# Austin Food Inspection Scores Scraper (`zerobreak/austin-food-inspection-scores-scraper`) Actor

Austin Food Inspection Scores Scraper is a Python tool to extract restaurant names, inspection dates, violation codes, and health scores from municipal health department databases. It exports structured hygiene datasets into clean CSV or JSON formats for public health monitoring and safety analysis.

- **URL**: https://apify.com/zerobreak/austin-food-inspection-scores-scraper.md
- **Developed by:** [ZeroBreak](https://apify.com/zerobreak) (community)
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

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

### Austin Food Inspection Scores Scraper — Restaurant Health Inspection Records

![Austin Food Inspection Scores Scraper cover](https://images.bigibyte.com/cdn-cgi/image/width=1260,height=540,fit=cover,format=webp/apify-actors-covers/austin-food-inspection-scores-scraper-cover.png)

### Overview

Collect public restaurant food inspection scores and establishment records from the City of Austin open data portal.

This actor retrieves inspection records in a structured format, including restaurant names, inspection scores, addresses, inspection dates, and inspection details. Choose between collecting all available rows, applying custom filters, or retrieving dataset metadata.

Export your results as JSON, CSV, Excel, and other supported formats for research, reporting, and business analysis.

### Features

- Collect Austin food establishment inspection records.
- Retrieve restaurant names, addresses, and ZIP codes.
- Extract inspection scores and dates.
- Collect inspection types and score categories.
- Retrieve all available rows or apply custom filters.
- Search records using text queries.
- Retrieve dataset column metadata.
- Set a maximum number of results per run.
- Export structured data in multiple formats.

### Collection Modes

**All Rows (`rows`)**

Collects inspection records from the dataset, with pagination and a configurable result limit.

**Filtered Rows (`filtered`)**

Collects records matching custom filter conditions or search terms. For example, filter restaurants with inspection scores below 70.

**Dataset Metadata (`metadata`)**

Retrieves information about the dataset's columns, including their names, data types, and descriptions.

### Use Cases

- **Restaurant Health Research:** Review public food inspection scores and inspection histories.
- **Restaurant Monitoring:** Track inspection results across establishments.
- **Food Safety Analysis:** Identify records with low inspection scores for further review.
- **Local Business Research:** Build structured datasets of restaurants and their inspection details.
- **Market Analysis:** Analyze inspection scores across locations and ZIP codes.
- **Data Reporting:** Export inspection records for spreadsheets, dashboards, and reports.

### Input Parameters

| Parameter | Type | Description |
|---|---|---|
| `mode` | String | Collection mode: `rows`, `filtered`, or `metadata`. |
| `maxItems` | Integer | Maximum number of records to collect. |
| `orderBy` | String | Optional field or expression used to order records. |
| `where` | String | Optional filter condition for filtered mode. |
| `search` | String | Optional full-text search term, if supported by the actor input. |
| `requestDelaySecs` | Number | Delay between requests. |

### Example Input

**Collect all rows**

```json id="aus01"
{
  "mode": "rows",
  "maxItems": 50,
  "orderBy": ":id",
  "requestDelaySecs": 1
}
```

**Collect filtered rows**

```json id="aus02"
{
  "mode": "filtered",
  "where": "score < 70",
  "maxItems": 25,
  "requestDelaySecs": 1
}
```

### What Data Does This Actor Extract?

| Field | Description |
|---|---|
| `restaurant_name` | Name of the inspected food establishment. |
| `zip_code` | Establishment ZIP code. |
| `inspection_date` | Date of the inspection. |
| `score` | Food inspection score. |
| `address` | Establishment address. |
| `facility_id` | Food establishment identifier. |
| `process_description` | Description of the inspection process. |
| `inspectionid` | Inspection record identifier. |
| `inspectionscorecategory` | Inspection score category. |
| `scraped_at` | Date and time the record was collected. |

### Example Output

```json id="aus03"
{
  "restaurant_name": "Hotel Viata",
  "zip_code": "78746-0032",
  "inspection_date": "2026-08-24T00:00:00.000",
  "score": "96.000000",
  "address": "320 S Capital of Texas Hwy Ste B West Lake Hills, TX 78746-0032",
  "facility_id": "12393953",
  "process_description": "Routine Inspection",
  "inspectionid": "1529497",
  "inspectionscorecategory": "90+ (Green)",
  "scraped_at": "2026-10-26T00:00:00+00:00"
}
```

### Working with Your Dataset

After the run finishes, open the **Dataset** tab to review the collected inspection records.

You can export your results in formats such as:

- JSON
- CSV
- Excel
- XML
- HTML

Use the exported data to build restaurant inspection trackers, analyze food safety records, or create reports and dashboards.

### FAQ

**Who is this actor for?**

It is useful for researchers, analysts, developers, and businesses interested in Austin restaurant inspection records.

**Can I collect all available inspection records?**

Yes. Select `rows` mode and set `maxItems` to your preferred collection limit.

**How do I find restaurants with low inspection scores?**

Use `filtered` mode with a condition such as `score < 70` in the `where` parameter.

**Can I search for specific records?**

Filtered mode supports custom conditions and text searches when the corresponding input is configured.

**What does metadata mode return?**

It retrieves dataset column information, including field names, types, and descriptions.

**Can I schedule recurring runs?**

Yes. Use Apify Schedules to refresh the dataset automatically at your preferred interval.

**What export formats are supported?**

You can export the dataset in JSON, CSV, Excel, and other supported formats.

### Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or officially associated with the City of Austin or its owners. It collects publicly available food inspection information. Users are responsible for ensuring that their use of the collected data complies with applicable laws and relevant terms of use.

### Is Web Scraping Legal?

Collecting information that is already public is generally legal. There is no single law that bans all forms of web scraping. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article [Is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/).

# Actor input Schema

## `mode` (type: `string`):

What to scrape.

## `where` (type: `string`):

SoQL $where clause, e.g. score < 70

## `q` (type: `string`):

Full-text search ($q) across text columns

## `orderBy` (type: `string`):

SoQL $order (stable paging needs a unique order)

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

Stop after this many successful rows. Hard max is 1000.

## `requestDelaySecs` (type: `number`):

Seconds to wait between requests.

## `userAgent` (type: `string`):

User-Agent header sent with each request.

## `timeoutSecs` (type: `integer`):

Overall run budget in seconds.

## `requestTimeoutSecs` (type: `integer`):

Per-request timeout in seconds.

## `proxyConfiguration` (type: `object`):

Optional proxy. Leave off unless you need it.

## Actor input object example

```json
{
  "mode": "rows",
  "where": "",
  "q": "",
  "orderBy": ":id",
  "maxItems": 100,
  "requestDelaySecs": 1,
  "userAgent": "ActorResearch/1.0",
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `overview` (type: `string`):

Dataset rows in the overview table.

## `dataset` (type: `string`):

Full dataset for this run.

## `items` (type: `string`):

Dataset items as JSON.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("zerobreak/austin-food-inspection-scores-scraper").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("zerobreak/austin-food-inspection-scores-scraper").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 '{}' |
apify call zerobreak/austin-food-inspection-scores-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,zerobreak/austin-food-inspection-scores-scraper"
        }
    }
}
```

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/5ZiaeZpTxiyyD9IgU/builds/o716DS3AZdXGDa4cm/openapi.json