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Tidy up and fix alignment of landing cards (#5317)

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Ines Montani 2020-04-20 20:33:13 +02:00 committed by GitHub
parent f7471abd82
commit b919844fce
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3 changed files with 34 additions and 28 deletions
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13
website/src/components/landing.js
View File

@ -46,10 +46,17 @@ export const LandingGrid = ({ cols = 3, blocks = false, children }) => (
export const LandingCol = ({ children }) => <div className={classes.col}>{children}</div>
export const LandingCard = ({ title, children }) => (
export const LandingCard = ({ title, button, url, children }) => (
<div className={classes.card}>
{title && <H3>{title}</H3>}
{children}
<section className={classes.cardText}>
{title && <H3>{title}</H3>}
<p>{children}</p>
</section>
{button && url && (
<footer>
<LandingButton to={url}>{button}</LandingButton>
</footer>
)}
</div>
)

5
website/src/styles/landing.module.sass
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@ -49,12 +49,17 @@
margin-bottom: -25rem
.card
display: flex
flex-direction: column
padding: 3rem 2.5rem
background: var(--color-back)
border-radius: var(--border-radius)
box-shadow: var(--box-shadow)
margin-bottom: 3rem
.card-text
flex: 100%
.button
width: 100%

44
website/src/widgets/landing.js
View File

@ -79,34 +79,28 @@ const Landing = ({ data }) => {
<LandingSubtitle>in Python</LandingSubtitle>
</LandingHeader>
<LandingGrid blocks>
<LandingCard title="Get things done">
<p>
spaCy is designed to help you do real work — to build real products, or
gather real insights. The library respects your time, and tries to avoid
wasting it. It's easy to install, and its API is simple and productive. We
like to think of spaCy as the Ruby on Rails of Natural Language Processing.
</p>
<LandingButton to="/usage/spacy-101">Get started</LandingButton>
<LandingCard title="Get things done" url="/usage/spacy-101" button="Get started">
spaCy is designed to help you do real work — to build real products, or gather
real insights. The library respects your time, and tries to avoid wasting it.
It's easy to install, and its API is simple and productive. We like to think of
spaCy as the Ruby on Rails of Natural Language Processing.
</LandingCard>
<LandingCard title="Blazing fast">
<p>
spaCy excels at large-scale information extraction tasks. It's written from
the ground up in carefully memory-managed Cython. Independent research in
2015 found spaCy to be the fastest in the world. If your application needs
to process entire web dumps, spaCy is the library you want to be using.
</p>
<LandingButton to="/usage/facts-figures">Facts & Figures</LandingButton>
<LandingCard
title="Blazing fast"
url="/usage/facts-figures"
button="Facts &amp; Figures"
>
spaCy excels at large-scale information extraction tasks. It's written from the
ground up in carefully memory-managed Cython. Independent research in 2015 found
spaCy to be the fastest in the world. If your application needs to process
entire web dumps, spaCy is the library you want to be using.
</LandingCard>
<LandingCard title="Deep learning">
<p>
spaCy is the best way to prepare text for deep learning. It interoperates
seamlessly with TensorFlow, PyTorch, scikit-learn, Gensim and the rest of
Python's awesome AI ecosystem. With spaCy, you can easily construct
linguistically sophisticated statistical models for a variety of NLP
problems.
</p>
<LandingButton to="/usage/training">Read more</LandingButton>
<LandingCard title="Deep learning" url="/usage/training" button="Read more">
spaCy is the best way to prepare text for deep learning. It interoperates
seamlessly with TensorFlow, PyTorch, scikit-learn, Gensim and the rest of
Python's awesome AI ecosystem. With spaCy, you can easily construct
linguistically sophisticated statistical models for a variety of NLP problems.
</LandingCard>
</LandingGrid>