# Dallas Restaurant Inspections Scraper (`kawsar/dallas-restaurant-inspections-scraper`) Actor

Collect Dallas food establishment inspection records, scores, and violation details. Export clean JSON, CSV, or Excel datasets for compliance research or lead generation.

- **URL**: https://apify.com/kawsar/dallas-restaurant-inspections-scraper.md
- **Developed by:** [Kawsar](https://apify.com/kawsar) (community)
- **Security:** Limited permissions
- **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

## Dallas Restaurant Inspections Scraper

![Dallas Restaurant Inspections Scraper cover](https://images.bigibyte.com/cdn-cgi/image/width=1260,height=540,fit=cover,format=webp/apify-actors-covers/dallas-restaurant-inspections-scraper-cover.png)

Collect restaurant and food establishment inspection records from Dallas, Texas. Retrieve establishment names, inspection types, dates, scores, addresses, and violation details. Export structured results in JSON, CSV, Excel, or other supported Apify dataset formats.

### What It Does

This actor collects restaurant and food establishment inspection records from the City of Dallas. It supports full dataset collection, keyword searches, custom filters, and dataset metadata retrieval.

Use the results for restaurant research, food safety analysis, compliance research, and business intelligence.

### Available Modes

- **All Rows:** Collect inspection records across the dataset.
- **Full-Text Search:** Find records matching a search term across searchable text fields.
- **SoQL Filter:** Apply custom conditions to narrow results, such as filtering by inspection date or establishment.
- **Dataset Metadata:** Retrieve available column names, data types, and descriptions.

### Input Example

**Collect all rows**

```json
{
  "mode": "all_rows",
  "maxItems": 50,
  "orderBy": ":id",
  "requestDelayMs": 500
}
```

**Search inspection records**

```json
{
  "mode": "search",
  "searchText": "inc",
  "maxItems": 25,
  "requestDelayMs": 500
}
```

**Filter inspection records**

```json
{
  "mode": "filter",
  "where": ":updated_at>'2020-01-01'",
  "maxItems": 25,
  "requestDelayMs": 500
}
```

### Output Example

```json
{
  "program_identifier": "FRESHII",
  "inspection_type": "Routine",
  "insp_date": "2018-10-31T00:00:00.000",
  "score": "96",
  "street_number": "2414",
  "street_name": "VICTORY PARK",
  "street_type": "LN",
  "site_address": "2414 VICTORY PARK LN",
  "zip": "75219",
  "violation1_description": "*24 Food Label-list of ingredients in descending..",
  "violation1_points": "2",
  "month": "Oct 2018",
  "inspection_year": "FY2019",
  "scraped_at": "2026-10-26T00:00:00+00:00"
}
```

### Output Fields

| Field | Description |
|---|---|
| `program_identifier` | Restaurant or establishment identifier |
| `inspection_type` | Type of inspection |
| `insp_date` | Inspection date |
| `score` | Inspection score |
| `street_number` | Street number |
| `street_name` | Street name |
| `street_type` | Street type or suffix |
| `site_address` | Complete establishment address |
| `zip` | ZIP code |
| `violation1_description` | Description of the first recorded violation |
| `violation1_points` | Points assigned to the first violation |
| `month` | Inspection month |
| `inspection_year` | Fiscal inspection year |
| `scraped_at` | Collection timestamp |

Additional source fields are preserved in the output when available. The source field `type` is stored as `inspection_type` to maintain a valid dataset schema.

### Use Cases

- **Food Safety Research:** Review restaurant inspection scores and reported violations.
- **Compliance Analysis:** Examine critical inspection findings and violation patterns.
- **Restaurant Research:** Build structured lists of food establishments in Dallas.
- **Public Health Analysis:** Study inspection trends across different periods.
- **Business Intelligence:** Organize establishment names, addresses, and inspection results for further analysis.

### FAQ

**What information does this actor collect?**

It collects establishment identifiers, inspection types, inspection dates, scores, addresses, violation descriptions, and related inspection details.

**Can I search for a specific restaurant?**

Yes. Select Full-Text Search mode and provide a keyword through `searchText`.

**Can I filter records by inspection date or establishment?**

Yes. Select SoQL Filter mode and provide a suitable condition through `where`.

**Does this dataset contain current restaurant inspections?**

The supplied dataset covers October 2016 through January 2024 and may no longer receive new updates. Its records should be treated as historical inspection information rather than a live view of current restaurant compliance.

**Can I export the results to Excel or CSV?**

Yes. Apify supports JSON, CSV, Excel, and other dataset export formats.

**Can I schedule recurring collections?**

Yes. Use Apify Schedules to run the actor automatically at your preferred intervals. Keep in mind that scheduling does not guarantee new records when the underlying dataset is no longer updated.

### Trademark Notice and Disclaimer

City of Dallas and its related names, logos, and trademarks belong to their respective owners. This actor is an independent data collection tool and is not affiliated with, sponsored by, or endorsed by the City of Dallas or its departments.

### Is Web Scraping Legal?

This actor collects publicly accessible restaurant inspection information without bypassing login screens, paywalls, or technical security measures. How collected information can be used depends on applicable laws and the source website's policies.

- **Personal Data:** Inspection records may contain business or individual names and other identifying details. Handle personal information responsibly and follow applicable privacy laws, including GDPR or CCPA where relevant.
- **Copyright and Licensing:** Publicly accessible government records may still be subject to applicable dataset licensing and attribution requirements. Review the source's terms before reusing or redistributing collected information.
- **Platform Terms and Rate Limits:** Respect the source platform's policies, attribution requirements, and reasonable request intervals.
- **Disclaimer:** This information is general guidance, not legal advice. Consult a qualified legal professional if you have questions about your intended use.

[Is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/)

# Actor input Schema

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

What to collect.

## `searchText` (type: `string`):

Full-text search across all columns ($q).

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

SoQL WHERE clause, e.g. :updated_at>'2020-01-01'.

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

SoQL $order. Stable paging needs a unique order.

## `appToken` (type: `string`):

Optional Socrata app token (X-App-Token) for higher limits.

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

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

## `requestDelayMs` (type: `integer`):

Polite pacing in milliseconds.

## `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": "all_rows",
  "searchText": "inc",
  "where": ":updated_at>'2020-01-01'",
  "orderBy": ":id",
  "maxItems": 100,
  "requestDelayMs": 500,
  "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 = {
    "searchText": "inc"
};

// Run the Actor and wait for it to finish
const run = await client.actor("kawsar/dallas-restaurant-inspections-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 = { "searchText": "inc" }

# Run the Actor and wait for it to finish
run = client.actor("kawsar/dallas-restaurant-inspections-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 '{
  "searchText": "inc"
}' |
apify call kawsar/dallas-restaurant-inspections-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,kawsar/dallas-restaurant-inspections-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/H9lCJyYxTbvJk7Zyl/builds/1arDaV2j73yGdvBbf/openapi.json