Kaitai Struct
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Kaitai Struct | nom | |
---|---|---|
44 | 85 | |
3,797 | 8,943 | |
1.4% | 1.6% | |
7.5 | 6.5 | |
6 days ago | 24 days ago | |
Shell | Rust | |
GPL-3.0-or-later | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Kaitai Struct
- Reverse-engineering an encrypted IoT protocol
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Parsing an Undocumented File Format
- ImHex [2], which has a pattern language [3] which allows parsing, and it seems more powerful than what Kaitai offers. I stumbled upon some limitations with it but it was still useful.
[1]: https://kaitai.io/
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HTTPie Desktop: cross-platform API testing client for humans
Beautiful. Didn't know something like this exists. Reminds me of Katai[0]
[0]. https://kaitai.io/
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Hacking the LG Monitor's EDID
An EDID override like this would be helpful for macOS as well, where the monitors swapping around after standby is a real annoyance [0] [1]
EDID rewrites are 99% of the time blocked by the monitor firmware: https://notes.alinpanaitiu.com/Decoding-monitor-EDID-on-macO...
By the way, one helpful tool that helped me navigate the EDID dump was Kaitai Struct [2]. It shows a side by side view with the hex view and the EDID structure, and it highlights the hex values in real time as you navigate the structure. Unfortunately [3] it doesn't support the extension blocks that the author needs.
[0] https://notes.alinpanaitiu.com/Weird-monitor-bugs
[1] https://forums.macrumors.com/threads/external-displays-swapp...
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Fq: Jq for Binary Formats
Kaitai Struct might be a good choice for that: https://kaitai.io/
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Ingesting, parsing and making sense of device log data
For binary log format, there's the excellent Kaitai Struct frameworks, that make it very easy to generate parsers from a declarative schema
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What is this tool? More info in comments
kaitai
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GNU poke: The extensible editor for structured binary data
* Kaitai Struct - https://kaitai.io/
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Please Review My Metalanguage
Have you seen this? https://kaitai.io/
(Disclaimer: I've never needed or used it, but stumbled upon it a while back and just filed it away for future reference)
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What projects are you working on or planning to do this year?
Speaking of reading binary data, later I found Kaitai Struct. You can write file format in YAML, then it would transpile it to different programming languages. Highly recommend it if all you need is to read (it can not serialize data back to binary). There's even a web IDE to play with files, which is quite fun.
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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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).
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winnow = toml_edit + combine + nom
On my side, nom is still advancing well and a new major version is in preparation, with some interesting work a new GAT based design inspired from the awesome work on chumsky, that promises to bring great performance with complex error types. 2023 will be fun for parser libraries!
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Question about lexer and parser generators in Rust
Checkout https://github.com/zesterer/chumsky or https://github.com/rust-bakery/nom
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Writing a parser in Rust
I recently did a parsing project - I used the nom crate which is a functional/combinatorial style parser. Here's a really good video about the technique: https://www.youtube.com/watch?v=dDtZLm7HIJs
What are some alternatives?
pest - The Elegant Parser
lalrpop - LR(1) parser generator for Rust
combine - A parser combinator library for Rust
pom - PEG parser combinators using operator overloading without macros.
rust-peg - Parsing Expression Grammar (PEG) parser generator for Rust
chumsky - Write expressive, high-performance parsers with ease.
Protobuf - Protocol Buffers - Google's data interchange format
chomp - A fast monadic-style parser combinator designed to work on stable Rust.
csvkit - A suite of utilities for converting to and working with CSV, the king of tabular file formats.
serde - Serialization framework for Rust
Camelot - A Python library to extract tabular data from PDFs
tablib - Python Module for Tabular Datasets in XLS, CSV, JSON, YAML, &c.