require 'csv'

CSV

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 = CSV.new(string_or_io, **options)

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

Reading

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

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

Writing

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

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

Shortcuts

# 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)
  Name,Department,Salary
  Bob,Engineering,1000
  Jane,Sales,2000
  John,Management,5000
ROWS

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:
CSV.parse('Bob,2018-03-01,100')
#=> [["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 Reference