# Homebrew Install Analytics Scraper (`real-estate-api/homebrew-install-analytics-scraper`) Actor

Homebrew Install Analytics Scraper is a Python tool designed to extract package installation counts, operating system distributions, and download metrics from Homebrew analytics. It exports structured package manager datasets into clean CSV or JSON formats for software trend analysis.

- **URL**: https://apify.com/real-estate-api/homebrew-install-analytics-scraper.md
- **Developed by:** [real-estate-api](https://apify.com/real-estate-api) (community)
- **Security:** Limited permissions
- **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

### Homebrew Install Analytics Scraper — Package Popularity and Formula Metadata

![Homebrew Install Analytics Scraper cover](https://images.bigibyte.com/cdn-cgi/image/width=1260,height=540,fit=cover,format=webp/apify-actors-covers/homebrew-install-analytics-scraper-cover.png)

Collect Homebrew installation statistics and formula metadata from publicly available sources. Explore popular packages over different time periods, look up formula details, and export structured results in JSON, CSV, Excel, and other supported dataset formats.

### Overview

Homebrew Install Analytics Scraper helps developers, SREs, and data analysts explore package popularity and collect formula information for research and reporting.

Choose an installation analytics period or provide a list of formula names to retrieve available details. Set a maximum item count to control the size of your dataset.

### Features

- **Installation Analytics:** Collect package installation rankings for 30-day, 90-day, or 365-day periods.
- **Formula Details:** Retrieve available metadata for selected formula names.
- **Popularity Research:** Compare installation counts and percentages across packages.
- **Flexible Collection:** Choose a collection mode and configure the maximum number of results.
- **Structured Results:** Export collected data in JSON, CSV, Excel, and other supported formats.
- **Scheduled Collection:** Run the actor periodically to maintain updated datasets.

### Use Cases

- **Package Popularity Research:** Identify popular Homebrew formulae across different time periods.
- **Dependency Research:** Compare installation statistics for packages such as OpenSSL and ca-certificates.
- **Formula Cataloging:** Collect descriptions, licenses, homepages, and stable versions for selected formulae.
- **Trend Analysis:** Save recurring snapshots for reports, charts, and historical comparisons.
- **Catalog Maintenance:** Maintain structured records of package rankings and formula metadata.

### Input Parameters

| Parameter | Type | Description |
|---|---|---|
| `mode` | String | Collection mode: `analytics` or `formula`. Defaults to `analytics`. |
| `period` | String | Analytics period: `30d`, `90d`, or `365d`. |
| `formulae` | Array | Formula names to look up in `formula` mode. |
| `maxItems` | Integer | Maximum number of results to collect. |
| `requestDelaySecs` | Number | Delay between requests, in seconds. |
| `requestTimeoutSecs` | Number | Maximum wait time for a request, in seconds. |
| `userAgent` | String | Optional custom client identification string. |

### Example Input

#### Installation Analytics

```json
{
  "mode": "analytics",
  "period": "30d",
  "maxItems": 50,
  "requestDelaySecs": 1,
  "userAgent": "ActorResearch/1.0",
  "requestTimeoutSecs": 30
}
```

#### Formula Details

```json
{
  "mode": "formula",
  "formulae": [
    "wget",
    "openssl@3"
  ],
  "maxItems": 10,
  "requestDelaySecs": 1,
  "userAgent": "ActorResearch/1.0"
}
```

### What Data Does This Actor Extract?

The output depends on the selected collection mode.

#### Installation Analytics Fields

| Field | Description |
|---|---|
| `number` | Package's position in the installation ranking. |
| `formula` | Homebrew formula name. |
| `count` | Reported installation count. |
| `percent` | Reported installation percentage. |
| `period` | Analytics period, such as `30d`. |
| `mode` | Collection mode used for the record. |
| `scrapedAt` | Timestamp when the record was collected. |

#### Formula Details Fields

Formula records can include available metadata such as:

| Field | Description |
|---|---|
| `name` | Formula name. |
| `desc` | Short formula description. |
| `license` | Declared license information. |
| `homepage` | Project homepage. |
| `versions` | Available version information, including the stable version when provided. |

The fields available for formula records depend on the metadata returned for each formula.

### Example Output

```json
{
  "number": 1,
  "formula": "openssl@3",
  "count": "388,919",
  "percent": "2.33",
  "period": "30d",
  "mode": "analytics",
  "scrapedAt": "2026-10-26T00:00:00+00:00"
}
```

The example illustrates an installation analytics record. Actual values depend on the selected period and the collected data.

### Working with Your Dataset

After the run finishes, open the actor's dataset to review the collected records.

You can:

- Export results as JSON, CSV, Excel, or another supported format.
- Filter and sort package rankings in a spreadsheet.
- Compare results from different analytics periods.
- Use formula metadata to organize package catalogs.
- Analyze saved datasets with Python, Pandas, or your preferred data analysis tools.

### FAQ

**Who is this actor for?**

It is designed for developers, SREs, researchers, and analysts who need Homebrew package rankings or formula metadata in a structured dataset.

**How do I change the analytics period?**

Set `period` to `30d`, `90d`, or `365d` while using `analytics` mode.

**How do I collect details for specific formulae?**

Set `mode` to `formula` and provide the formula names in the `formulae` array.

**What export formats are supported?**

You can export the dataset in JSON, CSV, Excel, and other formats supported by Apify.

**Can I run the actor automatically?**

Yes. Configure an Apify schedule to run the actor periodically and refresh your collected dataset.

### Disclaimer

This actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or officially associated with Homebrew or its owners. Users are responsible for complying with applicable terms of use and laws when collecting and using data.

### Is Web Scraping Legal?

Collecting information that is already public is generally legal. There is no single law that bans all forms of web scraping. 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

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

What to scrape. Analytics returns top installs for a period. Formula fetches details for named formulae.

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

Install analytics window. Used only in analytics mode.

## `formulae` (type: `array`):

Formula names for formula mode (for example wget or openssl@3).

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

Stop after this many successful rows. Hard max is 1000.

## `requestDelaySecs` (type: `number`):

Seconds to wait between requests.

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

User-Agent header sent with each request.

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

Overall run budget in seconds.

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

Per-request timeout in seconds.

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

Optional proxy. Leave off unless you need it.

## Actor input object example

```json
{
  "mode": "analytics",
  "period": "30d",
  "formulae": [
    "wget"
  ],
  "maxItems": 100,
  "requestDelaySecs": 1,
  "userAgent": "ActorResearch/1.0",
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

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

Dataset rows in the overview table.

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

Full dataset for this run.

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

Dataset items as JSON.

# 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 = {
    "formulae": [
        "wget"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("real-estate-api/homebrew-install-analytics-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 = { "formulae": ["wget"] }

# Run the Actor and wait for it to finish
run = client.actor("real-estate-api/homebrew-install-analytics-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 '{
  "formulae": [
    "wget"
  ]
}' |
apify call real-estate-api/homebrew-install-analytics-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,real-estate-api/homebrew-install-analytics-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/Um5acDqFdA0AMIuKb/builds/4STaZODvQV600SDVD/openapi.json