# Practicelink Scraper (`getdataforme/practicelink-scraper`) Actor

The scraper automates the process of extracting public LinkedIn posts, capturing key information like content, engagement metrics (likes, comments, shares), and timestamps. Whether you’re conducting competitor research, tracking industry developments, or exploring new opportunities.

- **URL**: https://apify.com/getdataforme/practicelink-scraper.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** Automation, Lead generation, Real estate
- **Stats:** 8 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$25.00/month + usage

To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors

## 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

### Python Scrapy template

A template example built with Scrapy to scrape page titles from URLs defined in the input parameter. It shows how to use Apify SDK for Python and Scrapy pipelines to save results.

### Included features

- **[Apify SDK](https://docs.apify.com/sdk/python/)** for Python - a toolkit for building Apify [Actors](https://apify.com/actors) and scrapers in Python
- **[Input schema](https://docs.apify.com/platform/actors/development/input-schema)** - define and easily validate a schema for your Actor's input
- **[Request queue](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-request-queues)** - queues into which you can put the URLs you want to scrape
- **[Dataset](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-datasets)** - store structured data where each object stored has the same attributes
- **[Scrapy](https://scrapy.org/)** - a fast high-level web scraping framework

### How it works

This code is a Python script that uses Scrapy to scrape web pages and extract data from them. Here's a brief overview of how it works:

- The script reads the input data from the Actor instance, which is expected to contain a `start_urls` key with a list of URLs to scrape.
- The script then creates a Scrapy spider that will scrape the URLs. This Spider (class `TitleSpider`) is storing URLs and titles.
- Scrapy pipeline is used to save the results to the default dataset associated with the Actor run using the `push_data` method of the Actor instance.
- The script catches any exceptions that occur during the [web scraping](https://apify.com/web-scraping) process and logs an error message using the `Actor.log.exception` method.

### Resources

- [Web scraping with Scrapy](https://blog.apify.com/web-scraping-with-scrapy/)
- [Python tutorials in Academy](https://docs.apify.com/academy/python)
- [Alternatives to Scrapy for web scraping in 2023](https://blog.apify.com/alternatives-scrapy-web-scraping/)
- [Beautiful Soup vs. Scrapy for web scraping](https://blog.apify.com/beautiful-soup-vs-scrapy-web-scraping/)
- [Integration with Zapier](https://apify.com/integrations), Make, Google Drive, and others
- [Video guide on getting scraped data using Apify API](https://www.youtube.com/watch?v=ViYYDHSBAKM)
- A short guide on how to build web scrapers using code templates:

[web scraper template](https://www.youtube.com/watch?v=u-i-Korzf8w)

### Getting started

For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the actor use the following command:

```bash
apify run
```

### Deploy to Apify

#### Connect Git repository to Apify

If you've created a Git repository for the project, you can easily connect to Apify:

1. Go to [Actor creation page](https://console.apify.com/actors/new)
2. Click on **Link Git Repository** button

#### Push project on your local machine to Apify

You can also deploy the project on your local machine to Apify without the need for the Git repository.

1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action.

   ```bash
   apify login
   ```

2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my).

   ```bash
   apify push
   ```

### Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

- [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js)
- [Apify SDK for Python documentation](https://docs.apify.com/sdk/python)
- [Apify Platform documentation](https://docs.apify.com/platform)
- [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU)

# Actor input Schema

## `urls` (type: `array`):

A list of URLs of the web pages you want to scrape data from.

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

Specifies proxy servers that will be used by the scraper in order to hide its origin.

## Actor input object example

```json
{
  "urls": [
    "https://jobs.practicelink.com/jobs/1007316/hospitalist/physician/texas/hendrick-medical-center-brownwood/"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# 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 = {
    "urls": [
        "https://jobs.practicelink.com/jobs/1007316/hospitalist/physician/texas/hendrick-medical-center-brownwood/"
    ],
    "proxyConfiguration": {
        "useApifyProxy": true
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/practicelink-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 = {
    "urls": ["https://jobs.practicelink.com/jobs/1007316/hospitalist/physician/texas/hendrick-medical-center-brownwood/"],
    "proxyConfiguration": { "useApifyProxy": True },
}

# Run the Actor and wait for it to finish
run = client.actor("getdataforme/practicelink-scraper").call(run_input=run_input)

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

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

```

## CLI example

```bash
echo '{
  "urls": [
    "https://jobs.practicelink.com/jobs/1007316/hospitalist/physician/texas/hendrick-medical-center-brownwood/"
  ],
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}' |
apify call getdataforme/practicelink-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=getdataforme/practicelink-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/gOdTLbWj4hzJOCt4r/builds/ZXg7LCakto5LB5MFr/openapi.json