# zg

zg provides Unicode text processing for Zig projects.

## Unicode Version

The Unicode version supported by zg is `16.0.0`.

## Zig Version

The minimum Zig version required is `0.14`.

## Integrating zg into your Zig Project

You first need to add zg as a dependency in your `build.zig.zon` file. In your
Zig project's root directory, run:

```plain
zig fetch --save https://codeberg.org/atman/zg/archive/v0.14.0-rc1.tar.gz
```

Then instantiate the dependency in your `build.zig`:

```zig
const zg = b.dependency("zg", .{});
```

## A Modular Approach

zg is a modular library. This approach minimizes binary file size and memory
requirements by only including the Unicode data required for the specified module.
The following sections describe the various modules and their specific use case.

### Init and Setup

The code examples will show the use of `Module.init(allocator)` to create the
various modules.  All of the allocating modules have a `setup` variant, which
takes a pointer and allocates in-place.

Example use:

```zig
test "Setup form" {
    var graphemes = try allocator.create(Graphemes);
    defer allocator.destroy(graphemes);
    try graphemes.setup(allocator);
    defer graphemes.deinit(allocator);
}
```


## Code Points

In the `code_point` module, you'll find a data structure representing a single code
point, `CodePoint`, and an `Iterator` to iterate over the code points in a string.

In your `build.zig`:

```zig
exe.root_module.addImport("code_point", zg.module("code_point"));
```

In your code:

```zig
const code_point = @import("code_point");

test "Code point iterator" {
    const str = "Hi 😊";
    var iter = code_point.Iterator{ .bytes = str };
    var i: usize = 0;

    while (iter.next()) |cp| : (i += 1) {
        // The `code` field is the actual code point scalar as a `u21`.
        if (i == 0) try expect(cp.code == 'H');
        if (i == 1) try expect(cp.code == 'i');
        if (i == 2) try expect(cp.code == ' ');

        if (i == 3) {
            try expect(cp.code == '😊');

            // The `offset` field is the byte offset in the
            // source string.
            try expect(cp.offset == 3);

            // The `len` field is the length in bytes of the
            // code point in the source string.
            try expect(cp.len == 4);
        }
    }
}
```

## Grapheme Clusters

Many characters are composed from more than one code point. These are known as
Grapheme Clusters, and the `Graphemes` module has a data structure to represent
them, `Grapheme`, and an `Iterator` to iterate over them in a string.

In your `build.zig`:

```zig
exe.root_module.addImport("Graphemes", zg.module("Graphemes"));
```

In your code:

```zig
const Graphemes = @import("Graphemes");

test "Grapheme cluster iterator" {
    const graph = try Graphemes.init(allocator);
    defer graph.deinit(allocator);

    const str = "He\u{301}"; // Hé
    var iter = graph.iterator(str);

    var i: usize = 0;

    while (iter.next()) |gc| : (i += 1) {
        // The `len` field is the length in bytes of the
        // grapheme cluster in the source string.
        if (i == 0) try expect(gc.len == 1);

        if (i == 1) {
            try expect(gc.len == 3);

            // The `offset` in bytes of the grapheme cluster
            // in the source string.
            try expect(gc.offset == 1);

            // The `bytes` method returns the slice of bytes
            // that comprise this grapheme cluster in the
            // source string `str`.
            try expectEqualStrings("e\u{301}", gc.bytes(str));
        }
    }
}
```

## Unicode General Categories

To detect the general category for a code point, use the `GeneralCategories` module.

In your `build.zig`:

```zig
exe.root_module.addImport("GeneralCategories", zg.module("GeneralCategories"));
```

In your code:

```zig
const GeneralCategories = @import("GeneralCategories");

test "General Category" {
    const gen_cat = try GeneralCategories.init(allocator);
    defer gen_cat.deinit(allocator);

    // The `gc` method returns the abbreviated General Category.
    // These abbreviations and descriptive comments can be found
    // in the source file `src/GenCatData.zig` as en enum.
    try expect(gen_cat.gc('A') == .Lu); // Lu: uppercase letter
    try expect(gen_cat.gc('3') == .Nd); // Nd: decimal number

    // The following are convenience methods for groups of General
    // Categories. For example, all letter categories start with `L`:
    // Lu, Ll, Lt, Lo.
    try expect(gen_cat.isControl(0));
    try expect(gen_cat.isLetter('z'));
    try expect(gen_cat.isMark('\u{301}'));
    try expect(gen_cat.isNumber('3'));
    try expect(gen_cat.isPunctuation('['));
    try expect(gen_cat.isSeparator(' '));
    try expect(gen_cat.isSymbol('©'));
}
```

## Unicode Properties

You can detect common properties of a code point with the `Properties` module.

In your `build.zig`:

```zig
exe.root_module.addImport("Properties", zg.module("Properties"));
```

In your code:

```zig
const Properties = @import("Properties");

test "Properties" {
    const props = try Properties.init(allocator);
    defer props.deinit(allocator);

    // Mathematical symbols and letters.
    try expect(props.isMath('+'));
    // Alphabetic only code points.
    try expect(props.isAlphabetic('Z'));
    // Space, tab, and other separators.
    try expect(props.isWhitespace(' '));
    // Hexadecimal digits and variations thereof.
    try expect(props.isHexDigit('f'));
    try expect(!props.isHexDigit('z'));

    // Accents, dieresis, and other combining marks.
    try expect(props.isDiacritic('\u{301}'));

    // Unicode has a specification for valid identifiers like
    // the ones used in programming and regular expressions.
    try expect(props.isIdStart('Z')); // Identifier start character
    try expect(!props.isIdStart('1'));
    try expect(props.isIdContinue('1'));

    // The `X` versions add some code points that can appear after
    // normalizing a string.
    try expect(props.isXidStart('\u{b33}')); // Extended identifier start character
    try expect(props.isXidContinue('\u{e33}'));
    try expect(!props.isXidStart('1'));

    // Note surprising Unicode numeric type properties!
    try expect(props.isNumeric('\u{277f}'));
    try expect(!props.isNumeric('3')); // 3 is not numeric!
    try expect(props.isDigit('\u{2070}'));
    try expect(!props.isDigit('3')); // 3 is not a digit!
    try expect(props.isDecimal('3')); // 3 is a decimal digit
}
```

## Letter Case Detection and Conversion

To detect and convert to and from different letter cases, use the `LetterCasing`
module.

In your `build.zig`:

```zig
exe.root_module.addImport("LetterCasing", zg.module("LetterCasing"));
```

In your code:

```zig
const LetterCasing = @import("LetterCasing");

test "Case" {
    const case = try LetterCasing.init(allocator);
    defer case.deinit(allocator);

    // Upper and lower case.
    try expect(case.isUpper('A'));
    try expect('A' == case.toUpper('a'));
    try expect(case.isLower('a'));
    try expect('a' == case.toLower('A'));

    // Code points that have case.
    try expect(case.isCased('É'));
    try expect(!case.isCased('3'));

    // Case detection and conversion for strings.
    try expect(case.isUpperStr("HELLO 123!"));
    const ucased = try case.toUpperStr(allocator, "hello 123");
    defer allocator.free(ucased);
    try expectEqualStrings("HELLO 123", ucased);

    try expect(case.isLowerStr("hello 123!"));
    const lcased = try case.toLowerStr(allocator, "HELLO 123");
    defer allocator.free(lcased);
    try expectEqualStrings("hello 123", lcased);
}
```

## Normalization

Unicode normalization is the process of converting a string into a uniform
representation that can guarantee a known structure by following a strict set
of rules. There are four normalization forms:

Canonical Composition (NFC)
: The most compact representation obtained by first
decomposing to Canonical Decomposition and then composing to NFC.

Compatibility Composition (NFKC)
: The most comprehensive composition obtained
by first decomposing to Compatibility Decomposition and then composing to NFKC.

Canonical Decomposition (NFD)
: Only code points with canonical decompositions
are decomposed. This is a more compact and faster decomposition but will not
provide the most comprehensive normalization possible.

Compatibility Decomposition (NFKD)
: The most comprehensive decomposition method
where both canonical and compatibility decompositions are performed recursively.

zg has methods to produce all four normalization forms in the `Normalize` module.

In your `build.zig`:

```zig
exe.root_module.addImport("Normalize", zg.module("Normalize"));
```

In your code:

```zig
const Normalize = @import("Normalize");

test "Normalization" {
    const normalize = try Normalize.init(allocator);
    defer normalize.deinit(allocator);

    // NFC: Canonical composition
    const nfc_result = try normalize.nfc(allocator, "Complex char: \u{3D2}\u{301}");
    defer nfc_result.deinit(allocator);
    try expectEqualStrings("Complex char: \u{3D3}", nfc_result.slice);

    // NFKC: Compatibility composition
    const nfkc_result = try normalize.nfkc(allocator, "Complex char: \u{03A5}\u{0301}");
    defer nfkc_result.deinit(allocator);
    try expectEqualStrings("Complex char: \u{038E}", nfkc_result.slice);

    // NFD: Canonical decomposition
    const nfd_result = try normalize.nfd(allocator, "Héllo World! \u{3d3}");
    defer nfd_result.deinit(allocator);
    try expectEqualStrings("He\u{301}llo World! \u{3d2}\u{301}", nfd_result.slice);

    // NFKD: Compatibility decomposition
    const nfkd_result = try normalize.nfkd(allocator, "Héllo World! \u{3d3}");
    defer nfkd_result.deinit(allocator);
    try expectEqualStrings("He\u{301}llo World! \u{3a5}\u{301}", nfkd_result.slice);

    // Test for equality of two strings after normalizing to NFC.
    try expect(try normalize.eql(allocator, "foé", "foe\u{0301}"));
    try expect(try normalize.eql(allocator, "foϓ", "fo\u{03D2}\u{0301}"));
}
```
The `Result` returned by normalization functions may or may not be copied from the
inputs given.  For example, an all-ASCII input does not need to be a copy, and will
be a view of the original slice.  Calling `result.deinit(allocator)` will only free
an allocated `Result`, not one which is a view.  Thus it is safe to do
unconditionally.

This does mean that the validity of a `Result` can depend on the original string
staying in memory.  To ensure that your `Result` is always a copy, you may call
`try result.toOwned(allocator)`, which will only make a copy if one was not
already made.


## Caseless Matching via Case Folding

Unicode provides a more efficient way of comparing strings while ignoring letter
case differences: case folding. When you case fold a string, it's converted into a
normalized case form suitable for efficient matching. Use the `CaseFold` module
for this.

In your `build.zig`:

```zig
exe.root_module.addImport("CaseFolding", zg.module("CaseFolding"));
```

In your code:

```zig
const CaseFolding = @import("CaseFolding");

test "Caseless matching" {
    // We need Unicode case fold data.
    const case_fold = try CaseFolding.init(allocator);
    defer case_fold.deinit(allocator);

    // `compatCaselessMatch` provides the deepest level of caseless
    // matching because it decomposes fully to NFKD.
    const a = "Héllo World! \u{3d3}";
    const b = "He\u{301}llo World! \u{3a5}\u{301}";
    try expect(try case_fold.compatCaselessMatch(allocator, &n, a, b));

    const c = "He\u{301}llo World! \u{3d2}\u{301}";
    try expect(try case_fold.compatCaselessMatch(allocator, &n, a, c));

    // `canonCaselessMatch` isn't as comprehensive as `compatCaselessMatch`
    // because it only decomposes to NFD. Naturally, it's faster because of this.
    try expect(!try case_fold.canonCaselessMatch(allocator, &n, a, b));
    try expect(try case_fold.canonCaselessMatch(allocator, &n, a, c));
}
```
Case folding needs to use the `Normalize` module in order to produce the compatibility
forms for comparison.  If you are already using a `Normalize` for other purposes,
`CaseFolding` can borrow it:

```zig
const CaseFolding = @import("CaseFolding");
const Normalize = @import("Normalize");

test "Initialize With a Normalize" {
    const normalize = try Normalize.init(allocator);
    // You're responsible for freeing this:
    defer normalize.deinit(allocator);
    const case_fold = try CaseFolding.initWithNormalize(allocator, normalize);
    // This will not free your normalize when it runs first.
    defer case_fold.deinit(allocator);
}
```
This has a `setupWithNormalize` variant as well, note that this also takes
a `Normalize` struct, and not a pointer to it.


## Display Width of Characters and Strings

When displaying text with a fixed-width font on a terminal screen, it's very
important to know exactly how many columns or cells each character should take.
Most characters will use one column, but there are many, like emoji and East-
Asian ideographs that need more space. The `DisplayWidth` module provides
methods for this purpose. It also has methods that use the display width calculation
to `center`, `padLeft`, `padRight`, and `wrap` text.

In your `build.zig`:

```zig
exe.root_module.addImport("DisplayWidth", zg.module("DisplayWidth"));
```

In your code:

```zig
const DisplayWidth = @import("DisplayWidth");

test "Display width" {
    const dw = try DisplayWidth.init(allocator);
    defer dw.deinit(allocator);

    // String display width
    try expectEqual(@as(usize, 5), dw.strWidth("Hello\r\n"));
    try expectEqual(@as(usize, 8), dw.strWidth("Hello 😊"));
    try expectEqual(@as(usize, 8), dw.strWidth("Héllo 😊"));
    try expectEqual(@as(usize, 9), dw.strWidth("Ẓ̌á̲l͔̝̞̄̑͌g̖̘̘̔̔͢͞͝o̪̔T̢̙̫̈̍͞e̬͈͕͌̏͑x̺̍ṭ̓̓ͅ"));
    try expectEqual(@as(usize, 17), dw.strWidth("슬라바 우크라이나"));

    // Centering text
    const centered = try dw.center(allocator, "w😊w", 10, "-");
    defer allocator.free(centered);
    try expectEqualStrings("---w😊w---", centered);

    // Pad left
    const right_aligned = try dw.padLeft(allocator, "abc", 9, "*");
    defer allocator.free(right_aligned);
    try expectEqualStrings("******abc", right_aligned);

    // Pad right
    const left_aligned = try dw.padRight(allocator, "abc", 9, "*");
    defer allocator.free(left_aligned);
    try expectEqualStrings("abc******", left_aligned);

    // Wrap text
    const input = "The quick brown fox\r\njumped over the lazy dog!";
    const wrapped = try dw.wrap(allocator, input, 10, 3);
    defer allocator.free(wrapped);
    const want =
        \\The quick
        \\brown fox
        \\jumped
        \\over the
        \\lazy dog!
    ;
    try expectEqualStrings(want, wrapped);
}
```

This module has build options.  The first is `cjk`, which will consider [ambiguous characters](https://www.unicode.org/reports/tr11/tr11-6.html) as double-width.

To choose this option, add it to the dependency like so:

```zig
const zg = b.dependency("zg", .{
    .cjk = true,
});
```

The other options are `c0_width` and `c1_width`.  The standard behavior is to treat
C0 and C1 control codes as zero-width, except for delete and backspace, which are
-1 (the logic ensures that a `strWidth` is always at least 0).  If printing
control codes with replacement characters, it's necessary to assign these a width,
hence the options.  When provided these values must fit in an `i4`, this allows
for C1s to be printed as `\u{80}` if desired.

`DisplayWidth` uses the `Graphemes` module internally.  If you already have one,
it can be borrowed using `DisplayWidth.initWithGraphemes(allocator, graphemes)`
in the same fashion as shown for `CaseFolding` and `Normalize`.

## Scripts

Unicode categorizes code points by the Script in which they belong. A Script
collects letters and other symbols that belong to a particular writing system.
You can detect the Script for a code point with the `Scripts` module.

In your `build.zig`:

```zig
exe.root_module.addImport("Scripts", zg.module("Scripts"));
```

In your code:

```zig
const Scripts= @import("Scripts");

test "Scripts" {
    const scripts = try Scripts.init(allocator);
    defer scripts.deinit(allocator);

    // To see the full list of Scripts, look at the
    // `src/Scripts.zig` file. They are list in an enum.
    try expect(scripts.script('A') == .Latin);
    try expect(scripts.script('Ω') == .Greek);
    try expect(scripts.script('צ') == .Hebrew);
}
```

## Relation to Ziglyph

zg is a total re-write of some of the components of Ziglyph. The idea was to
reduce binary size and improve performance. These goals were achieved by using
trie-like data structures (inspired by [Ghostty's implementation](https://mitchellh.com/writing/ghostty-devlog-006))
instead of generated functions. Where Ziglyph uses a function call, zg uses an
array lookup, which is quite faster. In addition, all these data structures in
zg are loaded at runtime from compressed versions in the binary. This allows
for smaller binary sizes at the expense of increased memory
footprint at runtime.

Benchmarks demonstrate the above stated goals have been met:

```plain
Binary sizes =======

149K ziglyph_case
87K zg_case

275K ziglyph_caseless
168K zg_caseless

68K ziglyph_codepoint
68K zg_codepoint

101K ziglyph_grapheme
86K zg_grapheme

185K ziglyph_normalizer
152K zg_normalize

101K ziglyph_width
86K zg_width

Benchmarks ==========

Ziglyph toUpperStr/toLowerStr: result: 7911596, took: 80
Ziglyph isUpperStr/isLowerStr: result: 110959, took: 17
zg toUpperStr/toLowerStr: result: 7911596, took: 62
zg isUpperStr/isLowerStr: result: 110959, took: 7

Ziglyph Normalizer.eqlCaseless: result: 625, took: 500
zg CaseFold.canonCaselessMatch: result: 625, took: 385
zg CaseFold.compatCaselessMatch: result: 625, took: 593

Ziglyph CodePointIterator: result: 3769314, took: 2
zg CodePointIterator: result: 3769314, took: 3

Ziglyph GraphemeIterator: result: 3691806, took: 48
zg GraphemeIterator: result: 3691806, took: 16

Ziglyph Normalizer.nfkc: result: 3934162, took: 416
zg Normalize.nfkc: result: 3934162, took: 182

Ziglyph Normalizer.nfc: result: 3955798, took: 57
zg Normalize.nfc: result: 3955798, took: 28

Ziglyph Normalizer.nfkd: result: 4006398, took: 172
zg Normalize.nfkd: result: 4006398, took: 104

Ziglyph Normalizer.nfd: result: 4028034, took: 169
zg Normalize.nfd: result: 4028034, took: 104

Ziglyph Normalizer.eql: result: 625, took: 337
Zg Normalize.eql: result: 625, took: 53

Ziglyph display_width.strWidth: result: 3700914, took: 71
zg DisplayWidth.strWidth: result: 3700914, took: 24
```

These results were obtained on an M1 Mac with 16 GiB of RAM.

In contrast to Ziglyph, zg does not have:

- Word segmentation
- Sentence segmentation
- Collation

It's possible that any missing functionality will be added in future versions,
but only if enough demand is present in the community.