# vadymmarkov/Fakery

:alien: Swift fake data generator

Repository: https://github.com/vadymmarkov/Fakery
Canonical: https://ross.abutalabs.com/products/fakery
Homepage: https://vadymmarkov.github.io
Language: Swift
License: NOASSERTION
License Family: other
Topics: fakery, lorem, swift-framework, unit-testing, fake
Last push: 2023-04-24T11:19:13+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4174, "days_push": 1227, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1825, forks 186 (observed 2026-08-28T04:05:41.269687+00:00)

## What it is
Fakery is a Swift port of Ruby's Faker library that generates realistic fake data such as names, addresses, phone numbers, and company info. It supports 20+ locales and is intended for testing and development seed data.

## Use cases
- generate fake user data for unit tests
- populate a database with dummy data during development
- generate locale-specific test names and addresses
- replace random character strings with realistic test data
- seed iOS app prototypes with sample data

## When to choose
- you write Swift or iOS tests needing realistic dummy data
- you need localized fake data across many locales
- you want a Faker-style API in Swift

## When to avoid
- you need guaranteed-unique generated values
- you work outside the Swift ecosystem
- you need actively developed features (project is in maintenance)

## Facets
- artifact type: library
- maturity: maintenance
- function: data-generation, testing
- domain: developer-tools, testing
- platform: -
- tags: fake-data, faker-port, unit-testing, localization, swift-package, swift, ios, macos

## Member repositories
- vadymmarkov/Fakery (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:41.269687+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:19:42.359638+00:00, confidence not recorded.
  - readme: https://github.com/vadymmarkov/Fakery (fetched 2026-08-28T04:05:41.269687+00:00, sha 7bc7ab1e8a2b)
  - homepage: https://vadymmarkov.github.io (fetched 2026-08-29T10:58:33.900968+00:00, sha d8ab5de25e9f)
- Data as of 2026-08-30T08:39:29.467469+00:00.