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Add links to alternatives to the readme #1006

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merged 6 commits into from Aug 27, 2022
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Add links to alternatives to the readme #1006

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add alternatives to readme
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Expand Up @@ -40,3 +40,19 @@ Contributions are very welcome, as are feature requests and suggestions. Please
[codecov-url]: https://codecov.io/gh/JuliaData/CSV.jl

[issues-url]: https://github.com/JuliaData/CSV.jl/issues

## Alternatives

There are several other packages for reading CSV files in Julia, which may suit your needs better:

* The standard library contains [DelimitedFiles.jl](https://docs.julialang.org/en/v1/stdlib/DelimitedFiles/),
which is perfect for quickly reading small files.
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Note that it returns Arrays, so for this to be perfect, your DelimitedFiles should probably be homogenous w/ respect to types, otherwise you'll get an Matrix{Any}, which I wouldn't call perfect, even for small files.

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@mcabbott mcabbott Jun 2, 2022 •
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Good point. Maybe something like this:

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* The standard library contains [DelimitedFiles.jl](https://docs.julialang.org/en/v1/stdlib/DelimitedFiles/),
which is perfect for quickly reading small files.
* The standard library contains [DelimitedFiles.jl](https://docs.julialang.org/en/v1/stdlib/DelimitedFiles/).
This returns a `Matrix` rather than a [Tables.jl](https://github.com/JuliaData/Tables.jl)-style container, thus works best for files of homogenous element type.
On large files, CSV.jl will be much faster.

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A couple more notes:

CSV doesn't return a DataFrame by default, it returns a CSV.File, so we should be careful not to imply it does

DelimitedFiles won't be a stdlib in upcoming Julia versions, I think

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Looks good.

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Clearly I shouldn't be writing this... see what you think, DataFrames -> Tables.jl now.

And, I hadn't seen, but JuliaLang/julia#44663 is the proposal to remove. But it will surely be a while, and the package will probably remain the right choice for reading 10 lines.

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DelimitedFiles won't be a stdlib in upcoming Julia versions

Well that's slightly horrifying


* [CSVFiles.jl](https://github.com/queryverse/CSVFiles.jl) uses the [FileIO.jl](https://github.com/JuliaIO/FileIO.jl) API
into any [IterableTables.jl](https://github.com/queryverse/IterableTables.jl) sink.
The package uses [TextParse.jl](https://github.com/queryverse/TextParse.jl) for parsing.
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* [DLMReader.jl](https://github.com/sl-solution/DLMReader.jl) also aims to be fast for large files.
Closely associated with [InMemoryDatasets.jl](https://github.com/sl-solution/InMemoryDatasets.jl) rather than [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl)

* [Pandas.jl](https://github.com/JuliaPy/Pandas.jl) wraps Python's pandas library, via PyCall.jl.