ATI.su User Data Scraping -- 2

@kamran2012

Hey, Я подготовлю Python-скрипт для выгрузки данных компаний через ATI API — наименование, статус, контакты сотрудников, рейтинг — и парсинг корпоративных сайтов для сбора парка, грузов и регионов. Итог: Excel-файл и отчёт о ходе парсинга. Для корпоративных сайтов я применю structured extraction с fallback на LLM-парсинг, чтобы корректно вытягивать данные даже с нестандартных вёрсток. Questions: 1) Сколько примерно компаний нужно обработать? 2) Лицензия API уже оформлена, или нужна помощь с подключением? Looking forward to talking through the details. Kamran

@tangramua

Dear ,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in Python, Web Scraping, Data Scraping, Data Extraction, Data Analysis, Automation, API Development, Data Collection and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@AliGhazanfar2

Hi Sir, Get a free sample first , Lets get connect over a chat. I have more than 9 years of experience in building custom platforms in python. I will walk through to my work samples as well. I am online right now. Thanks Ali

@mobiwebsolutions

✋ Привет!!! ✋ Цель проекта: - Автоматизировать выгрузку данных через ATI API, обогатить данные с защищенных сайтов и создать структурированный файл Excel с высоким уровнем доступа. Я внимательно прочитал описание проекта и понимаю, что приоритетом являются точные контакты пользователей, сбор данных компаний через API ATI, парсинг сайтов для автопарка, видов грузов и регионов, а также итоговый Excel и отчет по обработке. Имея более 9 лет опыта работы в качестве Full Stack разработчика, я отлично подхожу для создания надежного парсера и точной обработки данных. 1. Разработать парсер через ATI API с выгрузкой компаний, контактов, рейтингов и конфиденциальных данных. 2. Собрать данные с сайтов по автопарку, видам грузов, регионам и заполнить структурированный Excel. 3. Предоставить тестирование, управление базой данных, исходный код, запуск процедуры и отчет по дубликатам и пропускам. Я выполнял похожие проекты по интеграции API, очистке данных и автоматизации сбора данных. С нетерпением жду возможности пообщаться с вами и заключить сделку. С уважением, Элиша Мариам!

@albertc1996

How much can my skills in designing scalable systems help your projects? Hello, with over [years of experience] in Python development, I’m seeking opportunities to contribute to your challenging projects. My expertise lies in building scalable applications using Django and Flask. I’m committed to improving performance and delivering efficient APIs, confident I can add real value to your team. Looking forward to a conversation.

@Microlent

The tricky part here isn’t pulling data from the API, it’s keeping everything consistent once you start merging API data with website parsing. That’s usually where duplicates, broken contacts or mismatched rows creep in. I’ve worked on similar data extraction systems using Python + Selenium where structured data had to be cleaned, deduplicated and exported accurately. Here’s a relevant example https://www.freelancer.com/portfolio-items/11349812-web-scraping-automation I’d approach this in two stages, first pull clean company + contact data from the ATI API, then process each company website separately for fleet, goods and regions. Final step is merging with strict schema validation so every row stays aligned. Contacts and company names will be normalized to avoid duplicates, and categories like transported goods will be mapped exactly to your required structure. Output will be a clean Excel file plus a reusable script with instructions, and a short report covering processed records, duplicates and any gaps. I’ve handled similar pipelines where accuracy matters more than volume, so validation checks will be built in before final export. Timeline around 3-5 days depending on API limits and website variability. One thing to clarify early, do the company websites follow any consistent structure or are they completely varied? Best, Jenifer

@imfarrukh47

Hi I will scrape the requried data form the given website using python and selenium. I would like to discss the project with you. I also want to know if this is repeatable project or one-time or do you need source code for it

@adily1

Hey , looking over what you need for Data Collection, Data Analysis, API Development, Python, Automation, Data Scraping, Web Scraping and Data Extraction, I noticed you’re in a perfect spot to use a specific approach that completely eliminates the usual headaches people run into with these types of projects. Most freelancers will just do the bare minimum, but they completely miss a small structural tweak that actually makes the final result run flawlessly and saves you a ton of time. I’m not here to just bid and wait. I’ve already visualized the fix for that one specific gap in your project that usually drags these projects out for weeks, and keep you from looping back for revisions later. If you’re serious about getting this done right the first time without the back-and-forth, hit me up in the chat, and I’ll show you exactly what I mean I guarantee it’ll be the most helpful 5 minutes of your day and will take the entire weight of this project off your shoulders.

@nin1

? Как профессионал в области данных, я могу предложить решение для автоматизированной выгрузки информации с биржи ATI и структурирования её в Excel. С использованием API ATI я обеспечу точную и эффективную обработку данных Я извлеку информацию о наименовании компании, стране регистрации, статусе, контактах сотрудников, рейтинге, количестве сотрудников и корпоративном сайте Дополнительно, пройдя по корпоративным сайтам, добавлю информацию о парке подвижного состава, профиле перевозимых грузов, регионах и описании деятельности компании. Все данные будут организованы в Excel Могу ли я уточнить, есть ли предпочтения по типам данных или особенностям фильтрации информации?

@billybryan98

Hello there, I hope you are doing well. I am an independent data automation specialist with deep experience in building API-driven scrapers and reliable Excel exports. I structure end-to-end data flows that authenticate with and pull data from APIs (licensing provided), cleanly map fields, and deliver a single, well-formatted workbook ready for analysis. My approach focuses on accuracy of names and contact details while matching every required field to your schema. I’ve delivered similar projects where I extracted company records, regions, and fleet/operations data, then extended crawling to corporate sites for fleet types, freight profiles, regions, and short descriptions. I guarantee precise contact data, and I structure the output so cargo types (Consolidated, Dangerous, and General freight) appear exactly as requested. I’ll also provide a concise parsing progress report detailing processed companies, duplicates, gaps, and root causes. I can implement this as a runnable script (Python preferred) with a brief run guide for re-launch, plus the fully filled Excel file. If you’d like, I’ll tailor the run instructions to your environment and licensing setup. Best regards, Billy Bryan

@craigd43

I'm Craig, an experienced freelance developer with a specialization in web scraping using Python, which I believe is the ideal tool to automate your data extraction from ATI.su. I understand that your primary concern is accurately capturing and filling out each user's name and contacts, and I assure you that I will make sure all the data pulled through my script is properly aligned to match this concern. Having developed a deep interest in data analysis and collection, my proficiency extends to comprehensive processing of acquired data into a clear excel format. My attention to detail, paired with my expertise in Python guarantees a precise extraction of the required information including company names, registration countries, status, employee contacts, reliability ratings, number of employees and corporate websites. My commitment is not only restricted to efficient scraping but also prioritizing client satisfaction. To this end, I will provide you a comprehensive report tracking the progress of each parsing session as well as tackling any possible duplicates or missing information. After the scraping process I will incorporate an intuitive script with clear instructions for future use-based on your preferences. With me on your team, certainty and excellence are promised throughout your project.

@matheussilva114

Hi, I have checked the details. I am a senior engineer with over 7 year of experience on Python, Web Scraping, Data Scraping, Data Extraction, Data Analysis, Automation, API Development, Data Collection. Please visit my profile to view my latest projects, certificates, and work history. Best, Matheus Regards, Matheus

@rogelitoc

Hello, In my opinion, the problem of this project is that the data extraction and aggregation from the ATI API needs to be efficiently automated while ensuring data accuracy and completeness. I will develop a Python-based script utilizing libraries like Requests for API calls and Pandas for data manipulation. The architecture will consist of a modular approach: one module for API data retrieval, another for web scraping corporate sites, and a final one for data aggregation into an Excel file. I will implement error handling for edge cases, especially for contact details, while reusing any existing data validation logic. The deliverable will be a fully functional script, a comprehensive Excel workbook containing all required fields, and a concise report detailing the parsing process, including processed companies and any anomalies encountered. I have successfully completed similar data aggregation projects in the past. I can start immediately. Regards.

@daremat

Hello, I have extensive experience building automated data extraction and aggregation tools using Python. I can connect to the ATI API, retrieve company details and employee contacts, and enrich the data by scraping corporate websites for fleet, cargo types, activity regions, and company profiles. The final output will be a single well-structured Excel workbook matching your specified columns, with a brief parsing report. I will provide the script and instructions for easy reruns. Let's discuss your project in more detail. Best regards, Darko.

@Dimitarg1

Я могу помочь с автоматизированной выгрузкой данных с ATI через официальный API и собрать результат в аккуратный Excel-файл с нужной структурой. Сделаю парсер на Python: получение данных компаний, контактов сотрудников, рейтинга, статуса, сайта, а затем дополнительный сбор информации с корпоративных сайтов по парку, типам грузов, регионам и описанию деятельности. Особое внимание уделю корректности Ф. И. О., телефонов и e-mail каждого пользователя, так как это ключевой критерий проверки. Для типов грузов отдельно предусмотрю категории: сборные, опасные и комплектные грузы. Также добавлю обработку дублей, пропусков, ошибок API/сайтов и сформирую краткий отчёт по результатам парсинга. На выходе вы получите рабочий скрипт с инструкцией повторного запуска, заполненный Excel без смешанных столбцов и отчёт: сколько компаний обработано, где были дубли или недостающие данные. Готов реализовать решение так, чтобы его можно было удобно запускать повторно после оплаты API-доступа.

@dmytrom99pro

Hello, As an experienced and skilled freelancer, I want to leverage my expertise in data extraction and Python programming to tackle your challenging project. Over the past decade, I have successfully built scalable SaaS platforms, demonstrating my ability to deliver end-to-end solutions that meet complex requirements within tight deadlines. Specifically, I have extensive experience creating scraping algorithms that can efficiently extract data from various APIs and web sources, a skill that is indispensable for your project. Furthermore, my proficiency in building interactive systems and conducting real-time data synchronization aligns perfectly with the need to collect and consolidate information from different sources while maintaining formatting integrity. My systems prioritize low latency, high throughput and clean UX, critical factors for a large-scale parsing task like yours. Finally, let me assure you of my commitment to excellence. I will not only deliver a well-organized and error-free Excel file that precisely aligns with your requested structure but also provide periodic progress updates alongside a concise report detailing the parsing process(step'=>$step), potential duplicates, any data gaps and reasons assigned. My aim is to empower you with a finished product that exceeds expectations. I look forward to leveraging my skills in service of your project’s success. Thanks!

@camerone6

Hello, Greetings , Good morning! I am skilled mobile developer with skills including Data Analysis, Data Scraping, Automation, Data Extraction, Python, Web Scraping, API Development and Data Collection. Please contact me to discuss more regarding this project. Thanks

@muzammilf0

Здравствуйте, Я внимательно изучил ваше задание. Могу автоматизировать сбор данных через API ATI и аккуратно сформировать единый Excel-файл. Что я сделаю: Получу данные компаний, контакты и рейтинги через API Пройду по корпоративным сайтам и соберу парк, виды грузов, регионы и описание Обеспечу точное заполнение ФИО, телефонов и email (приоритет) Сформирую чистый Excel без ошибок в структуре Предоставлю отчёт по парсингу (обработано, дубли, пропуски) Передам скрипт (Python) с инструкцией для повторного запуска Вопрос: есть ли ограничение по количеству компаний? Best regards, Muzammil Fareed

@jeremyc85

Hello, With strong experience in API integrations, data extraction, and structured automation workflows, I offer a practical approach that combines reliable parsing with clean data normalization and export. I believe my background in Python-based data collection, web scraping, enrichment pipelines, and Excel automation makes me a strong fit for this project. In addition to building a parser to pull company records from the ATI API and consolidate them into a structured Excel workbook, I can help automate website-level enrichment for fleet data, cargo profiles, operating regions, and company descriptions while maintaining special attention to the accuracy of contact names and employee details. On top of that, I can structure validation checks for duplicates, missing data, and column consistency, and provide a reusable script with clear rerun instructions plus a summary report covering processed records, omissions, and data quality observations. My work philosophy prioritizes accuracy, clean data structure, and dependable automation. For a project like this, parsing is only half the work - normalization and validation are what make the output usable. I’d be glad to discuss similar data extraction projects I’ve handled and the best approach for delivering this efficiently. Thanks!