feat: Add ScraperV1Adapter and real data pipeline test
- Add ScraperV1Adapter to transform scraped reviews into pipeline format - Handles relative timestamps (centerDate) - Generates deterministic IDs for DOM-sourced reviews - Filters out empty (rating-only) reviews - Add sample barbershop reviews (79 reviews, 46 with text) - Real data from Las Palmas barbershop - Multi-language: Spanish, English, German, Norwegian, Italian - Add test_pipeline_real_data.py for E2E testing with real data - Uses mock classifier based on keywords and rating - Full pipeline flow: raw -> enriched -> spans -> issues -> facts Test results with real data: - 46 reviews processed - 6 languages detected (es: 35, en: 7, de: 1, no: 1, it: 1, ca: 1) - 3 issues identified from negative reviews - 29 fact records aggregated across date range 2017-2025 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Alejandro Gutiérrez
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data/samples/barbershop_reviews.json
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data/samples/barbershop_reviews.json
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[
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{
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"text": "",
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"author": "Andy Cabrera Ramírez",
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"rating": 5,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT2toMWNrZDFZbGcxZVZKNGVtMWFaR2t0TTIxVE5FRRAB",
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"timestamp": "a month ago",
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"minDate": "2025-11-26T18:31:09.843Z",
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"maxDate": "2025-12-25T18:31:09.843Z",
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"centerDate": "2025-12-11T06:31:09.843Z"
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},
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{
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"text": "El mejor servicio, el mejor trato y profesionalidad.",
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"author": "Patrick Scherschinski Luca de Tena",
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"rating": 5,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT2pCRU5GcGFZVXN6Y0VWWlozUTJRMnN5V0MxZlIyYxAB",
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"timestamp": "2 months ago",
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"minDate": "2025-10-27T18:31:09.843Z",
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"maxDate": "2025-11-25T18:31:09.843Z",
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"centerDate": "2025-11-11T06:31:09.843Z"
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},
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{
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"text": "De profesionales nada.a mi me dejaron fatal.no es solo pedir disculpas,por lo menos me hubiesen ofrecido arreglarme el desastre que me hicieron.no vuelvo mas a esta peluqueria.",
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"author": "Francisco javier Rodriguez limones",
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"rating": 1,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT25WMVVHRjVhVWQ1Um04M1VHWklYMjU1Ym5wMFpGRRAB",
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"timestamp": "2 months ago",
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"minDate": "2025-10-27T18:31:09.843Z",
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"maxDate": "2025-11-25T18:31:09.843Z",
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"centerDate": "2025-11-11T06:31:09.843Z"
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},
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{
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"text": "La primera vez que boy a esta peluqueria porque me la recomendaron y me dejaron fatal.",
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"author": "ECEM HOGAR",
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"rating": 1,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT25OTVFpMWxMV3BYYVVWZmVIWjBNbFZhWkdwaFJtYxAB",
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"timestamp": "Edited 2 months ago",
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"minDate": "2025-10-27T18:31:09.843Z",
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"maxDate": "2025-11-25T18:31:09.843Z",
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"centerDate": "2025-11-11T06:31:09.843Z"
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},
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{
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"text": "",
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"author": "Adrián Santana García",
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"rating": 5,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT21GR2NIUjFRbUk0WWs1Nk1Yb3lXWGRpYkVSVGNrRRAB",
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"timestamp": "3 months ago",
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"minDate": "2025-09-27T18:31:09.843Z",
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"maxDate": "2025-10-26T18:31:09.843Z",
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"centerDate": "2025-10-12T06:31:09.843Z"
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},
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{
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"text": "Rafa es mi nuevo referente en el sector. Atención profesional y dedicada por alguien con muchísima experiencia en este campo. Cortes modernos o clásicos, barba perfecta. 10/10",
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"author": "Alex Q.",
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"rating": 5,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT214TGMwRnhlR3BMZWxGUFJqTldkbEY2V0ZocmJGRRAB",
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"timestamp": "3 months ago",
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"minDate": "2025-09-27T18:31:09.843Z",
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"maxDate": "2025-10-26T18:31:09.843Z",
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"centerDate": "2025-10-12T06:31:09.843Z"
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},
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{
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"text": "Super mala la atención! No tienen buenos modales y mal educados en su totalidad jamas volveria! Quieres pasarla mal este es el sitio indicado",
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"author": "SoyWilliams",
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"rating": 1,
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"source": "api",
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"review_id": "Ci9DQUlRQUNvZENodHljRjlvT2xOTGVEaEZjV2R4Y2toMGF5MVVXUzFSYkdRMk1XYxAB",
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"timestamp": "5 months ago",
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"minDate": "2025-07-29T18:31:09.843Z",
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"maxDate": "2025-08-27T18:31:09.843Z",
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"centerDate": "2025-08-13T06:31:09.843Z"
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},
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{
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"text": "Se trata de una peluquería excepcional; profesionalidad y buen hacer en cada corte de pelo, no importa si te gusta más clásico o más moderno, siempre se da buen resultado.",
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"author": "Quique Con Q",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VMTE1oZG51MktiX3dnRRAB",
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"timestamp": "7 months ago",
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"minDate": "2025-05-30T18:31:09.843Z",
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"maxDate": "2025-06-28T18:31:09.843Z",
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"centerDate": "2025-06-14T06:31:09.843Z"
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},
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{
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"text": "Una Peluquería Profesional. Los Hermanos Fleitas Nunca Fallan.\nSiempre Obran El Milagro.\nBuenas Tertulias De Lo Divino y De Lo Humano.",
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"author": "JOSE MANUEL MORENO CASTAÑO",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VJQ0FnSURKb05ITWtnRRAB",
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"timestamp": "Edited 8 months ago",
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"minDate": "2025-04-30T18:31:09.843Z",
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"maxDate": "2025-05-29T18:31:09.843Z",
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"centerDate": "2025-05-15T06:31:09.843Z"
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},
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{
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"text": "Increíble trato, excelente servicio y muy rapido",
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"author": "Jaime Jesús García Mendoza",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VJQ0FnTURJOUpyY3J3RRAB",
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"timestamp": "9 months ago",
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"minDate": "2025-03-31T18:31:09.843Z",
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"maxDate": "2025-04-29T18:31:09.843Z",
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"centerDate": "2025-04-15T06:31:09.843Z"
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},
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{
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"text": "Fui por las reseñas de otros usuarios y estoy completamente de acuerdo, muy buen hacer… corte de pelo a tijera, nada de máquinas y rapados, he quedado muy satisfecho con mi corte de pelo, por supuesto volveré y lo recomiendo a todos ☺️",
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"author": "Jose Gerardo",
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"rating": 5,
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"source": "api",
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"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNyM29MSU9nEAE",
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"timestamp": "Edited 10 months ago",
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"minDate": "2025-03-01T18:31:09.843Z",
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"maxDate": "2025-03-30T18:31:09.843Z",
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"centerDate": "2025-03-16T06:31:09.843Z"
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},
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{
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"text": "Super Friseur, schönes Ambiente. Ich habe mir Haare und Bart schneiden lassen – beides TOP. Kann ich zu 100% Empfehlen! Ich komme definitiv wieder.",
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"author": "B F",
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"rating": 5,
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"source": "api",
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"review_id": "ChZDSUhNMG9nS0VJQ0FnTUNRdDd5QVBnEAE",
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"timestamp": "10 months ago",
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"minDate": "2025-03-01T18:31:09.843Z",
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"maxDate": "2025-03-30T18:31:09.843Z",
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"centerDate": "2025-03-16T06:31:09.843Z"
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},
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{
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"text": "",
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"author": "cristopher munizaga",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VJQ0FnTURBbkphVjdBRRAB",
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"timestamp": "11 months ago",
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"minDate": "2025-01-30T18:31:09.843Z",
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"maxDate": "2025-02-28T18:31:09.843Z",
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"centerDate": "2025-02-14T06:31:09.843Z"
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},
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{
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"text": "Profesjonell, bra pris, hyggelig! Anbefales på det sterkeste ✂️",
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"author": "Stian Øvstebø",
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"rating": 5,
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"source": "api",
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"review_id": "ChZDSUhNMG9nS0VJQ0FnSURfbm8yLVR3EAE",
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"timestamp": "a year ago",
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"minDate": "2024-01-26T18:31:09.843Z",
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"maxDate": "2025-01-24T18:31:09.843Z",
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"centerDate": "2024-07-26T18:31:09.843Z"
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},
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{
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"text": "El trato de Rafael es inmejorable siempre con una sonrisa y buena predisposición. Muy buen barbero, siempre dispuesto a recomendarte o mejorar la idea que tengas en mente. He ido a muchas barberías pero como esta ninguna. Gracias Rafael",
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"author": "David Rodríguez",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VJQ0FnSURleG9ENnJRRRAB",
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"timestamp": "Edited a year ago",
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"minDate": "2024-01-26T18:31:09.843Z",
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"maxDate": "2025-01-24T18:31:09.843Z",
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"centerDate": "2024-07-26T18:31:09.843Z"
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},
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{
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"text": "",
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"author": "Derians Jose Diaz",
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"rating": 5,
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"source": "api",
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"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNyb2FhcUxnEAE",
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"timestamp": "a year ago",
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"minDate": "2024-01-26T18:31:09.843Z",
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"maxDate": "2025-01-24T18:31:09.843Z",
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"centerDate": "2024-07-26T18:31:09.843Z"
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},
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{
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"text": "Profesionales de trato muy amable y cercano.\nSin duda alguna la mejor barbería de la zona.",
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"author": "Daniel PM",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VJQ0FnSUR4MU0zd3h3RRAB",
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"timestamp": "Edited a year ago",
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"minDate": "2024-01-26T18:31:09.843Z",
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"maxDate": "2025-01-24T18:31:09.843Z",
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"centerDate": "2024-07-26T18:31:09.843Z"
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},
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{
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"text": "El mejor sitio de Gran Canaria para pelarse sin duda, grandes profesionales.",
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"author": "Juan Mora",
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"rating": 5,
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"source": "api",
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"review_id": "ChZDSUhNMG9nS0VJQ0FnSUN6akxieFFBEAE",
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"timestamp": "a year ago",
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"minDate": "2024-01-26T18:31:09.843Z",
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"maxDate": "2025-01-24T18:31:09.843Z",
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"centerDate": "2024-07-26T18:31:09.843Z"
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},
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{
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"text": "professionale! precisione! brava! molto consigliato!\n\nprofessional! accurate! well done! highly recommended!\n\n¡profesional! ¡preciso! ¡bien hecho! ¡muy recomendable!",
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"author": "Alessandro “L” Sandri",
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"rating": 5,
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"source": "api",
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"review_id": "ChZDSUhNMG9nS0VJQ0FnSURONy1QeEJBEAE",
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"timestamp": "a year ago",
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"minDate": "2024-01-26T18:31:09.843Z",
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"maxDate": "2025-01-24T18:31:09.843Z",
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"centerDate": "2024-07-26T18:31:09.843Z"
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},
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{
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"text": "",
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"author": "Adrian Nuez Sosa",
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"rating": 5,
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"source": "api",
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"review_id": "ChdDSUhNMG9nS0VJQ0FnSUMxeHRQRHZ3RRAB",
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"timestamp": "2 years ago",
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"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "",
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"author": "Ancor Santana Martín",
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"rating": 5,
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"source": "dom",
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"timestamp": "2 years ago",
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"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "Excellent service from a professional who loves his job.",
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"author": "Pepe",
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"rating": 5,
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"source": "dom",
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"timestamp": "2 years ago",
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"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "Spectacular, art is what it has",
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"author": "Cristobal Ceballos vega",
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"rating": 5,
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"source": "dom",
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"timestamp": "2 years ago",
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|
"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "Professional, fast. Good price! Recommended.",
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"author": "Flavio",
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"rating": 5,
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"source": "dom",
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"timestamp": "2 years ago",
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"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "I came here after getting a haircut elsewhere that I wasn't happy with. They did an amazing job fixing it and refused to take my money when I tried to pay. Complete class act, would highly recommend and will be back when I stay in Las Palmas again",
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"author": "Ian Hannon",
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"rating": 5,
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"source": "dom",
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|
"timestamp": "2 years ago",
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"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "",
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"author": "Monica Campos Guerra",
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"rating": 5,
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"source": "dom",
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"timestamp": "2 years ago",
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|
"minDate": "2023-01-26T18:31:09.843Z",
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"maxDate": "2024-01-25T18:31:09.843Z",
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"centerDate": "2023-07-27T18:31:09.843Z"
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},
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{
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"text": "",
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"author": "Alfredo Rodriguez",
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"rating": 5,
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"source": "dom",
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||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Jesus Tanausu Gonzalez Gonzalez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "dom",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "I will definitely be back again. Raul is amazing.",
|
||||||
|
"author": "Paul Bechtold",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "dom",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Pablo Yanez Ortega",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "dom",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Muy buena peluquería, trato de 10 te hacen sentir como en casa desde que entras por la puerta",
|
||||||
|
"author": "Alejandro Tavio",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUR4enJPbjR3RRAB",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Judit Nolasco",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR4bHB1S0ZnEAE",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Manuel Moranchel",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR4LU1hZEl3EAE",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Mejor barber en Las Palmas. No veo la hora de volver de Croacia para cortarme el pelo.\nRecomiendo👍",
|
||||||
|
"author": "Dražen Zavoreo",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR4Z05YMUVREAE",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Rui Rego Soares",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUN4azllVHJnRRAB",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Marc Sherwood",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUN4eU16b0p3EAE",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Malísimo",
|
||||||
|
"author": "Iker Gomez",
|
||||||
|
"rating": 1,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNSeXVHeFhBEAE",
|
||||||
|
"timestamp": "2 years ago",
|
||||||
|
"minDate": "2023-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2024-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2023-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Peluquería de 10: me corté el pelo con Raúl y tuve todo el rato la sensación de estar con un gran profesional: minucioso, ocupado en conseguir lo que le pedí y un trato excelente. Y el precio desde luego es bajo por tan buen servicio. TOP",
|
||||||
|
"author": "Salvador Bosch",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNCb2VXaXRnRRAB",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Buen servicio",
|
||||||
|
"author": "Noelia Lopez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNCZ2NDWmJREAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "La primera vez que vengo, soy de Barcelona. Me han tratado muy bien, el corte muy fino muy bien 👌🏽 ambiente muy amistoso y agradable, precio recomiendo!",
|
||||||
|
"author": "Bohdan Savchenko",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUQtcWRlbnV3RRAB",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "ANGEL RODRIGUEZ",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUMtXzlIakpBEAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "La verdad es que estoy muy contento con el equipo de hermanos de esta peluquería. Están cualificados, responden cualquier duda y te tratan de forma muy profesional. Además no te intentan vender nada, simplemente te recomiendan productos para la mejora de tu salud capilar. Volveré encantado.",
|
||||||
|
"author": "Adrián Rodríguez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUMtNDU2UWVBEAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "La mejor barbería de la zona de guanarteme",
|
||||||
|
"author": "C Cdrs",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUMteVotMmpRRRAB",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Marco Santana Alonso",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNldktXVUlBEAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Profesional por Excelencia !!!\ny ciertamente gran conversador ,recomendable !!",
|
||||||
|
"author": "JOSÈ RODRIGUEZ",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR1bm96QmVREAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Fui de casualidad, por que no resido en las Palmas, y fue un acierto.\nMuy buen trato, y muy profesionales.\nSi viviera aquí, sin duda ya tendría peluquería donde ir.",
|
||||||
|
"author": "Daniel P. G.",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUR1eEtTSDR3RRAB",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Increíbles, atencion, trabajo perfecto, unos crack, Rafitaaaaa Un artista con esas manos te deja perfecto",
|
||||||
|
"author": "Eduardo Rodriguez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUN1X1B2MFpBEAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Sara Elizondo Santana",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUQyaE9fSkJnEAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Idafen Santana Pérez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSURXMWZQeGNREAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Desde la primera vez que vine a R. Feitas peluquería no me he arrepentido de estar ausente ahí cuando quiero tener un corte preciso, bonito y elegante, de la mano de Rafa. Me ha entregado un servicio y atención excepcional, digno de volver. Desde que entras hasta que sales puedes hablar y disfrutar de él humor, carisma o sentido del peluquero que te esté tratando. He aprendido mucho sentado en una silla junto a Rafa y he disfrutado de muchos momentos alegres. Y le sumas el resultado del arte que tiene Rafa ñara dejarte estilisticamente el pelo, como dije antes, \"preciso y bonito\". Recordarles. ⭐️⭐️⭐️⭐️⭐️",
|
||||||
|
"author": "Eli Lopez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNXOHNTTFp3EAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Leonardo Romeo",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSURtM3NqSGNREAE",
|
||||||
|
"timestamp": "3 years ago",
|
||||||
|
"minDate": "2022-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2023-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2022-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Good masters working there! David is simple a rockstar 🙌",
|
||||||
|
"author": "Ievgen Chernenko",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNtelp6NUFREAE",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Great service",
|
||||||
|
"author": "Markus Kramer",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNtaExqRld3EAE",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Rubén Cabrera",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUQ2N19ha1JREAE",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Jesus Rb",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNhNW82ejRRRRAB",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "jose manuel caamaño pais",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNxaTV1RzlnRRAB",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Buen trato",
|
||||||
|
"author": "Jordi Antonell Bladé",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNLemZET2xBRRAB",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Te hacen sentir muy cómodo y buenos profesionales",
|
||||||
|
"author": "Ignacio Santana Rodríguez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSURTdXRyNTZnRRAB",
|
||||||
|
"timestamp": "Edited 4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Ayoze Lopez ROMERO",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNLMElfbTBnRRAB",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Abel Redondo Santana",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR5aHUzQ1VnEAE",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Jonay Fuentes",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR5dXRpYkxnEAE",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "BLAS MANUEL GARCIA PEREZ",
|
||||||
|
"rating": 4,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUR5X01YTGRREAE",
|
||||||
|
"timestamp": "4 years ago",
|
||||||
|
"minDate": "2021-01-26T18:31:09.843Z",
|
||||||
|
"maxDate": "2022-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2021-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Santiago Ruiz",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNTa05hTUZREAE",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Rafael. Muy buen barbero. Profesional y buen talante.",
|
||||||
|
"author": "The Garden Lanzarote. Profesionales de jardinería.",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSURpM09UVWhBRRAB",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "La mejor peluquería de la ciudad 👌🏽",
|
||||||
|
"author": "Adrián Pérez Roger",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNpbXZlbl9RRRAB",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "No te puedes morir sin ir antes 💈✨",
|
||||||
|
"author": "Camilo",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSURDdktLalVnEAE",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Pequeño ,pero acojedor, buen profecional y muy cercano al cliente , Rafa eres un encanto como profecional y como persona, gracias nos volveremos ha ver,",
|
||||||
|
"author": "Paco Hornero",
|
||||||
|
"rating": 4,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUM4OHFTQ05nEAE",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Muy amables, profesional, cliente para toda la vida.",
|
||||||
|
"author": "Itaca",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSURjbF9pWnJnRRAB",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Esta peluquería es la mejor en la que he estado,simplemente tienen un servicio impecable,sus trabajadores tienen una profesionalidad del 100 %, magnífico.",
|
||||||
|
"author": "Guillermo Cedrés",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSURzcnBmZTlRRRAB",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Gabriel R. Castillo",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUNzcS1iazhRRRAB",
|
||||||
|
"timestamp": "5 years ago",
|
||||||
|
"minDate": "2020-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2021-01-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2020-07-27T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Poco que decir de este gran nuevo negocio llevado por una gente excepcional. Un trato muy a la altura de los gustos más exigentes. Y una calidad de trabajo que en pocos lugares de Las Palmas se podrá encontrar",
|
||||||
|
"author": "Nestor Lobato",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSUQwOU9HQzJnRRAB",
|
||||||
|
"timestamp": "6 years ago",
|
||||||
|
"minDate": "2019-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2020-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2019-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "alberto hernandez rodriguez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUMwaVBYWENREAE",
|
||||||
|
"timestamp": "6 years ago",
|
||||||
|
"minDate": "2019-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2020-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2019-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Airam Sánchez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSURVcTVhSUpBEAE",
|
||||||
|
"timestamp": "6 years ago",
|
||||||
|
"minDate": "2019-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2020-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2019-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Sin duda la mejor barbería de Las Palmas. Llevo arreglandome la barba unos 3 años y Rafael tiene unas manos de oro. Muy profesional y un trato exquisito. Comentar que usa unos productos de primera categoría. Un acierto haber ido hace tiempo a probar y quedarme como cliente para siempre. Un saludo Rafa!!!",
|
||||||
|
"author": "Ero Martinez Garcia",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSURVbnJTazd3RRAB",
|
||||||
|
"timestamp": "6 years ago",
|
||||||
|
"minDate": "2019-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2020-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2019-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Alfonzo Arteaga",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNZb3R6aFZnEAE",
|
||||||
|
"timestamp": "6 years ago",
|
||||||
|
"minDate": "2019-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2020-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2019-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Peluqueros muy trabajadore",
|
||||||
|
"author": "FernanGamer HDModzz",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChdDSUhNMG9nS0VJQ0FnSURvbnEtTnF3RRAB",
|
||||||
|
"timestamp": "6 years ago",
|
||||||
|
"minDate": "2019-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2020-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2019-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Goretti Cabrera Suárez",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUNJcklYV0p3EAE",
|
||||||
|
"timestamp": "7 years ago",
|
||||||
|
"minDate": "2018-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2019-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2018-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "",
|
||||||
|
"author": "Jose Ignacio Zaballos",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSURBeXR2b0tnEAE",
|
||||||
|
"timestamp": "7 years ago",
|
||||||
|
"minDate": "2018-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2019-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2018-07-28T18:31:09.843Z"
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"text": "Probablemente el mejor barbero / peluquero de la ciudad. Exquisito en el trato con los clientes, minucioso y perfeccionista en sus trabajos. Recomendable 100% pedir cita previa dada la demanda.",
|
||||||
|
"author": "Daniel Medina Claesson",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api",
|
||||||
|
"review_id": "ChZDSUhNMG9nS0VJQ0FnSUN3MXE2dVFBEAE",
|
||||||
|
"timestamp": "8 years ago",
|
||||||
|
"minDate": "2017-01-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2018-01-26T18:31:09.843Z",
|
||||||
|
"centerDate": "2017-07-28T18:31:09.843Z"
|
||||||
|
}
|
||||||
|
]
|
||||||
@@ -0,0 +1,5 @@
|
|||||||
|
"""Ingestion adapters for various review data formats."""
|
||||||
|
|
||||||
|
from reviewiq_pipeline.adapters.scraper_v1 import ScraperV1Adapter
|
||||||
|
|
||||||
|
__all__ = ["ScraperV1Adapter"]
|
||||||
@@ -0,0 +1,242 @@
|
|||||||
|
"""
|
||||||
|
Adapter for Scraper V1 output format.
|
||||||
|
|
||||||
|
This adapter transforms the raw scraped review format into the pipeline's
|
||||||
|
expected RawReview format for Stage 1 processing.
|
||||||
|
|
||||||
|
Input format (from scraper):
|
||||||
|
{
|
||||||
|
"text": "Review text...",
|
||||||
|
"author": "Author Name",
|
||||||
|
"rating": 5,
|
||||||
|
"source": "api" | "dom",
|
||||||
|
"review_id": "ABC123...", # Optional for DOM-sourced
|
||||||
|
"timestamp": "2 months ago",
|
||||||
|
"minDate": "2025-10-27T18:31:09.843Z",
|
||||||
|
"maxDate": "2025-11-25T18:31:09.843Z",
|
||||||
|
"centerDate": "2025-11-11T06:31:09.843Z"
|
||||||
|
}
|
||||||
|
|
||||||
|
Output format (for pipeline):
|
||||||
|
{
|
||||||
|
"review_id": "ABC123...",
|
||||||
|
"text": "Review text...",
|
||||||
|
"rating": 5,
|
||||||
|
"author_name": "Author Name",
|
||||||
|
"author_id": None,
|
||||||
|
"review_time": "2025-11-11T06:31:09.843Z",
|
||||||
|
"relative_time": "2 months ago",
|
||||||
|
"raw_payload": {...} # Original data
|
||||||
|
}
|
||||||
|
"""
|
||||||
|
|
||||||
|
from __future__ import annotations
|
||||||
|
|
||||||
|
import hashlib
|
||||||
|
import logging
|
||||||
|
from datetime import datetime, timezone
|
||||||
|
from typing import Any
|
||||||
|
from uuid import uuid4
|
||||||
|
|
||||||
|
logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
|
|
||||||
|
class ScraperV1Adapter:
|
||||||
|
"""
|
||||||
|
Adapter to transform Scraper V1 output into pipeline-compatible format.
|
||||||
|
|
||||||
|
The scraper produces reviews with relative timestamps ("2 months ago") and
|
||||||
|
estimated date ranges. This adapter normalizes them into absolute timestamps
|
||||||
|
using the centerDate field.
|
||||||
|
"""
|
||||||
|
|
||||||
|
def __init__(
|
||||||
|
self,
|
||||||
|
business_id: str,
|
||||||
|
place_id: str,
|
||||||
|
source: str = "google",
|
||||||
|
):
|
||||||
|
"""
|
||||||
|
Initialize the adapter.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
business_id: Business identifier for the reviews
|
||||||
|
place_id: Google Maps place ID
|
||||||
|
source: Review source platform (default: "google")
|
||||||
|
"""
|
||||||
|
self.business_id = business_id
|
||||||
|
self.place_id = place_id
|
||||||
|
self.source = source
|
||||||
|
self._seen_ids: set[str] = set()
|
||||||
|
|
||||||
|
def transform(self, scraped_reviews: list[dict[str, Any]]) -> list[dict[str, Any]]:
|
||||||
|
"""
|
||||||
|
Transform a list of scraped reviews into pipeline format.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
scraped_reviews: List of reviews from scraper output
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
List of reviews in pipeline RawReview format
|
||||||
|
"""
|
||||||
|
transformed = []
|
||||||
|
skipped_empty = 0
|
||||||
|
skipped_duplicate = 0
|
||||||
|
|
||||||
|
for review in scraped_reviews:
|
||||||
|
result = self.transform_single(review)
|
||||||
|
|
||||||
|
if result is None:
|
||||||
|
skipped_empty += 1
|
||||||
|
continue
|
||||||
|
|
||||||
|
if result["review_id"] in self._seen_ids:
|
||||||
|
skipped_duplicate += 1
|
||||||
|
continue
|
||||||
|
|
||||||
|
self._seen_ids.add(result["review_id"])
|
||||||
|
transformed.append(result)
|
||||||
|
|
||||||
|
logger.info(
|
||||||
|
f"Transformed {len(transformed)} reviews "
|
||||||
|
f"(skipped {skipped_empty} empty, {skipped_duplicate} duplicates)"
|
||||||
|
)
|
||||||
|
return transformed
|
||||||
|
|
||||||
|
def transform_single(self, review: dict[str, Any]) -> dict[str, Any] | None:
|
||||||
|
"""
|
||||||
|
Transform a single scraped review into pipeline format.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
review: Single review from scraper output
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Review in pipeline RawReview format, or None if should be skipped
|
||||||
|
"""
|
||||||
|
text = (review.get("text") or "").strip()
|
||||||
|
|
||||||
|
# Skip empty reviews (rating-only)
|
||||||
|
if not text:
|
||||||
|
return None
|
||||||
|
|
||||||
|
# Generate review_id if missing (DOM-sourced reviews)
|
||||||
|
review_id = review.get("review_id")
|
||||||
|
if not review_id:
|
||||||
|
# Generate deterministic ID from content
|
||||||
|
content_hash = hashlib.sha256(
|
||||||
|
f"{review.get('author', '')}:{text}:{review.get('rating', 0)}".encode()
|
||||||
|
).hexdigest()[:16]
|
||||||
|
review_id = f"DOM-{content_hash}"
|
||||||
|
|
||||||
|
# Parse review time from centerDate (best estimate)
|
||||||
|
review_time = self._parse_review_time(review)
|
||||||
|
|
||||||
|
return {
|
||||||
|
"review_id": review_id,
|
||||||
|
"text": text,
|
||||||
|
"rating": review.get("rating", 5),
|
||||||
|
"author_name": review.get("author", "Anonymous"),
|
||||||
|
"author_id": None, # Not available in scraper output
|
||||||
|
"review_time": review_time,
|
||||||
|
"relative_time": review.get("timestamp", ""),
|
||||||
|
"raw_payload": review, # Preserve original data
|
||||||
|
}
|
||||||
|
|
||||||
|
def _parse_review_time(self, review: dict[str, Any]) -> str:
|
||||||
|
"""
|
||||||
|
Parse the review time from available date fields.
|
||||||
|
|
||||||
|
Priority:
|
||||||
|
1. centerDate (best estimate from relative time)
|
||||||
|
2. minDate (earliest possible date)
|
||||||
|
3. Current time (fallback)
|
||||||
|
|
||||||
|
Args:
|
||||||
|
review: Review data with date fields
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
ISO 8601 timestamp string
|
||||||
|
"""
|
||||||
|
# Try centerDate first (most accurate estimate)
|
||||||
|
center_date = review.get("centerDate")
|
||||||
|
if center_date:
|
||||||
|
try:
|
||||||
|
# Parse and re-format to ensure consistency
|
||||||
|
dt = datetime.fromisoformat(center_date.replace("Z", "+00:00"))
|
||||||
|
return dt.isoformat()
|
||||||
|
except (ValueError, TypeError):
|
||||||
|
pass
|
||||||
|
|
||||||
|
# Try minDate as fallback
|
||||||
|
min_date = review.get("minDate")
|
||||||
|
if min_date:
|
||||||
|
try:
|
||||||
|
dt = datetime.fromisoformat(min_date.replace("Z", "+00:00"))
|
||||||
|
return dt.isoformat()
|
||||||
|
except (ValueError, TypeError):
|
||||||
|
pass
|
||||||
|
|
||||||
|
# Final fallback: current time
|
||||||
|
return datetime.now(timezone.utc).isoformat()
|
||||||
|
|
||||||
|
def to_scraper_output(
|
||||||
|
self,
|
||||||
|
scraped_reviews: list[dict[str, Any]],
|
||||||
|
job_id: str | None = None,
|
||||||
|
) -> dict[str, Any]:
|
||||||
|
"""
|
||||||
|
Create a full scraper output envelope for the pipeline.
|
||||||
|
|
||||||
|
This creates the complete structure expected by Pipeline.process().
|
||||||
|
|
||||||
|
Args:
|
||||||
|
scraped_reviews: List of reviews from scraper
|
||||||
|
job_id: Optional job ID (generates UUID if not provided)
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Complete scraper output dict for pipeline ingestion
|
||||||
|
"""
|
||||||
|
if job_id is None:
|
||||||
|
job_id = str(uuid4())
|
||||||
|
|
||||||
|
transformed = self.transform(scraped_reviews)
|
||||||
|
|
||||||
|
return {
|
||||||
|
"job_id": job_id,
|
||||||
|
"status": "completed",
|
||||||
|
"business_id": self.business_id,
|
||||||
|
"place_id": self.place_id,
|
||||||
|
"business_info": {
|
||||||
|
"name": self.business_id,
|
||||||
|
"place_id": self.place_id,
|
||||||
|
},
|
||||||
|
"reviews": transformed,
|
||||||
|
"scrape_time_ms": 0,
|
||||||
|
"reviews_scraped": len(transformed),
|
||||||
|
"scraper_version": "v1.0.0",
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
def load_and_transform(
|
||||||
|
file_path: str,
|
||||||
|
business_id: str,
|
||||||
|
place_id: str,
|
||||||
|
) -> dict[str, Any]:
|
||||||
|
"""
|
||||||
|
Convenience function to load a JSON file and transform it.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
file_path: Path to JSON file with scraped reviews
|
||||||
|
business_id: Business identifier
|
||||||
|
place_id: Google Maps place ID
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Complete scraper output dict for pipeline ingestion
|
||||||
|
"""
|
||||||
|
import json
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
data = json.loads(Path(file_path).read_text())
|
||||||
|
|
||||||
|
adapter = ScraperV1Adapter(business_id, place_id)
|
||||||
|
return adapter.to_scraper_output(data)
|
||||||
625
tools/test_pipeline_real_data.py
Normal file
625
tools/test_pipeline_real_data.py
Normal file
@@ -0,0 +1,625 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""
|
||||||
|
Test the pipeline with real scraped review data.
|
||||||
|
|
||||||
|
Usage:
|
||||||
|
python tools/test_pipeline_real_data.py --database-url $DATABASE_URL
|
||||||
|
|
||||||
|
This test:
|
||||||
|
1. Loads sample barbershop reviews from data/samples/
|
||||||
|
2. Uses ScraperV1Adapter to transform the data
|
||||||
|
3. Runs the full pipeline (Stage 1-4) with mocked LLM
|
||||||
|
4. Verifies data in all tables
|
||||||
|
5. Shows summary statistics
|
||||||
|
"""
|
||||||
|
|
||||||
|
import asyncio
|
||||||
|
import os
|
||||||
|
import sys
|
||||||
|
import argparse
|
||||||
|
import json
|
||||||
|
import logging
|
||||||
|
from datetime import datetime, timezone
|
||||||
|
from uuid import uuid4
|
||||||
|
from pathlib import Path
|
||||||
|
|
||||||
|
# Add project root and package to path
|
||||||
|
PROJECT_ROOT = Path(__file__).parent.parent
|
||||||
|
sys.path.insert(0, str(PROJECT_ROOT))
|
||||||
|
sys.path.insert(0, str(PROJECT_ROOT / "packages/reviewiq-pipeline/src"))
|
||||||
|
|
||||||
|
logging.basicConfig(
|
||||||
|
level=logging.INFO,
|
||||||
|
format="%(asctime)s - %(levelname)s - %(message)s",
|
||||||
|
)
|
||||||
|
logger = logging.getLogger(__name__)
|
||||||
|
|
||||||
|
|
||||||
|
async def run_pipeline_test(database_url: str, sample_file: str, cleanup: bool = True):
|
||||||
|
"""Run the pipeline test with real data."""
|
||||||
|
import asyncpg
|
||||||
|
from reviewiq_pipeline.adapters.scraper_v1 import ScraperV1Adapter, load_and_transform
|
||||||
|
from reviewiq_pipeline.config import Config
|
||||||
|
from reviewiq_pipeline.stages.stage1_normalize import Stage1Normalizer
|
||||||
|
from reviewiq_pipeline.stages.stage3_route import Stage3Router
|
||||||
|
from collections import defaultdict
|
||||||
|
|
||||||
|
# Generate unique test identifiers
|
||||||
|
test_id = uuid4().hex[:8]
|
||||||
|
business_id = f"barbershop-fleitas-{test_id}"
|
||||||
|
place_id = f"ChIJxxxxxx-{test_id}"
|
||||||
|
job_id = uuid4()
|
||||||
|
|
||||||
|
logger.info("=" * 60)
|
||||||
|
logger.info("PIPELINE TEST WITH REAL DATA")
|
||||||
|
logger.info("=" * 60)
|
||||||
|
logger.info(f"Sample file: {sample_file}")
|
||||||
|
logger.info(f"Business ID: {business_id}")
|
||||||
|
logger.info(f"Job ID: {job_id}")
|
||||||
|
logger.info("")
|
||||||
|
|
||||||
|
# Load and transform sample data
|
||||||
|
logger.info("Step 1: Loading and transforming sample data...")
|
||||||
|
sample_path = PROJECT_ROOT / sample_file
|
||||||
|
|
||||||
|
if not sample_path.exists():
|
||||||
|
logger.error(f"Sample file not found: {sample_path}")
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
raw_data = json.loads(sample_path.read_text())
|
||||||
|
logger.info(f" Loaded {len(raw_data)} raw reviews from file")
|
||||||
|
|
||||||
|
adapter = ScraperV1Adapter(business_id, place_id)
|
||||||
|
scraper_output = adapter.to_scraper_output(raw_data, str(job_id))
|
||||||
|
reviews = scraper_output["reviews"]
|
||||||
|
|
||||||
|
logger.info(f" Transformed {len(reviews)} reviews (skipped empty text)")
|
||||||
|
|
||||||
|
# Show sample review
|
||||||
|
if reviews:
|
||||||
|
sample = reviews[0]
|
||||||
|
logger.info(f" Sample review:")
|
||||||
|
logger.info(f" Author: {sample['author_name']}")
|
||||||
|
logger.info(f" Rating: {sample['rating']}")
|
||||||
|
logger.info(f" Text: {sample['text'][:80]}...")
|
||||||
|
|
||||||
|
# Connect to database
|
||||||
|
pool = await asyncpg.create_pool(database_url, min_size=2, max_size=5)
|
||||||
|
config = Config(database_url=database_url)
|
||||||
|
|
||||||
|
try:
|
||||||
|
# ========== STAGE 1: Insert raw reviews ==========
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Step 2: Stage 1 - Inserting raw reviews...")
|
||||||
|
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
for review in reviews:
|
||||||
|
review_time = datetime.fromisoformat(
|
||||||
|
review["review_time"].replace("Z", "+00:00")
|
||||||
|
)
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.reviews_raw (
|
||||||
|
job_id, source, review_id, place_id, raw_payload,
|
||||||
|
review_text, rating, review_time, reviewer_name, reviewer_id
|
||||||
|
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10)
|
||||||
|
ON CONFLICT (source, review_id, review_version) DO NOTHING
|
||||||
|
""",
|
||||||
|
job_id,
|
||||||
|
"google",
|
||||||
|
review["review_id"],
|
||||||
|
place_id,
|
||||||
|
json.dumps(review.get("raw_payload", {})),
|
||||||
|
review["text"],
|
||||||
|
review["rating"],
|
||||||
|
review_time,
|
||||||
|
review["author_name"],
|
||||||
|
review.get("author_id"),
|
||||||
|
)
|
||||||
|
|
||||||
|
raw_count = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.reviews_raw WHERE place_id = $1",
|
||||||
|
place_id,
|
||||||
|
)
|
||||||
|
logger.info(f" Inserted {raw_count} raw reviews")
|
||||||
|
|
||||||
|
# ========== STAGE 1: Normalize ==========
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Step 3: Stage 1 - Normalizing reviews...")
|
||||||
|
|
||||||
|
normalizer = Stage1Normalizer(config)
|
||||||
|
normalized_reviews = normalizer.normalize_batch(reviews, business_id, place_id)
|
||||||
|
logger.info(f" Normalized {len(normalized_reviews)} reviews")
|
||||||
|
|
||||||
|
# Language distribution
|
||||||
|
lang_dist = defaultdict(int)
|
||||||
|
for r in normalized_reviews:
|
||||||
|
lang_dist[r["text_language"]] += 1
|
||||||
|
logger.info(f" Languages: {dict(lang_dist)}")
|
||||||
|
|
||||||
|
# Insert into reviews_enriched
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
for norm in normalized_reviews:
|
||||||
|
raw_id = await conn.fetchval(
|
||||||
|
"SELECT id FROM pipeline.reviews_raw WHERE review_id = $1",
|
||||||
|
norm["review_id"],
|
||||||
|
)
|
||||||
|
|
||||||
|
review_time = datetime.fromisoformat(
|
||||||
|
norm["review_time"].replace("Z", "+00:00")
|
||||||
|
)
|
||||||
|
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.reviews_enriched (
|
||||||
|
source, review_id, review_version, is_latest, raw_id,
|
||||||
|
business_id, place_id, text, text_normalized, rating, review_time,
|
||||||
|
language, taxonomy_version
|
||||||
|
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12, $13)
|
||||||
|
ON CONFLICT (source, review_id, review_version) DO UPDATE SET
|
||||||
|
is_latest = EXCLUDED.is_latest
|
||||||
|
""",
|
||||||
|
norm["source"],
|
||||||
|
norm["review_id"],
|
||||||
|
norm["review_version"],
|
||||||
|
True,
|
||||||
|
raw_id,
|
||||||
|
business_id,
|
||||||
|
place_id,
|
||||||
|
norm["text"],
|
||||||
|
norm["text_normalized"],
|
||||||
|
norm["rating"],
|
||||||
|
review_time,
|
||||||
|
norm["text_language"],
|
||||||
|
"v5.1",
|
||||||
|
)
|
||||||
|
|
||||||
|
enriched_count = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.reviews_enriched WHERE business_id = $1",
|
||||||
|
business_id,
|
||||||
|
)
|
||||||
|
logger.info(f" Inserted {enriched_count} enriched reviews")
|
||||||
|
|
||||||
|
# ========== STAGE 2: Mock Classification ==========
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Step 4: Stage 2 - Classifying reviews (mocked LLM)...")
|
||||||
|
|
||||||
|
# Simple heuristic classification based on rating and keywords
|
||||||
|
def mock_classify(review: dict) -> dict:
|
||||||
|
text = review["text_normalized"].lower()
|
||||||
|
rating = review["rating"]
|
||||||
|
|
||||||
|
# Determine valence from rating
|
||||||
|
if rating >= 4:
|
||||||
|
valence = "V+"
|
||||||
|
elif rating <= 2:
|
||||||
|
valence = "V-"
|
||||||
|
else:
|
||||||
|
valence = "V0"
|
||||||
|
|
||||||
|
# Determine intensity from text length and rating extremity
|
||||||
|
if rating in (1, 5) and len(text) > 100:
|
||||||
|
intensity = "I3"
|
||||||
|
elif rating in (1, 2, 4, 5):
|
||||||
|
intensity = "I2"
|
||||||
|
else:
|
||||||
|
intensity = "I1"
|
||||||
|
|
||||||
|
# Simple URT classification based on keywords
|
||||||
|
if any(w in text for w in ["servicio", "service", "trato", "atención", "attention"]):
|
||||||
|
urt_primary = "A2.01" # Helpfulness
|
||||||
|
elif any(w in text for w in ["profesional", "professional", "expert"]):
|
||||||
|
urt_primary = "A4.01" # Knowledge/Expertise
|
||||||
|
elif any(w in text for w in ["precio", "price", "caro", "barato", "expensive", "cheap"]):
|
||||||
|
urt_primary = "P1.01" # Value Perception
|
||||||
|
elif any(w in text for w in ["espera", "wait", "tiempo", "time", "rápido", "fast"]):
|
||||||
|
urt_primary = "J1.01" # Wait Times
|
||||||
|
elif any(w in text for w in ["ambiente", "ambiance", "local", "lugar", "place"]):
|
||||||
|
urt_primary = "E2.01" # Ambiance
|
||||||
|
else:
|
||||||
|
urt_primary = "O1.01" # Core Product/Service
|
||||||
|
|
||||||
|
return {
|
||||||
|
"urt_primary": urt_primary,
|
||||||
|
"valence": valence,
|
||||||
|
"intensity": intensity,
|
||||||
|
"trust_score": 0.7 + (len(text) / 1000), # Longer = more trustworthy
|
||||||
|
}
|
||||||
|
|
||||||
|
batch_id = f"batch-{test_id}"
|
||||||
|
spans_created = 0
|
||||||
|
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
for norm in normalized_reviews:
|
||||||
|
cls = mock_classify(norm)
|
||||||
|
|
||||||
|
# Update classification in reviews_enriched
|
||||||
|
await conn.execute("""
|
||||||
|
UPDATE pipeline.reviews_enriched SET
|
||||||
|
urt_primary = $1,
|
||||||
|
valence = $2,
|
||||||
|
intensity = $3,
|
||||||
|
trust_score = $4,
|
||||||
|
classification_model = $5,
|
||||||
|
processed_at = NOW()
|
||||||
|
WHERE review_id = $6 AND business_id = $7
|
||||||
|
""",
|
||||||
|
cls["urt_primary"],
|
||||||
|
cls["valence"],
|
||||||
|
cls["intensity"],
|
||||||
|
cls["trust_score"],
|
||||||
|
"mock-classifier-v1",
|
||||||
|
norm["review_id"],
|
||||||
|
business_id,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Get review time for span
|
||||||
|
review_row = await conn.fetchrow(
|
||||||
|
"SELECT review_time FROM pipeline.reviews_enriched WHERE review_id = $1",
|
||||||
|
norm["review_id"],
|
||||||
|
)
|
||||||
|
|
||||||
|
# Create a single span for the whole review
|
||||||
|
span_id = f"SPN-{uuid4().hex[:12]}"
|
||||||
|
usn = f"google:{norm['review_id']}:1:0"
|
||||||
|
|
||||||
|
# Truncate span text to first 200 chars
|
||||||
|
span_text = norm["text"][:200]
|
||||||
|
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.review_spans (
|
||||||
|
span_id, business_id, place_id, source, review_id, review_version,
|
||||||
|
span_index, span_text, span_start, span_end,
|
||||||
|
profile, urt_primary, valence, intensity, comparative,
|
||||||
|
is_primary, is_active, review_time,
|
||||||
|
confidence, usn, taxonomy_version, model_version, ingest_batch_id
|
||||||
|
) VALUES (
|
||||||
|
$1, $2, $3, $4, $5, $6, $7, $8, $9, $10,
|
||||||
|
$11, $12, $13, $14, $15, $16, $17, $18, $19, $20, $21, $22, $23
|
||||||
|
)
|
||||||
|
ON CONFLICT (span_id) DO NOTHING
|
||||||
|
""",
|
||||||
|
span_id,
|
||||||
|
business_id,
|
||||||
|
place_id,
|
||||||
|
"google",
|
||||||
|
norm["review_id"],
|
||||||
|
1,
|
||||||
|
0, # span_index
|
||||||
|
span_text,
|
||||||
|
0, # span_start
|
||||||
|
len(span_text), # span_end
|
||||||
|
"standard",
|
||||||
|
cls["urt_primary"],
|
||||||
|
cls["valence"],
|
||||||
|
cls["intensity"],
|
||||||
|
"CR-N",
|
||||||
|
True, # is_primary
|
||||||
|
True, # is_active
|
||||||
|
review_row["review_time"],
|
||||||
|
"high",
|
||||||
|
usn,
|
||||||
|
"v5.1",
|
||||||
|
"mock-classifier-v1",
|
||||||
|
batch_id,
|
||||||
|
)
|
||||||
|
spans_created += 1
|
||||||
|
|
||||||
|
logger.info(f" Created {spans_created} spans")
|
||||||
|
|
||||||
|
# Show classification distribution
|
||||||
|
cls_dist = await conn.fetch("""
|
||||||
|
SELECT urt_primary, valence, COUNT(*) as cnt
|
||||||
|
FROM pipeline.reviews_enriched
|
||||||
|
WHERE business_id = $1
|
||||||
|
GROUP BY urt_primary, valence
|
||||||
|
ORDER BY cnt DESC
|
||||||
|
""", business_id)
|
||||||
|
|
||||||
|
logger.info(" Classification distribution:")
|
||||||
|
for row in cls_dist[:5]:
|
||||||
|
logger.info(f" {row['urt_primary']} ({row['valence']}): {row['cnt']}")
|
||||||
|
|
||||||
|
# ========== STAGE 3: Route Issues ==========
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Step 5: Stage 3 - Routing negative spans to issues...")
|
||||||
|
|
||||||
|
router = Stage3Router(config)
|
||||||
|
routed_count = 0
|
||||||
|
issues_created = 0
|
||||||
|
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
# Get negative/mixed spans
|
||||||
|
spans_to_route = await conn.fetch("""
|
||||||
|
SELECT span_id, business_id, place_id, urt_primary, valence, intensity,
|
||||||
|
entity_normalized, review_time, confidence, source, review_id, review_version
|
||||||
|
FROM pipeline.review_spans
|
||||||
|
WHERE business_id = $1 AND valence IN ('V-', 'V±')
|
||||||
|
""", business_id)
|
||||||
|
|
||||||
|
for span_row in spans_to_route:
|
||||||
|
span_data = {
|
||||||
|
"span_id": span_row["span_id"],
|
||||||
|
"business_id": span_row["business_id"],
|
||||||
|
"place_id": span_row["place_id"],
|
||||||
|
"urt_primary": span_row["urt_primary"],
|
||||||
|
"valence": span_row["valence"],
|
||||||
|
"intensity": span_row["intensity"],
|
||||||
|
"entity_normalized": span_row["entity_normalized"],
|
||||||
|
"review_time": span_row["review_time"].isoformat(),
|
||||||
|
"confidence": span_row["confidence"],
|
||||||
|
"trust_score": 0.85,
|
||||||
|
}
|
||||||
|
|
||||||
|
routed = router.route_span_sync(span_data)
|
||||||
|
|
||||||
|
# Check if issue exists
|
||||||
|
existing = await conn.fetchval(
|
||||||
|
"SELECT 1 FROM pipeline.issues WHERE issue_id = $1",
|
||||||
|
routed["issue_id"],
|
||||||
|
)
|
||||||
|
|
||||||
|
if not existing:
|
||||||
|
domain = span_row["urt_primary"][0]
|
||||||
|
intensity_scores = {"I1": 1.0, "I2": 2.0, "I3": 3.0}
|
||||||
|
priority_score = intensity_scores.get(span_row["intensity"], 1.0)
|
||||||
|
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.issues (
|
||||||
|
issue_id, business_id, place_id, primary_subcode, domain,
|
||||||
|
state, priority_score, span_count, max_intensity, taxonomy_version
|
||||||
|
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9, $10)
|
||||||
|
""",
|
||||||
|
routed["issue_id"],
|
||||||
|
business_id,
|
||||||
|
place_id,
|
||||||
|
span_row["urt_primary"],
|
||||||
|
domain,
|
||||||
|
"open",
|
||||||
|
priority_score,
|
||||||
|
1,
|
||||||
|
span_row["intensity"],
|
||||||
|
"v5.1",
|
||||||
|
)
|
||||||
|
issues_created += 1
|
||||||
|
else:
|
||||||
|
await conn.execute("""
|
||||||
|
UPDATE pipeline.issues SET span_count = span_count + 1, updated_at = NOW()
|
||||||
|
WHERE issue_id = $1
|
||||||
|
""", routed["issue_id"])
|
||||||
|
|
||||||
|
# Link span to issue
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.issue_spans (
|
||||||
|
issue_id, span_id, source, review_id, review_version,
|
||||||
|
is_primary_match, intensity, review_time
|
||||||
|
) VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
|
||||||
|
ON CONFLICT (span_id) DO NOTHING
|
||||||
|
""",
|
||||||
|
routed["issue_id"],
|
||||||
|
span_row["span_id"],
|
||||||
|
span_row["source"],
|
||||||
|
span_row["review_id"],
|
||||||
|
span_row["review_version"],
|
||||||
|
True,
|
||||||
|
span_row["intensity"],
|
||||||
|
span_row["review_time"],
|
||||||
|
)
|
||||||
|
|
||||||
|
# Log event
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.issue_events (issue_id, event_type, span_id)
|
||||||
|
VALUES ($1, $2, $3)
|
||||||
|
""", routed["issue_id"], "span_linked", span_row["span_id"])
|
||||||
|
|
||||||
|
routed_count += 1
|
||||||
|
|
||||||
|
logger.info(f" Routed {routed_count} spans to {issues_created} issues")
|
||||||
|
|
||||||
|
# ========== STAGE 4: Aggregation ==========
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Step 6: Stage 4 - Aggregating facts...")
|
||||||
|
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
# Get span data for aggregation
|
||||||
|
span_data = await conn.fetch("""
|
||||||
|
SELECT
|
||||||
|
rs.business_id,
|
||||||
|
rs.place_id,
|
||||||
|
DATE(rs.review_time) as review_date,
|
||||||
|
rs.urt_primary,
|
||||||
|
rs.valence,
|
||||||
|
rs.intensity,
|
||||||
|
rs.comparative,
|
||||||
|
re.trust_score,
|
||||||
|
re.rating
|
||||||
|
FROM pipeline.review_spans rs
|
||||||
|
JOIN pipeline.reviews_enriched re ON (
|
||||||
|
re.source = rs.source
|
||||||
|
AND re.review_id = rs.review_id
|
||||||
|
AND re.review_version = rs.review_version
|
||||||
|
)
|
||||||
|
WHERE rs.business_id = $1 AND rs.is_active = TRUE
|
||||||
|
""", business_id)
|
||||||
|
|
||||||
|
# Group by date and URT code
|
||||||
|
daily_data = defaultdict(lambda: defaultdict(list))
|
||||||
|
for row in span_data:
|
||||||
|
daily_data[row["review_date"]][row["urt_primary"]].append(dict(row))
|
||||||
|
|
||||||
|
facts_inserted = 0
|
||||||
|
for period_date, urt_groups in daily_data.items():
|
||||||
|
for urt_code, code_spans in urt_groups.items():
|
||||||
|
negative_count = sum(1 for s in code_spans if s["valence"] == "V-")
|
||||||
|
positive_count = sum(1 for s in code_spans if s["valence"] == "V+")
|
||||||
|
neutral_count = sum(1 for s in code_spans if s["valence"] == "V0")
|
||||||
|
mixed_count = sum(1 for s in code_spans if s["valence"] == "V±")
|
||||||
|
|
||||||
|
i1_count = sum(1 for s in code_spans if s["intensity"] == "I1")
|
||||||
|
i2_count = sum(1 for s in code_spans if s["intensity"] == "I2")
|
||||||
|
i3_count = sum(1 for s in code_spans if s["intensity"] == "I3")
|
||||||
|
|
||||||
|
strength_score = (positive_count - negative_count) / max(len(code_spans), 1)
|
||||||
|
|
||||||
|
await conn.execute("""
|
||||||
|
INSERT INTO pipeline.fact_timeseries (
|
||||||
|
business_id, place_id, period_date, bucket_type,
|
||||||
|
subject_type, subject_id, taxonomy_version,
|
||||||
|
review_count, span_count,
|
||||||
|
negative_count, positive_count, neutral_count, mixed_count,
|
||||||
|
strength_score, negative_strength, positive_strength,
|
||||||
|
i1_count, i2_count, i3_count,
|
||||||
|
cr_better, cr_worse, cr_same,
|
||||||
|
trust_weighted_strength, trust_weighted_negative
|
||||||
|
) VALUES (
|
||||||
|
$1, $2, $3, $4, $5, $6, $7, $8, $9, $10, $11, $12, $13,
|
||||||
|
$14, $15, $16, $17, $18, $19, $20, $21, $22, $23, $24
|
||||||
|
)
|
||||||
|
ON CONFLICT (business_id, place_id, period_date, bucket_type,
|
||||||
|
subject_type, subject_id, taxonomy_version)
|
||||||
|
DO UPDATE SET
|
||||||
|
span_count = EXCLUDED.span_count,
|
||||||
|
computed_at = NOW()
|
||||||
|
""",
|
||||||
|
business_id,
|
||||||
|
place_id,
|
||||||
|
period_date,
|
||||||
|
"day",
|
||||||
|
"urt_code",
|
||||||
|
urt_code,
|
||||||
|
"v5.1",
|
||||||
|
len(code_spans),
|
||||||
|
len(code_spans),
|
||||||
|
negative_count,
|
||||||
|
positive_count,
|
||||||
|
neutral_count,
|
||||||
|
mixed_count,
|
||||||
|
strength_score,
|
||||||
|
float(negative_count),
|
||||||
|
float(positive_count),
|
||||||
|
i1_count,
|
||||||
|
i2_count,
|
||||||
|
i3_count,
|
||||||
|
0, 0, 0,
|
||||||
|
strength_score,
|
||||||
|
float(negative_count),
|
||||||
|
)
|
||||||
|
facts_inserted += 1
|
||||||
|
|
||||||
|
logger.info(f" Inserted {facts_inserted} fact records")
|
||||||
|
|
||||||
|
# ========== RESULTS ==========
|
||||||
|
logger.info("")
|
||||||
|
logger.info("=" * 60)
|
||||||
|
logger.info("PIPELINE TEST RESULTS")
|
||||||
|
logger.info("=" * 60)
|
||||||
|
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
results = {}
|
||||||
|
results["reviews_raw"] = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.reviews_raw WHERE place_id = $1", place_id
|
||||||
|
)
|
||||||
|
results["reviews_enriched"] = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.reviews_enriched WHERE business_id = $1", business_id
|
||||||
|
)
|
||||||
|
results["review_spans"] = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.review_spans WHERE business_id = $1", business_id
|
||||||
|
)
|
||||||
|
results["issues"] = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.issues WHERE business_id = $1", business_id
|
||||||
|
)
|
||||||
|
results["issue_spans"] = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.issue_spans WHERE issue_id IN (SELECT issue_id FROM pipeline.issues WHERE business_id = $1)", business_id
|
||||||
|
)
|
||||||
|
results["fact_timeseries"] = await conn.fetchval(
|
||||||
|
"SELECT COUNT(*) FROM pipeline.fact_timeseries WHERE business_id = $1", business_id
|
||||||
|
)
|
||||||
|
|
||||||
|
logger.info(f" pipeline.reviews_raw: {results['reviews_raw']}")
|
||||||
|
logger.info(f" pipeline.reviews_enriched: {results['reviews_enriched']}")
|
||||||
|
logger.info(f" pipeline.review_spans: {results['review_spans']}")
|
||||||
|
logger.info(f" pipeline.issues: {results['issues']}")
|
||||||
|
logger.info(f" pipeline.issue_spans: {results['issue_spans']}")
|
||||||
|
logger.info(f" pipeline.fact_timeseries: {results['fact_timeseries']}")
|
||||||
|
|
||||||
|
# Show issues
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Issues identified:")
|
||||||
|
issues = await conn.fetch("""
|
||||||
|
SELECT issue_id, primary_subcode, span_count, max_intensity
|
||||||
|
FROM pipeline.issues
|
||||||
|
WHERE business_id = $1
|
||||||
|
ORDER BY span_count DESC
|
||||||
|
LIMIT 10
|
||||||
|
""", business_id)
|
||||||
|
|
||||||
|
for issue in issues:
|
||||||
|
logger.info(
|
||||||
|
f" {issue['issue_id'][:20]}... "
|
||||||
|
f"Code={issue['primary_subcode']} "
|
||||||
|
f"Spans={issue['span_count']} "
|
||||||
|
f"MaxInt={issue['max_intensity']}"
|
||||||
|
)
|
||||||
|
|
||||||
|
# Show date range
|
||||||
|
date_range = await conn.fetchrow("""
|
||||||
|
SELECT MIN(review_time)::date as min_date, MAX(review_time)::date as max_date
|
||||||
|
FROM pipeline.reviews_enriched
|
||||||
|
WHERE business_id = $1
|
||||||
|
""", business_id)
|
||||||
|
|
||||||
|
logger.info("")
|
||||||
|
logger.info(f"Date range: {date_range['min_date']} to {date_range['max_date']}")
|
||||||
|
|
||||||
|
# ========== CLEANUP ==========
|
||||||
|
if cleanup:
|
||||||
|
logger.info("")
|
||||||
|
logger.info("Cleaning up test data...")
|
||||||
|
|
||||||
|
async with pool.acquire() as conn:
|
||||||
|
await conn.execute("DELETE FROM pipeline.fact_timeseries WHERE business_id = $1", business_id)
|
||||||
|
await conn.execute("DELETE FROM pipeline.issue_events WHERE issue_id IN (SELECT issue_id FROM pipeline.issues WHERE business_id = $1)", business_id)
|
||||||
|
await conn.execute("DELETE FROM pipeline.issue_spans WHERE issue_id IN (SELECT issue_id FROM pipeline.issues WHERE business_id = $1)", business_id)
|
||||||
|
await conn.execute("DELETE FROM pipeline.issues WHERE business_id = $1", business_id)
|
||||||
|
await conn.execute("DELETE FROM pipeline.review_spans WHERE business_id = $1", business_id)
|
||||||
|
await conn.execute("DELETE FROM pipeline.reviews_enriched WHERE business_id = $1", business_id)
|
||||||
|
await conn.execute("DELETE FROM pipeline.reviews_raw WHERE place_id = $1", place_id)
|
||||||
|
|
||||||
|
logger.info("Test data cleaned up")
|
||||||
|
|
||||||
|
logger.info("")
|
||||||
|
logger.info("=" * 60)
|
||||||
|
logger.info("PIPELINE TEST COMPLETED SUCCESSFULLY!")
|
||||||
|
logger.info("=" * 60)
|
||||||
|
|
||||||
|
finally:
|
||||||
|
await pool.close()
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
parser = argparse.ArgumentParser(description="Test pipeline with real data")
|
||||||
|
parser.add_argument(
|
||||||
|
"--database-url",
|
||||||
|
default=os.environ.get("DATABASE_URL"),
|
||||||
|
help="PostgreSQL connection string (default: $DATABASE_URL)",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--sample-file",
|
||||||
|
default="data/samples/barbershop_reviews.json",
|
||||||
|
help="Path to sample data file (relative to project root)",
|
||||||
|
)
|
||||||
|
parser.add_argument(
|
||||||
|
"--no-cleanup",
|
||||||
|
action="store_true",
|
||||||
|
help="Don't clean up test data after running",
|
||||||
|
)
|
||||||
|
|
||||||
|
args = parser.parse_args()
|
||||||
|
|
||||||
|
if not args.database_url:
|
||||||
|
print("Error: --database-url required or set DATABASE_URL", file=sys.stderr)
|
||||||
|
sys.exit(1)
|
||||||
|
|
||||||
|
asyncio.run(run_pipeline_test(
|
||||||
|
args.database_url,
|
||||||
|
args.sample_file,
|
||||||
|
cleanup=not args.no_cleanup,
|
||||||
|
))
|
||||||
Reference in New Issue
Block a user