# Boulder CO Restaurant Inspections Scraper — 2013–2026 Snapshot (`groundplanes/boulder-county-restaurant-inspections`) Actor

Scrape Boulder County, CO restaurant inspections Jan 2013 – Jul 2026 (16,346 inspections at snapshot; static snapshot, no updates) via data.colorado.gov: score, result, violations or inspector comments, address, coordinates. Boulder, Longmont, Lafayette, Louisville. Filter by city, name, date.

- **URL**: https://apify.com/groundplanes/boulder-county-restaurant-inspections.md
- **Developed by:** [John](https://apify.com/groundplanes) (community)
- **Categories:** Lead generation, Business, Travel
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.10 / 1,000 inspections

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

The **Boulder County restaurant inspections scraper** gives you one row per restaurant inspection (inspector comments grouped) for **Boulder County, Colorado**, straight from **Boulder County** via the official State of Colorado open-data portal (data.colorado.gov). No login or coding needed: run it in your browser, on a schedule, or through the Apify API, and export results as **JSON, CSV or Excel**.

Get restaurant and food facility inspections for **Boulder County, Colorado** (Boulder, Longmont, Lafayette, Louisville, Niwot, Lyons and more) as clean JSON, CSV or Excel. The data comes from **Boulder County** through the official State of Colorado open-data portal ([data.colorado.gov dataset 6ytb-f2cq](https://data.colorado.gov/d/6ytb-f2cq), Sept 2025 – Jul 2026, and historical dataset [tuvj-xz3m](https://data.colorado.gov/d/tuvj-xz3m), Jan 2013 – Aug 2025).

**This is a one-time snapshot that will not update.** Both source datasets are marked "Never" / "Static" for updates by the state portal. The data runs from **2013-01-02 to 2026-07-21** and contains **16,346 inspections at snapshot** (633 from 6ytb-f2cq + 15,713 from tuvj-xz3m). No inspections after 2026-07-21 will appear.

### What you get

The source publishes **one row per inspector comment**. This actor groups them so that **each row is one inspection**: one facility + inspection type + final inspection date + score + result, with all inspector comments (violations and notes) in a `comments` list. Rows are sorted **newest final inspection first** (stable tiebreak on facility ID and `:id`).

The historical file (2013 – Aug 2025) is published as **one row per checklist item**; the actor groups those into one row per inspection (facility + date + type) too. Historical rows have a `violations` list (items marked Out / Out-High / Out-Medium / Out-Low / Full / Half) instead of free-text comments, `result` is `null` (not published), plus `facilityType` and `facilityCategory`. The `dataset` field tells you which file each row came from. `facilityType` and `facilityCategory` are always present (`null` for Sept 2025+ rows, which don't publish them).

**Linking a facility across both files:** the two files use different `businessId` schemes, so the same facility has two IDs (e.g. PHO KITCHEN BAR & GRILL is `FA0003878` in the historical file and `FA0001508` in the current one). Use `facilityKey` instead: the normalized facility name + street address (uppercase, punctuation removed, street suffixes abbreviated such as ROAD → RD, unit/suite words and a trailing unit number dropped, e.g. `1219 ROCK CREEK CIR 1` → `1219 ROCK CREEK CIR`; N/S/E/W directionals ignored). Chains keep one key per address, so different locations never merge, e.g. `PHO KITCHEN BAR GRILL|2900 BASELINE RD`. It's a best-effort match: renamed facilities, or ones whose address is spelled differently, won't link.

#### Sample output (real run)

```json
{
  "businessId": "FA0001669",
  "facilityName": "SEBS PIZZAS (MOBILE)",
  "address": "1219 ROCK CREEK CIRCLE 1",
  "city": "LAFAYETTE",
  "state": "CO",
  "zip": "80026",
  "inspectionType": "Routine",
  "firstInspectionDate": "2025-09-03",
  "finalInspectionDate": "2026-07-21",
  "score": 25,
  "result": "Pass",
  "commentCount": 2,
  "comments": [
    "3-501.16(A)(2) Cold holding\nPrep refrigerator ambient air temperature 59 degrees F.  \n\nMaintain 41°F and below cold holding.  Ambient temperature in the unit was 107 degrees F.\n\nUnit filled with ice and at ambient temperature of 79 deg. F, the air temperature of the unit was brought down to 35 de...",
    "4-203.12 Temperature Measuring Devices, Ambient Air\nThermometer not available in the prep cooler.\n\nProvide and accurate air thermometer to monitor temperature."
  ],
  "latitude": 39.97449,
  "longitude": -105.07242,
  "source": "Boulder County Public Health via data.colorado.gov"
}
```

### Use cases

- **Food-safety consultants, pest control and cleaning services:** `resultContains: "Reinspection"` lists facilities that failed and must be re-inspected.
- **Restaurant suppliers and equipment repair:** comments mention broken coolers, thermometers, hand sinks.
- **Journalists and researchers:** compare scores across Boulder County towns.

### How to scrape Boulder County restaurant inspections

1. Click **Try for free** (or **Start**) on this page. A free Apify account is enough.
2. Leave the prefilled input to get a quick sample, or set the filters described below.
3. Set **maxItems** to cap how many rows (and how much) a run returns.
4. Click **Start** and wait a few seconds to a minute.
5. Download the results as JSON, CSV or Excel, or connect them to Google Sheets, Zapier, Make or a webhook.

### Input

| Field | Description |
|---|---|
| inspectedSince | Optional real date, YYYY-MM-DD, applied to the final inspection date. Invalid dates fail fast with a clear message. |
| cities | e.g. `BOULDER`, `LONGMONT` (case-insensitive) |
| nameContains | Facility name text |
| resultContains | `Reinspection` or `Pass` (only Sept 2025 – Jul 2026 rows have a result, so this skips history) |
| includeHistory | Default on: add the 15,713 inspections from 2013 – Aug 2025 |
| maxItems | Default 200 |

### Pricing (pay per event)

$3 per 1,000 inspections ($0.003 each) plus Apify's minimal $0.00005 start fee. **Example:** 200 inspections = 200 × $0.003 + $0.00005 ≈ **$0.60**.

### Data caveats

Data is provided **as published by Boulder County**. This is a static snapshot (portal update frequency: Never/Static), newest inspection **2026-07-21**. The two files use different formats and scoring checklists, so scores are not directly comparable across them; 2020 has few inspections (COVID). A full 16k-inspection pull reads ~657k source rows and may take several minutes (default timeout is 600 s). `score` is points as published (higher means more issues). `firstInspectionDate` / `finalInspectionDate` are passed through unchanged even where they look out of order. City names are passed through as published (mixed case).

### License and disclaimer

The source dataset is **Public Domain** (data.colorado.gov). This actor uses only the official public open-data API and is **not affiliated with or endorsed by** Boulder County, Boulder County Public Health or the State of Colorado.

### FAQ

#### How much does it cost to scrape Boulder County restaurant inspections?

You pay $0.003 per result ($3 per 1,000) plus a $0.00005 start fee, and nothing else. Apify's free plan includes $5 of monthly credit, which covers about 1,600 results. See **Pricing** above for a worked example.

#### Is it legal to scrape Boulder County restaurant inspections?

This Actor reads public records from **Boulder County** via the official State of Colorado open-data portal (data.colorado.gov), using only public endpoints (no login, no CAPTCHA bypass, no private accounts). See the source/license section above for the dataset's terms. You are responsible for how you use the data; this is not legal advice.

#### How fresh is the data?

Each run reads the source live, so you get whatever the agency has published at that moment. How often the agency updates, and any known lag, is described in the data caveats/notes section above.

#### Can I use it via API, on a schedule, or with Google Sheets?

Yes. Every Apify Actor has a REST API and client libraries for Python and JavaScript. You can schedule daily or weekly runs, and send results to Google Sheets, Slack, Zapier, Make, n8n, webhooks, or an AI agent via the Apify MCP server.

#### I need another city, county or field. Can you add it?

Open an issue on the **Issues** tab with the city or data source you need. We build new public-records scrapers regularly.

### More public-records scrapers by Groundplanes

Same clean output, pay-per-result pricing and official public data sources:

#### Restaurant & food inspections

- [Maricopa County (Phoenix) Restaurant Inspections Scraper](https://apify.com/groundplanes/maricopa-restaurant-inspections)
- [Las Vegas Restaurant Inspections & Grades Scraper (SNHD)](https://apify.com/groundplanes/las-vegas-restaurant-inspections)
- [Pittsburgh Restaurant Inspections Scraper (Allegheny County)](https://apify.com/groundplanes/allegheny-restaurant-inspections)
- [Delaware Restaurant Inspections Scraper — Statewide Violations](https://apify.com/groundplanes/delaware-restaurant-inspections)
- [Montgomery County MD Restaurant & Food Inspections Scraper](https://apify.com/groundplanes/montgomery-md-food-inspections)
- [NY State Restaurant Inspections Scraper — NYSDOH, Non-NYC](https://apify.com/groundplanes/ny-state-food-service-inspections)

#### Code violations & distressed property leads

- [Pittsburgh Code Violations Scraper — Distressed Property Leads](https://apify.com/groundplanes/pittsburgh-code-violations)
- [Orlando FL Code Enforcement Scraper — Code Violation Leads](https://apify.com/groundplanes/orlando-code-enforcement-cases)
- [New Orleans Code Violations Scraper — Code Enforcement Leads](https://apify.com/groundplanes/nola-code-enforcement-violations)

#### Business licenses & new business leads

- [Delaware Business Licenses Scraper — New Business Leads](https://apify.com/groundplanes/delaware-business-licenses)
- [Norfolk VA Business Licenses Scraper — New Business Leads](https://apify.com/groundplanes/norfolk-va-business-licenses)
- [Berkeley CA Business Licenses Scraper — Local B2B Leads](https://apify.com/groundplanes/berkeley-ca-business-licenses)
- [New Orleans Business Licenses Scraper — New Business Leads](https://apify.com/groundplanes/nola-occupational-business-licenses)

# Actor input Schema

## `inspectedSince` (type: `string`):

Optional real date, YYYY-MM-DD. Empty = all 16,346 inspections at snapshot (Jan 2013 – Jul 2026).

## `cities` (type: `array`):

e.g. BOULDER (~60% of rows), LONGMONT, LAFAYETTE, LOUISVILLE, NIWOT, LYONS. Case-insensitive. Empty = all.

## `nameContains` (type: `string`):

Case-insensitive text the facility name must contain.

## `resultContains` (type: `string`):

e.g. Reinspection (only facilities that failed and need a reinspection) or Pass. Empty = all. Only the Sept 2025 – Jul 2026 file has results, so this skips history.

## `includeHistory` (type: `boolean`):

Default on. Adds 15,713 historical inspections (dataset tuvj-xz3m) after the 633 newer ones (6ytb-f2cq). Ignored when Result contains is set (the historical file has no Pass/Reinspection result).

## `maxItems` (type: `integer`):

Maximum inspections to return (newest first).

## Actor input object example

```json
{
  "includeHistory": true,
  "maxItems": 200
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "maxItems": 200
};

// Run the Actor and wait for it to finish
const run = await client.actor("groundplanes/boulder-county-restaurant-inspections").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "maxItems": 200 }

# Run the Actor and wait for it to finish
run = client.actor("groundplanes/boulder-county-restaurant-inspections").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "maxItems": 200
}' |
apify call groundplanes/boulder-county-restaurant-inspections --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,groundplanes/boulder-county-restaurant-inspections"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/5rwTPbbObLCy5uaYt/builds/l3PaXTuBIeVZPjJqK/openapi.json