HouseSigma Scraper

Unlock the Canadian real estate market with the HouseSigma Scraper — extract for-sale, for-lease, sold, and de-listed property listings from HouseSigma across every Canadian province. Build investor-grade property databases, track price history, and analyze school districts and rental yields — with live filters, optional full listing details, and clean structured output — from just $1.50 per 1,000 listings (plus $2.50 per 1,000 full detail payloads when enabled).

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What can HouseSigma Scraper do for you?

• 🏘️ Build complete property databases — scrape listings by city, municipality, or community (Toronto, Oshawa, Danforth, or any HouseSigma search), with pagination handled for you.
• 💰 Capture sold prices and price history — pull sold and de-listed listings with dateSold, priceSold, and full listingHistory for market comps and appraisal research.
• 🎓 Get school ratings with every listing — optional detail scraping adds nearby schools with scores, ranks, boards, and distance.
• 📈 Filter like the site, then some — price range, bedrooms, bathrooms, lot size, square footage, school score, rental yield, open houses, basement features, and more.
• 🏷️ Track listings in any status — for-sale, for-lease, sold, leased, sale de-listed, or lease de-listed — across all 13 provinces and territories.
• 🌐 Export clean structured data — every record includes address, price, photos, geo-coordinates, taxes, and a direct HouseSigma URL, ready for CSV, Excel, JSON, or your API.

What data can you extract?

Field group	Extracted data
🏠 Listing identity	idListing, idAddress, mlsNumber, url, address, municipality, community, province, houseType, status
💵 Pricing	price, priceText, priceSold, estimatePrice, estimateRent, tax, maintenanceFee
🛏️ Property specs	bedrooms, bedroomsPlus, bathrooms, parking (type, garage, total), lotSize, propertySize
📸 Photos	photoUrl, photoList (all gallery images)
📍 Location	latitude, longitude, cross street
🎓 Schools	name, type, board, score, rank, distance, programs (when detail scraping enabled)
📜 History	listingHistory (previous prices and statuses), dateAdded, dateSold, dom
🏷️ Details	propertyDetail (grouped property/building/inside/parking facts), openHouses, description, sourceQuery

Why use this scraper?

• 📊 Market research — analyze pricing trends across Canadian cities, communities, and property types without manual browsing.
• 🏦 Investment analysis — filter by rental yield, school score, and sold prices to shortlist high-potential properties.
• 🔁 Price monitoring — schedule recurring runs to track new listings, price drops, and days-on-market daily.
• 🧰 Automation — feed listing data into your CRM, analytics dashboards, or lead-generation pipeline via the Apify API and webhooks.

Pricing

• $1.50/1,000 listings (list cards) — $2.50/1,000 for full listing-detail payloads
• 💎 Apify plan discounts apply automatically: Bronze $1.40/$2.40 · Silver $1.30/$2.30 · Gold $1.20/$2.20 per 1,000
• Detail payloads are charged only when scrapeDetails is enabled
• No hidden fees or limits on usage.

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How to use HouseSigma Scraper

1. Create a free Apify account — no credit card required to start.
2. Open the HouseSigma Scraper actor page.
3. Enter your search queries (e.g. Toronto) or paste a HouseSigma map/search URL, apply filters, and set maxItems to cap the run.
4. Click Start and watch the run — no browser setup, no coding required.
5. Download the results from the dataset in JSON, HTML, CSV, or Excel, or fetch them via the Apify API.

Input

Provide location searches, HouseSigma map/search URLs, or both — plus optional filters. At least one of searchQueries or startUrls is required.

Input field	Type	Default	Description
searchQueries	array (optional)	["Toronto"]	Location searches, resolved to a HouseSigma municipality / map area
startUrls	array (optional)	—	HouseSigma map/search URLs; municipality, status, center, zoom, and page are read from the URL
province	string (optional)	ON	Province code: ON, AB, BC, MB, NB, NL, NS, NT, NU, PE, QC, SK, YT
listStatus	string (optional)	for-sale	for-sale, for-lease, sold, leased, sale-de-listed, lease-de-listed
houseTypes	array (optional)	["all"]	Detached, Semi-Detached, Townhouse, Condo Apt, Link, Multiplex, Vacant Land, Other
priceMin / priceMax	integer (optional)	0 / 6000000	Min/max list price in CAD (monthly rent for lease searches)
listingDays	string (optional)	"0"	Listed within 1/3/7/30/90 days; negative values mean older than N days
soldDays	integer (optional)	90	Days window when status is sold
deListDays	integer (optional)	90	Days window when status is de-listed
bedrooms	array (optional)	["0"]	Bedroom filter; -10 = 0 bedrooms, 5 = 5+
bathroomMin / garageMin	string (optional)	0	Minimum bathrooms / garage spaces (N+)
basement	array (optional)	[]	finished, separate (entrance), walkout
openHouseDate	string (optional)	0	Today, Tomorrow, Last 7 days, or All Open Houses
listingType	string (optional)	all	resale or assignment (exclusive)
lotSizeMin / lotSizeMax	integer (optional)	0 / 10000000	Lot size range in sqft
frontFeetMin / frontFeetMax	integer (optional)	0 / 100	Lot frontage range in feet
squareFootageMin / squareFootageMax	integer (optional)	0 / 4000	Interior square footage range
schoolScoreMin / schoolScoreMax	number (optional)	0 / 10	School score filter (0–10)
rentalYieldMin / rentalYieldMax	number (optional)	0 / 0.1	Rental yield as a fraction (0.05 = 5%)
municipalityId	integer (optional)	—	HouseSigma municipality id (e.g. 10343 = Toronto); also read from start URLs
scrapeDetails	boolean (optional)	true	Fetch full detail payloads (photos, schools, history, estimates) for each listing
sortType	integer (optional)	0	HouseSigma list sort type (0 = site default)
maxItems	integer (optional)	50	Maximum listings to scrape; 0 = unlimited
proxyConfiguration	object (optional)	Residential	Apify Proxy settings; residential recommended

📝 Copy for Use:

{
    "searchQueries": ["Toronto"],
    "listStatus": "for-sale",
    "houseTypes": ["all"],
    "scrapeDetails": true,
    "maxItems": 50,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Output

Each dataset item is a clean, structured listing record — a compact list card by default, or a full detail record when scrapeDetails is enabled. You can download the dataset in various formats such as JSON, HTML, CSV, or Excel.

Why Choose This Scraper?

• Affordable: Pay only $1.50 per 1,000 listings, plus $2.50 per 1,000 detail payloads only if you enable scraping details.
• Comprehensive: Rich listing data — prices, sold history, school ratings, photos, geo-coordinates, taxes, and rental estimates.
• Easy to Use: Enter a city name or pasted URL and start — no browser setup or code required.
• Reliable: Uses residential proxy support and HouseSigma's own API endpoints for stable, fast extraction.

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🙌 Why Buy Through Our Affiliate Link?

• Exclusive Deals: Some providers may offer special discounts or bonuses when you use our link.
• Support Our Work: Each purchase helps us maintain and improve the tools and services we provide.
• No Extra Cost: You pay the same price, but part of it goes to supporting our efforts.

Running via Apify Console

You can run this actor from the Apify Console by providing the necessary input parameters.

Running via API

You can trigger this actor using the Apify API, passing the required input in the request body.

API Examples

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

run_input = {
    "searchQueries": ["Toronto"],
    "listStatus": "for-sale",
    "houseTypes": ["all"],
    "scrapeDetails": True,
    "maxItems": 50,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

run = client.actor("rigelbytes/housesigma-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["address"], item["price"], item["mlsNumber"])

JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const runInput = {
    searchQueries: ['Toronto'],
    listStatus: 'for-sale',
    houseTypes: ['all'],
    scrapeDetails: true,
    maxItems: 50,
    proxyConfiguration: {
        useApifyProxy: true,
        apifyProxyGroups: ['RESIDENTIAL'],
    },
};

const run = await client.actor('rigelbytes/housesigma-scraper').call(runInput);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => console.log(item.address, item.price));

cURL

curl "https://api.apify.com/v2/acts/rigelbytes/housesigma-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchQueries": ["Toronto"],
    "listStatus": "for-sale",
    "houseTypes": ["all"],
    "scrapeDetails": true,
    "maxItems": 50,
    "proxyConfiguration": {
      "useApifyProxy": true,
      "apifyProxyGroups": ["RESIDENTIAL"]
    }
  }'

Scheduling & Deduplication

• Scheduling: Canadian real estate moves fast — listings are added, priced, and sold every day. Schedule daily runs via the Scheduler tab in Apify Console (or the Scheduler API) to stay on top of new inventory. Running multiple searchQueries per run lets you cover several cities in one schedule; alternatively, create a separate schedule per query for city-by-city cadence. Use listingDays (e.g. 1 or 3) with daily runs to isolate fresh listings, or listingDays: -90 for aging inventory.
• Deduplication: Every listing has a stable idListing (plus mlsNumber when present), so you can deduplicate across runs by keying on those fields. maxItems caps the size of each run, but it does not filter out listings you already scraped. To keep a clean database, merge run outputs on idListing:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
seen = set()
for item in client.dataset("YOUR_DATASET_ID").iterate_items():
    key = item.get("idListing") or item.get("mlsNumber")
    if key is None or key in seen:
        continue
    seen.add(key)
    # store/upsert item in your database

• Webhooks: Attach an Apify webhook to ACTOR.RUN.SUCCEEDED to push new listings into your CRM, spreadsheet, or database the moment each scheduled run completes.

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• Web Crawler — This web crawler is designed to provide users with complete flexibility by allowing them to use their **own...

Understanding Proxies:

When scraping data or browsing anonymously, proxies are essential. They act as intermediaries, masking your original IP address and allowing you to send requests from another location.

Why Use Proxies?

• Avoid IP Blocks: By routing requests through proxies, you prevent the target website from recognizing your IP as a scraper or spammer.
• Access Geo-restricted Content: Proxies let you access content or websites restricted by location.
• Enhance Anonymity: Hide your actual IP, ensuring privacy while scraping or browsing.

Types of Proxies

1. Residential Proxies
   • Real IP addresses provided by ISPs to home users.
   • They mimic regular users, making them harder to detect.
   • Best for: Long-term, undetectable scraping, and avoiding blocks.
2. Data Center Proxies
   • IP addresses from servers in data centers.
   • Faster and cheaper than residential proxies but easier to detect and block.
   • Best for: High-speed scraping, but with a higher risk of detection.
3. Mobile Proxies
   • IPs provided by mobile carriers (3G/4G/5G networks).
   • Very difficult to detect, as they appear as regular mobile users.
   • Best for: Mobile-related scraping or avoiding sophisticated blocks.

Rotating Proxies vs. Straight Proxies

• Rotating Proxies: Every request you send goes through a different proxy, making it harder for websites to detect patterns.
• Straight Proxies: All requests are sent through the same proxy, making it easier to track your IP.

FAQs & Troubleshooting

Q: What is the difference between list-card results and detail payloads?

With scrapeDetails: false, each record contains the list-card fields only (address, price, beds/baths, photos, geo-coordinates). With scrapeDetails: true (default), the actor also fetches the full detail payload per listing — school ratings, listing history, property facts, open houses, and estimates. Detail payloads cost extra per 1,000 records, so set scrapeDetails: false for large, budget-friendly scans and enable it only for enriched datasets.

Q: How do searchQueries and startUrls differ?

searchQueries are plain location names ("Toronto", "Danforth", "Oshawa") that the actor resolves through HouseSigma's suggest API into a municipality or map area. startUrls accept full HouseSigma map/search URLs (e.g. https://housesigma.com/on/toronto-real-estate/map/?municipality=10343&status=for-sale) — municipality, status, map center, zoom, and page are read from the URL and merged with your filters. Pasted URLs are best when you want to reuse an exact map view or saved search.

Q: Why do I get empty results or very few listings?

Most common causes: (1) no searchable input — provide at least one searchQueries entry or startUrls URL, otherwise the actor stops with "No searchable input"; (2) over-restrictive filters — e.g. listingDays: 1 on a quiet day, a priceMax below local pricing, or a schoolScoreMin close to 10; (3) geo-blocks — HouseSigma restricts some requests to Canadian IPs, so enable the residential proxy group or use Canadian proxies. If you see "Failed to obtain access token" or "Failed to obtain session secret" errors in the log, the request was blocked — switch to residential proxies and retry.

Q: What do the sold and de-listed statuses return, and how do soldDays / deListDays work?

listStatus: sold returns sold listings within the soldDays window (default 90 days) with priceSold, dateSold, and prior listingHistory entries — ideal for market comps. sale-de-listed / lease-de-listed return listings de-listed within deListDays (default 90). Set these windows wider (e.g. 180–365) if you need deeper history.

Q: What counts as one "result" for billing?

Each dataset item pushed counts against the listing event at $1.50/1,000 records. Each full detail payload fetched (when scrapeDetails is on) counts against the listing-details event at $2.50/1,000 records. Apify plan discounts (Bronze/Silver/Gold) lower both rates automatically. If your listing-details spending limit is reached mid-run, the actor logs it and continues pushing list cards — records affected are marked with _chargeLimitReached: true.

Q: How do I export the scraped listings?

Open the run's dataset and use the Export tab to download JSON, HTML, CSV, or Excel, or fetch items programmatically through the Apify Dataset API — the same dataset is accessible for API integrations, Zapier/Make, or Google Sheets.

About Rigel Bytes

Rigel Bytes specializes in web scraping, automation, and data analytics. We help businesses extract and leverage valuable data for informed decision-making.

Contact Us

Ready to unlock the power of data? Reach out to us at (contact@rigelbytes.com) or book an appointment with us to learn more about how we can help you achieve your data goals.

Detailed Data

Below are 2 sample records from an actual HouseSigma run for Toronto for-sale listings:

[
  {
    "idListing": "XRla7gb1bnNyjEvL",
    "idAddress": "BGMnKYqOk57w1Qrq",
    "mlsNumber": "C12411018",
    "url": "https://housesigma.com/on/toronto-real-estate/170-sudbury-street/home/BGMnKYqOk57w1Qrq/",
    "address": "170 Sudbury Street",
    "municipality": "Toronto",
    "community": "Little Portugal",
    "province": "ON",
    "houseType": "Parking Space",
    "status": "For Sale",
    "statusCode": "A",
    "price": 39000,
    "priceText": "39,000",
    "bedrooms": 0,
    "parking": {
      "total": 1,
      "garage_type": "Underground",
      "garage": 1,
      "parking_type": null,
      "parking": 1,
      "text": "Underground 1 garage,  1 parking"
    },
    "photoUrl": "https://cache17.housesigma.com/file/pix-treb/C12411018/cfe95_1.jpg?07d72025",
    "dateAdded": "2025-09-17",
    "latitude": 43.64161,
    "longitude": -79.4247,
    "sourceQuery": "Toronto",
    "source": "detail",
    "tax": "$- / 2025",
    "maintenanceFee": "$65/month",
    "schools": [
      {
        "name": "Parkdale Collegiate Institute",
        "board": "Toronto District School Board",
        "school_type": "Secondary",
        "score": 6.3,
        "rank": 328,
        "rank_total": 732,
        "distance": 995
      }
    ],
    "listingHistory": [
      {
        "id_listing": "XRla7gb1bnNyjEvL",
        "ml_num": "C12411018",
        "price": "$39,000",
        "price_sold": null,
        "date_start": null,
        "date_end": null,
        "status": "For Sale",
        "data_source": "PROPTX"
      }
    ],
    "description": "Discover the perfect starter home or investment opportunity at 170 Sudbury Street, Toronto, Ontario with HouseSigma today."
  },
  {
    "idListing": "JKdOYrBBOezY54lW",
    "idAddress": "GMnKYqpVr1R3w1Qr",
    "mlsNumber": "C12884018",
    "url": "https://housesigma.com/on/toronto-real-estate/b70-500-sherbourne-street/home/GMnKYqpVr1R3w1Qr/",
    "address": "Unit B70 - 500 Sherbourne Street",
    "municipality": "Toronto",
    "community": "North St. James Town",
    "province": "ON",
    "houseType": "Parking Space",
    "status": "For Sale",
    "statusCode": "A",
    "price": 50000,
    "priceText": "50,000",
    "bedrooms": 0,
    "parking": {
      "total": 1,
      "garage_type": "Underground",
      "garage": 1,
      "parking_type": null,
      "parking": 0,
      "text": "Underground 1 garage"
    },
    "photoUrl": "https://cache-e12.housesigma.com/file/pix-treb/C12884018/1d18e_1.jpg?5c738f9e",
    "dateAdded": "2026-03-14",
    "latitude": 43.66798,
    "longitude": -79.37558,
    "sourceQuery": "Toronto",
    "source": "detail",
    "tax": "$- / 2026",
    "maintenanceFee": "$47/month",
    "schools": [
      {
        "name": "Jesse Ketchum Junior and Senior Public School",
        "board": "Toronto District School Board",
        "school_type": "Elementary",
        "score": 7.4,
        "rank": 344,
        "rank_total": 2995,
        "distance": 1393
      }
    ],
    "listingHistory": [
      {
        "id_listing": "JKdOYrBBOezY54lW",
        "ml_num": "C12884018",
        "price": "$50,000",
        "price_sold": null,
        "date_start": null,
        "date_end": null,
        "status": "For Sale",
        "data_source": "PROPTX"
      }
    ],
    "description": "Discover the perfect starter home or investment opportunity at B70 - 500 Sherbourne Street, Toronto, Ontario with HouseSigma today."
  }
]