diff --git a/.github/workflows/collect-user-submission.py b/.github/workflows/collect-user-submission.py
deleted file mode 100644
index a70bb32fd..000000000
--- a/.github/workflows/collect-user-submission.py
+++ /dev/null
@@ -1,82 +0,0 @@
-import json
-import os
-import typing
-
-import frontmatter
-import pydantic
-from markdown_it import MarkdownIt
-
-
-class Author(pydantic.BaseModel):
-    name: str = 'anonymous'
-    affiliation: str = None
-    affiliation_url: typing.Union[str, pydantic.HttpUrl] = None
-    email: typing.Union[str, pydantic.EmailStr] = None
-
-
-class Submission(pydantic.BaseModel):
-    title: str
-    description: str
-    url: pydantic.HttpUrl
-    thumbnail: typing.Union[str, pydantic.HttpUrl] = None
-    authors: typing.List[Author] = None
-    tags: typing.Dict[str, typing.List[str]] = None
-
-
-@pydantic.dataclasses.dataclass
-class IssueInfo:
-    gh_event_path: pydantic.FilePath
-    submission: Submission = pydantic.Field(default=None)
-
-    def create_submission(self):
-        self._get_inputs()
-        self._create_submission_input()
-        return self
-
-    def _get_inputs(self):
-        with open(self.gh_event_path) as f:
-            self.data = json.load(f)
-
-        self.author = self.data['issue']['user']['login']
-        self.title = self.data['issue']['title']
-        self.body = self.data['issue']['body']
-
-    def _create_submission_input(self):
-        md = MarkdownIt()
-        inputs = None
-        for token in md.parse(self.body):
-            if token.tag == 'code':
-                inputs = frontmatter.loads(token.content).metadata
-                break
-        name = inputs.get('name')
-        title = inputs.get('title')
-        description = inputs.get('description')
-        url = inputs.get('url')
-        thumbnail = inputs.get('thumbnail')
-        _authors = inputs.get('authors')
-        authors = []
-        if _authors:
-            for item in _authors:
-                authors.append(
-                    Author(
-                        name=item.get('name', 'anyonymous'),
-                        affiliation=item.get('affiliation'),
-                        affiliation_url=item.get('affiliation_url'),
-                        email=item.get('email', ''),
-                    )
-                )
-        else:
-            authors = [Author(name='anyonymous')]
-        _tags = inputs.get(
-            'tags', {'packages': ['unspecified'], 'formats': ['unspecified'], 'domains': ['unspecified']}
-        )
-        self.submission = Submission(
-            name=name, title=title, description=description, url=url, thumbnail=thumbnail, authors=authors, tags=_tags
-        )
-
-
-if __name__ == '__main__':
-    issue = IssueInfo(gh_event_path=os.environ['GITHUB_EVENT_PATH']).create_submission()
-    inputs = issue.submission.model_dump_json()
-    with open('resource-gallery-submission-input.json', 'w') as f:
-        json.dump(inputs, f)
diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml
deleted file mode 100644
index 8994acefe..000000000
--- a/.github/workflows/deploy.yml
+++ /dev/null
@@ -1,57 +0,0 @@
-# This file was created automatically with `myst init --gh-pages` 🪄 💚
-# Ensure your GitHub Pages settings for this repository are set to deploy with **GitHub Actions**.
-
-name: MyST GitHub Pages Deploy
-on:
-  push:
-    # Runs on pushes targeting the default branch
-    branches: [main]
-env:
-  # `BASE_URL` determines the website is served from, including CSS & JS assets
-  # You may need to change this to `BASE_URL: /${{ github.event.repository.name }}`
-  BASE_URL: '' # Not required for 'projectpythia-mystmd.github.io' domain. Other repos will need to set this!
-
-# Sets permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
-permissions:
-  contents: read
-  pages: write
-  id-token: write
-# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
-# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
-concurrency:
-  group: 'pages'
-  cancel-in-progress: false
-jobs:
-  deploy:
-    environment:
-      name: github-pages
-      url: ${{ steps.deployment.outputs.page_url }}
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - name: Setup Pages
-        uses: actions/configure-pages@v3
-      - uses: actions/setup-node@v4
-        with:
-          node-version: 18.x
-      - name: Install MyST Markdown
-        run: npm install -g mystmd
-      - uses: actions/setup-python@v5
-        with:
-          python-version: '3.12'
-          cache: 'pip'
-      - name: Install Python dependencies
-        run: pip install -r requirements.txt
-      - name: Build HTML Assets
-        run: myst build --html --execute
-        # Only expose secrets here
-        env:
-          PRIVATE_KEY: ${{ secrets.PRIVATE_KEY }}
-          PRIVATE_KEY_ID: ${{ secrets.PRIVATE_KEY_ID }}
-      - name: Upload artifact
-        uses: actions/upload-pages-artifact@v3
-        with:
-          path: './_build/html'
-      - name: Deploy to GitHub Pages
-        id: deployment
-        uses: actions/deploy-pages@v4
diff --git a/.github/workflows/get-metrics.py b/.github/workflows/get-metrics.py
deleted file mode 100644
index ca72afe70..000000000
--- a/.github/workflows/get-metrics.py
+++ /dev/null
@@ -1,309 +0,0 @@
-import datetime
-import json
-import os
-
-import cartopy
-import google
-import matplotlib
-import matplotlib.cm as cm
-import matplotlib.colors as colors
-import matplotlib.pyplot as plt
-import numpy as np
-from google.analytics.data_v1beta import BetaAnalyticsDataClient
-from google.analytics.data_v1beta.types import DateRange, Dimension, Metric, RunReportRequest
-
-# Project ID Numbers
-PORTAL_ID = '266784902'
-FOUNDATIONS_ID = '281776420'
-COOKBOOKS_ID = '324070631'
-
-# Access Secrets
-PRIVATE_KEY_ID = os.environ.get('PRIVATE_KEY_ID')
-# Ensure GH secrets doesn't intrudce extra '\' new line characters (related to '\' being an escape character)
-PRIVATE_KEY = os.environ.get('PRIVATE_KEY').replace('\\n', '\n')
-
-credentials_dict = {
-    'type': 'service_account',
-    'project_id': 'cisl-vast-pythia',
-    'private_key_id': PRIVATE_KEY_ID,
-    'private_key': PRIVATE_KEY,
-    'client_email': 'pythia-metrics-api@cisl-vast-pythia.iam.gserviceaccount.com',
-    'client_id': '113402578114110723940',
-    'auth_uri': 'https://accounts.google.com/o/oauth2/auth',
-    'token_uri': 'https://oauth2.googleapis.com/token',
-    'auth_provider_x509_cert_url': 'https://www.googleapis.com/oauth2/v1/certs',
-    'client_x509_cert_url': 'https://www.googleapis.com/robot/v1/metadata/x509/pythia-metrics-api%40cisl-vast-pythia.iam.gserviceaccount.com',
-    'universe_domain': 'googleapis.com',
-}
-
-try:
-    client = BetaAnalyticsDataClient.from_service_account_info(credentials_dict)
-except google.auth.exceptions.MalformedError as e:
-    print('Malformed Error:', repr(e))
-    # Insight into reason for failure without exposing secret key
-    # 0: Secret not found, else malformed
-    # 706: extra quote, 732: extra '\', 734: both
-    print('Length of PRIVATE_KEY:', len(PRIVATE_KEY))
-
-pre_project_date = '2020-03-31'  # Random date before project start
-
-
-def _format_rounding(value):
-    """
-    Helper function for rounding string displays. 1,232 -> 1.2K
-    """
-    return f'{round(value / 1000, 1):.1f}K'
-
-
-# The rest of this file alternates between functions for requesting information from Google Analytics
-# And functions that use that request image to form either a .json or a .png file to be used in write-metrics-md.py
-def _run_total_users_report(property_id):
-    """
-    Function for requesting cumulative active users from a project since project start.
-    """
-    request = RunReportRequest(
-        property=f'properties/{property_id}',
-        dimensions=[],
-        metrics=[Metric(name='activeUsers')],
-        date_ranges=[DateRange(start_date=pre_project_date, end_date='today')],
-    )
-    response = client.run_report(request)
-
-    total_users = 0
-    for row in response.rows:
-        total_users += int(row.metric_values[0].value)
-
-    return _format_rounding(total_users)
-
-
-def get_total_users(PORTAL_ID, FOUNDATIONS_ID, COOKBOOKS_ID):
-    """
-    Function for taking cumulative active users from each project and dumping it into a JSON with the current datetime.
-    """
-    metrics_dict = {}
-    metrics_dict['Now'] = str(datetime.datetime.now())
-    metrics_dict['Portal'] = _run_total_users_report(PORTAL_ID)
-    metrics_dict['Foundations'] = _run_total_users_report(FOUNDATIONS_ID)
-    metrics_dict['Cookbooks'] = _run_total_users_report(COOKBOOKS_ID)
-
-    # Save to JSON, Remember Action is called from root directory
-    with open('portal/metrics/user_metrics.json', 'w') as outfile:
-        json.dump(metrics_dict, outfile)
-
-
-def _run_active_users_this_year(property_id):
-    """
-    Function for requesting active users by day from a project since year start.
-    """
-    current_year = datetime.datetime.now().year
-    start_date = f'{current_year}-01-01'
-
-    request = RunReportRequest(
-        property=f'properties/{property_id}',
-        dimensions=[Dimension(name='date')],
-        metrics=[Metric(name='activeUsers')],
-        date_ranges=[DateRange(start_date=start_date, end_date='today')],
-    )
-    response = client.run_report(request)
-
-    dates = []
-    user_counts = []
-    for row in response.rows:
-        date_str = row.dimension_values[0].value
-        date = datetime.datetime.strptime(date_str, '%Y%m%d')
-        dates.append(date)
-        user_counts.append(int(row.metric_values[0].value))
-
-    # Days need to be sorted chronologically
-    return zip(*sorted(zip(dates, user_counts), key=lambda x: x[0]))
-
-
-def plot_projects_this_year(PORTAL_ID, FOUNDATIONS_ID, COOKBOOKS_ID):
-    """
-    Function for taking year-to-date active users by day and plotting it for each project.
-    """
-    portal_dates, portal_users = _run_active_users_this_year(PORTAL_ID)
-    foundations_dates, foundations_users = _run_active_users_this_year(FOUNDATIONS_ID)
-    cookbooks_dates, cookbooks_users = _run_active_users_this_year(COOKBOOKS_ID)
-
-    # Plotting code
-    plt.figure(figsize=(10, 5.5))
-    plt.title('Year-to-Date Pythia Active Users', fontsize=15)
-
-    plt.plot(portal_dates, portal_users, color='purple', label='Portal')
-    plt.plot(foundations_dates, foundations_users, color='royalblue', label='Foundations')
-    plt.plot(cookbooks_dates, cookbooks_users, color='indianred', label='Cookbooks')
-
-    plt.legend(fontsize=12, loc='upper right')
-
-    plt.xlabel('Date', fontsize=12)
-    plt.savefig('portal/metrics/thisyear.png', bbox_inches='tight')
-
-
-def _run_top_pages_report(property_id):
-    """
-    Function for requesting top 5 pages from a project.
-    """
-    request = RunReportRequest(
-        property=f'properties/{property_id}',
-        dimensions=[Dimension(name='pageTitle')],
-        date_ranges=[DateRange(start_date=pre_project_date, end_date='today')],
-        metrics=[Metric(name='screenPageViews')],
-    )
-    response = client.run_report(request)
-
-    views_dict = {}
-    for row in response.rows:
-        page = row.dimension_values[0].value
-        views = int(row.metric_values[0].value)
-        views_dict[page] = views
-
-    # Sort by views and grab the top 5
-    top_pages = sorted(views_dict.items(), key=lambda item: item[1], reverse=True)[:5]
-    # String manipulation on page titles "Cartopy - Pythia Foundations" -> "Cartopy"
-    pages = [page.split('—')[0] for page, _ in top_pages]
-    views = [views for _, views in top_pages]
-
-    #  Reverse order of lists, so they'll plot with most visited page on top (i.e. last)
-    return pages[::-1], views[::-1]
-
-
-def plot_top_pages(PORTAL_ID, FOUNDATIONS_ID, COOKBOOKS_ID):
-    """
-    Function that takes the top 5 viewed pages for all 3 projects and plot them on a histogram.
-    """
-    portal_pages, portal_views = _run_top_pages_report(PORTAL_ID)
-    foundations_pages, foundations_views = _run_top_pages_report(FOUNDATIONS_ID)
-    cookbooks_pages, cookbooks_views = _run_top_pages_report(COOKBOOKS_ID)
-
-    # Plotting code
-    fig, ax = plt.subplots(figsize=(10, 5.5))
-    plt.title('All-Time Top Pages', fontsize=15)
-
-    y = np.arange(5)  # 0-4 for Cookbooks
-    y2 = np.arange(6, 11)  # 6-10 for Foundations
-    y3 = np.arange(12, 17)  # 12-16 for Portal
-
-    bar1 = ax.barh(y3, portal_views, align='center', label='Portal', color='purple')
-    bar2 = ax.barh(y2, foundations_views, align='center', label='Foundations', color='royalblue')
-    bar3 = ax.barh(y, cookbooks_views, align='center', label='Cookbooks', color='indianred')
-
-    y4 = np.append(y, y2)
-    y4 = np.append(y4, y3)  # 0-4,6-19,12-6 for page labels to have a gap between projects
-    pages = cookbooks_pages + foundations_pages + portal_pages  # List of all pages
-    ax.set_yticks(y4, labels=pages, fontsize=12)
-
-    # Adds round-formatted views label to end of each bar
-    ax.bar_label(bar1, fmt=_format_rounding, padding=5, fontsize=10)
-    ax.bar_label(bar2, fmt=_format_rounding, padding=5, fontsize=10)
-    ax.bar_label(bar3, fmt=_format_rounding, padding=5, fontsize=10)
-
-    ax.set_xscale('log')
-    ax.set_xlim([10, 10**5])  # set_xlim must be after setting xscale to log
-    ax.set_xlabel('Page Views', fontsize=12)
-
-    plt.legend(fontsize=12, loc='lower right')
-    plt.savefig('portal/metrics/toppages.png', bbox_inches='tight')
-
-
-def _run_usersXcountry_report(property_id):
-    """
-    Function for requesting users by country for a project.
-    """
-    request = RunReportRequest(
-        property=f'properties/{property_id}',
-        dimensions=[Dimension(name='country')],
-        metrics=[Metric(name='activeUsers')],
-        date_ranges=[DateRange(start_date=pre_project_date, end_date='today')],
-    )
-    response = client.run_report(request)
-
-    user_by_country = {}
-    for row in response.rows:
-        country = row.dimension_values[0].value
-        users = int(row.metric_values[0].value)
-        user_by_country[country] = user_by_country.get(country, 0) + users
-
-    return user_by_country
-
-
-def plot_usersXcountry(FOUNDATIONS_ID):
-    """
-    Function for taking users by country for Pythia Foundations and plotting them on a map.
-    """
-    users_by_country = _run_usersXcountry_report(FOUNDATIONS_ID)
-
-    # Google API Country names do not match Cartopy Country Shapefile names
-    dict_api2cartopy = {
-        'Tanzania': 'United Republic of Tanzania',
-        'United States': 'United States of America',
-        'Congo - Kinshasa': 'Democratic Republic of the Congo',
-        'Bahamas': 'The Bahamas',
-        'Timor-Leste': 'East Timor',
-        'C\u00f4te d\u2019Ivoire': 'Ivory Coast',
-        'Bosnia & Herzegovina': 'Bosnia and Herzegovina',
-        'Serbia': 'Republic of Serbia',
-        'Trinidad & Tobago': 'Trinidad and Tobago',
-    }
-
-    for key in dict_api2cartopy:
-        users_by_country[dict_api2cartopy[key]] = users_by_country.pop(key)
-
-    # Sort by views and grab the top 10 countries for a text box
-    top_10_countries = sorted(users_by_country.items(), key=lambda item: item[1], reverse=True)[:10]
-    top_10_text = '\n'.join(
-        f'{country}: {_format_rounding(value)}' for i, (country, value) in enumerate(top_10_countries)
-    )
-
-    # Plotting code
-    fig = plt.figure(figsize=(10, 4))
-    ax = plt.axes(projection=cartopy.crs.PlateCarree(), frameon=False)
-    ax.set_title('All-Time Pythia Foundations Users by Country', fontsize=15)
-
-    shapefile = cartopy.io.shapereader.natural_earth(category='cultural', resolution='110m', name='admin_0_countries')
-    reader = cartopy.io.shapereader.Reader(shapefile)
-    countries = reader.records()
-
-    colormap = plt.get_cmap('Blues')
-    newcmp = colors.ListedColormap(colormap(np.linspace(0.2, 1, 128)))  # Truncate colormap to remove white hues
-    newcmp.set_extremes(under='grey')
-
-    norm = colors.LogNorm(vmin=1, vmax=max(users_by_country.values()))  # Plot on log scale
-    mappable = cm.ScalarMappable(norm=norm, cmap=newcmp)
-
-    # Loop through countries and plot their color
-    for country in countries:
-        country_name = country.attributes['SOVEREIGNT']
-        if country_name in users_by_country.keys():
-            facecolor = newcmp(norm(users_by_country[country_name]))
-            ax.add_geometries(
-                [country.geometry],
-                cartopy.crs.PlateCarree(),
-                facecolor=facecolor,
-                edgecolor='white',
-                linewidth=0.7,
-                norm=matplotlib.colors.LogNorm(),
-            )
-        else:
-            ax.add_geometries(
-                [country.geometry], cartopy.crs.PlateCarree(), facecolor='grey', edgecolor='white', linewidth=0.7
-            )
-
-    # Add colorbar
-    cax = fig.add_axes([0.05, -0.015, 0.7, 0.03])  # [x0, y0, width, height]
-    cbar = fig.colorbar(mappable=mappable, cax=cax, spacing='uniform', orientation='horizontal', extend='min')
-    cbar.set_label('Unique Users')
-
-    # Add top 10 countries text
-    props = dict(boxstyle='round', facecolor='white', edgecolor='white')
-    ax.text(1.01, 0.5, top_10_text, transform=ax.transAxes, fontsize=12, verticalalignment='center', bbox=props)
-
-    plt.tight_layout()
-    plt.savefig('portal/metrics/bycountry.png', bbox_inches='tight')
-
-
-if __name__ == '__main__':
-    get_total_users(PORTAL_ID, FOUNDATIONS_ID, COOKBOOKS_ID)
-    plot_projects_this_year(PORTAL_ID, FOUNDATIONS_ID, COOKBOOKS_ID)
-    plot_top_pages(PORTAL_ID, FOUNDATIONS_ID, COOKBOOKS_ID)
-    plot_usersXcountry(FOUNDATIONS_ID)
diff --git a/.github/workflows/nightly-build.yaml b/.github/workflows/nightly-build.yaml
index f2ab77535..990e7eba9 100644
--- a/.github/workflows/nightly-build.yaml
+++ b/.github/workflows/nightly-build.yaml
@@ -3,20 +3,17 @@ name: nightly-build
 on:
   workflow_dispatch:
   schedule:
-    - cron: '0 0 * * *' # Daily “At 00:00”
+    - cron: "0 0 * * *" # Daily “At 00:00”
 
 jobs:
   build:
     if: ${{ github.repository_owner == 'ProjectPythia' }}
     uses: ProjectPythia/cookbook-actions/.github/workflows/build-book.yaml@main
-    with:
-      environment_file: 'environment.yml'
-      environment_name: pythia
-      path_to_notebooks: 'portal'
-      build_command: 'make -j4 html'
+
+  deploy:
+    needs: build
+    uses: ProjectPythia/cookbook-actions/.github/workflows/deploy-book.yaml@main
 
   link-check:
     if: ${{ github.repository_owner == 'ProjectPythia' }}
-    uses: ./.github/workflows/sphinx-link-checker.yaml
-    with:
-      path_to_source: 'portal'
+    uses: ProjectPythia/cookbook-actions/.github/workflows/link-checker.yaml@main
diff --git a/.github/workflows/publish-site.yaml b/.github/workflows/publish-site.yaml
new file mode 100644
index 000000000..594644f1f
--- /dev/null
+++ b/.github/workflows/publish-site.yaml
@@ -0,0 +1,16 @@
+name: publish-site
+
+on:
+  # Trigger the workflow on push to main branch
+  push:
+    branches:
+      - main
+  workflow_dispatch:
+
+jobs:
+  build:
+    uses: ProjectPythia/cookbook-actions/.github/workflows/build-book.yaml@main
+
+  deploy:
+    needs: build
+    uses: ProjectPythia/cookbook-actions/.github/workflows/deploy-book.yaml@main
diff --git a/.github/workflows/sphinx-link-checker.yaml b/.github/workflows/sphinx-link-checker.yaml
deleted file mode 100644
index 96ce43268..000000000
--- a/.github/workflows/sphinx-link-checker.yaml
+++ /dev/null
@@ -1,67 +0,0 @@
-name: sphinx-link-checker
-
-on:
-  workflow_call:
-    inputs:
-      environment_name:
-        description: 'Name of conda environment to activate'
-        required: false
-        default: 'pythia'
-        type: string
-      environment_file:
-        description: 'Name of conda environment file'
-        required: false
-        default: 'environment.yml'
-        type: string
-      path_to_source:
-        description: 'Location of the sphinx source relative to repo root'
-        required: false
-        default: './'
-        type: string
-      use_cached_environment:
-        description: 'Flag for whether we should attempt to retrieve a previously cached environment.'
-        required: false
-        default: 'true'
-        type: string  # had a lot of trouble with boolean types, see https://github.com/actions/runner/issues/1483
-
-jobs:
-  link-checker:
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        shell: bash -l {0}
-    steps:
-      - uses: actions/checkout@v3
-
-      - name: Setup Miniforge
-        uses: conda-incubator/setup-miniconda@v2
-        with:
-          miniforge-version: latest
-          python-version: "3.10"  # binderbot is failing with python 3.11
-          activate-environment: ${{ inputs.environment_name }}
-
-      - name: Set cache date
-        if: inputs.use_cached_environment == 'true'
-        run: echo "DATE=$(date +'%Y%m%d')" >> $GITHUB_ENV
-
-      - uses: actions/cache@v3
-        if: inputs.use_cached_environment == 'true'
-        with:
-          path: /usr/share/miniconda3/envs/${{ inputs.environment_name }}
-          # This should create a key that looks like 'linux-64-conda-environment.yml-[HASH]-DATE'
-          # Logic inspired by https://dev.to/epassaro/caching-anaconda-environments-on-github-actions-2d08
-          key: ${{ format('linux-64-conda-{0}-{1}-{2}', inputs.environment_file, hashFiles(format('{0}', inputs.environment_file)), env.DATE )}}
-        id: cache
-
-      - name: Update execution environment
-        if: |
-          (inputs.use_cached_environment != 'true'
-          || steps.cache.outputs.cache-hit != 'true')
-        run: |
-          conda env update -n ${{ inputs.environment_name }} -f ${{ inputs.environment_file }}
-          conda install -c conda-forge sphinxcontrib-applehelp=1.0.4 sphinxcontrib-devhelp=1.0.2 sphinxcontrib-htmlhelp=2.0.1 sphinxcontrib-qthelp=1.0.3 sphinxcontrib-serializinghtml=1.1.5
-
-      - name: Check external links
-        run: |
-          cd ${{ inputs.path_to_source }}
-          make linkcheck
diff --git a/.github/workflows/trigger-link-check.yaml b/.github/workflows/trigger-link-check.yaml
index d2ceb8c6b..e2402ddcd 100644
--- a/.github/workflows/trigger-link-check.yaml
+++ b/.github/workflows/trigger-link-check.yaml
@@ -4,6 +4,4 @@ on:
 
 jobs:
   link-check:
-    uses: ./.github/workflows/sphinx-link-checker.yaml
-    with:
-      path_to_source: 'portal'
+    uses: ProjectPythia/cookbook-actions/.github/workflows/link-checker.yaml@main
diff --git a/.github/workflows/trigger-preview.yaml b/.github/workflows/trigger-preview.yaml
index c3aea861f..049b5d0bd 100644
--- a/.github/workflows/trigger-preview.yaml
+++ b/.github/workflows/trigger-preview.yaml
@@ -2,7 +2,7 @@ name: trigger-preview
 on:
   workflow_run:
     workflows:
-      - trigger-site-build
+      - trigger-book-build
     types:
       - requested
       - completed
@@ -10,16 +10,14 @@ on:
 jobs:
   find-pull-request:
     uses: ProjectPythia/cookbook-actions/.github/workflows/find-pull-request.yaml@main
-
   deploy-preview:
     needs: find-pull-request
     if: github.event.workflow_run.conclusion == 'success'
     uses: ProjectPythia/cookbook-actions/.github/workflows/deploy-book.yaml@main
     with:
       artifact_name: book-zip-${{ needs.find-pull-request.outputs.number }}
-      destination_dir: _preview/${{ needs.find-pull-request.outputs.number }}  # deploy to subdirectory labeled with PR number
-      is_preview: 'true'
-      publish_dir: 'portal/_build/html'
+      destination_dir: _preview/${{ needs.find-pull-request.outputs.number }} # deploy to subdirectory labeled with PR number
+      is_preview: "true"
 
   preview-comment:
     needs: find-pull-request
diff --git a/.github/workflows/trigger-replace-links.yaml b/.github/workflows/trigger-replace-links.yaml
new file mode 100644
index 000000000..1d1e85479
--- /dev/null
+++ b/.github/workflows/trigger-replace-links.yaml
@@ -0,0 +1,31 @@
+name: trigger-replace-links
+
+on:
+  workflow_dispatch:
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: write
+
+    steps:
+      - uses: actions/checkout@v3
+      - name: Find and Replace Repository Name
+        uses: jacobtomlinson/gha-find-replace@v3
+        with:
+          find: "ProjectPythia/cookbook-template"
+          replace: "${{ github.repository_owner }}/${{ github.event.repository.name }}"
+          regex: false
+          exclude: ".github/workflows/trigger-replace-links.yaml"
+
+      - name: Find and Replace Repository ID
+        uses: jacobtomlinson/gha-find-replace@v3
+        with:
+          find: "475509405"
+          replace: "${{ github.repository_id}}"
+          regex: false
+          exclude: ".github/workflows/trigger-replace-links.yml"
+
+      - name: Push changes
+        uses: stefanzweifel/git-auto-commit-action@v4
diff --git a/.github/workflows/trigger-site-build.yaml b/.github/workflows/trigger-site-build.yaml
deleted file mode 100644
index ed8488cd9..000000000
--- a/.github/workflows/trigger-site-build.yaml
+++ /dev/null
@@ -1,14 +0,0 @@
-name: trigger-site-build
-on:
-  pull_request:
-
-jobs:
-  build:
-    uses: ProjectPythia/cookbook-actions/.github/workflows/build-book.yaml@main
-    with:
-      environment_file: 'environment.yml'
-      environment_name: pythia
-      artifact_name: book-zip-${{ github.event.number }}
-      path_to_notebooks: 'portal'
-      build_command: 'make -j4 html'
-      # Other input options are possible, see ProjectPythia/cookbook-actions/.github/workflows/build-book.yaml
diff --git a/.github/workflows/update-resource-gallery.yaml b/.github/workflows/update-resource-gallery.yaml
deleted file mode 100644
index 650e85cc9..000000000
--- a/.github/workflows/update-resource-gallery.yaml
+++ /dev/null
@@ -1,153 +0,0 @@
-name: Update Resource Gallery
-
-on:
-  issues:
-    types:
-      - opened
-      - edited
-
-jobs:
-  validate-user-submission:
-    if: |
-      github.repository == 'ProjectPythia/projectpythia.github.io'
-      && contains(github.event.issue.labels.*.name, 'resource-gallery-submission')
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        shell: bash -l {0}
-    steps:
-      - name: Find Comment
-        uses: peter-evans/find-comment@v1
-        id: fc
-        with:
-          issue-number: ${{ github.event.issue.number }}
-          comment-author: 'github-actions[bot]'
-          body-includes: Thank you for your contribution
-      - name: Create comment
-        if: steps.fc.outputs.comment-id == ''
-        uses: peter-evans/create-or-update-comment@v1
-        with:
-          issue-number: ${{ github.event.issue.number }}
-          body: |
-            Thank you for your contribution 🎉, @${{ github.actor }}!
-
-            We're currently running [validation checks](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}) to make sure the contents of your submission are okay. An update will be posted here shortly once the validation checks are passing.
-      - name: Update comment
-        if: steps.fc.outputs.comment-id != ''
-        uses: peter-evans/create-or-update-comment@v1
-        with:
-          comment-id: ${{ steps.fc.outputs.comment-id }}
-          edit-mode: replace
-          body: |
-            Thank you for your contribution 🎉, @${{ github.actor }}!
-
-            We're currently running [validation checks](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }}) to make sure the contents of your submission are okay. An update will be posted here shortly once the validation checks are passing.
-      - uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
-        with:
-          python-version: 3.8
-
-      - name: Install dependencies
-        run: |
-          python -m pip install pip --upgrade
-          python -m pip install python-frontmatter markdown-it-py pydantic[email]
-
-      - name: Validate input
-        run: |
-          python .github/workflows/collect-user-submission.py
-
-      - uses: actions/upload-artifact@v4
-        with:
-          name: submission
-          path: resource-gallery-submission-input.json
-
-  create-pull-request:
-    needs: validate-user-submission
-    runs-on: ubuntu-latest
-    defaults:
-      run:
-        shell: bash -l {0}
-    steps:
-      - uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
-        with:
-          python-version: 3.8
-      - uses: actions/download-artifact@v4
-        with:
-          name: submission
-
-      - name: Display structure of downloaded artifacts
-        run: |
-          ls -R
-
-      - name: Install dependencies
-        run: |
-          python -m pip install pip --upgrade
-          python -m pip install ruamel.yaml pre-commit
-
-      - name: Update resource gallery
-        shell: python
-        run: |
-          import yaml
-          import json
-
-          submission_file = 'resource-gallery-submission-input.json'
-          resource_gallery_file = 'portal/resource_gallery.yaml'
-
-          with open(submission_file, 'r') as file:
-              new_data = json.load(file)
-
-          with open(resource_gallery_file, 'r') as yaml_file:
-              existing_data = yaml.load(yaml_file, Loader=yaml.SafeLoader) or []
-
-          existing_data.append(new_data)
-
-          with open(resource_gallery_file, 'w') as yaml_file:
-              yaml.dump(existing_data, yaml_file, default_flow_style=False)
-
-      - name: Run pre-commit hooks
-        run: |
-          python -m pre_commit run --all-files
-          exit 0
-
-      - name: Create pull request
-        id: cpr
-        uses: peter-evans/create-pull-request@v3
-        with:
-          commit-message: 'Update resource gallery'
-          committer: GitHub <noreply@github.com>
-          author: ${{ github.actor }} <${{ github.actor }}@users.noreply.github.com>
-          signoff: false
-          branch: resource-gallery-${{ github.event.issue.number }}
-          title: 'Update resource gallery'
-          body: |
-            Update resource gallery as requested in #${{ github.event.issue.number }}. Closes #${{ github.event.issue.number }}.
-
-      - name: Find Comment
-        uses: peter-evans/find-comment@v1
-        id: fc
-        with:
-          issue-number: ${{ github.event.issue.number }}
-          comment-author: 'github-actions[bot]'
-          body-includes: We've created a pull request on your behalf
-
-      - name: Create comment
-        if: steps.fc.outputs.comment-id == ''
-        uses: peter-evans/create-or-update-comment@v1
-        with:
-          issue-number: ${{ github.event.issue.number }}
-          body: |
-            @${{ github.actor }}, your submission looks great! We've created a pull request on your behalf using the information you provided.
-
-            The pull request can be accessed from this url: ${{ steps.cpr.outputs.pull-request-url }}.
-
-      - name: Update comment
-        if: steps.fc.outputs.comment-id != ''
-        uses: peter-evans/create-or-update-comment@v1
-        with:
-          comment-id: ${{ steps.fc.outputs.comment-id }}
-          edit-mode: replace
-          body: |
-            @${{ github.actor }}, your submission looks great! We've created a pull request on your behalf using the information you provided.
-
-            The pull request can be accessed from this url: ${{ steps.cpr.outputs.pull-request-url }}.
diff --git a/.github/workflows/write-metrics-md.py b/.github/workflows/write-metrics-md.py
deleted file mode 100644
index 83a212900..000000000
--- a/.github/workflows/write-metrics-md.py
+++ /dev/null
@@ -1,68 +0,0 @@
-import json
-
-
-def process_user_data(json_file, top_pages, this_year, map, md_file):
-    """
-    Function for writing portal/metrics.md from saved files output by get-metrics.py
-    """
-    with open(json_file, 'r') as f:
-        user_data = json.load(f)
-
-    with open(md_file, 'w') as f:
-        f.write('# Metrics \n\n')
-        now = user_data['Now']
-        f.write(f'Last Updated: {now}')
-        user_data.pop('Now')
-        f.write('\n\n')
-
-        # Intro description
-        f.write(
-            'This metrics page provides an overview of user activity collected by Google Analytics across the three pillars of Project Pythia: our portal which includes information about the project as well as our resource gallery, our Foundations book, and our Cookbooks gallery. Information is either all-time (from a pre-project start date of March 2020) or year-to-date as indicated and is updated nightly to provide real-time and automated insights into our engagement, impact, and audience reach. If you would like to request a different metrics analysis, timeframe, or view, please [open a GitHub issue](https://github.com/ProjectPythia/projectpythia.github.io/issues/new/choose).\n\n'
-        )
-
-        # Markdown table
-        f.write('## Table of Total Active Users by Project\n\n')
-        f.write(
-            'This table displays the total active users of our 3 Pythia projects over the life of Project Pythia. Google analytics defines active users as the number of unique people who have visited the site and met certain [engagement requirements](https://support.google.com/analytics/answer/9234069?sjid=8697784525616937194-NC). You can read more from the [GA4 "Understand User Metrics" documentation](https://support.google.com/analytics/answer/12253918?hl=en).\n\n'
-        )
-        headers = '| Project | All-Time Users |'
-        separator = '| ' + ' | '.join(['-----'] * 2) + ' |'
-        rows = []
-        for key in user_data.keys():
-            rows.append('| ' + key + ' | ' + user_data[key] + ' |')
-        table = '\n'.join([headers, separator] + rows)
-        f.write(table)
-        f.write('\n\n')
-
-        # Add plots
-        f.write('## Chart of Active Users by Project Since Year Start\n\n')
-        f.write(
-            'This line plot displays active users for our 3 Pythia projects (Portal in purple, Foundations in blue, and Cookbooks in salmon) since January 1st of the current year.\n\n'
-        )
-        f.write(f'![Users this Year]({this_year})\n\n')
-
-        f.write('## Chart of Top 5 Pages by Project\n\n')
-        f.write(
-            'This bar-chart displays the top 5 pages by project over the life of Project Pythia, as determined by screen page views. Screen page views refers to the number of times users viewed a page, including repeated visits. To learn more visit the [GA4 "API Dimensions & Metrics" page](https://developers.google.com/analytics/devguides/reporting/data/v1/api-schema).\n\n'
-        )
-        f.write(f'![Top Pages]({top_pages})\n\n')
-
-        f.write('## Map of Total Foundation Active Users by Country\n\n')
-        f.write(
-            'This map displays the number of active users per country for Pythia Foundations for the entire life of Project Pythia.\n\n'
-        )
-        f.write(f'![Users by Country]({map})\n\n')
-
-    f.close()
-
-
-if __name__ == '__main__':
-    json_file = 'portal/metrics/user_metrics.json'  # Accessed from root repository
-
-    # HTML is built from within `portal/` directory, so paths differ from json file.
-    top_pages = 'metrics/toppages.png'
-    this_year = 'metrics/thisyear.png'
-    map = 'metrics/bycountry.png'
-
-    md_file = 'portal/metrics.md'  # Written from root repository
-    process_user_data(json_file, top_pages, this_year, map, md_file)
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 83f5fc078..1e1b30e19 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -15,15 +15,20 @@ repos:
       - id: black
 
   - repo: https://github.com/keewis/blackdoc
-    rev: v0.3.9
+    rev: v0.4.0
     hooks:
       - id: blackdoc
 
   - repo: https://github.com/PyCQA/flake8
-    rev: 7.1.2
+    rev: 7.2.0
     hooks:
       - id: flake8
 
+  - repo: https://github.com/asottile/seed-isort-config
+    rev: v2.2.0
+    hooks:
+      - id: seed-isort-config
+
   - repo: https://github.com/PyCQA/isort
     rev: 6.0.1
     hooks:
@@ -33,4 +38,9 @@ repos:
     rev: 1.9.1
     hooks:
       - id: nbqa-black
+        additional_dependencies: [black]
       - id: nbqa-pyupgrade
+        additional_dependencies: [pyupgrade]
+        exclude: foundations/quickstart.ipynb
+      - id: nbqa-isort
+        additional_dependencies: [isort]
diff --git a/.prettierrc.toml b/.prettierrc.toml
deleted file mode 100644
index addd6d363..000000000
--- a/.prettierrc.toml
+++ /dev/null
@@ -1,3 +0,0 @@
-tabWidth = 2
-semi = false
-singleQuote = true
diff --git a/myst.yml b/myst.yml
index 15760f4fe..df2c39bf7 100644
--- a/myst.yml
+++ b/myst.yml
@@ -21,7 +21,6 @@ project:
     - file: portal/cookbook-guide.md
     - file: portal/metrics.md
 site:
-  template: book-theme
   actions:
     - title: Learn More
       url: https://mystmd.org/guide
diff --git a/portal/Makefile b/portal/Makefile
deleted file mode 100644
index d4bb2cbb9..000000000
--- a/portal/Makefile
+++ /dev/null
@@ -1,20 +0,0 @@
-# Minimal makefile for Sphinx documentation
-#
-
-# You can set these variables from the command line, and also
-# from the environment for the first two.
-SPHINXOPTS    ?=
-SPHINXBUILD   ?= sphinx-build
-SOURCEDIR     = .
-BUILDDIR      = _build
-
-# Put it first so that "make" without argument is like "make help".
-help:
-	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
-
-.PHONY: help Makefile
-
-# Catch-all target: route all unknown targets to Sphinx using the new
-# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
-%: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
diff --git a/portal/_extensions/gallery_generator.py b/portal/_extensions/gallery_generator.py
deleted file mode 100644
index 922f23652..000000000
--- a/portal/_extensions/gallery_generator.py
+++ /dev/null
@@ -1,184 +0,0 @@
-import itertools
-import pathlib
-import re
-
-from truncatehtml import truncate
-
-
-def _generate_sorted_tag_keys(all_items):
-    key_set = set(itertools.chain(*[item['tags'].keys() for item in all_items]))
-    return sorted(key_set)
-
-
-def _title_case_preserve(s):
-    return re.sub(r'\b(\w)', lambda m: m.group(1).upper(), s)
-
-
-def _make_class(s):
-    return re.sub(r'^\d+', '', s.replace(' ', '-').lower())
-
-
-def _generate_tag_set(all_items, tag_key=None):
-    tag_set = set()
-    for item in all_items:
-        for k, e in item['tags'].items():
-            tags = [_title_case_preserve(t) for t in e]
-            if tag_key and k != tag_key:
-                continue
-            for t in tags:
-                tag_set.add(t)
-
-    return tag_set
-
-
-def _generate_tag_menu(all_items, tag_key):
-    tag_set = _generate_tag_set(all_items, tag_key)
-    tag_list = sorted(tag_set)
-
-    options = ''.join(
-        f'<li><label class="dropdown-item checkbox {tag_key}"><input type="checkbox" rel={_make_class(tag)} onchange="change();">&nbsp;{tag}</label></li>'
-        for tag in tag_list
-    )
-
-    return f"""
-            :::{{dropdown}} {tag_key}
-            <div class="dropdown">
-                <ul>
-                    {options}
-                </ul>
-            </div>
-            :::
-        """
-
-
-def generate_menu(all_items, submit_btn_txt=None, submit_btn_link=None):
-    key_list = _generate_sorted_tag_keys(all_items)
-
-    menu_html = '<div class="d-sm-flex mt-3 mb-4">\n'
-    menu_html += '<div class="d-flex gallery-menu">\n'
-    if submit_btn_txt:
-        menu_html += f'<div><a role="button" class="btn btn-primary btn-sm mx-1" href={submit_btn_link}>{submit_btn_txt}</a></div>\n'
-    menu_html += '</div>\n'
-    menu_html += '<div class="ml-auto d-flex">\n'
-    menu_html += '<div><button class="btn btn-link btn-sm mx-1" onclick="clearCbs()">Clear all filters</button></div>\n'
-    for tag_key in key_list:
-        menu_html += _generate_tag_menu(all_items, tag_key) + '\n'
-    menu_html += '</div>\n'
-    menu_html += '</div>\n'
-    menu_html += '<script>$(document).on("click",function(){$(".collapse").collapse("hide");}); </script>\n'
-    return menu_html
-
-
-def build_from_items(items, filename, title='Gallery', subtitle=None, subtext=None, menu_html='', max_descr_len=300):
-    # Build the gallery file
-    grid_body = []
-    for item in items:
-        if not item.get('thumbnail'):
-            item['thumbnail'] = '_static/images/ebp-logo.png'
-        thumbnail = item['thumbnail'][1:] if item['thumbnail'].startswith('/') else item['thumbnail']
-        tag_list = sorted((itertools.chain(*item['tags'].values())))
-        tag_list_f = [tag.replace(' ', '-') for tag in tag_list]
-
-        tags = [f'<span class="badge bg-primary mybadges">{_title_case_preserve(tag)}</span>' for tag in tag_list_f]
-        tags = '\n'.join(tags)
-        tag_classes = ' '.join(tag_list_f)
-
-        author_strs = set()
-        affiliation_strs = set()
-        for a in item['authors']:
-            author_name = a.get('name', 'Anonymous')
-            author_email = a.get('email', None)
-            if author_email:
-                _str = f'<a href="mailto:{author_email}">{author_name}</a>'
-            else:
-                _str = author_name
-            author_strs.add(_str)
-
-            affiliation_name = a.get('affiliation', None)
-            if affiliation_name:
-                affiliation_url = a.get('affiliation_url', None)
-                if affiliation_url:
-                    _str = f'<a href="{affiliation_url}">{affiliation_name}</a>'
-                else:
-                    _str = affiliation_name
-                affiliation_strs.add(_str)
-
-        authors_str = f"<strong>Author:</strong> {', '.join(author_strs)}"
-        if affiliation_strs:
-            affiliations_str = f"<strong>Affiliation:</strong> {' '.join(affiliation_strs)}"
-        else:
-            affiliations_str = ''
-
-        ellipsis_str = '<a class="modal-btn"> ... more</a>'
-        short_description = truncate(item['description'], max_descr_len, ellipsis=ellipsis_str)
-
-        if ellipsis_str in short_description:
-            modal_str = f"""
-            <div class="modal">
-                <div class="content">
-                    <img src="{thumbnail}" class="modal-img" />
-                    <h3 class="display-3">{item["title"]}</h3>
-                    {authors_str}
-                    <br/>
-                    {affiliations_str}
-                    <p class="my-2">{item['description']}</p>
-                    <p class="my-2">{tags}</p>
-                    <p class="mt-3 mb-0"><a href="{item["url"]}" class="btn btn-outline-primary btn-block">Visit Website</a></p>
-                </div>
-            </div>
-            """
-            modal_str = '\n'.join([m.lstrip() for m in modal_str.split('\n')])
-        else:
-            modal_str = ''
-
-        new_card = f"""
-                    :::{{grid-item-card}}
-                    :shadow: md
-                    :class-footer: card-footer
-                    :class-card: tagged-card {tag_classes}
-
-                    <div class="d-flex gallery-card">
-                        <img src="{thumbnail}" class="gallery-thumbnail" />
-                        <div class="container">
-                            <a href="{item["url"]}" class="text-decoration-none"><h4 class="display-4 p-0">{item["title"]}</h4></a>
-                            <p class="card-subtitle">{authors_str}<br/>{affiliations_str}</p>
-                            <p class="my-2">{short_description} </p>
-                        </div>
-                    </div>
-                    {modal_str}
-
-                    +++
-
-                    {tags}
-
-                    :::
-
-                    """
-
-        grid_body.append('\n'.join([m.lstrip() for m in new_card.split('\n')]))
-
-    stitle = f'#### {subtitle}' if subtitle else ''
-    stext = subtext if subtext else ''
-
-    grid_body = '\n'.join(grid_body)
-    grid = f"""\
-        {title}
-        {'=' * len(title)}
-
-        {stitle}
-        {stext}
-
-        {menu_html}
-
-        ::::{{grid}} 1
-        :gutter: 0
-
-        {grid_body}
-
-        <div class="modal-backdrop"></div>
-        <script src="../html/_static/custom.js"></script>
-    """
-
-    grid = '\n'.join([m.lstrip() for m in grid.split('\n')])
-
-    pathlib.Path(f'{filename}.md').write_text(grid)
diff --git a/portal/_extensions/resource_gallery_generator.py b/portal/_extensions/resource_gallery_generator.py
deleted file mode 100644
index 9f47a2d3e..000000000
--- a/portal/_extensions/resource_gallery_generator.py
+++ /dev/null
@@ -1,17 +0,0 @@
-import yaml
-from gallery_generator import build_from_items, generate_menu
-
-
-def main(app):
-    with open('resource_gallery.yaml') as fid:
-        all_items = yaml.safe_load(fid)
-
-    title = 'Resource Gallery'
-    submit_btn_link = 'https://github.com/ProjectPythia/projectpythia.github.io/issues/new?assignees=&labels=resource-gallery-submission&template=update-resource-gallery.md&title='
-    submit_btn_txt = 'Submit a new resource'
-    menu_html = generate_menu(all_items, submit_btn_txt=submit_btn_txt, submit_btn_link=submit_btn_link)
-    build_from_items(all_items, 'resource-gallery', title=title, menu_html=menu_html)
-
-
-def setup(app):
-    app.connect('builder-inited', main)
diff --git a/portal/_extensions/truncatehtml.py b/portal/_extensions/truncatehtml.py
deleted file mode 100644
index 9a6f63f54..000000000
--- a/portal/_extensions/truncatehtml.py
+++ /dev/null
@@ -1,183 +0,0 @@
-#!/usr/bin/env python
-
-# Copyright (c) 2015 Eric Entzel
-
-# Permission is hereby granted, free of charge, to any person obtaining a copy
-# of this software and associated documentation files (the "Software"), to deal
-# in the Software without restriction, including without limitation the rights
-# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-# copies of the Software, and to permit persons to whom the Software is
-# furnished to do so, subject to the following conditions:
-
-# The above copyright notice and this permission notice shall be included in all
-# copies or substantial portions of the Software.
-
-# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-# SOFTWARE.
-
-from __future__ import print_function
-
-END = -1
-
-# HTML5 void-elements that do not require a closing tag
-# https://html.spec.whatwg.org/multipage/syntax.html#void-elements
-VOID_ELEMENTS = (
-    'area',
-    'base',
-    'br',
-    'col',
-    'embed',
-    'hr',
-    'img',
-    'input',
-    'link',
-    'meta',
-    'param',
-    'source',
-    'track',
-    'wbr',
-)
-
-
-class UnbalancedError(Exception):
-    pass
-
-
-class OpenTag:
-    def __init__(self, tag, rest=''):
-        self.tag = tag
-        self.rest = rest
-
-    def as_string(self):
-        return '<' + self.tag + self.rest + '>'
-
-
-class CloseTag(OpenTag):
-    def as_string(self):
-        return '</' + self.tag + '>'
-
-
-class SelfClosingTag(OpenTag):
-    pass
-
-
-class Tokenizer:
-    def __init__(self, input):
-        self.input = input
-        self.counter = 0  # points at the next unconsumed character of the input
-
-    def __next_char(self):
-        self.counter += 1
-        return self.input[self.counter]
-
-    def next_token(self):
-        try:
-            char = self.input[self.counter]
-            self.counter += 1
-            if char == '&':
-                return self.__entity()
-            elif char != '<':
-                return char
-            elif self.input[self.counter] == '/':
-                self.counter += 1
-                return self.__close_tag()
-            else:
-                return self.__open_tag()
-        except IndexError:
-            return END
-
-    def __entity(self):
-        """Return a token representing an HTML character entity.
-        Precondition: self.counter points at the charcter after the &
-        Postcondition: self.counter points at the character after the ;
-        """
-        next_char = self.input[self.counter + 1]
-        if next_char == ' ':
-            return '&'
-
-        char = self.input[self.counter]
-        entity = ['&']
-        while char != ';':
-            entity.append(char)
-            char = self.__next_char()
-        entity.append(';')
-        self.counter += 1
-        return ''.join(entity)
-
-    def __open_tag(self):
-        """Return an open/close tag token.
-        Precondition: self.counter points at the first character of the tag name
-        Postcondition: self.counter points at the character after the <tag>
-        """
-        char = self.input[self.counter]
-        tag = []
-        rest = []
-        while char != '>' and char != ' ':
-            tag.append(char)
-            char = self.__next_char()
-        while char != '>':
-            rest.append(char)
-            char = self.__next_char()
-        if self.input[self.counter - 1] == '/':
-            self.counter += 1
-            return SelfClosingTag(''.join(tag), ''.join(rest))
-        elif ''.join(tag) in VOID_ELEMENTS:
-            self.counter += 1
-            return SelfClosingTag(''.join(tag), ''.join(rest))
-        else:
-            self.counter += 1
-            return OpenTag(''.join(tag), ''.join(rest))
-
-    def __close_tag(self):
-        """Return an open/close tag token.
-        Precondition: self.counter points at the first character of the tag name
-        Postcondition: self.counter points at the character after the <tag>
-        """
-        char = self.input[self.counter]
-        tag = []
-        while char != '>':
-            tag.append(char)
-            char = self.__next_char()
-        self.counter += 1
-        return CloseTag(''.join(tag))
-
-
-def truncate(str, target_len, ellipsis=''):
-    """Returns a copy of str truncated to target_len characters,
-    preserving HTML markup (which does not count towards the length).
-    Any tags that would be left open by truncation will be closed at
-    the end of the returned string.  Optionally append ellipsis if
-    the string was truncated."""
-    stack = []  # open tags are pushed on here, then popped when the matching close tag is found
-    retval = []  # string to be returned
-    length = 0  # number of characters (not counting markup) placed in retval so far
-    tokens = Tokenizer(str)
-    tok = tokens.next_token()
-    while tok != END:
-        if length >= target_len and tok == ' ':
-            retval.append(ellipsis)
-            break
-        if tok.__class__.__name__ == 'OpenTag':
-            stack.append(tok)
-            retval.append(tok.as_string())
-        elif tok.__class__.__name__ == 'CloseTag':
-            if stack[-1].tag == tok.tag:
-                stack.pop()
-                retval.append(tok.as_string())
-            else:
-                raise UnbalancedError(tok.as_string())
-        elif tok.__class__.__name__ == 'SelfClosingTag':
-            retval.append(tok.as_string())
-        else:
-            retval.append(tok)
-            length += 1
-        tok = tokens.next_token()
-    while len(stack) > 0:
-        tok = CloseTag(stack.pop().tag)
-        retval.append(tok.as_string())
-    return ''.join(retval)
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diff --git a/portal/_static/thumbnails/geopandas_icon.png b/portal/_static/thumbnails/geopandas_icon.png
deleted file mode 100644
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diff --git a/portal/_static/thumbnails/matplotlib.svg b/portal/_static/thumbnails/matplotlib.svg
deleted file mode 100644
index 6e4f4f49c..000000000
--- a/portal/_static/thumbnails/matplotlib.svg
+++ /dev/null
@@ -1,10 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<svg xmlns="http://www.w3.org/2000/svg" width="128" height="128" stroke="#777" fill-opacity=".8">
-<path fill="#FFF" d="m63,1a63,63 0 1,0 2,0zm0,14a49,49 0 1,0 2,0zm0,14a35,35 0 1,0
-2,0zm0,14a21,21 0 1,0 2,0zm0,14a7,7 0 1,0 2,0zm64,7H1m108-45-90,90m90,0-90-90m45-18v126"/>
-<path fill="#F60" d="m50,8-20,10 68,92 10-10L64,64z"/>
-<path fill="#FC0" d="m17,50v28L64,64z"/>
-<path fill="#7F7" d="m64,64 6,35H58z"/>
-<path fill="#CF3" d="m64,64 13-40 9,5z"/>
-<path fill="#04F" d="m64,64 14-6 1,4zl-26,13 3,4z"/>
-</svg>
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diff --git a/portal/_static/thumbnails/zero-to-pandas.png b/portal/_static/thumbnails/zero-to-pandas.png
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diff --git a/portal/cookbook-guide.md b/portal/cookbook-guide.md
index 487c42b09..2b9018baa 100644
--- a/portal/cookbook-guide.md
+++ b/portal/cookbook-guide.md
@@ -47,9 +47,9 @@ In the rest of this guide, we assume that you are familiar with the basics of us
 
 In order for your Cookbook to be included in the Gallery, the source repository needs to be housed within the [Project Pythia GitHub organization](https://github.com/ProjectPythia).
 
-You can keep your repository in your personal GitHub space while you're developing your content if that works better for you. Repository ownership can be transfered at any time.
+You can keep your repository in your personal GitHub space while you're developing your content if that works better for you. Repository ownership can be transferred at any time.
 
-However, we recommend transfering to the Pythia organization early, for a few reasons:
+However, we recommend transferring to the Pythia organization early, for a few reasons:
 - Fewer settings to tweak later
 - Easier to get help from the Pythia infrastructure team
 - Encourages collaboration
@@ -63,14 +63,14 @@ Also, _don't worry about breaking anything!_ Your repo will not affect any other
 ### Steps to transfer the repository
 
 1. [Contact the Pythia team via the Pangeo Discourse](https://discourse.pangeo.io/c/education/project-pythia/60) (or otherwise) to let us know about your cookbook.
-1. You will get an invitation to join the the [ProjectPythia organization](https://github.com/ProjectPythia).
+1. You will get an invitation to join the [ProjectPythia organization](https://github.com/ProjectPythia).
 1. Accept the GitHub invitation. _Welcome to the team!_
 1. Once you are a member of the organization, navigate to the Settings of your cookbook repository and scroll down to the **Danger Zone**.
 1. Click "Transfer".
 1. Select or type "ProjectPythia", confirm, and transfer.
 1. When prompted about which teams to give access to, select "core". _This will enable the Pythia maintenance team to have full access to your repository._
 
-Once you have successfully transfered the repository, you'll most likely want to make a [personal fork and a local clone of the repository](https://foundations.projectpythia.org/foundations/github/github-cloning-forking.html) so that you can continue to develop and collaborate on the Cookbook via the [forking workflow](https://foundations.projectpythia.org/foundations/github/github-workflows.html#forking-workflow).
+Once you have successfully transferred the repository, you'll most likely want to make a [personal fork and a local clone of the repository](https://foundations.projectpythia.org/foundations/github/github-cloning-forking.html) so that you can continue to develop and collaborate on the Cookbook via the [forking workflow](https://foundations.projectpythia.org/foundations/github/github-workflows.html#forking-workflow).
 
 ## Customize the paths in your repository
 
@@ -170,7 +170,7 @@ The link to your published book will then be displayed on the home page of the r
 ```{note}
 If you have transfered your repository to the ProjectPythia organization and also made a personal fork, the publishing pipeline automation will _only run on the upstream fork on the ProjectPythia organization_ so there's only one copy of the "published" book.
 
-It's possible to enable the workflows on your personal fork, but usually unneccesary if you preview your work via Pull Requests (see next section)!
+It's possible to enable the workflows on your personal fork, but usually unnecessary if you preview your work via Pull Requests (see next section)!
 ```
 
 ### Pull Requests and previews
@@ -206,7 +206,7 @@ The Binder uses your `environment.yml` file to create an image of an execution e
 
 ## Publish your Cookbook on the Pythia Gallery
 
-Once you're happy with your content and your Cookbook is building and deploying properly, it's time to think about submiting it for inclusion in the [Cookbook Gallery](https://cookbooks.projectpythia.org/)!
+Once you're happy with your content and your Cookbook is building and deploying properly, it's time to think about submitting it for inclusion in the [Cookbook Gallery](https://cookbooks.projectpythia.org/)!
 
 ```{note}
 Cookbooks don't need to be "finished" in order to accepted in the Gallery! Cookbooks are typically accepted so long as they run cleanly, are free of obvious errors, and have some relevant new content.
@@ -218,7 +218,7 @@ At this stage, there are a few more steps to get things ready to go.
 
 ### Authorship and the `CITATION.cff` file
 
-Cookbooks are scholarly objects. As part of the publication process, your Cookbook will get a citeable DOI (via [Zenodo](https://zenodo.org)). Just as for journal publications, you need to make decisions about who gets credited for authorship.
+Cookbooks are scholarly objects. As part of the publication process, your Cookbook will get a citable DOI (via [Zenodo](https://zenodo.org)). Just as for journal publications, you need to make decisions about who gets credited for authorship.
 
 This information is managed manually through the file `CITATION.cff` in the root of your repository. This will determine the names displayed on your card in the [gallery](https://cookbooks.projectpythia.org/) as well as your DOI-based citation.
 
diff --git a/portal/make.bat b/portal/make.bat
deleted file mode 100644
index 2119f5109..000000000
--- a/portal/make.bat
+++ /dev/null
@@ -1,35 +0,0 @@
-@ECHO OFF
-
-pushd %~dp0
-
-REM Command file for Sphinx documentation
-
-if "%SPHINXBUILD%" == "" (
-	set SPHINXBUILD=sphinx-build
-)
-set SOURCEDIR=.
-set BUILDDIR=_build
-
-if "%1" == "" goto help
-
-%SPHINXBUILD% >NUL 2>NUL
-if errorlevel 9009 (
-	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.http://sphinx-doc.org/
-	exit /b 1
-)
-
-%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-goto end
-
-:help
-%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-
-:end
-popd
diff --git a/portal/metrics/user_metrics.json b/portal/metrics/user_metrics.json
deleted file mode 100644
index 57a123c7f..000000000
--- a/portal/metrics/user_metrics.json
+++ /dev/null
@@ -1 +0,0 @@
-{"Now": "", "Portal": "0K", "Foundations": "0K", "Cookbooks": "0K"}
diff --git a/portal/posts/cookoff2025-website.md b/portal/posts/cookoff2025-website.md
index 0d0a40630..2955bbf63 100644
--- a/portal/posts/cookoff2025-website.md
+++ b/portal/posts/cookoff2025-website.md
@@ -4,9 +4,9 @@ author: Julia Kent
 tags: [cook-off]
 ---
 
-# Save the date for the 2025 Cook-off hackathon!
+# Register now for the 2025 Cook-off hackathon!
 
 The 2025 Pythia Cookbook Cook-Off Hackathon will take place August
 5-8, at the NCAR Mesa Lab, located in Boulder, Colorado.
 
-[The website for the event is live](https://projectpythia.org/pythia-cookoff-2025/). Registration is not open at this time.
+[The website for the event is live](https://projectpythia.org/pythia-cookoff-2025/). Registration is now open!
diff --git a/portal/posts/new-cookbooks.md b/portal/posts/new-cookbooks.md
index e0132edf0..dcaeed4b1 100644
--- a/portal/posts/new-cookbooks.md
+++ b/portal/posts/new-cookbooks.md
@@ -58,7 +58,7 @@ This Cookbook covers paleoclimate model-data comparison using spatio-temporal pa
 
 Paleoclimate observations obtained from tree rings or the geochemical composition of speleothems, ice and sediments provide an out-of-sample validation of climate models. However, comparing the output of climate models directly with the paleoclimate observations is difficult: (1) they are often expressed in different quantities (i.e., temperature vs ring width), (2) paleoclimate observations have large time uncertainties, (3) paleoclimate observations often incorporate more than one environmental signal (i.e., temperature AND moisture).
 
-Recently, [Steinman et al. (2022)](https://doi.org/10.1073/pnas.2120015119) used PCA analysis to compare model and data output. Here, we use a similar approach with the [CESM Last Millennium simulation](https://www2.cesm.ucar.edu/models/cesm1.2/) and proxy records stored on the [LiPDverse](https://lipdverse.org). This repository contains paleoclimate datasets that have been curated by the community and are archived in a standard format, facilitating analysis.
+Recently, [Steinman et al. (2022)](https://doi.org/10.1073/pnas.2120015119) used PCA analysis to compare model and data output. Here, we use a similar approach with the [CESM Last Millennium simulation](https://www.cesm.ucar.edu/community-projects/lme) and proxy records stored on the [LiPDverse](https://lipdverse.org). This repository contains paleoclimate datasets that have been curated by the community and are archived in a standard format, facilitating analysis.
 
 **Contributors:**
 <a href="https://github.com/ProjectPythia/paleoPCA-Cookbook/graphs/contributors">
diff --git a/portal/resource_gallery.yaml b/portal/resource_gallery.yaml
deleted file mode 100644
index 70fefa7f2..000000000
--- a/portal/resource_gallery.yaml
+++ /dev/null
@@ -1,1571 +0,0 @@
-- title: Your First Python Tutorial
-  url: https://ncar.github.io/python-tutorial/index.html
-  description: |
-    A tutorial for getting started with Python aimed at scientists with experience in at least one other coding language. Designed to teach you Python, not package specific syntax.
-  authors:
-  - name: Xdev Team
-    email: xdev@ucar.edu
-    url: https://ncar.github.io/xdev/
-    affiliation: NSF NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/Xdev.png
-  tags:
-    packages:
-    - pure python
-    formats:
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Unidata Python Training
-  url: https://unidata.github.io/python-training/python/intro-to-python/
-  description: |
-    Introduction to Python for Atmospheric Science and Meteorology. Unidata is working to create a collection of online training materials focused on the use of Python in the atmospheric sciences. While our examples and scenarios may feature Unidata tools and data technologies, our aim is to present a generic set of freely available tools that are generally useful to scientists, educators, and students in the geosciences, broadly defined.
-  authors:
-  - affiliation: Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/unidata_150x150.png
-  tags:
-    formats:
-    - course
-    affiliation:
-    - unidata
-
-- title: Unidata Python Workshop - Jupyter Notebooks Introduction
-  url:
-    https://unidata.github.io/python-training/workshop/Jupyter_Notebooks/jupyter-notebooks-introduction/
-  description: |
-    Jupyter notebooks are a great way to have code, output, images, video, and other information in one place. Notebooks are an ideal tool for the student, research scientist, and even software developer. In this lesson we will go over the basic features of Jupyter notebooks and how to use them.
-  authors:
-  - affiliation: Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/unidata_150x150.png
-  tags:
-    packages:
-    - jupyter
-    affiliation:
-    - unidata
-
-- title: An Introduction to Earth and Environmental Data Science
-  url: https://earth-env-data-science.github.io/intro
-  description: |
-    This book grew out of a course developed at Columbia University called Research Computing in Earth Science. It was written mostly by Ryan Abernathey, with significant contributions from Kerry Key. By separating the book from the class, we hope to create an open-source community resource for python education in the Earth and Environmental Sciences.
-  authors:
-  - name: Ryan Abernathey
-    affiliation: Lamont-Doherty Earth Observatory
-  - name: Kerry Key
-    affiliation: Lamont-Doherty Earth Observatory
-  thumbnail: /_static/thumbnails/earth_env_data_science.png
-  tags:
-    formats:
-    - course
-    affiliation:
-    - pangeo
-
-- title: The Climate Laboratory
-  url: https://brian-rose.github.io/ClimateLaboratoryBook/home
-  description: |
-    A hands on approach to climate physics and climate modeling. Fundamental climate processes are introduced through interactive and reproducible Python-based modeling exercises.  This JupyterBook serves as a course textbook at the University of Albany.
-  authors:
-  - name: Brian Rose
-    url: http://www.atmos.albany.edu/facstaff/brose/
-    affiliation: University of Albany
-  thumbnail: /_static/thumbnails/climlablogo.png
-  tags:
-    formats:
-    - course
-    - book
-    domains:
-    - climate science
-    - atmospheric science
-    packages:
-    - climlab
-
-- title: Earth Analytics Python Course
-  url: https://www.earthdatascience.org/courses/earth-analytics-python/
-  description: |
-    Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of heterogeneous ‘big scientific data’. This course is designed for graduate students and students participating in the Earth Data Analytics Professional Certificate.
-  authors:
-  - name: Earth Lab
-    url: https://www.earthdatascience.org/
-    affiliation: University of Colorado Boulder
-  thumbnail: /_static/thumbnails/earth-lab-logo.png
-  tags:
-    formats:
-    - course
-
-- title: Earth Data Science
-  url: https://www.earthdatascience.org/
-  description: |
-    This site contains open, tutorials and course materials covering topics including data integration, GIS and data intensive science.
-  authors:
-  - name: Earth Lab
-    affiliation: University of Colorado Boulder
-  thumbnail: /_static/thumbnails/earth-lab-logo.png
-  tags:
-    formats:
-    - course
-
-- title: Geohackweek 2019
-  url: https://geohackweek.github.io/
-  description: |
-    Geohackweek is a 5-day hackweek to be held at the University of Washington eScience Institute. Tutorials from the hackweek are available for everyone to follow (participants and non-participants alike).
-  authors:
-  - name: eScience Institute
-    url: https://escience.washington.edu/
-    affiliation: University of Washington
-  thumbnail: /_static/thumbnails/eScience_Logo_HR.png
-  tags:
-    formats:
-    - course
-
-- title: Research Software Engineering with Python
-  url: https://merely-useful.github.io/py-rse/
-  description: |
-    We believe every researcher should know how to write short programs that clean and analyze data in a reproducible way and how to use version control to keep track of what they have done. But just as some astronomers spend their careers designing telescopes, some researchers focus on building the software that makes research possible. People who do this are called research software engineers; the aim of this book is to get you ready for this role by helping you go from writing code for yourself to creating tools that help your entire field advance.
-  authors:
-  - name: Damien Irving, et al.
-  thumbnail:
-  tags:
-    formats:
-    - course
-
-- title: Data Analysis with Python- Zero to Pandas
-  url: https://jovian.ai/learn/data-analysis-with-python-zero-to-pandas
-  description: |
-    "Data Analysis with Python: Zero to Pandas" is a practical and beginner-friendly introduction to data analysis covering the basics of Python, Numpy, Pandas, Data Visualization, and Exploratory Data Analysis.
-  authors:
-  - name: Jovian.ai
-    url: https://www.jovian.ai/
-  thumbnail: /_static/thumbnails/zero-to-pandas.png
-  tags:
-    formats:
-    - course
-
-- title: MTH271- Mathematical Computing with Data
-  url: http://web.pdx.edu/~gjay/teaching/mth271_2020/html/_CONTENTS.html
-  description: |
-    In this course, we will have multiple occasions to procure, analyze, and visualize data. We will study mathematical and statistical techniques to discern patterns in complex data. We shall do so in an ecosystem of python computing modules developed by open-source enthusiasts worldwide.
-  authors:
-  - name: Jay Gopalakrishnan
-    url: http://web.pdx.edu/~gjay/
-    affiliation: Portland State University
-  thumbnail: /_static/thumbnails/portland-state.png
-  tags:
-    formats:
-    - course
-
-- title: ATSC301- Atmospheric Radiation and Remote Sensing
-  url: https://clouds.eos.ubc.ca/~phil/courses/atsc301/
-  description: |
-    This course teaches radiation and remote sensing, but also covers: how to write clear, documented and tested code that can ingest, manipulate and display data, and how to turn equations into computer algorithms in Python.
-  authors:
-  - name: Philip Austin
-    email: paustin@eos.ubc.ca
-    affiliation: University of British Columbia
-  thumbnail: /_static/thumbnails/british-columbia.jpg
-  tags:
-    formats:
-    - course
-    domains:
-    - remote sensing
-
-- title: Introduction to Geospatial Concepts
-  url: https://datacarpentry.org/organization-geospatial/
-  description: |
-    The goal of this lesson is to provide an introduction to core geospatial data concepts. It is intended for learners who have no prior experience working with geospatial data, and as a pre-requisite for the R for Raster and Vector Data lesson . This lesson can be taught in approximately 75 minutes and covers the following topics: Introduction to raster and vector data format and attributes, examples of data types commonly stored in raster vs vector format, an introduction to categorical vs continuous raster data and multi-layer rasters, an introduction to the file types and R packages used in the remainder of this workshop, an introduction to coordinate reference systems and the PROJ4 format,  and an overview of commonly used programs and applications for working with geospatial data.
-  authors:
-  - name: The Carpentries
-    url: https://carpentries.org/
-  thumbnail: /_static/thumbnails/DC_logo_vision.png
-  tags:
-    formats:
-    - course
-
-- title: Dani Arribas-Bel Course Repositories
-  url: http://darribas.org/materials.html
-  description: |
-    A collection of courework repositories for various data science classes taught by Dani Arribas-Bel.
-  authors:
-  - name: Dani Arribas-Bel
-    affiliation: University of Liverpool Department of Geography and Planning
-    affiliation_url: https://www.liverpool.ac.uk/geography-and-planning/
-  thumbnail:
-  tags:
-    formats:
-    - course
-    domains:
-    - data science
-
-- title: Cartopy Documentation
-  url: https://scitools.org.uk/cartopy/docs/latest/
-  description: |
-    Cartopy is a Python package designed for geospatial data processing in order to produce maps and other geospatial data analyses.
-  authors:
-  - name: UK Met Office
-  thumbnail: /_static/thumbnails/cartopy.png
-  tags:
-    packages:
-    - cartopy
-    formats:
-    - documentation
-
-- title: Cartopy Gallery
-  url: https://scitools.org.uk/cartopy/docs/latest/gallery/index.html
-  description: |
-    Visual examples demonstrating some of the functionality of Cartopy, particularly its matplotlib interface.
-  authors:
-  - name: UK Met Office
-  thumbnail: /_static/thumbnails/cartopy.png
-  tags:
-    packages:
-    - cartopy
-    formats:
-    - gallery
-  domains:
-  - data visualization
-
-- title: Contextily Documentation
-  url: https://contextily.readthedocs.io
-  description: |
-    contextily is a small Python 3 (3.6 and above) package to retrieve tile maps from the internet. It can add those tiles as basemap to matplotlib figures or write tile maps to disk into geospatial raster files. Bounding boxes can be passed in both WGS84 (EPSG:4326) and Spheric Mercator (EPSG:3857).
-  authors:
-  - name: Dani Arribas-Bel & Contexily Contributors
-  thumbnail:
-  tags:
-    packages:
-    - contextily
-    formats:
-    - documentation
-    - gallery
-
-- title: Contextily Tutorial
-  url: https://contextily.readthedocs.io/en/latest/intro_guide.html
-  description: |
-    Welcome to the taster guide for contextily, the package for contextual tiles in Python. In this notebook, we will show the basic functionality available in contextily, a package to work with web-tiles for background maps. To do that, we will use additional data to illustrate contextily can be integrated with other libraries such as geopandas and rasterio.
-  authors:
-  - name: Dani Arribas-Bel & Contexily Contributors
-  thumbnail:
-  tags:
-    packages:
-    - contextily
-    formats:
-    - tutorial
-
-- title: Dask
-  url: https://dask.org
-  description: |
-    Dask provides advanced parallelism for analytics, enabling performance at scale for the tools you love.
-  authors:
-  - name: Dask core developers
-  thumbnail: /_static/thumbnails/dask.png
-  tags:
-    packages:
-    - dask
-    formats:
-    - documentation
-
-- title: Dask Tutorial
-  url: https://tutorial.dask.org/
-  description: |
-    Dask is a parallel computing library that scales the existing Python ecosystem. This tutorial will introduce Dask and parallel data analysis more generally.
-  authors:
-  - name: Dask Developers
-  thumbnail: /_static/thumbnails/dask.png
-  tags:
-    packages:
-    - dask
-    formats:
-    - tutorial
-
-- title: GeoCAT Tutorial
-  url: https://geocat-comp.readthedocs.io/en/latest/examples.html
-  description: |
-    The examples below show GeoCAT-comp functions being utilized in real-world use cases. They also demonstrate how GeoCAT-comp can be used to make plots with Matplotlib (using Cartopy) and PyNGL (work in progress).
-  authors:
-  - name: GeoCat
-    url: https://geocat.ucar.edu/
-    affiliation: NSF NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/geocat.png
-  tags:
-    packages:
-    - geocat-comp
-    formats:
-    - tutorial
-
-- title: GeoCAT Gallery
-  url: https://geocat-examples.readthedocs.io/
-  description: |
-    A gallery of plotting examples from GeoCat.
-  authors:
-  - name: GeoCAT
-    url: https://geocat.ucar.edu/
-    affiliation: NSF NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/geocat.png
-  tags:
-    packages:
-    - geocat-comp
-    - geocat-viz
-    formats:
-    - gallery
-    domains:
-    - data visualization
-
-- title: GeoPandas Documentation
-  url: https://geopandas.org
-  description: |
-    GeoPandas is an open source project to make working with geospatial data in python easier. GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types. Geometric operations are performed by shapely. Geopandas further depends on fiona for file access and matplotlib for plotting.
-  authors:
-  - name: GeoPandas developers
-  thumbnail: /_static/thumbnails/geopandas_icon.png
-  tags:
-    packages:
-    - geopandas
-    formats:
-    - documentation
-
-- title: GeoPandas Gallery
-  url: https://geopandas.org/gallery/index.html
-  description: |
-    Examples that show off the functionality in GeoPandas. They highlight many of the things you can do with this package, and show off some best-practices.
-  authors:
-  - name: GeoPandas developers
-  thumbnail: /_static/thumbnails/geopandas_icon.png
-  tags:
-    packages:
-    - geopandas
-    formats:
-    - gallery
-
-- title: hvPlot
-  url: https://hvplot.holoviz.org/
-  description: |
-    hvPlot provides a high-level plotting API built on HoloViews that provides a general and consistent API for plotting data in all the abovementioned formats. hvPlot can integrate neatly with the individual libraries if an extension mechanism for the native plot APIs is offered, or it can be used as a standalone component.
-  authors:
-  - name: HoloViz developers
-    url: https://holoviz.org/
-  thumbnail: /_static/thumbnails/hvplot-wm.png
-  tags:
-    packages:
-    - hvPlot
-    formats:
-    - documentation
-
-- title: hvPlot Tutorial
-  url: https://hvplot.holoviz.org/user_guide/index.html
-  description: |
-    The user guide provides a detailed introduction to the API and features of hvPlot. In the Introduction you will learn how to activate the plotting API and start using it. Next you will learn to use the API for tabular data and get an overview of the types of plots you can generate and how to customize them; including how to customize interactivity using widgets. Next is an overview on how to display and save plots in the notebook, on the commandline, and from a script. Another section will introduce you to generating subplots from your data. Once the basics are covered you can learn how to use the plotting API for specific types of data including streaming data, gridded data network graphs, geographic data, and timeseries data.
-  authors:
-  - name: HoloViz developers
-    url: https://holoviz.org/
-  thumbnail: /_static/thumbnails/hvplot-wm.png
-  tags:
-    packages:
-    - hvPlot
-    formats:
-    - tutorial
-    domains:
-    - data visualization
-
-- title: hvPlot Gallery
-  url: https://hvplot.holoviz.org/reference/index.html
-  description: |
-    Incomplete Reference Gallery containing some small examples of different plot types using hvPlot.
-  authors:
-  - name: HoloViz developers
-    url: https://holoviz.org/
-  thumbnail: /_static/thumbnails/hvplot-wm.png
-  tags:
-    packages:
-    - hvPlot
-    formats:
-    - gallery
-    domains:
-    - data visualization
-
-- title: Ipyleaflet
-  url: https://ipyleaflet.readthedocs.io
-  description: |
-    Interactive maps in the Jupyter notebook.
-  authors:
-  - name: The Jupyter development team
-  thumbnail:
-  tags:
-    packages:
-    - ipyleaflet
-    formats:
-    - documentation
-
-- title: Matplotlib
-  url: https://matplotlib.org/
-  description: |
-    Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python.
-  authors:
-  - name: the Matplotlib development team
-  thumbnail: /_static/thumbnails/matplotlib.svg
-  tags:
-    packages:
-    - matplotlib
-    formats:
-    - documentation
-    domains:
-    - data visualization
-
-- title: Matplotlib Tutorial
-  url: https://matplotlib.org/stable/tutorials/index.html
-  description: |
-    This page contains more in-depth guides for using Matplotlib. It is broken up into beginner, intermediate, and advanced sections, as well as sections covering specific topics.
-  authors:
-  - name: the Matplotlib development team
-  thumbnail: /_static/thumbnails/matplotlib.svg
-  tags:
-    packages:
-    - matplotlib
-    formats:
-    - tutorial
-    domains:
-    - data visualization
-
-- title: Matplotlib Gallery
-  url: https://matplotlib.org/stable/gallery/index.html
-  description: |
-    This gallery contains examples of the many things you can do with Matplotlib.
-  authors:
-  - name: the Matplotlib development team
-  thumbnail: /_static/thumbnails/matplotlib.svg
-  tags:
-    packages:
-    - matplotlib
-    formats:
-    - gallery
-    domains:
-    - data visualization
-
-- title: MetPy
-  url: https://unidata.github.io/MetPy/latest/index.html
-  description: |
-    MetPy is a collection of tools in Python for reading, visualizing, and performing calculations with weather data.
-  authors:
-  - name: MetPy developers
-    affiliation: NSF Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/metpy.jpg
-  tags:
-    packages:
-    - metpy
-    formats:
-    - documentation
-
-- title: MetPy Tutorial
-  url: https://unidata.github.io/MetPy/latest/tutorials/index.html
-  description: |
-    This collection of tutorials (under development) demonstrates the use of MetPy to perform common meteorological tasks.
-  authors:
-  - name: MetPy developers
-    affiliation: NSF Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/metpy.jpg
-  tags:
-    packages:
-    - metpy
-    formats:
-    - tutorial
-
-- title: Unidata Python Workshop - MetPy
-  url:
-    https://unidata.github.io/python-training/workshop/Metpy_Introduction/introduction-to-metpy/
-  description: |
-    MetPy is a modern meteorological open-source toolkit for Python. It is a maintained project of Unidata to serve the academic meteorological community. MetPy consists of three major areas of functionality: plots, calculations, and file i/o.
-  authors:
-  - affiliation: Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/unidata_150x150.png
-  tags:
-    packages:
-    - metpy
-    formats:
-    - tutorial
-
-- title: MetPy Gallery
-  url: https://unidata.github.io/MetPy/latest/examples/index.html
-  description: |
-    Examples of using a variety of MetPy’s functionality together.
-  authors:
-  - name: MetPy Developers
-    affiliation: NSF Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/metpy.jpg
-  tags:
-    packages:
-    - metpy
-    formats:
-    - gallery
-
-- title: MetPy Mondays
-  url: https://www.youtube.com/playlist?list=PLQut5OXpV-0ir4IdllSt1iEZKTwFBa7kO
-  description: |
-    A weekly video series showing how to use MetPy or other Python libraries to solve problems relevant to geoscience applications.
-  authors:
-  - affiliation: NSF Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/metpy-mondays.jpeg
-  tags:
-    packages:
-    - metpy
-    formats:
-    - video
-
-- title: Numpy
-  url: https://numpy.org
-  description: |
-    The fundamental package for scientific computing with Python.
-  authors:
-  - name: NumPy
-  thumbnail: /_static/thumbnails/numpy.png
-  tags:
-    packages:
-    - numpy
-    formats:
-    - documentation
-
-- title: Numpy Tutorials
-  url: https://numpy.org/learn/
-  description: |
-    A curated collection of external resources teaching numpy from beginner to advanced uses.
-  authors:
-  - name: NumPy
-  thumbnail: /_static/thumbnails/numpy.png
-  tags:
-    packages:
-    - numpy
-
-- title: Intro to Numerical Computing with NumPy
-  url: https://youtu.be/ZB7BZMhfPgk
-  description: |
-    NumPy provides Python with a powerful array processing library and an elegant syntax that is well suited to expressing computational algorithms clearly and efficiently. We'll introduce basic array syntax and array indexing, review some of the available mathematical functions in NumPy, and discuss how to write your own routines. Along the way, we'll learn just enough about matplotlib to display results from our examples.
-  authors:
-  - name: A. Chabot-LeClerc
-    affiliation: Enthought
-    affiliation_url: https://www.enthought.com/
-  thumbnail: /_static/thumbnails/Enthought.png
-  tags:
-    packages:
-    - numpy
-    formats:
-    - video
-
-- title: Pandas
-  url: https://pandas.pydata.org/
-  description: |
-    Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
-  authors:
-  - name: Pandas Development Team
-  thumbnail: /_static/thumbnails/pandas.png
-  tags:
-    packages:
-    - pandas
-    formats:
-    - documentation
-
-- title: Pandas Tutorials
-  url: https://pandas.pydata.org/docs/getting_started/intro_tutorials/index.html
-  description: |
-    Tutorial for getting started with pandas.
-  authors:
-  - name: Pandas Development Team
-  thumbnail: /_static/thumbnails/pandas.png
-  tags:
-    packages:
-    - pandas
-    formats:
-    - tutorial
-
-- title: Pandas Gallery
-  url: https://pandas.pydata.org/pandas-docs/stable/user_guide/visualization.html
-  description: |
-    A gallery of example pandas functionality.
-  authors:
-  - name: Pandas Development Team
-  thumbnail: /_static/thumbnails/pandas.png
-  tags:
-    packages:
-    - pandas
-    formats:
-    - gallery
-
-- title: Rasterio
-  url: https://rasterio.readthedocs.io
-  description: |
-    Geographic information systems use GeoTIFF and other formats to organize and store gridded raster datasets such as satellite imagery and terrain models. Rasterio reads and writes these formats and provides a Python API based on Numpy N-dimensional arrays and GeoJSON.
-  authors:
-  - name: MapBox
-  thumbnail:
-  tags:
-    packages:
-    - rasterio
-    formats:
-    - documentation
-
-- title: Rasterio Tutorial
-  url: https://rasterio.readthedocs.io/en/latest/quickstart.html
-  description: |
-    This document explains how to use Rasterio to read existing files and to create new files. Some advanced topics are glossed over to be covered in more detail elsewhere in Rasterio’s documentation.
-  authors:
-  - name: MapBox
-  thumbnail: /_static/thumbnails/rasterio-tutorial.png
-  tags:
-    packages:
-    - rasterio
-    formats:
-    - tutorial
-
-- title: Siphon
-  url: https://unidata.github.io/siphon
-  description: |
-    Siphon is a collection of Python utilities for downloading data from remote data services. Much of Siphon’s current functionality focuses on access to data hosted on a THREDDS Data Server. It also provides clients to a variety of simple web services.
-  authors:
-  - name: Siphon Contributors
-    affiliation: NSF Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/siphon.png
-  tags:
-    packages:
-    - siphon
-    formats:
-    - documentation
-
-- title: Siphon Gallery
-  url: https://unidata.github.io/siphon/latest/examples/index.html
-  description: |
-    Examples of using Siphon’s functionality.
-  authors:
-  - name: Siphon Contributors
-    affiliation: NSF Unidata
-    affiliation_url: https://www.unidata.ucar.edu/
-  thumbnail: /_static/thumbnails/siphon.png
-  tags:
-    packages:
-    - siphon
-    formats:
-    - gallery
-
-- title: WRF-Python
-  url: https://wrf-python.readthedocs.io
-  description: |
-    A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model.
-  authors:
-  - affiliation: NSF NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail:
-  tags:
-    packages:
-    - wrf-python
-    formats:
-    - documentation
-
-- title: WRF-Python Gallery
-  url: https://wrf-python.readthedocs.io/en/latest/plot.html
-  description: |
-    Examples of how wrf-python can be used to make plots with matplotlib (with basemap and cartopy) and PyNGL. None of these examples make use of xarray’s builtin plotting functions, since additional work is most likely needed to extend xarray in order to work correctly.
-  authors:
-  - affiliation: NSF NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail:
-  tags:
-    packages:
-    - wrf-python
-    formats:
-    - gallery
-
-- title: Xarray
-  url: http://xarray.pydata.org/
-  description: |
-    xarray (formerly xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun!
-
-    Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures.
-
-    Xarray is inspired by and borrows heavily from pandas, the popular data analysis package focused on labelled tabular data. It is particularly tailored to working with netCDF files, which were the source of xarray’s data model, and integrates tightly with dask for parallel computing.
-  authors:
-  - name: Xarray Developers
-  thumbnail: /_static/thumbnails/xarray.png
-  tags:
-    packages:
-    - xarray
-    formats:
-    - documentation
-
-- title: Xarray Tutorial
-  url: https://tutorial.xarray.dev/intro.html
-  description: |
-    A collection of tutorials provided by the Xarray developers.
-  authors:
-  - name: Xarray Developers
-  thumbnail: /_static/thumbnails/xarray.png
-  tags:
-    packages:
-    - xarray
-    - dask
-    formats:
-    - tutorial
-
-- title: Python Programming for Earth Science Students
-  description: Python Programming for Earth Science Students
-  url:
-    https://nbviewer.jupyter.org/github/ltauxe/Python-for-Earth-Science-Students/tree/master/
-  thumbnail: ''
-  authors:
-  - name: Lisa Tauxe
-    affiliation: Scripps Institution of Oceanography
-    affiliation_url: https://scripps.ucsd.edu/
-    email: ltauxe@ucsd.edu
-  - name: Hanna Asefaw
-    affiliation: ''
-    affiliation_url: ''
-    email: hasefaw@ucsd.edu
-  - name: Brendan Cych
-    affiliation: ''
-    affiliation_url: ''
-    email: bcych@ucsd.edu
-  tags:
-    formats:
-    - tutorial
-    packages:
-    - pure python
-    - pandas
-    - scipy
-    - numpy
-    - matplotlib
-
-- title: Pangeo Gallery
-  description: A gallery of different Pangeo use cases
-  url: http://gallery.pangeo.io
-  thumbnail:
-    https://github.com/pangeo-data/pangeo/raw/master/docs/_static/pangeo_simple_logo.png
-  authors:
-  - name: Pangeo Community
-    affiliation: Pangeo
-    affiliation_url: http://pangeo.io/
-    email: ''
-  tags:
-    packages:
-    - jupyter
-    - xarray
-    - dask
-    - matplotlib
-    - intake
-    - xgcm
-    - holoviews
-    - pandas
-    - numpy
-    formats:
-    - gallery
-    - tutorial
-    domains:
-    - glaciology
-    - remote sensing
-    - physical oceanography
-    - hydrology
-    affiliation:
-    - pangeo
-
-- title: Python for Atmosphere and Ocean Science
-  description: Lesson materials for a one-day workshop on using Python in the atmosphere
-    and ocean sciences. Useful for any geoscientist working with raster (a.k.a. “gridded”)
-    data, the lessons cover packages/tools including conda, xarray, dask and netCDF,
-    as well as best practices including functions, command line programs, defensive
-    programming, provenance tracking and version control via git/GitHub.
-  url: https://carpentrieslab.github.io/python-aos-lesson/
-  thumbnail: /_static/thumbnails/DC_logo_vision.png
-  authors:
-  - name: ''
-    affiliation: Data Carpentry
-    affiliation_url: https://datacarpentry.org/
-    email: ''
-  - name: ''
-    affiliation: ''
-    affiliation_url: ''
-    email: ''
-  tags:
-    packages:
-    - xarray
-    - dask
-    - cartopy
-    - numpy
-    - matplotlib
-    formats:
-    - course
-    domains:
-    - atmospheric science
-    - climate science
-
-- title: Python for Geosciences
-  description: 'This is a short overview of how Python is used in science and particularly
-    in geosciences targeting people who already know programming (e.g. Matlab). '
-  url: https://github.com/koldunovn/python_for_geosciences
-  thumbnail: ''
-  authors:
-  - name: Nikolay Koldunov
-    affiliation: 'Alfred Wegener Institute for Polar and Marine Research '
-    affiliation_url: https://www.awi.de/en/
-    email: koldunovn@gmail.com
-  tags:
-    packages:
-    - matplotlib
-    - scipy
-    - pandas
-    - xarray
-    - cartopy
-    formats:
-    - course
-    - tutorial
-    - video
-    domains:
-    - atmospheric science
-    - climate science
-    - physical oceanography
-    - data science
-
-- title: Environmental Data Science Book
-  description: A living, open and community-driven resource to showcase and support
-    computational notebooks for collaborative, reproducible and transparent Environmental
-    Science
-  url: https://github.com/alan-turing-institute/environmental-ds-book
-  thumbnail:
-    https://raw.githubusercontent.com/alan-turing-institute/environmental-ds-book/master/book/figures/logo/logo.png
-  authors:
-  - name: EDS book community
-    affiliation: Environmental Data Science Book
-    affiliation_url: https://github.com/alan-turing-institute/environmental-ds-book#contributors
-    email: environmental.ds.book@gmail.com
-  tags:
-    packages:
-    - pangeo
-    - pooch
-    - intake
-    - pystac
-    - pandas
-    - geopandas
-    - xarray
-    - dask
-    - matplotlib
-    - holoviews
-    - cartopy
-    formats:
-    - book
-    - gallery
-    domains:
-    - environmental science
-    - climate science
-    - ecology
-    - hydrology
-    - physical geography
-    - remote sensing
-    - data science
-    affiliation:
-    - The Alan Turing Institute
-
-- title: Your First Python Tutorial - Reading in a .txt File
-  url: https://youtu.be/Jog7ybd6amw
-  description: |
-    Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers setting up a work environment and opening a .txt file. The content to follow along with this video is hosted on the <A href="https://ncar.github.io/python-tutorial/tutorials/yourfirst.html">Xdev Python Tutorial website</A>.
-  authors:
-  - name: Project Pythia
-  - name: Julia Kent
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-txtfile.jpeg
-  tags:
-    packages:
-    - pure python
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Your First Python Tutorial - Creating a Data Dictionary
-  url: https://youtu.be/5z6-t62x7Xs
-  description: |
-    Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers creating a data dictionary. The content to follow along with this video is hosted on the <A href="https://ncar.github.io/python-tutorial/tutorials/yourfirst.html#creating-a-data-dictionary">Xdev Python Tutorial website</A>.
-  authors:
-  - name: Project Pythia
-  - name: Julia Kent
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-datadict.jpeg
-  tags:
-    packages:
-    - pure python
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Your First Python Tutorial - Writing Functions
-  url: https://youtu.be/BerEf_3CsL8
-  description: |
-    Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to write and call functions in Python. The content to follow along with this video is hosted on the <A href ="https://ncar.github.io/python-tutorial/tutorials/yourfirst.html#writing-functions">Xdev Python Tutorial website</A>.
-  authors:
-  - name: Project Pythia
-  - name: Julia Kent
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-writingfx.jpeg
-  tags:
-    packages:
-    - pure python
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Your First Python Tutorial - Creating Your Own Package
-  url: https://youtu.be/6lbbTwGFcTc
-  description: |
-    Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to create and call modules and packages. The content to follow along with this video is hosted on the <A href="https://ncar.github.io/python-tutorial/tutorials/yourfirst.html#first-python-package">Xdev Python Tutorial website</A>.
-  authors:
-  - name: Project Pythia
-  - name: Julia Kent
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-firstpackage.jpeg
-  tags:
-    packages:
-    - pure python
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Your First Python Tutorial - Using a Built-In Package and Publishing Your
-    Package
-  url: https://youtu.be/44QUMCh2ZHU
-  description: |
-    Recording from the Python Tutorial Seminar Series designed to teach you Python, not package specific syntax. This lessons covers how to use your first external buil-in package, `math`, and how to publish your package. The content to follow along with this video is hosted on the <A href="https://ncar.github.io/python-tutorial/tutorials/yourfirst.html#using-a-built-in-package">Xdev Python Tutorial website</A>.
-  authors:
-  - name: Project Pythia
-  - name: Julia Kent
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-builtinpackage.jpeg
-  tags:
-    packages:
-    - pure python
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Jupyter Notebooks
-  url: https://youtu.be/xSzXvwzFsDU
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing JupyterLab and Jupyter Notebooks.
-  authors:
-  - name: Project Pythia
-  - name: Kevin Paul
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-jupyter.jpeg
-  tags:
-    packages:
-    - jupyter
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Numpy
-  url: https://youtu.be/kstc-6uz7AQ
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `numpy`. The content to follow along with this video is hosted on this <A href="https://colab.research.google.com/drive/1zcjaGXofLzUXkQzJKnANE9Z3yFUt0q7E?">Numpy Google Collab</A>.
-  authors:
-  - name: Project Pythia
-  - name: A Kootz
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-numpy.jpeg
-  tags:
-    packages:
-    - numpy
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Matplotlib
-  url: https://youtu.be/EiPRIdHQEmE
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `matplotlib`. The content to follow along with this video is hosted on this <A href="https://github.com/anissa111/matplotlib-tutorial">Matplotlib Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Anissa Zacharias
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-matplotlib.jpeg
-  tags:
-    packages:
-    - matplotlib
-    formats:
-    - video
-    - tutorial
-    domains:
-    - data visualization
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Object Oriented Programming
-  url: https://youtu.be/GEFnL8C62u8
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing Object Oriented Programming. The content to follow along with this video is hosted in this <A href="https://github.com/pilotchute/oop_hrrr_tutorial">Object Oriented Programming Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: A Kootz
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-oop.jpeg
-  tags:
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Cartopy
-  url: https://youtu.be/ivmd3RluMiw
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `cartopy`. The content to follow along with this video is hosted in this <A href="https://github.com/michaelavs/cartopy_tutorial">Cartopy Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Michaela Sizemore
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-cartopy.jpeg
-  tags:
-    packages:
-    - matplotlib
-    - cartopy
-    formats:
-    - video
-    - tutorial
-    domains:
-    - data visualization
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Git and GitHub
-  url: https://youtu.be/fYkPn0Nttlg
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the tools Git and GitHub. The content to follow along with this tutorial is hosted in this <A href="https://github.com/NCAR/git-github-demo">Git and GitHub Demo GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Kevin Paul
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-git.png
-  tags:
-    packages:
-    - git
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Pandas
-  url: https://youtu.be/BsV3ek7qsiM
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `pandas`. The content to follow along with this video is hosted in this <A href="https://github.com/mgrover1/ncar_pandas_tutorial">Pandas Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Max Grover
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  - name: Drew Camron
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-pandas.jpeg
-  tags:
-    packages:
-    - pandas
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Xarray Part 1
-  url: https://youtu.be/Ss4ryKukhi4
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Anderson Banihirwe
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-xarray1.jpeg
-  tags:
-    packages:
-    - xarray
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Xarray Part 2
-  url: https://youtu.be/2H_4drBwORY
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `xarray`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Anderson Banihirwe
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-xarray2.jpeg
-  tags:
-    packages:
-    - xarray
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Dask Part 1
-  url: https://youtu.be/wn-QM6QUB_U
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the first lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Anderson Banihirwe
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-dask1.jpeg
-  tags:
-    packages:
-    - dask
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Dask Part 2
-  url: https://youtu.be/yn4_-1pHC5k
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing the Python Package `dask`. This is the second lesson of a two part series. The content to follow along with this video is hosted in this <A href="https://github.com/andersy005/xarray-tutorial">Xarray Tutorial GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Anderson Banihirwe
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-dask2.jpeg
-  tags:
-    packages:
-    - dask
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - Plotting with GeoCAT
-  url: https://youtu.be/It231le1fAU
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing advanced plotting techniques and highlighting tools developed by GeoCAT. The content to follow along with this video is hosted in this <A href="https://github.com/anissa111/plotting-with-geocat-tutorial">Plotting with GeoCat GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: Anissa Zacharias
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-geocatplot.jpeg
-  tags:
-    packages:
-    - geocat-viz
-    formats:
-    - video
-    - tutorial
-    domains:
-    - data visualization
-    affiliation:
-    - pythia
-    - xdev
-
-- title: Python Tutorial Seminar Series - GeoCAT-Comp
-  url: https://www.youtube.com/watch?v=uiWDQKI8YTQ&t=6s
-  description: |
-    Recording from the Python Tutorial Seminar Series introducing `geocat-comp`. The content to follow along with this video is hosted in this <A href="https://github.com/pilotchute/geocat_comp_tutorial">GeoCat-Comp GitHub Repository</A>.
-  authors:
-  - name: Project Pythia
-  - name: A Kootz
-    affiliation: NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/ptss-geocatcomp.jpeg
-  tags:
-    packages:
-    - geocat-comp
-    formats:
-    - video
-    - tutorial
-    affiliation:
-    - pythia
-    - xdev
-
-- title: The Pythia Foundations Book
-  url: https://foundations.projectpythia.org/landing-page.html
-  description: |
-    Brought to you by Project Pythia, this growing collection covers the foundational skills everyone needs to get started with scientific computing in the open-source Python ecosystem.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-
-- title: Pythia Foundations - Getting started with Python
-  url: https://foundations.projectpythia.org/foundations/getting-started-python.html
-  description: |
-    This chapter of the Pythia Foundations book covers Python spin-up for new users. Here you will look at your first Python code and learn to run/install Python on various platforms.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - pure python
-
-- title: Pythia Foundations - Getting started with Jupyter
-  url: https://foundations.projectpythia.org/foundations/getting-started-jupyter.html
-  description: |
-    This chapter of the Pythia Foundations book covers Python spin-up using Jupyter. Here you will learn about the JupyterLab interface and markdown formatting.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - jupyter
-
-- title: Pythia Foundations - Getting started with GitHub
-  url: https://foundations.projectpythia.org/foundations/getting-started-github.html
-  description: |
-    This chapter of the Pythia Foundations book covers GitHub: what it is, basic version control, and how to open a pull request.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - git
-
-- title: Pythia Foundations - Numpy
-  url: https://foundations.projectpythia.org/core/numpy.html
-  description: |
-    This chapter of the Pythia Foundations book covers the Python package NumPy: NumPy basics, intermediate NumPy, and NumPy broadcasting.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - numpy
-
-- title: Pythia Foundations - Matplotlib
-  url: https://foundations.projectpythia.org/core/matplotlib.html
-  description: |
-    This chapter of the Pythia Foundations book covers basics of the Python package Matplotlib.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - matplotlib
-    domains:
-    - data visualization
-
-- title: Pythia Foundations - Cartopy
-  url: https://foundations.projectpythia.org/core/cartopy.html
-  description: |
-    This chapter of the Pythia Foundations book introduces the Python package Cartopy, a package designed for geospatial data processing and used for its ability to produce maps.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - cartopy
-    domains:
-    - data visualization
-
-- title: Pythia Foundations - Datetime
-  url: https://foundations.projectpythia.org/core/datetime.html
-  description: |
-    This section of the Pythia Foundations book contains tutorials on dealing with times and calendars in scientific Python, beginning with use of the datetime standard library.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - datetime
-
-- title: Pythia Foundations - Pandas
-  url: https://foundations.projectpythia.org/core/pandas.html
-  description: |
-    This section of the Pythia Foundations book covers Pandas, a very powerful library for working with tabular data (i.e. anything you might put in a spreadsheet – a common data type in the geosciences).
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - pandas
-
-- title: Pythia Foundations - Data Formats
-  url: https://foundations.projectpythia.org/core/pandas.html
-  description: |
-    This section of the Pythia Foundations book covers how to interact in Python with data file formats in widespread use in the geosciences, such as NetCDF.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    domains:
-    - data formats
-    packages:
-    - netCDF4
-
-- title: Pythia Foundations - Xarray
-  url: https://foundations.projectpythia.org/core/xarray.html
-  description: |
-    This section of the Pythia Foundations book contains tutorials on using Xarray. Xarray is used widely in the geosciences and beyond for analysis of gridded N-dimensional datasets.
-  authors:
-  - name: Project Pythia
-    email: projectpythia@ucar.edu
-    url: https://projectpythia.org/
-  thumbnail: /_static/thumbnails/ProjectPythia_Blue.png
-  tags:
-    formats:
-    - book
-    affiliation:
-    - pythia
-    packages:
-    - xarray
-
-- title: Climatematch Academy
-  url: https://academy.climatematch.io/about
-  description: |
-    Climatematch Academy (CMA) is a wide-reaching, inclusive and approachable program aimed to introduce computational methods for climate science. CMA strives to create a globally diverse climate sciences community, trained on cutting edge techniques to access and analyze open-source modeled and observational climate data.
-  authors:
-  - name: Climatematch Team
-    url: https://academy.climatematch.io/about/team
-  thumbnail: /_static/thumbnails/climatematch.png
-  tags:
-    formats:
-    - course
-    domains:
-    - climate science
-    affiliation:
-    - neuromatch
-    - pythia
-
-- title: Plotting Earth Science Data
-  url: https://ploting-earth-science-data.web.app/
-  description: |
-    A guide to analyze and plot Earth Science data for Scientist of all programming skill levels, using L-1 data product from CYGNSS mission as an example.
-  authors:
-  - name: Michael Nguyen
-  tags:
-    packages:
-    - cartopy
-    - xarray
-    - numpy
-    - matplotlib
-    - netCDF4
-    domains:
-    - data visualization
-    - remote sensing
-
-- title: 'Herbie: Retrieve NWP Model Data'
-  url: https://herbie.readthedocs.io/
-  description: |
-    Herbie is a python package that downloads recent and archived numerical weather prediction (NWP) model output from different cloud archive sources. Its most popular capability is to download HRRR model data. NWP data in the GRIB2 format can be read with xarray+cfgrib.
-  authors:
-  - name: Brian Blaylock
-  tags:
-    packages:
-    - xarray
-    - cfgrib
-  formats:
-  - documentation
-  - tutorial
-  domains:
-  - atmospheric science
-  - numerical weather prediction
-
-- title: The Earth Science Box Modelling Toolkit
-  url: https://github.com/uliw/esbmtk
-  description: |
-    ESBMTK is a python library that aims to simplify typical box modeling projects in the Earth-Sciences.
-    It uses a declarative approach to describe models, and abstracts typical modeling tasks like gas-exchange and carbonate dissolution through python classes. See the
-    manual at https://esbmtk.readthedocs.io/en/latest for installation instructions usage, and example code.
-  thumbnail: https://raw.githubusercontent.com/uliw/esbmtk/staging/mpc.png
-  authors:
-  - name: Ulrich G Wortmann
-    affiliation: Dept. of Earth Sciences, University of Toronto
-    affiliation_url: https://www.es.utoronto.ca/
-    email: uli.wortmann@utoronto.ca
-  tags:
-    packages:
-    - esbmtk
-    - matplotlib
-    - numpy
-    - pandas
-    formats:
-    - code
-    domains:
-    - Earth System Science
-    - Chemical Oceanography
-
-- title: The PO.DAAC Cookbook
-  url: https://podaac.github.io/tutorials/
-  description: |
-    A place to find NASA ocean, climate, and surface water data recipes and tutorials for the Physical Oceanography Distributed Active Archive Center (PO.DAAC) datasets, tools & services!
-  thumbnail: https://raw.githubusercontent.com/podaac/tutorials/master/images/podaac_cookbook_thumbnail.png
-  authors:
-  - name: PO.DAAC Team
-    affiliation: Jet Propulsion Laboratory, California Institute of Technology
-    affiliation_url: https://www.jpl.nasa.gov/
-  tags:
-    packages:
-    - earthaccess
-    - xarray
-    formats:
-    - book
-    - tutorial
-    domains:
-    - Remote sensing
-    - Oceanography
-    - Hydrology
-    affiliation:
-    - Physical Oceanography Distributed Active Archive Center (PO.DAAC)
-    - Jet Propulsion Laboratory
-    - California Institute of Technology
-
-- title: UXarray
-  url: https://uxarray.readthedocs.io/
-  description: Xarray extension for unstructured climate and global weather data
-  thumbnail: https://raw.githubusercontent.com/UXARRAY/uxarray/921dd8f42f661692f0cec170ee5c7dbedb294237/docs/_static/images/logos/uxarray_logo_v_dark.svg
-  authors:
-  - name: The UXarray Developers
-    affiliation: NSF NCAR & Department of Energy
-  tags:
-    packages:
-      - xarray
-      - dask
-      - numba
-      - numpy
-      - holoviews
-      - matplotlib
-    formats:
-      - documentation
-      - tutorial
-    domains:
-      - Unstructured Grids
-      - Data Analysis
-      - Data Visualization
-      - Atmospheric Science
-      - Climate Science
-    affiliation:
-      - Pangeo
-      - Raijin
-      - SEATS
-
-- title: GeoCAT Applications
-  url: https://ncar.github.io/geocat-applications/
-  description: |
-    GeoCAT Applications is a community resource managed by the GeoCAT team. Inspired by the NCL Applications page, this is designed to be a quick reference demonstrating capabilities within the Scientific Python Ecosystem that may be relevant to your geoscience workflows.
-  authors:
-  - name: GeoCAT Team
-    url: https://geocat.ucar.edu/
-    affiliation: NSF NCAR
-    affiliation_url: https://ncar.ucar.edu/
-  thumbnail: /_static/thumbnails/geocat.png
-  tags:
-    formats:
-    - documentation
diff --git a/pyproject.toml b/pyproject.toml
deleted file mode 100644
index 99227ca84..000000000
--- a/pyproject.toml
+++ /dev/null
@@ -1,15 +0,0 @@
-[tool.black]
-line-length = 120
-target-version = ['py38']
-skip-string-normalization = true
-
-[tool.nbqa.config]
-isort = "setup.cfg"
-black = "pyproject.toml"
-
-[tool.nbqa.mutate]
-black = 1
-pyupgrade = 1
-
-[tool.nbqa.addopts]
-pyupgrade = ["--py36-plus"]
diff --git a/requirements.txt b/requirements.txt
index 98823decc..3a941270a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,5 @@
-google-analytics-data 
-cartopy 
+google-analytics-data
+cartopy
 matplotlib
 jupyter-server
 ipykernel
diff --git a/setup.cfg b/setup.cfg
index 870b89f26..a0e8cb2d2 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -7,7 +7,7 @@ select = B,C,E,F,W,T4,B9
 
 [isort]
 known_first_party=
-known_third_party=frontmatter,gallery_generator,markdown_it,pydantic,truncatehtml,yaml
+known_third_party=
 multi_line_output=3
 include_trailing_comma=True
 force_grid_wrap=0