This class provides a complete interface to CSV files and data. It offers tools to enable you to read and write to and from Strings or IO objects, as needed.

The most generic interface of the library is:

csv =, **options)

# Reading: IO object should be open for read # => array of rows
# or
csv.each do |row|
  # ...
# or
row = csv.shift

# Writing: IO object should be open for write
csv << row

There are several specialized class methods for one-statement reading or writing, described in the Specialized Methods section.

If a String is passed into ::new, it is internally wrapped into a StringIO object.

options can be used for specifying the particular CSV flavor (column separators, row separators, value quoting and so on), and for data conversion, see Data Conversion section for the description of the latter.

Specialized Methods


# From a file: all at once
arr_of_rows ="path/to/file.csv", **options)
# iterator-style:
CSV.foreach("path/to/file.csv", **options) do |row|
  # ...

# From a string
arr_of_rows = CSV.parse("CSV,data,String", **options)
# or
CSV.parse("CSV,data,String", **options) do |row|
  # ...


# To a file"path/to/file.csv", "wb") do |csv|
  csv << ["row", "of", "CSV", "data"]
  csv << ["another", "row"]
  # ...

# To a String
csv_string = CSV.generate do |csv|
  csv << ["row", "of", "CSV", "data"]
  csv << ["another", "row"]
  # ...


# Core extensions for converting one line
csv_string = ["CSV", "data"].to_csv   # to CSV
csv_array  = "CSV,String".parse_csv   # from CSV

# CSV() method
CSV             { |csv_out| csv_out << %w{my data here} }  # to $stdout
CSV(csv = "")   { |csv_str| csv_str << %w{my data here} }  # to a String
CSV($stderr)    { |csv_err| csv_err << %w{my data here} }  # to $stderr
CSV($stdin)     { |csv_in|  csv_in.each { |row| p row } }  # from $stdin

Data Conversion

CSV with headers

CSV allows to specify column names of CSV file, whether they are in data, or provided separately. If headers specified, reading methods return an instance of CSV::Table, consisting of CSV::Row.

# Headers are part of data
data = CSV.parse(<<~ROWS, headers: true)

data.class      #=> CSV::Table
data.first      #=> #<CSV::Row "Name":"Bob" "Department":"Engineering" "Salary":"1000">
data.first.to_h #=> {"Name"=>"Bob", "Department"=>"Engineering", "Salary"=>"1000"}

# Headers provided by developer
data = CSV.parse('Bob,Engeneering,1000', headers: %i[name department salary])
data.first      #=> #<CSV::Row name:"Bob" department:"Engineering" salary:"1000">

Typed data reading

CSV allows to provide a set of data converters e.g. transformations to try on input data. Converter could be a symbol from CSV::Converters constant’s keys, or lambda.

# Without any converters:
#=> [["Bob", "2018-03-01", "100"]]

# With built-in converters:
CSV.parse('Bob,2018-03-01,100', converters: %i[numeric date])
#=> [["Bob", #<Date: 2018-03-01>, 100]]

# With custom converters:
CSV.parse('Bob,2018-03-01,100', converters: [->(v) { Time.parse(v) rescue v }])
#=> [["Bob", 2018-03-01 00:00:00 +0200, "100"]]

CSV and Character Encodings (M17n or Multilingualization)

This new CSV parser is m17n savvy. The parser works in the Encoding of the IO or String object being read from or written to. Your data is never transcoded (unless you ask Ruby to transcode it for you) and will literally be parsed in the Encoding it is in. Thus CSV will return Arrays or Rows of Strings in the Encoding of your data. This is accomplished by transcoding the parser itself into your Encoding.

Some transcoding must take place, of course, to accomplish this multiencoding support. For example, :col_sep, :row_sep, and :quote_char must be transcoded to match your data. Hopefully this makes the entire process feel transparent, since CSV’s defaults should just magically work for your data. However, you can set these values manually in the target Encoding to avoid the translation.

It’s also important to note that while all of CSV’s core parser is now Encoding agnostic, some features are not. For example, the built-in converters will try to transcode data to UTF-8 before making conversions. Again, you can provide custom converters that are aware of your Encodings to avoid this translation. It’s just too hard for me to support native conversions in all of Ruby’s Encodings.

Anyway, the practical side of this is simple: make sure IO and String objects passed into CSV have the proper Encoding set and everything should just work. CSV methods that allow you to open IO objects (CSV::foreach(), CSV::open(), CSV::read(), and CSV::readlines()) do allow you to specify the Encoding.

One minor exception comes when generating CSV into a String with an Encoding that is not ASCII compatible. There’s no existing data for CSV to use to prepare itself and thus you will probably need to manually specify the desired Encoding for most of those cases. It will try to guess using the fields in a row of output though, when using CSV::generate_line() or Array#to_csv().

I try to point out any other Encoding issues in the documentation of methods as they come up.

This has been tested to the best of my ability with all non-“dummy” Encodings Ruby ships with. However, it is brave new code and may have some bugs. Please feel free to report any issues you find with it.

frozen_string_literal: true

frozen_string_literal: true


VERSION = "3.0.9"

DEFAULT_OPTIONS = { col_sep: ",", row_sep: :auto, quote_char: '"', field_size_limit: nil, converters: nil, unconverted_fields: nil, headers: false, return_headers: false, header_converters: nil, skip_blanks: false, force_quotes: false, skip_lines: nil, liberal_parsing: false, quote_empty: true, }.freeze

HeaderConverters = { downcase: lambda { |h| h.encode(ConverterEncoding).downcase }, symbol: lambda { |h| h.encode(ConverterEncoding).downcase.gsub(/[^\s\w]+/, "").strip. gsub(/\s+/, "_").to_sym } }

Converters = { integer: lambda { |f| Integer(f.encode(ConverterEncoding)) rescue f }, float: lambda { |f| Float(f.encode(ConverterEncoding)) rescue f }, numeric: [:integer, :float], date: lambda { |f| begin e = f.encode(ConverterEncoding) e.match?(DateMatcher) ? Date.parse(e) : f rescue # encoding conversion or date parse errors f end }, date_time: lambda { |f| begin e = f.encode(ConverterEncoding) e.match?(DateTimeMatcher) ? DateTime.parse(e) : f rescue # encoding conversion or date parse errors f end }, all: [:date_time, :numeric], }

ConverterEncoding = Encoding.find("UTF-8")

DateTimeMatcher = / \A(?: (\w+,?\s+)?\w+\s+\d{1,2}\s+\d{1,2}:\d{1,2}:\d{1,2},?\s+\d{2,4} | \d{4}-\d{2}-\d{2}\s\d{2}:\d{2}:\d{2} | # ISO-8601 \d{4}-\d{2}-\d{2} (?:T\d{2}:\d{2}(?::\d{2}(?:\.\d+)?(?:[+-]\d{2}(?::\d{2})|Z)?)?)? )\z /x

DateMatcher = / \A(?: (\w+,?\s+)?\w+\s+\d{1,2},?\s+\d{2,4} | \d{4}-\d{2}-\d{2} )\z /x

FieldInfo =, :line, :header)


[R] encoding

The Encoding CSV is parsing or writing in. This will be the Encoding you receive parsed data in and/or the Encoding data will be written in.

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