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Choose the interface before writing code
Government data may be exposed through several interfaces. Compare them by permission, completeness, freshness, query flexibility, rate limits, stability and operating effort.
| Method | Use it when | Checks before automating |
|---|---|---|
| Official API | The service documents endpoints and supports your required filters or update schedule. | Authentication, terms, quota, pagination, response format and API version. |
| Bulk extract or direct file | You need a large, stable snapshot and the publisher supplies CSV, JSON or another download. | Format, update schedule, size, license and incremental-update options. |
| HTML retrieval | No suitable structured interface exists and page access is expressly permitted. | Terms, robots.txt, authentication, crawl limits, page structure and change risk. |
Find the authoritative dataset
- Locate the agency’s official dataset page and record the publisher and dataset identifier.
- Look for API documentation, bulk extracts and direct-download links. Data.gov supports dataset search and metadata retrieval; the federal Site Scanning Program publishes API and bulk CSV/JSON access.
- Confirm that the interface contains the fields, historical range and update cadence your job needs.
Read permission and usage rules
Public visibility is not blanket permission to automate. Read the service’s terms and the dataset’s “Access and Use Information.” Data.gov says most U.S. federal data available through it is free and without restriction, while warning that dataset-specific exceptions and non-federal licensing can differ.
Rules can be service-specific. SAM.gov terms prohibit automated data gathering and web-scraping tools; detected automation can cause associated accounts to be denied access through Login.gov. Do not generalize that rule to every government site, and never bypass authentication, bot challenges or other technical controls.
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Use robots.txt correctly
Digital.gov describes robots.txt as crawler guidance, not an authorization system. A compliant crawler can still violate terms, and a disallowed path should not be treated as an invitation to find a workaround. Check robots.txt alongside the terms, API documentation and any stated crawl-delay. Stop when the service denies access.
Automate an official API
Authentication and secrets
Create credentials through the agency’s documented process. Keep keys in environment variables or a secret manager, never in source control or logs. Confirm whether the key belongs in a query parameter, header or OAuth flow.
Pagination, validation and bounded retries
Implement the API’s documented pagination model, validate required fields and retry only transient failures. Use exponential backoff with a maximum attempt count; do not retry authentication errors or permission denials indefinitely.
import os, time, requests
API_KEY = os.environ["GOV_API_KEY"]
endpoint = "https://api.example.gov/v1/records"
params = {"api_key": API_KEY, "limit": 100, "page": 1}
records = []
while True:
response = requests.get(endpoint, params=params, timeout=30)
if response.status_code == 429:
retry_after = int(response.headers.get("Retry-After", "10"))
time.sleep(min(retry_after, 120))
continue
response.raise_for_status()
payload = response.json()
batch = payload.get("results", [])
records.extend(batch)
next_page = payload.get("next_page")
if not next_page or not batch:
break
params["page"] = next_page
print(f"Retrieved {len(records)} records")Replace the endpoint, parameter names and pagination fields with those in the target service’s documentation. Save the response headers and request parameters with each run when policy permits.
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Respect quotas and response headers
Data.gov’s undated live guidance lists 1,000 requests per hour for a personal API key. Its DEMO_KEY is limited to 30 requests per IP per hour and 50 per IP per day. The api.data.gov developer manual describes a default limit of 1,000 requests per hour per API key, while noting that individual services can vary. Inspect the service’s limit headers instead of assuming these values apply elsewhere.
Schedule work below the documented ceiling, cache unchanged responses and use a bulk file when the API would require thousands of small calls.
Prefer bulk files for large snapshots
A direct CSV or JSON download is often simpler and more reproducible than iterating through an API. Download to a temporary filename, verify the HTTP status and content type, record the file size and checksum, then atomically rename it into your data directory.
- Record the publisher, dataset identifier, download URL, retrieval timestamp and advertised publication or update date.
- Check whether the file is compressed, paginated or split into parts before parsing.
- Validate column names, row counts, encodings, date ranges and required identifiers.
- Keep the original file immutable; write cleaned data to a separate location with a transformation log.
The federal Site Scanning Program is an example of a government service offering both API access and bulk CSV/JSON files. Its guide describes more than 1.5 million fields covering about 26,000 federal .gov and .mil websites from daily scans; those figures describe that program, not government data generally.
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If HTML retrieval is the only permitted option
Check access before crawling
- Read the current terms and dataset-specific notices.
- Review robots.txt and any explicit crawl-delay or API recommendation.
- Confirm that the pages are accessible without defeating a login, CAPTCHA, paywall or rate control.
- Start with one page and a low request rate; stop on a denial or block.
Make the crawler conservative
Send a descriptive User-Agent with a contact address, maintain a small concurrency limit, honor Retry-After, cache pages and avoid downloading unchanged assets. Parse semantic labels rather than brittle screen coordinates, and write tests for missing, renamed and reordered fields.
The National Archives (UK) publishes a service-specific example allowing up to 3,000 requests in any five-minute period. That figure is not a general government-site rule; use the target service’s own limit instead.
Make every run reproducible
For each retrieval, store:
- Publisher, dataset identifier and interface type.
- Endpoint or exact download URL.
- Query parameters, request headers that affect results and code version.
- Retrieval timestamp, dataset publication date or version and response status.
- File checksum or raw response location.
- Transformations, filters, rejected-record counts and validation results.
- The terms or access notice consulted and its consultation date.
Record the source’s update cadence before scheduling. A daily job against a monthly dataset wastes quota; a monthly job against daily data creates stale results.
Performance, reliability and cost controls
Reduce requests
- Use server-side filters, field selection and pagination limits.
- Prefer incremental parameters such as modified-since when documented.
- Cache metadata and unchanged pages.
- Choose a bulk extract when a complete refresh would exceed practical API quotas.
Handle failure safely
- Set connect and read timeouts.
- Retry transient network errors and 429 or selected 5xx responses with capped exponential backoff.
- Persist a checkpoint after each page or file so a restart does not duplicate work.
- Alert on schema changes, unusually small result sets, authentication failures and repeated throttling.
Protect downstream users
Separate raw and transformed datasets, retain rejected records for review and expose the retrieval timestamp with published outputs. Never silently substitute an old cache when freshness is required; mark fallback data clearly.
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Troubleshooting common failures
401 or 403 response
Check the credential location, scope, expiration and required headers. Re-read the service terms; a valid key does not override a dataset restriction.
429 Too Many Requests
Read Retry-After and rate-limit headers, lower concurrency, add backoff and check whether another process shares the same key or IP. Do not rotate keys to evade a quota.
Empty or incomplete results
Verify pagination, default filters, date zones and maximum page size. Compare one API response with the dataset’s human-facing page or a small official download.
Schema or parser breakage
Preserve the raw response, compare field names and types with the documented schema, and fail loudly when required fields disappear. Update the parser only after confirming the publisher’s change.
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Blocked HTML requests
Stop and review terms, robots.txt and the service’s recommended interface. Switch to the official API or download rather than attempting to evade a block.
Or skip the browser setup
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See the ScreenshotNeo documentation for all options. cURL:
curl -G "https://api.screenshotneo.com/v1/shot" -d access_key=YOUR_API_KEY --data-urlencode url=https://stripe.com -o shot.webpPython:
import requests
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open("shot.webp", "wb").write(r.content)Node.js:
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Frequently Asked Questions
Is robots.txt permission to scrape a government website?
No. It is crawler guidance. The service’s terms, access controls and API documentation still govern what automation is allowed to do.
Should I use an API or download a file?
Use the documented API for selective or frequent queries; use a bulk extract for large, stable snapshots when one is available.
Quick Recap
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