Bot parser of advertisements from necessary websites by parameters

Main components

Telegram Bot (aiogram)

whitelist by user_id

roles: Admin / Operator / Recipient

menu through inline buttons + wizard dialogues (FSM)
…
Worker parser + scheduler

APScheduler (for MVP) or Celery (if you want scaling)

collecting ads more frequently (every 1–3 hours), sending a digest once a day

PostgreSQL

storing filters/parameters

blacklist of sellers (global + per-filter)

deduplication of ads and delivery history

Docker-compose

bot + worker + postgres (+ optional redis if Celery)

Sources: how exactly to parse

For each site, we create a separate module-adapter:

Wallapop: usually easier through output/search + cards, but the markup/anti-bot may change.

Idealista: known for strict anti-bot, sometimes requires more “careful” access (delays, headers, proxies), possible blocks.

Milanuncios: usually more accessible, but can also throttle.

Practical MVP approach:

start with HTML parsing (requests/httpx + lxml/bs4)

careful rate-limit, random delays, normal User-Agent/headers

if any source starts to “cut,” we lay down the option to switch to Playwright (more resource-intensive)

Dedup and blacklist — how it will work
Deduplication

primary key of the ad = site + listing_id (if available) or normalized URL

we save: first_seen, published_at (if retrieved), title, price, location, url, source

connection “ad seen by filter” through a relationship table

sending: only those that are “new for the period” and have not yet been delivered to recipients

Negative sellers

we support several identifiers: seller_profile_url, seller_id, seller_name, phone (if actually available)

blacklist can be:

global

by filter

filtering is done at the stage of processing the ad card

Telegram UI (how it will look)

Menu:

Filters

list

create (wizard: name → sources → parameters → recipients → sending time → enable)

edit

enable/disable

delete

Blacklist

add (insert link/id/name/phone)

list (with pagination)

delete

Status

last run by sources

found / filtered / errors

Test

manual filter launch (without waiting a day)

Settings

default digest time

message limits (batch 10–20)

delivery channels (TG mandatory, Email/WA — optional)

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Hello. I have reviewed the technical specifications - they are very professionally and thoroughly detailed, it is pleasant to work with such a clear task setting. This is exactly my profile. I specialize in developing complex parsers and Telegram bots with admin panels. Moreover, I already have a ready-made solution in my portfolio with identical architecture (a price monitoring system for Steam/OLX), which I can adapt to your needs. Why I will perform better than others: Ready architecture: I am already working with the stack Python + Aiogram + PostgreSQL + Docker. I have implemented the logic of "workers," task queues (Redis/Celery), and duplicate filtering. This is exactly what you described in the technical requirements (docker-compose: bot + worker + db). Experience with protection: Wallapop and Idealista have serious bot protection (Cloudflare/Datadome). Regular requests do not work there. I know how to bypass this through browser emulation (Playwright/Selenium) and rotation of User-Agents/Proxy. Admin panel: I will implement filter management and "minus-sellers" through a convenient menu with Inline buttons, as in my previous projects. My implementation plan: Deployment of the database (PostgreSQL) for storing ads and blacklists. Writing parsers for each source (Idealista, Wallapop, Milanuncios). Setting up a scheduler for data collection and sending reports once a day. I am ready to show examples of code and the architecture of my bots. I am confident that I can implement this project qualitatively and stably.

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Good day!
I specialize in Python development, process automation, and creating Telegram bots. Your technical task is clear: parsing ads from Wallapop, Idealista, and Milanuncios, filters with search parameters, a "minus-sellers" system, deduplication, and daily digests in Telegram.
I can implement the architecture in Python with a database (PostgreSQL), a scheduler, and Docker deployment. I am ready to discuss the details and deadlines for completion.

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Good day! I am ready to complete this project and have extensive experience in developing various applications.

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Good day!

I have reviewed the technical assignment for the development of a monitoring bot for advertisements (Wallapop / Idealista / Milanuncios) managed through Telegram. The project is well-structured, and the requirements are clear — this is exactly the type of tasks I regularly work on.

My experience and approach fully align with the stated requirements:

Technologies and stack

Python (async / sync, depending on the source)
…
Parsing: requests + BeautifulSoup / Playwright (where JS is needed)

Telegram Bot API (aiogram / pyTelegramBotAPI)

PostgreSQL (structured data model for filters, advertisements, blacklist, deliveries)

APScheduler / Celery beat for scheduling

Docker / docker-compose

VPS deployment (Linux)

Architecture

Separation into services: Telegram bot (UI) + parsing workers

Plugin structure for sources (each site is a separate module)

Deduplication by ID / normalized URL + hash of key fields

Support for global and local seller blacklists

Post-filtering of data if some parameters are unavailable through the URL

Functionality

Wizard for creating filters through Telegram (inline buttons, step-by-step dialogues)

Flexible filters (price, location, keywords, object parameters)

Daily digest with message batching

Manual trigger for filter checking

Logs, source statuses, error handling

Whitelist authorization by Telegram user_id

Additionally

Optimization for low-latency and stability

Possibility for further integration with Email / WhatsApp (through a provider)

Willingness to document the structure and hand over the project for support

I can take on:

the full implementation of the project turnkey

or separate parts (parsers, Telegram UI, architecture, deployment)

I am ready to discuss the details: the scope of MVP, timelines, collaboration format, and budget.
Thank you for your attention — I look forward to your feedback.

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Hello, all of this can really be developed, I am ready, just the neural network that wrote this technical specification for a couple of bucks here wrote Twilio at least)) Regarding the integration with WhatsApp, you should know that this is additional costs of approximately $10 per month if using the unofficial API, if the official one, the price ranges around $500 for 5000 messages.

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Hello! I have reviewed the technical specifications. The task is clear: stable monitoring of platforms with aggressive anti-fraud protection (Idealista, Wallapop, Milanuncios) is needed.

I have extensive experience working with Playwright and bypassing protection systems like DataDome/Cloudflare. For the implementation of the project, I propose the following stack:

Parsing: Playwright (Chromium-Ghost / Stealth patches) for complete imitation of real user behavior. This will allow bypassing automation checks.

Anti-ban: Setting up residential proxy rotation and generating unique fingerprints for each session.

Backend: Python (Aiogram 3.x) for management via Telegram.
…
Database: PostgreSQL for reliable storage of listings, deduplication history, and a blacklist of sellers.

Architecture: Docker-compose for convenient deployment on VPS, task scheduler (APScheduler) for flexible configuration of check frequency and sending digests.

I will implement all functionality: step-by-step filter builder in TG, global and local seller blacklist, deduplication by ID/URL, and daily reports.

I am ready to discuss the details: what specific limits on the number of requests are planned and whether integration with paid captcha solving services is required (in case they arise).

Please write in private messages, and we will discuss the architecture and timelines!

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Hello!

I have experience in creating bots for monitoring and parsing data, and I recently implemented a similar bot for automatically collecting listings from real estate websites with Telegram integration.

I will create a parser bot in Python using libraries for data parsing (such as BeautifulSoup or Scrapy) and aiogram for management through Telegram. I will implement a filtering system, a blacklist of sellers, as well as the formation of a daily digest with new listings.

This will provide convenient access to current listings without duplicates and the ability to customize for specific needs. Let's discuss the details!

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