Parsing opendatabot

Budget: 2000 UAH Deadline: 7 days

Hello, I created a similar parser for collecting companies from the registry by KVEDs: selection by activity code, extracting the name, EDRPOU, and phone number, recording directly into a Google Sheet on the required tab. I processed the mandatory phone field separately because it is not always returned cleanly in every record, and I cleaned duplicates.

If there are missing phone numbers in OpenDataBot for some records, it is worth immediately adding a collection from open sources by name or EDRPOU, which increases the completeness of the phone column by about 20-30%.

How many KVEDs are in the list and how many companies do you expect to get out, and is this a one-time parsing or do you need a regular run with table updates?

I suggest we get in touch; I will also outline a parser scheme for your KVED and Clients sheets, showing how the data will be structured.

Budget: 2000 UAH Deadline: 2 days

Good day. I specialize in automation and parsing in Python. I already have tools set up for your goals that will ensure accuracy and quality of data. I am ready to discuss the details and start working, feel free to write.

Budget: 3000 UAH Deadline: 3 days

Alex, in the Clients letter, in addition to the name, EDRPOU, and phone number, there is also the director, date of establishment, authorized capital, assets, income, tax debt, and status. The assets, income, and tax debt are taken not from the main company card, but from separate sections (financial reporting and debt verification), and not all companies submit financial reports, so these columns will not be filled for every counterparty; this is a feature of the source, not a script failure. The list of companies by KVED can be taken from the public classifier of opendatabot, without a request for a paid API. The same story applies to the phone number, as I have seen in the feed: it will not be in every card, I will add a collection based on the name or EDRPOU from open sources to increase the completeness.

I already have a similar pipeline parser plus recording in Google Sheets working: 12,932 products from a real store have been collected and are in a public sheet with an export in XLSX, example: https://freelancehunt.com/showcase/work/cataloglens-932-tovara-magazina-sobrannyie/2061489.html

I will first go through one or two KVEDs, show the first rows directly in the Clients letter, and upload the rest after your confirmation that the fields fit as needed. 3000 UAH and 3 days is for a typical volume, a few KVEDs and approximately up to a couple of thousand companies; if there are significantly more, I will provide a new figure as soon as I open the KVED letter. The letter is currently open only for viewing; editing access is needed to record the results.

Budget: 2000 UAH Deadline: 2 days

Good day, Alexander! I looked at your task and am ready to complete it. I have good experience in gathering information from this resource, feel free to reach out.

Budget: 2000 UAH Deadline: 4 days

Ready to take it on.
Need to clarify the order details, write to me!
I use Python, uv, GitHub, Docker.

Budget: 1000 UAH Deadline: 1 day

The task is to collect data from a list of queries in a table and export it to another one with a mandatory phone number. It is necessary to understand the source to choose the parsing method. My approach:
1. I will analyze the structure of the source (which website) and determine if Selenium is needed for dynamic content. 2. I will write a script in Python (BeautifulSoup or Selenium) for data collection, including phone numbers. 3. I will integrate the export of results into Google Sheets via API. 4. I will test on a sample and provide the finished script or filled table. I have experience with similar parsing using Selenium (link). Can I get access to the table? What is the data source website? Example of work: https://freelancehunt.com/showcase/work/selenium-veb-skraper-dlya-izvlecheniya-dannyih/1874474.html

Price: 1000 UAH
Deadline: 1 day

Budget: 5000 UAH Deadline: 5 days

Alexander, good afternoon. I looked at your table: on the "Kvedy" sheet, there is a list of codes, and the result needs to be compiled on the "Clients" sheet with a mandatory phone number for each contractor. I will implement this as a script in Node.js, which goes through each KVED, parses company cards from opendatabot (name, EDRPOU, phone, other necessary fields), and writes the result directly to Google Sheets via the Google Sheets API, based on the structure of the "Clients" sheet. I will add duplicate processing by EDRPOU and error logging if there is no phone number on the card, so you can see which records need to be checked manually. The script can be run again to update the database. The execution time is 5 days. Please clarify how many KVEDs are in the list and whether the table needs to be updated once or if there should be an option to restart the parsing in the future?

Budget: 3000 UAH Deadline: 2 days

Hello! Ready to complete this task quickly and efficiently. I will write a reliable script in Python (using requests/BeautifulSoup or Selenium if needed) that will scrape data based on the specified KVEDs and fill your Google Sheet, including the required phone numbers. I am ready to discuss the details, feel free to reach out!

Budget: 1000 UAH Deadline: 1 day

Good day, I am ready to complete your task quickly and efficiently. I have extensive experience in creating various parsers. Please write to me in private messages to discuss the details. I would be happy to help :)