Fragrantica Database CSV Extraction

@onkarkulkarni8

Hi, I checked your "Fragrantica Database CSV Extraction" project description, it looks like the focus is on delivering a clean, responsive website that works well across all devices. I prefer understanding the expected layout and user experience first, then building pages that closely match the design while keeping the code organized and easy to maintain. Feel free to share the design or current website, and I'll suggest the best implementation along with a realistic timeline. Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@muneeb6767

I can build a reproducible Python Scrapy/BeautifulSoup scraper for the factual fragrance catalogue, extracting exactly your nine CSV fields while cleaning HTML, removing duplicates, and keeping direct image URLs only. I’ll also include a sanity-check process against the live listings and structure the code so it can be rerun when the site changes.

@belarjsoufiane20

Hi, I can help build a clean, reproducible fragrance catalogue scraper focused strictly on the requested factual fields. I’ll structure the final CSV exactly as specified: id, name, brand, gender, release_date, description, accords, notes, and image_url, with no reviews or personal data included. I’m experienced with Python, BeautifulSoup/Scrapy, pandas, data cleaning, and large-scale web datasets. I’ll ensure the extracted text is cleaned, duplicates are removed, fields are consistently formatted, and image URLs are retained without downloading the images. I can also provide a reusable script so the extraction can be repeated if the permitted data source changes. I’ll perform quality checks and spot-check sample records against the source before final delivery. I’ll also respect Fragrantica’s applicable terms and access restrictions rather than bypassing them. Best regards, Soufiane

@mahads31

With a strong background in data processing and programming languages such as PHP and Python, I have the expertise to not just complete this one-time scrape project for you, but also assure that it's future-proof. My keen understanding of system architecture ensures that the code I write for you can be easily reproducible, enabling you to run it even if Fragrantica makes changes in their structure in the future. I have a proven track record of delivering clean and precise datasets with an eye for detail. I understand the significance of maintaining well-structured CSV files without any irrelevant or duplicate information, which aligns perfectly with your requirements. I can leverage my skills in data extraction, cleansing, and proficient knowledge of Scrapy or BeautifulSoup to gather all the specific details you need (id, name, brand, gender, release_date, description, accords, notes, image_url) without any clutter. Moreover, before handing over the final well-structured CSV file to you, I promise to meticulously verify a few random entries against the live site to ensure everything aligns correctly. My goal is not just to meet your expectations but to surpass them by delivering reliable solutions for long-term use. Choose me and I guarantee a seamless experience throughout this project along with invaluable deliverables that can help further your business growth.

@soniaashfaq334

Hi, I can build a clean, reproducible scraper and deliver the complete fragrance catalogue in the exact CSV structure you requested. Extract all required fields in the specified order Clean text and remove duplicates/HTML clutter Include direct image URLs only Ensure accurate, structured CSV output I’m experienced with tool web scraping and data cleaning, and I can focus on accuracy and reproducibility. Best regards, Khush

@albertc1996

You need a complete Fragrantica catalogue extraction that is accurate, deduplicated, and delivered in the exact CSV structure you specified—not just a quick scrape that happens to collect some pages. The main challenge here is reliably discovering every fragrance listing while keeping catalogue fields consistent, handling missing values, and avoiding reviews or user-generated data entirely. I have 5+ years of Python backend experience with Django/DRF and have built data-intensive systems for automation, analytics, and large-scale PDF processing. I’m comfortable designing reliable extraction workflows with validation and structured output. One detail I’d clarify before starting: should accords and notes be stored as delimited values within each CSV cell, or do you have a preferred format for those fields? Also, should release_date remain exactly as displayed when unavailable, or should missing dates be left blank? Would you like me to proceed with the extraction using your exact nine-column schema?

@tyronet2

You need a complete, deduplicated fragrance catalogue export from Fragrantica with a reproducible scraper and a CSV that matches your required schema exactly. I’ve built Python data-extraction and processing workflows where completeness, normalization, and rerun safety mattered as much as the scrape itself. I’d use Scrapy for structured crawling, with isolated parsing logic for name, brand, gender, release date, description, accords, notes, and direct image URL, then normalize text and remove duplicate product records before export. I’d also add request pacing, retry handling, logging, and a clear entry-point command so the scraper can be rerun later with minimal changes. Before delivery, I’ll spot-check random rows against the live listings and document any fields that are genuinely absent on source pages rather than inventing values. Do you want the `id` field based on Fragrantica’s own page/product identifier or a sequential ID generated in the export?

@adriank06

Hi, I can handle the one-time extraction and provide a clean, structured CSV with exactly the fields you listed. I’ll collect the fragrance catalogue information, clean the text, remove duplicates, and keep the image field as the direct URL without downloading the images. The scraper will be written in Python and kept reproducible so it can be adjusted if the site structure changes later. I’ll also do a random spot-check against the live listings before delivery to make sure the extracted data matches the source. I can focus strictly on the requested catalogue information and exclude reviews and personal data. Best regards,

@iterativeTech

As a seasoned AI and Cloud Data Engineering specialist, I am uniquely positioned to deliver the Fragrantica Database CSV Extraction you're seeking. My core services align perfectly with your needs, particularly in the realms of AI-driven business intelligence, scalable ETL/ELT pipelines, and Python-scripting for data processing. These exact skills will enable me to gather precisely the details you've requested (brand, gender, release_date, description, accords, notes, image_url) in a clean and well-structured couplet-separated format. Having worked across various industries like finance and healthcare has honed my ability to adapt to different datasets. I also prioritize robustness and long-term reliability as evidenced by my focus on building reproducible AI solutions that can handle possible future changes on Fragrantica. This approach guarantees that even if their data structure evolves over time, your extraction process remains smooth without any hiccups. In addition to delivering on the technical side of this project, I bring a business-first mindset to my work. This means that I understand the importance of your requirement for cost-efficiency and ROI generation from data projects. My skillset allows me not just to produce the CSV file you require but also to offer insights into its contents through interactive dashboards using Power BI or Tableau.

@petropankovdev

Hi, A one-time full pull of Fragrantica into a single CSV with exactly those nine columns, in that order: id, name, brand, gender, release_date, description, accords, notes, image_url. The image field stays a direct URL, nothing downloaded or embedded. How I would run it: - Scrapy spider walking the brand index, then every designer page, then each perfume page. That path reaches the whole catalogue rather than only what on-site search returns. - Text cleaned in the item pipeline: HTML tags stripped, line breaks collapsed, accords and notes normalised to one consistent separator so the CSV opens straight in Excel or pandas. - Dedupe on the perfume id, so a listing reachable from two brand pages lands once. - Throttling plus resume, so an interrupted run continues instead of starting over. Plain Python, re-runnable with one command when Fragrantica changes its markup. Before the full crawl I will scrape one brand, roughly 50 listings, and send you that CSV so you can check the columns and the text quality against the live site. If something is not what you expected, we fix it before I burn the whole run. For the sanity check at hand-off I will pull random rows, put them side by side with the live pages, and send that comparison together with the file. Relevant work: I have delivered a full product-card catalogue backup from a large retail site, exported to structured CSV that fed straight into another system, and a large multi-source directory harvest with the same cleaning and dedupe problem. On this account I have one completed project, rated 5 out of 5, delivered on time and on budget. Outside the platform, 15 merged pull requests into third party open source projects, mostly a 187 star Go security tool, each reviewed and accepted by the maintainers. Price 7500 INR, 5 days, source script included so the rerun is yours. Petro Pankov, BotCraft Group

@shikhajatav396

I can extract the complete fragrance catalogue into a clean, structured CSV with the exact required columns and a reproducible Python Scrapy/BeautifulSoup script. I have 5+ years - Python, Web Scraping, Data Extraction, CSV/Data Processing and automation, with proper validation and duplicate checks. Please open the chat window so that I can share my portfolio and we can proceed further on this project. In addition to your project needs, I'll provide you with clean source code, free bug patches, and maintenance. I am awaiting your positive response. Regards Shikha

@SmartDevLabs

I'll extract every Fragrantica listing with all 9 columns - id, name, brand, gender, release_date, description, accords, notes, image_url. Approach: - Python + BeautifulSoup for clean, reproducible extraction - Proper pagination and text normalization (no HTML, no duplicates) - Direct image URLs only Send me sample URLs and I'll deliver spot-checked sample rows before payment. The key challenge: handling Fragrantica's page structure and client-side rendering to capture everything completely. Delivery: within 3 hours of award. Does the script need auto-pagination, or one-time run? I offer a competitive flat rate with payment held in escrow until you verify the CSV accuracy.

@CliveMSoftware

I'll build a robust Scrapy spider that crawls Fragrantica's fragrance catalogue and extracts all nine columns in the exact order you specified. The script will handle pagination, clean all HTML tags and whitespace from text fields, deduplicate records by fragrance ID, and save everything to a single CSV. I'll include error handling for missing fields and make the script fully reproducible so you can re-run it anytime. Before delivery, I'll validate 10-15 random entries against the live site to confirm accuracy, then hand over the CSV and commented Python code so you own the full solution.

@RyanF172

We have over 5 years experience with similar projects for data extraction. You're looking to scrape every fragrance listing from Fragrantica and deliver a structured CSV with specific columns, ensuring clean text without user reviews or personal data. To approach this, I would use Python with Scrapy or BeautifulSoup to create a reproducible script. This will guarantee that you can easily rerun it if Fragrantica updates their site. I will ensure the CSV is meticulously structured as per your requirements and perform spot checks against live entries to confirm accuracy. Deliverables: - Complete CSV file with required columns - Reproducible scraping script - Cleaned text with no HTML or duplicates - Verification of random entries against the live site - Clear communication throughout the process I am happy to share relevant examples of my work. Let’s discuss any additional details to ensure a smooth execution. Regards, RyanF172

@LibraWS

Hi there, I'm a web developer based in Zadar, Croatia, and I'd like to bid on your Fragrantica scrape project. Here's what I'll deliver: A single, production-ready CSV with all fragrance listings—id, name, brand, gender, release_date, description, accords, notes, image_url—in the exact order you specified. The data will be clean (no HTML, no duplicates, no clutter), and I'll include a reproducible Python script using BeautifulSoup so you can rerun it anytime. Before handoff, I'll spot-check random entries against the live site to confirm everything aligns. Once you're satisfied, the job is done. I'm newer on the platform, so I'm offering milestone-based payment: you only release funds once you've verified the CSV meets your requirements. This removes your risk entirely. I work fast and stand behind quality—free revisions until it's right. Ready to get started?