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Why the CSV standard library is broken, broken, broken (and how to fix it), Part IV or Numerics a.k.a. Auto-Magic Type Inference for Strings and Numbers

What's broken (and wrong, wrong, wrong) with the CSV standard library? Let's count the ways.

Start with the (complete) series:

What about Numerics and Comma-Separated Values (CSV)?

Let's read data.csv:


What do you expect?

pp 'data.csv' )


[["1", "2", "3"],
 ["4", "5", "6"]]

That's great. At it's most basic a comma-separated values record once read in / parsed is always a list of string values. Period.

What about Numbers?

You can use the converters keyword option to (auto-)convert strings to nulls, booleans, dates, and, yes, integers and floats. Built-in converters include:

Converter Comments
:integer convert matching strings to integer
:float convert matching strings to float
:numeric shortcut for [:integer, :float]


records = 'data.csv', :converters => :numeric )
pp records
# => [[1, 2, 3],
#     [4, 5, 6]]

That's great again. Using type inference and data converters turns a comma-separated values record into a list of numbers.

Numbers and Strings Together - How? Possible?

Guess, what? There's a popular comma-separated values (CSV) convention / variant / dialect:

Rule 1: Use "un-quoted" values for float numbers e.g. 1,2,3 or 1.0, 2.0, 3.0 etc.

Rule 2: Use quoted values for "non-numeric" strings e.g. "4", "5", "6" or "Hello, World!" etc.

Now - try to read this format with the standard CSV library in ruby. Anyone? Sorry, it's impossible - why? how?

Oh no! Yes, - surprise, surprise - the CSV standard library is broken, broken, broken again. The built-in (or your own custom converters) only get the value (and the field position) but NOT if the value was quoted or un-quoted.

Let's fix it. Use a purpose built-parser that includes support for numerics (like the Python standard library or panda's read_csv and many others). What about ruby :-)?


require 'csv'


require 'csvreader'

And now try:

records = 'data.csv' )   # or
pp records
# => [[1.0, 2.0, 3.0],
#     ["4", "5", "6"]]

Voila! The new alternative csv reader library has built-in support for the numerics convention / variant / dialect. Note: By convention all (auto-converted) numbers are floats. What else?

What about Not A Number (NaN)?

The reader also lets you configure a list of values that get auto-converted to Float::NAN, that is, Not A Number (NaN). Example:

records = Csv.numeric.parse( '1,2,NAN,#NAN', nan: ['NAN', '#NAN'] )
pp records
# => [[1.0, 2.0, NaN, NaN]]

Note: The Not a Number (NaN) values are "un-quoted" values (like numbers) in the comma-separated values (CSV) format.

What's the point? The standard library is broken and too simplistic. A string#split kludge for "parsing" is a joke. Only "real" purpose built parsers work for handling all the edge case such as Not A Number (NaN) in "un-quoted" values for the numerics dialect / variant / format.

I disagree that it's broken. It's implementing the [strict] RFC [CSV format] and gives you the tools that allow you to be less strict.

Anyone? Show us how you handle the reading of the numerics variant and Not a Number (NaN) with the standard csv library?

Have you read the [strict] RFC 4180 [CSV format memo]? The quoting rules are in there.

What about numerics or Not a Number (NaN)? The numerics rules are NOT in there, sorry.

Innovate, Innovate, Innovate - CSV <3 JSON

Believe it or not? CSV the world's #1 and most popular data format is alive and kicking.

What's next for CSV? CSV <3 JSON and much more. Stay tuned for the next episode.

Questions? Comments?

Please post your questions or comments to the ruby-talk mailing list thread or in the reddit ruby discussion thread.