cell
| Model to evaluate. Can be a package or shortcut link name, or a
| path to a model data directory.
+row
+cell #[code data_path]
+cell positional
+cell Location of JSON-formatted evaluation data.
+row
+cell #[code --displacy-path], #[code -dp]
+cell option
+cell
| Directory to output rendered parses as HTML. If not set, no
| visualizations will be generated.
+row
+cell #[code --displacy-limit], #[code -dl]
+cell option
+cell
| Number of parses to generate per file. Defaults to #[code 25].
| Keep in mind that a significantly higher number might cause the
| #[code .html] files to render slowly.
+row
+cell #[code --gpu-id], #[code -g]
+cell option
+cell GPU to use, if any. Defaults to #[code -1] for CPU.
+row
+cell #[code --gold-preproc], #[code -G]
+cell flag
+cell Use gold preprocessing.
+h(3, "package") Package
p
| Generate a #[+a("/usage/training#models-generating") model Python package]
| from an existing model data directory. All data files are copied over.
| If the path to a meta.json is supplied, or a meta.json is found in the
| input directory, this file is used. Otherwise, the data can be entered
@ -336,8 +409,8 @@ p
| sure you're always using the latest versions. This means you need to be
| connected to the internet to use this command.
+code(false, "bash", "$").
spacy package [input_dir] [output_dir] [--meta] [--force]
+code(false, "bash", "$", false, false, true).
spacy package [input_dir] [output_dir] [--meta-path] [--create-meta] [--force]
+table(["Argument", "Type", "Description"])
+row
@ -353,14 +426,14 @@ p
+row
+cell #[code --meta-path], #[code -m]
+cell option
+cell Path to meta.json file (optional).
+cell #[+tag-new(2)] Path to meta.json file (optional).
+row
+cell #[code --create-meta], #[code -c]
+cell flag
+cell
| Create a meta.json file on the command line, even if one already
| exists in the directory.
| #[+tag-new(2)] Create a meta.json file on the command line, even
| if one already exists in the directory.
+row
+cell #[code --force], #[code -f]

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@ -0,0 +1,91 @@
//- 💫 DOCS > API > TOP-LEVEL > COMPATIBILITY
p
| All Python code is written in an
| #[strong intersection of Python 2 and Python 3]. This is easy in Cython,
| but somewhat ugly in Python. Logic that deals with Python or platform
| compatibility only lives in #[code spacy.compat]. To distinguish them from
| the builtin functions, replacement functions are suffixed with an
| undersocre, e.e #[code unicode_]. For specific checks, spaCy uses the
| #[code six] and #[code ftfy] packages.
+aside-code("Example").
from spacy.compat import unicode_, json_dumps
compatible_unicode = unicode_('hello world')
compatible_json = json_dumps({'key': 'value'})
+table(["Name", "Python 2", "Python 3"])
+row
+cell #[code compat.bytes_]
+cell #[code str]
+cell #[code bytes]
+row
+cell #[code compat.unicode_]
+cell #[code unicode]
+cell #[code str]
+row
+cell #[code compat.basestring_]
+cell #[code basestring]
+cell #[code str]
+row
+cell #[code compat.input_]
+cell #[code raw_input]
+cell #[code input]
+row
+cell #[code compat.json_dumps]
+cell #[code ujson.dumps] with #[code .decode('utf8')]
+cell #[code ujson.dumps]
+row
+cell #[code compat.path2str]
+cell #[code str(path)] with #[code .decode('utf8')]
+cell #[code str(path)]
+h(3, "is_config") compat.is_config
+tag function
p
| Check if a specific configuration of Python version and operating system
| matches the user's setup. Mostly used to display targeted error messages.
+aside-code("Example").
from spacy.compat import is_config
if is_config(python2=True, windows=True):
print("You are using Python 2 on Windows.")
+table(["Name", "Type", "Description"])
+row
+cell #[code python2]
+cell bool
+cell spaCy is executed with Python 2.x.
+row
+cell #[code python3]
+cell bool
+cell spaCy is executed with Python 3.x.
+row
+cell #[code windows]
+cell bool
+cell spaCy is executed on Windows.
+row
+cell #[code linux]
+cell bool
+cell spaCy is executed on Linux.
+row
+cell #[code osx]
+cell bool
+cell spaCy is executed on OS X or macOS.
+row("foot")
+cell returns
+cell bool
+cell Whether the specified configuration matches the user's platform.

24
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@ -1,14 +1,12 @@
//- 💫 DOCS > API > DISPLACY
include ../../_includes/_mixins
//- 💫 DOCS > API > TOP-LEVEL > DISPLACY
p
| As of v2.0, spaCy comes with a built-in visualization suite. For more
| info and examples, see the usage guide on
| #[+a("/docs/usage/visualizers") visualizing spaCy].
| #[+a("/usage/visualizers") visualizing spaCy].
+h(2, "serve") displacy.serve
+h(3, "displacy.serve") displacy.serve
+tag method
+tag-new(2)
@ -60,7 +58,7 @@ p
+cell bool
+cell
| Don't parse #[code Doc] and instead, expect a dict or list of
| dicts. #[+a("/docs/usage/visualizers#manual-usage") See here]
| dicts. #[+a("/usage/visualizers#manual-usage") See here]
| for formats and examples.
+cell #[code False]
@ -70,7 +68,7 @@ p
+cell Port to serve visualization.
+cell #[code 5000]
+h(2, "render") displacy.render
+h(3, "displacy.render") displacy.render
+tag method
+tag-new(2)
@ -127,24 +125,24 @@ p Render a dependency parse tree or named entity visualization.
+cell bool
+cell
| Don't parse #[code Doc] and instead, expect a dict or list of
| dicts. #[+a("/docs/usage/visualizers#manual-usage") See here]
| dicts. #[+a("/usage/visualizers#manual-usage") See here]
| for formats and examples.
+cell #[code False]
+footrow
+row("foot")
+cell returns
+cell unicode
+cell Rendered HTML markup.
+cell
+h(2, "options") Visualizer options
+h(3, "displacy_options") Visualizer options
p
| The #[code options] argument lets you specify additional settings for
| each visualizer. If a setting is not present in the options, the default
| value will be used.
+h(3, "options-dep") Dependency Visualizer options
+h(4, "options-dep") Dependency Visualizer options
+aside-code("Example").
options = {'compact': True, 'color': 'blue'}
@ -219,7 +217,7 @@ p
+cell Distance between words in px.
+cell #[code 175] / #[code 85] (compact)
+h(3, "options-ent") Named Entity Visualizer options
+h(4, "displacy_options-ent") Named Entity Visualizer options
+aside-code("Example").
options = {'ents': ['PERSON', 'ORG', 'PRODUCT'],
@ -244,6 +242,6 @@ p
p
| By default, displaCy comes with colours for all
| #[+a("/docs/api/annotation#named-entities") entity types supported by spaCy].
| #[+a("/api/annotation#named-entities") entity types supported by spaCy].
| If you're using custom entity types, you can use the #[code colors]
| setting to add your own colours for them.

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@ -1,15 +1,13 @@
//- 💫 DOCS > API > SPACY
//- 💫 DOCS > API > TOP-LEVEL > SPACY
include ../../_includes/_mixins
+h(2, "load") spacy.load
+h(3, "spacy.load") spacy.load
+tag function
+tag-model
p
| Load a model via its #[+a("/docs/usage/models#usage") shortcut link],
| Load a model via its #[+a("/usage/models#usage") shortcut link],
| the name of an installed
| #[+a("/docs/usage/saving-loading#generating") model package], a unicode
| #[+a("/usage/training#models-generating") model package], a unicode
| path or a #[code Path]-like object. spaCy will try resolving the load
| argument in this order. If a model is loaded from a shortcut link or
| package name, spaCy will assume it's a Python package and import it and
@ -38,25 +36,57 @@ p
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable].
| #[+a("/usage/processing-pipelines#disabling") disable].
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell A #[code Language] object with the loaded model.
+infobox("⚠️ Deprecation note")
+infobox("Deprecation note", "⚠️")
.o-block
| As of spaCy 2.0, the #[code path] keyword argument is deprecated. spaCy
| will also raise an error if no model could be loaded and never just
| return an empty #[code Language] object. If you need a blank language,
| you need to import it explicitly (#[code from spacy.lang.en import English])
| or use #[+api("util#get_lang_class") #[code util.get_lang_class]].
| you can use the new function #[+api("spacy#blank") #[code spacy.blank()]]
| or import the class explicitly, e.g.
| #[code from spacy.lang.en import English].
+code-new nlp = spacy.load('/model')
+code-old nlp = spacy.load('en', path='/model')
+h(2, "info") spacy.info
+h(3, "spacy.blank") spacy.blank
+tag function
+tag-new(2)
p
| Create a blank model of a given language class. This function is the
| twin of #[code spacy.load()].
+aside-code("Example").
nlp_en = spacy.blank('en')
nlp_de = spacy.blank('de')
+table(["Name", "Type", "Description"])
+row
+cell #[code name]
+cell unicode
+cell ISO code of the language class to load.
+row
+cell #[code disable]
+cell list
+cell
| Names of pipeline components to
| #[+a("/usage/processing-pipelines#disabling") disable].
+row("foot")
+cell returns
+cell #[code Language]
+cell An empty #[code Language] object of the appropriate subclass.
+h(4, "spacy.info") spacy.info
+tag function
p
@ -83,13 +113,13 @@ p
+cell Print information as Markdown.
+h(2, "explain") spacy.explain
+h(3, "spacy.explain") spacy.explain
+tag function
p
| Get a description for a given POS tag, dependency label or entity type.
| For a list of available terms, see
| #[+src(gh("spacy", "spacy/glossary.py")) glossary.py].
| #[+src(gh("spacy", "spacy/glossary.py")) #[code glossary.py]].
+aside-code("Example").
spacy.explain('NORP')
@ -107,18 +137,18 @@ p
+cell unicode
+cell Term to explain.
+footrow
+row("foot")
+cell returns
+cell unicode
+cell The explanation, or #[code None] if not found in the glossary.
+h(2, "set_factory") spacy.set_factory
+h(3, "spacy.set_factory") spacy.set_factory
+tag function
+tag-new(2)
p
| Set a factory that returns a custom
| #[+a("/docs/usage/language-processing-pipeline") processing pipeline]
| #[+a("/usage/processing-pipelines") processing pipeline]
| component. Factories are useful for creating stateful components, especially ones which depend on shared data.
+aside-code("Example").

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@ -1,10 +1,8 @@
//- 💫 DOCS > API > UTIL
include ../../_includes/_mixins
//- 💫 DOCS > API > TOP-LEVEL > UTIL
p
| spaCy comes with a small collection of utility functions located in
| #[+src(gh("spaCy", "spacy/util.py")) spacy/util.py].
| #[+src(gh("spaCy", "spacy/util.py")) #[code spacy/util.py]].
| Because utility functions are mostly intended for
| #[strong internal use within spaCy], their behaviour may change with
| future releases. The functions documented on this page should be safe
@ -12,7 +10,7 @@ p
| recommend having additional tests in place if your application depends on
| any of spaCy's utilities.
+h(2, "get_data_path") util.get_data_path
+h(3, "util.get_data_path") util.get_data_path
+tag function
p
@ -25,12 +23,12 @@ p
+cell bool
+cell Only return path if it exists, otherwise return #[code None].
+footrow
+row("foot")
+cell returns
+cell #[code Path] / #[code None]
+cell Data path or #[code None].
+h(2, "set_data_path") util.set_data_path
+h(3, "util.set_data_path") util.set_data_path
+tag function
p
@ -47,12 +45,12 @@ p
+cell unicode or #[code Path]
+cell Path to new data directory.
+h(2, "get_lang_class") util.get_lang_class
+h(3, "util.get_lang_class") util.get_lang_class
+tag function
p
| Import and load a #[code Language] class. Allows lazy-loading
| #[+a("/docs/usage/adding-languages") language data] and importing
| #[+a("/usage/adding-languages") language data] and importing
| languages using the two-letter language code.
+aside-code("Example").
@ -67,12 +65,12 @@ p
+cell unicode
+cell Two-letter language code, e.g. #[code 'en'].
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell Language class.
+h(2, "load_model") util.load_model
+h(3, "util.load_model") util.load_model
+tag function
+tag-new(2)
@ -101,12 +99,12 @@ p
+cell -
+cell Specific overrides, like pipeline components to disable.
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell #[code Language] class with the loaded model.
+h(2, "load_model_from_path") util.load_model_from_path
+h(3, "util.load_model_from_path") util.load_model_from_path
+tag function
+tag-new(2)
@ -139,18 +137,18 @@ p
+cell -
+cell Specific overrides, like pipeline components to disable.
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell #[code Language] class with the loaded model.
+h(2, "load_model_from_init_py") util.load_model_from_init_py
+h(3, "util.load_model_from_init_py") util.load_model_from_init_py
+tag function
+tag-new(2)
p
| A helper function to use in the #[code load()] method of a model package's
| #[+src(gh("spacy-dev-resources", "templates/model/en_model_name/__init__.py")) __init__.py].
| #[+src(gh("spacy-dev-resources", "templates/model/en_model_name/__init__.py")) #[code __init__.py]].
+aside-code("Example").
from spacy.util import load_model_from_init_py
@ -169,12 +167,12 @@ p
+cell -
+cell Specific overrides, like pipeline components to disable.
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell #[code Language] class with the loaded model.
+h(2, "get_model_meta") util.get_model_meta
+h(3, "util.get_model_meta") util.get_model_meta
+tag function
+tag-new(2)
@ -190,17 +188,17 @@ p
+cell unicode or #[code Path]
+cell Path to model directory.
+footrow
+row("foot")
+cell returns
+cell dict
+cell The model's meta data.
+h(2, "is_package") util.is_package
+h(3, "util.is_package") util.is_package
+tag function
p
| Check if string maps to a package installed via pip. Mainly used to
| validate #[+a("/docs/usage/models") model packages].
| validate #[+a("/usage/models") model packages].
+aside-code("Example").
util.is_package('en_core_web_sm') # True
@ -212,18 +210,18 @@ p
+cell unicode
+cell Name of package.
+footrow
+row("foot")
+cell returns
+cell #[code bool]
+cell #[code True] if installed package, #[code False] if not.
+h(2, "get_package_path") util.get_package_path
+h(3, "util.get_package_path") util.get_package_path
+tag function
+tag-new(2)
p
| Get path to an installed package. Mainly used to resolve the location of
| #[+a("/docs/usage/models") model packages]. Currently imports the package
| #[+a("/usage/models") model packages]. Currently imports the package
| to find its path.
+aside-code("Example").
@ -236,12 +234,12 @@ p
+cell unicode
+cell Name of installed package.
+footrow
+row("foot")
+cell returns
+cell #[code Path]
+cell Path to model package directory.
+h(2, "is_in_jupyter") util.is_in_jupyter
+h(3, "util.is_in_jupyter") util.is_in_jupyter
+tag function
+tag-new(2)
@ -257,17 +255,17 @@ p
return display(HTML(html))
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bool
+cell #[code True] if in Jupyter, #[code False] if not.
+h(2, "update_exc") util.update_exc
+h(3, "util.update_exc") util.update_exc
+tag function
p
| Update, validate and overwrite
| #[+a("/docs/usage/adding-languages#tokenizer-exceptions") tokenizer exceptions].
| #[+a("/usage/adding-languages#tokenizer-exceptions") tokenizer exceptions].
| Used to combine global exceptions with custom, language-specific
| exceptions. Will raise an error if key doesn't match #[code ORTH] values.
@ -288,20 +286,20 @@ p
+cell dicts
+cell Exception dictionaries to add to the base exceptions, in order.
+footrow
+row("foot")
+cell returns
+cell dict
+cell Combined tokenizer exceptions.
+h(2, "prints") util.prints
+h(3, "util.prints") util.prints
+tag function
+tag-new(2)
p
| Print a formatted, text-wrapped message with optional title. If a text
| argument is a #[code Path], it's converted to a string. Should only
| be used for interactive components like the #[+api("cli") cli].
| be used for interactive components like the command-line interface.
+aside-code("Example").
data_path = Path('/some/path')

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@ -0,0 +1,131 @@
//- 💫 DOCS > API > ANNOTATION SPECS
include ../_includes/_mixins
p This document describes the target annotations spaCy is trained to predict.
+section("tokenization")
+h(2, "tokenization") Tokenization
p
| Tokenization standards are based on the
| #[+a("https://catalog.ldc.upenn.edu/LDC2013T19") OntoNotes 5] corpus.
| The tokenizer differs from most by including tokens for significant
| whitespace. Any sequence of whitespace characters beyond a single space
| (#[code ' ']) is included as a token.
+aside-code("Example").
from spacy.lang.en import English
nlp = English()
tokens = nlp('Some\nspaces and\ttab characters')
tokens_text = [t.text for t in tokens]
assert tokens_text == ['Some', '\n', 'spaces', ' ', 'and',
'\t', 'tab', 'characters']
p
| The whitespace tokens are useful for much the same reason punctuation is
| – it's often an important delimiter in the text. By preserving it in the
| token output, we are able to maintain a simple alignment between the
| tokens and the original string, and we ensure that no information is
| lost during processing.
+section("sbd")
+h(2, "sentence-boundary") Sentence boundary detection
p
| Sentence boundaries are calculated from the syntactic parse tree, so
| features such as punctuation and capitalisation play an important but
| non-decisive role in determining the sentence boundaries. Usually this
| means that the sentence boundaries will at least coincide with clause
| boundaries, even given poorly punctuated text.
+section("pos-tagging")
+h(2, "pos-tagging") Part-of-speech Tagging
+aside("Tip: Understanding tags")
| You can also use #[code spacy.explain()] to get the description for the
| string representation of a tag. For example,
| #[code spacy.explain("RB")] will return "adverb".
include _annotation/_pos-tags
+section("lemmatization")
+h(2, "lemmatization") Lemmatization
p A "lemma" is the uninflected form of a word. In English, this means:
+list
+item #[strong Adjectives]: The form like "happy", not "happier" or "happiest"
+item #[strong Adverbs]: The form like "badly", not "worse" or "worst"
+item #[strong Nouns]: The form like "dog", not "dogs"; like "child", not "children"
+item #[strong Verbs]: The form like "write", not "writes", "writing", "wrote" or "written"
p
| The lemmatization data is taken from
| #[+a("https://wordnet.princeton.edu") WordNet]. However, we also add a
| special case for pronouns: all pronouns are lemmatized to the special
| token #[code -PRON-].
+infobox("About spaCy's custom pronoun lemma")
| Unlike verbs and common nouns, there's no clear base form of a personal
| pronoun. Should the lemma of "me" be "I", or should we normalize person
| as well, giving "it" — or maybe "he"? spaCy's solution is to introduce a
| novel symbol, #[code -PRON-], which is used as the lemma for
| all personal pronouns.
+section("dependency-parsing")
+h(2, "dependency-parsing") Syntactic Dependency Parsing
+aside("Tip: Understanding labels")
| You can also use #[code spacy.explain()] to get the description for the
| string representation of a label. For example,
| #[code spacy.explain("prt")] will return "particle".
include _annotation/_dep-labels
+section("named-entities")
+h(2, "named-entities") Named Entity Recognition
+aside("Tip: Understanding entity types")
| You can also use #[code spacy.explain()] to get the description for the
| string representation of an entity label. For example,
| #[code spacy.explain("LANGUAGE")] will return "any named language".
include _annotation/_named-entities
+h(3, "biluo") BILUO Scheme
include _annotation/_biluo
+section("training")
+h(2, "json-input") JSON input format for training
+under-construction
p spaCy takes training data in the following format:
+code("Example structure").
doc: {
id: string,
paragraphs: [{
raw: string,
sents: [int],
tokens: [{
start: int,
tag: string,
head: int,
dep: string
}],
ner: [{
start: int,
end: int,
label: string
}],
brackets: [{
start: int,
end: int,
label: string
}]
}]
}

2
website/docs/api/binder.jade → website/api/binder.jade
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > BINDER
include ../../_includes/_mixins
include ../_includes/_mixins
p A container class for serializing collections of #[code Doc] objects.

5
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@ -0,0 +1,5 @@
//- 💫 DOCS > API > DEPENDENCYPARSER
include ../_includes/_mixins
!=partial("pipe", { subclass: "DependencyParser", short: "parser", pipeline_id: "parser" })

48
website/docs/api/doc.jade → website/api/doc.jade
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@ -1,8 +1,6 @@
//- 💫 DOCS > API > DOC
include ../../_includes/_mixins
p A container for accessing linguistic annotations.
include ../_includes/_mixins
p
| A #[code Doc] is a sequence of #[+api("token") #[code Token]] objects.
@ -47,7 +45,7 @@ p
| subsequent space. Must have the same length as #[code words], if
| specified. Defaults to a sequence of #[code True].
+footrow
+row("foot")
+cell returns
+cell #[code Doc]
+cell The newly constructed object.
@ -73,7 +71,7 @@ p
+cell int
+cell The index of the token.
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell The token at #[code doc[i]].
@ -96,7 +94,7 @@ p
+cell tuple
+cell The slice of the document to get.
+footrow
+row("foot")
+cell returns
+cell #[code Span]
+cell The span at #[code doc[start : end]].
@ -120,7 +118,7 @@ p
| from Cython.
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A #[code Token] object.
@ -135,7 +133,7 @@ p Get the number of tokens in the document.
assert len(doc) == 7
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of tokens in the document.
@ -172,7 +170,7 @@ p Create a #[code Span] object from the slice #[code doc.text[start : end]].
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A meaning representation of the span.
+footrow
+row("foot")
+cell returns
+cell #[code Span]
+cell The newly constructed object.
@ -200,7 +198,7 @@ p
| The object to compare with. By default, accepts #[code Doc],
| #[code Span], #[code Token] and #[code Lexeme] objects.
+footrow
+row("foot")
+cell returns
+cell float
+cell A scalar similarity score. Higher is more similar.
@ -226,7 +224,7 @@ p
+cell int
+cell The attribute ID
+footrow
+row("foot")
+cell returns
+cell dict
+cell A dictionary mapping attributes to integer counts.
@ -251,7 +249,7 @@ p
+cell list
+cell A list of attribute ID ints.
+footrow
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=2, dtype='int32']]
+cell
@ -285,7 +283,7 @@ p
+cell #[code.u-break numpy.ndarray[ndim=2, dtype='int32']]
+cell The attribute values to load.
+footrow
+row("foot")
+cell returns
+cell #[code Doc]
+cell Itself.
@ -326,7 +324,7 @@ p Loads state from a directory. Modifies the object in place and returns it.
| A path to a directory. Paths may be either strings or
| #[code Path]-like objects.
+footrow
+row("foot")
+cell returns
+cell #[code Doc]
+cell The modified #[code Doc] object.
@ -341,7 +339,7 @@ p Serialize, i.e. export the document contents to a binary string.
doc_bytes = doc.to_bytes()
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bytes
+cell
@ -367,7 +365,7 @@ p Deserialize, i.e. import the document contents from a binary string.
+cell bytes
+cell The string to load from.
+footrow
+row("foot")
+cell returns
+cell #[code Doc]
+cell The #[code Doc] object.
@ -378,7 +376,7 @@ p Deserialize, i.e. import the document contents from a binary string.
p
| Retokenize the document, such that the span at
| #[code doc.text[start_idx : end_idx]] is merged into a single token. If
| #[code start_idx] and #[end_idx] do not mark start and end token
| #[code start_idx] and #[code end_idx] do not mark start and end token
| boundaries, the document remains unchanged.
+aside-code("Example").
@ -405,7 +403,7 @@ p
| attributes are inherited from the syntactic root token of
| the span.
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell
@ -440,7 +438,7 @@ p
+cell bool
+cell Don't include arcs or modifiers.
+footrow
+row("foot")
+cell returns
+cell dict
+cell Parse tree as dict.
@ -462,7 +460,7 @@ p
assert ents[0].text == 'Mr. Best'
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Span]
+cell Entities in the document.
@ -485,7 +483,7 @@ p
assert chunks[1].text == "another phrase"
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Span]
+cell Noun chunks in the document.
@ -507,7 +505,7 @@ p
assert [s.root.text for s in sents] == ["is", "'s"]
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Span]
+cell Sentences in the document.
@ -525,7 +523,7 @@ p
assert doc.has_vector
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the document has a vector data attached.
@ -544,7 +542,7 @@ p
assert doc.vector.shape == (300,)
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A 1D numpy array representing the document's semantics.
@ -564,7 +562,7 @@ p
assert doc1.vector_norm != doc2.vector_norm
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell float
+cell The L2 norm of the vector representation.

5
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@ -0,0 +1,5 @@
//- 💫 DOCS > API > ENTITYRECOGNIZER
include ../_includes/_mixins
!=partial("pipe", { subclass: "EntityRecognizer", short: "ner", pipeline_id: "ner" })

6
website/docs/api/goldcorpus.jade → website/api/goldcorpus.jade
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@ -1,14 +1,12 @@
//- 💫 DOCS > API > GOLDCORPUS
include ../../_includes/_mixins
include ../_includes/_mixins
p
| An annotated corpus, using the JSON file format. Manages annotations for
| tagging, dependency parsing and NER.
| This class manages annotations for tagging, dependency parsing and NER.
+h(2, "init") GoldCorpus.__init__
+tag method
+tag-new(2)
p Create a #[code GoldCorpus].

14
website/docs/api/goldparse.jade → website/api/goldparse.jade
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > GOLDPARSE
include ../../_includes/_mixins
include ../_includes/_mixins
p Collection for training annotations.
@ -40,7 +40,7 @@ p Create a #[code GoldParse].
+cell iterable
+cell A sequence of named entity annotations, either as BILUO tag strings, or as #[code (start_char, end_char, label)] tuples, representing the entity positions.
+footrow
+row("foot")
+cell returns
+cell #[code GoldParse]
+cell The newly constructed object.
@ -51,7 +51,7 @@ p Create a #[code GoldParse].
p Get the number of gold-standard tokens.
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of gold-standard tokens.
@ -64,7 +64,7 @@ p
| tree.
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether annotations form projective tree.
@ -119,7 +119,7 @@ p
p
| Encode labelled spans into per-token tags, using the
| #[+a("/docs/api/annotation#biluo") BILUO scheme] (Begin/In/Last/Unit/Out).
| #[+a("/api/annotation#biluo") BILUO scheme] (Begin/In/Last/Unit/Out).
p
| Returns a list of unicode strings, describing the tags. Each tag string
@ -157,11 +157,11 @@ p
| and #[code end] should be character-offset integers denoting the
| slice into the original string.
+footrow
+row("foot")
+cell returns
+cell list
+cell
| Unicode strings, describing the
| #[+a("/docs/api/annotation#biluo") BILUO] tags.
| #[+a("/api/annotation#biluo") BILUO] tags.

14
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@ -0,0 +1,14 @@
//- 💫 DOCS > API > ARCHITECTURE
include ../_includes/_mixins
+section("basics")
include ../usage/_spacy-101/_architecture
+section("nn-model")
+h(2, "nn-model") Neural network model architecture
include _architecture/_nn-model
+section("cython")
+h(2, "cython") Cython conventions
include _architecture/_cython

42
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@ -1,10 +1,10 @@
//- 💫 DOCS > API > LANGUAGE
include ../../_includes/_mixins
include ../_includes/_mixins
p
| A text-processing pipeline. Usually you'll load this once per process,
| and pass the instance around your application.
| Usually you'll load this once per process as #[code nlp] and pass the
| instance around your application.
+h(2, "init") Language.__init__
+tag method
@ -49,7 +49,7 @@ p Initialise a #[code Language] object.
| Custom meta data for the #[code Language] class. Is written to by
| models to add model meta data.
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell The newly constructed object.
@ -77,14 +77,14 @@ p
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable].
| #[+a("/usage/processing-pipelines#disabling") disable].
+footrow
+row("foot")
+cell returns
+cell #[code Doc]
+cell A container for accessing the annotations.
+infobox("⚠️ Deprecation note")
+infobox("Deprecation note", "⚠️")
.o-block
| Pipeline components to prevent from being loaded can now be added as
| a list to #[code disable], instead of specifying one keyword argument
@ -136,9 +136,9 @@ p
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable].
| #[+a("/usage/processing-pipelines#disabling") disable].
+footrow
+row("foot")
+cell yields
+cell #[code Doc]
+cell Documents in the order of the original text.
@ -175,7 +175,7 @@ p Update the models in the pipeline.
+cell callable
+cell An optimizer.
+footrow
+row("foot")
+cell returns
+cell dict
+cell Results from the update.
@ -200,7 +200,7 @@ p
+cell -
+cell Config parameters.
+footrow
+row("foot")
+cell yields
+cell tuple
+cell An optimizer.
@ -242,7 +242,7 @@ p
+cell iterable
+cell Tuples of #[code Doc] and #[code GoldParse] objects.
+footrow
+row("foot")
+cell yields
+cell tuple
+cell Tuples of #[code Doc] and #[code GoldParse] objects.
@ -271,7 +271,7 @@ p
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable]
| #[+a("/usage/processing-pipelines#disabling") disable]
| and prevent from being saved.
+h(2, "from_disk") Language.from_disk
@ -300,14 +300,14 @@ p
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable].
| #[+a("/usage/processing-pipelines#disabling") disable].
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell The modified #[code Language] object.
+infobox("⚠️ Deprecation note")
+infobox("Deprecation note", "⚠️")
.o-block
| As of spaCy v2.0, the #[code save_to_directory] method has been
| renamed to #[code to_disk], to improve consistency across classes.
@ -332,10 +332,10 @@ p Serialize the current state to a binary string.
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable]
| #[+a("/usage/processing-pipelines#disabling") disable]
| and prevent from being serialized.
+footrow
+row("foot")
+cell returns
+cell bytes
+cell The serialized form of the #[code Language] object.
@ -362,14 +362,14 @@ p Load state from a binary string.
+cell list
+cell
| Names of pipeline components to
| #[+a("/docs/usage/language-processing-pipeline#disabling") disable].
| #[+a("/usage/processing-pipelines#disabling") disable].
+footrow
+row("foot")
+cell returns
+cell #[code Language]
+cell The #[code Language] object.
+infobox("⚠️ Deprecation note")
+infobox("Deprecation note", "⚠️")
.o-block
| Pipeline components to prevent from being loaded can now be added as
| a list to #[code disable], instead of specifying one keyword argument

5
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@ -0,0 +1,5 @@
//- 💫 DOCS > API > LEMMATIZER
include ../_includes/_mixins
+under-construction

14
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > LEXEME
include ../../_includes/_mixins
include ../_includes/_mixins
p
| An entry in the vocabulary. A #[code Lexeme] has no string context – it's
@ -24,7 +24,7 @@ p Create a #[code Lexeme] object.
+cell int
+cell The orth id of the lexeme.
+footrow
+row("foot")
+cell returns
+cell #[code Lexeme]
+cell The newly constructed object.
@ -65,7 +65,7 @@ p Check the value of a boolean flag.
+cell int
+cell The attribute ID of the flag to query.
+footrow
+row("foot")
+cell returns
+cell bool
+cell The value of the flag.
@ -91,7 +91,7 @@ p Compute a semantic similarity estimate. Defaults to cosine over vectors.
| The object to compare with. By default, accepts #[code Doc],
| #[code Span], #[code Token] and #[code Lexeme] objects.
+footrow
+row("foot")
+cell returns
+cell float
+cell A scalar similarity score. Higher is more similar.
@ -110,7 +110,7 @@ p
assert apple.has_vector
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the lexeme has a vector data attached.
@ -127,7 +127,7 @@ p A real-valued meaning representation.
assert apple.vector.shape == (300,)
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A 1D numpy array representing the lexeme's semantics.
@ -146,7 +146,7 @@ p The L2 norm of the lexeme's vector representation.
assert apple.vector_norm != pasta.vector_norm
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell float
+cell The L2 norm of the vector representation.

23
website/docs/api/matcher.jade → website/api/matcher.jade
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@ -1,10 +1,8 @@
//- 💫 DOCS > API > MATCHER
include ../../_includes/_mixins
include ../_includes/_mixins
p Match sequences of tokens, based on pattern rules.
+infobox("⚠️ Deprecation note")
+infobox("Deprecation note", "⚠️")
| As of spaCy 2.0, #[code Matcher.add_pattern] and #[code Matcher.add_entity]
| are deprecated and have been replaced with a simpler
| #[+api("matcher#add") #[code Matcher.add]] that lets you add a list of
@ -39,7 +37,7 @@ p Create the rule-based #[code Matcher].
+cell dict
+cell Patterns to add to the matcher, keyed by ID.
+footrow
+row("foot")
+cell returns
+cell #[code Matcher]
+cell The newly constructed object.
@ -64,7 +62,7 @@ p Find all token sequences matching the supplied patterns on the #[code Doc].
+cell #[code Doc]
+cell The document to match over.
+footrow
+row("foot")
+cell returns
+cell list
+cell
@ -81,7 +79,7 @@ p Find all token sequences matching the supplied patterns on the #[code Doc].
| actions per pattern within the same matcher. For example, you might only
| want to merge some entity types, and set custom flags for other matched
| patterns. For more details and examples, see the usage guide on
| #[+a("/docs/usage/rule-based-matching") rule-based matching].
| #[+a("/usage/linguistic-features#rule-based-matching") rule-based matching].
+h(2, "pipe") Matcher.pipe
+tag method
@ -113,7 +111,7 @@ p Match a stream of documents, yielding them in turn.
| parallel, if the #[code Matcher] implementation supports
| multi-threading.
+footrow
+row("foot")
+cell yields
+cell #[code Doc]
+cell Documents, in order.
@ -134,7 +132,7 @@ p
assert len(matcher) == 1
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of rules.
@ -156,7 +154,8 @@ p Check whether the matcher contains rules for a match ID.
+cell #[code key]
+cell unicode
+cell The match ID.
+footrow
+row("foot")
+cell returns
+cell int
+cell Whether the matcher contains rules for this match ID.
@ -203,7 +202,7 @@ p
| Match pattern. A pattern consists of a list of dicts, where each
| dict describes a token.
+infobox("⚠️ Deprecation note")
+infobox("Deprecation note", "⚠️")
.o-block
| As of spaCy 2.0, #[code Matcher.add_pattern] and #[code Matcher.add_entity]
| are deprecated and have been replaced with a simpler
@ -257,7 +256,7 @@ p
+cell unicode
+cell The ID of the match rule.
+footrow
+row("foot")
+cell returns
+cell tuple
+cell The rule, as an #[code (on_match, patterns)] tuple.

181
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@ -0,0 +1,181 @@
//- 💫 DOCS > API > PHRASEMATCHER
include ../_includes/_mixins
p
| The #[code PhraseMatcher] lets you efficiently match large terminology
| lists. While the #[+api("matcher") #[code Matcher]] lets you match
| squences based on lists of token descriptions, the #[code PhraseMatcher]
| accepts match patterns in the form of #[code Doc] objects.
+h(2, "init") PhraseMatcher.__init__
+tag method
p Create the rule-based #[code PhraseMatcher].
+aside-code("Example").
from spacy.matcher import PhraseMatcher
matcher = PhraseMatcher(nlp.vocab, max_length=6)
+table(["Name", "Type", "Description"])
+row
+cell #[code vocab]
+cell #[code Vocab]
+cell
| The vocabulary object, which must be shared with the documents
| the matcher will operate on.
+row
+cell #[code max_length]
+cell int
+cell Mamimum length of a phrase pattern to add.
+row("foot")
+cell returns
+cell #[code PhraseMatcher]
+cell The newly constructed object.
+h(2, "call") PhraseMatcher.__call__
+tag method
p Find all token sequences matching the supplied patterns on the #[code Doc].
+aside-code("Example").
from spacy.matcher import PhraseMatcher
matcher = PhraseMatcher(nlp.vocab)
matcher.add('OBAMA', None, nlp(u"Barack Obama"))
doc = nlp(u"Barack Obama lifts America one last time in emotional farewell")
matches = matcher(doc)
+table(["Name", "Type", "Description"])
+row
+cell #[code doc]
+cell #[code Doc]
+cell The document to match over.
+row("foot")
+cell returns
+cell list
+cell
| A list of #[code (match_id, start, end)] tuples, describing the
| matches. A match tuple describes a span #[code doc[start:end]].
| The #[code match_id] is the ID of the added match pattern.
+h(2, "pipe") PhraseMatcher.pipe
+tag method
p Match a stream of documents, yielding them in turn.
+aside-code("Example").
from spacy.matcher import PhraseMatcher
matcher = PhraseMatcher(nlp.vocab)
for doc in matcher.pipe(texts, batch_size=50, n_threads=4):
pass
+table(["Name", "Type", "Description"])
+row
+cell #[code docs]
+cell iterable
+cell A stream of documents.
+row
+cell #[code batch_size]
+cell int
+cell The number of documents to accumulate into a working set.
+row
+cell #[code n_threads]
+cell int
+cell
| The number of threads with which to work on the buffer in
| parallel, if the #[code PhraseMatcher] implementation supports
| multi-threading.
+row("foot")
+cell yields
+cell #[code Doc]
+cell Documents, in order.
+h(2, "len") PhraseMatcher.__len__
+tag method
p
| Get the number of rules added to the matcher. Note that this only returns
| the number of rules (identical with the number of IDs), not the number
| of individual patterns.
+aside-code("Example").
matcher = PhraseMatcher(nlp.vocab)
assert len(matcher) == 0
matcher.add('OBAMA', None, nlp(u"Barack Obama"))
assert len(matcher) == 1
+table(["Name", "Type", "Description"])
+row("foot")
+cell returns
+cell int
+cell The number of rules.
+h(2, "contains") PhraseMatcher.__contains__
+tag method
p Check whether the matcher contains rules for a match ID.
+aside-code("Example").
matcher = PhraseMatcher(nlp.vocab)
assert len(matcher) == 0
matcher.add('OBAMA', None, nlp(u"Barack Obama"))
assert len(matcher) == 1
+table(["Name", "Type", "Description"])
+row
+cell #[code key]
+cell unicode
+cell The match ID.
+row("foot")
+cell returns
+cell int
+cell Whether the matcher contains rules for this match ID.
+h(2, "add") PhraseMatcher.add
+tag method
p
| Add a rule to the matcher, consisting of an ID key, one or more patterns, and
| a callback function to act on the matches. The callback function will
| receive the arguments #[code matcher], #[code doc], #[code i] and
| #[code matches]. If a pattern already exists for the given ID, the
| patterns will be extended. An #[code on_match] callback will be
| overwritten.
+aside-code("Example").
def on_match(matcher, doc, id, matches):
print('Matched!', matches)
matcher = PhraseMatcher(nlp.vocab)
matcher.add('OBAMA', on_match, nlp(u"Barack Obama"))
matcher.add('HEALTH', on_match, nlp(u"health care reform"),
nlp(u"healthcare reform"))
doc = nlp(u"Barack Obama urges Congress to find courage to defend his healthcare reforms")
matches = matcher(doc)
+table(["Name", "Type", "Description"])
+row
+cell #[code match_id]
+cell unicode
+cell An ID for the thing you're matching.
+row
+cell #[code on_match]
+cell callable or #[code None]
+cell
| Callback function to act on matches. Takes the arguments
| #[code matcher], #[code doc], #[code i] and #[code matches].
+row
+cell #[code *docs]
+cell list
+cell
| #[code Doc] objects of the phrases to match.

390
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@ -0,0 +1,390 @@
//- 💫 DOCS > API > PIPE
include ../_includes/_mixins
//- This page can be used as a template for all other classes that inherit
//- from `Pipe`.
if subclass
+infobox
| This class is a subclass of #[+api("pipe") #[code Pipe]] and
| follows the same API. The pipeline component is available in the
| #[+a("/usage/processing-pipelines") processing pipeline] via the ID
| #[code "#{pipeline_id}"].
else
p
| This class is not instantiated directly. Components inherit from it,
| and it defines the interface that components should follow to
| function as components in a spaCy analysis pipeline.
- CLASSNAME = subclass || 'Pipe'
- VARNAME = short || CLASSNAME.toLowerCase()
+h(2, "model") #{CLASSNAME}.Model
+tag classmethod
p
| Initialise a model for the pipe. The model should implement the
| #[code thinc.neural.Model] API. Wrappers are available for
| #[+a("/usage/deep-learning") most major machine learning libraries].
+table(["Name", "Type", "Description"])
+row
+cell #[code **kwargs]
+cell -
+cell Parameters for initialising the model
+row("foot")
+cell returns
+cell object
+cell The initialised model.
+h(2, "init") #{CLASSNAME}.__init__
+tag method
p Create a new pipeline instance.
+aside-code("Example").
from spacy.pipeline import #{CLASSNAME}
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
+table(["Name", "Type", "Description"])
+row
+cell #[code vocab]
+cell #[code Vocab]
+cell The shared vocabulary.
+row
+cell #[code model]
+cell #[code thinc.neural.Model] or #[code True]
+cell
| The model powering the pipeline component. If no model is
| supplied, the model is created when you call
| #[code begin_training], #[code from_disk] or #[code from_bytes].
+row
+cell #[code **cfg]
+cell -
+cell Configuration parameters.
+row("foot")
+cell returns
+cell #[code=CLASSNAME]
+cell The newly constructed object.
+h(2, "call") #{CLASSNAME}.__call__
+tag method
p
| Apply the pipe to one document. The document is modified in place, and
| returned. Both #[code #{CLASSNAME}.__call__] and
| #[code #{CLASSNAME}.pipe] should delegate to the
| #[code #{CLASSNAME}.predict] and #[code #{CLASSNAME}.set_annotations]
| methods.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
doc = nlp(u"This is a sentence.")
processed = #{VARNAME}(doc)
+table(["Name", "Type", "Description"])
+row
+cell #[code doc]
+cell #[code Doc]
+cell The document to process.
+row("foot")
+cell returns
+cell #[code Doc]
+cell The processed document.
+h(2, "pipe") #{CLASSNAME}.pipe
+tag method
p
| Apply the pipe to a stream of documents. Both
| #[code #{CLASSNAME}.__call__] and #[code #{CLASSNAME}.pipe] should
| delegate to the #[code #{CLASSNAME}.predict] and
| #[code #{CLASSNAME}.set_annotations] methods.
+aside-code("Example").
texts = [u'One doc', u'...', u'Lots of docs']
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
for doc in #{VARNAME}.pipe(texts, batch_size=50):
pass
+table(["Name", "Type", "Description"])
+row
+cell #[code stream]
+cell iterable
+cell A stream of documents.
+row
+cell #[code batch_size]
+cell int
+cell The number of texts to buffer. Defaults to #[code 128].
+row
+cell #[code n_threads]
+cell int
+cell
| The number of worker threads to use. If #[code -1], OpenMP will
| decide how many to use at run time. Default is #[code -1].
+row("foot")
+cell yields
+cell #[code Doc]
+cell Processed documents in the order of the original text.
+h(2, "predict") #{CLASSNAME}.predict
+tag method
p
| Apply the pipeline's model to a batch of docs, without modifying them.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
scores = #{VARNAME}.predict([doc1, doc2])
+table(["Name", "Type", "Description"])
+row
+cell #[code docs]
+cell iterable
+cell The documents to predict.
+row("foot")
+cell returns
+cell -
+cell Scores from the model.
+h(2, "set_annotations") #{CLASSNAME}.set_annotations
+tag method
p
| Modify a batch of documents, using pre-computed scores.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
scores = #{VARNAME}.predict([doc1, doc2])
#{VARNAME}.set_annotations([doc1, doc2], scores)
+table(["Name", "Type", "Description"])
+row
+cell #[code docs]
+cell iterable
+cell The documents to modify.
+row
+cell #[code scores]
+cell -
+cell The scores to set, produced by #[code #{CLASSNAME}.predict].
+h(2, "update") #{CLASSNAME}.update
+tag method
p
| Learn from a batch of documents and gold-standard information, updating
| the pipe's model. Delegates to #[code #{CLASSNAME}.predict] and
| #[code #{CLASSNAME}.get_loss].
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
losses = {}
optimizer = nlp.begin_training()
#{VARNAME}.update([doc1, doc2], [gold1, gold2], losses=losses, sgd=optimizer)
+table(["Name", "Type", "Description"])
+row
+cell #[code docs]
+cell iterable
+cell A batch of documents to learn from.
+row
+cell #[code golds]
+cell iterable
+cell The gold-standard data. Must have the same length as #[code docs].
+row
+cell #[code drop]
+cell int
+cell The dropout rate.
+row
+cell #[code sgd]
+cell callable
+cell
| The optimizer. Should take two arguments #[code weights] and
| #[code gradient], and an optional ID.
+row
+cell #[code losses]
+cell dict
+cell
| Optional record of the loss during training. The value keyed by
| the model's name is updated.
+h(2, "get_loss") #{CLASSNAME}.get_loss
+tag method
p
| Find the loss and gradient of loss for the batch of documents and their
| predicted scores.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
scores = #{VARNAME}.predict([doc1, doc2])
loss, d_loss = #{VARNAME}.get_loss([doc1, doc2], [gold1, gold2], scores)
+table(["Name", "Type", "Description"])
+row
+cell #[code docs]
+cell iterable
+cell The batch of documents.
+row
+cell #[code golds]
+cell iterable
+cell The gold-standard data. Must have the same length as #[code docs].
+row
+cell #[code scores]
+cell -
+cell Scores representing the model's predictions.
+row("foot")
+cell returns
+cell tuple
+cell The loss and the gradient, i.e. #[code (loss, gradient)].
+h(2, "begin_training") #{CLASSNAME}.begin_training
+tag method
p
| Initialize the pipe for training, using data exampes if available. If no
| model has been initialized yet, the model is added.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
nlp.pipeline.append(#{VARNAME})
#{VARNAME}.begin_training(pipeline=nlp.pipeline)
+table(["Name", "Type", "Description"])
+row
+cell #[code gold_tuples]
+cell iterable
+cell
| Optional gold-standard annotations from which to construct
| #[+api("goldparse") #[code GoldParse]] objects.
+row
+cell #[code pipeline]
+cell list
+cell
| Optional list of #[+api("pipe") #[code Pipe]] components that
| this component is part of.
+h(2, "use_params") #{CLASSNAME}.use_params
+tag method
+tag contextmanager
p Modify the pipe's model, to use the given parameter values.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
with #{VARNAME}.use_params():
#{VARNAME}.to_disk('/best_model')
+table(["Name", "Type", "Description"])
+row
+cell #[code params]
+cell -
+cell
| The parameter values to use in the model. At the end of the
| context, the original parameters are restored.
+h(2, "to_disk") #{CLASSNAME}.to_disk
+tag method
p Serialize the pipe to disk.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
#{VARNAME}.to_disk('/path/to/#{VARNAME}')
+table(["Name", "Type", "Description"])
+row
+cell #[code path]
+cell unicode or #[code Path]
+cell
| A path to a directory, which will be created if it doesn't exist.
| Paths may be either strings or #[code Path]-like objects.
+h(2, "from_disk") #{CLASSNAME}.from_disk
+tag method
p Load the pipe from disk. Modifies the object in place and returns it.
+aside-code("Example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
#{VARNAME}.from_disk('/path/to/#{VARNAME}')
+table(["Name", "Type", "Description"])
+row
+cell #[code path]
+cell unicode or #[code Path]
+cell
| A path to a directory. Paths may be either strings or
| #[code Path]-like objects.
+row("foot")
+cell returns
+cell #[code=CLASSNAME]
+cell The modified #[code=CLASSNAME] object.
+h(2, "to_bytes") #{CLASSNAME}.to_bytes
+tag method
+aside-code("example").
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
#{VARNAME}_bytes = #{VARNAME}.to_bytes()
p Serialize the pipe to a bytestring.
+table(["Name", "Type", "Description"])
+row
+cell #[code **exclude]
+cell -
+cell Named attributes to prevent from being serialized.
+row("foot")
+cell returns
+cell bytes
+cell The serialized form of the #[code=CLASSNAME] object.
+h(2, "from_bytes") #{CLASSNAME}.from_bytes
+tag method
p Load the pipe from a bytestring. Modifies the object in place and returns it.
+aside-code("Example").
#{VARNAME}_bytes = #{VARNAME}.to_bytes()
#{VARNAME} = #{CLASSNAME}(nlp.vocab)
#{VARNAME}.from_bytes(#{VARNAME}_bytes)
+table(["Name", "Type", "Description"])
+row
+cell #[code bytes_data]
+cell bytes
+cell The data to load from.
+row
+cell #[code **exclude]
+cell -
+cell Named attributes to prevent from being loaded.
+row("foot")
+cell returns
+cell #[code=CLASSNAME]
+cell The #[code=CLASSNAME] object.

32
website/docs/api/span.jade → website/api/span.jade
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > SPAN
include ../../_includes/_mixins
include ../_includes/_mixins
p A slice from a #[+api("doc") #[code Doc]] object.
@ -40,7 +40,7 @@ p Create a Span object from the #[code slice doc[start : end]].
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A meaning representation of the span.
+footrow
+row("foot")
+cell returns
+cell #[code Span]
+cell The newly constructed object.
@ -61,7 +61,7 @@ p Get a #[code Token] object.
+cell int
+cell The index of the token within the span.
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell The token at #[code span[i]].
@ -79,7 +79,7 @@ p Get a #[code Span] object.
+cell tuple
+cell The slice of the span to get.
+footrow
+row("foot")
+cell returns
+cell #[code Span]
+cell The span at #[code span[start : end]].
@ -95,7 +95,7 @@ p Iterate over #[code Token] objects.
assert [t.text for t in span] == ['it', 'back', '!']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A #[code Token] object.
@ -111,7 +111,7 @@ p Get the number of tokens in the span.
assert len(span) == 3
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of tokens in the span.
@ -140,7 +140,7 @@ p
| The object to compare with. By default, accepts #[code Doc],
| #[code Span], #[code Token] and #[code Lexeme] objects.
+footrow
+row("foot")
+cell returns
+cell float
+cell A scalar similarity score. Higher is more similar.
@ -167,7 +167,7 @@ p
+cell list
+cell A list of attribute ID ints.
+footrow
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[long, ndim=2]]
+cell
@ -194,7 +194,7 @@ p Retokenize the document, such that the span is merged into a single token.
| Attributes to assign to the merged token. By default, attributes
| are inherited from the syntactic root token of the span.
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell The newly merged token.
@ -216,7 +216,7 @@ p
assert new_york.root.text == 'York'
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell The root token.
@ -233,7 +233,7 @@ p Tokens that are to the left of the span, whose head is within the span.
assert lefts == [u'New']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A left-child of a token of the span.
@ -250,7 +250,7 @@ p Tokens that are to the right of the span, whose head is within the span.
assert rights == [u'in']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A right-child of a token of the span.
@ -267,7 +267,7 @@ p Tokens that descend from tokens in the span, but fall outside it.
assert subtree == [u'Give', u'it', u'back', u'!']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A descendant of a token within the span.
@ -285,7 +285,7 @@ p
assert doc[1:].has_vector
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the span has a vector data attached.
@ -304,7 +304,7 @@ p
assert doc[1:].vector.shape == (300,)
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A 1D numpy array representing the span's semantics.
@ -323,7 +323,7 @@ p
assert doc[1:].vector_norm != doc[2:].vector_norm
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell float
+cell The L2 norm of the vector representation.

22
website/docs/api/stringstore.jade → website/api/stringstore.jade
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > STRINGSTORE
include ../../_includes/_mixins
include ../_includes/_mixins
p
| Look up strings by 64-bit hashes. As of v2.0, spaCy uses hash values
@ -23,7 +23,7 @@ p
+cell iterable
+cell A sequence of unicode strings to add to the store.
+footrow
+row("foot")
+cell returns
+cell #[code StringStore]
+cell The newly constructed object.
@ -38,7 +38,7 @@ p Get the number of strings in the store.
assert len(stringstore) == 2
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of strings in the store.
@ -60,7 +60,7 @@ p Retrieve a string from a given hash, or vice versa.
+cell bytes, unicode or uint64
+cell The value to encode.
+footrow
+row("foot")
+cell returns
+cell unicode or int
+cell The value to be retrieved.
@ -81,7 +81,7 @@ p Check whether a string is in the store.
+cell unicode
+cell The string to check.
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the store contains the string.
@ -100,7 +100,7 @@ p
assert all_strings == [u'apple', u'orange']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell unicode
+cell A string in the store.
@ -125,7 +125,7 @@ p Add a string to the #[code StringStore].
+cell unicode
+cell The string to add.
+footrow
+row("foot")
+cell returns
+cell uint64
+cell The string's hash value.
@ -166,7 +166,7 @@ p Loads state from a directory. Modifies the object in place and returns it.
| A path to a directory. Paths may be either strings or
| #[code Path]-like objects.
+footrow
+row("foot")
+cell returns
+cell #[code StringStore]
+cell The modified #[code StringStore] object.
@ -185,7 +185,7 @@ p Serialize the current state to a binary string.
+cell -
+cell Named attributes to prevent from being serialized.
+footrow
+row("foot")
+cell returns
+cell bytes
+cell The serialized form of the #[code StringStore] object.
@ -211,7 +211,7 @@ p Load state from a binary string.
+cell -
+cell Named attributes to prevent from being loaded.
+footrow
+row("foot")
+cell returns
+cell #[code StringStore]
+cell The #[code StringStore] object.
@ -233,7 +233,7 @@ p Get a 64-bit hash for a given string.
+cell unicode
+cell The string to hash.
+footrow
+row("foot")
+cell returns
+cell uint64
+cell The hash.

5
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@ -0,0 +1,5 @@
//- 💫 DOCS > API > TAGGER
include ../_includes/_mixins
!=partial("pipe", { subclass: "Tagger", pipeline_id: "tagger" })

5
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@ -0,0 +1,5 @@
//- 💫 DOCS > API > TENSORIZER
include ../_includes/_mixins
!=partial("pipe", { subclass: "Tensorizer", pipeline_id: "tensorizer" })

19
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@ -0,0 +1,19 @@
//- 💫 DOCS > API > TEXTCATEGORIZER
include ../_includes/_mixins
p
| The model supports classification with multiple, non-mutually exclusive
| labels. You can change the model architecture rather easily, but by
| default, the #[code TextCategorizer] class uses a convolutional
| neural network to assign position-sensitive vectors to each word in the
| document. This step is similar to the #[+api("tensorizer") #[code Tensorizer]]
| component, but the #[code TextCategorizer] uses its own CNN model, to
| avoid sharing weights with the other pipeline components. The document
| tensor is then
| summarized by concatenating max and mean pooling, and a multilayer
| perceptron is used to predict an output vector of length #[code nr_class],
| before a logistic activation is applied elementwise. The value of each
| output neuron is the probability that some class is present.
!=partial("pipe", { subclass: "TextCategorizer", short: "textcat", pipeline_id: "textcat" })

45
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > TOKEN
include ../../_includes/_mixins
include ../_includes/_mixins
p An individual token — i.e. a word, punctuation symbol, whitespace, etc.
@ -30,7 +30,7 @@ p Construct a #[code Token] object.
+cell int
+cell The index of the token within the document.
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell The newly constructed object.
@ -46,7 +46,7 @@ p The number of unicode characters in the token, i.e. #[code token.text].
assert len(token) == 4
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of unicode characters in the token.
@ -68,7 +68,7 @@ p Check the value of a boolean flag.
+cell int
+cell The attribute ID of the flag to check.
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the flag is set.
@ -93,7 +93,7 @@ p Compute a semantic similarity estimate. Defaults to cosine over vectors.
| The object to compare with. By default, accepts #[code Doc],
| #[code Span], #[code Token] and #[code Lexeme] objects.
+footrow
+row("foot")
+cell returns
+cell float
+cell A scalar similarity score. Higher is more similar.
@ -114,7 +114,7 @@ p Get a neighboring token.
+cell int
+cell The relative position of the token to get. Defaults to #[code 1].
+footrow
+row("foot")
+cell returns
+cell #[code Token]
+cell The token at position #[code self.doc[self.i+i]].
@ -139,7 +139,7 @@ p
+cell #[code Token]
+cell Another token.
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether this token is the ancestor of the descendant.
@ -158,7 +158,7 @@ p The rightmost token of this token's syntactic descendants.
assert [t.text for t in he_ancestors] == [u'pleaded']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell
@ -177,7 +177,7 @@ p A sequence of coordinated tokens, including the token itself.
assert [t.text for t in apples_conjuncts] == [u'oranges']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A coordinated token.
@ -194,7 +194,7 @@ p A sequence of the token's immediate syntactic children.
assert [t.text for t in give_children] == [u'it', u'back', u'!']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A child token such that #[code child.head==self].
@ -211,7 +211,7 @@ p A sequence of all the token's syntactic descendents.
assert [t.text for t in give_subtree] == [u'Give', u'it', u'back', u'!']
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Token]
+cell A descendant token such that #[code self.is_ancestor(descendant)].
@ -230,7 +230,7 @@ p
assert apples.has_vector
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the token has a vector data attached.
@ -248,7 +248,7 @@ p A real-valued meaning representation.
assert apples.vector.shape == (300,)
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A 1D numpy array representing the token's semantics.
@ -268,7 +268,7 @@ p The L2 norm of the token's vector representation.
assert apples.vector_norm != pasta.vector_norm
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell float
+cell The L2 norm of the vector representation.
@ -280,20 +280,29 @@ p The L2 norm of the token's vector representation.
+cell #[code text]
+cell unicode
+cell Verbatim text content.
+row
+cell #[code text_with_ws]
+cell unicode
+cell Text content, with trailing space character if present.
+row
+cell #[code whitespace]
+cell int
+cell Trailing space character if present.
+row
+cell #[code whitespace_]
+cell unicode
+cell Trailing space character if present.
+row
+cell #[code orth]
+cell int
+cell ID of the verbatim text content.
+row
+cell #[code orth_]
+cell unicode
+cell
| Verbatim text content (identical to #[code Token.text]). Existst
| mostly for consistency with the other attributes.
+row
+cell #[code vocab]
+cell #[code Vocab]

16
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@ -1,6 +1,6 @@
//- 💫 DOCS > API > TOKENIZER
include ../../_includes/_mixins
include ../_includes/_mixins
p
| Segment text, and create #[code Doc] objects with the discovered segment
@ -57,7 +57,7 @@ p Create a #[code Tokenizer], to create #[code Doc] objects given unicode text.
+cell callable
+cell A boolean function matching strings to be recognised as tokens.
+footrow
+row("foot")
+cell returns
+cell #[code Tokenizer]
+cell The newly constructed object.
@ -77,7 +77,7 @@ p Tokenize a string.
+cell unicode
+cell The string to tokenize.
+footrow
+row("foot")
+cell returns
+cell #[code Doc]
+cell A container for linguistic annotations.
@ -110,7 +110,7 @@ p Tokenize a stream of texts.
| The number of threads to use, if the implementation supports
| multi-threading. The default tokenizer is single-threaded.
+footrow
+row("foot")
+cell yields
+cell #[code Doc]
+cell A sequence of Doc objects, in order.
@ -126,7 +126,7 @@ p Find internal split points of the string.
+cell unicode
+cell The string to split.
+footrow
+row("foot")
+cell returns
+cell list
+cell
@ -147,7 +147,7 @@ p
+cell unicode
+cell The string to segment.
+footrow
+row("foot")
+cell returns
+cell int
+cell The length of the prefix if present, otherwise #[code None].
@ -165,7 +165,7 @@ p
+cell unicode
+cell The string to segment.
+footrow
+row("foot")
+cell returns
+cell int / #[code None]
+cell The length of the suffix if present, otherwise #[code None].
@ -176,7 +176,7 @@ p
p
| Add a special-case tokenization rule. This mechanism is also used to add
| custom tokenizer exceptions to the language data. See the usage guide
| on #[+a("/docs/usage/adding-languages#tokenizer-exceptions") adding languages]
| on #[+a("/usage/adding-languages#tokenizer-exceptions") adding languages]
| for more details and examples.
+aside-code("Example").

24
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@ -0,0 +1,24 @@
//- 💫 DOCS > API > TOP-LEVEL
include ../_includes/_mixins
+section("spacy")
//-+h(2, "spacy") spaCy
//- spacy/__init__.py
include _top-level/_spacy
+section("displacy")
+h(2, "displacy", "spacy/displacy") displaCy
include _top-level/_displacy
+section("util")
+h(2, "util", "spacy/util.py") Utility functions
include _top-level/_util
+section("compat")
+h(2, "compat", "spacy/compaty.py") Compatibility functions
include _top-level/_compat
+section("cli", "spacy/cli")
+h(2, "cli") Command line
include _top-level/_cli

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@ -0,0 +1,333 @@
//- 💫 DOCS > API > VECTORS
include ../_includes/_mixins
p
| Vectors data is kept in the #[code Vectors.data] attribute, which should
| be an instance of #[code numpy.ndarray] (for CPU vectors) or
| #[code cupy.ndarray] (for GPU vectors).
+h(2, "init") Vectors.__init__
+tag method
p
| Create a new vector store. To keep the vector table empty, pass
| #[code data_or_width=0]. You can also create the vector table and add
| vectors one by one, or set the vector values directly on initialisation.
+aside-code("Example").
from spacy.vectors import Vectors
from spacy.strings import StringStore
empty_vectors = Vectors(StringStore())
vectors = Vectors([u'cat'], 300)
vectors[u'cat'] = numpy.random.uniform(-1, 1, (300,))
vector_table = numpy.zeros((3, 300), dtype='f')
vectors = Vectors(StringStore(), vector_table)
+table(["Name", "Type", "Description"])
+row
+cell #[code strings]
+cell #[code StringStore] or list
+cell
| List of strings, or a #[+api("stringstore") #[code StringStore]]
| that maps strings to hash values, and vice versa.
+row
+cell #[code data_or_width]
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']] or int
+cell Vector data or number of dimensions.
+row("foot")
+cell returns
+cell #[code Vectors]
+cell The newly created object.
+h(2, "getitem") Vectors.__getitem__
+tag method
p
| Get a vector by key. If key is a string, it is hashed to an integer ID
| using the #[code Vectors.strings] table. If the integer key is not found
| in the table, a #[code KeyError] is raised.
+aside-code("Example").
vectors = Vectors(StringStore(), 300)
vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
cat_vector = vectors[u'cat']
+table(["Name", "Type", "Description"])
+row
+cell #[code key]
+cell unicode / int
+cell The key to get the vector for.
+row
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell The vector for the key.
+h(2, "setitem") Vectors.__setitem__
+tag method
p
| Set a vector for the given key. If key is a string, it is hashed to an
| integer ID using the #[code Vectors.strings] table.
+aside-code("Example").
vectors = Vectors(StringStore(), 300)
vectors[u'cat'] = numpy.random.uniform(-1, 1, (300,))
+table(["Name", "Type", "Description"])
+row
+cell #[code key]
+cell unicode / int
+cell The key to set the vector for.
+row
+cell #[code vector]
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell The vector to set.
+h(2, "iter") Vectors.__iter__
+tag method
p Yield vectors from the table.
+aside-code("Example").
vector_table = numpy.zeros((3, 300), dtype='f')
vectors = Vectors(StringStore(), vector_table)
for vector in vectors:
print(vector)
+table(["Name", "Type", "Description"])
+row("foot")
+cell yields
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell A vector from the table.
+h(2, "len") Vectors.__len__
+tag method
p Return the number of vectors that have been assigned.
+aside-code("Example").
vector_table = numpy.zeros((3, 300), dtype='f')
vectors = Vectors(StringStore(), vector_table)
assert len(vectors) == 3
+table(["Name", "Type", "Description"])
+row("foot")
+cell returns
+cell int
+cell The number of vectors in the data.
+h(2, "contains") Vectors.__contains__
+tag method
p
| Check whether a key has a vector entry in the table. If key is a string,
| it is hashed to an integer ID using the #[code Vectors.strings] table.
+aside-code("Example").
vectors = Vectors(StringStore(), 300)
vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
assert u'cat' in vectors
+table(["Name", "Type", "Description"])
+row
+cell #[code key]
+cell unicode / int
+cell The key to check.
+row("foot")
+cell returns
+cell bool
+cell Whether the key has a vector entry.
+h(2, "add") Vectors.add
+tag method
p
| Add a key to the table, optionally setting a vector value as well. If
| key is a string, it is hashed to an integer ID using the
| #[code Vectors.strings] table.
+aside-code("Example").
vectors = Vectors(StringStore(), 300)
vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
+table(["Name", "Type", "Description"])
+row
+cell #[code key]
+cell unicode / int
+cell The key to add.
+row
+cell #[code vector]
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell An optional vector to add.
+h(2, "items") Vectors.items
+tag method
p Iterate over #[code (string key, vector)] pairs, in order.
+aside-code("Example").
vectors = Vectors(StringStore(), 300)
vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
for key, vector in vectors.items():
print(key, vector)
+table(["Name", "Type", "Description"])
+row("foot")
+cell yields
+cell tuple
+cell #[code (string key, vector)] pairs, in order.
+h(2, "shape") Vectors.shape
+tag property
p
| Get #[code (rows, dims)] tuples of number of rows and number of
| dimensions in the vector table.
+aside-code("Example").
vectors = Vectors(StringStore(), 300)
vectors.add(u'cat', numpy.random.uniform(-1, 1, (300,)))
rows, dims = vectors.shape
assert rows == 1
assert dims == 300
+table(["Name", "Type", "Description"])
+row("foot")
+cell returns
+cell tuple
+cell #[code (rows, dims)] pairs.
+h(2, "from_glove") Vectors.from_glove
+tag method
p
| Load #[+a("https://nlp.stanford.edu/projects/glove/") GloVe] vectors from
| a directory. Assumes binary format, that the vocab is in a
| #[code vocab.txt], and that vectors are named
| #[code vectors.{size}.[fd].bin], e.g. #[code vectors.128.f.bin] for 128d
| float32 vectors, #[code vectors.300.d.bin] for 300d float64 (double)
| vectors, etc. By default GloVe outputs 64-bit vectors.
+table(["Name", "Type", "Description"])
+row
+cell #[code path]
+cell unicode / #[code Path]
+cell The path to load the GloVe vectors from.
+h(2, "to_disk") Vectors.to_disk
+tag method
p Save the current state to a directory.
+aside-code("Example").
vectors.to_disk('/path/to/vectors')
+table(["Name", "Type", "Description"])
+row
+cell #[code path]
+cell unicode or #[code Path]
+cell
| A path to a directory, which will be created if it doesn't exist.
| Paths may be either strings or #[code Path]-like objects.
+h(2, "from_disk") Vectors.from_disk
+tag method
p Loads state from a directory. Modifies the object in place and returns it.
+aside-code("Example").
vectors = Vectors(StringStore())
vectors.from_disk('/path/to/vectors')
+table(["Name", "Type", "Description"])
+row
+cell #[code path]
+cell unicode or #[code Path]
+cell
| A path to a directory. Paths may be either strings or
| #[code Path]-like objects.
+row("foot")
+cell returns
+cell #[code Vectors]
+cell The modified #[code Vectors] object.
+h(2, "to_bytes") Vectors.to_bytes
+tag method
p Serialize the current state to a binary string.
+aside-code("Example").
vectors_bytes = vectors.to_bytes()
+table(["Name", "Type", "Description"])
+row
+cell #[code **exclude]
+cell -
+cell Named attributes to prevent from being serialized.
+row("foot")
+cell returns
+cell bytes
+cell The serialized form of the #[code Vectors] object.
+h(2, "from_bytes") Vectors.from_bytes
+tag method
p Load state from a binary string.
+aside-code("Example").
fron spacy.vectors import Vectors
vectors_bytes = vectors.to_bytes()
new_vectors = Vectors(StringStore())
new_vectors.from_bytes(vectors_bytes)
+table(["Name", "Type", "Description"])
+row
+cell #[code bytes_data]
+cell bytes
+cell The data to load from.
+row
+cell #[code **exclude]
+cell -
+cell Named attributes to prevent from being loaded.
+row("foot")
+cell returns
+cell #[code Vectors]
+cell The #[code Vectors] object.
+h(2, "attributes") Attributes
+table(["Name", "Type", "Description"])
+row
+cell #[code data]
+cell #[code numpy.ndarray] / #[code cupy.ndarray]
+cell
| Stored vectors data. #[code numpy] is used for CPU vectors,
| #[code cupy] for GPU vectors.
+row
+cell #[code key2row]
+cell dict
+cell
| Dictionary mapping word hashes to rows in the
| #[code Vectors.data] table.
+row
+cell #[code keys]
+cell #[code numpy.ndarray]
+cell
| Array keeping the keys in order, such that
| #[code keys[vectors.key2row[key]] == key]

131
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@ -1,17 +1,22 @@
//- 💫 DOCS > API > VOCAB
include ../../_includes/_mixins
include ../_includes/_mixins
p
| A lookup table that allows you to access #[code Lexeme] objects. The
| #[code Vocab] instance also provides access to the #[code StringStore],
| and owns underlying C-data that is shared between #[code Doc] objects.
| The #[code Vocab] object provides a lookup table that allows you to
| access #[+api("lexeme") #[code Lexeme]] objects, as well as the
| #[+api("stringstore") #[code StringStore]]. It also owns underlying
| C-data that is shared between #[code Doc] objects.
+h(2, "init") Vocab.__init__
+tag method
p Create the vocabulary.
+aside-code("Example").
from spacy.vocab import Vocab
vocab = Vocab(strings=[u'hello', u'world'])
+table(["Name", "Type", "Description"])
+row
+cell #[code lex_attr_getters]
@ -39,7 +44,7 @@ p Create the vocabulary.
| A #[+api("stringstore") #[code StringStore]] that maps
| strings to hash values, and vice versa, or a list of strings.
+footrow
+row("foot")
+cell returns
+cell #[code Vocab]
+cell The newly constructed object.
@ -54,7 +59,7 @@ p Get the current number of lexemes in the vocabulary.
assert len(nlp.vocab) > 0
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell returns
+cell int
+cell The number of lexems in the vocabulary.
@ -76,7 +81,7 @@ p
+cell int / unicode
+cell The hash value of a word, or its unicode string.
+footrow
+row("foot")
+cell returns
+cell #[code Lexeme]
+cell The lexeme indicated by the given ID.
@ -90,7 +95,7 @@ p Iterate over the lexemes in the vocabulary.
stop_words = (lex for lex in nlp.vocab if lex.is_stop)
+table(["Name", "Type", "Description"])
+footrow
+row("foot")
+cell yields
+cell #[code Lexeme]
+cell An entry in the vocabulary.
@ -115,7 +120,7 @@ p
+cell unicode
+cell The ID string.
+footrow
+row("foot")
+cell returns
+cell bool
+cell Whether the string has an entry in the vocabulary.
@ -152,11 +157,100 @@ p
| which the flag will be stored. If #[code -1], the lowest
| available bit will be chosen.
+footrow
+row("foot")
+cell returns
+cell int
+cell The integer ID by which the flag value can be checked.
+h(2, "add_flag") Vocab.clear_vectors
+tag method
+tag-new(2)
p
| Drop the current vector table. Because all vectors must be the same
| width, you have to call this to change the size of the vectors.
+aside-code("Example").
nlp.vocab.clear_vectors(new_dim=300)
+table(["Name", "Type", "Description"])
+row
+cell #[code new_dim]
+cell int
+cell
| Number of dimensions of the new vectors. If #[code None], size
| is not changed.
+h(2, "add_flag") Vocab.get_vector
+tag method
+tag-new(2)
p
| Retrieve a vector for a word in the vocabulary. Words can be looked up
| by string or hash value. If no vectors data is loaded, a
| #[code ValueError] is raised.
+aside-code("Example").
nlp.vocab.get_vector(u'apple')
+table(["Name", "Type", "Description"])
+row
+cell #[code orth]
+cell int / unicode
+cell The hash value of a word, or its unicode string.
+row("foot")
+cell returns
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell
| A word vector. Size and shape are determined by the
| #[code Vocab.vectors] instance.
+h(2, "add_flag") Vocab.set_vector
+tag method
+tag-new(2)
p
| Set a vector for a word in the vocabulary. Words can be referenced by
| by string or hash value.
+aside-code("Example").
nlp.vocab.set_vector(u'apple', array([...]))
+table(["Name", "Type", "Description"])
+row
+cell #[code orth]
+cell int / unicode
+cell The hash value of a word, or its unicode string.
+row
+cell #[code vector]
+cell #[code.u-break numpy.ndarray[ndim=1, dtype='float32']]
+cell The vector to set.
+h(2, "add_flag") Vocab.has_vector
+tag method
+tag-new(2)
p
| Check whether a word has a vector. Returns #[code False] if no vectors
| are loaded. Words can be looked up by string or hash value.
+aside-code("Example").
if nlp.vocab.has_vector(u'apple'):
vector = nlp.vocab.get_vector(u'apple')
+table(["Name", "Type", "Description"])
+row
+cell #[code orth]
+cell int / unicode
+cell The hash value of a word, or its unicode string.
+row("foot")
+cell returns
+cell bool
+cell Whether the word has a vector.
+h(2, "to_disk") Vocab.to_disk
+tag method
+tag-new(2)
@ -192,7 +286,7 @@ p Loads state from a directory. Modifies the object in place and returns it.
| A path to a directory. Paths may be either strings or
| #[code Path]-like objects.
+footrow
+row("foot")
+cell returns
+cell #[code Vocab]
+cell The modified #[code Vocab] object.
@ -211,7 +305,7 @@ p Serialize the current state to a binary string.
+cell -
+cell Named attributes to prevent from being serialized.
+footrow
+row("foot")
+cell returns
+cell bytes
+cell The serialized form of the #[code Vocab] object.
@ -238,7 +332,7 @@ p Load state from a binary string.
+cell -
+cell Named attributes to prevent from being loaded.
+footrow
+row("foot")
+cell returns
+cell #[code Vocab]
+cell The #[code Vocab] object.
@ -256,3 +350,14 @@ p Load state from a binary string.
+cell #[code strings]
+cell #[code StringStore]
+cell A table managing the string-to-int mapping.
+row
+cell #[code vectors]
+tag-new(2)
+cell #[code Vectors]
+cell A table associating word IDs to word vectors.
+row
+cell #[code vectors_length]
+cell int
+cell Number of dimensions for each word vector.

7
website/assets/css/_base/_animations.sass
View File

@ -19,3 +19,10 @@
to
transform: translate3d(0, 0, 0)
//- Element rotates
@keyframes rotate
to
transform: rotate(360deg)

44
website/assets/css/_base/_fonts.sass
View File

@ -1,41 +1,27 @@
//- 💫 CSS > BASE > FONTS
// Source Sans Pro
// HK Grotesk
@font-face
font-family: "Source Sans Pro"
font-family: "HK Grotesk"
font-style: normal
font-weight: 400
src: url("/assets/fonts/sourcesanspro-regular.eot")
src: url("/assets/fonts/sourcesanspro-regular.eot?#iefix") format("embedded-opentype"), url("/assets/fonts/sourcesanspro-regular.woff2") format("woff2"), url("/assets/fonts/sourcesanspro-regular.woff") format("woff"), url("/assets/fonts/sourcesanspro-regular.ttf") format("truetype"), url("/assets/fonts/sourcesanspro-regular.svg#source_sans_proregular") format("svg")
font-weight: 500
src: url("/assets/fonts/hkgrotesk-semibold.woff2") format("woff2"), url("/assets/fonts/hkgrotesk-semibold.woff") format("woff")
@font-face
font-family: "Source Sans Pro"
font-family: "HK Grotesk"
font-style: italic
font-weight: 400
src: url("/assets/fonts/sourcesanspro-italic.eot")
src: url("/assets/fonts/sourcesanspro-italic.eot?#iefix") format("embedded-opentype"), url("/assets/fonts/sourcesanspro-italic.woff2") format("woff2"), url("/assets/fonts/sourcesanspro-italic.woff") format("woff"), url("/assets/fonts/sourcesanspro-italic.ttf") format("truetype"), url("/assets/fonts/sourcesanspro-italic.svg#source_sans_proitalic") format("svg")
font-weight: 500
src: url("/assets/fonts/hkgrotesk-semibolditalic.woff2") format("woff2"), url("/assets/fonts/hkgrotesk-semibolditalic.woff") format("woff")
@font-face
font-family: "Source Sans Pro"
font-style: normal
font-weight: 700
src: url("/assets/fonts/sourcesanspro-bold.eot")
src: url("/assets/fonts/sourcesanspro-bold.eot?#iefix") format("embedded-opentype"), url("/assets/fonts/sourcesanspro-bold.woff2") format("woff2"), url("/assets/fonts/sourcesanspro-bold.woff") format("woff"), url("/assets/fonts/sourcesanspro-bold.ttf") format("truetype"), url("/assets/fonts/sourcesanspro-bold.svg#source_sans_probold") format("svg")
@font-face
font-family: "Source Sans Pro"
font-style: italic
font-weight: 700
src: url("/assets/fonts/sourcesanspro-bolditalic.eot")
src: url("/assets/fonts/sourcesanspro-bolditalic.eot?#iefix") format("embedded-opentype"), url("/assets/fonts/sourcesanspro-bolditalic.woff2") format("woff2"), url("/assets/fonts/sourcesanspro-bolditalic.woff") format("woff"), url("/assets/fonts/sourcesanspro-bolditalic.ttf") format("truetype"), url("/assets/fonts/sourcesanspro-bolditalic.svg#source_sans_probold_italic") format("svg")
// Source Code Pro
@font-face
font-family: "Source Code Pro"
font-family: "HK Grotesk"
font-style: normal
font-weight: 600
src: url("/assets/fonts/sourcecodepro-semibold.eot")
src: url("/assets/fonts/sourcecodepro-semibold.eot?#iefix") format("embedded-opentype"), url("/assets/fonts/sourcecodepro-semibold.woff") format("woff"), url("/assets/fonts/sourcecodepro-semibold.ttf") format("truetype"), url("/assets/fonts/sourcecodepro-semibold.svg#sourcecodepro_semibold") format("svg")
src: url("/assets/fonts/hkgrotesk-bold.woff2") format("woff2"), url("/assets/fonts/hkgrotesk-bold.woff") format("woff")
@font-face
font-family: "HK Grotesk"
font-style: italic
font-weight: 600
src: url("/assets/fonts/hkgrotesk-bolditalic.woff2") format("woff2"), url("/assets/fonts/hkgrotesk-bolditalic.woff") format("woff")

10
website/assets/css/_base/_grid.sass
View File

@ -15,6 +15,15 @@
align-items: center
justify-content: center
&.o-grid--vcenter
align-items: center
&.o-grid--space
justify-content: space-between
&.o-grid--nowrap
flex-wrap: nowrap
//- Grid column
@ -22,7 +31,6 @@
$grid-gutter: 2rem
margin-top: $grid-gutter
overflow: hidden
@include breakpoint(min, lg)
display: flex

4
website/assets/css/_base/_layout.sass
View File

@ -12,6 +12,7 @@ body
animation: fadeIn 0.25s ease
background: $color-back
color: $color-front
//scroll-behavior: smooth
//- Paragraphs
@ -19,6 +20,9 @@ body
p
@extend .o-block, .u-text
p:empty
margin-bottom: 0
//- Links

79
website/assets/css/_base/_objects.sass
View File

@ -43,12 +43,25 @@
position: relative
padding: 2.5rem 0
overflow: auto
background: $color-subtle-light
.o-main &
border-top-left-radius: $border-radius
//- Blocks
.o-section
width: 100%
max-width: 100%
&:not(:last-child)
margin-bottom: 7rem
padding-bottom: 4rem
border-bottom: 1px dotted $color-subtle
.o-block
margin-bottom: 3rem
margin-bottom: 4rem
.o-block-small
margin-bottom: 2rem
@ -58,17 +71,18 @@
.o-card
background: $color-back
border-radius: 2px
border: 1px solid $color-subtle
padding: 3rem 2.5%
border-radius: $border-radius
box-shadow: $box-shadow
//- Box
.o-box
background: $color-theme-light
background: $color-subtle-light
padding: 2rem
border-left: 4px solid $color-theme
border-radius: $border-radius
.o-box__logos
padding-bottom: 1rem
//- Icons
@ -77,7 +91,14 @@
vertical-align: middle
&.o-icon--inline
margin: 0 0.5rem 0 0.25rem
margin: 0 0.5rem 0 0.1rem
.o-emoji
margin-right: 0.75rem
vertical-align: text-bottom
.o-badge
border-radius: 1em
//- SVG
@ -102,3 +123,45 @@
fill: currentColor
vertical-align: middle
margin: 0 0.5rem
//- Embeds
.o-chart
max-width: 100%
.cp_embed_iframe
border: 1px solid $color-subtle
border-radius: $border-radius
//- Form fields
.o-field
background: $color-back
padding: 0 0.25em
border-radius: 2em
border: 1px solid $color-subtle
margin-bottom: 0.25rem
.o-field__input,
.o-field__button
padding: 0 0.35em
.o-field__input
width: 100%
.o-field__select
background: transparent
color: $color-dark
height: 1.4em
border: none
text-align-last: center
.o-empty:empty:before
@include size(1em)
border-radius: 50%
content: ""
display: inline-block
background: $color-red
vertical-align: middle

7
website/assets/css/_base/_reset.sass
View File

@ -1,6 +1,6 @@
//- 💫 CSS > BASE > RESET
*
*, *:before, *:after
box-sizing: border-box
padding: 0
margin: 0
@ -94,7 +94,10 @@ ul, ol
input, button
appearance: none
background: transparent
button
background: transparent
cursor: pointer
progress
appearance: none

153
website/assets/css/_base/_utilities.sass
View File

@ -2,38 +2,53 @@
//- Text
.u-text,
.u-text-small,
.u-text-tiny
font-family: $font-primary
.u-text
font: 1.5rem/#{1.55} $font-primary
font-size: 1.35rem
line-height: 1.5
.u-text-small
font: 1.4rem/#{1.375} $font-primary
font-size: 1.3rem
line-height: 1.375
.u-text-tiny
font: 1.1rem/#{1.375} $font-primary
font-size: 1.1rem
line-height: 1.375
//- Labels & Tags
.u-text-label
font: normal 600 1.4rem/#{1.5} $font-code
font: normal 600 1.4rem/#{1.5} $font-secondary
text-transform: uppercase
&.u-text-label--light,
&.u-text-label--dark
display: inline-block
border-radius: 1em
padding: 0 1rem 0.15rem
&.u-text-label--dark
background: $color-dark
box-shadow: inset 1px 1px 1px rgba($color-front, 0.25)
color: $color-back
padding: 0 0.75rem
margin: 1.5rem 0 0 2rem
border-radius: 2px
&.u-text-label--light
background: $color-back
color: $color-theme
margin-bottom: 1rem
.u-text-tag
display: inline-block
font: 600 1.1rem/#{1} $font-code
font: 600 1.1rem/#{1} $font-secondary
background: $color-theme
color: $color-back
padding: 0.15em 0.25em
border-radius: 2px
padding: 0.15em 0.5em 0.35em
border-radius: 1em
text-transform: uppercase
vertical-align: middle
@ -45,7 +60,7 @@
//- Headings
.u-heading
margin-bottom: 2rem
margin-bottom: 1em
@include breakpoint(max, md)
word-wrap: break-word
@ -53,12 +68,29 @@
&:not(:first-child)
padding-top: 3.5rem
&.u-heading--title:after
content: ""
display: block
width: 10%
min-width: 6rem
height: 6px
background: $color-theme
margin-top: 3rem
.u-heading-0
font: normal bold 7rem/#{1} $font-primary
font: normal 600 7rem/#{1} $font-secondary
@include breakpoint(max, sm)
font-size: 6rem
@each $level, $size in $headings
.u-heading-#{$level}
font: normal bold #{$size}rem/#{1.25} $font-primary
font: normal 500 #{$size}rem/#{1.1} $font-secondary
.u-heading__teaser
margin-top: 2rem
font-weight: normal
//- Links
@ -66,31 +98,59 @@
.u-link
color: $color-theme
border-bottom: 1px solid
transition: color 0.2s ease
&:hover
color: $color-theme-dark
.u-hide-link.u-hide-link
border: none
color: inherit
&:hover
color: inherit
.u-permalink
position: relative
&:before
content: "\00b6"
font-size: 0.9em
font-weight: normal
color: $color-subtle
@include position(absolute, top, left, 0.15em, -2.85rem)
opacity: 0
transition: opacity 0.2s ease
&:hover:before
opacity: 1
&:active:before
color: $color-theme
&:target
display: inline-block
&:before
bottom: 0.15em
top: initial
[id]:target
padding-top: $nav-height * 1.25
& + *
margin-top: $nav-height * 1.25
.u-permalink__icon
@include position(absolute, bottom, left, 0.35em, -2.75rem)
@include size(1.5rem)
color: $color-subtle
.u-permalink:hover &
color: $color-subtle-dark
.u-permalink:active &
color: $color-theme
//- Layout
.u-float-left
float: left
margin-right: 1rem
.u-float-right
float: right
margin-left: 1rem
.u-text-center
text-align: center
@ -104,14 +164,20 @@
padding: 0.5em 0.75em
.u-padding-medium
padding: 2.5rem
padding: 1.8rem
.u-inline-block
display: inline-block
.u-flex-full
flex: 1
.u-nowrap
white-space: nowrap
.u-wrap
white-space: pre-wrap
.u-break.u-break
word-wrap: break-word
white-space: initial
@ -123,13 +189,10 @@
border: 1px solid $color-subtle
border-radius: 2px
.u-border-bottom
border: 1px solid $color-subtle
.u-border-dotted
border-top: 1px dotted $color-subtle
border-bottom: 1px dotted $color-subtle
@each $name, $color in (theme: $color-theme, subtle: $color-subtle-dark, light: $color-back, red: $color-red, green: $color-green, yellow: $color-yellow)
@each $name, $color in (theme: $color-theme, dark: $color-dark, subtle: $color-subtle-dark, light: $color-back, red: $color-red, green: $color-green, yellow: $color-yellow)
.u-color-#{$name}
color: $color
@ -145,6 +208,32 @@
background: $pattern
//- Loaders
.u-loading,
[data-loading]
$spinner-size: 75px
$spinner-bar: 8px
position: relative
& > *
opacity: 0.35
&:before
@include position(absolute, top, left, 0, 0)
@include size($spinner-size)
right: 0
bottom: 0
margin: auto
content: ""
border: $spinner-bar solid $color-subtle
border-right: $spinner-bar solid $color-theme
border-radius: 50%
animation: rotate 1s linear infinite
z-index: 10
//- Hidden elements
.u-hidden

6
website/assets/css/_components/_asides.sass
View File

@ -10,6 +10,8 @@
.c-aside__content
background: $color-front
border-top-left-radius: $border-radius
border-bottom-left-radius: $border-radius
z-index: 10
@include breakpoint(min, md)
@ -21,12 +23,12 @@
&:after
$triangle-size: 2rem
@include position(absolute, bottom, left, -$triangle-size / 2, 0)
@include position(absolute, bottom, left, -$triangle-size / 2, $border-radius / 2)
@include size(0)
border-color: transparent
border-style: solid
border-top-color: $color-dark
border-width: $triangle-size / 2 0 0 $triangle-size
border-width: $triangle-size / 2 0 0 calc(#{$triangle-size} - #{$border-radius / 2})
content: ""
@include breakpoint(max, sm)

41
website/assets/css/_components/_buttons.sass
View File

@ -3,23 +3,50 @@
.c-button
display: inline-block
font-weight: bold
padding: 0.75em 1em
padding: 0.8em 1.1em 1em
margin-bottom: 1px
border: 2px solid
border-radius: 2px
border: 2px solid $color-theme
border-radius: 2em
text-align: center
transition: background 0.25s ease
transition: background-color, color 0.25s ease
&:hover
border-color: $color-theme-dark
&.c-button--small
font-size: 1.1rem
padding: 0.65rem 1.1rem 0.825rem
&.c-button--primary
background: $color-theme
color: $color-back
border-color: $color-theme
&:hover
background: $color-theme-dark
border-color: $color-theme-dark
&.c-button--secondary
background: $color-back
color: $color-theme
border-color: $color-theme
&:hover
color: $color-theme-dark
&.c-button--secondary-light
background: transparent
color: $color-back
border-color: $color-back
.c-icon-button
@include size(35px)
background: $color-subtle-light
color: $color-subtle-dark
border-radius: 50%
padding: 0.5rem
transition: color 0.2s ease
&:hover
color: $color-theme
&.c-icon-button--right
float: right
margin-left: 3rem

27
website/assets/css/_components/_chat.sass
View File

@ -24,9 +24,9 @@
transform: translateX(110%)
&:before
@include position(absolute, top, left, 1rem, 2rem)
@include position(absolute, top, left, 1.25rem, 2rem)
content: attr(data-title)
font: bold 1.4rem $font-code
font: bold 1.4rem $font-secondary
text-transform: uppercase
color: $color-back
@ -88,13 +88,18 @@
background-image: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0Ij48cGF0aCBmaWxsPSIjZmZmIiBkPSJNMTguOTg0IDYuNDIybC01LjU3OCA1LjU3OCA1LjU3OCA1LjU3OC0xLjQwNiAxLjQwNi01LjU3OC01LjU3OC01LjU3OCA1LjU3OC0xLjQwNi0xLjQwNiA1LjU3OC01LjU3OC01LjU3OC01LjU3OCAxLjQwNi0xLjQwNiA1LjU3OCA1LjU3OCA1LjU3OC01LjU3OHoiPjwvcGF0aD48L3N2Zz4=)
.c-chat__button
@include position(fixed, bottom, right, 0, 2rem)
padding: 1rem 1.5rem
background: $color-front
@include position(fixed, bottom, right, 1.5rem, 1.5rem)
z-index: 5
color: $color-back
border-top-left-radius: 4px
border-top-right-radius: 4px
z-index: 20
border-color: $color-theme
border-style: solid
border-width: 1px 1px 0 1px
background: $color-front
border-radius: 1em
padding: 0.5rem 1.15rem 0.35rem
opacity: 0.7
transition: opacity 0.2s ease
&:hover
opacity: 1
.gitter-open-chat-button
display: none

29
website/assets/css/_components/_code.sass
View File

@ -4,9 +4,9 @@
.c-code-block
background: $color-front
color: $color-back
color: darken($color-back, 20)
padding: 0.75em 0
border-radius: 2px
border-radius: $border-radius
overflow: auto
width: 100%
max-width: 100%
@ -16,6 +16,8 @@
&.c-code-block--has-icon
padding: 0
display: flex
border-top-left-radius: 0
border-bottom-left-radius: 0
.c-code-block__icon
padding: 0 0 0 1rem
@ -43,17 +45,26 @@
opacity: 0.5
//- Code
code
-webkit-font-smoothing: subpixel-antialiased
-moz-osx-font-smoothing: auto
//- Inline code
*:not(a):not(.c-code-block) > code
color: $color-dark
*:not(.c-code-block) > code
font: normal 600 0.8em/#{1} $font-code
background: darken($color-theme-light, 5)
box-shadow: 1px 1px 0 rgba($color-front, 0.05)
text-shadow: 1px 1px 0 rgba($color-back, 0.5)
color: $color-front
padding: 0.1em 0.5em
font-size: 90%
background-color: $color-subtle-light
padding: 0.2rem 0.4rem
border-radius: 0.25rem
font-family: $font-code
white-space: nowrap
margin: 0
border-radius: 1px
box-decoration-break: clone
white-space: nowrap

39
website/assets/css/_components/_landing.sass
View File

@ -2,12 +2,11 @@
.c-landing
background: $color-theme
padding-top: 5rem
padding-top: $nav-height * 1.5
width: 100%
.c-landing__wrapper
background: $pattern
padding-bottom: 6rem
width: 100%
.c-landing__content
@ -15,9 +14,45 @@
width: 100%
min-height: 573px
.c-landing__headlines
position: relative
top: -1.5rem
left: 1rem
.c-landing__title
color: $color-back
text-align: center
margin-bottom: 0.75rem
.c-landing__blocks
@include breakpoint(min, sm)
position: relative
top: -25rem
margin-bottom: -25rem
.c-landing__card
padding: 3rem 2.5rem
.c-landing__banner
background: $color-theme
.c-landing__banner__content
@include breakpoint(min, md)
border: 4px solid
padding: 1rem 6.5rem 2rem 4rem
.c-landing__banner__text
font-weight: 500
strong
font-weight: 800
p
font-size: 1.5rem
@include breakpoint(min, md)
padding-top: 7rem
.c-landing__badge
transform: rotate(7deg)

5
website/assets/css/_components/_lists.sass
View File

@ -9,6 +9,8 @@
.c-list__item:before
content: counter(li, #{$counter}) '.'
font-size: 1em
padding-right: 1rem
//- List Item
@ -21,13 +23,14 @@
&:before
content: '\25CF'
display: inline-block
font-size: 1em
font-size: 0.6em
font-weight: bold
padding-right: 1.25rem
margin-left: -3.75rem
text-align: right
width: 2.5rem
counter-increment: li
box-sizing: content-box
//- List icon

5
website/assets/css/_components/_misc.sass
View File

@ -3,9 +3,8 @@
.x-terminal
background: $color-subtle-light
color: $color-front
padding: 4px
border: 1px dotted $color-subtle
border-radius: 5px
padding: $border-radius
border-radius: 1em
width: 100%
.x-terminal__icons

26
website/assets/css/_components/_navigation.sass
View File

@ -1,22 +1,21 @@
//- 💫 CSS > COMPONENTS > NAVIGATION
.c-nav
@include position(absolute, top, left, 0, 0)
@include position(fixed, top, left, 0, 0)
@include size(100%, $nav-height)
background: $color-back
color: $color-theme
align-items: center
display: flex
justify-content: space-between
flex-flow: row wrap
padding: 0 2rem 0 1rem
z-index: 20
z-index: 30
width: 100%
border-bottom: 1px solid $color-subtle
box-shadow: $box-shadow
&.c-nav--theme
background: $color-theme
color: $color-back
border-bottom: none
//@include breakpoint(min, md)
// position: fixed
&.is-fixed
animation: slideInDown 0.5s ease-in-out
@ -28,12 +27,21 @@
justify-content: flex-end
flex-flow: row nowrap
border-color: inherit
flex: 1
.c-nav__menu__item
display: flex
align-items: center
height: 100%
text-transform: uppercase
font-family: $font-secondary
font-size: 1.6rem
font-weight: bold
color: $color-theme
&:not(:last-child)
margin-right: 1em
&:not(:first-child)
margin-left: 2em
&.is-active
color: $color-dark
pointer-events: none

24
website/assets/css/_components/_progress.sass Normal file
View File

@ -0,0 +1,24 @@
//- 💫 CSS > COMPONENTS > PROGRESS
.c-progress
display: block
flex: 105%
width: 105%
height: 3px
color: $color-theme
background: transparent
border: none
position: absolute
bottom: 0
left: -2.5%
&::-webkit-progress-bar
background: $color-back
border-radius: none
&::-webkit-progress-value
background: $color-theme
border-radius: none
&::-moz-progress-bar
background: $color-theme

10
website/assets/css/_components/_quickstart.sass
View File

@ -1,14 +1,17 @@
//- 💫 CSS > COMPONENTS > QUICKSTART
.c-quickstart
border: 1px solid $color-subtle
border-radius: 2px
border-radius: $border-radius
display: none
background: $color-subtle-light
&:not([style]) + .c-quickstart__info
display: none
.c-code-block
border-top-left-radius: 0
border-top-right-radius: 0
.c-quickstart__content
padding: 2rem 3rem
@ -72,7 +75,6 @@
flex: 100%
.c-quickstart__legend
color: $color-subtle-dark
margin-right: 2rem
padding-top: 0.75rem
flex: 1 1 35%
@ -95,4 +97,4 @@
padding: 1.5rem 0
.c-quickstart__code
font-size: 1.6rem
font-size: 1.4rem

65
website/assets/css/_components/_sidebar.sass
View File

@ -3,16 +3,15 @@
//- Sidebar container
.c-sidebar
background: $color-subtle-light
overflow-y: auto
@include breakpoint(min, md)
@include position(fixed, top, left, 0, 0)
@include size($sidebar-width, 100vh)
@include size($sidebar-width, calc(100vh - 3px))
@include scroll-shadow($color-back, $color-front, $nav-height)
flex: 0 0 $sidebar-width
padding: calc(#{$nav-height} + 1.5rem) 0 0
z-index: 10
border-right: 1px solid $color-subtle
@include breakpoint(max, sm)
flex: 100%
@ -27,7 +26,7 @@
.c-sidebar__section
& > *
padding: 0 2rem
padding: 0 2rem 0.35rem
@include breakpoint(max, sm)
flex: 1 1 0
@ -38,7 +37,59 @@
&:not(:last-child)
border-right: 1px solid $color-subtle
.is-active
font-weight: bold
.c-sidebar__item
color: $color-theme
background: rgba($color-subtle, 0.4)
&:hover
color: $color-theme-dark
& > .is-active
font-weight: bold
color: $color-dark
margin-top: 1rem
//- Sidebar subsections
$crumb-bullet: 14px
$crumb-bar: 2px
.c-sidebar__crumb
display: block
padding-top: 1rem
padding-left: 1rem
position: relative
.c-sidebar__crumb__item
margin-bottom: $crumb-bullet / 2
position: relative
padding-left: 2rem
color: $color-theme
font-size: 1.2rem
&:hover
color: $color-theme-dark
&:after
@include size($crumb-bullet)
@include position(absolute, top, left, $crumb-bullet / 4, 0)
content: ""
border-radius: 50%
background: $color-theme
z-index: 10
&:not(:last-child):before
@include size($crumb-bar, 100%)
@include position(absolute, top, left, $crumb-bullet, ($crumb-bullet - $crumb-bar) / 2)
content: ""
background: $color-subtle
&:first-child:before
height: calc(100% + #{$crumb-bullet * 2})
top: -$crumb-bullet / 2
&.is-active
color: $color-dark
&:after
background: $color-dark

3
website/assets/css/_components/_tables.sass
View File

@ -9,7 +9,7 @@
//- Table row
.c-table__row
&:nth-child(odd)
&:nth-child(odd):not(.c-table__row--head)
background: rgba($color-subtle-light, 0.35)
&.c-table__row--foot
@ -38,7 +38,6 @@
.c-table__head-cell
font-weight: bold
color: $color-theme
background: $color-back
padding: 1rem 0.5rem
border-bottom: 2px solid $color-theme

18
website/assets/css/_components/_tooltips.sass
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@ -4,24 +4,34 @@
position: relative
@include breakpoint(min, sm)
&[data-tooltip-style="code"]:before
-webkit-font-smoothing: subpixel-antialiased
-moz-osx-font-smoothing: auto
padding: 0.35em 0.85em 0.45em
font: normal 1rem/#{1.25} $font-code
white-space: nowrap
min-width: auto
&:before
@include position(absolute, top, left, 125%, 50%)
display: inline-block
content: attr(data-tooltip)
background: $color-front
border-radius: 2px
border-radius: $border-radius
border: 1px solid rgba($color-subtle-dark, 0.5)
color: $color-back
font: normal 1.3rem/#{1.25} $font-primary
font: normal 1.2rem/#{1.25} $font-primary
text-transform: none
text-align: left
opacity: 0
padding: 0.5em 0.75em
transform: translateX(-50%) translateY(-2px)
transition: opacity 0.1s ease-out, transform 0.1s ease-out
visibility: hidden
min-width: 200px
max-width: 300px
min-width: 200px
padding: 0.75em 1em 1em
z-index: 200
white-space: pre-wrap
&:hover:before
opacity: 1

17
website/assets/css/_mixins.sass
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@ -42,8 +42,8 @@
// $scroll-shadow-side - side to cover shadow (left or right)
// $scroll-shadow-background - original background color to match
@mixin scroll-shadow-base($scroll-shadow-color)
background: radial-gradient(left, ellipse, rgba(0,0,0, .2) 0%, rgba(0,0,0, 0) 75%) 0 center, radial-gradient(right, ellipse, rgba(0,0,0, .2) 0%, rgba(0,0,0, 0) 75%) 100% center
@mixin scroll-shadow-base($scroll-shadow-color, $scroll-shadow-intensity: 0.2)
background: radial-gradient(ellipse at 0 50%, rgba($scroll-shadow-color, $scroll-shadow-intensity) 0%, rgba(0,0,0,0) 75%) 0 center, radial-gradient(ellipse at 100% 50%, rgba($scroll-shadow-color, $scroll-shadow-intensity) 0%, transparent 75%) 100% center
background-attachment: scroll, scroll
background-repeat: no-repeat
background-size: 10px 100%, 10px 100%
@ -58,3 +58,16 @@
background-image: linear-gradient(to #{$scroll-gradient-direction}, rgba($scroll-shadow-background, 1) 50%, rgba($scroll-shadow-background, 0) 100%)
background-repeat: no-repeat
background-size: 20px 100%
// Full vertical scroll shadows
// adapted from: https://codepen.io/laustdeleuran/pen/DBaAu
@mixin scroll-shadow($background-color, $shadow-color, $shadow-offset: 0, $shadow-intensity: 0.4, $cover-size: 40px, $shadow-size: 15px)
background: linear-gradient($background-color 30%, rgba($background-color,0)) 0 $shadow-offset, linear-gradient(rgba($background-color,0), $background-color 70%) 0 100%, radial-gradient(50% 0, farthest-side, rgba($shadow-color,$shadow-intensity), rgba($shadow-color,0)) 0 $shadow-offset, radial-gradient(50% 100%,farthest-side, rgba($shadow-color,$shadow-intensity), rgba($shadow-color,0)) 0 100%
background: linear-gradient($background-color 30%, rgba($background-color,0)) 0 $shadow-offset, linear-gradient(rgba($background-color,0), $background-color 70%) 0 100%, radial-gradient(farthest-side at 50% 0, rgba($shadow-color,$shadow-intensity), rgba($shadow-color,0)) -20px $shadow-offset, radial-gradient(farthest-side at 50% 100%, rgba($shadow-color, $shadow-intensity), rgba($shadow-color,0)) 0 100%
background-repeat: no-repeat
background-color: $background-color
background-size: 100% $cover-size, 100% $cover-size, 100% $shadow-size, 100% $shadow-size
background-attachment: local, local, scroll, scroll

25
website/assets/css/_variables.sass
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@ -4,47 +4,48 @@
$type-base: 11px
$nav-height: 45px
$nav-height: 55px
$content-width: 1250px
$sidebar-width: 200px
$aside-width: 30vw
$sidebar-width: 235px
$aside-width: 27.5vw
$aside-padding: 25px
$border-radius: 6px
$logo-width: 85px
$logo-height: 27px
$grid: ( quarter: 4, third: 3, half: 2, two-thirds: 1.5, three-quarters: 1.33 )
$breakpoints: ( sm: 768px, md: 992px, lg: 1200px )
$headings: (1: 3, 2: 2.6, 3: 2, 4: 1.8, 5: 1.5)
$headings: (1: 4.4, 2: 3.4, 3: 2.6, 4: 2.2, 5: 1.8)
// Fonts
$font-primary: "Source Sans Pro", Tahoma, Geneva, sans-serif !default
$font-code: 'Source Code Pro', Consolas, 'Andale Mono', Menlo, Monaco, Courier, monospace !default
$font-primary: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol" !default
$font-secondary: "HK Grotesk", Roboto, Helvetica, Arial, sans-serif !default
$font-code: Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace !default
// Colors
$colors: ( blue: #09a3d5, red: #d9515d, green: #08c35e )
$colors: ( blue: #09a3d5, green: #05b083 )
$color-back: #fff !default
$color-front: #1a1e23 !default
$color-dark: lighten($color-front, 20) !default
$color-theme: map-get($colors, $theme)
$color-theme-dark: darken(map-get($colors, $theme), 5)
$color-theme-dark: darken(map-get($colors, $theme), 10)
$color-theme-light: rgba($color-theme, 0.05)
$color-subtle: #ddd !default
$color-subtle-light: #f6f6f6 !default
$color-subtle-dark: #949e9b !default
$color-red: #d9515d
$color-green: #3ec930
$color-red: #ef476f
$color-green: #7ddf64
$color-yellow: #f4c025
$syntax-highlighting: ( comment: #949e9b, tag: #b084eb, number: #b084eb, selector: #ffb86c, operator: #ff2c6d, function: #35b3dc, keyword: #ff2c6d, regex: #f4c025 )
$pattern: $color-theme url("/assets/img/pattern_#{$theme}.jpg") center top repeat
$pattern-overlay: transparent url("/assets/img/pattern_landing.jpg") center -138px no-repeat
$box-shadow: 0 1px 5px rgba(0, 0, 0, 0.2)

1
website/assets/css/style.sass
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@ -30,6 +30,7 @@ $theme: blue !default
@import _components/lists
@import _components/misc
@import _components/navigation
@import _components/progress
@import _components/sidebar
@import _components/tables
@import _components/quickstart

4
website/assets/css/style_red.sass
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@ -1,4 +0,0 @@
//- 💫 STYLESHEET (RED)
$theme: red
@import style

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244
website/assets/fonts/sourcecodepro-semibold.svg
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@ -1,244 +0,0 @@
<?xml version="1.0" standalone="no"?>
<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd" >
<svg xmlns="http://www.w3.org/2000/svg">
<metadata></metadata>
<defs>
<font id="source_code_prosemibold" horiz-adv-x="1228" >
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