Δ(19 vs 18) Scenario (feed)

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• Turbulence

GitHub Profiles

Here we can start by taking five (5) repositories to be assigned as the home base and four (4) zones. Let's discuss how to arrange them.

User Profile

The following sample information is exposed to Jekyll templates in the site.github namespace:

{% for item in site.github %}
  * {{ item | jsonify }}: {{ site.github[item] | jsonify }}
{% endfor %}

Jekyll supports loading data from YAML, JSON, CSV, and TSV files located in the _data directory. Note that CSV and TSV files must contain a header row.

{
    "versions": {
        "jekyll": <version>,
        "kramdown": <version>,
        "liquid": <version>,
        "maruku": <version>,
        "rdiscount": <version>,
        "redcarpet": <version>,
        "RedCloth": <version>,
        "jemoji": <version>,
        "jekyll-mentions": <version>,
        "jekyll-redirect-from": <version>,
        "jekyll-sitemap": <version>,
        "github-pages": <version>,
        "ruby": <version>"
    },
    "hostname": "github.com",
    "pages_hostname": "github.io",
    "api_url": "https://api.github.com",
    "help_url": "https://help.github.com",
    "environment": "dotcom",
    "pages_env": "dotcom",
    "public_repositories": [ Repository Objects ],
    "organization_members": [ User Objects ],
    "build_revision": "cbd866ebf142088896cbe71422b949de7f864bce",
    "project_title": "metadata-example",
    "project_tagline": "A GitHub Pages site to showcase repository metadata",
    "owner_name": "github",
    "owner_url": "https://github.com/github",
    "owner_gravatar_url": "https://github.com/github.png",
    "repository_url": "https://github.com/github/metadata-example",
    "repository_nwo": "github/metadata-example",
    "repository_name": "metadata-example",
    "zip_url": "https://github.com/github/metadata-example/zipball/gh-pages",
    "tar_url": "https://github.com/github/metadata-example/tarball/gh-pages",
    "clone_url": "https://github.com/github/metadata-example.git",
    "releases_url": "https://github.com/github/metadata-example/releases",
    "issues_url": "https://github.com/github/metadata-example/issues",
    "wiki_url": "https://github.com/github/metadata-example/wiki",
    "language": null,
    "is_user_page": false,
    "is_project_page": true,
    "show_downloads": true,
    "url": "http://username.github.io/metadata-example", // (or the CNAME)
    "baseurl": "/metadata-example",
    "contributors": [ User Objects ],
    "releases": [ Release Objects ],
    "latest_release": [ Release Object ],
    "private": false,
    "archived": false,
    "disabled": false,
    "license": {
      "key": "mit",
      "name": "MIT License",
      "spdx_id": "MIT",
      "url": "https://api.github.com/licenses/mit"
    },
    "source": {
      "branch": "gh-pages",
      "path": "/"
    }
}

The _data folder is where you can store additional data for Jekyll to use when generating your site and they will be accessible via site.data.

Organization Profile

We are going to correlate the user profiles with the organizations. Therefore we will need to add additional data. For adding new entry we can use jq.

$ echo '[ "data1" ]' | jq '. + [ "data2" ]'
[
  "data1",
  "data2"
]

$ echo '{"key1": "value1"}' | jq '. + {"key2": "value2"}'
{
  "key1": "value1",
  "key2": "value2"
}

$ echo '[ {"key1": "value1"} ]' | jq '. + [{"key2": "value2"}]'
[
  {
    "key1": "value1"
  },
  {
    "key2": "value2"
  }
]

All of the repositories are arranged by hexagonal forms of modulo 6. So each of them will consist of one (1) sub root frame, one (1) sub home page and four (4) sub zones.

gh api -H "${HEADER}" /user/orgs  --jq '.[].login' | sort -uf | yq eval -P | sed "s/ /, /g" > /tmp/user_orgs
IFS=', '; array=($(cat /tmp/user_orgs))

echo "[" > _data/orgs.json
for ((i=0; i < ${#array[@]}; i++)); do
  
  gh api -H "${HEADER}" /orgs/${array[$i]} >> _data/orgs.json
  IFS=', '; p1=($(pinned_repos.rb ${array[$i]} member | yq eval -P | sed "s/ /, /g"))      
  IFS=', '; p2=($(pinned_repos.rb ${array[$i]} public | yq eval -P | sed "s/ /, /g"))      
      
  gh api -H "${HEADER}" /orgs/${array[$i]} | jq '. +
    {"key1": ["'${p1[0]}'","'${p1[1]}'","'${p1[2]}'","'${p1[3]}'","'${p1[4]}'","'${p1[5]}'"]} +       
    {"key2": ["'${p2[0]}'","'${p2[1]}'","'${p2[2]}'","'${p2[3]}'","'${p2[4]}'","'${p2[5]}'"]}' >> /tmp/orgs.json

  if [[ "$i" -lt "${#array[@]}-1" ]]; then echo "," >> _data/orgs.json; fi
done
echo "]" >> _data/orgs.json

By each of organizations we can create a profile inside a .github repository. We also use this repository to propagate the root function so it stands as Root Profiles

Root Profiles

By executing the shell code above then using Jekyll/liquid we can tabulate repositories based on the two (2) user profiles and eleven (11) organizations.

{% for item in site.data.orgs %}
  1. {{ item.name | jsonify }}
     - {{ item.key1 | jsonify }}
     - {{ item.key2 | jsonify }}
{% endfor %}

Below is the result of the code above for the eleven (11) organizations. Combining with their root profiles and two (2) user repositories then the total will be 168.

7 + (11 x 1) + 7 + (11 x 13) = 24 x 7 = 168

1. "Scenarios"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["Schema","Artifacts","Assets","depot_tools","distribution","sitemap"]
2. "Feeding"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["docs","screen","builder","genius","rapidjson","Ventoy"]
3. "Entrypoint"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["JSONFeed","SEOstats","OpenSEO","falcon","NPPGit","webpack"]
4. "Mapping"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["steps","jquery.soap","bash","json-html","store","gtm"]
5. "Keyring"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["ga-beacon","flakes","jsonix","lanyon","progit-book","wiki"]
6. "Enneagram"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["core","bulbea","pedia","poole","cards","bootstrap"]
7. "Twisting"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["Cloud-Site-API","Google-Ads-API","Toko-Chetabahana","KeepFit","World","Tutorial-Buka-Toko"]
8. "Recycling"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["NeuralTeams","collab","container-push","includeHTML","now","wheel"]
9. "Exchange"
   • ["maps","feed","lexer","parser","syntax","grammar"]
   • ["screen","buffer-ruby","github-graphql-action","scrapy","wpt","system"]
10. "Runners"
    • ["maps","feed","lexer","parser","syntax","grammar"]
    • ["classifier","domJSON","openoffice","landing-page-theme","asciidoc","recommendations-ai"]
11. "Manifest"
    • ["maps","feed","lexer","parser","syntax","grammar"]
    • ["storj","monsterpost","veles","spectral","finraos","dstroot"]

These 11 set of organizations will be organized per the scheme below. We are going to compile the result which shall confirm to 1000 nodes.

This tabulation is confined within a 24-cell hexagon which is formed when integers are sequentially added to a field of tessellating equilateral triangles.

5 + 2 x 5 x 168 = 5 + 1680 = 1685 = 5 x 337 root functions

By the Structure of MEC30, each repositories brings their own wiki of 37 files which are organized by a set of seven (7) gists. So by the 11 organizations there will be a total set of 11 x 7 = 77 objects which are organized by the rest of 18 - 7 = 11 gists.

The configuration between these wikis and gists would bring the nodes of the objects in to clustering between prime pair 11 and 13 which will need the implementation of the complex numbers. Such detail will be discussed on the following topics.

Thus the arrangement of all repositories will be the key point to enable us to explore the prime hexagon quickly and discover patterns that can be further analyzed