K Fragments
The article discusses the author's experience of reviewing and digitizing their work notebooks, which contain around 900 handwritten pages. It highlights various programming fragments that solve problems or illustrate idioms, primarily in the K programming language. The author notes the similarities in solutions among different programmers and provides examples of specific functions and their applications.
- ▪The author digitized approximately 900 handwritten pages from their work notebooks.
- ▪The article features various K programming fragments that solve interesting problems.
- ▪Examples include functions for Pascal's Triangle, matrix determinants, and merging dictionaries.
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Record
| Original publisher | Beyondloom |
| Canonical URL | https://beyondloom.com/blog/fragments.html |
| Publication time | Sun, 24 May 2026 10:02:24 +0000 |
| Retrieval time | 2026-05-24T10:07:32.096Z |
| Last seen | 2026-05-24T10:07:32.096Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
K Fragments I recently reviewed and digitized my work notebooks from the last four years- about 900 handwritten pages. In the process, I collected a number of short K fragments which solve interesting problems or illustrate idioms. Most of these I personally “discovered”, but in some cases I later found find prior art elsewhere on the internet. This provides a nice illustration of how crystalline K programs can be: presented with the same problem, two programmers are surprisingly likely to arrive at character-for-character identical solutions. Since these were mostly composed at work, many are k3-based. I have annotated which fragments work in several dialects. Accumulator Generator (oK only) In oK, dyadic .
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Beyondloom.
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