Build a care-home directory
Find nursing-home locations in Devon, with published CQC details and missing values kept visible.
What the output looks like
Five saved rows and six selected columns from the DataScoop import recorded at . This is the import time, not the date each record was updated.
| Name | Provider | Primary service type | Postcode | Overall rating | Latest check |
|---|---|---|---|---|---|
| Spring House | BRAND Elysium Healthcare | Nursing homes | EX2 4PD | Requires improvement | 2022-08-16 |
| The Harry Care Home | Nursing homes | EX39 1JD | |||
| Pinewood Residential Home | Nursing homes | EX9 6JP | 2019-08-07 | ||
| Woodhayes | Nursing homes | EX2 4LR | Good | ||
| Park Lane Care Home | Nursing homes | EX32 9AL | Good | 2018-12-05 |
These five saved rows were captured on 17 October using localAuthority=Devon, the older contains filter. The current request below uses localAuthorityExact=Devon. The saved table is a dated illustration, not a claim about the rows or count in today's exact result.
Check the scope and fields
CQC covers England. This request selects the Devon local-authority name exactly; it does not include the separate Plymouth or Torbay authorities. The service-type filter matches Nursing homes within a location's listed service types.
- A row is a registered location, not a unique provider. A provider can appear more than once.
- Names, provider details, addresses, service types and published contact fields are available where supplied. Ratings and beds depend on the imported source; neither is complete for every location. There is no email column or registered-manager name in the public output.
- The latest-check field is separate from the rating date and DataScoop's import date. Blank values stay blank. The data does not show current vacancies or care fees.
Source: Care Quality Commission. Contains public sector information licensed under the Open Government Licence v3.0. Source: Care Quality Commission (CQC). This product is not endorsed by or affiliated with the CQC.
The current request's filters
careHometrue
Keep care homes onlylocalAuthorityExactDevon
Exact name and caseserviceTypeNursing homes
Contains; case-insensitive
strict_filters=1 rejects invalid or unknown nonempty filters. It does not change a contains filter into an exact match.
Use this with an assistant
In an assistant that supports hosted MCP, add https://datascoop.io/mcp using its connection settings. A key is optional for a free preview. Keep any key in the connection settings; do not paste it into a prompt.
Find nursing-home locations in the Devon local-authority area using DataScoop's CQC dataset. Use careHome=true, localAuthorityExact=Devon and serviceType=Nursing homes. Start with 25 rows. Show the name, provider, postcode, published overall rating and latest check where available. Leave missing values blank. Include the source, recorded import date and whether more rows match. Do not turn this list into a recommendation of which home to choose.
Ask the assistant to inspect get_dataset_schema, then call query_dataset with these arguments:
{
"dataset": "cqc",
"filters": {
"careHome": "true",
"localAuthorityExact": "Devon",
"serviceType": "Nursing homes"
},
"strict_filters": true,
"limit": 25,
"offset": 0
}Read total, returned, truncated, applied_filters and provenance.imported_at before describing the result. If more rows match, request further pages only when you need them. A failed query or an empty result is not evidence that no such businesses exist.
Use this in your app
These examples use standard libraries: Node.js 20 or later, or Python 3. Save the file, then run it from a terminal. No account or paid AI model is needed to try a free query. If you have a DataScoop key, set DATASCOOP_API_KEY in your environment; it is sent as a Bearer header.
The code requests 25 rows per page, supports free pagination and stops above 2,500 matching rows or 100 pages. It prints JSON only after all reported rows have been retrieved. A zero-match result prints an empty row list; errors exit without printing a partial list.
JavaScript · Node.js 20+
Save as query.mjs, then run node query.mjs. Download the JavaScript example.
// Node.js 20+. No packages required. Optional key: DATASCOOP_API_KEY.
const endpoint = "https://datascoop.io/v1/datasets/cqc/query";
const dataset = "cqc";
const filters = {
"careHome": "true",
"localAuthorityExact": "Devon",
"serviceType": "Nursing homes"
};
const PAGE_SIZE = 25, MAX_ROWS = 2500, MAX_PAGES = 100;
const headers = { Accept: "application/json" };
const key = (process.env.DATASCOOP_API_KEY || "").trim();
if (key) headers.Authorization = "Bearer " + key;
async function retrieve() {
const rows = [];
let total = null, importedAt = null, first = null;
for (let page = 0; page < MAX_PAGES; page++) {
const url = new URL(endpoint);
url.search = new URLSearchParams({ ...filters, strict_filters: "1",
limit: String(PAGE_SIZE), offset: String(rows.length) });
const response = await fetch(url, { headers, signal: AbortSignal.timeout(30000) });
if (!response.ok) throw new Error("Query failed: HTTP " + response.status +
". Check filters and access; retry later for rate limits or server errors.");
const result = await response.json();
if (result.dataset !== dataset || !Array.isArray(result.rows) ||
result.rows.some(row => !row || typeof row !== "object" || Array.isArray(row)) ||
!Array.isArray(result.ignored) || result.ignored.length ||
!Number.isSafeInteger(result.total) || result.total < 0 ||
result.offset !== rows.length || result.returned !== result.rows.length ||
result.returned > PAGE_SIZE || typeof result.truncated !== "boolean") {
throw new Error("Unexpected query response; no partial result was printed.");
}
if (result.total > MAX_ROWS) throw new Error("More than " + MAX_ROWS +
" rows match. Narrow the filters or review the bound before increasing it.");
for (const [name, value] of Object.entries(filters)) {
if (String(result.applied_filters?.[name]) !== String(value))
throw new Error("A requested filter was not applied: " + name);
}
const imported = result.provenance?.imported_at;
if (typeof imported !== "string" || !Number.isFinite(Date.parse(imported)))
throw new Error("Import date is missing; no partial result was printed.");
if (first === null) { first = result; total = result.total; importedAt = imported; }
if (result.total !== total || imported !== importedAt)
throw new Error("The import or match count changed. Run the request again.");
const next = rows.length + result.returned;
if (next > total || result.truncated !== (next < total) ||
(result.returned === 0 && next < total))
throw new Error("Pagination stopped making sense; no partial result was printed.");
rows.push(...result.rows);
if (rows.length === total) return { dataset, filters, total, rows,
provenance: first.provenance, licence: first.licence, attribution: first.attribution };
}
throw new Error("Page limit reached. Narrow the filters; no partial result was printed.");
}
try {
const result = await retrieve();
if (result.total === 0) console.error("No matching records. Check the selected area and filters.");
// Keep provenance and attribution with cached or republished data.
console.log(JSON.stringify(result, null, 2));
} catch (error) {
console.error(error instanceof Error ? error.message : "Request failed.");
process.exitCode = 1;
}
Python · standard library
Save as query.py, then run python3 query.py. Download the Python example.
# Python 3. No packages required. Optional key: DATASCOOP_API_KEY.
import json
import os
import sys
from datetime import datetime
from urllib.error import HTTPError, URLError
from urllib.parse import urlencode
from urllib.request import Request, urlopen
ENDPOINT = "https://datascoop.io/v1/datasets/cqc/query"
DATASET = "cqc"
FILTERS = json.loads("{\"careHome\":\"true\",\"localAuthorityExact\":\"Devon\",\"serviceType\":\"Nursing homes\"}")
PAGE_SIZE, MAX_ROWS, MAX_PAGES = 25, 2500, 100
HEADERS = {"Accept": "application/json"}
key = os.environ.get("DATASCOOP_API_KEY", "").strip()
if key:
HEADERS["Authorization"] = "Bearer " + key
def text_value(value):
return "true" if value is True else "false" if value is False else str(value)
def retrieve():
rows, total, imported_at, first = [], None, None, None
for _ in range(MAX_PAGES):
params = dict(FILTERS, strict_filters="1", limit=PAGE_SIZE, offset=len(rows))
request = Request(ENDPOINT + "?" + urlencode(params), headers=HEADERS)
with urlopen(request, timeout=30) as response:
result = json.load(response)
if (not isinstance(result, dict) or result.get("dataset") != DATASET or
not isinstance(result.get("rows"), list) or
any(not isinstance(row, dict) for row in result["rows"]) or
not isinstance(result.get("ignored"), list) or result["ignored"] or
type(result.get("total")) is not int or result["total"] < 0 or
type(result.get("offset")) is not int or result["offset"] != len(rows) or
type(result.get("returned")) is not int or
result.get("returned") != len(result["rows"]) or
result["returned"] > PAGE_SIZE or type(result.get("truncated")) is not bool):
raise ValueError("Unexpected query response; no partial result was printed.")
if result["total"] > MAX_ROWS:
raise ValueError("More than 2500 rows match. Narrow filters or review the bound.")
applied = result.get("applied_filters")
if not isinstance(applied, dict):
raise ValueError("Applied filters are missing.")
for name, value in FILTERS.items():
if name not in applied or text_value(applied[name]) != text_value(value):
raise ValueError("A requested filter was not applied: " + name)
provenance = result.get("provenance")
imported = provenance.get("imported_at") if isinstance(provenance, dict) else None
if not isinstance(imported, str):
raise ValueError("Import date is missing; no partial result was printed.")
datetime.fromisoformat(imported.replace("Z", "+00:00"))
if first is None:
first, total, imported_at = result, result["total"], imported
if result["total"] != total or imported != imported_at:
raise ValueError("The import or match count changed. Run the request again.")
next_offset = len(rows) + result["returned"]
if (next_offset > total or result["truncated"] != (next_offset < total) or
(result["returned"] == 0 and next_offset < total)):
raise ValueError("Pagination stopped making sense; no partial result was printed.")
rows.extend(result["rows"])
if len(rows) == total:
return dict(dataset=DATASET, filters=FILTERS, total=total, rows=rows,
provenance=first["provenance"], licence=first.get("licence"),
attribution=first.get("attribution"))
raise ValueError("Page limit reached. Narrow filters; no partial result was printed.")
try:
result = retrieve()
if result["total"] == 0:
print("No matching records. Check the selected area and filters.", file=sys.stderr)
# Keep provenance and attribution with cached or republished data.
print(json.dumps(result, indent=2))
except HTTPError as error:
print("Query failed: HTTP " + str(error.code) + ". Check filters and access; retry later for rate limits or server errors.", file=sys.stderr)
sys.exit(1)
except (URLError, TimeoutError, ValueError, TypeError, KeyError) as error:
print(str(error), file=sys.stderr)
sys.exit(1)
The code stops if the reported import date or total changes between pages. Requests do not pin a retained snapshot, so an unchanged date does not guarantee that an import cannot cause missing or repeated rows across pages. Keep the source, filters, import date and attribution with saved results; cache them instead of polling.
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