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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
mcabbott Jun 2, 2022
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two more links
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Expand Up @@ -40,3 +40,20 @@ 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/), at least until Julia 1.8.
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.

* [CSVFiles.jl](https://github.com/queryverse/CSVFiles.jl) uses the [FileIO.jl](https://github.com/JuliaIO/FileIO.jl)'s `load` / `save` API,
but otherwise has similar goals. Like CSV.jl, it works with [Tables.jl](https://github.com/JuliaData/Tables.jl objects such as DataFrames.

* [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).
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DLMReader.jl is a great reference because it supports some more exotic parsing configurations if you need to get really custom.

Should this link say something like "exotic custom parsing"?


* [Pandas.jl](https://github.com/JuliaPy/Pandas.jl) wraps Python's [pandas](https://pandas.pydata.org) library (using [PyCall.jl](https://github.com/JuliaPy/PyCall.jl)).
This is a closer cousin of [DataFrames.jl](https://github.com/JuliaData/DataFrames.jl), but builds in the ability to read/write CSV files.