Condos APIcondos.ca ↗
Access condo listings, pre-construction developments, neighbourhood market stats, mortgage rates, and building details from Condos.ca via 7 structured endpoints.
What is the Condos API?
The Condos.ca API exposes 7 endpoints covering active condo listings, pre-construction developments, building pages, neighbourhood market statistics, and Canadian mortgage rates. The search_listings endpoint returns paginated MLS results with asking price, bed type, square footage, and neighbourhood name, while get_neighbourhood_stats delivers historical sold/leased price data and current market averages for any Toronto-area locality or neighbourhood.
curl -X GET 'https://api.parse.bot/scraper/76380264-a705-4e8f-a5ac-70c7c676e2e7/search_listings?beds=1-1&mode=Sale&page=0&sort=newest&limit=5&locality_id=1' \ -H 'X-API-Key: $PARSE_API_KEY'
Typed, relational, agent-ready
A generated client with real types, enums, and the links between objects — the structure a flat JSON response can't carry. Autocompletes in your editor and reads cleanly to coding agents.
- Fully typed · autocompletes
- Objects link to objects
- Typed errors & pagination
Typed Python client. Set up the SDK in your uv project, then pull this API’s typed client:
uv add parse-sdk uv run parse init uv run parse add --marketplace condos-ca-api
uv run parse add --marketplace pulls a pinned snapshot of this canonical API — it won’t change underneath you. To customize it, subscribe and swap to your own copy.
"""Walkthrough: Condos.ca SDK — search listings, explore buildings, mortgage tools."""
from parse_apis.condos_ca_api import Condos, Sort, ListingMode, Beds, ListingNotFound
condos = Condos()
# Search rental listings filtered by 1-bedroom, sorted cheapest first
for listing in condos.listings.search(mode=ListingMode.RENT, sort=Sort.CHEAPEST, beds=Beds._1_1, limit=5):
print(listing.title, listing.asking_price, listing.bed_type, listing.neighbourhood_name)
# Drill into a single listing's full detail page
listing = condos.listings.search(mode=ListingMode.SALE, sort=Sort.NEWEST, limit=1).first()
if listing:
detail = listing.details()
print(detail.component, detail.area_type)
# Search pre-construction developments
for building in condos.buildings.search(query="king", limit=3):
print(building.name, building.construction_status, building.developers)
# Constructible neighbourhood — get stats and browse listings
king_west = condos.neighbourhood("toronto/king-west")
stats = king_west.stats()
print(stats.display_name, stats.sold_count, stats.sold_avg_price)
# Get current mortgage rates
for rate in condos.mortgagerates.list(purchase_price=800000, down_payment=160000, limit=3):
print(rate.lender_name, rate.rate, rate.mortgage_term, rate.monthly_payment)
# Calculate a mortgage payment
calc = condos.mortgagecalculations.calculate(price=800000, down_payment=160000, rate=5.0, years=25)
print(calc.principal, calc.monthly_payment, calc.total_interest)
# Typed error handling
try:
bad = condos.neighbourhood("toronto/nonexistent-area-xyz")
bad.stats()
except ListingNotFound as exc:
print(f"Area not found: {exc.slug}")
print("exercised: listings.search / listing.details / buildings.search / neighbourhood.stats / mortgagerates.list / mortgagecalculations.calculate")
Search active condo listings via Algolia index. Supports filtering by bedrooms, price range, square footage, and locality/neighbourhood. Returns paginated results sorted by date, price ascending, or price descending. Each hit includes MLS number, asking price, bed type, sqft, neighbourhood, and a URL slug usable with get_listing_detail.
| Param | Type | Description |
|---|---|---|
| beds | string | Bedrooms filter in range format: '1-1' for 1BD, '1.1-1.9' for 1+1, '2-2' for 2BD, '3-3' for 3BD. The decimal represents den presence. |
| mode | string | Listing mode. |
| page | integer | Page number (0-indexed). |
| sort | string | Sort order. |
| limit | integer | Max results per page. |
| query | string | Text search query. |
| max_sqft | integer | Maximum square footage. |
| min_sqft | integer | Minimum square footage. |
| max_price | integer | Maximum price filter. |
| min_price | integer | Minimum price filter. |
| locality_id | integer | Locality ID (1 for Toronto). |
| neighbourhood_id | integer | Neighbourhood ID to filter by. |
| neighbourhood_slug | string | Neighbourhood URL slug (e.g., 'toronto/king-west') to auto-resolve neighbourhood or locality ID. |
{
"type": "object",
"fields": {
"hits": "array of listing objects with mls_number, title, asking_price, bed_type, sqft, neighbourhood_name, url, and other listing details",
"page": "integer current page number",
"nbHits": "integer total number of matching results",
"nbPages": "integer total number of pages",
"hitsPerPage": "integer results per page"
},
"sample": {
"data": {
"hits": [
{
"id": 2230534,
"url": "toronto/bristol-house-10-tobermory-dr/unit-1206-W13423826",
"sqft": 996,
"title": "1206 - 10 Tobermory Drive",
"bed_type": "3",
"bathrooms": 2,
"mls_number": "W13423826",
"asking_price": 549999,
"locality_name": "Toronto",
"parking_spots": 1,
"neighbourhood_name": "Black Creek"
}
],
"page": 0,
"nbHits": 7205,
"nbPages": 1441,
"hitsPerPage": 5
},
"status": "success"
}
}About the Condos API
Listing Search and Detail
The search_listings endpoint queries active condo listings with filters for bedroom count (using range format strings like '1-1' for 1BD or '1.1-1.9' for 1+1), price range, square footage (min_sqft, max_sqft), and free-text query. Results are 0-indexed and sortable by date, price ascending, or price descending. Each hit includes mls_number, asking_price, bed_type, sqft, neighbourhood_name, and a url slug. That slug feeds directly into get_listing_detail, which returns the full initial state for a listing page — including lookups (component ID, area type, header tags) and an areasData object describing the neighbourhood hierarchy.
Pre-Construction and Building Data
search_preconstruction queries new development projects and returns each building's construction_status, sales_status, developers, price_min, price_max, and average_psf. The locality_id parameter (1 = Toronto) scopes results geographically. Each hit carries a url slug passable to get_building_detail, which returns the building-level initial state including component info and neighbourhood hierarchy — the same structural pattern as get_listing_detail.
Neighbourhood Statistics
get_neighbourhood_stats accepts a slug (e.g., 'toronto/king-west'), a locality_id, or a neighbourhood_id. The data response contains summary_stats, area_stats with historical chart data broken down by year and bed type, and an insights object with current averages for price, price per square foot, and days on market. Area descriptions are also included.
Mortgage Tools
get_mortgage_rates returns live rates from Canadian lenders, parameterised by purchase_price and down_payment. Each rate object includes lender_name, rate, rate_type (fixed or variable), mortgage_term, monthly_payment, rate_hold_days, and a logo_url. calculate_mortgage runs the standard Canadian mortgage formula (semi-annual compounding) locally and returns principal, monthly_payment, total_interest, and total_mortgage for any combination of price, down_payment, rate, and amortization years.
The Condos API is a managed, monitored endpoint for condos.ca — not a raw scraper you maintain. Every endpoint is automatically health-checked on a schedule, and when condos.ca changes and a check fails, the API is automatically queued for repair and re-verified. It is built to keep working as the site underneath it changes.
This isn't an official condos.ca API — it's an independent, maintained REST wrapper over public data. Where the source has no official API (or only a limited one), Parse gives you a stable contract over a source that never promised one, and keeps it current. Need a new endpoint or field? You can revise it yourself in plain English and the agent rebuilds it against the live site in minutes — contributing the change back to the shared API is free.
Will this API break when the source site changes?+
Is this an official API from the source site?+
Can I fix or extend this API myself if I need a new endpoint or field?+
What happens if I call an endpoint that has an issue?+
- Build a condo search portal filtered by bed type and price range using
search_listingsMLS data. - Track pre-construction launch pricing and developer names across Toronto developments with
search_preconstruction. - Display historical sold price trends by bedroom type for any neighbourhood using
get_neighbourhood_statschart data. - Compare current Canadian mortgage rates by term and type for a given purchase price via
get_mortgage_rates. - Embed a mortgage affordability calculator using
calculate_mortgagewith semi-annual compounding. - Resolve neighbourhood hierarchy and area metadata for a specific listing using the
areasDatafield fromget_listing_detail. - Show average price-per-square-foot and days on market for a locality to support investment research with
get_neighbourhood_statsinsights.
| Tier | Price | Credits/month | Rate limit |
|---|---|---|---|
| Free | $0/mo | 100 | 5 req/min |
| Hobby | $30/mo | 1,000 | 20 req/min |
| Developer | $100/mo | 5,000 | 100 req/min |
One credit = one API call regardless of which marketplace API you call. Exceeding the rate limit returns a 429 response. Authenticate with the X-API-Key header.
Does Condos.ca have an official developer API?+
How does the bedroom filter work in `search_listings`?+
beds parameter takes a range string rather than a plain integer. Use '1-1' for 1-bedroom, '1.1-1.9' for 1-bedroom-plus-den, '2-2' for 2-bedroom, and '3-3' for 3-bedroom. The decimal range notation distinguishes den configurations from whole-bedroom counts.What geographic coverage does `get_neighbourhood_stats` support?+
slug nor a neighbourhood_id is supplied, it defaults to locality_id 1 (Toronto). Coverage outside the Toronto market is not currently documented in the response schema. You can fork the API on Parse and revise it to add additional locality IDs or regions if the underlying data supports them.Does the API return sold transaction history or only active listings?+
search_listings returns active listings only. Historical sold and leased price data is available at the aggregate level through get_neighbourhood_stats (in the area_stats field, broken down by year and bed type), but individual sold transaction records are not exposed. You can fork the API on Parse and revise it to add a sold-listings endpoint if that granularity is needed.Are listing images or floor plans returned by any endpoint?+
get_listing_detail and get_building_detail return structural metadata — component IDs, area types, neighbourhood hierarchy — rather than media assets. You can fork the API on Parse and revise it to include media fields if they are accessible from the listing page state.