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Add word-count exercise #127

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8 changes: 8 additions & 0 deletions config.json
Original file line number Diff line number Diff line change
Expand Up @@ -423,6 +423,14 @@
"prerequisites": [],
"difficulty": 3
},
{
"slug": "word-count",
"name": "Word Count",
"uuid": "225716ce-363d-4ece-bfe2-b25e2cb25d52",
"practices": [],
"prerequisites": [],
"difficulty": 3
},
{
"slug": "yacht",
"name": "Yacht",
Expand Down
47 changes: 47 additions & 0 deletions exercises/practice/word-count/.docs/instructions.md
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# Instructions

Your task is to count how many times each word occurs in a subtitle of a drama.

The subtitles from these dramas use only ASCII characters.

The characters often speak in casual English, using contractions like _they're_ or _it's_.
Though these contractions come from two words (e.g. _we are_), the contraction (_we're_) is considered a single word.

Words can be separated by any form of punctuation (e.g. ":", "!", or "?") or whitespace (e.g. "\t", "\n", or " ").
The only punctuation that does not separate words is the apostrophe in contractions.

Numbers are considered words.
If the subtitles say _It costs 100 dollars._ then _100_ will be its own word.

Words are case insensitive.
For example, the word _you_ occurs three times in the following sentence:

> You come back, you hear me? DO YOU HEAR ME?

The ordering of the word counts in the results doesn't matter.

Here's an example that incorporates several of the elements discussed above:

- simple words
- contractions
- numbers
- case insensitive words
- punctuation (including apostrophes) to separate words
- different forms of whitespace to separate words

`"That's the password: 'PASSWORD 123'!", cried the Special Agent.\nSo I fled.`

The mapping for this subtitle would be:

```text
123: 1
agent: 1
cried: 1
fled: 1
i: 1
password: 2
so: 1
special: 1
that's: 1
the: 2
```
8 changes: 8 additions & 0 deletions exercises/practice/word-count/.docs/introduction.md
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# Introduction

You teach English as a foreign language to high school students.

You've decided to base your entire curriculum on TV shows.
You need to analyze which words are used, and how often they're repeated.

This will let you choose the simplest shows to start with, and to gradually increase the difficulty as time passes.
39 changes: 39 additions & 0 deletions exercises/practice/word-count/.meta/Example.roc
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module [countWords]

countWords : Str -> Dict Str U64
countWords = \sentence ->
sentence
|> Str.toUtf8
|> List.append ' ' # to ensure the last word is added
|> List.walk { words: [], word: [], contractionStarted: Bool.false } \state, char ->
{ words, word, contractionStarted } = state
when char is
c if c >= 'A' && c <= 'Z' ->
{ words, word: word |> List.append (c - 'A' + 'a'), contractionStarted: Bool.false }

c if c >= 'a' && c <= 'z' || c >= '0' && c <= '9' ->
{ words, word: word |> List.append c, contractionStarted: Bool.false }

c ->
if List.isEmpty word then
state
else if c != '\'' || contractionStarted then
if contractionStarted then
{ words: words |> List.append (word |> List.dropLast 1), word: [], contractionStarted: Bool.false }
else
{ words: words |> List.append word, word: [], contractionStarted: Bool.false }
else

{ words, word: word |> List.append c, contractionStarted: Bool.true }
|> .words
|> List.dropIf List.isEmpty
|> List.walk (Dict.empty {}) \result, chars ->
word =
when chars |> Str.fromUtf8 is
Ok parsedWord -> parsedWord
Err (BadUtf8 _ _) -> crash "Unreachable: we only use ASCII characters"
result
|> Dict.update word \maybeCount ->
when maybeCount is
Ok count -> Ok (count + 1)
Err Missing -> Ok 1
18 changes: 18 additions & 0 deletions exercises/practice/word-count/.meta/config.json
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{
"authors": [
"ageron"
],
"files": {
"solution": [
"WordCount.roc"
],
"test": [
"word-count-test.roc"
],
"example": [
".meta/Example.roc"
]
},
"blurb": "Given a phrase, count the occurrences of each word in that phrase.",
"source": "This is a classic toy problem, but we were reminded of it by seeing it in the Go Tour."
}
18 changes: 18 additions & 0 deletions exercises/practice/word-count/.meta/template.j2
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{%- import "generator_macros.j2" as macros with context -%}
{{ macros.canonical_ref() }}
{{ macros.header() }}

import {{ exercise | to_pascal }} exposing [{{ cases[0]["property"] | to_camel }}]

{% for case in cases -%}
# {{ case["description"] }}
expect
result = {{ case["property"] | to_camel }} {{ case["input"]["sentence"] | to_roc }}
expected = Dict.fromList [
{%- for word, count in case["expected"].items() %}
({{ word | to_roc }}, {{ count }}),
{%- endfor %}
]
result == expected

{% endfor %}
57 changes: 57 additions & 0 deletions exercises/practice/word-count/.meta/tests.toml
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# This is an auto-generated file.
#
# Regenerating this file via `configlet sync` will:
# - Recreate every `description` key/value pair
# - Recreate every `reimplements` key/value pair, where they exist in problem-specifications
# - Remove any `include = true` key/value pair (an omitted `include` key implies inclusion)
# - Preserve any other key/value pair
#
# As user-added comments (using the # character) will be removed when this file
# is regenerated, comments can be added via a `comment` key.

[61559d5f-2cad-48fb-af53-d3973a9ee9ef]
description = "count one word"

[5abd53a3-1aed-43a4-a15a-29f88c09cbbd]
description = "count one of each word"

[2a3091e5-952e-4099-9fac-8f85d9655c0e]
description = "multiple occurrences of a word"

[e81877ae-d4da-4af4-931c-d923cd621ca6]
description = "handles cramped lists"

[7349f682-9707-47c0-a9af-be56e1e7ff30]
description = "handles expanded lists"

[a514a0f2-8589-4279-8892-887f76a14c82]
description = "ignore punctuation"

[d2e5cee6-d2ec-497b-bdc9-3ebe092ce55e]
description = "include numbers"

[dac6bc6a-21ae-4954-945d-d7f716392dbf]
description = "normalize case"

[4185a902-bdb0-4074-864c-f416e42a0f19]
description = "with apostrophes"
include = false

[4ff6c7d7-fcfc-43ef-b8e7-34ff1837a2d3]
description = "with apostrophes"
reimplements = "4185a902-bdb0-4074-864c-f416e42a0f19"

[be72af2b-8afe-4337-b151-b297202e4a7b]
description = "with quotations"

[8d6815fe-8a51-4a65-96f9-2fb3f6dc6ed6]
description = "substrings from the beginning"

[c5f4ef26-f3f7-4725-b314-855c04fb4c13]
description = "multiple spaces not detected as a word"

[50176e8a-fe8e-4f4c-b6b6-aa9cf8f20360]
description = "alternating word separators not detected as a word"

[6d00f1db-901c-4bec-9829-d20eb3044557]
description = "quotation for word with apostrophe"
5 changes: 5 additions & 0 deletions exercises/practice/word-count/WordCount.roc
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module [countWords]

countWords : Str -> Dict Str U64
countWords = \sentence ->
crash "Please implement the 'countWords' function"
164 changes: 164 additions & 0 deletions exercises/practice/word-count/word-count-test.roc
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# These tests are auto-generated with test data from:
# https://github.com/exercism/problem-specifications/tree/main/exercises/word-count/canonical-data.json
# File last updated on 2024-09-29
app [main] {
pf: platform "https://github.com/roc-lang/basic-cli/releases/download/0.15.0/SlwdbJ-3GR7uBWQo6zlmYWNYOxnvo8r6YABXD-45UOw.tar.br",
}

main =
Task.ok {}

import WordCount exposing [countWords]

# count one word
expect
result = countWords "word"
expected = Dict.fromList [
("word", 1),
]
result == expected

# count one of each word
expect
result = countWords "one of each"
expected = Dict.fromList [
("one", 1),
("of", 1),
("each", 1),
]
result == expected

# multiple occurrences of a word
expect
result = countWords "one fish two fish red fish blue fish"
expected = Dict.fromList [
("one", 1),
("fish", 4),
("two", 1),
("red", 1),
("blue", 1),
]
result == expected

# handles cramped lists
expect
result = countWords "one,two,three"
expected = Dict.fromList [
("one", 1),
("two", 1),
("three", 1),
]
result == expected

# handles expanded lists
expect
result = countWords "one,\ntwo,\nthree"
expected = Dict.fromList [
("one", 1),
("two", 1),
("three", 1),
]
result == expected

# ignore punctuation
expect
result = countWords "car: carpet as java: javascript!!&@$%^&"
expected = Dict.fromList [
("car", 1),
("carpet", 1),
("as", 1),
("java", 1),
("javascript", 1),
]
result == expected

# include numbers
expect
result = countWords "testing, 1, 2 testing"
expected = Dict.fromList [
("testing", 2),
("1", 1),
("2", 1),
]
result == expected

# normalize case
expect
result = countWords "go Go GO Stop stop"
expected = Dict.fromList [
("go", 3),
("stop", 2),
]
result == expected

# with apostrophes
expect
result = countWords "'First: don't laugh. Then: don't cry. You're getting it.'"
expected = Dict.fromList [
("first", 1),
("don't", 2),
("laugh", 1),
("then", 1),
("cry", 1),
("you're", 1),
("getting", 1),
("it", 1),
]
result == expected

# with quotations
expect
result = countWords "Joe can't tell between 'large' and large."
expected = Dict.fromList [
("joe", 1),
("can't", 1),
("tell", 1),
("between", 1),
("large", 2),
("and", 1),
]
result == expected

# substrings from the beginning
expect
result = countWords "Joe can't tell between app, apple and a."
expected = Dict.fromList [
("joe", 1),
("can't", 1),
("tell", 1),
("between", 1),
("app", 1),
("apple", 1),
("and", 1),
("a", 1),
]
result == expected

# multiple spaces not detected as a word
expect
result = countWords " multiple whitespaces"
expected = Dict.fromList [
("multiple", 1),
("whitespaces", 1),
]
result == expected

# alternating word separators not detected as a word
expect
result = countWords ",\n,one,\n ,two \n 'three'"
expected = Dict.fromList [
("one", 1),
("two", 1),
("three", 1),
]
result == expected

# quotation for word with apostrophe
expect
result = countWords "can, can't, 'can't'"
expected = Dict.fromList [
("can", 1),
("can't", 2),
]
result == expected