geographicportugalreal-estatepropertycasasapoimobiliariaeurope

Portugal Real Estate Listings — casa.sapo (sample)

Updated Oct 22, 2026

$39

Fixed price

Sample structure: 100 / 100
0 download links issued
Seller: DigiKuo
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Category
Geographic
Records
250 rows
Format
JSONL
Update Frequency
Not documented
Collection Method
uploaded
PII
No flagged field names; not a privacy audit
File Size
~0.26 MB
Download links issued
0

Source, license and coverage

Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.

License
DataBazaar Open Use
Source / creator
casa.sapo.pt
Collection method
uploaded
Coverage start
Not documented
Coverage end
Not documented
Data last updated
Not documented
Update schedule
Not documented

Commercial use, modification, redistribution, and model training are permitted without attribution. Access charges still apply. Read default reuse terms

Sample structure score: 100 / 100

This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.

Assessed 10 sample records (JSONL) on 2026-10-22. All records in the provided sample were checked.

CheckPointsEvidence
Populated cells50 / 50180 of 180 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated.
Consistent value types30 / 30180 of 180 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth.
Consistent record shape20 / 2010 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys.
Field-level findings and improvements

Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.

FieldMissing cellsMost common typeOther populated types
listing_title0 / 10string0 / 10
listing_description0 / 10string0 / 10
price0 / 10string0 / 10
currency0 / 10string0 / 10
region0 / 10string0 / 10
city0 / 10string0 / 10
country0 / 10string0 / 10
lat0 / 10number0 / 10
lon0 / 10number0 / 10
listing_type0 / 10string0 / 10
category0 / 10string0 / 10
listing_id0 / 10string0 / 10
itemurl0 / 10string0 / 10
agency0 / 10string0 / 10
agency_url0 / 10string0 / 10
image_url0 / 10string0 / 10
source0 / 10string0 / 10
rights_note0 / 10string0 / 10
How the score is calculated, its limitations, and how to correct an assessment →

About this data

Sample of 250 property listings crawled from casa.sapo.pt (Portugal's national real-estate portal) in October 2026. Fields per row: listing title and description (PT), asking price + currency, region, city, country, latitude/longitude, listing_type (SALE/RENT), category (apartments, houses, buildings, land, etc.), listing_id, itemurl, agency name and location. Scope: metadata-only records of publicly advertised listings from real-estate agencies. NO private contact data: no personal emails, no personal phone numbers, no owner identities. Listings are advertisements published publicly by agencies on casa.sapo.pt; redistribution of portal content is prohibited and buyers may use this sample for analytics/market-research evaluation only with citation of casa.sapo.pt as source. Covers multiple Portuguese municipalities; ~269 KB JSONL, 250 records.

Retrieve with your agent or Python

Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.

Download the Python example
python3 retrieve-dataset.py 5039c2c1-afe5-4aee-8523-e7002e6815b7 --output dataset.bin

Schema

NameTypeDescription
listing_titlestring
listing_descriptionstring
pricestring
currencystring
regionstring
citystring
countrystring
latnumber
lonnumber
listing_typestring
categorystring
listing_idstring
itemurlstring
agencystring
agency_urlstring
image_urlstring
sourcestring
rights_notestring

Sample Data

Download a free sample to inspect the data before purchasing.

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For AI Agents

Via MCP Server
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
  "mcpServers": {
    "databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
  }
}

# 2. Your agent can then call:
search_datasets({ query: "Portugal Real Estate Listings " })
// Found: 5039c2c1-afe5-4aee-8523-e7002e6815b7
buy_now({ dataset_id: "5039c2c1-afe5-4aee-8523-e7002e6815b7" })  // uses your saved card
Via REST API
# Authenticate with your API key:
curl https://api.databazaar.io/datasets/5039c2c1-afe5-4aee-8523-e7002e6815b7 \
  -H "Authorization: Bearer YOUR_API_KEY"

# Purchase:
curl -X POST https://api.databazaar.io/datasets/5039c2c1-afe5-4aee-8523-e7002e6815b7/buy \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"dataset_id": "5039c2c1-afe5-4aee-8523-e7002e6815b7"}'