Portugal Restaurant Data Scraper

@a4logic

Hello, As a leading web service provider, our company understands the value of clean and comprehensive data in driving effective decision-making. I am well-versed with the intricacies of web scraping and data extraction from platforms like Google using tools such as BeautifulSoup, Scrapy, and Selenium. Completing your project with high accuracy and quality will be my top priority. I bring profound knowledge of JavaScript to the table, a vital asset when it comes to efficiently handling and structuring large datasets. In addition to capturing contact details accurately, I understand the significance of correctly classifying restaurants offering a fixed-price menu and calculating their pricing breakdowns. My experience will ensure at least 95% accuracy in such classifications. Tagging each record with its district and municipality will ensure regional filtering capabilities, adding an extra layer of usability to your dataset. Finally, my aim is not just to scrape data for you but also imparting self-sufficiency by providing you with the script or notebook used for the project. You can trust me to develop this project in accordance with Google's terms of service while also using other supplementary public sources where necessary and clearly noting their origins. I believe in developing a long-term relationship based on mutual respect and trust. Let's turn this into a reality that will take your business to new reaches! Thanks!

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Comprehensive Restaurant Dataset for Portugal ❇️ Hi My Friend, I hope you are doing well. I've reviewed your project requirements and see you are looking for a dataset of restaurants in Portugal. You don’t need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for data scraping. I will gather all required information using Python tools like BeautifulSoup and Scrapy, ensuring a clean and structured dataset delivered within your budget. ➡️ Why Me? I can easily build your restaurant dataset as I have 5 years of experience in web scraping and data collection. My expertise includes data extraction, data cleaning, and database management. I also have a strong grip on technologies like Python, SQL, and various web scraping libraries, ensuring your project is handled efficiently. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Web Scraping ✅ Data Collection ✅ Python Programming ✅ BeautifulSoup ✅ Scrapy ✅ Data Cleaning ✅ CSV/Excel Formatting ✅ Database Management ✅ API Integration ✅ Data Analysis ✅ Error Handling ✅ Google Terms Compliance Waiting for your response! Best Regards, Zohaib

@techplusintl

Hi, To build a clean dataset of restaurants, I'll scrape the required information from Google Maps. This will include: - Capturing complete contact details for each restaurant. - Extracting ratings and review counts as displayed on Google. - Identifying fixed-price menu details if available. - Tagging each record with district and municipality for filtering. I will use Python with libraries like BeautifulSoup or Scrapy to ensure the scraping is efficient and compliant with Google’s terms of service. Ready to start once you provide access to any necessary accounts or further clarification. Thanks!

@justmian876

As a highly skilled and experienced web developer, I am confident that my team at BN-Droids Digital Services is perfectly suited to handle your Portugal Restaurant Data Scraper project. Our company specializes in data collection and mining, with a proven track record of extracting over a million entries daily, including from sites like Google. Using our expertise in Python and Scrapy, we can create a custom script or notebook for you that will provide all the necessary details about each restaurant, while effectively respecting Google’s terms of service. Being well-versed in web scraping techniques with tools like Selenium, we guarantee to deliver a clean and well-structured dataset with no duplicate records - organizing the information by district and municipality for regional filtering purposes as requested. We emphasize the importance of accuracy, which is why I assure you that mandatory entries will be fully populated where the data exists on Google - ensuring at least 95% correct classification for fixed-price menu status and pricing.

@vashishtrupinder

Hello,I can build this using Node.js with a robust scraping pipeline tailored for structured restaurant data extraction across Portugal. The system will use tools like Puppeteer for dynamic rendering, along with clean parsing logic to capture name, address, contact details, ratings, review counts, and “menu do dia” availability with pricing and meal components. Each entry will be tagged by district and municipality, deduplicated, and normalized into a consistent schema. Output will be a validated CSV/Excel file plus a fully documented, reusable script so you can rerun or scale it later. I can start immediately and deliver a production-ready dataset pipeline.

@kamran2012

Hey, I will build your Portugal restaurant scraper — contact details, ratings/reviews, and fixed-price menu detection — delivering a clean CSV tagged by district and municipality, plus the full Python script for reruns. For the "menu do dia" classification, I will parse structured snippets and menu pages to detect stage combinations (Plate+Drink, etc.) and prices, using pattern matching tuned to Portuguese-language menu formats for that 95%+ accuracy target. Questions: 1) Do you have a target restaurant count or specific districts to prioritize first? 2) Should the script handle periodic re-scraping with diff detection for new/changed listings? Ready to start whenever you are. Kamran

@asifdwan

As a dedicated and experienced freelancer, I can assure you of clean, efficient data scraping tailored to your needs. My extensive track record of working with complex websites, including those with advanced ant-bot protection, positions me perfectly to handle this Portugal Restaurant Data Scraper project. Comfortable with tools like BeautifulSoup, Scrapy and Selenium, I will extract comprehensive restaurant data for you while maintaining Google's terms of service. Not only will I ensure that all the contact details and rating information are successfully collected but I'll go above and beyond to classify each restaurant for the fixed-price menu status and pricing. My aim is always to surpass client expectations and deliver projects that are accurate, reliable, and usable. Furthermore, a robust system is indispensable for any data project. In line with this understanding, I provide not just the final scraped dataset but also the scripts or notebooks used specifically built on renowned technologies like Python. My commitment to post-delivery assistance allows you to rerun the scrape whenever necessary. The strength of my experience combined with my dedication guarantees a high-quality outcome. Let's chat about how I can best cater to your unique needs!

@salmaakternisa

I can build a reliable Python scraper using BeautifulSoup to collect accurate Portugal restaurant data exactly as required, with clean, well-commented code for easy use. I have strong experience in web scraping and data extraction, ensuring fast delivery and high-quality results.

@bytessolution

As a seasoned data scraper and analyst, my extensive experience in the field (over 6 years) has equipped me with the expertise you require for this project. Having worked on similar projects i.e scraping restaurants from Google Maps, I can assure you that my results are always accurate, reliable, and specifically tailored to meet your needs. Leveraging advanced skills such as Python, BeautifulSoup, Scrapy etc., I am confident in my ability to collect complete contact information (name, address, phone, email or website if listed), accurately extract ratings and review counts without any loss of data. Importantly, my approach is always respectful of Google's terms of service, ensuring full compliance throughout the entire process. You can rest assured that my dedication to quality is unparalleled; within the given timelines, I guarantee a minimum of 95% categorization accuracy for fixed-price menu status and pricing (which we better off than most). My comprehensive deliverables will include a CSV or Excel file containing one row per restaurant with all required fields clearly labelled along with the script or notebook used so you can readily rerun the scrape if needed. Enable me to translate SPAGHETTI ANALYTICS into SWEET INSIGHTS.

@ShaikhAneesa

Hello, I have carefully reviewed your project requirements to build a structured dataset of restaurants in Portugal by scraping Google for contact details, ratings, reviews, and fixed-price menu information. Let's chat and discuss it further. To handle your project, I will start with utilizing Python along with BeautifulSoup for web scraping. I will extract the necessary information such as restaurant details, ratings, reviews, and fixed-price menu data. I will ensure no duplicates, populate all mandatory columns, and correctly classify fixed-price menu statuses. Deliverables will include a comprehensive CSV/Excel file with all required fields labeled clearly and the Python script/notebook used for scraping. Before signing-off my bid, I would like to ask a question, i.e., how many restaurants are you aiming to include in the dataset? Best Regards, Aneesa.

@hiberokpars

Hello, I will create a PHP script to automate your task. Please provide the details: the website URL, the list of fields to collect, or an example of the output. I have extensive experience in writing PHP scripts for automating data collection and posting. Please see my reviews for reference.

@iosifpeterfi

I'm Iosif Peterfi, 15+ years delivering practical data and security projects across Europe, turning public information into reliable datasets. This is my speciality Turning scattered public data into clean, governed datasets with repeatable quality controls and risk-aware workflows that scale across regions. You're building a Portugal restaurant dataset with complete contact details, Google ratings and review counts as shown, fixed-price menu status with price and inclusions, plus district and municipality tags. Deliver a single CSV/Excel and a reusable script/notebook; no duplicates; aim for 95% accuracy on fixed-price classification; note any enrichment origins and respect Google terms. Deliver a clean, deduplicated dataset with labeled fields and a retriable script/notebook. Provide a data dictionary and region tags to enable regional filters. Use clear validation rules to fill mandatory columns when data exists. Include a concise runbook and notes on source provenance. Outcome: accurate, scalable data you can act on, with reduced manual effort and lower business risk. Last quarter I helped a hospitality client build a regional restaurant dataset for Spain. We tackled noisy sources and duplicates, achieving 98% data completeness and cutting manual review by 60%. 3-5 business days. Happy to discuss scope alignment. Let's chat - I can walk you through my approach in 15 minutes.

@johnallenvillan1

Hello, your requirement to scrape complete restaurant records across Portugal from Google stood out, especially the need to classify “menu do dia” options with up to five stages. I’ve handled similar national‑scale scrapes and previously delivered a 40k‑row dataset for hospitality venues with fully verified contact details and rating metadata. I know the real challenge here is Google’s structure variability: phone numbers missing on Maps but present on Search, menus shown inconsistently, and location metadata not always clean. Handling these without triggering rate limits or losing data is where most scrapers fail. I will structure a Selenium‑based flow for dynamic elements, use BeautifulSoup for stable parse regions, and implement duplicate‑safe storage keyed on place IDs. I’ll add a classification routine to extract menu stages and pricing with confidence thresholds and tag each record with district and municipality using geocoded boundaries. I need to confirm your preferred data refresh frequency and whether you intend to run the script from a local machine or a server environment. The full dataset and script will be delivered cleanly documented. Sincerely, John allen.

@codefusion53

Hi, I understand you need a clean and reusable restaurant dataset for Portugal built from publicly available sources, with strong focus on contact details, Google rating data, and accurate identification of menu do dia availability, pricing, and included items. The key is balancing data quality, structure, and repeatability while keeping the collection process respectful and dependable. My solution is to build a Python based scraping workflow that gathers restaurant records, normalizes fields, removes duplicates, and enriches each entry with district and municipality tags. I would structure the logic to capture contact details, ratings, review counts, and detect fixed price menu signals with clear parsing rules for price and included stages. The final output will be a well labeled CSV or Excel file, along with the script or notebook so you can rerun the process later. Before delivery, I will run validation checks for duplicate removal, field completeness, sample based accuracy review for menu classification, and consistency testing across the exported dataset to ensure the file is clean and reliable. Best, Justin

@juanjosec63

Hi, I have strong experience in Python, web scraping, data mining, Selenium, BeautifulSoup, and building clean reusable data collection pipelines with deduplication and structured export to CSV or Excel. I can build a reliable scraper workflow that collects restaurant contact details, ratings, review counts, district and municipality tags, and fixed-price menu information with clear classification logic, while keeping the dataset clean, reproducible, and easy for you to rerun later from the included script or notebook. You can expect clear communication, fast turnaround, and a high-quality result that fits seamlessly into your existing workflow. Best regards, Juan

@durgesh8527

With over 12 years of full-stack development experience, I'm confident I can deliver the results you're looking for with your Portugal Restaurant Data Scraper project. Not only am I proficient in Python, which is highly suited to web scraping tasks, but my skills also extend to JavaScript, providing further flexibility for the assignment. Rest assured, I'm familiar with technologies like BeautifulSoup and Scrapy that you prefer and can certainly ensure respect for Google’s terms of service to prevent any violations. One of the most essential aspects of this project is ensuring data accuracy. With my strong attention to detail and rigorous testing approach, I guarantee no duplicate entries and at least 95% correct classification for fixed-price menus. I'll leverage my comprehensive knowledge of Google platforms and available public sources effectively to enrich the dataset where necessary while always howing transparency about any data origins in the code comments. Beyond the delivery of a clean CSV or Excel file, I'll make sure you are equipped for future reliability by giving you access to the script or notebook for self-management of subsequent scrapes. My commitment to on-time delivery and accessible service guarantees a positive project experience from start to finish. Let's talk strategy and get started on building this impressive database!

@nickyjohnl

Hello, I have strong experience building structured datasets from map-based sources, including restaurant and retail scraping projects using Python (Selenium, BeautifulSoup) with deduplication, geo-tagging, and enrichment pipelines. I’ve handled similar cases extracting ratings, review counts, and menu-related signals, then normalizing them into clean CSV datasets with high accuracy and reproducibility. For your project, I will collect restaurant data via controlled scraping and structured parsing, map each entry to district and municipality, and detect “menu do dia” using pattern matching and fallback sources when needed. The dataset will be validated for duplicates, completeness, and classification accuracy, and I will provide a reusable script with clear comments for future runs. Output will be a clean CSV or Excel file with all required fields consistently formatted. Could you confirm the expected scale of restaurants to be collected across Portugal? Also, do you want the script optimized for periodic updates or just a one-time full dataset generation? Regards, Nicky

@AvinaHSinha7

Hi there, I have strong experience in large-scale data scraping and building clean, structured datasets from sources like Google and public websites. I can collect restaurant data across Portugal including contact details, ratings, review counts, and menu do dia information with proper classification. I’ll also tag district and municipality, remove duplicates, and deliver a clean CSV along with a reusable Python script. I focus on accuracy and scalable scraping while keeping the approach stable and well-structured. Ready to start. Best regards, Avinash

@hdlan

Hello! I’m a skilled data entry professional from Vietnam. I can accurately and efficiently extract business details for Portugal-based restaurants from Google Maps, directories, and social media, and organize them into a CSV or Excel spreadsheet. Please refer to my similar projects https://www.freelancer.com/projects/web-scraping/Website-Contact-List-Scraping/ https://www.freelancer.com/projects/internet-marketing/Data-extraction-from-the-website I’m available online most of the time and respond to messages within 12-24 hours. Let's talk! Duong