this post was submitted on 24 Jan 2026
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There exists a peculiar amnesia in software engineering regarding XML. Mention it in most circles and you will receive knowing smiles, dismissive waves, the sort of patronizing acknowledgment reserved for technologies deemed passé. "Oh, XML," they say, as if the very syllables carry the weight of obsolescence. "We use JSON now. Much cleaner."

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[–] unique_hemp@discuss.tchncs.de 6 points 15 hours ago (3 children)

CSV >>> JSON when dealing with large tabular data:

  1. Can be parsed row by row
  2. Does not repeat column names, more complicated (so slower) to parse

1 can be solved with JSONL, but 2 is unavoidable.

[–] entwine@programming.dev 1 points 4 minutes ago* (last edited 4 minutes ago)
{
    "columns": ["id", "name", "age"],
    "rows": [
        [1, "bob", 44], [2, "alice", 7], ...
    ]
}

There ya go, problem solved without the unparseable ambiguity of CSV

Please stop using CSV.

[–] flying_sheep@lemmy.ml 1 points 4 hours ago

No:

  • CSV isn't good for anything unless you exactly specify the dialect. CSV is unstandardized, so you can't parse arbitrary CSV files correctly.
  • you don't have to serialize tables to JSON in the “list of named records” format

Just user Zarr or so for array data. A table with more than 200 rows isn't ”human readable” anyway.

[–] abruptly8951@lemmy.world 1 points 11 hours ago (1 children)

Yes..but compression

And with csv you just gotta pray that you're parser parses the same as their writer..and that their writer was correctly implemented..and they set the settings correctly

[–] unique_hemp@discuss.tchncs.de 1 points 5 hours ago (1 children)

Compression adds another layer of complexity for parsing.

JSON can also have configuration mismatch problems. Main one that comes to mind is case (in)sensitivity for keys.

[–] abruptly8951@lemmy.world 1 points 5 hours ago

Nahh your nitpicking there, large csvs are gonna be compressed anyways

In practice I've never met a Json I cant parse, every second csv is unparseable