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  • Parcing all the information from subscribers’ accounts on Instagram

    Data Parsing
    We parsing all the information of subscribers on Instagram.

    Parcing is the automation of the collection of information (in our case, all the information of subscribers from the accounts of the competitor).

    The information you get in the table: numbers, mail, name, account information, link, id, publications(col-vo) , subscriptions(col-vo) , subscribers(col-vo), whether the profile is closed, the availability of the avatar, whether there is verification and so on. (On some accounts some data may be hidden)

    The stages:
    1 . You give a link or username to the account from which you need to spark the audience.
    2nd We are doing parsing.
    Three We will send you a table with information.

    Up to 50,000 subscribers from one account!
    Maximum for one quark - 1 account!


  • Parking of chats in Telegram

    Data Parsing
    Parking is the automation of information collection (in our case, CA from competitor chats)

    The stages:
    1 . You send a list of chats with which you need to spart the audience.
    2nd Choose the Filters
    Three We perform parsing users according to the chosen criteria from these chats.
    4 . We send you a list of username or id. With each chat list with a separate file.


  • 7 USD

    Parsing data from OLX

    Data Parsing
    For parsing data from OLH I use pyhon with bs4 and selenium booklets, this will allow the parser to quickly work with the announcements.
    What can I spark from Olh? Yes, the phone number, photo, product description, etc.
    You can save it in any you convenient format (.json, .scv, .xlsx), in the general where you like.
    The ! ! ! The price of 300 UAH for 1000 SPARCHENY announced!!The !
    thank you
    #python #Parsing #parser #database #excel #cvs #json #xlsx #selenium #bs4 #olx #fast


  • 23 USD

    Tracking currency changes from the site and keeping history in JSON

    Data Parsing
    The task is to immediately inform the user of the changes to each currency on the site, as well as to fix these changes (with the date indication) in the json format.
    Solution: With the help of the Selenium parsing library I attach to each column in the table and track the changes every second. To check the last value in the dictionary, I add the last key and compare it with it.
    Feature: Due to the high cost of connecting to the API of cryptocurrency sites, parsing data from a page is the most profitable solution, although not the optimal.
    #python #Parsing #selenium #cryptocurrencies #scraping #html #analysis #cryptocurrencies


  • 11 USD

    OLX parser with numbers, with additional accounts

    Data Parsing
    Parser is implemented in Python using the library of selenium. The speed of the parser:
    - 2 to 3 ads per minute (with numbers)
    • 6-8 ads per minute (without numbers)
    The probability of IP ban is very low.


  • The Linkedin

    Data Parsing
    User parser from LinkedIn to CSV file


  • 11 USD

    Parking on auto.ria.com

    Data Parsing
    Parsing numbers of tel, links and prices from the site auto.ria.com + file download > 5000 pieces.

    #Parsing #scraping #Parsing #Parser #python #auto.ria.com #sparsy


  • 34 USD

    Parsers Olx

    Data Parsing
    Simple script for parsing the site olh.ua

    Parser collects the title, url, tel. Removes duplicates of numbers and brings all numbers to one register +380


  • 28 USD

    Parking of Telegram Users

    Data Parsing
    Parsing people from Telegram chats. There is the possibility to filter people according to different criteria (online in Telegram, privileges in chat and activity in Germany). The number of people is not limited, you can gather bases of 100,000 people. On the output we have a txt file with user logs.

    1 . Base of 40,000 people - 3 000 UAH
    The 2nd Base of 5,000 to 40,000 people - 1,800 UAH
    3 . Yuan up to 5,000 people - 1200 UAH

    So I’m selecting your target audience for further work with it!

    #Telegram #Telegram #Telegram #Telegram #Telegram #Telegram


  • 800 USD

    Automatic parser of goods with Allegro

    Data Parsing
    Goods with Allegro. He receives the search edition Allegro.pl, as well as detailed information about the goods.

    It is very easy to integrate with your site. The site will make the usual HTTP query for the parser and receive the data in JSON format. Parser is universal, it doesn’t matter on which CMS or engine the site is made.

    Now others have ceased to work the Allegro parser, and this parser works stable.

    The parser works “on summer”, i.e. it parsits the data with Allegro in real time when a request is made (from the site when the user enters a page).
    This ensures 100% data relevance and reduces the load on the server.

    #allegro #parser-Allegro #commodities #parser #parsing #web-parsing #Poland #Polish


  • Parking of contacts by cars.av.by

    Data Parsing
    Parser that collects data on the ads for the sale of cars.
    The speed is ~5,000 ads per minute. It works directly from the site.

    #Parsing #scrapy #scrapping #Python3 #python-scraping #webscraping #webscraping #webparts #parts #parts #collectorInformation #collector #parts #parts #parts #parts #parts #parts #parts #parts #parts #parts


  • Parking tripoli.land

    Data Parsing
    Parking by tripoli.land
    It works very quickly, collects all phone numbers, mail and addresses.

    #Parsing #scrapy #scrapping #Python3 #python-scraping #webscraping #webscraping #partsers #partsers #collectorInformation #collector #partsing #partsers #partsers #partsers #partsers #partsers