If you are evaluating a beach data API, one of the first questions is simple: what does the actual payload look like when you request a beach and then request its recent conditions? Beach Day API is easiest to understand when you look at a real response, see which fields stay stable across endpoints, and decide how those fields map into your product.
In this walkthrough, we use real Beach Day API responses for Bondi Beach in Australia to show the difference between a beach profile record and a conditions record. The goal is to help developers and technical buyers understand what each endpoint returns, which fields are nested, and how to use the data in travel, weather, rental, and coastal safety products.
The two records most teams start with
For many integrations, the first two calls that matter are:
- GET /v1/beaches/{id}/ for a beach profile
- GET /v1/beaches/{id}/conditions/ for recent condition snapshots
The profile endpoint gives you the stable identity and descriptive context for a beach. The conditions endpoint gives you time-based operational data such as water quality, weather, ocean conditions, tides, and Beach Day Score snapshots.
A real beach profile example
We polled the live API for Bondi Beach using a user dashboard key and received a profile object with fields like these:
{
"id": 1707,
"name": "Bondi Beach",
"state": "AU-NSW",
"country": "Australia",
"county": "Waverley Council",
"city": "Sydney City",
"latitude": -33.891157,
"longitude": 151.278267,
"description": "Ocean beach in Sydney. Councils: Waverley Council.",
"beach_day_score": 72.0,
"water_quality": {
"grade": "A",
"source": "NSW BeachWatch",
"updated": "2026-07-06",
"advisory": null,
"bacteria_level": "Unlikely"
},
"weather": {
"temp_f": 52.3,
"humidity": 96,
"uv_index": 0.0,
"wind_mph": 33.8,
"condition": "drizzle",
"precip_in": 0.0,
"feels_like_f": 48.9
},
"ocean_conditions": {
"water_temp_f": null,
"wave_height_ft": null,
"rip_current_risk": null
},
"rules": [],
"amenities": []
}This is useful because it shows that the profile endpoint is not only static directory metadata. It can also include the current score and current nested condition summaries directly on the beach object. For many product teams, that means a single detail call can power a beach page, a destination detail panel, or a recommendation card.
What the profile fields mean
Identity and geography
Fields such as id, name, state, country, county, city, latitude, and longitude give you the beach identity and map position. These are the fields you use to join beach data into your own search results, route planning flows, map markers, and destination pages.
Description and source context
The description field helps with UI copy and fallback content. Nested objects like water_quality also include a source name and update date, which is important if you need to explain provenance to users or compliance teams.
Current operational summary
The top-level beach_day_score, plus the nested water_quality, weather, and ocean_conditions objects, make the profile endpoint useful as a quick summary layer. If your app only needs the latest state for a beach page, this payload may already cover most of what you need.
Structured but sparse arrays
In this Bondi sample, rules and amenities are present but empty. That is still valuable. It tells developers to expect these keys consistently, while also planning for beaches where some sub-datasets may not yet be populated. A robust integration should treat empty arrays and null values as normal, not as API failures.
A real conditions response example
The conditions endpoint returns a time series rather than a single beach object. For Bondi Beach, the response looked like this:
{
"beach_id": 1707,
"count": 3,
"results": [
{
"id": 14605,
"beach_id": 1707,
"date": "2026-07-06",
"water_quality": {
"grade": "A",
"source": "NSW BeachWatch",
"updated": "2026-07-06",
"advisory": null,
"bacteria_level": "Unlikely"
},
"weather": {
"temp_f": 52.3,
"humidity": 96,
"uv_index": 0.0,
"wind_mph": 33.8,
"condition": "drizzle",
"precip_in": 0.0,
"feels_like_f": 48.9
},
"ocean_conditions": {
"water_temp_f": null,
"wave_height_ft": null,
"rip_current_risk": null
},
"tides": null,
"beach_day_score": 72.0
},
{
"id": 2098,
"beach_id": 1707,
"date": "2026-06-29",
"water_quality": {
"grade": "C",
"source": "NSW BeachWatch",
"updated": "2026-06-29",
"advisory": null,
"bacteria_level": "Possible"
},
"beach_day_score": 58.0
}
]
}This is where the API becomes more useful for trend-aware products. Instead of only seeing the latest state, you can inspect change over time. In this sample, the most recent record shows an A water quality grade and a Beach Day Score of 72.0, while the earlier snapshot shows a C grade and a score of 58.0. That is enough signal to build trend views, recent-history cards, alerting logic, or internal QA tooling.
How the conditions record differs from the profile record
The profile record answers the question, what is this beach? The conditions record answers, what was happening at this beach on a specific date?
That difference matters in product design:
- Use the profile endpoint for map pins, beach detail pages, search result cards, and general metadata.
- Use the conditions endpoint for historical trends, refresh jobs, notification logic, and date-specific summaries.
- Use both together when you want a stable beach object plus a recent history panel.
Nested objects developers should plan around
One of the more important implementation details is that the most useful fields are nested. That includes:
water_quality.gradewater_quality.sourcewater_quality.updatedwater_quality.bacteria_levelweather.temp_fweather.wind_mphweather.conditionocean_conditions.water_temp_focean_conditions.wave_height_ftocean_conditions.rip_current_risk
That structure is good for clarity, but it means you should flatten or normalize fields before feeding them into analytics dashboards, search indexes, or feature stores. A light transformation layer can make the API much easier to reuse internally.
Nulls and empty arrays are part of the contract
The Bondi sample also shows several null values and empty arrays. For example, tides is null in the conditions response, and some ocean condition metrics are null in both endpoints. This is common in real-world environmental datasets because source coverage and refresh cadence vary by location.
In practice, a production integration should do three things:
- treat nulls as expected for optional subfields
- render graceful fallbacks in the UI instead of blank or broken components
- separate truly missing data from negative states such as an actual advisory
This is especially important for buyer-facing products where a missing wave-height value should not be confused with safe or unsafe surf conditions.
A simple parsing example in Python
If you are building against Beach Day API in Python, the basic pattern looks like this:
import requests
API_KEY = "your_user_dashboard_key"
BASE_URL = "https://beachdayapi.com/v1"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}
beach_id = 1707
profile = requests.get(
f"{BASE_URL}/beaches/{beach_id}/",
headers=HEADERS,
timeout=30,
).json()
conditions = requests.get(
f"{BASE_URL}/beaches/{beach_id}/conditions/",
params={"limit": 7},
headers=HEADERS,
timeout=30,
).json()
latest = conditions["results"][0]
summary = {
"name": profile["name"],
"score": latest.get("beach_day_score"),
"water_grade": (latest.get("water_quality") or {}).get("grade"),
"weather": (latest.get("weather") or {}).get("condition"),
}
That small pattern is enough to support a beach conditions card, a destination summary block, or a daily sync job.
Where this payload structure is especially useful
- Travel apps: enrich destination pages and recommendation modules with live beach context
- Weather products: combine coastal weather views with beach-specific water quality and score data
- Vacation rental platforms: show guests which nearby beach looks best this week
- Tourism and municipal tools: expose a cleaner public-facing layer over mixed coastal source systems
Why this matters when evaluating a beach data API
A beach API is more useful when the records are shaped in a way that product teams can actually ship with. Beach Day API does that well by combining beach identity, score data, and nested condition objects into predictable JSON responses. It also exposes transparent developer resources through the docs, the coverage page, and the pricing page.
If you want to understand the platform quickly, start by pulling one beach profile and one conditions record for a beach you already know. That will tell you how much UI, caching, and normalization work you need for your own product. In many cases, it is less than teams expect.