# Ourairports Data Scraper (`zerobreak/ourairports-data-scraper`) Actor

OurAirports Data Scraper extracts global aviation metadata (ICAO/IATA codes, coordinates, runways, frequencies) from OurAirports into CSV/JSON formats for GIS and flight tracking.

- **URL**: https://apify.com/zerobreak/ourairports-data-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

## OurAirports Data Scraper: Airports and Runways CSV Export

<p align="center">
  <img src="https://imgur.com/NCSEbZK.png" alt="OurAirports Data Scraper" width="800" />
</p>

Collect publicly available airport and runway data from OurAirports and save filtered records to an Apify dataset. Export results as JSON, CSV, or Excel for aviation research, geographic analysis, travel planning, and reference-data matching.

The actor supports two datasets: airports and runways. It downloads the selected CSV file once per run, applies the relevant filters, removes duplicate IDs, and stops when the configured row limit is reached.

### Use Cases

- **Airport directories:** Collect airport identifiers, IATA and ICAO codes, coordinates, and airport types.
- **Runway datasets:** Organize runway length, width, surface, and runway-end identifiers.
- **Travel research:** Combine airport names with municipalities, elevation, and scheduled-service information.
- **Scheduled data refreshes:** Rerun the same country and airport-type filters to compare changes over time.
- **Reference-data matching:** Join runway records to airport records using `airport_ident` and `ident`.

### What Data Does the OurAirports Scraper Extract?

The actor supports two collection modes:

- **Airports:** Produces one row per matching airport after applying the country and airport-type filters.
- **Runways:** Produces one row per runway, including dimensions, surface, lighting, closure status, and runway-end information.

Country and airport-type filters apply only to airport records because the runway dataset does not contain those fields. You can join the two datasets afterward to associate runways with airports.

The source column `type` is saved as `airportType` to avoid conflicts with the dataset field name.

### Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `dataset` | string | `airports` | Dataset to collect: `airports` or `runways`. Unsupported values produce an error row. |
| `country` | string | `US` | ISO country code matched against `iso_country`. An empty value includes all countries. Ignored in runway mode. |
| `type` | string | `large_airport` | Airport type, such as `large_airport` or `heliport`. An empty value includes all airport types. Ignored in runway mode. |
| `maxItems` | integer | `100` | Maximum matching rows to save. Hard maximum: 1,000. |
| `timeoutSecs` | integer | `300` | Maximum run duration in seconds. |
| `requestTimeoutSecs` | integer | `30` | Timeout for an individual download attempt before retry handling. |

### Example Input

Collect large airports in the United States:

```json
{
  "dataset": "airports",
  "country": "US",
  "type": "large_airport",
  "maxItems": 100,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30
}
```

To collect runway records instead, change `dataset` to `runways`. Country and airport-type filters will not apply in that mode.

### Output Fields

| Field | Type | Description |
|---|---|---|
| `id` | string | Source record identifier. |
| `ident` | string | Airport identifier. |
| `airportType` | string | Airport category from the source `type` column. |
| `name` | string | Airport name with HTML tags removed. |
| `latitude_deg` | string | Latitude in degrees. |
| `longitude_deg` | string | Longitude in degrees. |
| `elevation_ft` | string | Elevation in feet. |
| `continent` | string | Continent code. |
| `iso_country` | string | ISO country code. |
| `iso_region` | string | ISO region code. |
| `municipality` | string | Associated city or town. |
| `scheduled_service` | string | Scheduled-service indicator. |
| `iata_code` | string | IATA airport code. |
| `icao_code` | string | ICAO airport code. |
| `gps_code` | string | GPS identifier. |
| `local_code` | string | Local airport code. |
| `home_link` | string | Airport homepage reference, when available. |
| `wikipedia_link` | string | Wikipedia reference, when available. |
| `keywords` | string | Additional source keywords. |
| `airport_ident` | string | Associated airport identifier on a runway record. |
| `airport_ref` | string | Airport reference associated with a runway. |
| `length_ft` | string | Runway length in feet. |
| `width_ft` | string | Runway width in feet. |
| `surface` | string | Runway surface type. |
| `lighted` | string | Indicates whether the runway is lighted. |
| `closed` | string | Runway closure indicator. |
| Runway-end fields | string | Low-end and high-end identifiers, coordinates, elevations, headings, and displaced thresholds. |
| `sourceUrl` | string | Source CSV reference for the download. |
| `scrapedAt` | string | UTC timestamp when the row was saved. |
| `error` | string | Error information, present on error rows. |
| `input` | string | JSON snapshot of the input associated with an error row. |

#### Example Airport Record

```json
{
  "id": "323361",
  "ident": "00AA",
  "airportType": "small_airport",
  "name": "Aero B Ranch Airport",
  "latitude_deg": "38.704022",
  "longitude_deg": "-101.473911",
  "elevation_ft": "3435",
  "continent": "NA",
  "iso_country": "US",
  "iso_region": "US-KS",
  "municipality": "Leoti",
  "scheduled_service": "no",
  "icao_code": "",
  "iata_code": "",
  "gps_code": "00AA",
  "local_code": "00AA",
  "home_link": "",
  "wikipedia_link": "",
  "keywords": "",
  "sourceUrl": "AIRPORTS_CSV_SOURCE",
  "scrapedAt": "2026-10-12T00:00:00+00:00"
}
```

### Limits and Error Handling

#### Row Limits and Processing

The actor clamps `maxItems` to a range of 1–1,000. It downloads the selected CSV file once per run, filters the records locally, skips duplicate `id` values, and saves rows until the configured cap or timeout is reached.

There is no page-based pagination. The source files are large, so each run processes the selected file after downloading it.

#### Download Retries

Failed downloads are retried up to three additional times for HTTP 429 responses, HTTP 5xx responses, and timeouts. The retry delays are 2, 4, and 8 seconds unless a `Retry-After` value specifies a different wait.

If the response is not a valid CSV file, including an HTML page returned with a successful HTTP status, the actor saves an error row.

#### Empty Results and Invalid Inputs

- Unsupported dataset names produce an error row without attempting a download.
- If the selected filters match no records, the actor saves an error row.
- If a download fails, error information is included in the dataset.
- Country and airport-type filters are ignored in runway mode.

### Data Source and Licensing

The actor uses the public OurAirports airport and runway datasets. Review the source's licensing and attribution requirements before redistributing collected records.

Each output row includes `sourceUrl` to identify the relevant source file.

### FAQ

#### Does the OurAirports scraper need an API key?

No. The actor downloads publicly available CSV files. No login or API key is required.

#### Why is the airport type field called `airportType`?

The source CSV uses `type` for airport classification. The actor renames that field to `airportType` in the output.

#### Can I filter runways by country?

Not directly. The runway dataset does not include a country column. Collect airport records for your desired country, then join the datasets using `ident` on airport records and `airport_ident` on runway records.

#### What happens if I enter an unsupported dataset name?

The actor saves an error row and finishes without attempting to download an unsupported file.

#### Can I export the results to CSV or JSON?

Yes. Use the Apify dataset export options to download records as JSON, CSV, or Excel.

#### How does the actor handle failed downloads?

It retries eligible failures, including rate limits, server errors, and timeouts. If the download still fails or the response is not a valid CSV, an error row is saved.

### Changelog

- **1.0:** Added airport and runway CSV collection, local airport filtering, duplicate-ID handling, download retries, and capped dataset exports.

### Trademark Notice

OurAirports and its related names, logos, and trademarks belong to their respective owners. They are used in this documentation solely to identify the source of the data and do not imply affiliation, sponsorship, endorsement, or partnership.

### Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or otherwise officially associated with OurAirports or its owners. Users are responsible for complying with applicable source terms, licensing, attribution, and data-use requirements.

### Is Web Scraping Legal?

Collecting information that is already public is generally legal. Scraping is not the same thing as hacking, and there is no single law that bans it. 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

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

Which verified public CSV to download. airports reads airports.csv. runways reads runways.csv. Any other name is saved as an error row and is not requested.

## `country` (type: `string`):

ISO country code matched against iso_country on airports.csv, for example US. Leave empty to keep every country. Ignored for runways.csv, which has no country column.

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

Airport type matched against the type column on airports.csv, for example large_airport, medium_airport, small_airport, heliport, or seaplane_base. Leave empty to keep every type. Ignored for runways.csv.

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

Maximum matching rows to save after local filtering. Values above 1000 are clamped to 1000.

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

Stop the run after this many seconds. Rows already saved stay in the dataset.

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

Seconds to wait for the CSV download before a retry.

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

Optional proxy for the CSV download. Default is no proxy. The public files do not require one.

## Actor input object example

```json
{
  "dataset": "airports",
  "country": "US",
  "type": "large_airport",
  "maxItems": 100,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

Default dataset of airport or runway rows.

## `datasetItems` (type: `string`):

JSON items from the default dataset.

# 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 = {
    "dataset": "airports",
    "country": "US",
    "type": "large_airport",
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("zerobreak/ourairports-data-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 = {
    "dataset": "airports",
    "country": "US",
    "type": "large_airport",
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("zerobreak/ourairports-data-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 '{
  "dataset": "airports",
  "country": "US",
  "type": "large_airport",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call zerobreak/ourairports-data-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,zerobreak/ourairports-data-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/mLyRRyhE6tcWdPbQw/builds/usiOzmIVqd70W4c2R/openapi.json