Data parsing
All my wishes have been fulfilled.
Thank you for the work.
Budget: 1000 UAH Deadline: 1 day
Good day!
I am interested in your project regarding image parsing from the website matematika-doma.org. I have experience in web scraping and programming in Python, particularly using libraries such as BeautifulSoup and Selenium.
I am ready to create a script that can collect all images, categorizing them by classes, subjects, authors, and sections, just like on the original site. My goal is to ensure the accuracy and structure of the data for further use.
Let's discuss the details so I can start working on the project.
I look forward to your response!
Budget: 1000 UAH Deadline: 1 day
Ready to perform your project with high quality
Contact us for clarification of the technical specifications
Budget: 1300 UAH Deadline: 2 days
Hello!
I have 2 years of experience in web scraping, so there shouldn't be any problems!)
I will be happy to help!
Budget: 1000 UAH Deadline: 2 days
Good afternoon, Alexander
Let's clarify all the details in private
Message me in private, we will discuss your parsing requirements in more detail
Best regards, Alexander
Budget: 800 UAH Deadline: 1 day
I will do it quickly and efficiently, contact me t_g dresscode_casual . . .
Budget: 1000 UAH Deadline: 1 day
Good day, I will quickly complete your order, please write in private messages for clarification of the terms of reference.
Budget: 1000 UAH Deadline: 1 day
Your task is easily accomplished in Python, ready to solve) to solve it will be enough to clarify some information
Budget: 2000 UAH Deadline: 2 days
Good day!
I have extensive experience in web scraping.
I will be able to complete the task quickly.
I will be happy to work with you.
Budget: 1000 UAH Deadline: 1 day
Hello, I am engaged in parsing, I can help you with the execution of this project. In what format do you need the result? Write to me in private.
Budget: 1000 UAH Deadline: 3 days
Good day.
I will download the photo, extensive experience in photo parsing.
I perform everything with quality.
Budget: 3000 UAH Deadline: 2 days
Hello. I am ready to write a script for parsing this website. Feel free to contact me.
Budget: 3000 UAH Deadline: 3 days
Good afternoon, Alexander! There are about 160,000 cards on the website. There are probably just as many photos. I will gather them quickly and efficiently at the specified rate, feel free to contact me!
Budget: 1000 UAH Deadline: 1 day
Good day, I have experience in developing parsers, I understand the essence of the project, I will execute it qualitatively and cheaply, feel free to contact me :)
Budget: 1000 UAH Deadline: 1 day
Hello!
I am interested in your project, I have extensive experience in asynchronous/multithreaded parsing (Requests, Websockets, AioHTTP, HTTPX, BS4) and emulating user actions (Selenium/Playwright). I use a personal pool of proxy servers for seamless and fast parsing.
Contact me to discuss the details and timelines for this project!
Budget: 1200 UAH Deadline: 1 day
Hello. The project is quite interesting, I am ready to start working on the project right now.
Budget: 1000 UAH Deadline: 1 day
Hello! I am working on Python development and I am ready to quickly and efficiently scrape images from the website. If you have any questions or details - feel free to write, I will be happy to help.
Budget: 1000 UAH Deadline: 1 day
Ready to complete
Ready to complete
Ready to complete
Ready to complete
Ready to complete
Ready to complete
Budget: 500 UAH Deadline: 7 days
Ready to take it on.
Write to discuss the order details.
I will implement it in Python.
Budget: 900 UAH Deadline: 1 day
Hello!
I am ready to perform quickly and efficiently according to your requirements. Experience of more than 4 years.
Budget: 700 UAH Deadline: 1 day
Good day. I will parse this website according to your specifications. Please contact me.
Budget: 1000 UAH Deadline: 1 day
I will collect everything thoroughly. Files + links to them....
I will collect everything thoroughly. Files + links to them....
Budget: 1000 UAH Deadline: 2 days
Ready to complete, you can send the link to the website for familiarization.
Budget: 600 UAH Deadline: 1 day
Good day. I have extensive experience in parsing. I need to clarify a few things to provide a clear price and timeline. Message me privately, I will do this as quickly and affordably as possible.
Добрий день, можливо буде більше сенсу просто парсити сайт при кожному запиті?
Таким чином не треба буде зберігати усю інформацію (яка ще можливо буде оновлюватись). Фактично, бот буде працювати так само
Good day! Two tasks need to be completed: 1. Develop a product parser from an external website (10–40 thousand items, marketplace) with structured data saved in MySQL for subsequent output in WordPress. 2. Install and configure n8n on VPS, as well as organize AI content processing: prompt setup, text rewriting, image processing, SEO optimization, and text checking for AI detection. You can estimate the cost of completing both the entire project and each task separately. .
It is necessary to perform parsing from Viber channels (Total number - 49 channels, about 80 thousand subscribers).
An independent service handler for Excel files is required for the existing microservices system. The task involves creating a reliable pipeline for receiving, validating, and transforming data from tables into a structured database format. Functional tasks: Development of an API based on gRPC for receiving processing commands and returning execution statuses. Implementation of file parsing logic: reading large volumes of data (XLSX), cleaning, type checking, and mapping to business models. Implementation of a data access layer (Repository/Unit of Work) for saving results in PostgreSQL via Entity Framework Core. Ensuring thread safety and efficient resource usage (especially when processing large files). Technical requirements: Platform: .NET 10. Architectural patterns: Dependency Injection, CQRS, modular project architecture. Communication: Strictly gRPC. Working with Excel: Use of efficient libraries (e.g., EPPlus, OpenXML, or similar of your choice). Modularity: Code should be organized so that the service is easily scalable and testable. Expected results: A fully functional microservice ready for deployment in a containerized environment. A clean codebase adhering to SOLID principles. Documented .proto files. Basic unit tests for critical data processing nodes. Candidate requirements: In your response, please specify: Your experience with .NET in microservices architecture. Examples of how you organize DI and modularity in your projects. Experience with Excel libraries in .NET. Willingness to work with gRPC contracts.
Good afternoon. I need a keyword parser that outputs results through a Telegram bot. How it should work: Automatic search on 4 websites for keywords that change from time to time. Search queries are sent every few minutes. The words are uploaded in the form of a .txt file. The Telegram bot should have buttons: start bot, stop bot, download file (downloads a file with active keywords), upload file (uploads an edited file with new words). The bot should ignore previously found results, i.e., it should not indicate the same ad twice. The result comes to the bot in the form of a link with a photo, but just a link is sufficient. P.S. searching websites without API, VPS with 6TB and 50 IPs are already available. For detailed information, please contact me via private message.
Task: one dashboard with all business metrics — advertising, funnel, payments, manager performance, revenue planning. Data is pulled automatically via API. Scope: only the YCL direction (employment in Europe). Kommo has other directions — only YCL funnel deals will be included in the repository (filter by funnel/tag to be agreed upon).1. Data Sources (Integrations) Kommo CRM — leads, deals, funnel stages, responsible persons, sources, dates of transitions between stages (must keep history), reasons for refusals, custom deal fields (see point 2). Stripe — payments, amounts, statuses (success/failure/refund), linked to deals. Meta Ads — expenses, impressions, clicks, CPL, leads by campaigns (currently operational). Google Ads, Reddit Ads, LinkedIn Ads — planned; architecture — extensible connectors without core rework. SEO/organic— Google Search Console + GA4. Cross-link: traffic source → lead in Kommo → payment in Stripe (UTM, deal ID in Stripe metadata — propose the mechanism). 2. Mandatory Cuts (Deal Fields in Kommo) Each metric must be filtered/grouped by: Client Citizenship (Kenya, Nigeria, India, etc.). Residence Status: lives in their country / expat (already in Europe). These are two different segments with different cycles, conversion rates, and checks. Country of Placement / Service: Poland, Serbia, Slovakia, Germany (ZAV). Manager, team, traffic channel, period. If any fields are missing in Kommo — the executor indicates which fields need to be added, the client adds them.3. Funnel and Leading Indicators Data by funnel, for each stage — summary and leading metrics: Traffic → lead: leads, CPL by channels + day-to-day expense/click dynamics. Lead → qualification: conversion + first response speed, touches/calls to the manager per day, unanswered leads. Qualification → contract/invoice: conversion + sent offers, stalled deals (days in stage above norm). Invoice → payment: payments, average check + unpaid invoices, failed payments. Summary: revenue, ROMI by channels, run rate to monthly plan. 4. Deal Cycle Average and median lead → payment cycle (business benchmark ~4 weeks), cycle trend over time. Breakdown of cycle by stages (how many days a deal sits at each stage) — to see which stage is dragging. List of deals that have stalled at a stage longer than normal. Cycle breakdown by segments: citizenship, residence status, country of placement, manager. 5. Early Warning of Decline (Key Block) Since the cycle is ~4 weeks, today's leads = payments in a month. The system must: Compare leads/qualifications of the current week with the moving average (4 weeks) and issue an alert if there is a downward deviation: “leads -X%, with a 4-week cycle expect a payment decline in the week [date].” Build payment forecast for 4 weeks ahead from the current pipeline: deals at each stage × historical conversion of the stage × remaining cycle. Highlight in red weeks where the forecast is below plan — with time to react. 6. Additional Payments and Sales Planning In the Kommo deal card, the date and amount of the planned additional payment are stored. The system must: Collect a calendar of upcoming additional payments: total expected, by weeks/months. Highlight overdue additional payments (date passed, no payments in Stripe) — a separate list for follow-up. Calculate the monthly plan as: plan − already paid − scheduled additional payments = how many new sales are needed (in money and in deal units at average check). Weekly schedule: additional payments + forecast of new payments against the weekly plan. 7. Manager Performance Daily snapshot for each manager: touches/calls, conversations, sent offers, payments — for each day separately, with a chart over the period. Progress on personal plan compared to monthly pace (ahead / on pace / behind). Benchmarking with colleagues. 8. Visualization and Roles “Traffic lights” (green/yellow/red) for key metrics relative to norms/plans; progress scales; trend graphs; mobile adaptive. Roles: CEO — everything; COO — entire funnel and managers; team lead — their team; manager — their metrics and position relative to colleagues. 9. Reports and AI Automated reports on schedule (daily summary, weekly report) in the dashboard and/or messenger. Free-form queries (“how has CPL from Meta changed over 2 weeks?”) — LLM over the repository. Alerts in the red zone and according to the rules from points 5–6. 10. Technical Expectations and Staging Repository (PostgreSQL/BigQuery or equivalent) + ETL: Kommo webhooks + periodic synchronization (15–60 min). Frontend: custom or BI tool — propose with justification; requirements for roles, traffic lights, forecasts, and AI queries must be implementable. Stages: (1) audit and metrics map → (2) MVP: Kommo + Stripe + Meta, funnel, traffic lights, roles → (3) deal cycle, early warning, additional payments and plan → (4) SEO, AI reports, alerts → (5) new advertising channels. Payment is staged, with a demo for each stage. In the response, indicate: similar projects (end-to-end analytics), stack with justification, timeline and cost estimates by stages, monthly ownership cost (hosting, tokens, licenses).