Expand description

A low level, performance oriented parser for save and game files from Paradox Development Studio titles (eg: Europa Universalis (EU4), Hearts of Iron (HOI4), and Crusader Kings (CK3), Imperator, Stellaris, and Victoria).

For an in-depth look at the Paradox Clausewitz format and the pitfalls that come trying to support all variations, consult the write-up. In short, it’s extremely difficult to write a robust and fast parser that abstracts over the format difference between games as well as differences between game patches. Jomini hits the sweet spot between flexibility while still being ergonomic.

Jomini is the cornerstone of the online EU4 save file analyzer. This library also powers the Paradox Game Converters and pdxu.

Features

  • ✔ Versatile: Handle both plaintext and binary encoded data
  • ✔ Fast: Parse data at 1 GB/s
  • ✔ Small: Compile with zero dependencies
  • ✔ Safe: Extensively fuzzed against potential malicious input
  • ✔ Ergonomic: Use serde-like macros to have parsing logic automatically implemented
  • ✔ Embeddable: Cross platform native apps, statically compiled services, or in the browser via WASM

Quick Start

Below is a demonstration on parsing plaintext data using jomini tools.

use jomini::{JominiDeserialize, TextDeserializer};

#[derive(JominiDeserialize, PartialEq, Debug)]
pub struct Model {
    human: bool,
    first: Option<u16>,
    #[jomini(alias = "forth")]
    fourth: u16,
    #[jomini(alias = "core", duplicated)]
    cores: Vec<String>,
    names: Vec<String>,
}

let data = br#"
    human = yes
    forth = 10
    core = "HAB"
    names = { "Johan" "Frederick" }
    core = FRA
"#;

let expected = Model {
    human: true,
    first: None,
    fourth: 10,
    cores: vec!["HAB".to_string(), "FRA".to_string()],
    names: vec!["Johan".to_string(), "Frederick".to_string()],
};

let actual: Model = TextDeserializer::from_windows1252_slice(data)?;
assert_eq!(actual, expected);

Binary Parsing

Parsing data encoded in the binary format is done in a similar fashion but with a couple extra steps for the caller to supply:

  • How text should be decoded (typically Windows-1252 or UTF-8)
  • How rational (floating point) numbers are decoded
  • How tokens, which are 16 bit integers that uniquely identify strings, are resolved

Implementors be warned, not only does each Paradox game have a different binary format, but the binary format can vary between patches!

Below is an example that defines a sample binary format and uses a hashmap token lookup.

use jomini::{BinaryDeserializer, BinaryFlavor, Encoding, JominiDeserialize, Windows1252Encoding};
use std::{borrow::Cow, collections::HashMap};

#[derive(JominiDeserialize, PartialEq, Debug)]
struct MyStruct {
    field1: String,
}

#[derive(Debug, Default)]
pub struct BinaryTestFlavor;

impl BinaryFlavor for BinaryTestFlavor {
    fn visit_f32(&self, data: [u8; 4]) -> f32 {
        f32::from_le_bytes(data)
    }

    fn visit_f64(&self, data: [u8; 8]) -> f64 {
        f64::from_le_bytes(data)
    }
}

impl Encoding for BinaryTestFlavor {
    fn decode<'a>(&self, data: &'a [u8]) -> Cow<'a, str> {
        Windows1252Encoding::decode(data)
    }
}

let data = [ 0x82, 0x2d, 0x01, 0x00, 0x0f, 0x00, 0x03, 0x00, 0x45, 0x4e, 0x47 ];

let mut map = HashMap::new();
map.insert(0x2d82, "field1");

let actual: MyStruct = BinaryDeserializer::builder_flavor(BinaryTestFlavor)
    .from_slice(&data[..], &map)?;
assert_eq!(actual, MyStruct { field1: "ENG".to_string() });

When done correctly, one can use the same structure to represent both the plaintext and binary data without any duplication.

One can configure the behavior when a token is unknown (ie: fail immediately or try to continue).

Caveats

Caller is responsible for:

  • Determining the correct format (text or binary) ahead of time
  • Stripping off any header that may be present (eg: EU4txt / EU4bin)
  • Providing the token resolver for the binary format
  • Providing the conversion to reconcile how, for example, a date may be encoded as an integer in the binary format, but as a string when in plaintext.

The Mid-level API

If the automatic deserialization via JominiDeserialize is too high level, there is a mid-level api where one can easily iterate through the parsed document and interrogate fields for their information.

use jomini::TextTape;

let data = b"name=aaa name=bbb core=123 name=ccc name=ddd";
let tape = TextTape::from_slice(data).unwrap();
let mut reader = tape.windows1252_reader();

while let Some((key, _op, value)) = reader.next_field() {
    println!("{:?}={:?}", key.read_str(), value.read_str().unwrap());
}

One Level Lower

At the lowest layer, one can interact with the raw data directly via TextTape and BinaryTape.

use jomini::{TextTape, TextToken, Scalar};

let data = b"foo=bar";

assert_eq!(
    TextTape::from_slice(&data[..])?.tokens(),
    &[
        TextToken::Unquoted(Scalar::new(b"foo")),
        TextToken::Unquoted(Scalar::new(b"bar")),
    ]
);

If one will only use TextTape and BinaryTape then jomini can be compiled without default features, resulting in a build without dependencies.

Write API

There are two targeted use cases for the write API. One is when a text tape is on hand. This is useful when one needs to reformat a document (note that comments are not preserved):

use jomini::{TextTape, TextWriterBuilder};

let tape = TextTape::from_slice(b"hello   = world")?;
let mut out: Vec<u8> = Vec::new();
let mut writer = TextWriterBuilder::new().from_writer(&mut out);
writer.write_tape(&tape)?;
assert_eq!(&out, b"hello=world\n");

The writer normalizes any formatting issues. The writer is not able to losslessly write all parsed documents, but these are limited to truly esoteric situations and hope to be resolved in future releases.

The other use case is geared more towards incremental writing that can be found in melters or those crafting documents by hand. These use cases need to manually drive the writer:

use jomini::TextWriterBuilder;
let mut out: Vec<u8> = Vec::new();
let mut writer = TextWriterBuilder::new().from_writer(&mut out);
writer.write_unquoted(b"hello")?;
writer.write_unquoted(b"world")?;
writer.write_unquoted(b"foo")?;
writer.write_unquoted(b"bar")?;
assert_eq!(&out, b"hello=world\nfoo=bar\n");

Modules

Common data structures used across games

Structs

A text reader that advances through a sequence of values

A structure to deserialize binary data into Rust values.

Build a tweaked binary deserializer

Houses the tape of tokens that is extracted from binary data

Customizes how the binary tape is parsed from data

A date error.

The default writer that will write floating point at full representation

A Serde deserialization error.

An error that can occur when processing data

A reader that will advance through an object

Extracted color info

A byte slice that represents a single value.

A text reader that wraps an underlying scalar value

A structure to deserialize text data into Rust values.

Houses the tape of tokens that is extracted from plaintext data

Write data in PDS format.

Construct a customized text writer

Decodes bytes according to the utf8 standard

A text reader for a text value

Decodes bytes according to the windows1252 code page

Enums

Represents any valid binary value

The type of a Serde deserialization error.

Specific type of error

Customize how the deserializer reacts when a token can’t be resolved

An operator token

All possible text reader variants

An error that can occur when converting a scalar into the requested type.

Represents a valid text value

Traits

Trait customizing decoding values from binary data

An encoding for interpreting byte data as UTF-8 text

Resolves binary 16bit tokens to field names

Customizes writer behavior at a field level

Derive Macros

Creates a serde compatible Deserialize implementation