Fix external links, update GH Actions workflow (#165)

.github/workflows/test_external_links.yml

@@ -1,18 +1,23 @@
 name: Testing External Links
-on: pull_request
+on:
+  schedule:
+    - cron: '0 5 * * 0'  # every Sunday at 05:00 UTC (midnight EST)
+  pull_request:
+  workflow_dispatch:
+
 jobs:
   build-and-test:
     name: Testing External Links
     runs-on: ubuntu-latest
     strategy:
       fail-fast: false
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
       - run: git fetch --prune --unshallow --tags
       - name: Setup Python
-        uses: actions/setup-python@v2
+        uses: actions/setup-python@v5
         with:
-          python-version: 3.9
+          python-version: 3.11
       - name: Install sphinx Dependencies
         run: pip install -r requirements.txt
       - name: Test External Links

.readthedocs.yaml

@@ -6,9 +6,9 @@
 version: 2
 
 build:
-  os: ubuntu-20.04
+  os: ubuntu-22.04
   tools:
-    python: '3.8'
+    python: '3.11'
 
 # Build documentation in the docs/ directory with Sphinx
 sphinx:
@@ -25,8 +25,3 @@ formats: all
 python:
   install:
     - requirements: requirements.txt
-
-# Optionally include all submodules
-submodules:
-  include: all
-  recursive: true

docs/source/community_gallery/community_gallery.rst

@@ -14,7 +14,7 @@ Data Conversion
     :class: align-left, no-scaled-link
     :width: 100
 
-:neuroconv-docs:`NeuroConv Catalog <catalogue/catalogue.html>` is a collection of real-world examples of labs using :neuroconv-docs:`NeuroConv <>` to convert their data to NWB files. Each project listed contains a description and a link to an open GitHub repository. Many of the projects listed use advanced customization features beyond what is demonstrated in the core :neuroconv-docs:`NeuroConv conversion gallery <conversion_examples_gallery/conversion_example_gallery.html>`. :bdg-link-primary:`NeuroConv Catalog <https://neuroconv.readthedocs.io/en/main/catalogue/catalogue.html>`
+:neuroconv-docs:`NeuroConv Catalog <catalogue/index.html>` is a collection of real-world examples of labs using :neuroconv-docs:`NeuroConv <>` to convert their data to NWB files. Each project listed contains a description and a link to an open GitHub repository. Many of the projects listed use advanced customization features beyond what is demonstrated in the core :neuroconv-docs:`NeuroConv conversion gallery <conversion_examples_gallery/index.html>`. :bdg-link-primary:`NeuroConv Catalog <https://neuroconv.readthedocs.io/en/main/catalogue/index.html>`
 
 .. image:: figures/bristol_neuroscience_data_guide.png
     :class: align-left, no-scaled-link
@@ -41,7 +41,7 @@ Data Analysis and Reuse
 .. raw:: html
 
     <br/>
-    
+
 In addition, the neuroscience community is creating examples demonstrating the reuse of NWB data published on DANDI. For example:
 
        * The `INCF working group on NWB <https://www.incf.org/sig/incf-working-group-nwb>`_ has created a `library of MATLAB examples <https://github.com/INCF/example-live-scripts>`_ using DANDI datasets authored as MATLAB live scripts. :bdg-link-primary:`Source <https://github.com/INCF/example-live-scripts>`

docs/source/conf_extlinks.py

@@ -48,7 +48,7 @@
     'nwb-helpdesk': ('https://github.com/dandi/helpdesk/discussions/%s', '%s'),
     'nwb-mailing-list': ('https://mailchi.mp/fe2a9bc55a1a/nwb-signup/%s', '%s'),
     'datajoint': ('https://www.datajoint.com/%s', '%s'),
-    'datajoint-elements': ('https://www.datajoint.com/elements/%s', '%s'),
+    'datajoint-elements': ('https://datajoint.com/docs/elements/%s', '%s'),
     'openscope-databook': ('https://alleninstitute.github.io/openscope_databook/%s', '%s'),
     'openscope-project': ('https://alleninstitute.org/what-we-do/brain-science/research/mindscope-program/openscope/%s',
                           '%s'),

docs/source/conversion_tutorial/02_format_conversions.md

@@ -2,11 +2,11 @@
 
 [NeuroConv](https://neuroconv.readthedocs.io/) is a library for automatic conversions from proprietary formats to NWB.
 A gallery of all supported formats can be found
-[here](https://neuroconv.readthedocs.io/en/main/conversion_examples_gallery/conversion_example_gallery.html).
+[here](https://neuroconv.readthedocs.io/en/main/conversion_examples_gallery/index.html).
 If NeuroConv supports your source data format, this is the recommended approach, because it is easiest to
 implement and automatically helps you adhere to best practices. For advanced usage of NeuroConv, including creating
 conversions of ensembles of multiple data streams, see the
-[NeuroConv User Guide](https://neuroconv.readthedocs.io/en/main/user_guide/user_guide.html).
+[NeuroConv User Guide](https://neuroconv.readthedocs.io/en/main/user_guide/index.html).
 
 Although NeuroConv supports many common formats, it may not support every type of source data you need.
 If your source format is likely to be a common need in the community, for example the output of an acquisition

docs/source/tools/datajoint/datajoint.rst

@@ -5,6 +5,6 @@ DataJoint
 
 .. short_description_start
 
-:ref:`analysistools-datajoint` is an open-source project for defining and operating computational data pipelines—sequences of steps for data acquisition, processing, and transformation. Some `DataJoint Elements <https://datajoint.com/elements>`_ support automatic conversion to NWB :bdg-link-primary:`Export element_array_ephys to NWB <https://github.com/datajoint/element-array-ephys/blob/main/element_array_ephys/export/nwb/README.md>`
+:ref:`analysistools-datajoint` is an open-source project for defining and operating computational data pipelines—sequences of steps for data acquisition, processing, and transformation. Some :datajoint-elements:`DataJoint Elements <>` support automatic conversion to NWB :bdg-link-primary:`Export element_array_ephys to NWB <https://github.com/datajoint/element-array-ephys/blob/main/element_array_ephys/export/nwb/README.md>`
 
 .. short_description_end

docs/source/tools/extract/extract.rst

@@ -10,7 +10,7 @@ which *extracts* the activities of cells as time series from both one-photon and
 EXTRACT makes minimal assumptions about the data, which is the main reason behind its high robustness and superior
 performance.
 :bdg-link-primary:`Source <https://github.com/schnitzer-lab/EXTRACT-public>`
-:bdg-link-primary:`NWB tutorials <https://github.com/schnitzer-lab/EXTRACT-public/tree/master/Learning%20materials/NWB%20Tutorials>`
+:bdg-link-primary:`NWB demos <https://github.com/schnitzer-lab/EXTRACT-public/tree/master/Learning%20materials/Additional%20demos/NWB%20Demos>`
 :bdg-link-primary:`Publication <https://www.biorxiv.org/content/10.1101/2021.03.24.436279v2>`
 
 .. image:: https://img.shields.io/github/stars/schnitzer-lab/EXTRACT-public?style=social

docs/source/tools/pynapple/pynapple.rst

@@ -6,7 +6,7 @@ pynapple
 .. short_description_start
 
 :ref:`analysistools-pynapple` is a unified toolbox for integrated analysis of multiple data sources. Designed to be "plug & play", users define and import their own time-relevant variables. Supported data sources include, but are not limited to, electrophysiology, calcium imaging, and motion capture data. Pynapple contains integrated functions for common neuroscience analyses, including cross-correlograms, tuning curves, decoding and perievent time histogram.
-:bdg-link-primary:`Docs <https://pynapple-org.github.io/pynapple/>` :bdg-link-primary:`DANDI Demo <https://pynapple-org.github.io/pynapple/generated/gallery/tutorial_pynapple_dandi/>` :bdg-link-primary:`Source <https://github.com/pynapple-org/pynapple>` :bdg-link-primary:`Twitter <https://twitter.com/thepynapple>`
+:bdg-link-primary:`Docs <https://pynapple-org.github.io/pynapple/>` :bdg-link-primary:`DANDI Demo <https://pynapple-org.github.io/pynapple/generated/examples/tutorial_pynapple_dandi/>` :bdg-link-primary:`Source <https://github.com/pynapple-org/pynapple>` :bdg-link-primary:`Twitter <https://twitter.com/thepynapple>`
 
 .. image:: https://img.shields.io/github/stars/pynapple-org/pynapple?style=social
     :alt: GitHub Repo stars for pynapple