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Keeps the pace gentle by\n// running only ONE batch per schedule tick, then stopping.\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nasync function main() {\n // Re-verify nothing; just confirm whether work remains.\n const rows = await sqlite.execute(\"SELECT queried_name FROM verify_results\");\n console.log(`verify_results rows so far: ${rows.rows.length}`);\n}\n\nexport default async function () {\n await main();\n}\n","createdAt",["D",1788537980682],"branchVersion","branchId","780a019f-b3f0-478c-8bec-f5e9ea5e4951","id","cfe62995-5847-4c90-b90d-483a41dc5933","longlist",["D",1788530401973],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","","imageUrl","93474b45-6cda-4b01-9c86-872d85871021","pinnedFileId","ec528ff0-a868-11f1-a682-1607ee4eb77e","pinPreview","pinMigrated","screenshotVersion","likeCount",0,"orgId","01a010ad-0285-700c-b1e3-70dfce8e2fe2","tursoName","cfe6299558474c90b90d483a41dc5933","tursoHostname","cfe6299558474c90b90d483a41dc5933-val-town.aws-us-east-2.turso.io","tursoMeasuredAt",["D",1789488693443],"pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_104":103,"_110":58},"org",{"_104":103,"_105":58,"_106":58,"_19":60,"_107":108,"_109":32},"branch",{"_13":93,"_38":94,"_48":47,"_95":49,"_96":-5,"_97":-5,"_98":-5,"_99":-5,"_100":-5,"_101":50,"_102":103},"isOwned",41,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","rarefrog5","handle","displayName","avatar","tier","pro","canRestrictVals","profileImageUrl","branchName","adoptOrgId",{"_48":49,"_38":50,"_43":192,"_52":-5,"_53":32,"_54":55,"_56":55,"_57":58,"_59":-5,"_19":60,"_61":62,"_63":30,"_64":-5,"_65":-5,"_66":67,"_68":69,"_70":71,"_72":73,"_74":193,"_76":-5,"_77":78,"_79":78,"_80":81,"_82":81,"_83":81,"_84":78,"_85":78,"_86":194,"_88":195,"_90":196,"_92":32},"tree",[175,176,177,178],"files",[175,176,177,178],"counts",{"_165":67,"_166":162,"_167":67,"_168":169,"_170":171},"contents",[132,133,134,135],"upstreamProject","upstreamBranch","emptyEnvVars","flags",[],"hasHttpFiles","grants","orgs","customDomains",{},{"_48":157,"_38":158,"_36":159,"_137":-5,"_46":47,"_45":160,"_138":32,"_43":161,"_13":162,"_39":154,"_41":163,"_29":32,"_140":-5,"_33":164},{"_48":149,"_38":150,"_36":151,"_137":-5,"_46":47,"_45":152,"_138":30,"_43":153,"_13":67,"_39":154,"_41":155,"_29":32,"_140":-5,"_33":156},{"_48":142,"_38":143,"_36":62,"_137":-5,"_46":47,"_45":144,"_138":32,"_43":145,"_13":146,"_39":40,"_41":147,"_29":32,"_140":-5,"_33":148},{"_48":136,"_38":34,"_36":37,"_137":-5,"_46":47,"_45":14,"_138":32,"_43":139,"_13":67,"_39":40,"_41":42,"_29":32,"_140":-5,"_33":141},"4f254375-a08c-47fe-b9ad-29154eb05d4d","parentId","latest",["D",1788537980682],"label",[34],"500ccb94-56da-4247-aa5d-be7786d5afd8","main.ts",18,["D",1788537778768],12,"// ============================================================================\n// FORWARD FREQUENCY — PODCAST VERIFICATION SCRIPT (resumable, for Val Town)\n// ----------------------------------------------------------------------------\n// Checks a list of podcast NAMES (stored in this val's blob storage as\n// names_1, via the ingest.ts web page) against the REAL Apple catalog, and\n// keeps only real shows. Runs NOTHING to the \"fake\" bucket without a second,\n// more thorough lookup — because Apple's top-N fuzzy search misses real shows.\n//\n// Each result is one of four statuses:\n// verified -> confidently matched a real Apple show (kept)\n// uncertain -> a plausible near-match existed but wasn't an exact title;\n// kept for HUMAN review so no real show is dropped\n// not_found -> searched generously, no real show found (dropped)\n// (duplicate) -> matched but already in your existing directory\n//\n// RESUMABLE: a single execution has a time limit, so each run:\n// loads names, skips ones already in the DB, verifies BATCH (~150), saves\n// each result, prints totals + how far along. Run repeatedly until ALL DONE.\n// ============================================================================\n\nimport { blob } from \"https://esm.town/v/std/blob/main.ts\";\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\n// How many names to try per run. A run must finish under the execution time\n// limit. Apple rate-limits rapidly-fired requests (we got 403s on a burst),\n// so the batch size and delay below are tuned to stay well clear of that:\n// BATCH requests, each preceded by a THROTTLE_MS delay, and genuinely short.\nconst BATCH = 50;\nconst THROTTLE_MS = 600; // real politeness delay between Apple calls\nconst COUNTRY = \"US\";\n\n// Title-similarity thresholds:\n// >= CONFIDENT : treat as a verified real match\n// >= PLAUSIBLE : a real show might exist under a slightly different title\n// -> mark \"uncertain\" (human review) instead of \"not_found\"\nconst CONFIDENT = 0.8;\n// Real shows are frequently listed under a slightly different title on Apple\n// (e.g. \"Abolition Science\" vs \"Abolition Science Radio\"), and Apple's fuzzy\n// search often surfaces them imperfectly. So anything with at least a partial\n// word overlap is flagged for human review rather than silently dropped. The\n// PLAUSIBLE bar is deliberately low so real shows aren't thrown away.\nconst PLAUSIBLE = 0.35;\n\n// ---- optional dedupe against existing shows (leave empty to skip) ----------\nconst EXISTING: { ids: number[]; names: string[] } = { ids: [], names: [] };\nconst existingIds = new Set(EXISTING.ids);\nconst existingNames = new Set(EXISTING.names);\n\n// ---- text + matching helpers ----------------------------------------------\nfunction norm(s: string): string {\n return (s || \"\").toLowerCase().replace(/[^a-z0-9]/g, \"\");\n}\nconst FILLER = new Set([\n \"podcast\", \"the\", \"show\", \"radio\", \"with\", \"a\", \"an\", \"official\", \"audio\",\n \"pod\", \"network\", \"series\", \"miniseries\", \"dispatch\", \"file\", \"inquest\",\n \"archive\", \"wire\", \"review\", \"report\", \"watch\", \"voice\", \"front\",\n \"expose\", \"today\", \"studies\", \"theory\", \"reader\", \"seminar\", \"workshop\",\n]);\nfunction core(s: string): string {\n return (s || \"\")\n .toLowerCase()\n .replace(/[^a-z0-9\\s]/g, \" \")\n .split(/\\s+/)\n .filter((w) => w && !FILLER.has(w))\n .join(\"\");\n}\nfunction tokens(s: string): string[] {\n return (s || \"\").toLowerCase().replace(/[^a-z0-9\\s]/g, \" \").split(/\\s+/)\n .filter(Boolean);\n}\n// Similarity score 0..1. Handles filler words, minor punctuation/typos.\nfunction titleSim(a: string, b: string): number {\n const na = norm(a), nb = norm(b);\n if (!na || !nb) return 0;\n if (na === nb) return 1;\n const ca = core(a), cb = core(b);\n if (ca && cb && ca === cb) return 1;\n let contain = 0;\n if (ca && cb && (ca.includes(cb) || cb.includes(ca))) {\n const ratio = Math.min(ca.length, cb.length) / Math.max(ca.length, cb.length);\n contain = ratio >= 0.7 ? 0.9 : ratio * 0.5;\n }\n const ta = new Set(tokens(a).filter((w) => !FILLER.has(w)));\n const tb = new Set(tokens(b).filter((w) => !FILLER.has(w)));\n let inter = 0;\n for (const t of ta) if (tb.has(t)) inter++;\n const union = new Set([...ta, ...tb]).size || 1;\n const jac = inter / union;\n return Math.max(contain, jac);\n}\n\n// ---- Apple search (generous: longer result list) --------------------------\nasync function itunesSearch(term: string, limit = 10): Promise {\n const url = \"https://itunes.apple.com/search?\" +\n new URLSearchParams({\n term,\n media: \"podcast\",\n entity: \"podcast\",\n limit: String(limit),\n country: COUNTRY,\n }).toString();\n try {\n const r = await fetch(url, { headers: { \"User-Agent\": \"FF-Directory-Verify/1.0\" } });\n if (!r.ok) return [];\n return (await r.json()).results || [];\n } catch (_e) {\n return [];\n }\n}\n\n// ---- classification (mirrors original directory's logic) ------------------\nconst FOCUS_KEYWORDS: [string, string[]][] = [\n [\"democracy\", [\"democracy\", \"democratic\", \"voting rights\", \"election integrity\", \"authoritarian\", \"fascism\", \"civic\", \"constitution\"]],\n [\"racial_justice\", [\"racial justice\", \"race\", \"black\", \"blm\", \"civil rights\", \"anti-racis\", \"racism\"]],\n [\"climate\", [\"climate\", \"environment\", \"warming\", \"emissions\", \"sustainab\", \"green energy\", \"fossil\"]],\n [\"environmental_justice\", [\"environmental justice\", \"pollution\", \"frontline communit\", \"toxic\"]],\n [\"labor\", [\"labor\", \"union\", \"worker\", \"strike\", \"wages\", \"gig work\", \"organizing\"]],\n [\"immigration\", [\"immigra\", \"migrant\", \"border\", \"asylum\", \"refugee\", \"ice \", \"deportation\"]],\n [\"housing\", [\"housing\", \"rent\", \"tenant\", \"eviction\", \"homeless\", \"affordable housing\"]],\n [\"reproductive\", [\"reproductive\", \"abortion\", \"roe\", \"pro-choice\", \"reproductive rights\"]],\n [\"lgbtq_rights\", [\"lgbtq\", \"queer\", \"trans \", \"transgender\", \"gay \", \"pride\", \"gender identity\"]],\n [\"disability_rights\", [\"disability\", \"disabled\", \"ableism\", \"accessib\", \"neurodiver\"]],\n [\"criminal_justice\", [\"criminal justice\", \"prison\", \"incarcerat\", \"police\", \"carceral\", \"abolition\", \"mass incarceration\"]],\n [\"health\", [\"health care\", \"healthcare\", \"public health\", \"medicaid\", \"medicare\", \"mental health\"]],\n [\"indigenous\", [\"indigenous\", \"native american\", \"tribal\", \"first nations\", \"sovereignty\"]],\n [\"socialism\", [\"socialis\", \"marxis\", \"communis\", \"anti-capitalis\", \"leftist theory\", \"class struggle\"]],\n [\"feminism\", [\"feminis\", \"women's rights\", \"gender equality\", \"patriarchy\"]],\n [\"education\", [\"education\", \"public school\", \"teacher\", \"student debt\", \"curriculum\"]],\n];\nconst FN_KEYWORDS: [string, string[]][] = [\n [\"local_journalism\", [\"local news\", \"city council\", \"statehouse\", \"municipal\", \"county\", \"regional\", \"community journalism\", \"public radio\", \"local report\"]],\n [\"electoral\", [\"election\", \"campaign\", \"candidate\", \"ballot\", \"voter\", \"primary\", \"electoral\", \"politics\", \"political analysis\", \"congress\", \"senate\"]],\n [\"democratic_institutions\", [\"democracy\", \"institution\", \"court\", \"supreme court\", \"constitution\", \"governance\", \"policy analysis\", \"rule of law\"]],\n [\"issue_advocacy\", [\"advocacy\", \"activis\", \"rights\", \"justice\", \"reform\", \"campaign for\", \"fight for\", \"movement for\"]],\n [\"community_movement\", [\"community\", \"movement\", \"grassroots\", \"organizing\", \"mutual aid\", \"solidarity\", \"collective\"]],\n];\nfunction classify(name: string, desc: string, eps: number, genres: string[]) {\n const text = (name + \" \" + desc + \" \" + (genres || []).join(\" \")).toLowerCase();\n let focus = \"\";\n for (const [f, kws] of FOCUS_KEYWORDS) {\n if (kws.some((k) => text.includes(k))) { focus = f; break; }\n }\n let fn = \"other\";\n for (const [f, kws] of FN_KEYWORDS) {\n if (kws.some((k) => text.includes(k))) { fn = f; break; }\n }\n const corePol = [\"politics\", \"election\", \"campaign\", \"congress\", \"senate\", \"policy\", \"government\", \"democrat\", \"republican\", \"left\", \"progressive\", \"conservative\"];\n const tier = corePol.some((k) => text.includes(k)) ? \"core_political\" : \"civic_adjacent\";\n const reach = eps >= 200 ? \"established\" : eps >= 50 ? \"growing\" : \"emerging\";\n const invest = reach === \"emerging\" ? \"high\" : reach === \"growing\" ? \"medium\" : \"low\";\n return { tier, fn, focus, reach, invest };\n}\nfunction toRecord(res: any) {\n const id = res.collectionId || res.trackId;\n const eps = res.trackCount || 0;\n const genres: string[] = res.genres || [];\n const name = res.collectionName || res.trackName || \"\";\n const cls = classify(name, \"\", eps, genres);\n return {\n id, name, pub: res.artistName || \"\", desc: \"\",\n tier: cls.tier, fn: cls.fn, focus: cls.focus, eps,\n yrs: 0, active: true, reach: cls.reach, invest: cls.invest,\n art: res.artworkUrl600 || res.artworkUrl100 || \"\",\n link: id ? `https://pod.link/${id}` : (res.collectionViewUrl || \"\"),\n rec: [], source: \"verified_apple\",\n feed: res.feedUrl || \"\", genres,\n score: 0,\n };\n}\n\n// ---- name loading ----------------------------------------------------------\nasync function parseNamesTxt(txt: string): Promise {\n try {\n const j = JSON.parse(txt);\n if (Array.isArray(j)) return j.map(String);\n } catch (_e) { /* not JSON */ }\n return txt.split(/\\r?\\n/).map((s) => s.trim()).filter(Boolean);\n}\nasync function loadAllNames(): Promise {\n const parts: string[] = [];\n for (let k = 1; k <= 50; k++) {\n try {\n const res = await blob.get(`names_${k}`);\n if (!res) break;\n parts.push(...(await parseNamesTxt(await res.text())));\n } catch (_e) { break; }\n }\n return parts;\n}\n\n// ---- verify ONE name, generously. Never drops on a single flaky search. ---\n// One search per name (Apple rate-limits bursts, so we keep volume down).\n// We search the filler-trimmed query (e.g. \"5-4 Podcast\" -> \"5-4\") which best\n// matches a real Apple title.\nasync function itunesSearchTrimmed(query: string): Promise {\n const trimmed = query\n .replace(/\\b(podcast|audio|pod|show|radio|series|the|network|today)\\b/ig, \"\")\n .replace(/\\s+/g, \" \").trim();\n return itunesSearch(trimmed && trimmed.length >= 2 ? trimmed : query);\n}\nasync function verifyOne(query: string) {\n const all = await itunesSearchTrimmed(query);\n\n let best: any = null, bestScore = 0;\n for (const res of all) {\n const cand = res.collectionName || res.trackName || \"\";\n const s = titleSim(query, cand);\n if (s > bestScore) { bestScore = s; best = res; }\n }\n\n if (!best) return { status: \"not_found\", record: null, score: 0 };\n\n if (bestScore >= CONFIDENT) {\n const rec = toRecord(best);\n rec.score = Math.round(bestScore * 100) / 100;\n // dedupe\n if (existingIds.has(rec.id) || existingNames.has(norm(rec.name))) {\n return { status: \"duplicate\", record: rec, score: bestScore };\n }\n return { status: \"verified\", record: rec, score: bestScore };\n }\n\n if (bestScore >= PLAUSIBLE) {\n // A real show may exist under a near-but-not-exact title. Store it as\n // \"uncertain\" WITH the best candidate, so a human can confirm. Not dropped.\n const rec = toRecord(best);\n rec.score = Math.round(bestScore * 100) / 100;\n return { status: \"uncertain\", record: rec, score: bestScore };\n }\n\n return { status: \"not_found\", record: null, score: bestScore };\n}\n\n// ---- main: one resumable run ----------------------------------------------\nexport default async function main() {\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS verify_results (\n queried_name TEXT PRIMARY KEY,\n status TEXT NOT NULL,\n record TEXT,\n score REAL\n )`);\n\n const names = await loadAllNames();\n const uniqueNames = Array.from(new Set(\n names.map((n) => (n || \"\").trim()).filter((n) => n && n.toLowerCase() !== \"podcast\"),\n ));\n\n const doneRows = await sqlite.execute(\"SELECT queried_name FROM verify_results\");\n const done = new Set(doneRows.rows.map((r) => r.queried_name as string));\n const pending = uniqueNames.filter((n) => !done.has(n));\n\n console.log(`Total unique names: ${uniqueNames.length}`);\n console.log(`Already done: ${done.size}`);\n console.log(`Pending: ${pending.length}`);\n\n if (pending.length === 0) { console.log(\"\\n=== ALL DONE ===\"); return; }\n\n const todo = pending.slice(0, BATCH);\n const counts = { verified: 0, uncertain: 0, not_found: 0, duplicate: 0 };\n\n for (let i = 0; i < todo.length; i++) {\n const query = todo[i];\n const { status, record, score } = await verifyOne(query);\n counts[status as keyof typeof counts]++;\n await sqlite.execute({\n sql: \"INSERT OR REPLACE INTO verify_results (queried_name, status, record, score) VALUES (?, ?, ?, ?)\",\n args: [query, status, record ? JSON.stringify(record) : null, score ?? null],\n });\n // Real politeness delay so Apple doesn't rate-limit us.\n await new Promise((r) => setTimeout(r, THROTTLE_MS));\n if ((i + 1) % 50 === 0) {\n console.log(`... ${i + 1}/${todo.length} this run | done overall ~${done.size + i + 1}/${uniqueNames.length}`);\n }\n }\n\n console.log(`\\nThis run checked ${todo.length} names.`);\n console.log(` verified: ${counts.verified}`);\n console.log(` uncertain: ${counts.uncertain} (near-match, review before dropping)`);\n console.log(` not_found: ${counts.not_found}`);\n console.log(` duplicate: ${counts.duplicate}`);\n console.log(`Progress: ${done.size + todo.length}/${uniqueNames.length} complete.`);\n console.log(`\\nRun this val again to do the next batch (${BATCH} more).`);\n}\n\nawait main();\n",[143],"60680860-1a8f-487e-850c-c426216c229e","ingest.ts","e041c0d2-a86d-11f1-b23f-1607ee4eb77e",8,["D",1788532529232],"http","// Ingest page for the longlist verifier.\n// Paste your whole list of podcast names here, click Save — it writes them\n// into the val's blob storage under names_1 so main.ts can read them.\nimport { blob } from \"https://esm.town/v/std/blob/main.ts\";\n\nconst PAGE = `\n\nUpload podcast names\n\n

Paste your podcast names here

One per line, or as a JSON array — either works. Then click Save names.

\n \n

\n\n`;\n\nfunction parseNames(txt: string): string[] {\n try {\n const j = JSON.parse(txt);\n if (Array.isArray(j)) return j.map((s) => String(s).trim()).filter(Boolean);\n } catch (_e) {\n /* not JSON */\n }\n return txt.split(/\\r?\\n/).map((s) => s.trim()).filter(Boolean);\n}\n\nexport default async function (req: Request): Promise {\n const url = new URL(req.url);\n if (req.method === \"POST\" && url.searchParams.get(\"action\") === \"save\") {\n try {\n const txt = await req.text();\n const names = parseNames(txt);\n await blob.set(\"names_1\", JSON.stringify(names));\n return new Response(\n `Saved ${names.length} names. Now run main.ts (the verifier) to check them.`,\n { headers: { \"Content-Type\": \"text/plain\" } },\n );\n } catch (e) {\n const msg = e instanceof Error ? `${e.name}: ${e.message}` : String(e);\n return new Response(\"ERROR: \" + msg, { status: 500, headers: { \"Content-Type\": \"text/plain\" } });\n }\n }\n return new Response(PAGE, { headers: { \"Content-Type\": \"text/html; charset=utf-8\" } });\n}\n",[150],"c5d47e1d-68b4-4899-bda6-024a82ca41e2","export.ts","204dde48-a87a-11f1-867b-1607ee4eb77e",20,["D",1788537798150],1,"// Export page: downloads verification results grouped into clear buckets so\n// nothing is silently dropped. Every name is accounted for.\nimport { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst PAGE = `\n\nVerification results\n\n

Podcast verification results

Loading…

Download everything, grouped so you can review before deciding what to drop:

\n Verified (keep)\n Uncertain (review me)\n Not found\n All results\n

\"Verified\" = confident real match. \"Uncertain\" = Apple has a near-match under a slightly different title — check these before dropping. \"Not found\" = no Apple show under that name.

\n\n`;\n\nconst esc = (v: unknown): string => {\n const s = v === null || v === undefined ? \"\" : String(v);\n if (/[\",\\n\\r]/.test(s)) return `\"${s.replace(/\"/g, '\"\"')}\"`;\n return s;\n};\nconst toCsv = (rows: any[], fields: string[]): string => {\n const lines = [fields.join(\",\")];\n for (const r of rows) lines.push(fields.map((f) => esc(r[f])).join(\",\"));\n return lines.join(\"\\n\");\n};\n\nexport default async function (req: Request): Promise {\n const url = new URL(req.url);\n const status = url.searchParams.get(\"download\");\n const wantSummary = url.searchParams.get(\"summary\") !== null;\n\n const res = await sqlite.execute(\n \"SELECT queried_name, status, score, record FROM verify_results\",\n );\n const rows = res.rows;\n\n if (wantSummary) {\n const counts = { verified: 0, uncertain: 0, not_found: 0, duplicate: 0, total: rows.length };\n for (const r of rows) {\n const s = r.status as string;\n if (s in counts) (counts as any)[s]++;\n }\n return new Response(JSON.stringify(counts), {\n headers: { \"Content-Type\": \"application/json\" },\n });\n }\n\n if (!status) return new Response(PAGE, { headers: { \"Content-Type\": \"text/html; charset=utf-8\" } });\n\n let filtered = rows;\n if (status !== \"all\") filtered = rows.filter((r) => r.status === status);\n\n const fields = [\"queried_name\", \"status\", \"score\", \"matched_name\", \"itunes_id\", \"publisher\", \"podlink\"];\n const csvRows = filtered.map((r) => {\n let rec: any = {};\n try { rec = JSON.parse((r.record as string) || \"{}\"); } catch (_e) { /* ignore */ }\n return {\n queried_name: r.queried_name,\n status: r.status,\n score: r.score === null || r.score === undefined ? \"\" : Math.round((r.score as number) * 100),\n matched_name: rec.name || \"\",\n itunes_id: rec.id || \"\",\n publisher: rec.pub || \"\",\n podlink: rec.link || \"\",\n };\n });\n\n const csv = toCsv(csvRows, fields);\n const name = { verified: \"verified\", uncertain: \"review\", not_found: \"not_found\", all: \"all\", duplicate: \"duplicate\" }[status] || status;\n return new Response(csv, {\n headers: {\n \"Content-Type\": \"text/csv\",\n \"Content-Disposition\": `attachment; filename=\"podcast_${name}.csv\"`,\n },\n });\n}\n",[158],"pulls","branches","forks","envVars",{"_172":67,"_174":67},"connections",{"_172":67,"_173":67},"count","unfilledCount","emptyCount",{"_48":157,"_38":158,"_36":159,"_137":-5,"_46":47,"_45":160,"_138":32,"_43":189,"_13":162,"_39":154,"_41":163,"_29":32,"_140":-5,"_180":190,"_33":191},{"_48":149,"_38":150,"_36":151,"_137":-5,"_46":47,"_45":152,"_138":30,"_43":186,"_13":67,"_39":154,"_41":155,"_29":32,"_140":-5,"_180":187,"_33":188},{"_48":142,"_38":143,"_36":62,"_137":-5,"_46":47,"_45":144,"_138":32,"_43":183,"_13":146,"_39":40,"_41":147,"_29":32,"_140":-5,"_180":184,"_33":185},{"_48":136,"_38":34,"_36":37,"_137":-5,"_46":47,"_45":14,"_138":32,"_43":179,"_13":67,"_39":40,"_41":42,"_29":32,"_140":-5,"_180":181,"_33":182},["D",1788537980682],"children",[],[34],["D",1788537778768],[],[143],["D",1788532529232],[],[150],["D",1788537798150],[],[158],["D",1788530401973],["D",1789488693443],{"_104":103,"_110":58},{"_104":103,"_105":58,"_106":58,"_19":60,"_107":108,"_109":32},{"_13":93,"_38":94,"_48":47,"_95":49,"_96":-5,"_97":-5,"_98":-5,"_99":-5,"_100":-5,"_101":50,"_102":103},"ctx",{"_86":-5,"_129":230,"_231":232,"_233":234,"_235":32,"_236":32,"_237":32,"_238":30,"_239":-5,"_240":-7,"_241":-7,"_242":67,"_243":32,"_244":32,"_245":-5,"_246":32,"_247":32,"_248":32,"_249":-5},"ENV",{"_201":202,"_203":204,"_205":94,"_206":207,"_208":209,"_210":211,"_212":213,"_214":215,"_216":217,"_218":219,"_220":221,"_222":223,"_224":225,"_226":227,"_228":229},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Diff · v21