Do you have the Gemini:// URL? I’m getting a URL resolution error.

Given that the author mentions CSV and text table formats, the article's list of the "entire Unix toolchain" is significantly impoverished not only by the lack of ex (which is usefully scriptable) but by the lack of mlr.

* https://miller.readthedocs.io/

vis/unvis are fairly important tools for those text tables, too.

Also, FediVerse discussion: https://social.pollux.casa/@adele/statuses/01K1VA9NQSST4KDZP...

> Unlike binary formats or database dumps, these files don't hide their meaning behind layers of abstraction. They're built for clarity, for resilience, and for people who like to know what's going on under the hood.

Csv files hide their meaning in external documentation or someone’s head, are extremely unclear in many cases (is this a number or a string? A date?) and is extremely fragile when it comes to people editing them in text editors. They entirely lack checks and verification at the most basic level and worse still they’re often but not always perfectly line based. Many tools then work fine until they completely break you file and you won’t even know. Until I get the file and tell you I guess.

I’ve spent years fixing issues introduced by people editing them like they’re text.

If you’ve got to use tools to not completely bugger them then you might as well use a good format.

Clearly there’s a very real need for binary data formats, or we wouldn’t have them. For one, it’s much more space efficient. Does the author know how much storage cost in 1985? Or how slow computers were?

If I time traveled back to 1985 and told corporate to adopt CSV because it’d be useful in 50 years when unearthing old customer records I’d be laughed out of the cigar lounge.

I journeyed from fancy commercial bookkeeping systems that changed data formats every few years (with no useful migration) to GNU Cash and finally to Plain-Text Accounting. I can finally get the information I need with easy backups (through VCS) and flexibility (through various tools that transform the data). The focus is on content, not tools or presentation or product.

When I write I write text. I can transform text using various tools to provide various presentations consumable through various products. The focus is on content, not presentation, tools, or product.

I prefer human-readable file formats, and that has only been reinforced over more than 4 decades as a computer professional.

I concur with most of these arguments, especially about longevity. But, this only applies to smallish files like configurations because I don't agree with the last paragraph regarding its efficiency.

I have had to work with large 1GB+ JSON files, and it is not fun. Amazing projects such as jsoncons for streaming JSONs, and simdjson, for parsing JSON with SIMD, exist, but as far as I know, the latter still does not support streaming and even has an open issue for files larger than 4 GiB. So you cannot have streaming for memory efficiency and SIMD-parsing for computational efficiency at the same time. You want streaming because holding the whole JSON in memory is wasteful and sometimes not even possible. JSONL tries to change the format to fix that, but now you have another format that you need to support.

I was also contemplating the mentioned formats for another project, but they are hardly usable when you need to store binary data, such as images, compressed data, or simply arbitrary data. Storing binary data as base64 strings seems wasteful. Random access into these files is also an issue, depending on the use case. Sometimes it would be a nice feature to jump over some data, but for JSON, you cannot do that without parsing everything in search of the closing bracket or quotes, accounting for escaped brackets and quotes, and nesting.

I can understand this for "small" data, say less than 10 Mb.

In bioinformatics, basically all of the file formats are human-readable/text based. And file sizes range between 1-2Mb and 1 Tb. I regularly encounter 300-600 Gb files.

In this context, human-readable files are ridiculously inefficient, on every axis you can think of (space, parsing, searching, processing, etc.). It's a GD crime against efficiency.

And at that scale, "readable" has no value, since it would take you longer to read the file than 10 lifetimes.

I'll take sexprs over CSV/JSON/YAML/XML any day.

Lets hear it for RTF for documents

Are there any binary formats that include the specification in the format itself?

Readable files are great… until they’re 1TB and you just want to cry.

I'm not sure the author knows much about binary formats.

Binary formats are binary for a reason. Speed of interpretation is one reason. Usage of memory is another reason. Directly mapping it and using it, is another reason. Binary formats can make assumptions about system memory page size. They can store internal offsets to make incremental reading faster. None of this is offered by text formats.

Also, the ability to modify text formats is completely wrong. Nothing can be changed if we introduce checksums inside text formats. Also if we digitally sign a format, then nothing can be changed despite the fact that it's a text format.

Also, comparing CSV files to internal database binary format? It's like comparing a book cover to the ERP system of a library. Meaning, it's comparing two completely different things.

Let’s say that hypothetically one were to disagree with this. What would be the best alternative format? One that has ample of tooling for editing and diffing, as though it was text, yet stores things more efficiently.

Most of the arguments presented in TFA are about openness, which can still be achieved with standard binary formats and a schema. Hence the problem left to solve is accessibility.

I’m thinking something like parquet, protobuf or sqllite. Despite their popularities, still aren’t trivial for anyone to edit.

Human-readability was one of the aspects that I enjoyed about using CCL,the Categorical Configuration Language (https://chshersh.com/blog/2025-01-06-the-most-elegant-config...), in one of my projects recently.

It saves you from escaping stuff inside of multiline-strings by using meaningful whitespace.

What I did not like about CCL so much that it leaves a bunch of stuff underspecified. You can make lists and comments with it, but YOU have to decide how.

Even "human-readable" formats are only readable if you have proper tools - i.e. editors or viewers.

If a binary file has a well-known format and tools available to view/edit it, I see zero problems with it.

Ease of: reading, comprehension, manipulation, short- and long-term retrieval are not the same problems. All file formats are bad at at least one of these.

Given an arbitrary stream of bytes, readability only means the human can inspect the file. We say "text is readable" but that's really only because all our tooling for the last sixty years speaks ASCII and we're very US-centric. Pick up a text file from 1982 and it could be unreadable (EBCDIC, say). Time to break out dd and cross your fingers.

Comprehension breaks down very quickly beyond a few thousand words. No geneticist is loading up a gig of CTAGT... and keeping that in their head as they whiz up and down a genome. Humans have a working set size.

Short term retrieval is excellent for text and a PITA for everything else. Raise your hand if you've gotten a stream of bytes, thrown file(1) at it, then strings(1), and then resorted to od or picking through the bytes.

Long term retrieval sucks for everyone. Even textfiles. After all, a string of bytes has no intrinsic meaning except what the operating system and the application give it. So who knows if people in 2075 will recognise "48 65 6C 6C 6F 20 48 4E 21"?

You want JARs to be human-readable? PNGs? MP3s?

I think the author is thinking about a very narrow set of files.

We learned the hard way, for some of us it's all too easy to make careless design errors that become baked-in and can't be fixed in a backward-compatible way (either at the DSL or API level). An example in Graphviz is its handling of backslash in string literals: to escape special characters (like quotes \"), to map special characters (like several flavors of newline with optional justification \n \l \r) and to indicate variables (like node names in labels \N) along with magic code that knows that if the -default- node name is the empty string that actually means \N but if a particular node name is the empty string, then it stays.

There was a published study, Wrangling Messy CSV Files by Detecting Row and Type Patterns by Gerrit J. J. van den Burg, Alfredo Nazábal, and Charles Sutton (Data Mining and Knowledge Discovery, 2019) that showed many pitfalls with parsing CSV files found on GitHub. They achieved 97%. It's easy to write code that slings out some text fields separated by commas, with the objective of using a human-readable portable format.

You can learn even more by allowing autofuzz to test your nice simple code to parse human readable files.

It’s not about human-readable, it’s about standard format & available tooling to read for it. Be it .txt or json or yaml; standard format & tooling; digital content anyways isn’t human readable either digital interface.

/* Technically, most binary formats are legible to a human, given a proper renderer, e.g. journalctl. What TFA speaks about is ASCII/UTF-8 text formats that need no processing besides rendering CR, LF, and TAB characters specially. Assuming a Unix command line, I would call these "cat-readable" formats, or maybe even "less-readable". */