dune VS zsv

If you are using the dune build system, add the tag(s) to your dune-project file's package stanza. E.g.:

One way to get around this is to modify the api/dune file with (include_subdirs qualified); this means that every subdirectory of api/ can be referenced by module namespacing and we don't have to write dune files for every route (or pages) folder. However, the OCaml LSP does not like it and red squiggles will show up in the editor (although the app with still compile without errors). Trying to develop the app knowing those red squiggles cannot be vanquished would drive me nuts, so instead of using (include_subdirs qualified) I just wrote dune files for every route (and page) which gets rid of the red squiggles.

2) Neither would having all source/targets specified, as that would entail listing them all in the dune file as wildcard rules is apparently still not a thing: https://github.com/ocaml/dune/issues/307

There is a small example on the dune home page: https://dune.build/

Dune (https://dune.build/) is the preeminent build tool for OCaml development. I don't love its input syntax (s-expressions), and I sometimes miss the ability to write high-level functions to reduce boilerplate (especially for unit tests), but it always gets the dependencies right, and it's fast. This is in stark contrast to some of my experiences with various other build systems, and I am super happy that the default option for OCaml build systems is so good.

It's still weird because dune's own site only makes Jane Street references: https://dune.build/.

ONE of the big benefits of OCaml is its powerful REPL (also called the toplevel), the interactive command-line utility where you can load modules, type in and execute code, and see its results. The modern REPL, utop, has powerful auto-completion and integration with the build system dune, which enables productive workflows like loading an entire project's libraries in the REPL and interactively exploring them.

If it could be tabular in nature, maybe convert to sqlite3 so you can make use of indexing, or CSV to make use of high-performance tools like xsv or zsv (the latter of which I'm an author).

https://github.com/BurntSushi/xsv

https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...

Parsing CSV doesn't have to be slow if you use something like xsv or zsv (https://github.com/liquidaty/zsv) (disclaimer: I'm an author). The speed of CSV parsers is fast enough that unless you are doing something ultra-trivial such as "count rows", your bottleneck will be elsewhere.

The benefits of CSV are:

- human readable

- does not need to be typed (sometimes, data in the raw such as date-formatted data is not amenable to typing without introducing a pre-processing layer that gets you further from the original data)

- accessible to anyone: you don't need to be a data person to dbl-click and open in Excel or similar

The main drawback is that if your data is already typed, CSV does not communicate what the type is. You can alleviate this through various approaches such as is described at https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql..., though I wouldn't disagree that if you can be assured that your starting data conforms to non-text data types, there are probably better formats than CSV.

The main benefit of Arrow, IMHO, is less as a format for transmitting / communicating but rather as a format for data at rest, that would benefit from having higher performance column-based read and compression

I wanted so much to use csvkit and all the features it had, but its horrendous performance made it unscalable and therefore the more I used it, the more technical debt I accumulated.

This was one of the reasons I wrote zsv (https://github.com/liquidaty/zsv). Maybe csvkit could incorporate the zsv engine and we could get the best of both worlds?

Examples (using majestic million csv):

---

}

```

This of course assumes that each line is a single record, so you'll need some preprocessing if your CSV might contain embedded line-ends. For the preprocessing, you can use something like the `2tsv` command of https://github.com/liquidaty/zsv (disclaimer: I'm its author), which converts CSV to TSV and replaces newline with \n.

You can also use something like `xsv split` (see https://lib.rs/crates/xsv) which frankly is probably your best option as of today (though zsv will be getting its own shard command soon)

Am looking for one-time help creating documentation (e.g. man pages, tutorials) for open source project (e.g. https://github.com/liquidaty/zsv) as well as product documentation for commercial products, but not enough need for a full-time job. Requires familiarity with, for lack of better term, data janitorial work, and preferably with methods of auto-generating documentation. Any suggestions as to forums or other ways to find folks who might fit the bill for ad-hoc or part-time work of this nature?

Nice work. I am a fan of tools like this and look forward to giving this a try.

However, in my first attempted query (version 3.1.6 on MacOS), I ran into significant performance limitations and more importantly, it did not give correct output.

In particular, running on a narrow table with 1mm rows (the same one used in the xsv examples) using the command "select country, count() from worldcitiespop_mil.csv group by country" takes 12 seconds just to get an incorrect error 'no such column: country'.

using sqlite3, it takes two seconds or so to load, and less than a second to run, and gives me the correct result.

Using https://github.com/liquidaty/zsv (disclaimer, I'm one of its authors), I get the correct results in 0.95 seconds with the one-liner `zsv sql 'select country, count() from data group by country' worldcitiespop_mil.csv`.

I look forward to trying it again sometime soon

All this banter arguing over CSV, JSON, sqlite seems unnecessary when you can just push format X through a pipe and get whichever format Y you want back out: https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...

(disclaimer: I'm one of the zsv authors)