Merge remote-tracking branch 'upstream/master'

Author: shaloo

.scripts/build.sh

@@ -5,5 +5,5 @@
 # Refer: https://github.com/numpy/numpy.org/pull/58/files#r336767432
 
 git submodule update --init
-hugo
+sudo hugo
 

.scripts/deploy.sh

@@ -3,27 +3,26 @@
 # Should be moved to build.sh
 # NOTE: Running build.sh and then deploy.sh is not finding the public
 # folder which is generated after the build command (hugo).
-git submodule update --init
-hugo
+# git submodule update --init
+# hugo
 
 # deploy in surge
 npm install -g surge
 
-if [ "$PR_NUMBER" != "false" ]
+if [ "$TRAVIS_PULL_REQUEST" != "false" ]
 then
-    echo "PR_NUMBER value is ${PR_NUMBER}"
+    echo "PR_NUMBER value is ${TRAVIS_PULL_REQUEST}"
 else
-  echo "PR_NUMBER value is ${PR_NUMBER}."
+  echo "PR_NUMBER value is ${TRAVIS_PULL_REQUEST}."
   exit 3
 fi
 
 PROJECT_BUILD="./public"
-DOMAIN="http://numpy-${PR_NUMBER}.surge.sh"
-echo "PR_NUMBER: $PR_NUMBER"
+DOMAIN="http://numpy-${TRAVIS_PULL_REQUEST}.surge.sh"
 echo "SURGE_LOGIN: $SURGE_LOGIN"
 echo "SURGE_TOKEN: $SURGE_TOKEN"
 ls "./public"
 
 surge --project $PROJECT_BUILD --domain $DOMAIN;
 
-echo ::set-output name=deployed-domain::"numpy-${PR_NUMBER}.surge.sh"
+echo "numpy-${TRAVIS_PULL_REQUEST}.surge.sh"

.scripts/install.sh

@@ -12,7 +12,7 @@ tar -xzf $tarball
 
 chmod +x hugo
 
-mv hugo /usr/local/bin/
+sudo mv hugo /usr/local/bin/
 
 location="$(which hugo)"
 echo "Hugo binary location: $location"

.travis.yml

@@ -1,14 +1,21 @@
-language: python
+sudo: required
+dist: trusty
+language: node_js
 
 os:
   - linux
 
-services:
-  - docker
-
 before_install:
-  - docker build -t deploy_surge .
-  - docker images
+  - chmod +x .scripts/install.sh
+  - chmod +x .scripts/build.sh
+  - chmod +x .scripts/deploy.sh
+
+before_script:
+  - ls
+  - .scripts/install.sh
 
 script:
-  - docker run -e SURGE_LOGIN=${SURGE_LOGIN} -e SURGE_TOKEN=${SURGE_TOKEN} -e PR_NUMBER=${TRAVIS_PULL_REQUEST} deploy_surge
+  - bash .scripts/build.sh
+
+after_script:
+  - bash .scripts/deploy.sh

Dockerfile

@@ -1,3 +1,6 @@
+# Not using it.
+# Refer: https://github.com/numpy/numpy.org/pull/146
+
 FROM node:10-alpine
 ADD . ./app
 WORKDIR /app

README.md

@@ -29,3 +29,39 @@ hugo server -D
 to run the hugo server with draft enabled.
 
 after which the site should be served at http://localhost:1313.
+
+## Using docker:
+
+* Build the docker image:
+
+```
+
+  $ docker build -t deploy_surge .
+  $ docker images
+
+```
+
+Run the image:
+
+```
+  $ docker run -e SURGE_LOGIN=${SURGE_LOGIN} -e SURGE_TOKEN=${SURGE_TOKEN} -e PR_NUMBER=${TRAVIS_PULL_REQUEST} deploy_surge
+```
+
+Note: `SURGE_LOGIN` and `SURGE_TOKEN` is needed only when you want to push the
+build in surge server. The URL will look like: numpy-${PR_NUMBER}.surge.sh
+
+So you can use some random number instead of `TRAVIS_PULL_REQUEST` variable.
+
+You also can run the docker image in daemon mode and then interact with the container and run the hugo server.
+
+## User Experience (UX)
+
+### NumPy Color Palette
+
+#FFC553 Mustard
+#4DABCF Maximum Blue
+#4D77CF Han Blue
+#FFFFFF White
+#EEEEEE Isabelline
+#6C7A89 Aurometalsaurus
+#013243 Warm Black

config.yaml

@@ -3,16 +3,21 @@ languageCode: en-us
 title: NumPy
 theme: hugo-fresh
 disableKinds: ["taxonomyTerm"]
+googleAnalytics: UA-162151853-1
 DefaultContentLanguage: en
+markup:
+  goldmark:
+    renderer:
+      unsafe: true
 
 params:
   navColor: blue
   navbarlogo:
     image: logos/numpy.svg
     link: /
   font:
-    name: "Ubuntu"
-    sizes: [400,600]
+    name: "Lato"
+    sizes: [400,900]
   hero:
     # Main hero title
     title: NumPy
@@ -21,7 +26,7 @@ params:
     # Button text
     buttontext: Get started
     # Where the main hero button links to
-    buttonlink: "#"
+    buttonlink: "/learn"
     # Hero image (from static/images/___)
     image: logos/numpy.svg
   # Customizable navbar. For a dropdown, add a "sublinks" list.
@@ -32,27 +37,33 @@ params:
     - title: First Image of a Black Hole
       text: How NumPy, together with libraries like SciPy and Matplotlib that depend on NumPy, enabled the Event Horizon Telescope to produce the first ever image of a black hole
       img: images/content_images/case_studies/blackhole.png
+      alttext: First image of a black hole. It is an orange circle in a black background.
       url: /case-studies/blackhole-image
     - title: Detection of Gravitational Waves
       text: One hundred years after they were predicted by Albert Einstein, NumPy was instrumental in the first observation of gravitational waves by LIGO in 2016.
       img: images/content_images/case_studies/gravitional.png
+      alttext: Two orbs orbiting each other. They are displacing gravity around them.
       url: /case-studies/gw-discov
     - title: Sports Analytics
       text: TODO!
       img: images/content_images/case_studies/sports.jpg
+      alttext: Cricket ball on green field.
       url: /
   section2:
     title: KEY FEATURES
     features:
     - title: Powerful N-dimensional arrays
-      subtitle: Fast, versatile and easy to use
-      text:  Fast, versatile and easy to use, the NumPy vectorization, indexing and broadcasting concepts are the de-facto standards of array computing today.
+      text:  Fast and versatile, the NumPy vectorization, indexing and broadcasting concepts are the de-facto standards of array computing today.
     - title: Numerical computing tools
-      text: Fundamental package for scientific computing, NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms and more.
+      text: NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms and more.
     - title: Interoperable
-      text: Works on your choice of computing platform, whether your code fits in memory and runs on a CPU or requires a GPU. NumPy supports a wide range of computing platforms and works well with all major distributed arrays and sparse arrays libraries. 
+      text: NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU and sparse array libraries.
+    - title: Performant
+      text: The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code.
+    - title: Easy to use
+      text: NumPy's high level syntax makes it accessible to and productive for programmers from any background or experience level.
     - title: Open source
-      text: Distributed under a liberal [BSD license](https://github.com/numpy/numpy/blob/master/LICENSE.txt), NumPy is developed and maintained publicly on GitHub by a vibrant, responsive and diverse community.
+      text: Distributed under a liberal [BSD license](https://github.com/numpy/numpy/blob/master/LICENSE.txt), NumPy is developed and maintained [publicly on GitHub](https://github.com/numpy/numpy) by a vibrant, responsive and diverse [community](/community).
   tabs:
     title: ECOSYSTEM
   section5: false
@@ -67,7 +78,7 @@ languages:
       - title: Install
         url: /install
       - title: Documentation
-        url: /doc
+        url: https://numpy.org/doc/
       - title: Learn
         url: /learn
       - title: Array computing
@@ -93,33 +104,29 @@ languages:
             - text: Install
               link: /install
             - text: Documentation
-              link: /docs
+              link: https://numpy.org/doc/
             - text: Learn
               link: /learn
             - text: Roadmap
               link: https://numpy.org/neps/roadmap.html
         column2:
-          title: ""
           links:
             - text: About us
               link: /about
             - text: Community
               link: /community
-            - text: Code of conduct
-              link: /code-of-conduct
-            - text: Get help
-              link: /help
             - text: Contribute
               link: /contribute
+            - text: Code of conduct
+              link: /code-of-conduct
         column3:
-          title: ""
           links:
+            - text: Get help
+              link: /gethelp
             - text: Terms of use
               link: /terms
             - text: Privacy
               link: /privacy
-            - text: Trademarks
-              link: /trademarks
             - text: Press kit
               link: /press-kit
   nl:
@@ -131,7 +138,7 @@ languages:
       - title: Install
         url: /nl/install
       - title: Documentation
-        url: /nl/doc
+        url: https://numpy.org/doc/
       - title: Array computing
         url: /nl/arraycomputing
       - title: Case Studies
@@ -159,7 +166,7 @@ languages:
             - text: Install
               link: /nl/install
             - text: Documentation
-              link: /nl/docs
+              link: https://numpy.org/doc/
             - text: Release notes
               link: /nl/release-notes
             - text: Roadmap
@@ -169,84 +176,20 @@ languages:
           links:
             - text: About us
               link: /nl/about
-            - text: Code of conduct
-              link: /nl/code-of-conduct
-            - text: Get help
-              link: /nl/help
+            - text: Community
+              link: /community
             - text: Contribute
               link: /nl/contribute
+            - text: Code of conduct
+              link:  /nl/code-of-conduct
         column3:
           title: ""
           links:
+            - text: Get help
+              link: /nl/gethelp
             - text: Terms of use
               link: /nl/terms
             - text: Privacy
               link: /nl/privacy
-            - text: Trademarks
-              link: /nl/trademarks
             - text: Press kit
               link: /nl/press-kit
-  hi:
-    title: NumPy
-    languageName: हिंदी
-    weight: 3
-    contentDir: content/hi
-    navbar:
-      - title: Install
-        url: /hi/install
-      - title: Documentation
-        url: /hi/doc
-      - title: Array computing
-        url: /hi/arraycomputing
-      - title: Case Studies
-        url: /hi/case-studies/blackhole-image
-      - title: Learn
-        url: /hi/learn
-      - title: Community
-        url: /hi/community
-      - title: About Us
-        url: /hi/about
-      - title: Contribute
-        url: /hi/contribute
-    footer:
-      logo: numpy.svg
-      socialmediatitle: ""
-      socialmedia:
-      - link: https://github.com/numpy/numpy
-        icon: github
-      - link: https://twitter.com/numpy_team
-        icon: twitter
-      quicklinks:
-        column1:
-          title: ""
-          links:
-            - text: Install
-              link: /hi/install
-            - text: Documentation
-              link: /hi/docs
-            - text: Release notes
-              link: /hi/release-notes
-            - text: Roadmap
-              link: /hi/roadmap
-        column2:
-          title: ""
-          links:
-            - text: About us
-              link: /hi/about
-            - text: Code of conduct
-              link: /hi/code-of-conduct
-            - text: Get help
-              link: /hi/help
-            - text: Contribute
-              link: /hi/contribute
-        column3:
-          title: ""
-          links:
-            - text: Terms of use
-              link: /hi/terms
-            - text: Privacy
-              link: /hi/privacy
-            - text: Trademarks
-              link: /hi/trademarks
-            - text: Press kit
-              link: /hi/press-kit

content/en/about.md

@@ -43,7 +43,7 @@ The NumPy project is growing, we have separate teams for:
 - Funding & grants
 - Admin
 
-See the [Team](/team) page for individual team members.
+See the [Team](/team) page for the individual team members.
 
 
 ## Sponsors
@@ -62,9 +62,9 @@ Institutional Partners are organizations that support the project by employing p
 
 If you have found NumPy to be useful in your work, research or company, please consider making a donation to the project commensurate with your resources. Any amount helps! All donations will be used strictly to fund the development of NumPy’s open source software, documentation and community.
 
-NumPy is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides NumPy with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit numfocus.org for more information.
+NumPy is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides NumPy with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit [numfocus.org](https://numfocus.org) for more information.
 
 Donations to NumPy are managed by [NumFOCUS](https://numfocus.org). For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax adviser about your particular tax situation.
 
 NumPy's Steering Council will make the decisions on how to best use any funds received. Technical and infrastructure priorities are documented on the [NumPy Roadmap](https://www.numpy.org/neps/index.html#roadmap).
-{{< numfocus >}}
+{{< numfocus >}}

content/en/arraycomputing.md

@@ -29,7 +29,7 @@ pack newer algorithms and features geared towards machine learning and artificia
   title="Array Computing Landscape">
 
 **Array computing** is based on **arrays** data structures. *Arrays* are used
-to organize vast amounts of data such that related set of values can be easily
+to organize vast amounts of data such that a related set of values can be easily
 sorted, searched, mathematically manipulated and transformed easily and quickly.
 
 Array computing is *unique* as it involves operating on the data array *at