This tutorial shows how to scrape Vivanuncios real estate post details into CSV with the Vivanuncios Post Details Scraper for UScraper. You will import the workflow, replace the sample URLs, set the export path, run a short validation batch, and fix the common issues that appear on dynamic listing pages.
CSV
17
URL loop
30s + pauses
Local file
Before you start
Prerequisites and Vivanuncios policy checks
You need UScraper installed as a local desktop app, a small list of Vivanuncios post detail URLs you are allowed to process, and a folder where CSV exports can be written. Start with five URLs, not fifty. Vivanuncios pages can vary by category, city, listing age, seller type, language, consent state, and whether the post is still live.
This guide covers visible real estate detail pages only. It does not cover account dashboards, private messages, payment flows, CAPTCHA bypassing, or high-volume crawling. Review the official Vivanuncios site and its help center before automation, especially if the output will be used for outreach, resale, model training, or public redistribution.
Technical access is not the same as permission. Keep runs modest, avoid defeating access controls, and document why each URL set is being collected.
Workflow anatomy
What the Vivanuncios post details scraper does
The template is designed for known detail URLs, not search-result discovery. Use it after you have collected property links from a shortlist, a CRM, a manual review, or a separate search workflow. Each URL should represent one listing you want to verify or normalize.
The JSON export is the authoritative workflow definition. In plain English, the flow is:
Navigate -> Wait for Page Load -> Sleep -> Inject JavaScript
-> Sleep -> Wait for Element -> Structured Export -> Loop Continue
Navigate owns the list of Vivanuncios URLs. The wait and sleep blocks give dynamic modules time to load. The interaction block clicks common labels such as accept, close, show phone, and contact when they appear. Structured Export reads the current page and appends a CSV row. Loop Continue advances to the next URL.
The columns use active DOM and metadata selectors first. For the bundled demo listing IDs, the workflow also includes fallback values because analyzed sample pages may expire or be blocked later. That makes the JSON useful for understanding the intended export shape, but live production rows should always be validated against the browser.
| Export group | Fields | How to validate |
|---|---|---|
| Source and identity | pagina_url, titulo, anuncio | Confirm the URL and title match the open listing. |
| Price and property facts | precio, recamaras, banos, garage, superficie_total | Compare with the visible facts panel and description. |
| Location | direccion | Check breadcrumbs, address text, and city/category context. |
| Contact and seller | telefono, agente, url_agente | Only expect phone values when the page exposes them in your session. |
| Media and freshness | image_url1, image_url2, image_url3, publicado | Open image URLs and spot-check published-date text. |
Runbook
How to scrape Vivanuncios post details to CSV
Import the template
Open Vivanuncios Post Details Scraper, download the JSON, and import it into UScraper.
Replace the sample URLs
Open the Navigate block and paste your approved Vivanuncios detail URLs. Keep each URL on its own line and avoid mixing test links with a production batch.
Confirm the export path
In Structured Export, set the save folder and filename. The stock filename is vivanuncios_detalles_scraper.csv, headers are enabled, and append mode is on.
Run one listing
Start with one URL. Watch the browser load, wait, click any visible consent or contact controls, and write one row.
Validate, then widen
Open the CSV beside the browser. If title, price, address, seller, phone, and image fields look correct, run a five-url batch before scaling further.
Append mode is useful for loops, but it can also create duplicates during testing. Before a fresh run, move the old CSV to an archive folder or change the filename to include the city, client, and date.
Output
Vivanuncios real estate data export shape
The export is intentionally spreadsheet-friendly. It keeps raw listing text close to what the browser showed, so an analyst can clean and normalize later rather than losing context too early.
vivanuncios_detalles_scraper.csvColumn
pagina_url
Final listing URL opened by the Navigate block.
Column
titulo
Listing title from the page, breadcrumb, Open Graph title, or fallback.
Column
precio
Visible price or metadata price when available.
Column
recamaras
Bedroom text parsed from page metadata, description, or visible facts.
Column
banos
Bathroom text parsed from page metadata, description, or visible facts.
Column
direccion
Address or location assembled from labels and breadcrumbs.
Column
telefono
Phone value when visible after the interaction step or present in page text.
Column
url_agente
Seller or agent profile URL when Vivanuncios exposes it.
Sample rows
1 of many
| pagina_url | titulo | precio | recamaras | banos | direccion | telefono | url_agente |
|---|---|---|---|---|---|---|---|
| Townhouse de 2 Habs 2.5 Banos | MN 15,000 | 2rec. | 2 banos | Temozon Norte, Merida | 9991464650 | /u-anuncios-del-vendedor/inmobiliarialb/... |
For recurring projects, keep the source URL list, run date, CSV filename, selector edits, and any manual browser notes in the same folder. Vivanuncios inventory changes over time, so the collection context matters when someone reviews the file later.
Validation
Validate the Vivanuncios CSV before using it
Open the CSV next to the browser after the first listing and again after the first small batch. Check the first row, a middle row, and the last row. Sorting by pagina_url is the fastest way to spot duplicate URLs or accidental reruns.
| Symptom | Likely cause | Fix |
|---|---|---|
| Zero rows exported | Page did not load, consent blocked the page, or the URL is expired | Open the URL manually, handle prompts, then rerun one listing. |
Blank telefono | Contact value is hidden, not available, or not exposed in the session | Click visible contact controls manually and confirm the page actually shows a phone. |
| Price mismatch | Cached page text, layout change, or multiple price strings in metadata | Compare against the browser and update the price selector if needed. |
| Repeated rows | Append mode reused an old CSV or the URL list has duplicates | Archive the old file and dedupe URLs before running again. |
| Broken image URLs | Gallery did not load or a post image was removed | Treat images as optional and verify a few URLs in the browser. |
Guardrails for reliable Vivanuncios exports
Do not turn the URL loop into a high-frequency crawler
Keep waits in place, avoid parallel runs, and stop when Vivanuncios presents unusual response pages or access challenges.
Expect layout drift on real estate detail pages
If blanks increase suddenly, inspect one live page and update the JavaScript-backed columns before collecting more rows.
Treat seller, phone, image, and description fields carefully
Confirm your legal basis before outreach, resale, public redistribution, or model training with exported listing content.
Alternatives
UScraper vs Octoparse, Apify, Piloterr, and custom code
If you search for a Vivanuncios scraper tutorial, you will see several valid approaches. Octoparse offers a no-code Vivanuncios detail scraper template. Apify actors are useful when a developer wants a cloud actor, input schema, and API examples for broader search scraping. Piloterr focuses on hosted APIs for Vivanuncios search and ad details. A custom Selenium, Scrapy, or notebook project gives engineering control, but also means owning every selector, wait, retry, and anti-bot decision.
UScraper fits a narrower workflow: supervised local CSV extraction from detail URLs where the analyst can watch the browser, edit columns, and keep the exported file in a local project folder.
| Approach | Best fit | Trade-off |
|---|---|---|
| UScraper template | Local no-code CSV exports from known detail URLs | You validate selectors and pacing when Vivanuncios changes. |
| Octoparse template | Cloud or desktop no-code workflows with a template catalog | Vendor workflow behavior and pricing depend on that platform. |
| Apify actor | Developer-driven cloud runs, APIs, and scheduled scraping | Data custody, compute, and actor settings live in Apify. |
| Piloterr API | Structured API calls for search or ad details | API pricing and returned schema are controlled by the provider. |
| Custom code | Fully custom ETL and research pipelines | Requires ongoing engineering maintenance and compliance review. |
For a small real estate research CSV, start with the UScraper template library. For official platform context, review Vivanuncios pages directly before collecting anything at scale.
FAQ
Vivanuncios post details scraper FAQ
Vivanuncios pages can be visible in a browser and still be governed by platform terms, robots guidance, copyright, privacy rules, and local real estate regulations. Use modest pacing, avoid access-control bypassing, do not republish protected listing content without permission, and get legal review before commercial reuse.
Next step
Download the Vivanuncios post details scraper template
Download the JSON from Vivanuncios Post Details Scraper, import it into UScraper, and keep this guide open for the first validation pass. Once the first rows match the browser, archive the test CSV, rename the production export, and run the approved URL list.
For related workflows, browse all UScraper templates or the UScraper blog for more local desktop app scraping tutorials.