{"version":3,"sources":["../../src/table-kind.ts","../../src/table-kind-mapping.json"],"sourcesContent":["// src/table-kind.ts — A TABLE IS A KIND (KINDS-GLUE wave 3 §1–2).\n//\n// `table:` names \"a record of that Table\". It is never a registry row: its schema is\n// derived, when asked for, from the Table's live Fields as the store's door\n// `custom.table_kind_facts` (N1) answers them — `TableKindFacts` is that door's JSON verbatim.\n//\n// ONE MAPPING, THREE OUTPUTS, TWO LANGUAGES. `table-kind-mapping.json` beside this file is the\n// one data file (aidream copies it verbatim into matrx-graph). From it:\n// - stored — the JSON Schema a value is validated against (mirrors custom.validate_values and\n// custom._undeclared_key_guard: closed only on a `fields` Table, platform keys allowed;\n// uses the door's column_source / platform_keys / per-Field field_kind when present,\n// else derives them);\n// - authored — a plain object every provider binds (no allOf / if / patternProperties);\n// - render — the content-ir KindSchema the web draws with, never stricter than the store.\n// Each is Fields-only here (`tableJsonSchema`, `tableRenderSchema`); the control keys are wave 2's\n// one function (`withControlKeys` / `withControlKeyFields` in @ai-matrx/content-ir), applied by\n// the caller. The Python twin is `matrx_graph.table_kinds`; both write byte-identical JSON for\n// the golden fixture (guard 3 (a), `__tests__/table-kind-round-trip.test.ts`).\n\nimport { isLowercaseUuidShape } from \"@ai-matrx/kit/uuid\";\nimport MAPPING from \"./table-kind-mapping.json\";\n\nexport const TABLE_KIND_PREFIX = \"table:\";\nconst KIND_KEY = \"__kind\";\n\ntype Json = Record;\n\n/** `custom.table_kind_facts(p_table_id)` verbatim (N1). */\nexport interface TableKindFacts {\n organization_id: string;\n table_id: string;\n name: string | null;\n title_field: string | null;\n agent_writable: boolean;\n purpose: string | null;\n version: number | null;\n type_field: string | null;\n stamp: string | null;\n /** Every live Field document (typed ones included), plus `id` and `version`, in `sort` order. */\n fields: Array>;\n /** `{: [{key, label, id, retired, position}]}`, retired included, live first. */\n choices: Record>;\n /** `custom.table_column_source` (`fields` / `free_form` / `code`) once the door carries it; absent, the mapping's default. */\n column_source?: string | null;\n /** `custom.record_platform_keys()` once the door carries it; absent, the mapping's keys. */\n platform_keys?: string[] | null;\n}\n\n/** The content-ir `KindSchema` shape, structurally (this package does not depend on content-ir). */\nexport interface TableRenderSchema {\n kind: string;\n fields: Record>;\n}\n\nexport type TableSchemaMode = \"stored\" | \"authored\";\n\ntype KindSpec = {\n shape: \"string\" | \"number\" | \"boolean\" | \"datetime\" | \"choice\" | \"relation\" | \"entity_reference\" | \"address\" | \"computed\";\n value?: Json;\n authored?: boolean;\n unit?: boolean;\n hint?: string;\n rating?: boolean;\n};\n\ntype Mapping = {\n kernels: { file: string; person: string };\n system_kinds: string[];\n by_behaviour: Record;\n choice_enum_limit: number;\n rating_max: number;\n address_parts: string[];\n address_part_max: number;\n column_source_default: string;\n platform_keys: Record;\n stored_patterns: { record_id: string; datetime: string };\n kinds: Record;\n render: Record;\n};\n\nconst M = MAPPING as unknown as Mapping;\n\n/** The one mapping (records' own file; the Python copy is generated from it). */\nexport function tableKindMapping(): Readonly {\n return M;\n}\n\nexport function isTableKind(slug: unknown): slug is `table:${string}` {\n return typeof slug === \"string\" && slug.startsWith(TABLE_KIND_PREFIX) && isLowercaseUuidShape(slug.slice(TABLE_KIND_PREFIX.length));\n}\n\nexport function tableKindSlug(tableId: string): `table:${string}` {\n const slug = `${TABLE_KIND_PREFIX}${String(tableId).trim().toLowerCase()}`;\n if (!isTableKind(slug)) throw new Error(`${JSON.stringify(tableId)} is not a table id`);\n return slug;\n}\n\nexport function tableIdOf(slug: string): string {\n if (!isTableKind(slug)) throw new Error(`${JSON.stringify(slug)} is not a table kind`);\n return slug.slice(TABLE_KIND_PREFIX.length);\n}\n\n// ── field kinds ─────────────────────────────────────────────────────────────────────────\n\nfunction clone(value: T): T {\n return JSON.parse(JSON.stringify(value)) as T;\n}\n\nfunction truthy(value: unknown): boolean {\n return value === true || value === \"true\";\n}\n\nfunction configOf(d: Json): Json {\n const cfg = d.config;\n return cfg && typeof cfg === \"object\" && !Array.isArray(cfg) ? (cfg as Json) : {};\n}\n\n/** Twin of `custom.parity_type` — the first answer wins. */\nfunction parityType(d: Json): string | null {\n const t = d.type;\n const fmt = d.format;\n const cfg = configOf(d);\n if (t === \"boolean\") return \"checkbox\";\n if (t === \"list\") return truthy(d.multi) ? \"multi_select\" : \"select\";\n if (t === \"relation\" && d.relation_target === M.kernels.file) return \"attachment\";\n if (t === \"relation\" && d.relation_target === M.kernels.person) return \"member\";\n if (t === \"formula\" && \"pick\" in cfg) return \"lookup\";\n if (t === \"formula\" && \"agg\" in cfg) return \"rollup\";\n if (t === \"formula\" && \"expr\" in cfg) return \"formula\";\n if (t === \"text\" && (fmt === \"url\" || fmt === \"email\" || fmt === \"phone\")) return fmt;\n if (t === \"range\" && fmt === \"percent\") return \"percent\";\n if (t === \"range\" && d.unit && fmt === \"currency\") return \"currency\";\n if (t === \"range\" && (cfg.kind === \"date\" || cfg.kind === \"datetime\")) return \"datetime\";\n return null;\n}\n\n/** Twin of `custom.field_kind_of`: the field kind a stored Field document declares. */\nexport function fieldKindOf(d: Record): string | null {\n const t = d.type;\n const fmt = d.format;\n const cfg = configOf(d);\n if (t === \"range\" && (fmt === \"rating\" || fmt === \"duration\")) return fmt;\n if (t === \"text\" && (fmt === \"address\" || fmt === \"barcode\" || fmt === \"rich_text\" || fmt === \"signature\")) return fmt;\n if (t === \"list\" && fmt === \"status\") return \"status\";\n if (t === \"formula\" && fmt === \"count\" && cfg.agg === \"count\") return \"count\";\n if (t === \"formula\" && typeof cfg.system === \"string\" && M.system_kinds.includes(cfg.system)) return cfg.system;\n if (t === \"relation\" && Array.isArray(cfg.allowed_types)) return \"entity_reference\";\n const parity = parityType(d);\n if (parity !== null) return parity;\n if (t === \"text\") return fmt === \"long\" || truthy(cfg.multiline) ? \"long_text\" : \"text\";\n if (t === \"range\") return \"number\";\n if (t === \"relation\") return \"relation\";\n return null;\n}\n\n/**\n * The store's own `field_kind` when the facts carry it (`custom.field_kind_of` per Field, asked\n * of the door); otherwise this twin's derivation of the same answer.\n */\nfunction fieldKind(d: Json): string | null {\n if (\"field_kind\" in d) return typeof d.field_kind === \"string\" ? d.field_kind : null;\n return fieldKindOf(d);\n}\n\nfunction kindSpec(d: Json): KindSpec {\n const kind = fieldKind(d) ?? M.by_behaviour[String(d.type)] ?? \"formula\";\n return M.kinds[kind] ?? M.kinds.formula!;\n}\n\n// ── per Field ───────────────────────────────────────────────────────────────────────────\n\nfunction unconditionalRules(d: Json): Json[] {\n const rules = Array.isArray(d.rules) ? (d.rules as unknown[]) : [];\n return rules.filter(\n (r): r is Json =>\n !!r &&\n typeof r === \"object\" &&\n !Array.isArray(r) &&\n !(Array.isArray((r as Json).applies_to_types) && ((r as Json).applies_to_types as unknown[]).length > 0) &&\n !(typeof (r as Json).applies_to_types === \"string\" && (r as Json).applies_to_types !== \"\"),\n );\n}\n\n/** A rule's number, as Python's twin writes it (6.0 is 6). */\nfunction numberOf(value: unknown): number | null {\n if (typeof value === \"boolean\") return null;\n if (typeof value === \"number\" && Number.isFinite(value)) return value;\n if (typeof value === \"string\" && /^-?[0-9]+(\\.[0-9]+)?$/.test(value)) return Number(value);\n return null;\n}\n\nfunction choiceTokens(facts: TableKindFacts, key: string): string[] {\n const tokens: string[] = [];\n for (const choice of facts.choices?.[key] ?? []) {\n for (const token of [choice.key, choice.label, choice.id]) {\n if (typeof token === \"string\" && token && !tokens.includes(token)) tokens.push(token);\n }\n }\n return tokens;\n}\n\nfunction liveChoiceKeys(facts: TableKindFacts, key: string): string[] {\n const keys: string[] = [];\n for (const choice of facts.choices?.[key] ?? []) {\n const k = choice.key;\n if (!choice.retired && typeof k === \"string\" && k && !keys.includes(k)) keys.push(k);\n }\n return keys;\n}\n\nfunction item(facts: TableKindFacts, d: Json, mode: TableSchemaMode): Json {\n const spec = kindSpec(d);\n const shape = spec.shape;\n const cfg = configOf(d);\n const key = String(d.key);\n if (shape === \"string\" || shape === \"number\" || shape === \"boolean\") {\n const out = clone(spec.value ?? {});\n for (const rule of unconditionalRules(d)) {\n const kind = rule.kind;\n const value = numberOf(rule.value);\n if (shape === \"number\" && kind === \"min\" && value !== null) out.minimum = value;\n else if (shape === \"number\" && kind === \"max\" && value !== null) out.maximum = value;\n else if (shape === \"string\" && kind === \"length\" && value !== null) out.maxLength = Math.trunc(value);\n }\n if (spec.rating && !(\"maximum\" in out)) out.maximum = M.rating_max;\n if (spec.unit && d.unit && mode === \"stored\") out[\"x-matrx-unit\"] = d.unit;\n return out;\n }\n if (shape === \"datetime\") {\n // The store casts a string to timestamptz; the pattern refuses what no cast can read.\n if (mode === \"stored\") return { type: [\"number\", \"string\"], pattern: M.stored_patterns.datetime };\n return { type: \"string\", format: cfg.kind === \"date\" ? \"date\" : \"date-time\" };\n }\n if (shape === \"choice\") {\n if (truthy(cfg.allow_other)) return { type: \"string\" };\n if (mode === \"stored\") return { type: \"string\", enum: choiceTokens(facts, key) };\n const live = liveChoiceKeys(facts, key);\n if (live.length === 0 || live.length > M.choice_enum_limit) return { type: \"string\" };\n return { type: \"string\", enum: live };\n }\n if (shape === \"relation\") {\n // custom.validate_values refuses a value that is not an id by this very regex.\n if (mode === \"stored\") return { type: \"string\", format: \"uuid\", pattern: M.stored_patterns.record_id };\n return { type: \"string\", format: \"uuid\" };\n }\n if (shape === \"entity_reference\") {\n const allowed = (Array.isArray(cfg.allowed_types) ? (cfg.allowed_types as unknown[]) : []).filter(\n (t): t is string => typeof t === \"string\",\n );\n const id: Json = { type: \"string\", format: \"uuid\" };\n if (mode === \"stored\") id.pattern = M.stored_patterns.record_id;\n const out: Json = {\n type: \"object\",\n properties: { token: { type: \"string\", enum: allowed }, id },\n required: [\"token\", \"id\"],\n };\n if (mode === \"authored\") out.additionalProperties = false;\n return out;\n }\n if (shape === \"address\") {\n const part: Json =\n mode === \"authored\"\n ? { type: \"string\", maxLength: M.address_part_max }\n : { type: [\"string\", \"null\"], maxLength: M.address_part_max };\n const out: Json = {\n type: \"object\",\n properties: Object.fromEntries(M.address_parts.map((p) => [p, { ...part }])),\n additionalProperties: false,\n };\n if (mode === \"stored\") out.minProperties = 1;\n return out;\n }\n return { readOnly: true };\n}\n\nfunction isTyped(d: Json): boolean {\n return Array.isArray(d.applies_to_types) && (d.applies_to_types as unknown[]).length > 0;\n}\n\nfunction storedValue(facts: TableKindFacts, d: Json): Json {\n const shape = kindSpec(d).shape;\n if (shape === \"computed\") return { readOnly: true };\n const one = item(facts, d, \"stored\");\n const required = truthy(d.required) && !isTyped(d);\n let value: Json;\n if (shape === \"relation\" || shape === \"entity_reference\") {\n const many: Json = { type: \"array\", items: one };\n const ceiling = numberOf(d.relation_max);\n if (ceiling !== null) many.maxItems = Math.trunc(ceiling);\n if (required) many.minItems = 1;\n value = { anyOf: [one, many] };\n } else if (truthy(d.multi)) {\n value = { type: \"array\", items: one };\n if (required) value.minItems = 1;\n } else {\n value = one;\n }\n return required ? value : { anyOf: [value, { type: \"null\" }] };\n}\n\nfunction authoredValue(facts: TableKindFacts, d: Json, typeLabels: string[]): Json {\n const spec = kindSpec(d);\n const shape = spec.shape;\n const one = item(facts, d, \"authored\");\n let value: Json;\n if (shape === \"relation\" || shape === \"entity_reference\") {\n value = { type: \"array\", items: one };\n const ceiling = numberOf(d.relation_max);\n if (ceiling !== null) value.maxItems = Math.trunc(ceiling);\n } else if (truthy(d.multi)) {\n value = { type: \"array\", items: one };\n } else {\n value = one;\n }\n const extras: string[] = [];\n if (spec.unit && d.unit) extras.push(`Amount in ${String(d.unit)}.`);\n if (spec.hint) extras.push(spec.hint);\n if (typeLabels.length > 0) extras.push(`Only for ${typeLabels.join(\", \")} records.`);\n const label = String(d.label || d.key);\n value.description = extras.length > 0 ? `${label}. ${extras.join(\" \")}` : label;\n return value;\n}\n\nfunction isAuthored(d: Json): boolean {\n const spec = kindSpec(d);\n return spec.shape !== \"computed\" && spec.authored !== false;\n}\n\nfunction typeChoice(facts: TableKindFacts, word: string) {\n for (const choice of facts.choices?.[facts.type_field ?? \"\"] ?? []) {\n if (word === choice.key || word === choice.label || word === choice.id) return choice;\n }\n return null;\n}\n\nfunction typeSynonyms(facts: TableKindFacts, word: string): [string, string[]] {\n const choice = typeChoice(facts, word);\n if (!choice) return [word, [word]];\n const out: string[] = [];\n for (const token of [choice.key, choice.label, choice.id]) {\n if (typeof token === \"string\" && token && !out.includes(token)) out.push(token);\n }\n return [String(choice.key || word), out];\n}\n\nfunction typeLabels(facts: TableKindFacts, d: Json): string[] {\n const labels: string[] = [];\n for (const word of (d.applies_to_types as unknown[]) ?? []) {\n const choice = typeChoice(facts, String(word));\n const label = choice ? String(choice.label || choice.key) : String(word);\n if (!labels.includes(label)) labels.push(label);\n }\n return labels;\n}\n\nfunction liveFields(facts: TableKindFacts): Json[] {\n return (facts.fields ?? []).filter((d): d is Json => !!d && typeof d === \"object\" && !!(d as Json).key);\n}\n\n// ── whole schemas ───────────────────────────────────────────────────────────────────────\n\n/** The Fields-only JSON Schema of a record of this Table (no control keys). */\nexport function tableJsonSchema(facts: TableKindFacts, mode: TableSchemaMode): Json {\n const slug = tableKindSlug(String(facts.table_id));\n const fields = liveFields(facts);\n const properties: Json = { [KIND_KEY]: { const: slug } };\n const required: string[] = [KIND_KEY];\n\n if (mode === \"stored\") {\n const branches = new Map();\n for (const d of fields) {\n const key = String(d.key);\n properties[key] = storedValue(facts, d);\n const computed = kindSpec(d).shape === \"computed\";\n if (!truthy(d.required) || computed) continue;\n if (!isTyped(d)) {\n required.push(key);\n continue;\n }\n if (!facts.type_field) continue;\n for (const word of d.applies_to_types as unknown[]) {\n const [typeKey, synonyms] = typeSynonyms(facts, String(word));\n let branch = branches.get(typeKey);\n if (!branch) {\n branch = {\n if: { properties: { [facts.type_field]: { enum: synonyms } }, required: [facts.type_field] },\n then: { required: [], properties: {} },\n };\n branches.set(typeKey, branch);\n }\n if (!branch.then.required.includes(key)) {\n branch.then.required.push(key);\n branch.then.properties[key] = { not: { type: \"null\" } };\n }\n }\n }\n const platformKeys = Array.isArray(facts.platform_keys) ? facts.platform_keys : Object.keys(M.platform_keys);\n for (const name of platformKeys) {\n // A key the platform writes into every record (custom.record_platform_keys()); a Field of\n // the same name is the column and keeps its own shape.\n if (typeof name === \"string\" && !(name in properties)) properties[name] = clone(M.platform_keys[name] ?? {});\n }\n const schema: Json = {\n type: \"object\",\n properties,\n patternProperties: { \"^_\": {} },\n required,\n };\n // custom._undeclared_key_guard judges only a `fields` Table: a free_form (document) or code\n // Table keeps any key, so its schema stays open (custom.table_column_source).\n if ((facts.column_source || M.column_source_default) === \"fields\") schema.additionalProperties = false;\n if (branches.size > 0) schema.allOf = [...branches.values()];\n return schema;\n }\n\n for (const d of fields) {\n if (!isAuthored(d)) continue;\n const key = String(d.key);\n const typed = isTyped(d);\n properties[key] = authoredValue(facts, d, typed ? typeLabels(facts, d) : []);\n if (truthy(d.required) && !typed) required.push(key);\n }\n return { type: \"object\", properties, required, additionalProperties: false };\n}\n\n/**\n * The Fields-only content-ir `KindSchema` the web draws a record of this Table with: every Field\n * nullable and optional, choices open to every word the store accepts (keys, labels, ids,\n * retired included). Wrap it with `withControlKeyFields` from @ai-matrx/content-ir — table kinds\n * never pass through `kindSchemaFromJsonSchema`.\n */\nexport function tableRenderSchema(facts: TableKindFacts): TableRenderSchema {\n const slug = tableKindSlug(String(facts.table_id));\n const out: Record> = {};\n for (const d of liveFields(facts)) {\n const key = String(d.key);\n const shape = kindSpec(d).shape;\n const multi = truthy(d.multi);\n let field: Json;\n if (shape === \"choice\") {\n field = { type: multi ? \"string[]\" : \"enum\", values: choiceTokens(facts, key) };\n if (truthy(configOf(d).allow_other)) field.open = true;\n } else {\n field = clone(M.render[shape]![multi ? \"many\" : \"one\"]);\n }\n field.nullable = true;\n out[key] = field;\n }\n return { kind: slug, fields: out };\n}\n","{\n \"about\": \"THE ONE MAPPING from a store Field to a kind's three schemas (KINDS-GLUE wave 3 §2). Hand-written here; aidream copies it verbatim to packages/matrx-graph/matrx_graph/table_kind_mapping.json (scripts/generate_table_kind_mapping.py --check). Both languages derive from this file only: @ai-matrx/records src/table-kind.ts and matrx_graph.table_kinds. Keys of `kinds` are the store's field kinds (custom.field_kinds() plus the formula `system` kinds custom.field_kind_of answers). Stored mode only: `column_source_default` is custom.table_column_source's answer when the facts carry none (silence means the doctrine: Field rows are the columns); `platform_keys` mirrors custom.record_platform_keys() with each key's shape (parent_id: custom.containment_parent's uuid cast; icon: the record's own @ai-matrx/icons name, a string or null); `stored_patterns` mirror custom.validate_values' relation id regex and, for dates, refuse a string the timestamptz cast can never read (no digits, not a special word) while never refusing one it can.\",\n \"version\": 2,\n \"kernels\": {\n \"file\": \"11111111-0000-4000-8000-000000000006\",\n \"person\": \"11111111-0000-4000-8000-000000000005\"\n },\n \"system_kinds\": [\"created_by\", \"modified_by\", \"autonumber\", \"created_time\", \"modified_time\"],\n \"by_behaviour\": {\n \"text\": \"text\",\n \"range\": \"number\",\n \"list\": \"select\",\n \"relation\": \"relation\",\n \"boolean\": \"checkbox\",\n \"formula\": \"formula\"\n },\n \"choice_enum_limit\": 100,\n \"rating_max\": 5,\n \"address_parts\": [\"street\", \"city\", \"region\", \"postal_code\", \"country\"],\n \"address_part_max\": 200,\n \"column_source_default\": \"fields\",\n \"platform_keys\": {\n \"parent_id\": { \"type\": [\"string\", \"null\"], \"pattern\": \"^(?:\\\\{[0-9a-fA-F]{4}(?:-?[0-9a-fA-F]{4}){7}\\\\}|[0-9a-fA-F]{4}(?:-?[0-9a-fA-F]{4}){7})$\" },\n \"icon\": { \"type\": [\"string\", \"null\"] }\n },\n \"stored_patterns\": {\n \"record_id\": \"^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}$\",\n \"datetime\": \"[0-9][^0-9]+[0-9]|[0-9]{5}|^\\\\s*(?:[Nn][Oo][Ww]|[Tt][Oo][Dd][Aa][Yy]|[Tt][Oo][Mm][Oo][Rr][Rr][Oo][Ww]|[Yy][Ee][Ss][Tt][Ee][Rr][Dd][Aa][Yy]|[Ee][Pp][Oo][Cc][Hh])(?![A-Za-z])\"\n },\n \"kinds\": {\n \"text\": { \"shape\": \"string\", \"value\": { \"type\": \"string\" } },\n \"long_text\": { \"shape\": \"string\", \"value\": { \"type\": \"string\" } },\n \"email\": { \"shape\": \"string\", \"value\": { \"type\": \"string\", \"format\": \"email\" } },\n \"phone\": { \"shape\": \"string\", \"value\": { \"type\": \"string\" } },\n \"url\": { \"shape\": \"string\", \"value\": { \"type\": \"string\" } },\n \"barcode\": { \"shape\": \"string\", \"value\": { \"type\": \"string\", \"maxLength\": 256 } },\n \"rich_text\": { \"shape\": \"string\", \"value\": { \"type\": \"string\" }, \"hint\": \"Markdown, no HTML.\" },\n \"signature\": { \"shape\": \"string\", \"value\": { \"type\": \"string\", \"readOnly\": true }, \"authored\": false },\n \"number\": { \"shape\": \"number\", \"value\": { \"type\": \"number\" } },\n \"currency\": { \"shape\": \"number\", \"value\": { \"type\": \"number\" }, \"unit\": true },\n \"percent\": { \"shape\": \"number\", \"value\": { \"type\": \"number\" }, \"hint\": \"A whole percent: 6 means 6%.\" },\n \"rating\": { \"shape\": \"number\", \"value\": { \"type\": \"integer\", \"minimum\": 0 }, \"rating\": true },\n \"duration\": { \"shape\": \"number\", \"value\": { \"type\": \"number\", \"minimum\": 0 }, \"hint\": \"A length of time in seconds.\" },\n \"datetime\": { \"shape\": \"datetime\" },\n \"checkbox\": { \"shape\": \"boolean\", \"value\": { \"type\": \"boolean\" } },\n \"select\": { \"shape\": \"choice\" },\n \"multi_select\": { \"shape\": \"choice\" },\n \"status\": { \"shape\": \"choice\" },\n \"relation\": { \"shape\": \"relation\" },\n \"member\": { \"shape\": \"relation\" },\n \"attachment\": { \"shape\": \"relation\", \"authored\": false },\n \"entity_reference\": { \"shape\": \"entity_reference\" },\n \"address\": { \"shape\": \"address\" },\n \"formula\": { \"shape\": \"computed\" },\n \"lookup\": { \"shape\": \"computed\" },\n \"rollup\": { \"shape\": \"computed\" },\n \"count\": { \"shape\": \"computed\" },\n \"created_by\": { \"shape\": \"computed\" },\n \"modified_by\": { \"shape\": \"computed\" },\n \"autonumber\": { \"shape\": \"computed\" },\n \"created_time\": { \"shape\": \"computed\" },\n \"modified_time\": { \"shape\": \"computed\" }\n },\n \"render\": {\n \"string\": { \"one\": { \"type\": \"string\" }, \"many\": { \"type\": \"string[]\" } },\n \"number\": { \"one\": { \"type\": \"number\" }, \"many\": { \"type\": \"number[]\" } },\n \"boolean\": { \"one\": { \"type\": \"boolean\" }, \"many\": { \"type\": \"boolean[]\" } },\n \"datetime\": { \"one\": { \"type\": \"union\", \"scalars\": [\"string\", \"number\"] }, \"many\": { \"type\": \"json\" } },\n \"relation\": { \"one\": { \"type\": \"json\" }, \"many\": { \"type\": \"json\" } },\n \"entity_reference\": { \"one\": { \"type\": \"json\" }, \"many\": { \"type\": \"json\" } },\n \"address\": { \"one\": { \"type\": \"json\" }, \"many\": { \"type\": \"json\" } },\n \"computed\": { \"one\": { \"type\": \"json\" }, \"many\": { \"type\": \"json\" } }\n 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