'ACSets (Attributed C-Sets): Algebraic databases as in-memory data structures.
Scanned 9/2/2026
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---
name: acsets
description: 'ACSets (Attributed C-Sets): Algebraic databases as in-memory data structures.
Category-theoretic formalism for relational databases generalizing graphs and data
frames.'
---
# SKILL: ACSets Relational Thinking
**Version**: 2.0.0
**Trit**: 0 (ERGODIC)
**Domain**: database, category-theory, rewriting
**Source**: Topos Institute RelationalThinking Course + AlgebraicJulia
---
## Overview
ACSets (Attributed C-Sets) are **functors X: C → Set** where C is a small category (schema). This skill integrates:
1. **RelationalThinking Course** - Topos Institute's pedagogical approach
2. **DPO Rewriting** - Double Pushout graph transformation
3. **Self-Play Loop** - Query → Execute → Evaluate → Refine
4. **GF(3) Conservation** - Triadic skill composition
---
## Core Concept: C-Set as Functor
```
Schema (Category C) Instance (Functor X: C → Set)
┌─────────────────┐ ┌─────────────────────────────┐
│ E ──src──→ V │ X │ X(E) = {e1, e2, e3} │
│ ←──tgt── │ ───→ │ X(V) = {v1, v2} │
└─────────────────┘ │ X(src): e1↦v1, e2↦v1, e3↦v2│
│ X(tgt): e1↦v2, e2↦v2, e3↦v1│
└─────────────────────────────┘
```
---
## Schema Definition
### Basic Graph Schema
```julia
using Catlab.CategoricalAlgebra
@present SchGraph(FreeSchema) begin
V::Ob # Vertices (object)
E::Ob # Edges (object)
src::Hom(E, V) # Source morphism
tgt::Hom(E, V) # Target morphism
end
@acset_type Graph(SchGraph, index=[:src, :tgt])
```
### Entity-Subtype Hierarchy (from RelationalThinking Ch8)
```julia
@present SchKitchen(FreeSchema) begin
Entity::Ob
Food::Ob
food_in_on::Hom(Food, Entity)
food_is_entity::Hom(Food, Entity)
Kitchenware::Ob
ware_in_on::Hom(Kitchenware, Entity)
ware_is_entity::Hom(Kitchenware, Entity)
BreadLoaf::Ob
bread_loaf_is_food::Hom(BreadLoaf, Food)
Knife::Ob
knife_is_ware::Hom(Knife, Kitchenware)
end
@acset_type Kitchen(SchKitchen)
```
---
## DPO Rewriting (Double Pushout)
### The Pattern: L ← K → R
```
L ←──l── K ──r──→ R
│ │ │
match│ │ │
↓ ↓ ↓
G ←───── D ──────→ H
pushout pushout
complement
```
- **L** = Find (what to match)
- **K** = Keep (overlap preserved)
- **R** = Replace (new structure)
- **G** = Host graph
- **H** = Result graph
### Rule Definition
```julia
using AlgebraicRewriting
# Slice bread rule: adds BreadSlice when knife + loaf present
slice_bread = @migration(SchKitchen, begin
L => @join begin
loaf::BreadLoaf
knife::Knife
end
R => @join begin
loaf::BreadLoaf
slice::BreadSlice
food_in_on(bread_slice_is_food(slice)) == food_in_on(bread_loaf_is_food(loaf))
knife::Knife
end
K => @join begin
loaf::BreadLoaf
knife::Knife
end
end)
rule = make_rule(slice_bread, yKitchen)
```
### Apply Rewrite
```julia
matches = get_matches(rule, state)
new_state = rewrite_match(rule, matches[1])
```
---
## Self-Play Loop
The ACSet self-refinement monad:
```
Query₀ → Execute → Evaluate → Mine Patterns → Refine → Query₁ → ...
```
### Implementation
```julia
struct SelfRefinementLoop
schema::Presentation
state::ACSet
patterns::Vector{Pattern}
generation::Int
end
function step!(loop::SelfRefinementLoop, rule::Rule)
# Find matches
matches = get_matches(rule, loop.state)
# Evaluate each match
evaluations = [evaluate_match(m, loop.patterns) for m in matches]
# Mine new patterns from successful evaluations
new_patterns = mine_patterns(evaluations)
append!(loop.patterns, new_patterns)
# Apply best match
best = argmax(e -> e.score, evaluations)
loop.state = rewrite_match(rule, matches[best.index])
loop.generation += 1
loop
end
```
### Convergence Criterion
```julia
function converged(loop::SelfRefinementLoop; threshold=0.95)
recent = loop.patterns[end-10:end]
stability = std([p.score for p in recent])
stability < (1 - threshold)
end
```
---
## GF(3) Integration
### Trit Assignment
```julia
function acset_to_trits(g::Graph, seed::UInt64)
rng = SplitMix64(seed)
trits = Int[]
for e in parts(g, :E)
h = next_u64!(rng)
hue = (h >> 16 & 0xffff) / 65535.0 * 360
trit = hue < 60 || hue >= 300 ? 1 :
hue < 180 ? 0 : -1
push!(trits, trit)
end
trits
end
# Conservation check
gf3_conserved(trits) = sum(trits) % 3 == 0
```
### Synergistic Triads Containing ACSets
```
clj-kondo-3color (-1) ⊗ acsets (0) ⊗ rama-gay-clojure (+1) = 0 ✓
three-match (-1) ⊗ acsets (0) ⊗ gay-mcp (+1) = 0 ✓
slime-lisp (-1) ⊗ acsets (0) ⊗ cider-clojure (+1) = 0 ✓
hatchery-papers (-1) ⊗ acsets (0) ⊗ frontend-design (+1) = 0 ✓
```
---
## Orthogonal Bundles
ACSets participates in the **STRUCTURAL** bundle:
| Direction | Skills | Behavior |
|-----------|--------|----------|
| STRUCTURAL | clj-kondo(-1) ⊗ acsets(0) ⊗ rama-gay(+1) | Schema validation → transport → generation |
| TEMPORAL | three-match(-1) ⊗ unworld(0) ⊗ gay-mcp(+1) | Reduction → derivation → coloring |
| STRATEGIC | proofgeneral(-1) ⊗ glass-bead(0) ⊗ rubato(+1) | Verification → hopping → composition |
---
## Visual Conventions (from RelationalThinking)
| Concept | Visual |
|---------|--------|
| Schema object | Gray circle |
| Schema morphism | Colored arrow (cyan=src, blue=tgt) |
| Instance element | Filled shape |
| Morphism mapping | Slot/containment |
| Pushout | Merged regions with distinct colors |
| DPO rule | Thought bubble (L,K,R) |
---
## Commands
```bash
# Schema operations
just acset-schema FILE # Display schema diagram
just acset-instance FILE # Display instance elements
just acset-morphism F G # Show homomorphism F → G
# DPO rewriting
just acset-rule RULE STATE # Apply rewrite rule
just acset-matches RULE STATE # Find all matches
just acset-chain RULES STATE # Chain multiple rewrites
# Self-play
just acset-selfplay SCHEMA # Run self-refinement loop
just acset-patterns STATE # Mine patterns from state
just acset-converge SCHEMA # Run until convergence
# GF(3) operations
just acset-trits STATE SEED # Color state with seed
just acset-gf3 STATE # Check GF(3) conservation
just acset-triads # Show synergistic triads
```
---
## References
### Topos Institute
- [RelationalThinking Book](https://toposinstitute.github.io/RelationalThinking-Book/)
- [RelationalThinking Code](https://github.com/ToposInstitute/RelationalThinking-code)
### AlgebraicJulia
- [Catlab.jl](https://github.com/AlgebraicJulia/Catlab.jl)
- [ACSets.jl](https://github.com/AlgebraicJulia/ACSets.jl)
- [AlgebraicRewriting.jl](https://github.com/AlgebraicJulia/AlgebraicRewriting.jl)
### Papers
- Patterson et al. "Categorical data structures for technical computing" (Compositionality 2022)
- Aguinaldo et al. "Categorical Representation Language for Knowledge-Based Planning" (AAAI 2023)
---
## Related Skills
- `rama-gay-clojure` (+1) - Scalable backends with color tracing
- `clj-kondo-3color` (-1) - Schema validation/linting
- `glass-bead-game` (0) - World hopping across schemas
- `unworld` (0) - Derivational chains for state evolution
- `discohy-streams` (0) - DisCoPy categorical color streams
---
**Skill Name**: acsets-relational-thinking
**Type**: Category-Theoretic Database / DPO Rewriting
**Trit**: 0 (ERGODIC)
**GF(3)**: Conserved via triadic composition
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