fictional
Generate fake data deterministically from a given input
import { word } from 'fictional'
word('id-1')
word('id-2')
word('id-1')
import { words, shape } from 'fictional'
const user = shape({
name: words.options({ capitalize: 'all' })
})
user('id-1')
user('id-2')
user('id-1')
# Why? How is this different to faker?
Libraries like faker or
chance allow you to seed a psuedo-random number
generator (PRNG), such that the same sequence of values will be generated every
time. If that is all you need, those libraries are for you.
Sometimes though, instead of needing to obtain the same sequence of generated
values every time, from some set of identifiers, you need to obtain the same
mapping to generated values every time. This is where fictional comes in.
For example, when generating api response data in tests, you need to rely on
each field always mapping to the same generated value every test run. To
illustrate, you could use fictional to generate some user entity in a test:
import { word, shape, int } from 'fictional'
const name = shape({
first: word,
last: word
})
const user = shape({
id: int,
name
})
user('id-1')
To some extent, there are ways of achieving similar results with libraries like
faker, but we haven't found ways that do not have practical limitations:
- It is possible to simply seed the PRNG for every identifier, and then use it
to generate only a single value. This seems to be a misuse of these libraries
though: there is an up-front cost to seeding these PRNGs that can be expensive
if done for each and every value to be generated.
Here are benchmarks
that point to this up-front cost.
- You can generate a sequence of N values, hash identifiers to some integer
smaller than N, then simply use that as an index to lookup a value in the
sequence. This can even be done lazily. Still, you're now limiting the
uniqueness of the values to N. The larger N is, the larger the cost of keeping
these sequences in memory, or the more computationally expensive it is if you
do not hold onto the sequences in memory. The smaller N is, the less unique
your generated values are.
# API Overview
# Makers
Fictional provides functions that take in some identifying value as input, and
generate a corresponding output value. These functions are called makers.
import { word } from 'fictional'
word('id-1')
The given input can be any JSON-serializable value. For any two calls to the
same maker function, provided the input given in each call serializes down to
the same value, the same output will be returned. Makers work statelessly, so
for the same input, the same value will be returned regardless of the
enviornment, process, call ordering, or any other external factors.
Note that unlike JSON.stringify()
, object property ordering is not considered.
import { word } from 'fictional'
word({
a: 21,
b: 23
})
word({
b: 23,
a: 21
})
# Composition
const streetAddress = join(' ', [
int.options({
min: 1,
max: 200
}),
word,
oneOf(['Drive', 'Street', 'Avenue'])
])
streetAddress('id-1')
streetAddress('id-2')
Some makers take in identifying value as the only required argument and return.
These kinds of makers are described in the docs as
primary makers. word()
is an example of such a maker.
However, sometimes the data you need generated requires a combination of
different makers. Fictional provides functions for doing this: they take in an
identifying value and makers as arguments, and compose these makers in some way
to produce a corresponding output. These kinds of makers are described in the
docs as composition makers. join()
(shown above) is
an example of a such a maker.
In the example above, a maker returning fictitious street addresses is formed by
using join()
to compose int
, word()
, and other
composing maker, oneOf
.
Under the hood, composition makers re-hash the identifying value each time a
maker is given as input is used. This ensures that a unique value is generated
for each maker provided, while still keeping the result deterministic. In the
example below, the tuple()
maker ensures that each word in the
returned array has a different value.
tuple('id-1', [word, word])
word(hash('id-1')), word(hash(hash('id-1')))
# Options
Many makers accept an options object as an argument for configuring how the
generated output looks:
int('id-1')
int('id-1', {
min: 1,
max: 99
})
As a convenience, it is also possible to extend these makers to use specific
options by using the .options()
api:
const newInt = int.options({
min: 1,
max: 99
})
newInt('id-1')
newInt('id-2')
.options()
returns a new function that will call the original maker function
with the given arguments. It is still possible to provide options when calling
the returned function. In this case, these options will override any options
given to .options()
:
const newInt = int.options({
min: 1,
max: 99
})
newInt('id-1', { max: 3 })
.options()
can also be called on the returned function, to further extend the
maker:
const newInt = int.options({ min: 1 }).options({ max: 99 })
newInt('id-1')
newInt('id-2')
# Currying
Composition makers take in more than one required argument. If
the identifying input
value is not given as an argument
(one less than the required arguments is provided), then a new function will be
returned. This function will take an identifying input value as its only
argument, and call the original composition maker with both this argument and
the other required arguments initially given. This limited form of
currying can be convienent for
composing makers:
const companyName = join(' ', [word, oneOf(['Incorporated', 'Systems'])])
companyName('id-1')
companyName('id-2')
# Security
Under the hood, Fictional uses a
keyed hash function called SipHash in
order to map input values to output values deterministically.
Out of the box, fictional uses a hardcoded key. If it is important that no
information about the input values can be inferred, then you'll need to generate
and use your own key instead:
const key = hash.setKey('aSY3k#uf^dHlj12@')
# API Reference
# Primaries
# int(input[, options])
Takes in an identifying input
value and returns an
integer.
int('id-23')
options
min=1
and max=Number.MAX_SAFE_INTEGER
: the minimum and maximum
possible values for returned numbers
int('id-2', {
min: 2,
max: 99
})
# bool(id)
Takes in an identifying input
value and returns a boolean.
bool('id-23')
# float(id[, options])
Takes in an identifying input
value and returns a number
value with both a whole and decimal segment.
float('id-23')
options
min=1
and max=Number.MAX_SAFE_INTEGER
: the minimum and maximum
possible values for returned numbers
float('id-2', {
min: 2,
max: 99
})
# dateString(id[, options])
Takes in an identifying input
value and returns a string
representing a date in
ISO 8601
format.
dateString('id-23')
options
minYear=1980
and maxYear=2019
: the minimum and maximum possible year
values for returned dates
dateString('id-2', {
minYear: 1980,
maxYear: 2089
})
# char(input)
Takes in an identifying input
value and returns a string
with a single character.
char('id-23')
The generated character will be an alphanumeric: lower and upper case ASCII
letters and digits 0 to 9. Alternative character ranges are listed
below. To choose your own range of characters, see
char.inRanges()
.
Predefined character ranges
char.ascii('id-2')
char.digit('id-3')
Fictional ships with makers for a predefined set of character ranges. Similar to
char()
, these makers take in only an identifying input
value as an argument and return a string with a single character. The following
ranges are available:
-
char.ascii
: Any ASCII character
-
char.digit
: Characters for numbers 0 to 9
-
char.alphanumeric
(alias: char
): lower and upper case ASCII letters and
digits 0 to 9
-
char.letter
(alias: char.asciiLetter
): Lower and upper case ASCII letters
-
char.lower
(alias: asciiLower
): Lower case ASCII letters
-
char.upper
(alias char.asciiUpper
): Upper case ASCII letters
-
char.unicode
: Any character from the ASCII and
Latin-1 Supplement
unicode blocks
-
char.unicodeLetter
: Lower and upper case letters from the ASCII and Latin-1
Supplement unicode blocks
-
char.unicodeLower
: Lower case letters from the ASCII and Latin-1 Supplement
unicode blocks
-
char.unicodeUpper
: Upper case letters from the ASCII and Latin-1 Supplement
unicode blocks
-
char.latin1
: Any character from the Latin-1 Supplement unicode block
-
char.latin1Letter
: Lower and upper case Latin-1 Supplement letters
-
char.latin1Lower
: Lower case Latin-1 Supplement letters
-
char.latin1Upper
: Upper case Latin-1 Supplement letters
# char.inRanges(ranges)
Takes in an array of [min, max]
pairs, where min
and max
are integers
specifying the minimum and maximum possible
Unicode code point
values for a desired range of characters, and returns a maker function that will
return characters in those given ranges.
const symbols = char.inRanges([
[0x2600, 0x26ff],
[0x1f600, 0x1f64f]
])
symbols('id-1')
char.inRanges
is designed to allow characters in the ranges given to all have
a similar likelihood of being returned.
To allow for composition, each item in the array of ranges
can also be a
pre-defined character range, or another character range defined using
char.inRanges()
:
const misc = char.inRanges([[0x2600, 0x26ff]])
const emoticons = char.inRanges([[0x1f600, 0x1f64f]])
const letterOrSymbol = char.inRanges([misc, emoticons, char.letter])
letterOrSymbol('id-2')
# word(id[, options])
Takes in an identifying input
value and returns a string
value resembling a fictitious word.
word('id-23')
options
capitalize=true
: whether or not the word should start with an upper case
letterunicode=false
: whether or not the string should contain non-ascii
unicode characters. If true
is given, each returned word will always contain
a single unicode character. If false
is given, each returned word will never
contain non-ascii characters. If a value between 0
and 1
is given, that
value will represent the probability of a returned value containing a single
unicode character.minSyllables=1
and maxSyllables=4
: the minimum and maximum possible
number of syllables that returned words will contain
word('id-2', {
minSyllables: 1,
maxSyllables: 6,
unicode: 0.382
})
# words(id[, options])
Takes in an identifying input
value and returns a string
value resembling fictitious words.
words('id-23')
options
min=2
and max=3
: the minimum and maximum possible number of words that
returned strings will contain.capitalize='first'
: whether or not the words should start with upper
case letters. If true
or 'all'
is given, each string returned will start
with an upper case letter in each word. If 'first'
is given, for each string
returned, only the first word will start with an upper case letter. If false
is given, each string returned will always contain only lower case letters.unicode=false
: whether or not the string should contain non-ascii
unicode characters. If true
is given, each returned word will always contain
a single unicode character. If false
is given, each returned word will never
contain non-ascii characters. If a value between 0
and 1
is given, that
value will represent the probability of a returned value containing a single
unicode character.minSyllables=1
and maxSyllables=4
: the minimum and maximum possible
number of syllables that returned words will contain
words('id-2', {
min: 5,
max: 8,
unicode: 0.618,
capitalize: 'all'
})
# sentence(id[, options])
Takes in an identifying input
value and returns a string
value resembling a sentence of fictitious words.
sentence('id-23')
options
minClauses=1
and maxClauses=2
: the minimum and maximum possible number
of clauses that a returned sentence will contain.minWords=5
and maxWords=8
: the minimum and maximum possible number of
words that each clause will contain.unicode=false
: whether or not the string should contain non-ascii
unicode characters. If true
is given, each returned word will always contain
a single unicode character. If false
is given, each returned word will never
contain non-ascii characters. If a value between 0
and 1
is given, that
value will represent the probability of a returned value containing a single
unicode character.minSyllables=1
and maxSyllables=4
: the minimum and maximum possible
number of syllables that returned words will contain
sentence('id-2', {
minClauses: 2,
maxClauses: 3,
minWords: 2,
maxWords: 3,
unicode: 0.9
})
# paragraph(id[, options])
Takes in an identifying input
value and returns a string
value resembling a paragraph of fictitious words.
paragraph('id-23')
options
minSentences=3
and minSentences=7
: the minimum and maximum possible
number of sentences that a returned paragraph will contain.minClauses=1
and maxClauses=2
: the minimum and maximum possible number
of clauses that each sentence will contain.minWords=5
and maxWords=8
: the minimum and maximum possible number of
words that each clause will contain.unicode=false
: whether or not the string should contain non-ascii
unicode characters. If true
is given, each returned word will always contain
a single unicode character. If false
is given, each returned word will never
contain non-ascii characters. If a value between 0
and 1
is given, that
value will represent the probability of a returned value containing a single
unicode character.minSyllables=1
and maxSyllables=4
: the minimum and maximum possible
number of syllables that returned words will contain.
paragraph('id-2', {
minSentences: 2,
minSentences: 3,
unicode: 0.9
})
# Composition
# join(input, joiner, values)
Takes in an identifying input
value and an array of makers
as values
, calls each with a unique identifying input, and joins the results
with the given joiner
.
join('id-23', ' ', [word, oneOf(['Street', 'Drive'])])
If an item in the value
array is not a function, that value will be used
as-is:
join('id-2', ' ', [word, 'Drive'])
joiner
can also be a function, in which case it will be called with the
results of resolving each item in values
as input:
join('id-3', ([a, b, c]) => `${a}-${b} ${c}`, [word, word, word])
If any of the items in values
resolves to a nested array, that array will be
flattened (regardless of nesting depth):
join('id-2', '', [char.letter, times(3, char.alphanumeric)])
# oneOf(input, values)
Takes in an identifying input
value and an array of
values
, and returns an item in values
that corresponds to that input
:
oneOf('id-23', ['red', 'green', 'blue'])
If an item in values
is a maker, that maker will be called and the result will
be returned:
oneOf('id-2', [int, word, char])
# someOf(input, range, values)
Takes in an identifying input
value and an array of
values
, repeatedly picks items from that array a number of times within the
given range
. Each item will be picked no more than once.
someOf('id-23', [1, 2], ['red', 'green', 'blue'])
As shown above, range
can be a tuple array of the minimum and maximum possible
number of items that can be picked.
It can also be given as a number, in which case exactly that number of items
will be picked:
someOf('id-2', 2, ['red', 'green', 'blue'])
If an item in values
is a maker, that maker will be called and the result will
be returned:
someOf('id-3', [1, 2], [int, word, char])
# times(input, range, maker)
Takes in an identifying input
value and a maker
, calls
that maker repeatedly (each time with a unique input) for a number of times
within the given range
, and returns the results as an array:
times('id-23', [4, 5], word)
As shown above, range
can be a tuple array of the minimum and maximum possible
number of times the maker should be called. It can also be given as a number, in
which case the given maker will be called exactly that number of times:
times('id-2', 2, word)
# tuple(input, values)
Takes in an identifying input
value and an array of makers
as values
, calls each with a unique identifying input, and returns the array
of results.
tuple('id-23', [char, char])
If an item in the value
array is not a function, that value will be used
as-is:
tuple('id-2', [char, '!'])
# shape(input, properties)
Takes in an identifying input
value and an object of
makers as properties
, calls each property's value with a unique identifying
input, and returns results as an object.
shape('id-23', {
firstName: word,
lastName: word
})
If an item in the properties
object is not a function, that value will be used
as-is:
shape('id-23', {
name: join(' ', [word, word]),
active: true
})
# oneOfWeighted(id, values)
Takes in an identifying input
value and a value
array of
consisting of [probability, value]
pairs, and returns one of one of the values
in that array. The likelihood of a particular value
being returned will
correspond to the probability
given for it, where probability
is a number
between 0
and 1
.
oneOfWeighted('id-23', [
[0.9, 'red'],
[0.05, 'green'],
[0.05, 'blue']
])
If an item in values
is a maker, that maker will be called and the result will
be returned:
oneOfWeighted('id-2', [
[0.9, word],
[0.05, char],
[0.05, int]
])
For each [probability, value]
pair in the array of values
, if the given
probability
is not a number, that probability will be considered unassigned.
All items with unassigned probabilities will receive an equal share of the
remaining probability after accounting for all items with assigned probabilities
(all items for which a number value was given for their probability). In the
example below, 'green'
and 'blue'
will both have a probability of 0.4
of
being returned ((1 - 0.2) / 2
).
oneOfWeighted('id-23', [
[0.2, 'red'],
[null, 'green'],
[null, 'blue']
])
# Install & Use
You can use fictional as the npm package fictional
:
npm i -D fictional # chances are you want it as a devDependency
# or
yarn add -D fictional
Fictional can be used in both es-module-aware and commonjs
bundlers/environments.
import { word } from 'fictional'
import word from 'fictional/word'
const { word } = require('fictional')
const word = require('fictional/word')
It can also be used a <script>
:
<script
crossorigin
src="https://unpkg.com/fictional/dist/umd/fictional.js"
></script>
<script>
fictional.word('some-identifier')
</script>