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Browser History ACSet
Basado en la clasificación ocupacional SOC
Query and explore the 2600: The Hacker Quarterly magazine archive (1984-present) via DuckDB. Provides structured access to 168+ issues covering hacker culture, security, privacy, telephony, and digital rights without loading full content into context.
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Attributed C-Sets as algebraic databases. Category-theoretic data structures generalizing graphs and dataframes with Gay.jl color integration.
ACSets (Attributed C-Sets): Algebraic databases with Specter-style bidirectional
Bridge active inference theory with robot control using K-Scale's JAX/MuJoCo stack. Use when connecting predictive coding to locomotion policies, mapping KL divergence minimization to RL training, applying mean field approximation to robotics state estimation, or implementing sim2real as inference about future observations.
Implement affective valence as directional derivative of interoceptive energy landscapes for AI alignment. Use when building alignment-aware RL agents, validating GF(3) conservation in reward signals, training Langevin-based policies, or analyzing fold-change detection signals in POMDP environments.
| name | browser-history-acset |
| description | Browser History ACSet |
| version | 1.0.0 |
Trit: 0 (ERGODIC - information coordination)
Foundation: PyACSet ↔ ACSets.jl path equivalence verified
Unified categorical structure for browser history across:
Uses GF(3) trit classification for browsing behavior analysis.
┌─────────────────────────────────────────────────────────────┐
│ BrowserHistoryACSet Schema │
├─────────────────────────────────────────────────────────────┤
│ Objects: Browser, URL, Visit, Domain, SearchQuery │
│ │
│ Morphisms: │
│ browser_of: URL → Browser │
│ domain_of: URL → Domain │
│ url_of: Visit → URL │
│ from_visit: Visit → Visit (reflexive, navigation chain) │
│ │
│ Attributes: │
│ browser_name: Browser → String │
│ url_text: URL → String │
│ visit_time: Visit → Int │
│ domain_name: Domain → String │
│ trit: Domain → Int (-1, 0, +1) │
└─────────────────────────────────────────────────────────────┘
Verified cross-language compatibility between Python and Julia:
| Operation | Python (PyACSet) | Julia (ACSets.jl) | Match |
|---|---|---|---|
| nparts(A) | 2 | 2 | ✓ |
| subpart(1, :f) | 1 | 1 | ✓ |
| incident(1, :f) | [1] | [1] | ✓ |
| path 1→f→g | 1 | 1 | ✓ |
# Python (PyACSet)
url = acset.subpart(visit_id, "url_of")
domain = acset.path(visit_id, "url_of", "domain_of")
referrers = acset.incident(url_id, "url_of")
# Julia (ACSets.jl)
url = subpart(acs, visit_id, :url_of)
domain = subpart(acs, subpart(acs, visit_id, :url_of), :domain_of)
referrers = incident(acs, url_id, :url_of)
| Trit | Category | Examples | Behavior |
|---|---|---|---|
| +1 | PLUS (Creation) | github.com, ampcode.com, arxiv.org | Building, learning |
| 0 | ERGODIC (Info) | google.com, youtube.com, x.com | Coordination, info |
| -1 | MINUS (Consumption) | amazon.com, netflix.com, reddit.com | Consuming, extracting |
╔═══════════════════════════════════════════════════════════════╗
║ Browser History ACSet ║
╠═══════════════════════════════════════════════════════════════╣
║ Browser : 3 parts ║
║ URL : 4529 parts ║
║ Visit : 8569 parts ║
║ Domain : 511 parts ║
║ SearchQuery : 36 parts ║
║ Download : 41 parts ║
╠═══════════════════════════════════════════════════════════════╣
║ GF(3) Sum : 13 ║
╚═══════════════════════════════════════════════════════════════╝
Top Domains:
[+] github.com : 1066 visits (creation)
[○] mermaid.live : 655 visits (coordination)
[+] ampcode.com : 453 visits (creation)
[+] elevenlabs.io : 268 visits (creation)
[+] huggingface.co : 188 visits (creation)
# Extract browser history as ACSet
python3 browser_history_acset.py
# Run path equivalence tests
python3 path_equivalence_test.py
# Julia verification
julia path_equivalence_test.jl
# Select all visits to github.com
github_visits = (
SELECT(ALL("Visit"))
>> FILTER(lambda v: acset.path(v, "url_of", "domain_of")
and acset.subpart(acset.path(v, "url_of", "domain_of"), "domain_name") == "github.com")
)
# Transform: add trit to all URLs in domain
TRANSFORM(
SELECT(ALL("URL")) >> FILTER(lambda u: acset.subpart(u, "domain_of") == d1),
lambda u: acset.set_subpart(u, "trit", 1)
)
browser-history-acset (0) ⊗ olmoearth-mlx (+1) ⊗ tenderloin (-1) = 0 ✓
py-acset (0) ⊗ ACSets.jl (+1) ⊗ DuckDB (-1) = 0 ✓
coequalizers (0) - Path equivalence via coequalizer quotientsacsets (0) - ACSet foundationstemporal-coalgebra (-1) - Time-based path analysisThis skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
general: 734 citations in bib.duckdbThis skill connects to Software Design for Flexibility (Hanson & Sussman, 2021):
Concepts: autonomous agent, game, synthesis
browser-history-acset (○) + SDF.Ch10 (+) + [balancer] (−) = 0
Skill Trit: 0 (ERGODIC - coordination)
Adventure games synthesize techniques. This skill integrates multiple patterns.
This skill maps to Cat# = Comod(P) as a bicomodule in the equipment structure:
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
The skill participates in triads satisfying:
(-1) + (0) + (+1) ≡ 0 (mod 3)
This ensures compositional coherence in the Cat# equipment structure.