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//! Lorem ipsum generator.
//!
//! This crate generates pseudo-Latin [lorem ipsum placeholder
//! text][wiki]. The traditional lorem ipsum text start like this:
//!
//! > Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do
//! > eiusmod tempor incididunt ut labore et dolore magna aliqua.
//!
//! This text is in the [`LOREM_IPSUM`] constant. Random looking text
//! like the above can be generated using the [`lipsum`] function. The
//! function allows you to generate as much text as desired and each
//! invocation will generate different text.
//!
//! The random looking text is generated using a [Markov chain] of
//! order two, which simply means that the next word is based on the
//! previous two words in the input texts. The Markov chain can be
//! used with other input texts by creating an instance of
//! [`MarkovChain`] and calling its [`learn`] method.
//!
//! [wiki]: https://en.wikipedia.org/wiki/Lorem_ipsum
//! [`lipsum`]: fn.lipsum.html
//! [`MarkovChain`]: struct.MarkovChain.html
//! [`learn`]: struct.MarkovChain.html#method.learn
//! [Markov chain]: https://en.wikipedia.org/wiki/Markov_chain
#![doc(html_root_url = "https://docs.rs/lipsum/0.9.1")]
#![forbid(unsafe_code)]
#![deny(missing_docs)]
use rand::seq::SliceRandom;
use rand::{Rng, SeedableRng};
use rand_chacha::ChaCha20Rng;
use std::collections::HashMap;
/// A bigram is simply two consecutive words.
pub type Bigram<'a> = (&'a str, &'a str);
/// Simple order two Markov chain implementation.
///
/// The [Markov chain] is a chain of order two, which means that it
/// will use the previous two words (a bigram) when predicting the
/// next word. This is normally enough to generate random text that
/// looks somewhat plausible. The implementation is based on
/// [Generating arbitrary text with Markov chains in Rust][blog post].
///
/// [Markov chain]: https://en.wikipedia.org/wiki/Markov_chain
/// [blog post]: https://blakewilliams.me/posts/generating-arbitrary-text-with-markov-chains-in-rust
#[derive(Debug, Clone, Default)]
pub struct MarkovChain<'a> {
map: HashMap<Bigram<'a>, Vec<&'a str>>,
keys: Vec<Bigram<'a>>,
}
impl<'a> MarkovChain<'a> {
/// Create a new empty Markov chain.
///
/// # Examples
///
/// ```
/// # fn main() {
/// use lipsum::MarkovChain;
/// use rand::SeedableRng;
/// use rand_chacha::ChaCha20Rng;
///
/// let mut chain = MarkovChain::new();
/// chain.learn("infra-red red orange yellow green blue indigo x-ray");
///
/// let mut rng = ChaCha20Rng::seed_from_u64(0);
///
/// // The chain jumps consistently like this:
/// assert_eq!(chain.generate_with_rng(&mut rng, 1), "Orange.");
/// assert_eq!(chain.generate_with_rng(&mut rng, 1), "Infra-red.");
/// assert_eq!(chain.generate_with_rng(&mut rng, 1), "Yellow.");
/// # }
/// ```
pub fn new() -> MarkovChain<'a> {
Default::default()
}
/// Add new text to the Markov chain. This can be called several
/// times to build up the chain.
///
/// # Examples
///
/// ```
/// use lipsum::MarkovChain;
///
/// let mut chain = MarkovChain::new();
/// chain.learn("red green blue");
/// assert_eq!(chain.words(("red", "green")), Some(&vec!["blue"]));
///
/// chain.learn("red green yellow");
/// assert_eq!(chain.words(("red", "green")), Some(&vec!["blue", "yellow"]));
/// ```
pub fn learn(&mut self, sentence: &'a str) {
let words = sentence.split_whitespace().collect::<Vec<&str>>();
for window in words.windows(3) {
let (a, b, c) = (window[0], window[1], window[2]);
self.map.entry((a, b)).or_default().push(c);
}
// Sync the keys with the current map.
self.keys = self.map.keys().cloned().collect();
self.keys.sort_unstable();
}
/// Returs the number of states in the Markov chain.
///
/// # Examples
///
/// ```
/// use lipsum::MarkovChain;
///
/// let mut chain = MarkovChain::new();
/// assert_eq!(chain.len(), 0);
///
/// chain.learn("red orange yellow green blue indigo");
/// assert_eq!(chain.len(), 4);
/// ```
#[inline]
pub fn len(&self) -> usize {
self.map.len()
}
/// Returns `true` if the Markov chain has no states.
///
/// # Examples
///
/// ```
/// use lipsum::MarkovChain;
///
/// let mut chain = MarkovChain::new();
/// assert!(chain.is_empty());
///
/// chain.learn("foo bar baz");
/// assert!(!chain.is_empty());
/// ```
pub fn is_empty(&self) -> bool {
self.len() == 0
}
/// Get the possible words following the given bigram, or `None`
/// if the state is invalid.
///
/// # Examples
///
/// ```
/// use lipsum::MarkovChain;
///
/// let mut chain = MarkovChain::new();
/// chain.learn("red green blue");
/// assert_eq!(chain.words(("red", "green")), Some(&vec!["blue"]));
/// assert_eq!(chain.words(("foo", "bar")), None);
/// ```
pub fn words(&self, state: Bigram<'a>) -> Option<&Vec<&str>> {
self.map.get(&state)
}
/// Generate a sentence with `n` words of lorem ipsum text. The
/// sentence will start from a random point in the Markov chain
/// generated using the specified random number generator,
/// and a `.` will be added as necessary to form a full sentence.
///
/// See [`generate_with_rng_from`] if you want to control the
/// starting point for the generated text and see [`iter_with_rng`]
/// if you simply want a sequence of words.
///
/// # Examples
///
/// Generating the sounds of a grandfather clock:
///
/// ```
/// use lipsum::MarkovChain;
/// use rand_chacha::ChaCha20Rng;
/// use rand::SeedableRng;
///
/// let mut chain = MarkovChain::new();
/// chain.learn("Tick, Tock, Tick, Tock, Ding! Tick, Tock, Ding! Ding!");
/// println!("{}", chain.generate_with_rng(ChaCha20Rng::seed_from_u64(0), 15));
/// ```
///
/// The output looks like this:
///
/// > Ding! Tick, Tock, Tick, Tock, Ding! Ding! Tock, Ding! Tick,
/// > Tock, Tick, Tock, Tick, Tock.
///
/// [`generate_with_rng_from`]: struct.MarkovChain.html#method.generate_with_rng_from
/// [`iter_with_rng`]: struct.MarkovChain.html#method.iter_with_rng
pub fn generate_with_rng<R: Rng>(&self, rng: R, n: usize) -> String {
join_words(self.iter_with_rng(rng).take(n))
}
/// Generate a sentence with `n` words of lorem ipsum text. The sentence
/// will start from a predetermined point in the Markov chain generated
/// using the default random number generator and a `.` will be added as
/// necessary to form a full sentence.
///
/// See [`generate_from`] if you want to control the starting point for the
/// generated text and see [`iter`] if you simply want a sequence of words.
///
/// # Examples
///
/// Generating the sounds of a grandfather clock:
///
/// ```
/// use lipsum::MarkovChain;
///
/// let mut chain = MarkovChain::new();
/// chain.learn("Tick, Tock, Tick, Tock, Ding! Tick, Tock, Ding! Ding!");
/// println!("{}", chain.generate(15));
/// ```
///
/// The output looks like this:
///
/// > Ding! Tick, Tock, Tick, Tock, Ding! Ding! Tock, Ding! Tick,
/// > Tock, Tick, Tock, Tick, Tock.
///
/// [`generate_from`]: struct.MarkovChain.html#method.generate_from
/// [`iter`]: struct.MarkovChain.html#method.iter
pub fn generate(&self, n: usize) -> String {
self.generate_with_rng(default_rng(), n)
}
/// Generate a sentence with `n` words of lorem ipsum text. The
/// sentence will start from the given bigram and a `.` will be
/// added as necessary to form a full sentence.
///
/// Use [`generate_with_rng`] if the starting point is not important. See
/// [`iter_with_rng_from`] if you want a sequence of words that you can
/// format yourself.
///
/// [`generate_with_rng`]: struct.MarkovChain.html#method.generate_with_rng
/// [`iter_with_rng_from`]: struct.MarkovChain.html#method.iter_with_rng_from
pub fn generate_with_rng_from<R: Rng>(&self, rng: R, n: usize, from: Bigram<'a>) -> String {
join_words(self.iter_with_rng_from(rng, from).take(n))
}
/// Generate a sentence with `n` words of lorem ipsum text. The
/// sentence will start from the given bigram and a `.` will be
/// added as necessary to form a full sentence.
///
/// Use [`generate`] if the starting point is not important. See
/// [`iter_from`] if you want a sequence of words that you can
/// format yourself.
///
/// [`generate`]: struct.MarkovChain.html#method.generate
/// [`iter_from`]: struct.MarkovChain.html#method.iter_from
pub fn generate_from(&self, n: usize, from: Bigram<'a>) -> String {
self.generate_with_rng_from(default_rng(), n, from)
}
/// Make a never-ending iterator over the words in the Markov
/// chain. The iterator starts at a random point in the chain.
pub fn iter_with_rng<R: Rng>(&self, mut rng: R) -> Words<'_, R> {
let initial_bigram = if self.is_empty() {
("", "")
} else {
*self.keys.choose(&mut rng).unwrap()
};
self.iter_with_rng_from(rng, initial_bigram)
}
/// Make a never-ending iterator over the words in the Markov chain. The
/// iterator starts at a predetermined point in the chain.
pub fn iter(&self) -> Words<'_, impl Rng> {
self.iter_with_rng(default_rng())
}
/// Make a never-ending iterator over the words in the Markov
/// chain. The iterator starts at the given bigram.
pub fn iter_with_rng_from<R: Rng>(&self, rng: R, from: Bigram<'a>) -> Words<'_, R> {
Words {
map: &self.map,
rng,
keys: &self.keys,
state: from,
}
}
/// Make a never-ending iterator over the words in the Markov
/// chain. The iterator starts at the given bigram.
pub fn iter_from(&self, from: Bigram<'a>) -> Words<'_, impl Rng> {
self.iter_with_rng_from(default_rng(), from)
}
}
/// Provide a default random number generator. This generator is seeded and will
/// always produce the same sequence of numbers. The seed is chosen to yield
/// good results for the included Markov chain.
fn default_rng() -> impl Rng {
ChaCha20Rng::seed_from_u64(97)
}
/// Never-ending iterator over words in the Markov chain.
///
/// Generated with the [`iter`] or [`iter_from`] methods.
///
/// [`iter`]: struct.MarkovChain.html#method.iter
/// [`iter_from`]: struct.MarkovChain.html#method.iter_from
pub struct Words<'a, R: Rng> {
map: &'a HashMap<Bigram<'a>, Vec<&'a str>>,
rng: R,
keys: &'a Vec<Bigram<'a>>,
state: Bigram<'a>,
}
impl<'a, R: Rng> Iterator for Words<'a, R> {
type Item = &'a str;
fn next(&mut self) -> Option<&'a str> {
if self.map.is_empty() {
return None;
}
let result = Some(self.state.0);
while !self.map.contains_key(&self.state) {
self.state = *self.keys.choose(&mut self.rng).unwrap();
}
let next_words = &self.map[&self.state];
let next = next_words.choose(&mut self.rng).unwrap();
self.state = (self.state.1, next);
result
}
}
/// Check if `c` is an ASCII punctuation character.
fn is_ascii_punctuation(c: char) -> bool {
c.is_ascii_punctuation()
}
/// Capitalize the first character in a string.
fn capitalize(word: &str) -> String {
let idx = match word.chars().next() {
Some(c) => c.len_utf8(),
None => 0,
};
let mut result = String::with_capacity(word.len());
result.push_str(&word[..idx].to_uppercase());
result.push_str(&word[idx..]);
result
}
/// Join words from an iterator. The first word is always capitalized
/// and the generated sentence will end with `'.'` if it doesn't
/// already end with some other ASCII punctuation character.
fn join_words<'a, I: Iterator<Item = &'a str>>(mut words: I) -> String {
match words.next() {
None => String::new(),
Some(word) => {
// Punctuation characters which ends a sentence.
let punctuation: &[char] = &['.', '!', '?'];
let mut sentence = capitalize(word);
let mut needs_cap = sentence.ends_with(punctuation);
// Add remaining words.
for word in words {
sentence.push(' ');
if needs_cap {
sentence.push_str(&capitalize(word));
} else {
sentence.push_str(word);
}
needs_cap = word.ends_with(punctuation);
}
// Ensure the sentence ends with either one of ".!?".
if !sentence.ends_with(punctuation) {
// Trim all trailing punctuation characters to avoid
// adding '.' after a ',' or similar.
let idx = sentence.trim_end_matches(is_ascii_punctuation).len();
sentence.truncate(idx);
sentence.push('.');
}
sentence
}
}
}
/// The traditional lorem ipsum text as given in [Wikipedia]. Using
/// this text alone for a Markov chain of order two doesn't work very
/// well since each bigram (two consequtive words) is followed by just
/// one other word. In other words, the Markov chain will always
/// produce the same output and recreate the lorem ipsum text
/// precisely. However, combining it with the full text in
/// [`LIBER_PRIMUS`] works well.
///
/// [Wikipedia]: https://en.wikipedia.org/wiki/Lorem_ipsum
/// [`LIBER_PRIMUS`]: constant.LIBER_PRIMUS.html
pub const LOREM_IPSUM: &str = include_str!("lorem-ipsum.txt");
/// The first book in Cicero's work De finibus bonorum et malorum ("On
/// the ends of good and evil"). The lorem ipsum text in
/// [`LOREM_IPSUM`] is derived from part of this text.
///
/// [`LOREM_IPSUM`]: constant.LOREM_IPSUM.html
pub const LIBER_PRIMUS: &str = include_str!("liber-primus.txt");
thread_local! {
// Markov chain generating lorem ipsum text.
static LOREM_IPSUM_CHAIN: MarkovChain<'static> = {
let mut chain = MarkovChain::new();
// The cost of learning increases as more and more text is
// added, so we start with the smallest text.
chain.learn(LOREM_IPSUM);
chain.learn(LIBER_PRIMUS);
chain
}
}
/// Generate `n` words of lorem ipsum text. The output will always start with
/// "Lorem ipsum".
///
/// The text continues with the standard lorem ipsum text from [`LOREM_IPSUM`]
/// and becomes randomly generated but deterministic if more than 18 words is
/// requested. See [`lipsum_words`] if fully random text is needed.
///
/// # Examples
///
/// ```
/// use lipsum::lipsum;
///
/// assert_eq!(lipsum(7), "Lorem ipsum dolor sit amet, consectetur adipiscing.");
/// ```
///
/// [`LOREM_IPSUM`]: constant.LOREM_IPSUM.html
/// [`lipsum_words`]: fn.lipsum_words.html
pub fn lipsum(n: usize) -> String {
LOREM_IPSUM_CHAIN.with(|chain| chain.generate_from(n, ("Lorem", "ipsum")))
}
/// Generate `n` words of lorem ipsum text with a custom RNG. The output will
/// always start with "Lorem ipsum".
///
/// A custom RNG allows to base the markov chain on a different random number
/// sequence. This also allows using a regular [`thread_rng`] random number
/// generator. If that generator is used, the text will differ in each
/// invocation.
///
/// # Examples
///
/// ```
/// use lipsum::lipsum_with_rng;
/// use rand::thread_rng;
///
/// println!("{}", lipsum_with_rng(thread_rng(), 23));
/// // -> "Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do
/// // eiusmod tempor incididunt ut labore et dolore magnam aliquam
/// // quaerat voluptatem. Ut enim."
/// ```
///
/// [`thread_rng`]: https://docs.rs/rand/latest/rand/fn.thread_rng.html
pub fn lipsum_with_rng(rng: impl Rng, n: usize) -> String {
LOREM_IPSUM_CHAIN.with(|chain| chain.generate_with_rng_from(rng, n, ("Lorem", "ipsum")))
}
/// Generate `n` words of lorem ipsum text.
///
/// The text is deterministically sampled from a Markov chain based on
/// [`LOREM_IPSUM`]. Multiple sentences may be generated, depending on the
/// punctuation of the words being selected.
///
/// # Examples
///
/// ```
/// use lipsum::lipsum_words;
///
/// assert_eq!(lipsum_words(6), "Ullus investigandi veri, nisi inveneris, et.");
/// ```
///
/// [`LOREM_IPSUM`]: constant.LOREM_IPSUM.html
pub fn lipsum_words(n: usize) -> String {
LOREM_IPSUM_CHAIN.with(|chain| chain.generate(n))
}
/// Generate `n` words of lorem ipsum text with a custom RNG.
///
/// A custom RNG allows to base the markov chain on a different random number
/// sequence. This also allows using a regular [`thread_rng`] random number
/// generator. If that generator is used, the text will differ in each
/// invocation.
///
/// # Examples
///
/// ```
/// use lipsum::lipsum_words_with_rng;
/// use rand::thread_rng;
///
/// println!("{}", lipsum_words_with_rng(thread_rng(), 7));
/// // -> "Quot homines, tot sententiae; falli igitur possumus."
/// ```
///
/// [`thread_rng`]: https://docs.rs/rand/latest/rand/fn.thread_rng.html
pub fn lipsum_words_with_rng(rng: impl Rng, n: usize) -> String {
LOREM_IPSUM_CHAIN.with(|chain| chain.generate_with_rng(rng, n))
}
/// Minimum number of words to include in a title.
const TITLE_MIN_WORDS: usize = 3;
/// Maximum number of words to include in a title.
const TITLE_MAX_WORDS: usize = 8;
/// Words shorter than this size are not capitalized.
const TITLE_SMALL_WORD: usize = 3;
/// Generate a short lorem ipsum text with words in title case.
///
/// The words are capitalized and stripped for punctuation characters.
///
/// # Examples
///
/// ```
/// use lipsum::lipsum_title;
///
/// println!("{}", lipsum_title());
/// ```
///
/// This will generate a string like
///
/// > Grate Meminit et Praesentibus
///
/// which should be suitable for use in a document title for section
/// heading.
pub fn lipsum_title() -> String {
lipsum_title_with_rng(default_rng())
}
/// Generate a short lorem ipsum text with words in title case with a custom RNG.
///
/// A custom RNG allows to base the markov chain on a different random number
/// sequence. This also allows using a regular [`thread_rng`] random number
/// generator. If that generator is used, the text will differ in each
/// invocation.
///
/// The words are capitalized and stripped for punctuation characters.
///
/// # Examples
///
/// ```
/// use lipsum::lipsum_title_with_rng;
/// use rand::thread_rng;
///
/// println!("{}", lipsum_title_with_rng(thread_rng()));
/// ```
///
/// This will generate a string like
///
/// > Grate Meminit et Praesentibus
///
/// which should be suitable for use in a document title for section
/// heading.
///
/// [`thread_rng`]: https://docs.rs/rand/latest/rand/fn.thread_rng.html
pub fn lipsum_title_with_rng(mut rng: impl Rng) -> String {
LOREM_IPSUM_CHAIN.with(|chain| {
let n = rng.gen_range(TITLE_MIN_WORDS..TITLE_MAX_WORDS);
// The average word length with our corpus is 7.6 bytes so
// this capacity will avoid most allocations.
let mut title = String::with_capacity(8 * n);
let words = chain
.iter_with_rng(rng)
.map(|word| word.trim_matches(is_ascii_punctuation))
.filter(|word| !word.is_empty())
.take(n);
for (i, word) in words.enumerate() {
if i > 0 {
title.push(' ');
}
// Capitalize the first word and all long words.
if i == 0 || word.len() > TITLE_SMALL_WORD {
title.push_str(&capitalize(word));
} else {
title.push_str(word);
}
}
title
})
}
#[cfg(test)]
mod tests {
use super::*;
use rand::thread_rng;
#[test]
fn starts_with_lorem_ipsum() {
assert_eq!(&lipsum(10)[..11], "Lorem ipsum");
}
#[test]
fn generate_zero_words() {
assert_eq!(lipsum(0).split_whitespace().count(), 0);
}
#[test]
fn generate_one_word() {
assert_eq!(lipsum(1).split_whitespace().count(), 1);
}
#[test]
fn generate_two_words() {
assert_eq!(lipsum(2).split_whitespace().count(), 2);
}
#[test]
fn starts_differently() {
// Check that calls to lipsum_words don't always start with
// "Lorem ipsum".
let idx = "Lorem ipsum".len();
assert_ne!(
&lipsum_words_with_rng(thread_rng(), 5)[..idx],
&lipsum_words_with_rng(thread_rng(), 5)[..idx]
);
}
#[test]
fn generate_title() {
for word in lipsum_title().split_whitespace() {
assert!(
!word.starts_with(is_ascii_punctuation) && !word.ends_with(is_ascii_punctuation),
"Unexpected punctuation: {:?}",
word
);
if word.len() > TITLE_SMALL_WORD {
assert!(
word.starts_with(char::is_uppercase),
"Expected small word to be capitalized: {:?}",
word
);
}
}
}
#[test]
fn capitalize_after_punctiation() {
// The Markov Chain will yield a "habitut." as the second word. However,
// the following "voluptatem" is not capitalized, which does not make
// much sense, given that it appears after a full stop. The `join_words`
// must ensure that every word appearing after sentence-ending
// punctuation is capitalized.
assert_eq!(
lipsum_words_with_rng(ChaCha20Rng::seed_from_u64(5), 9),
"Nullam habuit. Voluptatem cum summum bonum in voluptate est."
);
}
#[test]
fn empty_chain() {
let chain = MarkovChain::new();
assert_eq!(chain.generate(10), "");
}
#[test]
fn generate_from() {
let mut chain = MarkovChain::new();
chain.learn("red orange yellow green blue indigo violet");
assert_eq!(
chain.generate_from(5, ("orange", "yellow")),
"Orange yellow green blue indigo."
);
}
#[test]
fn generate_last_bigram() {
// The bigram "yyy zzz" will not be present in the Markov
// chain's map, and so we will not generate "xxx yyy zzz" as
// one would expect. The chain moves from state "xxx yyy" to
// "yyy zzz", but sees that as invalid state and resets itself
// back to "xxx yyy".
let mut chain = MarkovChain::new();
chain.learn("xxx yyy zzz");
assert_ne!(chain.generate_from(3, ("xxx", "yyy")), "xxx yyy zzz");
}
#[test]
fn generate_from_no_panic() {
// No panic when asked to generate a chain from a starting
// point that doesn't exist in the chain.
let mut chain = MarkovChain::new();
chain.learn("foo bar baz");
chain.generate_from(3, ("xxx", "yyy"));
}
#[test]
fn chain_map() {
let mut chain = MarkovChain::new();
chain.learn("foo bar baz quuz");
let map = &chain.map;
assert_eq!(map.len(), 2);
assert_eq!(map[&("foo", "bar")], vec!["baz"]);
assert_eq!(map[&("bar", "baz")], vec!["quuz"]);
}
#[test]
fn new_with_rng() {
let rng = ChaCha20Rng::seed_from_u64(1234);
let mut chain = MarkovChain::new();
chain.learn("foo bar x y z");
chain.learn("foo bar a b c");
assert_eq!(
chain.generate_with_rng(rng, 15),
"A b bar a b a b bar a b x y b y x."
);
}
}