whatisgithub

What is fcker?

nsecho/fcker — explained in plain English

Analysis updated 2026-07-17 · repo last pushed 2022-04-09

3GoAudience · developerComplexity · 2/5DormantSetup · easy

In one sentence

A Go command-line tool that generates realistic fake person profiles, names, addresses, and AI-made photos, for testing and prototyping.

Mindmap

mindmap
  root((repo))
    What it does
      Fake names
      Fake addresses
      AI profile photos
    Tech stack
      Go
      CLI tool
    Use cases
      Seed test databases
      QA stress testing
      UI mockups
    Audience
      Developers
      QA teams

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

What do people build with it?

USE CASE 1

Populate test databases with realistic fake user profiles instead of real personal data.

USE CASE 2

Stress-test user registration and onboarding flows with generated profiles.

USE CASE 3

Mock up UI screens that display user profiles using believable placeholder data.

USE CASE 4

Grab synthetic profile photos for prototypes needing sample avatars.

What is it built with?

Go

How does it compare?

nsecho/fckeralexremn/finalizer-doctorazer/diskwhere
Stars333
LanguageGoGoGo
Last pushed2022-04-09
MaintenanceDormant
Setup difficultyeasyeasyeasy
Complexity2/53/51/5
Audiencedeveloperops devopsdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · easy Time to first run · 5min

So what is it?

fcker is a command-line tool that generates realistic-looking fake person profiles. Instead of manually inventing names, addresses, and other personal details, you run a simple command and get complete fake person information instantly. It pulls from two sources: fakenamegenerator.com for biographical details like names and addresses, and thispersondoesnotexist.com for AI-generated profile photos that look convincingly real. The tool works by letting you choose what you want to generate. You can ask it to fetch a complete fake person profile with all their details, just grab a synthetic photo, or list the available country and user codes so you can customize which region or profile type the fake person comes from. It's written in Go, which means it's fast and runs as a lightweight command-line program on your computer. Developers and testers use tools like this to populate databases with realistic test data without using real people's information, which matters for privacy and legal reasons. QA teams might use it to stress-test user registration flows. Product teams building features around user profiles can mock up interfaces with convincing fake data. Anyone prototyping an application that needs sample user information can generate dozens of profiles in seconds instead of typing them out by hand. It's purely for testing and development, the fake data helps you work faster without the ethical or legal complications of using real personal information during development. The README doesn't elaborate on specific features or configuration options beyond the basic commands available, so the tool appears straightforward: command, generate, move on. It's a focused utility for one job, quickly producing believable fake person data from public sources.

Copy-paste prompts

Prompt 1
Write a script that calls fcker to generate 50 fake user profiles and insert them into my test database.
Prompt 2
Show me how to use fcker's Go CLI to fetch a fake person's photo and save it to a local folder.
Prompt 3
Help me list the available country and user codes in fcker so I can generate region-specific fake profiles.
Prompt 4
Integrate fcker into my QA test suite to seed dummy user accounts before each test run.

Frequently asked questions

What is fcker?

A Go command-line tool that generates realistic fake person profiles, names, addresses, and AI-made photos, for testing and prototyping.

What language is fcker written in?

Mainly Go. The stack also includes Go.

Is fcker actively maintained?

Dormant — no commits in 2+ years (last push 2022-04-09).

How hard is fcker to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is fcker for?

Mainly developer.

Open on GitHub → Ask about another repo

This repo across BitVibe Labs

Verify against the repo before relying on details.