update community page

doc/source/community.md

@@ -4,6 +4,38 @@ inclusive and positive community. Read the
 [ArviZ Code of Conduct](https://github.com/arviz-devs/arviz/blob/main/CODE_OF_CONDUCT.md)
 for guidance on how to interact with each other and make the community thrive.
 
+Our main goal is to provide backend-agnostic tools for diagnostics and visualizations of Bayesian
+inference.
+
+We do this by:
+
+* Creating and maintaining the ArviZ library with functions for posterior analysis, data storage,
+  sample diagnostics, model checking, and comparison.
+* Creating social infrastructure through a welcoming and diverse community
+* Making the right data, tools and best practices more discoverable
+* Promoting advocacy for a culture of principled iterative modeling based on the Bayesian Workflow
+
+This page aims to gather resources related to Bayesian modeling and ArviZ from a variety of
+sources to work towards the 2nd and 3rd bullet points.
+This page covers how can someone participate of the ArviZ community (this someone could be you!),
+gives an overview of the ecosystem of Python libraries for Bayesian analysis and serves
+as a compilation for community resources around ArviZ.
+
+*But what is the ArviZ community?*
+The ArviZ community is a self-identifying group composed of probabilistic programming practitioners who,
+together, contribute to the technical and social infrastructure for open and reproducible research.
+Our specific focus is on Bayesian modeling and best practices that lower the barriers to working using
+a fully fledged Bayesian modeling workflow, as opposed to a rigid toolbox approach.
+
+Community members are people who use, cite and share use cases for ArviZ,
+write posts or give talks about using ArviZ,
+participate in issues to help define the roadmap and improve the project,
+or answer questions in any of the affine forums.
+
+This page is part of the Python ArviZ library and is therefore specific to Python,
+but the ArviZ community is not restricted to Python and in fact aims to act as a bridge
+between programming languages and encourage collaboration.
+
 ## Participate online
 There are many alternatives and channels available to interact with other ArviZ users.
 
@@ -21,51 +53,54 @@ Many ArviZ contributors are also active in one of [PyMC3 Discourse](https://disc
 or [Stan Discourse](https://discourse.mc-stan.org/) (and sometimes even in both!).
 
 ## Conferences
-* StanCon
-* PyMCon
+* [StanCon](https://mc-stan.org/events/)
+* [PyMCon](https://pymcon.com)
+
+# The Bayesian Python ecosystem
+In the last years, many libraries for Bayesian data analysis have been created,
+and there is a slight tendency towards more modular libraries. ArviZ plays
+an important role in this ecosystem both as the go-to library for visualization
+and diagnostics in Python for any and all PPLs and as a way to standardize and
+share the results of PPL libraries.
+
+The PPLs that integrate with ArviZ are:
+
+* PyMC3
+* Stan
+* MCX
+* Pyro/NumPyro
+* PyJAGS
+* TensorFlow Probability
+
+Moreover, there are other libraries that use ArviZ for visualization and diagnostics
+and/or that are compatible with `InfereceData` objects:
+
+* Bambi
+* corner.py
 
 # Community educational resources
 ArviZ is a transversal and backend agnostic project. One can use ArviZ with _any_ PPL,
 but one has to be used in order to have some data for ArviZ to analyze.
 This makes writing detailed and complete documentation for ArviZ complicated.
 This section aims to act as a compilation of community resources related to ArviZ
-that hopefully can bridge the gap.
+that hopefully can bridge the gap. These can be books, case studies in the documentation of
+PPLs, personal blogs...
 
 Do you know of resources about ArviZ that are not listed here? Open an issue or a PR and
 let us know!
 
 ## Books
-* Bayesian Modeling and Computation in Python
-* BAP
-* BDA3
+* Bayesian Modeling and Computation in Python: available soon
+* [Bayesian Analysis with Python](https://github.com/aloctavodia/BAP)
+* [Bayesian Data Analysis 3](http://www.stat.columbia.edu/~gelman/book/)
 
 ## Podcasts
-* Learning Bayesian Statistics
-* dats'n'stats
+* [Learning Bayesian Statistics](https://www.learnbayesstats.com/)
+* [dats'n'stats](https://www.pydata-podcast.com/)
 
 ## Blogs and example compilations
 If you have a blog that has 2 or more posts tagged as "ArviZ", you can submit
 a pull request to add your blog to this list
 
-* https://github.com/pymc-devs/pymc-examples
-* https://mc-stan.org/users/documentation/case-studies
-
-```{panels}
-Blog title
-^^^
-Somewhat descriptive but not too long, maybe 1-2 tweets worth of text to explain
-what the blog is about and why should ArviZ users care
-+++
-Blog author + half sentence about them
----
-[Oriol Unraveled](https://oriolabril.github.io/oriol_unraveled/categories/#arviz)
-^^^
-![labeled_arys](https://oriolabril.github.io/oriol_unraveled/images/nb/labeled_arys.png)
-I plan to use the blog to write about topics that I care about and are interesting to me
-such as statistics, diversity or open source. The specific topic that is probably the
-most interesting to people reading this is that I also use the blog as an experimental
-ground for new pages in ArviZ docs.
-+++
-Oriol Abril Pla is an ArviZ core contributor and PhD student working on Bayesian workflow
-at Helsinki University
+```{include} external_resources.md
 ```

doc/source/conf.py

@@ -19,7 +19,7 @@
 #
 import os
 import sys
-from typing import Dict, Sequence
+from typing import Dict, Any
 
 sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
 import arviz
@@ -161,17 +161,16 @@
     "github_version": "main",
     "doc_path": "doc/source/",
 }
+html_sidebars : Dict[str, Any] = {
+  "community": []
+}
 
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
 # html_theme_path = sphinx_bootstrap_theme.get_html_theme_path()
 html_static_path = ["_static", thumb_directory]
 
-# Custom sidebar templates, must be a dictionary that maps document names
-# to template names.
-# html_sidebars = {}
-
 # use additional pages to add a 404 page
 html_additional_pages = {
     "404": "404.html",

doc/source/external_resources.md

@@ -0,0 +1,60 @@
+````{panels}
+:column: col-lg-4 col-md-4 col-sm-6 col-xs-12
+
+---
+:img-top: https://raw.githubusercontent.com/pymc-devs/pymc3/master/docs/logos/PyMC3.png
+:img-top-cls: pl-5 pr-5
+
+
+```{link-button} https://github.com/pymc-devs/pymc-examples
+:text: PyMC3 example notebooks
+:classes: btn-link stretched-link
+```
+
+Curated selection of PyMC3 guides and case studies.
++++
+Examples authored by PyMC3 developers and expert users.
+
+
+---
+:img-top: https://raw.githubusercontent.com/stan-dev/logos/master/logo.png
+:img-top-cls: pl-5 pr-5
+
+```{link-button} https://mc-stan.org/users/documentation/case-studies
+:text: Stan case studies
+:classes: btn-link stretched-link
+```
+
+The case studies on this page are intended to reflect best practices in Bayesian methodology and Stan programming.
++++
+Examples authored by Stan developers and expert users.
+
+---
+:img-top: _static/images/bambi.png
+
+
+```{link-button} https://github.com/bambinos/Bambi_resources
+:text: Bambi educational resources
+:classes: btn-link stretched-link
+```
+
+Bambi is a high-level Bayesian model-building interface written in Python,
+designed to make it extremely easy to fit mixed-effects models.
++++
+Tutorials and book translations maintained by the Bambi team
+
+---
+:img-top: https://oriolabril.github.io/oriol_unraveled/images/nb/labeled_arys.png
+
+```{link-button} https://oriolabril.github.io/oriol_unraveled/categories/#arviz
+:text: Oriol unraveled
+:classes: btn-link stretched-link
+```
+
+Blog mostly on statistics, diversity and open source. I also use the blog as a playground
+ground to test new pages for ArviZ docs.
++++
+Oriol Abril Pla is an ArviZ core contributor pursuing his PhD
+at Helsinki University
+
+````