DEV Community: drew

Get new UK planning applications near any postcode as a weekly spreadsheet (no code)

drew — Sat, 31 Oct 2026 11:04:08 +0000

Builders, solar installers, architects, surveyors and local journalists all watch the same thing: new planning applications. Each council publishes them on its own portal, which means a different search form, layout and export button (when there is one) for every area you cover.

This guide shows how to get them into one spreadsheet, filtered by keyword and distance from a postcode, and how to set it up so that every week you only receive the applications you haven't seen yet. No code is needed.

Disclosure: I built the Apify Actor used here. The data comes from PlanIt, an open aggregator of UK council planning data. The Actor is a client for its public API.

What you get

One row per application:

council, reference, address and postcode
the description ("Installation of 12 roof-mounted solar panels...")
application type and size (Small / Medium / Large)
status (Undecided, Permitted, Conditions, Rejected, Withdrawn...)
received, validated, decided and consultation-end dates
latitude/longitude and a link to the original council page
optional details: agent company, case officer, parish, and document and comment counts

Step 1: Open the Actor

Go to UK Planning Applications Scraper on Apify You can also browse recent applications by council on Rowsift. and click Try for free. You'll need a free Apify account.

Step 2: Say what and where

Example: house extensions within 5 km of central Leeds from the last 14 days.

{
  "search": "extension",
  "postcode": "LS1 4AP",
  "radiusKm": 5,
  "recentDays": 14,
  "maxItems": 200
}

Other useful filters:

authorities: whole councils instead of a radius, e.g. ["Leeds", "Bradford"]
appState: e.g. "Permitted" to see only approved schemes
appSize: "Large" to focus on bigger developments
startDate / endDate: a fixed window instead of "last N days"

Keyword ideas by trade: solar, loft conversion, HMO, heat pump, dropped kerb, change of use, demolition.

Step 3: Export

When the run finishes, open the Output tab and export as CSV, Excel or JSON, or connect it to Google Sheets with Apify's integration.

Step 4: Make it a weekly feed of only new applications

Tick incremental in the input. The Actor remembers what it already delivered for that same input and skips it next time, so you only pay for new rows.
Create a Schedule in Apify (e.g. every Monday 07:00).
Optionally, add a Google Sheets or email integration so the new rows land somewhere you'll see them.

You now have a Monday-morning list of fresh, local, relevant applications.

What does it cost?

Pay per result, with no subscription to the Actor: $0.012 per application (about $12 per 1,000) plus a $0.003 start fee per run. Detailed rows (includeDetails) are $0.02 each. A weekly local search usually returns a handful to a few dozen rows (that Leeds search returned 8 when I tested it on 31 Oct 2026), so it costs pennies a week. Apify's free plan includes monthly platform credit, enough to try it.

For developers

You can call the same thing from code or from an AI agent (the Actor works as an MCP tool):

curl -X POST "https://api.apify.com/v2/acts/devteamdrew~uk-planning-applications/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  -d '{"search":"extension","postcode":"LS1 4AP","radiusKm":5,"recentDays":14,"maxItems":50}'

Set "outputFormat": "llm" to get a compact Markdown block per application for RAG or summarising.

Notes and limits

Coverage and freshness depend on PlanIt's council feeds. Most English, Welsh and Scottish councils are included, but a few update slowly.
This is public planning data. If you use it for outreach, follow UK GDPR and PECR, and don't treat individual applicants' addresses as a marketing list.

Questions or a council that looks wrong? Leave a comment and I'll take a look.

Scrape Bluesky posts and profiles without an API key

drew — Fri, 30 Oct 2026 17:02:16 +0000

Bluesky is unusually open: almost everything public is available through the AT Protocol's public AppView API at public.api.bsky.app / api.bsky.app, with no login. (Tested 30 Oct 2026: post search returned 403 on public.api.bsky.app but worked on api.bsky.app. Profiles and feeds worked on both.) Here's how to use it directly, and how to get the same data with no code at all.

Disclosure: I built the Apify Actor shown in part 2.

Part 1: The raw API (no key needed)

Search recent posts:

curl "https://api.bsky.app/xrpc/app.bsky.feed.searchPosts?q=web%20scraping&sort=latest&limit=5"

Look up a profile:

curl "https://public.api.bsky.app/xrpc/app.bsky.actor.getProfile?actor=bsky.app"

Get an account's posts:

curl "https://public.api.bsky.app/xrpc/app.bsky.feed.getAuthorFeed?actor=bsky.app&limit=10"

This works fine for one-off calls. You'll start writing plumbing once you need cursor pagination, rate-limit backoff, flattening nested record/embed objects, extracting links and hashtags from facets, and remembering which posts you've already seen.

Part 2: No-code with the Bluesky Scraper Actor

Bluesky Scraper on Apify handles that plumbing. Pick a mode (Search posts, Search profiles or Posts from accounts) and enter queries. Bluesky's search syntax works, e.g. from:handle, lang:en and #hashtags.

Input from a real run:

{
  "mode": "searchPosts",
  "queries": ["web scraping"],
  "maxItems": 20,
  "sort": "latest",
  "outputFormat": "both"
}

That run finished in about 3 seconds. One of the items, exactly as returned:

{
  "type": "post",
  "url": "https://bsky.app/profile/hugovalters.bsky.social/post/3mz3rucjn3h2o",
  "text": "Fill web forms from a JSON file using Playwright. 136 lines, intermediate level, takes a screenshot after submit so you can verify. Built for QA and smoke tests. #python #playwright #scraping https://www.valtersit.com/python/playwright-browser-automation-for-form-filling/",
  "createdAt": "2026-10-30T12:30:00.600753Z",
  "authorHandle": "hugovalters.bsky.social",
  "likeCount": 0,
  "repostCount": 0,
  "replyCount": 0,
  "quoteCount": 0,
  "links": ["https://www.valtersit.com/python/playwright-browser-automation-for-form-filling/"],
  "imageCount": 0,
  "isReply": false,
  "query": "web scraping",
  "markdown": "## Post by @hugovalters.bsky.social\n- **url:** https://bsky.app/profile/hugovalters.bsky.social/post/3mz3rucjn3h2o\n- **date:** 2026-10-30T12:30:00.600753Z\n- **likes:** 0 ..."
}

outputFormat: "both" adds the markdown field, a compact version that's easy to drop into an LLM prompt or a RAG index.

Monitoring a keyword or brand

Turn on incremental mode and add a schedule (for example, hourly). Each run returns only posts it hasn't returned before, so you can wire a webhook to Slack, a Google Sheet or your own endpoint without dealing with duplicates.

Exporting

Dataset → Export → CSV/Excel/JSON, or call the run's dataset API from your code.

Cost

$0.003 per run plus $0.001 per result, so 1,000 posts cost about $1. Small tests fit in Apify's free monthly credit.

Be a good citizen

It's public data, but it's still people's posts. Respect deletions, don't build profiles on individuals, and follow Bluesky's developer guidelines and UK/EU GDPR if you store personal data.

What would you monitor on Bluesky? Let me know in the comments.

How to pull UK Companies House data into a spreadsheet without code

drew — Fri, 30 Oct 2026 17:01:41 +0000

If you've ever needed a list of UK companies (suppliers to check, leads in a sector, or the directors behind a competitor), you've probably copied rows out of the Companies House website one at a time. The data is public and comes from a good official API, but that API needs a key, pagination and some JSON wrangling.

This guide shows how to get the same data into a spreadsheet without writing any code, using a ready-made Apify Actor that calls the official Companies House Public Data API for you.

Disclosure: I built the Actor used here. Everything it returns comes from Companies House's own API.

What you get

For each company:

company number, name, status (active/dissolved) and type (ltd, plc…)
incorporation and dissolution dates
SIC codes (industry)
registered address and postcode
next accounts and confirmation statement due dates
flags for charges and insolvency history
optionally: current and past officers (directors, secretaries) and the 25 most recent filings

Step 1: Open the Actor

Go to Companies House Scraper on Apify and click Try for free. You'll need a free Apify account. You don't need your own Companies House key, but you can paste one in for dedicated rate limits.

Step 2: Enter what you're looking for

You can search by name/keyword, or paste exact company numbers. Here's the input I used:

{
  "searchQueries": ["tesco"],
  "maxItems": 5,
  "includeOfficers": true
}

Other useful switches:

Only active companies: skips dissolved and liquidated ones
Include filing history: adds recent filings
Incremental mode: on a schedule, returns only companies you haven't already received (handy for watching new incorporations matching a keyword)

Step 3: Run it and look at the output

That run returned 5 companies in about 8 seconds. Here's the first record, trimmed to the first two officers:

{
  "companyNumber": "00445790",
  "url": "https://find-and-update.company-information.service.gov.uk/company/00445790",
  "name": "TESCO PLC",
  "status": "active",
  "type": "plc",
  "incorporatedOn": "1947-11-27",
  "sicCodes": ["47110"],
  "registeredAddress": "Tesco House, Shire Park, Kestrel Way, Welwyn Garden City, AL7 1GA, United Kingdom",
  "postcode": "AL7 1GA",
  "jurisdiction": "england-wales",
  "accountsNextDue": "2027-08-26",
  "confirmationStatementNextDue": "2027-07-02",
  "hasCharges": false,
  "hasInsolvencyHistory": false,
  "officers": [
    { "name": "TAYLOR, Christopher Jon", "role": "secretary", "appointedOn": "2025-04-14", "resignedOn": null },
    { "name": "BETHELL, Melissa", "role": "director", "appointedOn": "2018-09-24", "resignedOn": null, "nationality": "British" }
  ]
}

Step 4: Export to a spreadsheet

In the run's Storage → Dataset tab, click Export and choose CSV or Excel. Fields are flat, so they open as clean columns. To send rows straight to Google Sheets, use Apify's Google Sheets integration on the Actor's Integrations tab, or schedule the Actor and add the integration so the sheet updates itself.

What it costs

Pricing is pay-per-event: $0.003 per run start, $0.008 per company, and $0.02 per enriched company (with officers/filings). So 100 basic company records cost about $0.80 plus the start fee. Apify's free plan includes monthly usage credit, which covers small tests.

Ideas

Lead lists: search a sector keyword ("coffee roasters", "solar"), keep active companies, export to CSV.
Supplier checks: paste company numbers, turn on officers and filings, and look for insolvency flags.
New-company watch: schedule daily with incremental mode on.

A note on personal data: officer names are public register data, but if you use them for outreach, UK GDPR still applies (legitimate interest, an opt-out, and no special-category data).

Questions or missing fields? Leave a comment, I'm actively improving it.