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To automate weather data collection, first check whether a documented weather API provides the locations, variables, and time span you need. An API usually gives you structured responses that are easier to parse and maintain than values extracted from a rendered web page. Scrape a weather page only when the needed information is available there, automated access is allowed by that site, and you cannot get the data through a suitable documented interface.
This guide shows how to plan a weather-data pipeline, make a Python request to a documented API, scrape an accessible page when necessary, and handle caching, attribution, and failures. The examples use MET Norway’s API documentation as a reference; product versions, fields, and provider rules can change, so check the current documentation before deploying.
Decide what weather data you need before choosing a source
“Weather data” can mean a forecast, a past observation, or a rendered summary on a web page. Before writing code, turn the request into specific requirements. The right source depends on these choices, not just on whether a page can be scraped.
- Geography: list the locations and check whether the provider covers them. MET Norway identifies its Locationforecast product as global and its Frost product as a REST API for meteorological observations; verify current product details in its interface documentation.
- Purpose and period: decide whether you need forecasts or observations, how far back historical data must go, and whether the provider offers the relevant product.
- Variables and units: name the fields you require, such as temperature or precipitation, and confirm the selected product supplies them in usable units.
- Timing and resolution: specify how often your application needs an update and the time intervals it can use. Do not request data more frequently than the service’s rules and cache guidance allow.
- Use and distribution: check the source’s terms, attribution requirements, and commercial-use conditions before building a production workflow.
These checks prevent a common failure: collecting a field from a page that looks useful but does not provide the geography, history, or update cadence the application actually needs.
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Choose an API or a web page
Start with a documented API when it fits
A documented API is generally the better starting point when it exposes the required data. Its documentation describes products, parameters, response formats, and service expectations. MET Norway’s general Weather API usage guide describes encrypted HTTPS and HTTP GET requests; responses may be JSON, XML, or product-specific binary data. Parse the schema for the product you select rather than assuming one provider’s fields or format apply to another.
MET Norway’s API interface documentation identifies its documentation as version 3 and lists products including Locationforecast 2.0 and Frost 0.9. Those are documentation product labels, not a promise that versions or availability will remain unchanged. Check the live product documentation before coding.
Scrape only when the page is the appropriate source
Page scraping can be useful when the required information is published on an accessible page and no suitable documented data interface meets the need. A page is not automatically permission to automate access just because a human can view it. Check the specific website’s current terms and access rules; this guide makes no blanket legal claim about scraping.
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Rendered pages also make brittle data sources. A redesign, changed labels, dynamic content, or a new consent dialog can break a selector without changing the underlying weather. If the provider offers a documented API for the same information, prefer it over scraping the page’s presentation layer.
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For a real deployment, use the endpoint and parameters documented for the chosen product. The example below shows the request-and-parse pattern for MET Norway’s Locationforecast product. It requests a compact forecast for a latitude and longitude, sends an identifying User-Agent, checks the HTTP response, and reads the JSON payload. Confirm the current endpoint, fields, and any required client identification in MET Norway’s Getting Started guide and usage documentation before running it.
import requests
endpoint = "https://api.met.no/weatherapi/locationforecast/2.0/compact"
params = {"lat": 59.91, "lon": 10.75}
headers = {
"User-Agent": "weather-collector/1.0 contact: ops@example.com"
}
response = requests.get(endpoint, params=params, headers=headers, timeout=30)
response.raise_for_status()
data = response.json()
# Keep the original response or extract fields according to the
# current Locationforecast schema documented by MET Norway.
print(data["properties"]["timeseries"][0])Install the dependency with python -m pip install requests. Replace the example contact route with a working way for the service operator to identify or reach the person responsible for the client. A successful request only confirms that a response arrived; it does not prove that you selected the right product or that your downstream interpretation of its schema is correct.
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Scraping a page with Python when an API is not suitable
For page scraping, use the target site’s permitted page and inspect its HTML to choose selectors tied to stable, meaningful elements. This template uses Requests and Beautiful Soup; the CSS selector is intentionally a site-specific value you must determine from the permitted page’s actual markup. Do not assume the same selector works across weather sites.
import requests
from bs4 import BeautifulSoup
page_url = "https://weather.example/your-permitted-page"
headers = {"User-Agent": "weather-collector/1.0 contact: ops@example.com"}
response = requests.get(page_url, headers=headers, timeout=30)
response.raise_for_status()
soup = BeautifulSoup(response.text, "html.parser")
# Replace with a selector verified against this page's HTML.
reading = soup.select_one(".weather-reading")
if reading is None:
raise RuntimeError("Expected weather element was not found")
print(reading.get_text(" ", strip=True))The page URL and selector in this template are illustrative rather than a supplied weather source. Replace them only after checking that automated access is allowed and the page actually contains the data you need. If the content is populated by client-side JavaScript, a basic HTTP request may not contain the rendered value; do not silently treat a missing element as a valid reading. Prefer a documented data endpoint if one is available and appropriate.
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Identify your client and control request volume
MET Norway’s Terms of Service state, “You must identify yourself”. Its guidance asks users to provide an identifying User-Agent where possible, such as an application or domain name and a contact route. Avoid a generic or misleading identity. The same terms say that more than 20 requests per second per application requires special agreement; that is a MET Norway-specific condition, not a universal weather-service limit. Read the current MET Norway Terms of Service for the rules that apply to your use.
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Cache instead of repeating unchanged requests
Do not poll merely because a scheduled job runs. MET Norway asks clients not to repeat requests before the indicated expiry, recommends local caching and conditional requests where supported, and cautions against overloading the service. Store the response and its retrieval time, honor provider expiry information, and use conditional requests only when the provider documents support for them. Apply the actual provider’s instructions rather than importing MET Norway’s behavior into another service.
Log errors and watch for product changes
Check HTTP status codes, retain enough context to diagnose failures, and handle timeouts and malformed or unexpected responses explicitly. MET Norway documents product versioning and advises monitoring deprecation signals. Periodically review the live documentation for endpoint, schema, and product changes; build extraction code so that a missing field raises a visible error instead of being stored as a plausible-looking blank value.
Keep provenance and attribution with your records
For each collected record, preserve practical provenance such as the source, retrieval time, requested location, units, and transformations applied. MET Norway says its open data require appropriate credit, a link to the CC BY 4.0 license, and an indication of changes. Check the applicable license and attribution language for the actual data source, and carry that information wherever you publish or redistribute the data.
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Check commercial terms and request thresholds
Service rules are provider-specific. Open-Meteo’s project guidance says its APIs are free for open-source and non-commercial use, asks applications exceeding 10,000 requests per day to contact the provider, and directs commercial users to contact it. Verify the current guidance and the service terms relevant to your application at Open-Meteo’s project page; do not treat those conditions as applying to other providers.
MET Norway’s terms direct users seeking customized delivery of weather data and products to the ECOMET catalogue. That is a route to investigate for tailored delivery, not a statement that every product or commercial arrangement is available on the same terms.
Troubleshoot common collection failures
- HTTP error or blocked request: inspect the response status and provider guidance. For MET Norway, check that your client is identifiable and that your request pattern follows its current terms; do not retry rapidly in a tight loop.
- Timeout: set a finite timeout, record the failed attempt, and retry later with a bounded backoff rather than launching repeated immediate requests. A timeout is not a weather reading.
- JSON parsing or missing-field error: confirm that you requested the intended product and response format, then compare the response against that product’s current schema. Handle missing data explicitly.
- Page selector returns no result: inspect the current HTML and verify that the page still contains the expected element. The site may have changed its markup or populated content with JavaScript; a selector copied from another page is not reliable.
- Values look stale: check retrieval timestamps, cache expiry, and the provider’s update cadence. Do not defeat cache guidance by making more frequent calls than the source permits.
- Unexpected cost or use restriction: recheck the provider’s current commercial conditions, request thresholds, and the way your application distributes data before launch.
Or skip the browser setup
If your task is to keep a visual record of a weather page rather than extract structured measurements, ScreenshotNeo can return a screenshot from one GET request. A screenshot is an image, not a substitute for parsing API data into temperature, precipitation, or forecast records.
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://www.met.no/ -o shot.webpSee the ScreenshotNeo documentation for request options. Cookie banners, popups, and chat widgets are removed before the shot; bot checks, blank pages, and failed loads are never billed. Its MCP server lets AI agents take screenshots. The free plan includes 1,000 screenshots a month with no card, and paid plans start at $5 for 3,000. Sign up for free.
Frequently Asked Questions
Can a screenshot API collect structured weather readings?
No. A screenshot captures the page as an image; use a documented weather API or an appropriate page parser when you need data fields.
Does public access to a forecast page mean automated scraping is allowed?
Not necessarily. Check the particular site’s current terms and access rules before automating requests.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
