# Hiking Project Scraper (`lulzasaur/hikingproject-scraper`) Actor

Scrapes hiking trail data from Hiking Project (hikingproject.com). Extracts trail name, difficulty, rating, elevation, length, route type, GPS coordinates, and more. Supports search by location or trail name.

- **URL**: https://apify.com/lulzasaur/hikingproject-scraper.md
- **Developed by:** [lulz bot](https://apify.com/lulzasaur) (community)
- **Categories:** E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $10.00 / 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.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Hiking Project Scraper

Scrapes hiking trail data from [Hiking Project](https://www.hikingproject.com) — one of the largest trail databases in the US with over 80,000 trails.

### What data does it extract?

For each trail, the scraper extracts:

| Field | Description |
|-------|-------------|
| `trailName` | Name of the hiking trail |
| `location` | Geographic location (state, region, area) |
| `difficulty` | Difficulty level (Easy, Intermediate, Difficult, etc.) |
| `difficultyRating` | Numeric difficulty rating |
| `length` | Trail length in miles |
| `elevationGain` | Total elevation gain (detail mode) |
| `highestPoint` | Highest elevation point (detail mode) |
| `routeType` | Route type: Out and Back, Loop, Point to Point (detail mode) |
| `rating` | User rating (0-5) |
| `ratingCount` | Number of user ratings (detail mode) |
| `description` | Trail overview/description |
| `features` | Trail features and tags |
| `imageUrl` | Trail photo URL |
| `latitude` | GPS latitude |
| `longitude` | GPS longitude |
| `sourceUrl` | Direct link to the trail page |
| `scrapedAt` | Timestamp of when the data was scraped |

### Input Configuration

| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `searchQueries` | string\[] | `["Colorado"]` | Location or trail name search queries |
| `maxListings` | integer | `50` | Maximum number of trails to scrape (max 1000) |
| `scrapeDetails` | boolean | `false` | Fetch full details from each trail page |
| `proxyConfiguration` | object | — | Proxy settings |

#### Search tips

- **By state**: `"Colorado"`, `"California"`, `"Utah"`
- **By region**: `"Rocky Mountain"`, `"Yosemite"`, `"Grand Canyon"`
- **By trail name**: `"Bear Peak"`, `"Manitou Incline"`, `"Ice Lake"`
- **By city**: `"Boulder"`, `"Denver"`, `"Portland"`

#### Detail mode

When `scrapeDetails` is enabled, the scraper visits each trail's detail page to extract additional fields:

- Elevation gain and highest point
- Route type (Out and Back, Loop, etc.)
- Number of user ratings
- Full trail description
- Trail features

This is slower (adds ~1 second per trail) but provides more complete data.

### Example Output

```json
{
    "trailName": "Ice Lake Trail",
    "location": "Colorado > Southwest Rockies > Silverton",
    "difficulty": "Difficult",
    "difficultyRating": 4.8,
    "length": "7.2 mi",
    "elevationGain": "2541 ft",
    "highestPoint": "12585 ft",
    "routeType": "Out and Back",
    "rating": 5,
    "ratingCount": 77,
    "description": "Ice Lake Trail is a stunning hike through beautiful wildflower meadows...",
    "features": [],
    "imageUrl": "https://hikingproject.com/assets/photos/hike/...",
    "latitude": 37.81,
    "longitude": -107.79,
    "sourceUrl": "https://www.hikingproject.com/trail/7009883/ice-lake-trail",
    "scrapedAt": "2026-04-26T07:30:00.000Z"
}
```

### Cost

The scraper uses the Hiking Project search API for listing trails and optionally fetches detail pages.

- **Listing only** (`scrapeDetails: false`): Very fast, ~1 API call per 25 trails
- **With details** (`scrapeDetails: true`): 1 additional page load per trail

Estimated cost: ~$0.005 per result (pay-per-event pricing).

# Actor input Schema

## `searchQueries` (type: `array`):

Location or trail name search queries (e.g., 'Colorado', 'Bear Peak', 'Yosemite')

## `maxListings` (type: `integer`):

Maximum number of trail listings to scrape across all queries

## `scrapeDetails` (type: `boolean`):

If enabled, fetches each trail's detail page for elevation gain, route type, features, and full description. Slower but more complete data.

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

Proxy settings for the scraper

## Actor input object example

```json
{
  "searchQueries": [
    "Colorado"
  ],
  "maxListings": 50,
  "scrapeDetails": false
}
```

# 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 = {
    "searchQueries": [
        "Colorado"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("lulzasaur/hikingproject-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 = { "searchQueries": ["Colorado"] }

# Run the Actor and wait for it to finish
run = client.actor("lulzasaur/hikingproject-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 '{
  "searchQueries": [
    "Colorado"
  ]
}' |
apify call lulzasaur/hikingproject-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,lulzasaur/hikingproject-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/rsZ3qeqKov6mV9P7L/builds/w1jD47qxYKTq34MQg/openapi.json