FortniteReplayDecompressor
nom
| FortniteReplayDecompressor | nom | |
|---|---|---|
| 2 | 85 | |
| 90 | 9,020 | |
| - | 0.9% | |
| 5.4 | 7.4 | |
| about 1 month ago | 10 days ago | |
| C# | Rust | |
| MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
FortniteReplayDecompressor
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Kaitai Struct: A new way to develop parsers for binary structures
https://fortnitereplaydecompressor.readthedocs.io/en/latest/...
Unreal engine encode the network packet like it's a BitStream, when it want to write a boolean for example, it will write a single bit. The following integer won't be aligned.
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Competitive analytics?
The main entry-point is Github: Shiqan/FortniteReplayDecompressor and there is a link to the Discord he runs which is where a lot of the people doing this research are.
nom
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Planespotting with Rust: using nom to parse ADS-B messages
Just in case you are not familiar with nom, it is a parser combinator written in Rust. The most basic thing you can do with it is import one of its parsing functions, give it some byte or string input and then get a Result as output with the parsed value and the rest of the input or an error if the parser failed. tag for example is used to recognize literal character/byte sequences.
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Show HN: Rust nom parsing Starcraft2 Replays into Arrow for Polars data analysis
I may be the only one not familiar, but nom refers to https://github.com/rust-bakery/nom which looks like a pretty handy way to parse binary data in Rust.
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Is this a good way to free up some memory?
Lots of people use nom for their parsing needs, but that's not the only game in town and there other options.
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What is the state of the art for creating domain-specific languages (DSLs) with Rust?
As much as I love nom as well as other parser combinator libraries, regex-based parsers, BNF/EBNF-based parsers, etc. I always end up going back to plain old text-based char-by-char scanners.
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What's everyone working on this week (22/2023)?
I am using nom / nom_locate to build the parser side because I've done a handful of other projects with it, and I plan to use tower-lsp to hook up the language server side.
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Tokenizing
Look into a parsing library such as https://github.com/rust-bakery/nom
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Something like pydantic but for just strings?
If we were in /r/learnrust I'd have recommended the nom crate for this.
- Nom: Parser Combinators Library in Rust
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lua bytecode parser written in rust
Thanks to the flexibility of [nom](https://github.com/rust-bakery/nom), it is very easy to write your own parser in rust, read [this article](https://github.com/metaworm/luac-parser-rs/wiki/Write-custom-luac-parser) to learn how to write a luac parser
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Should I revisit my choice to use nom?
I've been working on an assembler and right now it uses nom. While nom isn't great for error messages, good error messages will be important for this particular assembler (current code), so I've been attempting to use the methods described by Eyal Kalderon in Error recovery with parser combinators (using nom).
What are some alternatives?
Galaxy-Swapper-v2 - Revamp your Fortnite experience with our skin swapper designed for the latest version of Fortnite.
pest - The Elegant Parser
Unreal-Binary-Builder - An application designed to create installed Unreal Engine builds (aka Rocket builds) from Unreal Engine GitHub source.
lalrpop - LR(1) parser generator for Rust
LeapUnrealModules - Leap Motion Unreal modules and example content.
combine - A parser combinator library for Rust
fortnite-replay-reader - Fortnites favorite assistent is here to help you parse replay files
pom - PEG parser combinators using operator overloading without macros.
binrw - A Rust crate for helping parse and rebuild binary data using ✨macro magic✨.
rust-peg - Parsing Expression Grammar (PEG) parser generator for Rust
smm2-documentation - Documentation for the game Super Mario Maker 2.
chumsky - Write expressive, high-performance parsers with ease.