Initial project import

tools/v/examples/lorem.v

@@ -0,0 +1,60 @@
+/*
+Random Markov Text Generator
+
+This program generates pseudo-random text using a Markov chain built from
+one of several embedded corpora in the strings module. It produces structured output in the
+form of paragraphs and sentences, with configurable parameters.
+
+Usage:
+
+    v run lorem.v [--options]
+    ./lorem [--options]
+
+Example:
+
+    ./lorem -order 2 -words 12 -sentences 4 -paragraphs 3 -corpus poe
+*/
+import strings.lorem
+import flag
+import os
+import rand
+import time
+
+fn main() {
+	mut fp := flag.new_flag_parser(os.args[1..])
+	fp.application('lorem')
+	fp.version('1.0')
+	fp.description('Random text generator using a Markov chain')
+
+	order := fp.int('order', `o`, 2, 'Markov order [default: 2]')
+	words_per_sentence := fp.int('words', `w`, 10, 'Words per sentence [default: 10]')
+	sentences_per_paragraph := fp.int('sentences', `s`, 5, 'Sentences per paragraph [default: 5]')
+	paragraphs := fp.int('paragraphs', `p`, 3, 'Paragraph count [default: 3]')
+	corpus_name := fp.string('corpus', `c`, 'lorem',
+		'Corpus name (lorem, poe, darwin, bard) [default: lorem]')
+	seed_text := fp.string('seed', `S`, '', 'Seed phrase (random if omitted)')
+	mut rng_seed := fp.int('rngseed', `r`, 0, 'RNG seed (0 = random)')
+
+	fp.finalize() or {
+		eprintln(err)
+		return
+	}
+
+	if rng_seed == 0 {
+		t := time.now().unix_milli()
+		rand.seed([u32(t), u32(t >> 32)])
+		rng_seed = rand.int()
+	}
+
+	text := lorem.generate(
+		markov_order:            order
+		words_per_sentence:      words_per_sentence
+		sentences_per_paragraph: sentences_per_paragraph
+		paragraphs:              paragraphs
+		corpus_name:             corpus_name
+		seed_text:               seed_text
+		rng_seed:                rng_seed
+	)
+
+	println(text)
+}