Repository: lvgalvao/WebScraping-2025-Jornada-Aovivo
Branch: main
Commit: 7feeebb61b8e
Files: 12
Total size: 127.0 KB
Directory structure:
gitextract_jsk0yvsl/
├── .gitignore
├── README.md
├── data/
│ └── data.jsonl
├── requirements.txt
└── src/
├── dashboard/
│ └── app.py
├── extraction/
│ ├── coleta/
│ │ ├── __init__.py
│ │ ├── items.py
│ │ ├── settings.py
│ │ └── spiders/
│ │ ├── __init__.py
│ │ └── notebook.py
│ └── scrapy.cfg
└── transformLoad/
└── main.py
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FILE CONTENTS
================================================
================================================
FILE: .gitignore
================================================
.venv
================================================
FILE: README.md
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# Web Scraping Mercado livre case Samsung
<p align="center">
<a href="https://suajornadadedados.com.br/"><img src="pic/logo.png" alt="Jornada de Dados"></a>
</p>
<p align="center">
<em>Nossa missão é fornecer o melhor ensino em engenharia de dados</em>
</p>
================================================
FILE: data/data.jsonl
================================================
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{"brand": "DELL", "name": "Notebook Dell Inspiron I15 Intel Core i3 -1215U (12ªGeração), 8GB RAM, 256GB SSD, Linux, Tela 15,6\" FULL HD - I15-I120K-U10P", "seller": null, "reviews_rating_number": "4.9", "reviews_amount": "(10)", "old_money": "3.525", "new_money": "338"}
{"brand": "LENOVO", "name": "Notebook Lenovo Ideapad 14 N4020 Win 11- 4gb - 128gb Cinza", "seller": null, "reviews_rating_number": "3.8", "reviews_amount": "(14)", "old_money": "1.749", "new_money": "168"}
{"brand": "DELL", "name": "Notebook Dell Vostro 5490 I5 10th 8gb Ssd 240gb", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.499", "new_money": "240"}
{"brand": "DELL", "name": "Notebook Dell Latitude 3450 Ultra5 135u 14th 16gb 512ssd", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "4.550", "new_money": "437"}
{"brand": null, "name": "Alienware M18 R2 Fhd+ 480 hz i9-14900HX 64 GB Rtx 4090 4 TB Cor da lua metálica escura", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "38.499", "new_money": "3.700"}
{"brand": "HP", "name": "Notebook Hp 240 G8 Core I3 Ssd 240gb - 10a Geração", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "1.590", "new_money": "152"}
{"brand": "LENOVO", "name": "Notebook Lenovo Legion Slim 5 Intel Core i7 16gb Ram 512gb Ssd 16'' Windows 11", "seller": null, "reviews_rating_number": "4.7", "reviews_amount": "(131)", "old_money": "8.458", "new_money": "812"}
{"brand": "DELL", "name": "Notebook Dell Latitude 3480 I7 8gb 240gb Ssd Windows 10 Pro", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.499", "new_money": "1.394"}
{"brand": "HP", "name": "Notebook Hp 745, 16gb 240gb, Vga Radeon R5 - Com Garantia", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.095", "new_money": "105"}
{"brand": null, "name": "Notebook ASUS Vivobook X1502ZA-EJ1751W Intel Core i3 1220P 3,3GHz 8Gb Ram 256Gb SSD Windows 11 Home 15,6” Led Fhd Intel UHD Graphics Prata Metálico", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(3)", "old_money": "4.200", "new_money": null}
{"brand": null, "name": "Notebook Book Celeron-6305 4gb 500gb W10 15.6'' Cinza Chumbo", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.299", "new_money": "220"}
{"brand": "DELL", "name": "Notebook Dell Core I5 4ª Gen 8gb / Hd/ Hdmi / Com Garantia.", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.395", "new_money": "1.163"}
{"brand": "LENOVO", "name": "Ultrabook Ook Lenovo Thinkpad T440s", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.399", "new_money": "135"}
{"brand": null, "name": "Apple Macbook Air 13 M4 16gb Ram | 256gb Ssd | Lacrado Azul", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "10.699", "new_money": "1.028"}
{"brand": null, "name": "Macbook Air Retina Processador M2 8gb Ram 512ssd - 2022", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "8.827", "new_money": "882"}
{"brand": "DELL", "name": "Notebook Dell Alienware M18 R1 18\" cor cinza 64GB - 2TB SSD - 4TB HDD - Intel Core i9", "seller": null, "reviews_rating_number": "4.9", "reviews_amount": "(8)", "old_money": "34.499", "new_money": "3.315"}
{"brand": "DELL", "name": "Notebook Dell Latitude 5410 I5 10210u 16gb 256ssd - Seminovo", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.249", "new_money": "216"}
{"brand": "LENOVO", "name": "Lenovo Thinkpad I7 8a 8gb Ssd 480gb Tela 12,5 + Mouse Brinde", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.498", "new_money": "1.998"}
{"brand": "LENOVO", "name": "Desktop Lenovo Thinkcentre Intel Core I7 16gb 512gb W11 Pro", "seller": "Por Lenovo ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "5.615", "new_money": "539"}
{"brand": "ASUS", "name": "Notebook Asus Vivobook Go Core I3 N305 8gb 512ssd 15,6 Fhd", "seller": "Por Asus ", "reviews_rating_number": "4.5", "reviews_amount": "(12)", "old_money": "2.679", "new_money": "267"}
{"brand": "ACER", "name": "Notebook Predator 99my Intel Ci9 14ªg 32gb 1ssd Rtx4070 W11", "seller": "Por Acer Brasil ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "14.999", "new_money": "1.499"}
{"brand": "ASUS", "name": "Notebook Asus X515 N4500 16gb Ram Ddr4 512gb Nvme Windows 11", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "3.299", "new_money": "3.035"}
{"brand": "LENOVO", "name": "Notebook Lenovo Core I7(10ª Ger) 16gb Ram 256 Ssd Hdmi Usbc", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "2.490", "new_money": "239"}
{"brand": "ASUS", "name": "Notebook Asus Zenbook S14 Core Ultra7 258v 32gb 1tb Ssd W11", "seller": "Por Asus ", "reviews_rating_number": "4.0", "reviews_amount": "(4)", "old_money": "14.999", "new_money": "13.919"}
{"brand": "LENOVO", "name": "Notebook Lenovo Lenovo V14 G4 Amd Ryzen 5 8gb 256gb Linux", "seller": "Por Lenovo ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.799", "new_money": "2.649"}
{"brand": null, "name": "Notebook Barato I5 Para Dia A Dia 8gb De Ram Hd 500 Gb Win", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.458", "new_money": "1.239"}
{"brand": "LENOVO", "name": "Notebook Lenovo T480 Core I5-8ªth 16gb Ssd 240gb Tela Hd Cor Black - Bom (Recondicionado)", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(3)", "old_money": "1.699", "new_money": "169"}
{"brand": "DELL", "name": "Notebook Dell Latitude 3400 Core I7-8565u 16gb Ddr4 Ssd 256", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.805", "new_money": "280"}
{"brand": "DELL", "name": "Notebook Dell Latitude 5440 I5 16 GB de RAM 512 GB Ssd 14 Fhd", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "6.399", "new_money": "639"}
{"brand": "HP", "name": "Notebook Hp 64/4 Gb Tela 14 Intel Celeron N4120 - Branco", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.099", "new_money": "201"}
{"brand": "LENOVO", "name": "Notebook I5 8350u Ssd 240 Gb 16gb Ddr4 Usb C Hdmi Lan T480", "seller": null, "reviews_rating_number": "4.9", "reviews_amount": "(15)", "old_money": "1.899", "new_money": "189"}
{"brand": "LENOVO", "name": "Notebook I5 Tela Touch Ssd 256gb 32gb Fhd Hdmi Usb-c Tb3 T14", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(5)", "old_money": "3.999", "new_money": "2.799"}
{"brand": "ACER", "name": "Notebook Acer Core I7 12ªgen 12gb Nvme 512gb 15.6' Full Hd", "seller": "Por Facini Informatica ", "reviews_rating_number": "4.9", "reviews_amount": "(20)", "old_money": "4.223", "new_money": "405"}
{"brand": "DELL", "name": "Notebook Workstation Dell M6800 Intel Core I7 Touchscreen", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "3.899", "new_money": "3.704"}
{"brand": null, "name": "Notebook Netbook Positivo Mobo S7 Laptop- Com Garantia E Nf", "seller": null, "reviews_rating_number": "3.5", "reviews_amount": "(66)", "old_money": "369", "new_money": "36"}
{"brand": null, "name": "Notebook Vaio Fe14 Intel Core I3 8gb 256gb 14'' W11 Pro. Cor Preto", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.990", "new_money": "299"}
{"brand": "HP", "name": "Note Hp Pavilion 15, 15.6'', I5, 16gb, Ssd256gb, Touchscreen", "seller": "Por OTH Produtos ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.790", "new_money": "279"}
{"brand": "LENOVO", "name": "Notebook Lenovo Thinkpad T495 Ryzen 5 Pro Ram 16gb Ssd 256gb", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.000", "new_money": "192"}
{"brand": "LENOVO", "name": "Ultrabook Lenovo Thinkpad L14 Gen2 I5-1145g7 16gb Nvme256+nf Cor Preto", "seller": null, "reviews_rating_number": "3.3", "reviews_amount": "(6)", "old_money": "3.449", "new_money": "344"}
{"brand": null, "name": "Notebook Positivo Vision i15 Intel Core i5 11ª gen 8GB RAM 512GB SSD, Lumina Bar Windows 11 Home, Tela 15” Full HD Antirreflexo – Cinza", "seller": null, "reviews_rating_number": "4.8", "reviews_amount": "(53)", "old_money": "3.699", "new_money": "3.123"}
{"brand": "DELL", "name": "Notebook Dell, Lat 5300, 13.3'', Core I5 8th, 16gb, Ssd256gb", "seller": "Por OTH Produtos ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.990", "new_money": "199"}
{"brand": "HP", "name": "Notebook ProBook 440 G5 14\" prata 8GB de Ram - 500GB HDD - Intel Core i5", "seller": null, "reviews_rating_number": "3.4", "reviews_amount": "(14)", "old_money": "3.000", "new_money": "288"}
{"brand": "LENOVO", "name": "Notebook Lenovo LOQ-e 15iax9e Intel Core i5-12450hx 16gb 512gb Ssd Rtx 3050 Windows 11 15.6 - 83me0007br Luna Grey", "seller": "Por Mobcom ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "9.510", "new_money": "4.799"}
{"brand": "HP", "name": "Notebook HP 256 G9 Intel® Core™ i5 da 12ª geração SSD 256GB 8GB Intel UHD 15,6\" Windows 11", "seller": "Por INPOWER ", "reviews_rating_number": "4.8", "reviews_amount": "(519)", "old_money": "4.221", "new_money": "3.123"}
{"brand": "ACER", "name": "Acer Aspire 5 15.6 Fhd I7-12650h Ssd 256gb 8gb Linux Gutta Cor Gamut", "seller": "Por INPOWER ", "reviews_rating_number": "4.7", "reviews_amount": "(137)", "old_money": "4.629", "new_money": "3.299"}
{"brand": "DELL", "name": "Notebook Dell 3400 Intel I7 8565u Ssd 1tb Ram 32gb", "seller": "Por 4Show ", "reviews_rating_number": "2.8", "reviews_amount": "(4)", "old_money": "3.399", "new_money": "339"}
{"brand": "HP", "name": "Notebook ProBook 440 G5 14\" prata 8GB de Ram - 500GB HDD - Intel Core i5", "seller": null, "reviews_rating_number": "3.4", "reviews_amount": "(14)", "old_money": "3.000", "new_money": "288"}
{"brand": "LENOVO", "name": "Notebook Lenovo Ideapad 1 I5 8gb 512gb W11h 14 Abyss Blue", "seller": "Por Lenovo ", "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "3.299", "new_money": "3.089"}
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{"brand": "LENOVO", "name": "Lenovo Thinkpad X1 Carbon I7-8th 16gb 512gb Ssd Nvm (brinde)", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "5.999", "new_money": "2.939"}
{"brand": null, "name": "Notebook Ultra Win11 Home 14 Pol Celeron 4g Ram 128gb Ub250", "seller": "Por Loja Multi ", "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "1.499", "new_money": "149"}
{"brand": "DELL", "name": "Notebook Dell Inspiron 3467 I3-6th Ram 8gb Ssd 240gb", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "2.599", "new_money": "1.169"}
{"brand": null, "name": "Notebook Intel Core, I7 16gb, Ssd 240gb, Com Garantia", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "1.390", "new_money": "139"}
{"brand": "DELL", "name": "Notebook Dell Latitude 5290 I5 32gb Ram 1tb Ssd Win11 Hdmi", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "3.650", "new_money": "365"}
{"brand": null, "name": "Notebook Vaio Fe 16 Amd Ryzen 5 - 5625u Linux 16gb 512gb Ssd Tela 16 Ips Wuxga Antirreflexo - Cinza Grafite - Vjfe69f11xb0711h", "seller": "Por Vaio ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "4.359", "new_money": "3.599"}
{"brand": "ASUS", "name": "Notebook Asus Zenbook S14 Oled Ux5406sa Intel Core Ultra 7 256v 16gb Ram 1tb Ssd Windows 11 Home Tela 14 Fhd 120hz Gray - Pz176w", "seller": "Por Asus ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "13.999", "new_money": "10.269"}
{"brand": "LENOVO", "name": "Notebook Ideapad 1i I7 16gb 512gb W11 Home 15.6 82vy000nbr", "seller": "Por Lenovo ", "reviews_rating_number": "4.8", "reviews_amount": "(25)", "old_money": "4.599", "new_money": "4.309"}
{"brand": "LENOVO", "name": "Notebook Lenovo Ideapad Core I7 1165g7 8gb 256ssd 15itl6", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "5.111", "new_money": "4.549"}
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{"brand": "LENOVO", "name": "Notebook Lenovo V15 Intel Core I5 8gb 256gb W11 Pro 15.6 ", "seller": "Por Lenovo ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "4.634", "new_money": "445"}
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{"brand": "LENOVO", "name": "Notebook Lenovo Thinkbook 14 Intel Core I7 32gb 1tb W11pro", "seller": "Por Lenovo ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "7.899", "new_money": "7.394"}
{"brand": "ACER", "name": "Notebook Acer Intel I5 1135g7 8gb Ddr4 M.2 256gb Vitrine", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.899", "new_money": "289"}
{"brand": "HP", "name": "Notebook Hp Probook, 440 G5, 14'', I5 8th, 8gb, Ssd-256gb", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "1.399", "new_money": "139"}
{"brand": "LENOVO", "name": "Notebook Lenovo Thinkpad X1 Carbon I7-8th 16gb 256gb +brinde", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.797", "new_money": "2.321"}
{"brand": "DELL", "name": "Notebook Dell Inspiron 15- 3501 I3 - 1115ge/4 Gb/1 Tb/ W10 H Cinza", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "3.540", "new_money": "340"}
{"brand": "LENOVO", "name": "Notebook Ideapad 1 R3 4gb 256gb Linux 15.6 82x5s00600", "seller": "Por Lenovo ", "reviews_rating_number": "4.7", "reviews_amount": "(6)", "old_money": "2.199", "new_money": "2.079"}
{"brand": "LENOVO", "name": "Notebook Lenovo Thinkbook 14 Intel Core I5 16gb 512gb W11", "seller": "Por Lenovo ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "5.299", "new_money": "4.964"}
{"brand": "DELL", "name": "Notebook Dell Xps 13 9370 13.3 I7 8th 16gb M2 512gb 4k Touch", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "3.999", "new_money": "399"}
{"brand": null, "name": "Apple Macbook Pro 14 Chip M4 2024 16gb 512gb A3112 Preto-espacial", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "14.999", "new_money": "1.500"}
{"brand": "DELL", "name": "Notebook Dell Latitude E5440 14\" 16GB de Ram 512GB SSD Intel Core i5 Cor Cinza", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "5.655", "new_money": "5.315"}
{"brand": null, "name": "Notebook Presario CQ-25 14.1\" gray 4GB de Ram - 120GB SSD - Intel Pentium", "seller": null, "reviews_rating_number": "4.2", "reviews_amount": "(33)", "old_money": "1.099", "new_money": null}
{"brand": "ASUS", "name": "Notebook ASUS ExpertBook B1502CBA Intel Core i5 1235U 8GB Ram 512GB SSD Windows 11 Pro Tela 15,6\" FHD Black - BQ2862X", "seller": "Por Asus ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "5.999", "new_money": "4.799"}
{"brand": "HP", "name": "Notebook Hp 640 G4 Core I5 8° Ger 8gb Ssd 256gb", "seller": null, "reviews_rating_number": "4.0", "reviews_amount": "(1)", "old_money": "1.699", "new_money": "169"}
{"brand": "ASUS", "name": "Notebook ASUS Vivobook I3 8GB 512GB Endless X1500EA-EJ3667", "seller": null, "reviews_rating_number": "4.6", "reviews_amount": "(236)", "old_money": "2.999", "new_money": "299"}
{"brand": "ACER", "name": "Notebook Acer Predator Gamer I7-13650hx 16gb512gbssdrtx4060", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "8.170", "new_money": "817"}
{"brand": "ASUS", "name": "Notebook Asus Amd Ryzen 5 3500u 8gb Vega 8 256gb Ssd 15,6", "seller": null, "reviews_rating_number": "4.8", "reviews_amount": "(477)", "old_money": "3.189", "new_money": "318"}
{"brand": "LENOVO", "name": "Notebook Lenovo Ultrafino Ideapad 3i I3-1215u 8gb 256gb Ssd ", "seller": "Por Login ", "reviews_rating_number": null, "reviews_amount": null, "old_money": "3.199", "new_money": "2.849"}
{"brand": null, "name": "Tapete Office Mouse Pad Dupla Face Tecido sintético impermeável e antiderrapante Toque macio Geonav Preto E Rosa", "seller": null, "reviews_rating_number": "4.9", "reviews_amount": "(74)", "old_money": "68", "new_money": "34"}
{"brand": "DELL", "name": "Notebook Dell Latitude 3440 Intel Core I5 12th 8gb 256 Gb", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "4.699", "new_money": "469"}
{"brand": null, "name": "Notebook Positivo N2140 Core I5 8°ger 8gb 1tb Vitrine", "seller": null, "reviews_rating_number": "4.8", "reviews_amount": "(5)", "old_money": "1.799", "new_money": "180"}
{"brand": "LENOVO", "name": "Notebook Lenovo V-Series V15-IGL", "seller": null, "reviews_rating_number": null, "reviews_amount": null, "old_money": "2.800", "new_money": "280"}
{"brand": "HP", "name": "Notebook Hp Elitebook 840 G7 Core I5 10ª Ger 16gb Ssd 256gb", "seller": null, "reviews_rating_number": "5.0", "reviews_amount": "(2)", "old_money": "2.349", "new_money": "234"}
{"brand": "HP", "name": "Notebook Hp Elitebook 840 G9 Intel Vpro I5- W11p 256gb", "seller": "Por HP ", "reviews_rating_number": "5.0", "reviews_amount": "(1)", "old_money": "8.177", "new_money": "4.599"}
{"brand": null, "name": "Notebook Motion Q4128B 14\" deep blue 4GB de Ram - 128GB SSD - Intel Atom", "seller": null, "reviews_rating_number": "4.5", "reviews_amount": "(2)", "old_money": "1.245", "new_money": "124"}
{"brand": "DELL", "name": "Notebook Dell Alienware I9-13900hx 16gb Ddr5 Nvidia Rtx 4060 Cor Dark Metallic Moon", "seller": null, "reviews_rating_number": "4.6", "reviews_amount": "(11)", "old_money": "14.999", "new_money": "1.499"}
================================================
FILE: requirements.txt
================================================
pandas
streamlit
scrapy
================================================
FILE: src/dashboard/app.py
================================================
# import
import streamlit as st
import pandas as pd
import sqlite3
# Conectar ao banco de dados SQLite
conn = sqlite3.connect('data/mercadolivre.db')
# Carregar os dados da tabela 'notebooks' em um DataFrame pandas
df = pd.read_sql_query("SELECT * FROM notebook", conn)
# Fechar a conexão com o banco de dados
conn.close()
# Título da aplicação
st.title('📊 Pesquisa de Mercado - Notebooks no Mercado Livre')
# Melhorar o layout com colunas para KPIs
st.subheader('💡 KPIs principais')
col1, col2, col3 = st.columns(3)
# KPI 1: Número total de itens
total_itens = df.shape[0]
col1.metric(label="🖥️ Total de Notebooks", value=total_itens)
# KPI 2: Número de marcas únicas
unique_brands = df['brand'].nunique()
col2.metric(label="🏷️ Marcas Únicas", value=unique_brands)
# KPI 3: Preço médio novo (em reais)
average_new_price = df['new_money'].mean()
col3.metric(label="💰 Preço Médio (R$)", value=f"{average_new_price:.2f}")
# Marcas mais frequentes
st.subheader('🏆 Marcas mais encontradas até a 10ª página')
col1, col2 = st.columns([4, 2])
top_brands = df['brand'].value_counts().sort_values(ascending=False)
col1.bar_chart(top_brands)
col2.write(top_brands)
# Preço médio por marca
st.subheader('💵 Preço médio por marca')
col1, col2 = st.columns([4, 2])
df_non_zero_prices = df[df['new_money'] > 0]
average_price_by_brand = df_non_zero_prices.groupby('brand')['new_money'].mean().sort_values(ascending=False)
col1.bar_chart(average_price_by_brand)
col2.write(average_price_by_brand)
# Satisfação média por marca
st.subheader('⭐ Satisfação média por marca')
col1, col2 = st.columns([4, 2])
df_non_zero_reviews = df[df['reviews_rating_number'] > 0]
satisfaction_by_brand = df_non_zero_reviews.groupby('brand')['reviews_rating_number'].mean().sort_values(ascending=False)
col1.bar_chart(satisfaction_by_brand)
col2.write(satisfaction_by_brand)
================================================
FILE: src/extraction/coleta/__init__.py
================================================
================================================
FILE: src/extraction/coleta/items.py
================================================
# Define here the models for your scraped items
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/items.html
import scrapy
class ColetaItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
pass
================================================
FILE: src/extraction/coleta/settings.py
================================================
# Scrapy settings for coleta project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# https://docs.scrapy.org/en/latest/topics/settings.html
# https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
# https://docs.scrapy.org/en/latest/topics/spider-middleware.html
BOT_NAME = "coleta"
SPIDER_MODULES = ["coleta.spiders"]
NEWSPIDER_MODULE = "coleta.spiders"
# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36"
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32
# Configure a delay for requests for the same website (default: 0)
# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16
# Disable cookies (enabled by default)
#COOKIES_ENABLED = False
# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False
# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
# "Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8",
# "Accept-Language": "en",
#}
# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
# "coleta.middlewares.ColetaSpiderMiddleware": 543,
#}
# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
# "coleta.middlewares.ColetaDownloaderMiddleware": 543,
#}
# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
# "scrapy.extensions.telnet.TelnetConsole": None,
#}
# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
#ITEM_PIPELINES = {
# "coleta.pipelines.ColetaPipeline": 300,
#}
# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False
# Enable and configure HTTP caching (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = "httpcache"
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = "scrapy.extensions.httpcache.FilesystemCacheStorage"
# Set settings whose default value is deprecated to a future-proof value
TWISTED_REACTOR = "twisted.internet.asyncioreactor.AsyncioSelectorReactor"
FEED_EXPORT_ENCODING = "utf-8"
================================================
FILE: src/extraction/coleta/spiders/__init__.py
================================================
# This package will contain the spiders of your Scrapy project
#
# Please refer to the documentation for information on how to create and manage
# your spiders.
================================================
FILE: src/extraction/coleta/spiders/notebook.py
================================================
import scrapy
class NotebookSpider(scrapy.Spider):
name = "notebook"
allowed_domains = ["lista.mercadolivre.com.br"]
start_urls = ["https://lista.mercadolivre.com.br/notebook?sb=rb#D[A:notebook]"]
page_count = 1
max_page = 10
def parse(self, response):
products = response.css('div.ui-search-result__wrapper')
for product in products:
prices = product.css('span.andes-money-amount__fraction::text').getall()
yield {
'brand': product.css('span.poly-component__brand::text').get(),
'name': product.css('a.poly-component__title::text').get(),
'seller': product.css('span.poly-component__seller::text').get(),
'reviews_rating_number': product.css('span.poly-reviews__rating::text').get(),
'reviews_amount': product.css('span.poly-reviews__total::text').get(),
'old_money': prices[0] if len (prices) > 0 else None,
'new_money': prices[1] if len (prices) > 1 else None
}
if self.page_count < self.max_page:
next_page = response.css('li.andes-pagination__button.andes-pagination__button--next a::attr(href)').get()
if next_page:
self.page_count += 1
yield scrapy.Request(url=next_page, callback=self.parse)
================================================
FILE: src/extraction/scrapy.cfg
================================================
# Automatically created by: scrapy startproject
#
# For more information about the [deploy] section see:
# https://scrapyd.readthedocs.io/en/latest/deploy.html
[settings]
default = coleta.settings
[deploy]
#url = http://localhost:6800/
project = coleta
================================================
FILE: src/transformLoad/main.py
================================================
# Vamos importar o que precisamos
import pandas as pd
import sqlite3
from datetime import datetime
# Definir o caminho para o arquivo JSONL
df = pd.read_json('data/data.jsonl', lines = True)
# Setar o pandas para mostrar todas as colunas
pd.options.display.max_columns = None
# Adicionar a coluna _source com um valor fixo
df['_source'] = "https://lista.mercadolivre.com.br/notebook"
# Adicionar a coluna _data_coleta com a data e hora atuais
df['_datetime'] = datetime.now()
# Tratar nulos
df['old_money'] = df['old_money'].fillna('0')
df['new_money'] = df['new_money'].fillna('0')
df['reviews_rating_number'] = df['reviews_rating_number'].fillna('0')
df['reviews_amount'] = df['reviews_amount'].fillna('(0)')
# Garantir que estão como strings antes de usar .str
df['old_money'] = df['old_money'].astype(str).str.replace('.', '', regex=False)
df['new_money'] = df['new_money'].astype(str).str.replace('.', '', regex=False)
df['reviews_amount'] = df['reviews_amount'].astype(str).str.replace('[\(\)]', '', regex=True)
# Converter para números
df['old_money'] = df['old_money'].astype(float)
df['new_money'] = df['new_money'].astype(float)
df['reviews_rating_number'] = df['reviews_rating_number'].astype(float)
df['reviews_amount'] = df['reviews_amount'].astype(int)
# Tratar os preços como floats e calcular os valores totais
# Manter apenas produtos com preço entre 1000 e 10000 reais
df = df[
(df['old_money'] >= 1000) & (df['old_money'] <= 10000) &
(df['new_money'] >= 1000) & (df['new_money'] <= 10000)
]
# Remover as colunas antigas de preços
# Conectar ao banco de dados SQLite (ou criar um novo)
conn = sqlite3.connect('data/mercadolivre.db')
# Salvar o DataFrame no banco de dados SQLite
df.to_sql('notebook', conn, if_exists='replace', index=False)
# Fechar a conexão com o banco de dados
conn.close()
# Configurar pandas para mostrar todas as colunas
# Exibir o DataFrame resultante
gitextract_jsk0yvsl/
├── .gitignore
├── README.md
├── data/
│ └── data.jsonl
├── requirements.txt
└── src/
├── dashboard/
│ └── app.py
├── extraction/
│ ├── coleta/
│ │ ├── __init__.py
│ │ ├── items.py
│ │ ├── settings.py
│ │ └── spiders/
│ │ ├── __init__.py
│ │ └── notebook.py
│ └── scrapy.cfg
└── transformLoad/
└── main.py
SYMBOL INDEX (3 symbols across 2 files)
FILE: src/extraction/coleta/items.py
class ColetaItem (line 9) | class ColetaItem(scrapy.Item):
FILE: src/extraction/coleta/spiders/notebook.py
class NotebookSpider (line 4) | class NotebookSpider(scrapy.Spider):
method parse (line 11) | def parse(self, response):
Condensed preview — 12 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (145K chars).
[
{
"path": ".gitignore",
"chars": 5,
"preview": ".venv"
},
{
"path": "README.md",
"chars": 266,
"preview": "# Web Scraping Mercado livre case Samsung\n\n<p align=\"center\">\n <a href=\"https://suajornadadedados.com.br/\"><img src=\"pi"
},
{
"path": "data/data.jsonl",
"chars": 120598,
"preview": "{\"brand\": \"LENOVO\", \"name\": \"Notebook Lenovo Ideapad B330-15ikb I3 7° 8gb Ddr4 240gb Ssd\", \"seller\": \"Por GSOLD ELECTRO "
},
{
"path": "requirements.txt",
"chars": 23,
"preview": "pandas\nstreamlit\nscrapy"
},
{
"path": "src/dashboard/app.py",
"chars": 1849,
"preview": "# import\nimport streamlit as st\nimport pandas as pd\nimport sqlite3\n\n# Conectar ao banco de dados SQLite\nconn = sqlite3.c"
},
{
"path": "src/extraction/coleta/__init__.py",
"chars": 0,
"preview": ""
},
{
"path": "src/extraction/coleta/items.py",
"chars": 262,
"preview": "# Define here the models for your scraped items\n#\n# See documentation in:\n# https://docs.scrapy.org/en/latest/topics/ite"
},
{
"path": "src/extraction/coleta/settings.py",
"chars": 3321,
"preview": "# Scrapy settings for coleta project\n#\n# For simplicity, this file contains only settings considered important or\n# comm"
},
{
"path": "src/extraction/coleta/spiders/__init__.py",
"chars": 161,
"preview": "# This package will contain the spiders of your Scrapy project\n#\n# Please refer to the documentation for information on "
},
{
"path": "src/extraction/coleta/spiders/notebook.py",
"chars": 1359,
"preview": "import scrapy\n\n\nclass NotebookSpider(scrapy.Spider):\n name = \"notebook\"\n allowed_domains = [\"lista.mercadolivre.co"
},
{
"path": "src/extraction/scrapy.cfg",
"chars": 255,
"preview": "# Automatically created by: scrapy startproject\n#\n# For more information about the [deploy] section see:\n# https://scrap"
},
{
"path": "src/transformLoad/main.py",
"chars": 1916,
"preview": "# Vamos importar o que precisamos\nimport pandas as pd\nimport sqlite3\nfrom datetime import datetime\n\n# Definir o caminho "
}
]
About this extraction
This page contains the full source code of the lvgalvao/WebScraping-2025-Jornada-Aovivo GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 12 files (127.0 KB), approximately 45.0k tokens, and a symbol index with 3 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.