Add a reference to Blosc2 as an array library (#882)

Author: FrancescAlted

content/en/tabcontents.yaml

@@ -73,6 +73,11 @@ params:
       img: /images/content_images/arlib/tensorly.png
       alttext: tensorly
       url: http://tensorly.org/stable/home.html
+    - title: Blosc2
+      text: Accelerated computation for in-memory, on-disk, or remote compressed arrays.
+      img: /images/content_images/arlib/blosc-logo.svg
+      alttext: blosc2
+      url: https://www.blosc.org/python-blosc2/
 
   scientificdomains:
     intro:

content/es/tabcontents.yaml

@@ -70,6 +70,12 @@ params:
         img: /images/content_images/arlib/tensorly.png
         alttext: tensorly
         url: http://tensorly.org/stable/home.html
+      - title: Blosc2
+        text: Cálculo acelerado con arrays comprimidos en memoria, en disco o remotos.
+        img: /images/content_images/arlib/blosc-logo.svg
+        alttext: blosc2
+        url: https://www.blosc.org/python-blosc2/
+
   scientificdomains:
     intro:
       - text: Casi todos los científicos que trabajan en Python recurren a la potencia de NumPy.

content/pt/tabcontents.yaml

@@ -75,6 +75,12 @@ params:
         img: /images/content_images/arlib/tensorly.png
         alttext: tensorly
         url: http://tensorly.org/stable/home.html
+      - title: Blosc2
+        text: Cálculo acelerado com arrays comprimidos na memória, no disco ou remotos.
+        img: /images/content_images/arlib/blosc-logo.svg
+        alttext: blosc2
+        url: https://www.blosc.org/python-blosc2/
+
   scientificdomains:
     intro:
       - text: Quase todos os cientistas que trabalham em Python se baseiam na potência do NumPy.