fejkdata/README.md

fakes

A Go library and CLI for generating fake data, built for internationalization. It exists because the existing Go fake libraries lacked the locale coverage and format control we needed.

• Standards first — formats, names and structures follow international and local standards first and foremost.
• Locale-aware — names, addresses, postal codes and phone numbers follow per-locale data and formats. The shipped data is organised by full locale tag (sv_SE), but the engine treats folders as plain namespaces — name yours anything.
• Data lives in JSON — all source data is recursive JSON on disk, read when you create a faker and then served from memory. Add or change data without touching the library. Behavior belongs in data too: the engine grows a built-in function only for what data can't express (a checksum, a time-based id), never for what character classes and choices already do.
• Composable — templates nest without limit: weighted choices, character classes and sub-templates combine to model any format.
• Reproducible — seed a faker and it emits the same sequence every time. Every built-in draws only from that seed — no wall-clock, no crypto/rand — so determinism holds end to end.
• Zero dependencies — standard library only.

CLI

Install the fakes command, then give it one or more -data-path directories and a path — it prints one value to stdout. Each dot segment descends one level: folders, then the category (a JSON file), then fields inside it.

go install github.com/Timewave-AB/fakes/cmd/fakes@latest

fakes -data-path ./data/sv_SE person               # Sara Eriksson
fakes -data-path ./data/sv_SE person.last          # Eriksson  (dotted path into a category)
fakes -data-path ./data sv_SE.person               # point at the tree; the folder is a segment
fakes -data-path ./data/sv_SE -data-path ./mydata word  # layer dirs; the last wins a name clash
fakes -seed 42 -data-path ./data/sv_SE address
fakes -repeat 3 -data-path ./data/sv_SE person             # three values, one per line
fakes -repeat 3 -separator ', ' -data-path ./data/sv_SE word  # nät, barn, sol

-data-path is repeatable (last wins a name clash) and the path comes last, after the flags. -repeat N renders the path N times — each an independent draw — joined by -separator (default a newline, so values land one per line).

Without installing, run it from a checkout with go run ./cmd/fakes …. Exit codes: 0 success, 1 runtime error (missing dir, unknown path), 2 misuse.

Generating a file from a custom template

A category is just a JSON file in a data directory, so you can drop in your own and render it — no code change. Save this as data/sv_SE/sql.json:

{
  "format": "INSERT INTO users V#ALUES({sql-username});",
  "sql-username": {
    "format": "'{username}'",
    "repeat": 3,
    "separator": "),(",
    "username": ["pixelfox", "snork", "turbohund", "blip", "zoom", "wahoo"]
  }
}

sql-username renders '{username}' repeat times and joins the results with the ),( separator; the outer V#ALUES(…) wraps that into one valid row list. (#A escapes the literal A, which a format string would otherwise read as a letter token — see Data format.)

fakes -seed 1 -data-path ./data/sv_SE sql
# INSERT INTO users VALUES('zoom'),('wahoo'),('blip');

Raise the template's repeat for more rows per statement; use the CLI's -repeat for more statements — together they build a whole seed file:

fakes -repeat 100 -data-path ./data/sv_SE sql > seed.sql

Library

go get github.com/Timewave-AB/fakes   # requires Go 1.22+ (for math/rand/v2)

Point New at one or more data directories, then generate values by path with Fake. Each dot segment descends one level: folders, then the category (a JSON file), then fields inside it.

package main

import (
	"fmt"
	"log"

	"github.com/Timewave-AB/fakes"
)

func main() {
	f, err := fakes.New([]string{"./data/sv_SE"})
	if err != nil {
		log.Fatal(err)
	}

	for _, path := range []string{"person", "address", "phone", "address.locality"} {
		v, err := f.Fake(path)
		if err != nil {
			log.Fatal(err)
		}
		fmt.Printf("%-18s %s\n", path, v)
	}
}

person             Sara Eriksson
address            Kungsvägen 68
                   379 17 Stockholm
phone              072-402 91 67
address.locality   Linköping

Seed a faker for reproducible output — same seed + locale yields an identical sequence, handy for stable tests:

a, _ := fakes.New([]string{"./data/sv_SE"}, fakes.WithSeed(42))
b, _ := fakes.New([]string{"./data/sv_SE"}, fakes.WithSeed(42))
av, _ := a.Fake("person")
bv, _ := b.Fake("person")
av == bv // true

A *Fakes is not safe for concurrent use — create one per goroutine.

Data

The library ships a ready-to-use set under data/: one folder per locale (en_US, sv_SE) plus a locale-neutral misc folder. Point either tool at the whole tree, a single folder, a copy, or your own directory — anywhere on disk; no naming rules.

A directory is just a namespace. Each JSON file is a category named after the file; each subdirectory is a dot-path segment — folders nest exactly like JSON objects do. So data/sv_SE/person.json is Fake("person") when you point at data/sv_SE, or Fake("sv_SE.person") when you point at data.

Pass several directories and they merge, left to right: matching folders combine by their children, and any other clash is won by the last directory loaded. That lets you layer your own data over the built-ins without copying them:

fakes.New([]string{"./data/sv_SE", "./mydata"}) // mydata overrides on a clash

Each shipped locale carries these categories, formatted per locale (e.g. date is MM/DD/YYYY in en_US, YYYY-MM-DD in sv_SE; ssn is a US SSN vs a Swedish personnummer): address, color, company, date, email, ip, person, phone, price, sentence, ssn, time, url, username, uuid, version, word.

data/misc carries locale-neutral categories: uuid (a proper random v4), mac, and creditcard (per-network numbers ending in a valid {luhn()} digit). A time-ordered v7 UUID can't be expressed as data, so it's the {uuid()} builtin instead (see Functions).

Data format

Each JSON file in a data directory is a category named after the file (address.json → address), rendered by Fake("address"). Drop in a new file or folder — no code change, no recompile.

Every value is a node, one of three shapes, nestable without limit:

Node	JSON	Meaning
literal	"Malmö"	emitted verbatim — never formatted
choice	["a", "b", …]	one element, picked at random
template	{"format": "…", …}	a format string plus the named sub-nodes it references

Weight. A template node may carry a weight (default 1) to skew its odds within a choice:

[
  { "format": "#070-000 00 00", "weight": 10 },
  { "format": "#01-000 00 00" },
  { "format": "#010-000 00 00" }
]

Only template (object) nodes carry weight — a bare string or nested array in a choice always counts as 1. Weights are checked when you create the faker: a negative, non-numeric, or all-zero set is rejected at New, so a typo fails fast instead of silently skewing output.

Repeat. A template node may carry a repeat (default 1) to render its format that many times — each render an independent pick — joined by separator (default ""):

{ "format": "{word}", "repeat": 3, "separator": " ", "word": ["foo", "bar", "baz"] }

This yields e.g. bar foo baz. repeat must be a positive integer and separator a string, both checked at New.

Functions. A {name()} token calls a built-in function instead of rendering a field. {luhn()} appends a Luhn check digit over the digits emitted so far in the current format (non-digits skipped but kept); unknown functions or wrong argument counts are rejected at New. This is what makes a generated Swedish personnummer valid — its last digit is a Luhn checksum over the nine before it:

{ "format": "00{mmdd}-000{luhn()}", "mmdd": [ … ] }

renders e.g. 811218-987, then {luhn()} appends 6 → 811218-9876. Place it after its payload (it reads what is to its left). The buffer it reads is per-expansion, so nesting keeps fixed parts out of the sum — e.g. a 12-digit form prefixes the century outside the checksummed core:

{ "format": "{century}{core}", "century": ["19", "20"],
  "core": { "format": "00{mmdd}-000{luhn()}", "mmdd": [ … ] } }

A function must be deterministic in the seeded rng (no wall-clock), so a seeded faker stays reproducible. A time-based id (UUID v7, ULID) therefore draws its timestamp from the rng, not the clock — the result is a valid, reproducible value, not a real point in time.

There are two kinds. Derivations read the digits emitted so far, so put them after their payload; generators read only the rng, so they stand alone. Arguments are validated at New (a bad count, range, or country fails fast).

Function	Kind	Emits
{luhn()}	derivation	Luhn check digit (mod-10) over preceding digits
{mod11()}	derivation	weighted mod-11 check char (weights 2–7 from the right); X when it would be 10
{ean()}	derivation	EAN-13 / UPC-A / ISBN-13 / GTIN check digit
{uuid()}	generator	UUID v7 (v4 ships as data — see Data)
{ulid()}	generator	ULID, 26-char Crockford base32
{objectid()}	generator	MongoDB ObjectID, 24 hex chars
{nanoid(n)}	generator	URL-safe Nano ID, n chars
{hex(n)}	generator	n lowercase hex digits
{base64(n)}	generator	n random bytes, base64
{int(min,max)}	generator	uniform integer in [min, max]
{float(min,max,dp)}	generator	number in [min, max] with dp decimals
{iban(CC)}	generator	a length- and mod-97-valid IBAN for country CC (BE, DE, DK, ES, FI, NO, SE)

{ean()} is also the ISBN-13 check (an ISBN-13 is an EAN-13 — build the 978/979 prefix in data and call {ean()}). {iban()} is a generator, not a derivation: an IBAN's check digits sit before the account number, which a left-to-right reader can't reach, so it emits the whole value (a generic numeric BBAN — valid length and checksum, not real bank routing).

References. A {..path} token renders a node from the data root instead of a sibling field — the dot path is the one Fake takes, resolved across every loaded directory. One category can borrow another, even across folders or layered data dirs:

{ "format": "Hej, {..en_US.person}!" }

renders e.g. Hej, Pat Smith!. References are bound when you create the faker, so a path that is unknown, names a folder, or steps through a multi-variant choice fails at New. A reference must not lead back to its own value (directly or through a chain), or rendering won't terminate.

Format string. Every character is literal except:

Token	Expands to
0	digit 0–9
1	digit 1–9
A	letter A–Z
a	letter a–z
#	escape — the next char is literal (#0 → 0, ## → #)
{name}	render the sibling field name
{name()}	call a built-in function (see Functions)
{..path}	render the node at a dot path from the data root (see References)

{a|b} renders one of the sibling fields a or b, chosen at random; an arm may be a {..path} reference too ({name|..en_US.person}).

Putting it together (person.json):

[
  {
    "format": "{prefix}{femalefirst|malefirst} {last}",
    "femalefirst": ["Anna", "Astrid", "Elin"],
    "malefirst": ["Anders", "Erik", "Gustav"],
    "last": [
      { "format": "{first}sson", "first": ["Ander", "Erik", "Karl"] },
      ["Berg", "von Flemming"]
    ],
    "prefix": [
      "",
      { "format": "{string} ", "string": ["dr", "prof"], "weight": 0.05 }
    ]
  }
]

This yields e.g. Anna Eriksson, Erik Berg, or rarely dr Astrid von Flemming. Any field is reachable by dotted path — Fake("person.last") renders just a surname; choices along the path are resolved at random.

Performance

Each file is parsed, validated and weight-indexed once, in New. After that a Fake call costs about what its output costs — it scans the chosen format and renders nested tokens, independent of how large your lists are:

• Picking from a list is O(1) whatever its length — a 10-name list and a 100 000-name list cost the same.
• Giving entries a weight makes that list's pick O(log n) instead (a search over cumulative weights). Still tiny, but an unweighted list is the cheapest — only add weight where you actually want skew.
• Long format strings, deep nesting and many {tokens} add cost in proportion to the output produced.

Development

Everything runs in Docker — no local tooling beyond Docker is needed. Source is bind-mounted; build caches persist in the gocache volume.

docker compose run --rm test    # run tests
docker compose run --rm ci      # vet + format check + tests
docker compose run --rm cover   # tests with coverage
docker compose run --rm build   # compile the library
docker compose run --rm vet     # go vet
docker compose run --rm dev     # interactive shell

Commands that rewrite source keep your file ownership when run with --user:

docker compose run --rm --user "$(id -u):$(id -g)" fmt   # gofmt -w .
docker compose run --rm --user "$(id -u):$(id -g)" tidy  # go mod tidy

docker build . runs go vet and the tests, so it works as a CI gate too.

Tests run against the latest Go by default. Set GO_VERSION to check the lowest supported version too:

GO_VERSION=1.22 docker compose run --rm test   # lowest supported
docker compose run --rm test                   # latest

Layout

fakes.go        Fakes, New, options, seeding
template.go     Fake, the recursive renderer (choices, format strings, paths)
builtins.go     the {name()} function registry and its implementations
data.go         data loading: folders/files -> namespace tree, multi-path merge
cmd/fakes/      the `fakes` CLI (New + Fake over stdout)
data/           shipped data (JSON): locale folders + a misc folder

To add a category, drop a JSON file into a data directory; to add a locale, add a subdirectory of JSON files.

License

MIT — see LICENSE.