Homebrew Install Analytics Scraper

Homebrew Install Analytics Scraper — Package Popularity and Formula Metadata

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

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

Formula Details

{
  "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

{
  "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?.