# Apnews Discovery Parser Spider (`getdataforme/apnews-discovery-parser-spider`) Actor
The Apnews Discovery Parser Spider efficiently scrapes and parses news articles from the AP website using keyword-based searches. It provides high-quality data with customizable limits, extracting details like titles, URLs, and images. Ideal for research, market analysis, and content aggregation.
- **URL**: https://apify.com/getdataforme/apnews-discovery-parser-spider.md
- **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community)
- **Categories:** AI, Automation, E-commerce
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $9.00 / 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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## Apnews Discovery Parser Spider
The Apnews Discovery Parser Spider is a powerful tool designed to scrape and parse news articles from the Associated Press (AP) website. This actor allows users to efficiently gather news data based on specific search keywords, making it an invaluable resource for researchers, analysts, and businesses looking to stay informed on current events.
### Features
- **Keyword-Based Search**: Easily search for news articles using specific keywords.
- **Customizable Item Limit**: Set a maximum number of articles to process, ensuring focused data collection.
- **High-Quality Data**: Extracts comprehensive article details including title, URL, description, timestamps, and images.
- **Efficient Performance**: Optimized for quick data retrieval and processing.
- **Reliable Output**: Consistent and structured data format for seamless integration into workflows.
- **Scalable**: Suitable for both small-scale and large-scale data collection needs.
### Input Parameters
| Parameter | Type | Required | Description | Example |
|--------------|---------|----------|--------------------------------------------------|---------|
| SearchKey | String | No | The search key for the spider. | "iran" |
| itemLimit | Integer | No | Specifies the maximum number of items to process.| 20 |
### Example Usage
#### Example Input JSON
```json
{
"SearchKey": "iran",
"itemLimit": 20
}
````
#### Example Output JSON
```json
[
{
"title": "Iran says it would resume nuclear talks with US if guaranteed no further attacks",
"url": "https://apnews.com/article/iran-us-nuclear-talks-araghchi-d0f424e954d7c6379ef075aa394af198",
"description": "Iranβs foreign minister says the country is open to resuming nuclear talks with the U.S. if guaranteed no further attacks.",
"posted_timestamp": 1752331439000,
"updated_timestamp": 1752380343000,
"comment_count": null,
"image": "https://dims.apnews.com/dims4/default/1808d12/2147483647/strip/true/crop/5616x3744+0+0/resize/240x160!/quality/90/?url=https%3A%2F%2Fassets.apnews.com%2Fac%2F5a%2F63724e555a2f3b8067128f168d0a%2Fcea6325d844a4201b8eb2a9f271a57a0",
"actor_id": "BiR07Jc009DJBRJL3",
"run_id": "FR1KOqMzOpEGD1YMp"
}
]
```
### Use Cases
- **Market Research and Analysis**: Gather insights on industry trends and consumer sentiment.
- **Competitive Intelligence**: Monitor competitors' activities and media presence.
- **Content Aggregation**: Compile news articles for newsletters or websites.
- **Academic Research**: Access a wealth of information for scholarly studies.
- **Business Automation**: Automate news data collection for reporting and decision-making.
### Installation and Usage
1. Search for "Apnews Discovery Parser Spider" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters.
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).
### Output Format
The output is a JSON array where each object contains:
- **title**: The headline of the article.
- **url**: Direct link to the article.
- **description**: A brief summary of the article.
- **posted\_timestamp**: The original publication timestamp.
- **updated\_timestamp**: The last update timestamp.
- **comment\_count**: Number of comments on the article (if available).
- **image**: URL of the article's featured image.
- **actor\_id**: Unique identifier for the actor run.
- **run\_id**: Unique identifier for the specific run.
### Support
For custom/simplified outputs or bug reports, please contact:
- Email: support@getdataforme.com
- Subject line: "custom support"
- Contact form:
We're here to help you get the most out of this Actor!
# Actor input Schema
## `SearchKey` (type: `string`):
The search key for the spider.
## `itemLimit` (type: `integer`):
Specifies the maximum number of items to process.
## Actor input object example
```json
{
"SearchKey": "iran",
"itemLimit": 20
}
```
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"itemLimit": 20
};
// Run the Actor and wait for it to finish
const run = await client.actor("getdataforme/apnews-discovery-parser-spider").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ 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);
});
// π Want to learn more π? Go to β 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "itemLimit": 20 }
# Run the Actor and wait for it to finish
run = client.actor("getdataforme/apnews-discovery-parser-spider").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("πΎ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"itemLimit": 20
}' |
apify call getdataforme/apnews-discovery-parser-spider --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=getdataforme/apnews-discovery-parser-spider",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Apnews Discovery Parser Spider",
"description": "The Apnews Discovery Parser Spider efficiently scrapes and parses news articles from the AP website using keyword-based searches. It provides high-quality data with customizable limits, extracting details like titles, URLs, and images. Ideal for research, market analysis, and content aggregation.",
"version": "0.0",
"x-build-id": "XJ8bGHAGjsgVaYNKP"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/getdataforme~apnews-discovery-parser-spider/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-getdataforme-apnews-discovery-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/getdataforme~apnews-discovery-parser-spider/runs": {
"post": {
"operationId": "runs-sync-getdataforme-apnews-discovery-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/getdataforme~apnews-discovery-parser-spider/run-sync": {
"post": {
"operationId": "run-sync-getdataforme-apnews-discovery-parser-spider",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"SearchKey": {
"title": "Search Key",
"type": "string",
"description": "The search key for the spider.",
"default": "iran"
},
"itemLimit": {
"title": "Item Limit",
"type": "integer",
"description": "Specifies the maximum number of items to process.",
"default": 20
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```