# devRant Scraper (`muhammadafzal/devrant-scraper`) Actor

Scrape public devRant feed, top, and search results into structured rant records with text, tags, scores, authors, links, comments, and source metadata.

- **URL**: https://apify.com/muhammadafzal/devrant-scraper.md
- **Developed by:** [Muhammad Afzal](https://apify.com/muhammadafzal) (community)
- **Categories:** Social media, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.00 / 1,000 devrant rant records

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## devRant Scraper

Scrapes public devRant feed data from the public devRant JSON endpoint. It supports the default algorithmic feed, recent/top sorting, time ranges, optional public search terms, pagination, deduplication, and structured rant records.

### Input

- `query`: optional public search term.
- `sort`: `algo`, `recent`, or `top`.
- `range`: `day`, `week`, `month`, or `all`.
- `maxResults`: 1–500, default 25.
- `pageSize`: 1–50, default 50.
- `requestDelayMs`: 500–10,000, default 1,000.
- `includeLinks`: include links returned by devRant, default true.

Each dataset item is one public rant with text, score, timestamp, author summary, tags, vote counts, comments count, links, and source metadata. The run summary is stored in the `OUTPUT` key-value record.

### Pricing and limitations

The primary PPE event is `$0.003` per unique rant record delivered. The actor does not access private accounts, perform authentication, vote, post, bypass challenges, or defeat access controls. A source outage or block produces a truthful diagnostic with no fabricated records.

Use the source responsibly and follow devRant terms and applicable laws. This actor is private until the owner reviews permissions, branding, and publication settings.

### Local development

```bash
npm ci
npm test
npm run validate:schema
```

### What data does devRant Scraper return?

| Field | Type | Description |
|---|---|---|
| `id` | integer | Stable public devRant rant identifier. |
| `url` | string | Public devRant URL. |
| `text` | string | Public rant text. |
| `score` | number | devRant score returned by the public source. |
| `createdAt` | string or null | Rant creation timestamp when returned by the source. |
| `author` | object | Author |
| `tags` | array | Tags |
| `commentsCount` | integer | Comments |
| `upvotes` | integer | Upvotes |
| `downvotes` | integer | Downvotes |
| `attachedImageUrl` | string or null | Attached image |
| `links` | array | Extracted links |
| `sort` | string | Sort mode |
| `range` | string | Range |
| `query` | string or null | Query |
| `sourceUrl` | string | Source API URL |
| `scrapedAt` | string | Scraped at |

### Use cases

- Collect public content and engagement signals for research and reporting.
- Add a repeatable structured-data step to applications, agents, and automation pipelines.
- Run a one-off research job and export the structured result as JSON, CSV, Excel, XML, or RSS from Apify.
- Schedule the same input to monitor changes over time and send completed datasets to a webhook or integration.
- Feed schema-shaped records into a database, spreadsheet, BI tool, or AI workflow with the source URL retained for verification.

#### Input example

```json
{
  "query": "",
  "sort": "algo",
  "range": "day",
  "maxResults": 25,
  "pageSize": 50,
  "requestDelayMs": 1000,
  "includeLinks": true
}
```

### Output example

```json
{
  "id": 1,
  "url": "Example Rant URL",
  "text": "Example Rant text",
  "score": 1,
  "createdAt": "Example Created at",
  "author": {},
  "tags": [],
  "commentsCount": 1,
  "upvotes": 1,
  "downvotes": 1,
  "attachedImageUrl": "Example Attached image",
  "links": []
}
```

The exact fields depend on the selected input and what the public source exposes. Use the dataset schema as the machine-readable contract and retain source URLs for verification.

### Run devRant Scraper with the Apify API

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/devrant-scraper').call({
  "query": "",
  "sort": "algo",
  "range": "day",
  "maxResults": 25,
  "pageSize": 50,
  "requestDelayMs": 1000,
  "includeLinks": true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

You can also run the Actor from Apify Console, schedules, webhooks, the REST API, Make, Zapier, n8n, or the hosted Apify MCP server.

### Responsible use

Use this Actor only for data you are authorized to access. Follow the target website's terms, robots and access policies, and applicable privacy, database, copyright, anti-spam, and data-protection laws. Do not use it to bypass authentication or other access controls, collect private data, harass people, or make high-impact decisions without independent verification.

### Frequently asked questions

#### Can I schedule devRant Scraper?

Yes. Use an Apify schedule to run the same saved input at a chosen interval, then connect a webhook or integration to process the dataset when the run finishes.

#### How should I test a new input?

Begin with the prefilled example or a small limit. Confirm that the output fields, source coverage, runtime, and live charges match your workflow before increasing the scope.

#### How do I export the results?

Open the run's default dataset in Apify Console and export JSON, CSV, Excel, XML, or RSS. Applications can retrieve the same records through the Apify API client or REST dataset endpoint.

#### Can an AI agent call this Actor?

Yes. Add `muhammadafzal/devrant-scraper` through the hosted Apify MCP server or call it through the API. The Actor's input and dataset schemas help agents construct valid requests and interpret returned records.

# Actor input Schema

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

Use this to filter public devRant results by a term, for example 'javascript' or 'remote work'. Leave blank for the selected public feed. This is not a private-account search.

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

Use algo for the default public feed, recent for newest rants, or top for popular rants. Defaults to algo.

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

Use day, week, month, or all with top/algo feeds. Defaults to day. The public source may apply its own range rules.

## `maxResults` (type: `integer`):

Maximum unique rant records to store and charge. Enter 1 to 500; defaults to 25. One result event costs $0.003.

## `pageSize` (type: `integer`):

Page size sent to the public devRant endpoint. Enter 1 to 50; defaults to 50. Smaller pages can reduce request load.

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

Delay between paginated requests. Enter 500 to 10,000 milliseconds; defaults to 1,000 to keep requests polite.

## `includeLinks` (type: `boolean`):

Keep public links detected in rant text when true. Defaults to true; set false for smaller records.

## Actor input object example

```json
{
  "query": "",
  "sort": "algo",
  "range": "day",
  "maxResults": 25,
  "pageSize": 50,
  "requestDelayMs": 1000,
  "includeLinks": true
}
```

# Actor output Schema

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

No description

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

No description

# 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 = {
    "query": "",
    "sort": "algo",
    "range": "day",
    "maxResults": 25,
    "pageSize": 50,
    "requestDelayMs": 1000,
    "includeLinks": true
};

// Run the Actor and wait for it to finish
const run = await client.actor("muhammadafzal/devrant-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 = {
    "query": "",
    "sort": "algo",
    "range": "day",
    "maxResults": 25,
    "pageSize": 50,
    "requestDelayMs": 1000,
    "includeLinks": True,
}

# Run the Actor and wait for it to finish
run = client.actor("muhammadafzal/devrant-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 '{
  "query": "",
  "sort": "algo",
  "range": "day",
  "maxResults": 25,
  "pageSize": 50,
  "requestDelayMs": 1000,
  "includeLinks": true
}' |
apify call muhammadafzal/devrant-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,muhammadafzal/devrant-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/ZXAbiTLsAHp7IAkpi/builds/iRpjHPSSHvXb9gTVR/openapi.json