{"parentUuid":null,"isSidechain":true,"promptId":"97d13177-e1fb-4157-b04b-8f8e5f00cef7","agentId":"a06c2ed5ce2ee13c3","type":"user","message":{"role":"user","content":"Sto cercando, dentro il repo Python `PYTHON/MyICR_Suite` (path completo dalla root: `/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite`, sola lettura da qui), il modulo \"Linker\" — un foglio/griglia storico (originariamente VBA/Excel, poi migrato in Python) che per ogni prodotto mostra in una sola riga un riassunto di campi anagrafici + diritti + emesso + boxoffice + Gemma. So che c'è un file `linker/src/gui/gemma_sheet.py` e `filter_bar.py` citati altrove, quindi il modulo si chiama probabilmente `linker/`.\n\nIl mio obiettivo: trovare la lista dei CAMPI ANAGRAFICI specifici che il foglio Linker mostra/espone per ogni prodotto (non diritti/emesso/boxoffice, solo la parte \"anagrafica\" — es. potrebbero essere cose come titolo, anno produzione, genere, durata, ecc., ma voglio i nomi esatti dei campi/colonne usati nel codice, non un'ipotesi).\n\nCerca:\n1. La cartella `linker/` dentro MyICR_Suite (potrebbe essere sotto `app/modules/linker/` o simile)\n2. File che definiscono le colonne/campi mostrati nella griglia principale (es. `gemma_sheet.py`, o un file di configurazione colonne, o una query SQL che seleziona i campi anagrafici)\n3. Eventuali costanti tipo `ANAGRAFICA_FIELDS`, liste di nomi colonna, o header di tabella\n\nRiporta: il path esatto dei file rilevanti, e l'elenco preciso dei campi anagrafici che hai trovato (nomi colonna esatti, non parafrasati), con il file/riga dove li hai trovati. Se trovi anche a quali tabelle/parquet fanno riferimento, riportalo. Rispondi in italiano, sii preciso e cita sempre file:riga."},"uuid":"a925d341-2994-485a-950a-d1f52c67353b","timestamp":"2026-08-07T08:46:07.268Z","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
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{"parentUuid":"242fac79-caf9-4d6c-a0c4-3fe00e5124f0","isSidechain":true,"agentId":"a06c2ed5ce2ee13c3","attachment":{"type":"skill_listing","content":"- avvio-sessione: Checklist di inizio sessione — identifica l'istanza (Nave/Ufficio), legge memory/MEMORY.md, apre l'hub di archivio/, e su Nave avvia il Monitor persistente per voice-chat. Invocare sempre a inizio sessione, idealmente al primo turno — normalmente richiamata da un hook SessionStart, ma va eseguita anche se manca il promemoria dell'hook.\n- chiusura-sessione: Checklist di fine sessione per aggiornare memoria e archivio in modo coerente prima di chiudere — cosa va in memory/MEMORY.md, cosa in archivio/ come storico, cosa in CLAUDE.md, cosa va committato. Usare quando Mauro segnala che sta per chiudere/staccare, o quando si nota che sono passate molte ore/molti argomenti dall'ultimo aggiornamento di memoria.\n- manutenzione-archivio: Scansione meccanica di archivio/ per trovare link rotti, file orfani e hub incompleti — riporta i risultati a Mauro, non corregge nulla in autonomia. Usare su richiesta esplicita di Mauro (\"controlla l'archivio\", \"scansione generale\"), o quando ci si accorge di disordine strutturale mentre si lavora su un'altra cosa.\n- processa-inbox: Processa i documenti caricati da Mauro in inbox-documenti/ (scansioni, PDF firmati, email .eml, ecc.) e li archivia correttamente in archivio/_documenti/ con nota sidecar. Usare quando Mauro segnala che ha caricato qualcosa in inbox, quando si nota che inbox-documenti/ non è vuota, o quando un messaggio inizia con `@inbox`.\n- processa-promemoria: Intercetta i promemoria che Mauro scrive su Apple Reminders (arrivano su Microsoft To Do tramite l'account agganciato) e li smista al volo in conversazione — thread in memory/MEMORY.md, nota in archivio/, o scarto se già gestiti. Consulta anche il calendario (stesso account) per contesto su scadenze/impegni. Modello: check-in periodico, non per-item — usare quando Mauro segnala di aver aggiunto promemoria, chiede di controllare Reminders/calendario, a inizio sessione se è passato tempo dall'ultimo giro, o quando un messaggio inizia con `@gate` (bypassa Reminders, il testo va processato con lo stesso triage).\n- loop: Sei Adrian. Mettiti in ascolto sul cockpit Adrian↔Elon↔Mauro.\n- dataviz: Use this skill whenever you are about to create ANY chart, graph, plot, dashboard, or data visualization, in ANY output medium — an HTML or React artifact, inline SVG, plotting code in any library (matplotlib, plotly, d3, Recharts, …), an image/PNG you will render and upload, or a chart shared into Slack. Read it BEFORE writing the first line of chart code, choosing chart colors, building a stat tile / meter / KPI row, or laying out a dashboard. Produces visualizations that read as one system — elegant, accessible, consistent in light and dark — using a brand-neutral placeholder palette you swap for your own. Teaches a design-system-agnostic method: a form heuristic, a color formula with a runnable validator, mark specs, and interaction rules. A validated default palette is documented in `references/palette.md` — swap that file's values for your brand's. Triggers on: \"chart\", \"graph\", \"plot\", \"data viz\", \"visualization\", \"dashboard\", \"analytics\", \"visualize data\", \"categorical colors\", \"sequential / diverging palette\", \"stat tile\", \"sparkline\", \"heatmap\", \"legend\", \"axis\", \"tooltip\", \"chart colors\", \"color by series\".\n- artifact-design: Design guidance and fundamentals for Artifacts.\n- artifact-diagramming: Diagramming know-how for Artifacts — when a picture earns its place, how to draw one that shows the real mechanism, and the inline-SVG mechanics that keep it legible in both themes.\n- artifact-capabilities: Runtime capabilities a published Artifact page can be granted — behavior static HTML cannot provide on its own, such as the page reading live or connected data, keeping state shared across viewers, or updating and republishing itself. Serves this user's live capability roster and the typed call definitions. Load it whenever the user asks for an artifact needing any such runtime behavior.\n- update-config: Use this skill to configure the Claude Code harness via settings.json. Automated behaviors (\"from now on when X\", \"each time X\", \"whenever X\", \"before/after X\") require hooks configured in settings.json - the harness executes these, not Claude, so memory/preferences cannot fulfill them. Also use for: permissions (\"allow X\", \"add permission\", \"move permission to\"), env vars (\"set X=Y\"), hook troubleshooting, or any changes to settings.json/settings.local.json files. Examples: \"allow npm commands\", \"add bq permission to global settings\", \"move permission to user settings\", \"set DEBUG=true\", \"when claude stops show X\". For simple settings like theme/model, suggest the /config command.\n- keybindings-help: Use when the user wants to customize keyboard shortcuts, rebind keys, add chord bindings, or modify ~/.claude/keybindings.json. Examples: \"rebind ctrl+s\", \"add a chord shortcut\", \"change the submit key\", \"customize keybindings\".\n- simplify: Review the changed code for reuse, simplification, efficiency, and altitude cleanups, then apply the fixes. Quality only — it does not hunt for bugs; use /code-review for that.\n- fewer-permission-prompts: Scan your transcripts for common read-only Bash and MCP tool calls, then add a prioritized allowlist to project .claude/settings.json to reduce permission prompts.\n- schedule: Create, update, list, or run scheduled cloud agents (routines) that execute on a cron schedule. - When the user wants to schedule a recurring cloud agent, set up automated tasks, create a cron job for Claude Code, or manage their scheduled agents/routines. Also use when the user wants a one-time scheduled run (\"run this once at 3pm\", \"remind me to check X tomorrow\").\n- claude-api: Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration.\nTRIGGER — read BEFORE opening the target file; don't skip because it \"looks like a one-liner\" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens).\nSKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).\n- run: Launch and drive this project's app to see a change working. Use when asked to run, start, or screenshot the app, or to confirm a change works in the real app (not just tests). First looks for a project skill that already covers launching the app; otherwise falls back to built-in patterns per project type (CLI, server, TUI, Electron, browser-driven, library).\n- init: Initialize a new CLAUDE.md file with codebase documentation\n- review: Review a GitHub pull request; for your working diff use /code-review\n- security-review: Complete a security review of the pending changes on the current branch","skillCount":20,"isInitial":true,"names":["avvio-sessione","chiusura-sessione","manutenzione-archivio","processa-inbox","processa-promemoria","loop","dataviz","artifact-design","artifact-diagramming","artifact-capabilities","update-config","keybindings-help","simplify","fewer-permission-prompts","schedule","claude-api","run","init","review","security-review"]},"type":"attachment","uuid":"0d77b9e9-d748-4c2c-a6e2-53585fe27314","timestamp":"2026-08-07T08:46:07.279Z","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
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{"parentUuid":"223c39d4-eee8-41cb-9cc7-d3111e636ef2","isSidechain":true,"promptId":"97d13177-e1fb-4157-b04b-8f8e5f00cef7","agentId":"a06c2ed5ce2ee13c3","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01AJrKSovNbdmRYuCSG1BvFo","type":"tool_result","content":"1\t---\n2\taliases: [\"Linker\"]\n3\ttype: modulo\n4\tparent: \"MyICR Suite\"\n5\t---\n6\t\n7\t# CLAUDE.md — Linker\n8\t**Versione:** v1\n9\t**Ultimo aggiornamento:** 2026-07-02\n10\t\n11\t---\n12\t\n13\t## Visione architetturale (2026-05-21)\n14\t\n15\tIl modulo PyQt6 \"Linker\" è l'erede di MyICR (il vecchio tool VBA in Excel).\n16\t\"Linker\" è sia il nome del contenitore sia il nome dell'app standard al suo interno.\n17\t\n18\t### Nomenclatura ufficiale\n19\t\n20\t| Nome | Classe | Descrizione |\n21\t|---|---|---|\n22\t| **Linker** (contenitore) | `MainWindow` | La finestra PyQt6 che ospita tutti i fogli |\n23\t| **Linker** (app standard) | `LinkerSheet` | Foglio con input manuale RIFER/titoli |\n24\t| **Aggancio** | `AggancioSheet` | Foglio con input da listino fornitore |\n25\t| **In Scadenza** | `InScadenzaSheet` | Foglio feeder automatico da parquet |\n26\t\n27\t### Modello concettuale\n28\t\n29\t```\n30\tLinker (contenitore)\n31\t  ├── Linker 1      (istanza LinkerSheet)\n32\t  ├── Linker 2      (istanza LinkerSheet)\n33\t  ├── Aggancio 1    (istanza AggancioSheet)\n34\t  └── In Scadenza 1 (istanza InScadenzaSheet)\n35\t```\n36\t\n37\t**Ogni tab è un'istanza di un'app specifica** — non un foglio generico.\n38\tIl nome del tab è `[NomeApp] [N]` (es. \"Linker 1\", \"Aggancio 1\"). L'utente può\n39\trinominare il label visibile, ma il tipo (`app_type`) è immutabile e MyICR lo ricorda\n40\tin `session.json`.\n41\t\n42\t### Tre livelli distinti\n43\t\n44\t1. **Feeder** — popola un foglio con RIFER:\n45\t   - Input manuale (Linker standard)\n46\t   - Listino fornitore (Aggancio)\n47\t   - Parquet automatico (In Scadenza)\n48\t   - Un foglio può essere popolato da più feeder in momenti diversi\n49\t\n50\t2. **Renderer** — modulo trasversale (`GridFiller` + pipeline fetch parquet):\n51\t   - Prende una lista di RIFER → produce colonne standardizzate\n52\t   - Indifferente alla sorgente dei RIFER\n53\t   - Condiviso tra tutti i tipi di foglio\n54\t\n55\t3. **Output** — la griglia renderizzata, sempre la stessa struttura\n56\t\n57\t### Colonne derivate (DECOR_FORN, DELTA, MOTIVO)\n58\t\n59\tAppartengono al workflow di aggancio (confronto date decorrenza listino vs diritti\n60\tesistenti). Non hanno senso in un foglio Linker standard o In Scadenza standalone.\n61\t**Regola:** mostrarle solo se il foglio è di tipo Aggancio, o se è \"In Scadenza\" aperto\n62\tin contesto di un Aggancio attivo. In tutti gli altri casi: colonne nascoste.\n63\t\n64\t### Accoppiamento contenitore ↔ feeder\n65\t\n66\t\"In Scadenza\" non deve interrogare direttamente gli altri fogli. È il **contenitore**\n67\t(MainWindow) che conosce i fogli aperti e passa le informazioni necessarie a \"In Scadenza\"\n68\tcome parametro al momento dell'apertura. Nessun accoppiamento diretto tra fogli.\n69\t\n70\t---\n71\t\n72\t## Sorgenti dati — NO MS Access\n73\t\n74\t**Il Linker non usa MS Access.** Migrazione completata 2026-04-29.\n75\t\n76\t- Dati prodotti: DuckDB su Parquet DataHub_v2\n77\t- Repository Linker: `linker.db` SQLite sidecar\n78\t- Offline: parquet sincronizzati in `local_db/parquet/`\n79\t\n80\t---\n81\t\n82\t## Modalità offline\n83\t\n84\tLinker può funzionare offline se i parquet sono stati sincronizzati.\n85\tUsa DuckDB/Parquet (`local_db/parquet/`) + `linker.db` SQLite — nessuna dipendenza di rete.\n86\t\n87\t---\n88\t\n89\t## GemmaSheet (completato 2026-07-01)\n90\t\n91\tMigrazione modulo Gemma da VBA completata come PyQt6 sheet nel Linker container.\n92\tScelta PyQt6 (non Flask) per performance su 51K righe.\n93\t\n94\t- File: `src/gui/gemma_sheet.py`\n95\t- Tipo: `QTableView + QAbstractTableModel` — virtual scrolling (solo righe visibili)\n96\t- Read-only — dati da `gemma.parquet` via DuckDB/SQLite mirror\n97\t- Integrato come tab aggiuntivo nel Linker `MainWindow`\n98\t\n99\t---\n100\t\n101\t## Standard UI — fogli Linker\n102\t\n103\tOgni nuovo foglio del Linker deve rispettare:\n104\t\n105\t| Feature | Standard |\n106\t|---|---|\n107\t| Selezione celle | `SelectItems` (singola cella, stile Excel) — **non** `SelectRows` |\n108\t| Cella selezionata | `background: #CCE8FF; color: #0078D7` via stylesheet |\n109\t| Tasto destro → Copia | `_copy_selection()` — copia selezione singola o multipla in TSV |\n110\t| Hamburger menu | Importa / Esporta / Filtro colonne (Ctrl+F) / Mostra valutazioni |\n111\t| FilterBar | presente, toggled via Ctrl+F e hamburger |\n112\t| Font griglia | Calibri 8 |\n113\t\n114\t```python\n115\tself.table.setStyleSheet(\"\"\"\n116\t    QTableWidget { gridline-color: #C0C0C0; }\n117\t    QTableWidget::item { padding: 0px 3px; }\n118\t    QTableWidget::item:selected { background-color: #CCE8FF; color: #0078D7; }\n119\t\"\"\")\n120\t```\n121\t\n122\t---\n123\t\n124\t## Backlog\n125\t\n126\t- **Linker Step 4**: match tra tabelle — checkbox \"Escludi titoli già in Linker\"\n127\t- **MT-03 Fase 2**: configurazione utente Modalità Mercato (tipologie, range anni, filtri)\n128\t- **OTT**: spostare colonne valutazioni nella griglia ✓ — flag NO ICR auto-valorizzato ✓\n129\t"}]},"uuid":"fc46c3f7-e4d3-4306-acbd-06322ded4f33","timestamp":"2026-08-07T08:46:15.882Z","sourceToolAssistantUUID":"223c39d4-eee8-41cb-9cc7-d3111e636ef2","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
{"parentUuid":"4e32f60b-7d02-4c42-8f57-2d2090ff1dbc","isSidechain":true,"promptId":"97d13177-e1fb-4157-b04b-8f8e5f00cef7","agentId":"a06c2ed5ce2ee13c3","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01HbfNCVJ8BUjp2PyEbW7V7r","type":"tool_result","content":"1\t\"\"\"\n2\tcolumn_defs.py — dizionario centralizzato colonne Linker.\n3\t\n4\tFonte unica di verità per: colore intestazione, larghezza, label.\n5\tTutti i fogli (ott_sheet, linker_sheet, diritti_tab, …) importano da qui.\n6\t\n7\tStruttura FIELDS:\n8\t    key  → identificatore semantico univoco del campo (es. 'EM_RETE' ≠ 'TEM_RETE')\n9\t    label → testo intestazione visualizzato\n10\t    width → larghezza colonna in pixel\n11\t    color → colore intestazione (istanza HC)\n12\t\"\"\"\n13\tfrom PyQt6.QtGui import QColor\n14\t\n15\t\n16\t# ── Palette canonica intestazioni ─────────────────────────────────────────\n17\tclass HC:\n18\t    \"\"\"HeaderColor — tutti i fogli Linker usano solo questi colori.\"\"\"\n19\t    SEGNALAZ   = QColor('#AAFF00')   # verde acido — segnalazioni automatiche\n20\t    OTT        = QColor('#9DC3E6')   # blu chiaro — dati OTT / piattaforme\n21\t    EDITABILE  = QColor('#00E5FF')   # ciano vivo — colonne editabili dall'utente\n22\t    IMDB       = QColor('#00BFFF')   # ciano — IMDB read-only da parquet\n23\t    GREY       = QColor('#D9D9D9')   # grigio — metadati secondari (voto, votanti)\n24\t    ORANGE     = QColor('#FFB347')   # arancione — anagrafica ONAIR + emesso generaliste\n25\t    YELLOW     = QColor('#FFFF00')   # giallo — valutazioni rete / box office\n26\t    VAL        = QColor('#FFF59D')   # giallo pastello — valutazioni Gemma\n27\t    DIRITTI    = QColor('#90EE90')   # verde — diritti\n28\t    PURPLE     = QColor('#C39BD3')   # viola — emesso tematiche\n29\t    LIGHT_RED  = QColor('#FFAAAA')   # rosso chiaro — RETE SLOT / OTT\n30\t    FUCHSIA    = QColor('#FF91C4')   # fucsia — feeder (decorrenza listino)\n31\t    DEFAULT    = QColor('#CCCCCC')   # grigio chiaro — non classificato\n32\t    BORDER     = QColor('#A0A0A0')   # bordo intestazioni\n33\t\n34\t\n35\t# ── Campi condivisi tra tutti i fogli Linker ─────────────────────────────\n36\t# Key: identificatore semantico univoco (es. 'EM_RETE' ≠ 'TEM_RETE')\n37\t# label: testo intestazione — può non essere univoco, il key lo è\n38\t# width: larghezza default in pixel\n39\t# color: colore intestazione (HC.*)\n40\tFIELDS: dict[str, dict] = {\n41\t\n42\t    # ── Anagrafica / ONAIR ──────────────────────────────────────────────\n43\t    'RIFER':         {'label': 'RIFER',         'width': 61,  'color': HC.ORANGE},\n44\t    'IMDB':          {'label': 'IMDB',          'width': 61,  'color': HC.IMDB},\n45\t    'TIPOL':         {'label': 'TIPOL',         'width': 75,  'color': HC.ORANGE},\n46\t    'TI':            {'label': 'TI',            'width': 200, 'color': HC.ORANGE},\n47\t    'TO':            {'label': 'TO',            'width': 200, 'color': HC.ORANGE},\n48\t    'ANNO':          {'label': 'ANNO',          'width': 61,  'color': HC.ORANGE},\n49\t    'PAESE':         {'label': 'PAESE',         'width': 61,  'color': HC.ORANGE},\n50\t    'GENERE':        {'label': 'GENERE',        'width': 100, 'color': HC.ORANGE},\n51\t    'EPIS':          {'label': 'EPIS',          'width': 47,  'color': HC.ORANGE},\n52\t    'DURATA':        {'label': 'DURATA',        'width': 60,  'color': HC.ORANGE},\n53\t    'SUPERSERIE':    {'label': 'SUPERSERIE',    'width': 110, 'color': HC.ORANGE},\n54\t    'VEG_FREE':      {'label': 'VEG',           'width': 40,  'color': HC.ORANGE},\n55\t    'REGISTA':       {'label': 'REGISTA',       'width': 131, 'color': HC.ORANGE},\n56\t    'ATTORI':        {'label': 'ATTORI',        'width': 131, 'color': HC.ORANGE},\n57\t\n58\t    # ── Diritti ─────────────────────────────────────────────────────────\n59\t    'SD':            {'label': 'SD',            'width': 35,  'color': HC.DIRITTI},\n60\t    'DECOR':         {'label': 'DECOR.',        'width': 68,  'color': HC.DIRITTI},\n61\t    'SCAD':          {'label': 'SCAD.',         'width': 68,  'color': HC.DIRITTI},\n62\t    'DISTRIBUTORE':  {'label': 'DISTRIBUTORE',  'width': 120, 'color': HC.DIRITTI},\n63\t    'PERC':          {'label': '%',             'width': 40,  'color': HC.DIRITTI},\n64\t    'PASS_CONS':     {'label': 'P.CONS.',       'width': 40,  'color': HC.DIRITTI},\n65\t    'PASS_EFF':      {'label': 'P.EFF.',        'width': 40,  'color': HC.DIRITTI},\n66\t    'CAUS':          {'label': 'CAUS.',         'width': 40,  'color': HC.DIRITTI},\n67\t    'DECOR_FUT':     {'label': 'DECOR. FUT.',   'width': 90,  'color': HC.DIRITTI},\n68\t    'SCAD_FUT':      {'label': 'SCAD. FUT.',    'width': 90,  'color': HC.DIRITTI},\n69\t    'RETE_SLOT':     {'label': 'RETE SLOT',     'width': 89,  'color': HC.DIRITTI},\n70\t\n71\t    # ── Emesso generaliste ──────────────────────────────────────────────\n72\t    'EM_RETE':       {'label': 'RETE',          'width': 45,  'color': HC.ORANGE},\n73\t    'EM_DATA':       {'label': 'DATA',          'width': 68,  'color': HC.ORANGE},\n74\t    'EM_INIZIO':     {'label': 'INIZIO',        'width': 55,  'color': HC.ORANGE},\n75\t    'EM_FASCIA':     {'label': 'FASCIA',        'width': 47,  'color': HC.ORANGE},\n76\t    'EM_AUD':        {'label': 'AUD',           'width': 55,  'color': HC.ORANGE},\n77\t    'EM_SHA':        {'label': 'SHA',           'width': 50,  'color': HC.ORANGE},\n78\t\n79\t    # ── Emesso tematiche (.T suffix distingue dai generaliste) ──────────\n80\t    'TEM_RETE':      {'label': 'RETE.T',        'width': 45,  'color': HC.PURPLE},\n81\t    'TEM_DATA':      {'label': 'DATA.T',        'width': 68,  'color': HC.PURPLE},\n82\t    'TEM_INIZIO':    {'label': 'INIZIO.T',      'width': 55,  'color': HC.PURPLE},\n83\t    'TEM_FASCIA':    {'label': 'FASCIA.T',      'width': 47,  'color': HC.PURPLE},\n84\t    'TEM_AUD':       {'label': 'AUD.T',         'width': 55,  'color': HC.PURPLE},\n85\t    'TEM_SHA':       {'label': 'SHA.T',         'width': 50,  'color': HC.PURPLE},\n86\t\n87\t    # ── Box Office ──────────────────────────────────────────────────────\n88\t    'BO_DEB':        {'label': 'DEBUTTO',       'width': 68,  'color': HC.YELLOW},\n89\t    'BO_INCASSO':    {'label': 'INCASSO',       'width': 61,  'color': HC.YELLOW},\n90\t    'BO_SPETT':      {'label': 'SPETTATORI',    'width': 61,  'color': HC.YELLOW},\n91\t    'BO_DIST':       {'label': 'DIST. CINEMA',  'width': 120, 'color': HC.YELLOW},\n92\t\n93\t    # ── Valutazioni Gemma (slot 0–15) ────────────────────────────────────\n94\t    'VAL_FORNITORE': {'label': 'FORNITORE',     'width': 120, 'color': HC.VAL},\n95\t    'VAL_RDA':       {'label': 'RDA',           'width': 120, 'color': HC.VAL},\n96\t    'VAL_C5':        {'label': 'C5',            'width': 45,  'color': HC.VAL},\n97\t    'VAL_I1':        {'label': 'I1',            'width': 45,  'color': HC.VAL},\n98\t    'VAL_R4':        {'label': 'R4',            'width': 45,  'color': HC.VAL},\n99\t    'VAL_LA5':       {'label': 'LA5',           'width': 45,  'color': HC.VAL},\n100\t    'VAL_I2':        {'label': 'I2',            'width': 45,  'color': HC.VAL},\n101\t    'VAL_IRIS':      {'label': 'IRIS',          'width': 45,  'color': HC.VAL},\n102\t    'VAL_TOP':       {'label': 'TOP CRIME',     'width': 70,  'color': HC.VAL},\n103\t    'VAL_FOC':       {'label': 'FOCUS',         'width': 55,  'color': HC.VAL},\n104\t    'VAL_C20':       {'label': 'C20',           'width': 45,  'color': HC.VAL},\n105\t    'VAL_CI34':      {'label': 'CINE34',        'width': 55,  'color': HC.VAL},\n106\t    'VAL_C27':       {'label': 'TWENTY SEVEN',  'width': 80,  'color': HC.VAL},\n107\t    'VAL_SUPPORTO':  {'label': 'SUPPORTO',      'width': 120, 'color': HC.VAL},\n108\t    'VAL_DATA':      {'label': 'DATA VAL.',     'width': 80,  'color': HC.VAL},\n109\t    'VAL_GEM_SIN':   {'label': 'GEM SIN',       'width': 60,  'color': HC.VAL},\n110\t}\n111\t\n112\t\n113\tdef fl(key: str) -> str:\n114\t    \"\"\"Label intestazione del campo.\"\"\"\n115\t    return FIELDS[key]['label']\n116\t\n117\t\n118\tdef fw(key: str) -> int:\n119\t    \"\"\"Larghezza default del campo in pixel.\"\"\"\n120\t    return FIELDS[key]['width']\n121\t\n122\t\n123\tdef fc(key: str) -> QColor:\n124\t    \"\"\"Colore intestazione del campo.\"\"\"\n125\t    return FIELDS[key]['color']\n126\t\n127\t\n128\t"}]},"uuid":"b20fd605-e4b6-4f17-9b83-debf978e7d9b","timestamp":"2026-08-07T08:46:15.884Z","sourceToolAssistantUUID":"4e32f60b-7d02-4c42-8f57-2d2090ff1dbc","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
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{"parentUuid":"27621195-8b93-41ef-8a89-22de546ba62a","isSidechain":true,"promptId":"97d13177-e1fb-4157-b04b-8f8e5f00cef7","agentId":"a06c2ed5ce2ee13c3","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012bzkzViUT9r5TK6KE1wJvr","type":"tool_result","content":"35:        prod_f = str(p / 'prodotti.parquet').replace('\\\\', '/')\n36:        cast_f = str(p / 'cast.parquet').replace('\\\\', '/')\n37:        imdb_f = str(p / 'imdb.parquet').replace('\\\\', '/')\n41:            CREATE VIEW v_custom_anagr AS\n54:                SELECT prodotto, cognome AS REGISTA_COGN, nome AS REGISTA_NOME\n83:                CAST(p.prodotto AS VARCHAR) AS RIFER,\n84:                p.tipologia                 AS TIPOL,\n92:                p.superserie_descr          AS SUPERSERIE,\n93:                CASE p.veg WHEN 'EVER GREEN' THEN 'EV.GR' ELSE p.veg END AS VEG_FREE,\n95:                r.REGISTA_COGN,\n96:                r.REGISTA_NOME,\n114:                tipologia             AS TIPOLOGIA,\n132:        \"\"\"Dict IMDB→RIFER da scansione completa di imdb.parquet (no IN clause).\"\"\"\n134:            imdb_f = str(self.parquet_path / 'imdb.parquet').replace('\\\\', '/')\n136:                SELECT riferimento_imdb AS IMDB_CODICE, CAST(codice AS VARCHAR) AS RIFER\n143:            return dict(zip(df['IMDB_CODICE'].astype(str), df['RIFER'].astype(str)))\n157:                SELECT RIFER, tipo_rete,\n177:                df = self._get_con().execute(\"SELECT * FROM v_custom_anagr\").df()\n191:                sql = f\"SELECT * FROM v_imdb_full WHERE REGISTA ILIKE '%{safe}%' LIMIT 999999\"\n204:                    f\"SELECT RIFER, TIPOL, \\\"TO\\\", TI, ANNO, REGISTA_COGN, REGISTA_NOME \"\n205:                    f\"FROM v_custom_anagr WHERE REGISTA_COGN ILIKE '%{safe}%' LIMIT 999999\"\n209:                    f\"SELECT RIFER, TIPOL, \\\"TO\\\", TI, ANNO, REGISTA_COGN, REGISTA_NOME \"\n210:                    f\"FROM v_custom_anagr WHERE \\\"TO\\\" ILIKE '{safe}%' OR TI ILIKE '{safe}%' LIMIT 999999\"\n221:                f\"SELECT * FROM v_custom_anagr WHERE RIFER = '{safe}'\"\n231:                f\"SELECT * FROM v_custom_anagr WHERE IMDB_CODICE = '{safe}'\"\n259:                f\"SELECT * FROM v_custom_anagr WHERE RIFER IN ({placeholders})\"\n295:                \"SELECT DISTINCT TIPOLOGIA FROM v_diritti \"\n297:                \"AND TIPOLOGIA IS NOT NULL ORDER BY TIPOLOGIA\"\n299:            return df['TIPOLOGIA'].dropna().tolist()\n309:                tipol_clause = f\"AND TIPOLOGIA IN ({placeholders})\"\n312:                    \"AND TIPOLOGIA IN \"\n333:                    CAST(prod AS VARCHAR) AS RIFER,\n353:                    CAST(prod AS VARCHAR) AS RIFER,\n383:                    SELECT RIFER, tipo_rete,\n391:                    WHERE RIFER IN ({placeholders})\n397:                    CAST(prodotto AS VARCHAR) AS RIFER,\n426:                    SELECT RIFER, tipo_rete,\n434:                    WHERE RIFER IN ({placeholders})\n440:                    CAST(prodotto AS VARCHAR) AS RIFER,\n540:        \"\"\"Dato un elenco di codici IMDB (tt...) restituisce IMDB_CODICE → RIFER OnAir.\"\"\"\n543:        imdb_f = str(self.parquet_path / 'imdb.parquet').replace('\\\\', '/')\n550:                       CAST(codice AS VARCHAR) AS RIFER,\n581:        \"\"\"Restituisce rete/slot aggregati per lista RIFER (una riga per RIFER).\"\"\"\n592:                        CAST(prodotto AS VARCHAR) AS RIFER,\n604:                SELECT RIFER,\n608:                GROUP BY RIFER\n616:        \"\"\"Restituisce dati box office (debutto, incasso, spettatori, distributore) per lista RIFER.\"\"\"\n627:                    CAST(prodotto AS VARCHAR) AS RIFER,\n701:        \"\"\"Restituisce tutte le edizioni di un prodotto (ED, TIPOL, DUR, VM).\"\"\"\n704:        prod_f = str(self.parquet_path / 'prodotti.parquet').replace('\\\\', '/')\n710:                    tipologia AS TIPOL,\n722:        \"\"\"Restituisce tutti i prodotti di una superserie (VEG, TIPOL, TI).\"\"\"\n725:        prod_f = str(self.parquet_path / 'prodotti.parquet').replace('\\\\', '/')\n731:                    tipologia       AS TIPOL,","is_error":false}]},"uuid":"5004da70-244c-4d7c-83a8-0880eea789e3","timestamp":"2026-08-07T08:46:25.426Z","sourceToolAssistantUUID":"27621195-8b93-41ef-8a89-22de546ba62a","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
{"parentUuid":"5004da70-244c-4d7c-83a8-0880eea789e3","isSidechain":true,"agentId":"a06c2ed5ce2ee13c3","message":{"model":"claude-sonnet-5","id":"msg_011Cdo6YChG69SNbchVRBYaV","type":"message","role":"assistant","content":[{"type":"text","text":"Ottima conferma. Leggo la view SQL completa per avere l'elenco esatto e i mapping colonna→sorgente."}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2164,"cache_read_input_tokens":31954,"cache_creation":{"ephemeral_5m_input_tokens":2164,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011Cdo6Y5WufkD85jgsk63Ys","attributionAgent":"Explore","type":"assistant","uuid":"c6024fef-b3e9-410e-b9a5-ff1727988d6d","timestamp":"2026-08-07T08:46:31.013Z","effort":"medium","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
{"parentUuid":"c6024fef-b3e9-410e-b9a5-ff1727988d6d","isSidechain":true,"agentId":"a06c2ed5ce2ee13c3","message":{"model":"claude-sonnet-5","id":"msg_011Cdo6YChG69SNbchVRBYaV","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_014sLWqnwGv4DQGKsoYgnYHr","name":"Read","input":{"file_path":"/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py","offset":30,"limit":100},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2164,"cache_read_input_tokens":31954,"cache_creation":{"ephemeral_5m_input_tokens":2164,"ephemeral_1h_input_tokens":0},"output_tokens":3,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011Cdo6Y5WufkD85jgsk63Ys","attributionAgent":"Explore","type":"assistant","uuid":"7cfff218-b867-4813-b110-82c928ee0624","timestamp":"2026-08-07T08:46:32.161Z","effort":"medium","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
{"parentUuid":"7cfff218-b867-4813-b110-82c928ee0624","isSidechain":true,"promptId":"97d13177-e1fb-4157-b04b-8f8e5f00cef7","agentId":"a06c2ed5ce2ee13c3","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_014sLWqnwGv4DQGKsoYgnYHr","type":"tool_result","content":"30\t            self._setup_views()\n31\t        return self._con\n32\t\n33\t    def _setup_views(self):\n34\t        p = self.parquet_path\n35\t        prod_f = str(p / 'prodotti.parquet').replace('\\\\', '/')\n36\t        cast_f = str(p / 'cast.parquet').replace('\\\\', '/')\n37\t        imdb_f = str(p / 'imdb.parquet').replace('\\\\', '/')\n38\t        dir_f  = str(p / 'diritti.parquet').replace('\\\\', '/')\n39\t\n40\t        self._con.execute(f\"\"\"\n41\t            CREATE VIEW v_custom_anagr AS\n42\t            WITH\n43\t            prod AS (\n44\t                SELECT *\n45\t                FROM read_parquet('{prod_f}')\n46\t                QUALIFY ROW_NUMBER() OVER (PARTITION BY prodotto ORDER BY edizione) = 1\n47\t            ),\n48\t            imdb AS (\n49\t                SELECT codice, MIN(riferimento_imdb) AS riferimento_imdb\n50\t                FROM read_parquet('{imdb_f}')\n51\t                GROUP BY codice\n52\t            ),\n53\t            reg AS (\n54\t                SELECT prodotto, cognome AS REGISTA_COGN, nome AS REGISTA_NOME\n55\t                FROM read_parquet('{cast_f}')\n56\t                WHERE ruolo = 'FRE'\n57\t                QUALIFY ROW_NUMBER() OVER (PARTITION BY prodotto ORDER BY progr_cast) = 1\n58\t            ),\n59\t            a1 AS (\n60\t                SELECT prodotto,\n61\t                       TRIM(COALESCE(nome, '') || ' ' || COALESCE(cognome, '')) AS ATTORE1\n62\t                FROM read_parquet('{cast_f}')\n63\t                WHERE ruolo = 'C001' AND progr_cast = 1\n64\t            ),\n65\t            a2 AS (\n66\t                SELECT prodotto,\n67\t                       TRIM(COALESCE(nome, '') || ' ' || COALESCE(cognome, '')) AS ATTORE2\n68\t                FROM read_parquet('{cast_f}')\n69\t                WHERE ruolo = 'C001' AND progr_cast = 2\n70\t            ),\n71\t            a3 AS (\n72\t                SELECT prodotto,\n73\t                       TRIM(COALESCE(nome, '') || ' ' || COALESCE(cognome, '')) AS ATTORE3\n74\t                FROM read_parquet('{cast_f}')\n75\t                WHERE ruolo = 'C001' AND progr_cast = 3\n76\t            ),\n77\t            distr AS (\n78\t                SELECT prod AS prodotto, MIN(ragsoc_distr) AS DF_RAGSOC_DISTR\n79\t                FROM read_parquet('{dir_f}')\n80\t                GROUP BY prod\n81\t            )\n82\t            SELECT\n83\t                CAST(p.prodotto AS VARCHAR) AS RIFER,\n84\t                p.tipologia                 AS TIPOL,\n85\t                p.titolo_originale          AS \"TO\",\n86\t                p.titolo_italiano           AS TI,\n87\t                p.anno_produzione           AS ANNO,\n88\t                p.paesi_produzione1         AS PAESE,\n89\t                p.genere1                   AS GENERE1,\n90\t                p.num_episodi               AS EPIS,\n91\t                p.durata                    AS DUR,\n92\t                p.superserie_descr          AS SUPERSERIE,\n93\t                CASE p.veg WHEN 'EVER GREEN' THEN 'EV.GR' ELSE p.veg END AS VEG_FREE,\n94\t                i.riferimento_imdb          AS IMDB_CODICE,\n95\t                r.REGISTA_COGN,\n96\t                r.REGISTA_NOME,\n97\t                a1.ATTORE1,\n98\t                a2.ATTORE2,\n99\t                a3.ATTORE3,\n100\t                d.DF_RAGSOC_DISTR\n101\t            FROM prod p\n102\t            LEFT JOIN imdb i  ON i.codice    = p.prodotto\n103\t            LEFT JOIN reg  r  ON r.prodotto  = p.prodotto\n104\t            LEFT JOIN a1      ON a1.prodotto = p.prodotto\n105\t            LEFT JOIN a2      ON a2.prodotto = p.prodotto\n106\t            LEFT JOIN a3      ON a3.prodotto = p.prodotto\n107\t            LEFT JOIN distr d ON d.prodotto  = p.prodotto\n108\t        \"\"\")\n109\t\n110\t        self._con.execute(f\"\"\"\n111\t            CREATE VIEW v_diritti AS\n112\t            SELECT\n113\t                CAST(prod AS VARCHAR) AS PROD,\n114\t                tipologia             AS TIPOLOGIA,\n115\t                scad                  AS SCAD,\n116\t                decr                  AS DECR,\n117\t                ragsoc_distr          AS DF_RAGSOC_DISTR\n118\t            FROM read_parquet('{dir_f}')\n119\t        \"\"\")\n120\t\n121\t        imdb_full_f = str(p / 'imdb_full.parquet').replace('\\\\', '/')\n122\t        if (p / 'imdb_full.parquet').exists():\n123\t            self._con.execute(f\"\"\"\n124\t                CREATE VIEW v_imdb_full AS\n125\t                SELECT *, DUR AS DURATA\n126\t                FROM read_parquet('{imdb_full_f}')\n127\t            \"\"\")\n128\t\n129\t        logger.info(f\"ParquetCatalog: VIEW pronte su {p}\")"}]},"uuid":"ad9071f0-d663-480c-8b84-60fb92de689c","timestamp":"2026-08-07T08:46:32.220Z","sourceToolAssistantUUID":"7cfff218-b867-4813-b110-82c928ee0624","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
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{"parentUuid":"48d4baa3-9efc-4c92-b24f-61a193b355da","isSidechain":true,"agentId":"a06c2ed5ce2ee13c3","message":{"model":"claude-sonnet-5","id":"msg_011Cdo6YcH6Hw33yb1UvRpXZ","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01SiwzAbGvstm2vJyFZKdMZG","name":"Bash","input":{"command":"grep -n \"GENERE\\|DUR\\b\\|DURATA\\|ATTORI\\|ATTORE\\|REGISTA\" /mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/grid_filler.py | head -60","description":"Search grid_filler for GENERE/DURATA/ATTORI mapping"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":2157,"cache_read_input_tokens":34118,"output_tokens":364,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":2157},"inference_geo":"not_available","iterations":[{"input_tokens":2,"output_tokens":364,"cache_read_input_tokens":34118,"cache_creation_input_tokens":2157,"cache_creation":{"ephemeral_5m_input_tokens":2157,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Cdo6YbYwGy82ftBCV1NXh","attributionAgent":"Explore","type":"assistant","uuid":"c4094ac1-6540-44b5-bbcf-99b59c42f6ed","timestamp":"2026-08-07T08:46:37.177Z","effort":"medium","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
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{"parentUuid":"43e573cc-4982-4c5f-a3fe-90572487e10d","isSidechain":true,"agentId":"a06c2ed5ce2ee13c3","message":{"model":"claude-sonnet-5","id":"msg_011Cdo6YyVo57VdZY5j9VFtH","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01PzgcrZop6AL21wTXF9p8Pk","name":"Bash","input":{"command":"grep -rn \"GENERE1\\|'DUR'\\|ATTORE1\\|ATTORE2\\|ATTORE3\\|REGISTA_COGN\\|REGISTA_NOME\" /mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src --include=*.py","description":"Find where anagrafica raw fields get remapped to display fields"},"caller":{"type":"direct"}}],"stop_reason":null,"stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":379,"cache_read_input_tokens":36275,"cache_creation":{"ephemeral_5m_input_tokens":379,"ephemeral_1h_input_tokens":0},"output_tokens":20,"service_tier":"standard","inference_geo":"not_available"},"diagnostics":null},"requestId":"req_011Cdo6YwzkUr64hqePZzx4w","attributionAgent":"Explore","type":"assistant","uuid":"4694f107-063b-4236-9f8a-9c2e1dca28f5","timestamp":"2026-08-07T08:46:41.355Z","effort":"medium","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
{"parentUuid":"4694f107-063b-4236-9f8a-9c2e1dca28f5","isSidechain":true,"promptId":"97d13177-e1fb-4157-b04b-8f8e5f00cef7","agentId":"a06c2ed5ce2ee13c3","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01PzgcrZop6AL21wTXF9p8Pk","type":"tool_result","content":"/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:463:                reg_c = self._safe(crow.get('REGISTA_COGN'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:464:                reg_n = self._safe(crow.get('REGISTA_NOME'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:468:                result['GENERE']  = self._safe(crow.get('GENERE1'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:470:                result['DURATA']  = self._safe(crow.get('DUR'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:538:                reg_c = self._safe(crow.get('REGISTA_COGN'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:539:                reg_n = self._safe(crow.get('REGISTA_NOME'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:543:                result['GENERE']  = self._safe(crow.get('GENERE1'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet_aggancio.py:545:                result['DURATA']  = self._safe(crow.get('DUR'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:54:                SELECT prodotto, cognome AS REGISTA_COGN, nome AS REGISTA_NOME\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:61:                       TRIM(COALESCE(nome, '') || ' ' || COALESCE(cognome, '')) AS ATTORE1\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:67:                       TRIM(COALESCE(nome, '') || ' ' || COALESCE(cognome, '')) AS ATTORE2\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:73:                       TRIM(COALESCE(nome, '') || ' ' || COALESCE(cognome, '')) AS ATTORE3\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:89:                p.genere1                   AS GENERE1,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:95:                r.REGISTA_COGN,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:96:                r.REGISTA_NOME,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:97:                a1.ATTORE1,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:98:                a2.ATTORE2,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:99:                a3.ATTORE3,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:204:                    f\"SELECT RIFER, TIPOL, \\\"TO\\\", TI, ANNO, REGISTA_COGN, REGISTA_NOME \"\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:205:                    f\"FROM v_custom_anagr WHERE REGISTA_COGN ILIKE '%{safe}%' LIMIT 999999\"\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/database/parquet_db.py:209:                    f\"SELECT RIFER, TIPOL, \\\"TO\\\", TI, ANNO, REGISTA_COGN, REGISTA_NOME \"\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:72:_COLS_ONAIR = ['TIPOL', 'TI', 'TO', 'ANNO', 'PAESE', 'GENERE1', 'GENERE2',\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:73:               'DUR', 'REGISTA', 'ATTORE 1', 'ATTORE 2', 'ATTORE 3']\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:126:    'GENERE1': 90, 'GENERE2': 90, 'DUR': 45,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:731:        regista = ' '.join(filter(None, [_s(data.get('REGISTA_COGN')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:732:                                         _s(data.get('REGISTA_NOME'))]))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:740:            COL_GENERE:  _s(data.get('GENERE1')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:742:            COL_DUR:     _s(data.get('DUR')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:744:            COL_ATT1:    _s(data.get('ATTORE1')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:745:            COL_ATT2:    _s(data.get('ATTORE2')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/prossime_uscite_sheet.py:746:            COL_ATT3:    _s(data.get('ATTORE3')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:331:        tbl.setHorizontalHeaderLabels(['ED', 'TIPOL', 'DUR', 'V.M.'])\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:345:            for col_idx, key in enumerate(('ED', 'TIPOL', 'DUR', 'VM')):\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:794:                    SELECT prodotto, cognome AS REGISTA_COGN, nome AS REGISTA_NOME\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:799:                a1 AS (SELECT prodotto, TRIM(COALESCE(nome,'') || ' ' || COALESCE(cognome,'')) AS ATTORE1\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:801:                a2 AS (SELECT prodotto, TRIM(COALESCE(nome,'') || ' ' || COALESCE(cognome,'')) AS ATTORE2\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:803:                a3 AS (SELECT prodotto, TRIM(COALESCE(nome,'') || ' ' || COALESCE(cognome,'')) AS ATTORE3\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:812:                    p.genere1                    AS GENERE1,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:818:                    r.REGISTA_COGN, r.REGISTA_NOME,\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:819:                    a1.ATTORE1, a2.ATTORE2, a3.ATTORE3\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:901:                    reg_c = _s(crow.get('REGISTA_COGN'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:902:                    reg_n = _s(crow.get('REGISTA_NOME'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:906:                    result['GENERE']  = _s(crow.get('GENERE1'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:908:                    result['DURATA']  = _s(crow.get('DUR'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:911:                    result['ATTORI']  = ', '.join(filter(None, [_s(crow.get('ATTORE1')), _s(crow.get('ATTORE2')), _s(crow.get('ATTORE3'))]))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:2208:                reg_c = self._safe(crow.get('REGISTA_COGN'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:2209:                reg_n = self._safe(crow.get('REGISTA_NOME'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:2224:                    'GENERE':       self._safe(crow.get('GENERE1')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/linker_sheet.py:2226:                    'DURATA':       self._safe(crow.get('DUR')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/search_dialog.py:284:                reg_c = str(row.get('REGISTA_COGN', '') or '')\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/search_dialog.py:285:                reg_n = str(row.get('REGISTA_NOME', '') or '')\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1855:                _set(self.table, row_idx, COL_GENERE,    gf_safe(merged.get('GENERE1')))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1857:                _set(self.table, row_idx, COL_DURATA,    gf_fmt_num(merged.get('DUR')))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1861:                    gf_safe(merged.get('REGISTA_COGN')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1862:                    gf_safe(merged.get('REGISTA_NOME')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1866:                    gf_safe(merged.get('ATTORE1')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1867:                    gf_safe(merged.get('ATTORE2')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1868:                    gf_safe(merged.get('ATTORE3')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/ott_sheet.py:1878:                _set(self.table, row_idx, COL_DURATA,    gf_fmt_num(imdb_data.get('DUR')))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/engine/linker_engine.py:319:        reg_cogn = self._safe_str(row.get('REGISTA_COGN'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/engine/linker_engine.py:320:        reg_nome = self._safe_str(row.get('REGISTA_NOME'))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/engine/linker_engine.py:332:            'GENERE': self._safe_str(row.get('GENERE1')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/engine/linker_engine.py:334:            'DURATA': self._safe_str(row.get('DUR')),\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/diritti_tab.py:261:    'GENERE':       'GENERE1',\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/diritti_tab.py:263:    'DURATA':       'DUR',\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/diritti_tab.py:266:    'REGISTA':      None,   # REGISTA_COGN + REGISTA_NOME\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/diritti_tab.py:267:    'ATTORI':       None,   # ATTORE1+2+3\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/diritti_tab.py:1200:            cogn = gf_safe(row.get('REGISTA_COGN', ''))\n/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/src/gui/diritti_tab.py:1201:            nome = gf_safe(row.get('REGISTA_NOME', ''))","is_error":false}]},"uuid":"299c577a-8a00-4118-aa0d-5cb6b413d4b4","timestamp":"2026-08-07T08:46:41.403Z","sourceToolAssistantUUID":"4694f107-063b-4236-9f8a-9c2e1dca28f5","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}
{"parentUuid":"299c577a-8a00-4118-aa0d-5cb6b413d4b4","isSidechain":true,"agentId":"a06c2ed5ce2ee13c3","message":{"model":"claude-sonnet-5","id":"msg_011Cdo6ZHKMBVcjJP9ZfufzV","type":"message","role":"assistant","content":[{"type":"text","text":"Ho un quadro completo. Rispondo in italiano.\n\n## Risultato ricerca\n\n**Modulo:** `/mnt/ssd/data/Dropbox/adrian/PYTHON/MyICR_Suite/app/modules/linker/`\n\n**File chiave con definizione dei campi:**\n1. `src/gui/column_defs.py` — dizionario `FIELDS`, fonte unica di verità per label/colore/larghezza di tutte le colonne mostrate nei fogli Linker (usato da `ott_sheet.py`, `linker_sheet.py`, `diritti_tab.py`, ecc.)\n2. `src/database/parquet_db.py` — query SQL (DuckDB) `v_custom_anagr` che produce i campi anagrafici a partire dai parquet sorgente\n3. `src/gui/linker_sheet.py`, `src/gui/ott_sheet.py`, `src/gui/diritti_tab.py`, `src/engine/linker_engine.py` — punti dove i campi grezzi della view vengono rimappati sulle chiavi anagrafiche esposte nella griglia\n\n### Elenco campi anagrafici (sezione \"Anagrafica / ONAIR\")\nDa `column_defs.py:43-56` (dict `FIELDS`), colore header `HC.ORANGE` (tranne IMDB in `HC.IMDB`):\n\n| key (colonna griglia) | label | width | riga |\n|---|---|---|---|\n| `RIFER` | RIFER | 61 | column_defs.py:43 |\n| `IMDB` | IMDB | 61 | column_defs.py:44 |\n| `TIPOL` | TIPOL | 75 | column_defs.py:45 |\n| `TI` | TI (titolo italiano) | 200 | column_defs.py:46 |\n| `TO` | TO (titolo originale) | 200 | column_defs.py:47 |\n| `ANNO` | ANNO | 61 | column_defs.py:48 |\n| `PAESE` | PAESE | 61 | column_defs.py:49 |\n| `GENERE` | GENERE | 100 | column_defs.py:50 |\n| `EPIS` | EPIS | 47 | column_defs.py:51 |\n| `DURATA` | DURATA | 60 | column_defs.py:52 |\n| `SUPERSERIE` | SUPERSERIE | 110 | column_defs.py:53 |\n| `VEG_FREE` | VEG | 40 | column_defs.py:54 |\n| `REGISTA` | REGISTA | 131 | column_defs.py:55 |\n| `ATTORI` | ATTORI | 131 | column_defs.py:56 |\n\nLe altre sezioni del dict `FIELDS` (Diritti, Emesso generaliste, Emesso tematiche, Box Office, Valutazioni Gemma) iniziano da `column_defs.py:59` in poi e sono esplicitamente separate dall'anagrafica.\n\n### Origine dati e mapping esatto\nLa view DuckDB `v_custom_anagr` (`src/database/parquet_db.py:40-108`) è la fonte che alimenta questi campi, joinando quattro parquet di DataHub_v2:\n\n- `prodotti.parquet` → `RIFER`(=prodotto), `TIPOL`(=tipologia), `TO`(=titolo_originale), `TI`(=titolo_italiano), `ANNO`(=anno_produzione), `PAESE`(=paesi_produzione1), `GENERE1`(=genere1), `EPIS`(=num_episodi), `DUR`(=durata), `SUPERSERIE`(=superserie_descr), `VEG_FREE`(=veg, con remap \"EVER GREEN\"→\"EV.GR\")\n- `imdb.parquet` → `IMDB_CODICE`(=riferimento_imdb, MIN per codice)\n- `cast.parquet` → `REGISTA_COGN`/`REGISTA_NOME` (ruolo='FRE'), `ATTORE1`/`ATTORE2`/`ATTORE3` (ruolo='C001', progr_cast 1/2/3)\n- `diritti.parquet` → `DF_RAGSOC_DISTR` (non anagrafico, usato altrove)\n\nNota importante: i nomi delle colonne nella view grezza NON coincidono sempre 1:1 con le key di `column_defs.py`. Il rimapping avviene nel codice chiamante, es. in `src/gui/linker_sheet.py:906-911`:\n```\nresult['GENERE']  = _s(crow.get('GENERE1'))\nresult['DURATA']  = _s(crow.get('DUR'))\nresult['ATTORI']  = ', '.join(filter(None, [_s(crow.get('ATTORE1')), _s(crow.get('ATTORE2')), _s(crow.get('ATTORE3'))]))\n```\ne `REGISTA` è la concatenazione di `REGISTA_COGN` + `REGISTA_NOME` (stesso file, righe 901-902 circa). Lo stesso pattern si ripete identico in `src/gui/ott_sheet.py:1855-1868`, `src/engine/linker_engine.py:319-334`, `src/gui/linker_sheet_aggancio.py:463-470/538-545`, e nella mappa di corrispondenza colonne di `src/gui/diritti_tab.py:261-267` (`'GENERE': 'GENERE1'`, `'DURATA': 'DUR'`, `'REGISTA': None  # REGISTA_COGN + REGISTA_NOME`, `'ATTORI': None  # ATTORE1+2+3`).\n\n### Riepilogo\n- **File \"fonte unica di verità\" per le colonne visualizzate:** `app/modules/linker/src/gui/column_defs.py` (righe 40-110, dict `FIELDS`)\n- **Campi anagrafici esatti (key colonna griglia):** `RIFER, IMDB, TIPOL, TI, TO, ANNO, PAESE, GENERE, EPIS, DURATA, SUPERSERIE, VEG_FREE, REGISTA, ATTORI`\n- **Sorgente SQL/parquet:** view `v_custom_anagr` in `app/modules/linker/src/database/parquet_db.py:41-108`, che legge `prodotti.parquet`, `imdb.parquet`, `cast.parquet` (e `diritti.parquet` per `DF_RAGSOC_DISTR`) da `DataHub_v2/parquet/`\n- Colore intestazione: arancione `HC.ORANGE` (`#FFB347`) per tutti tranne `IMDB` che ha colore dedicato `HC.IMDB` (`#00BFFF`)"}],"stop_reason":"end_turn","stop_sequence":null,"stop_details":null,"usage":{"input_tokens":2,"cache_creation_input_tokens":6602,"cache_read_input_tokens":36654,"output_tokens":2316,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":6602},"inference_geo":"not_available","iterations":[{"input_tokens":2,"output_tokens":2316,"cache_read_input_tokens":36654,"cache_creation_input_tokens":6602,"cache_creation":{"ephemeral_5m_input_tokens":6602,"ephemeral_1h_input_tokens":0},"type":"message"}],"speed":"standard"},"diagnostics":null},"requestId":"req_011Cdo6ZG9uKFPM8CtnVMx2x","attributionAgent":"Explore","type":"assistant","uuid":"8f2d2e4d-59c8-467e-9d88-cb312f2c3be3","timestamp":"2026-08-07T08:47:02.245Z","effort":"medium","userType":"external","entrypoint":"claude-vscode","cwd":"/mnt/ssd/data/Dropbox/adrian","sessionId":"6291f451-faa1-400b-9478-3e3eee223c48","version":"2.1.221","gitBranch":"master"}