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Recipes for Parsing CSV ↑

For other recipes, see Recipes for CSV.

All code snippets on this page assume that the following has been executed:

require 'csv'

Contents ↑

Source Formats ↑

You can parse CSV data from a String, from a File (via its path), or from an IO stream.

Parsing from a String ↑

You can parse CSV data from a String, with or without headers.

Recipe: Parse from String with Headers ↑

Use class method CSV.parse with option headers to read a source String all at once (may have memory resource implications):

string = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
CSV.parse(string, headers: true) # => #<CSV::Table mode:col_or_row row_count:4>

Use instance method CSV#each with option headers to read a source String one row at a time:

CSV.new(string, headers: true).each do |row|
  p row
end

Output:

#<CSV::Row "Name":"foo" "Value":"0">
#<CSV::Row "Name":"bar" "Value":"1">
#<CSV::Row "Name":"baz" "Value":"2">
Recipe: Parse from String Without Headers ↑

Use class method CSV.parse without option headers to read a source String all at once (may have memory resource implications):

string = "foo,0\nbar,1\nbaz,2\n"
CSV.parse(string) # => [["foo", "0"], ["bar", "1"], ["baz", "2"]]

Use instance method CSV#each without option headers to read a source String one row at a time:

CSV.new(string).each do |row|
  p row
end

Output:

["foo", "0"]
["bar", "1"]
["baz", "2"]

Parsing from a File ↑

You can parse CSV data from a File, with or without headers.

Recipe: Parse from File with Headers ↑

Use instance method CSV#read with option headers to read a file all at once:

string = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
path = 't.csv'
File.write(path, string)
CSV.read(path, headers: true) # => #<CSV::Table mode:col_or_row row_count:4>

Use class method CSV.foreach with option headers to read one row at a time:

CSV.foreach(path, headers: true) do |row|
  p row
end

Output:

#<CSV::Row "Name":"foo" "Value":"0">
#<CSV::Row "Name":"bar" "Value":"1">
#<CSV::Row "Name":"baz" "Value":"2">
Recipe: Parse from File Without Headers ↑

Use class method CSV.read without option headers to read a file all at once:

string = "foo,0\nbar,1\nbaz,2\n"
path = 't.csv'
File.write(path, string)
CSV.read(path) # => [["foo", "0"], ["bar", "1"], ["baz", "2"]]

Use class method CSV.foreach without option headers to read one row at a time:

CSV.foreach(path) do |row|
  p row
end

Output:

["foo", "0"]
["bar", "1"]
["baz", "2"]

Parsing from an IO Stream ↑

You can parse CSV data from an IO stream, with or without headers.

Recipe: Parse from IO Stream with Headers ↑

Use class method CSV.parse with option headers to read an IO stream all at once:

string = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
path = 't.csv'
File.write(path, string)
File.open(path) do |file|
  CSV.parse(file, headers: true)
end # => #<CSV::Table mode:col_or_row row_count:4>

Use class method CSV.foreach with option headers to read one row at a time:

File.open(path) do |file|
  CSV.foreach(file, headers: true) do |row|
    p row
  end
end

Output:

#<CSV::Row "Name":"foo" "Value":"0">
#<CSV::Row "Name":"bar" "Value":"1">
#<CSV::Row "Name":"baz" "Value":"2">
Recipe: Parse from IO Stream Without Headers ↑

Use class method CSV.parse without option headers to read an IO stream all at once:

string = "foo,0\nbar,1\nbaz,2\n"
path = 't.csv'
File.write(path, string)
File.open(path) do |file|
  CSV.parse(file)
end # => [["foo", "0"], ["bar", "1"], ["baz", "2"]]

Use class method CSV.foreach without option headers to read one row at a time:

File.open(path) do |file|
  CSV.foreach(file) do |row|
    p row
  end
end

Output:

["foo", "0"]
["bar", "1"]
["baz", "2"]

RFC 4180 Compliance ↑

By default, CSV parses data that is compliant with RFC 4180 with respect to:

Row Separator ↑

RFC 4180 specifies the row separator CRLF (Ruby "\r\n").

Although the CSV default row separator is "\n", the parser also by default handles row separator "\r" and the RFC-compliant "\r\n".

Recipe: Handle Compliant Row Separator ↑

For strict compliance, use option :row_sep to specify row separator "\r\n", which allows the compliant row separator:

source = "foo,1\r\nbar,1\r\nbaz,2\r\n"
CSV.parse(source, row_sep: "\r\n") # => [["foo", "1"], ["bar", "1"], ["baz", "2"]]

But rejects other row separators:

source = "foo,1\nbar,1\nbaz,2\n"
CSV.parse(source, row_sep: "\r\n") # Raised MalformedCSVError
source = "foo,1\rbar,1\rbaz,2\r"
CSV.parse(source, row_sep: "\r\n") # Raised MalformedCSVError
source = "foo,1\n\rbar,1\n\rbaz,2\n\r"
CSV.parse(source, row_sep: "\r\n") # Raised MalformedCSVError
Recipe: Handle Non-Compliant Row Separator ↑

For data with non-compliant row separators, use option :row_sep. This example source uses semicolon (";") as its row separator:

source = "foo,1;bar,1;baz,2;"
CSV.parse(source, row_sep: ';') # => [["foo", "1"], ["bar", "1"], ["baz", "2"]]

Column Separator ↑

RFC 4180 specifies column separator COMMA (Ruby ",").

Recipe: Handle Compliant Column Separator ↑

Because the CSV default comma separator is ',', you need not specify option :col_sep for compliant data:

source = "foo,1\nbar,1\nbaz,2\n"
CSV.parse(source) # => [["foo", "1"], ["bar", "1"], ["baz", "2"]]
Recipe: Handle Non-Compliant Column Separator ↑

For data with non-compliant column separators, use option :col_sep. This example source uses TAB ("\t") as its column separator:

source = "foo,1\tbar,1\tbaz,2"
CSV.parse(source, col_sep: "\t") # => [["foo", "1"], ["bar", "1"], ["baz", "2"]]

Quote Character ↑

RFC 4180 specifies quote character DQUOTE (Ruby "\"").

Recipe: Handle Compliant Quote Character ↑

Because the CSV default quote character is "\"", you need not specify option :quote_char for compliant data:

source = "\"foo\",\"1\"\n\"bar\",\"1\"\n\"baz\",\"2\"\n"
CSV.parse(source) # => [["foo", "1"], ["bar", "1"], ["baz", "2"]]
Recipe: Handle Non-Compliant Quote Character ↑

For data with non-compliant quote characters, use option :quote_char. This example source uses SQUOTE ("'") as its quote character:

source = "'foo','1'\n'bar','1'\n'baz','2'\n"
CSV.parse(source, quote_char: "'") # => [["foo", "1"], ["bar", "1"], ["baz", "2"]]

Recipe: Allow Liberal Parsing ↑

Use option :liberal_parsing to specify that CSV should attempt to parse input not conformant with RFC 4180, such as double quotes in unquoted fields:

source = 'is,this "three, or four",fields'
CSV.parse(source) # Raises MalformedCSVError
CSV.parse(source, liberal_parsing: true) # => [["is", "this \"three", " or four\"", "fields"]]

Special Handling ↑

You can use parsing options to specify special handling for certain lines and fields.

Special Line Handling ↑

Use parsing options to specify special handling for blank lines, or for other selected lines.

Recipe: Ignore Blank Lines ↑

Use option :skip_blanks to ignore blank lines:

source = <<-EOT
foo,0

bar,1
baz,2

,
EOT
parsed = CSV.parse(source, skip_blanks: true)
parsed # => [["foo", "0"], ["bar", "1"], ["baz", "2"], [nil, nil]]
Recipe: Ignore Selected Lines ↑

Use option :skip_lines to ignore selected lines.

source = <<-EOT
# Comment
foo,0
bar,1
baz,2
# Another comment
EOT
parsed = CSV.parse(source, skip_lines: /^#/)
parsed # => [["foo", "0"], ["bar", "1"], ["baz", "2"]]

Special Field Handling ↑

Use parsing options to specify special handling for certain field values.

Recipe: Strip Fields ↑

Use option :strip to strip parsed field values:

CSV.parse_line(' a , b ', strip: true) # => ["a", "b"]
Recipe: Handle Null Fields ↑

Use option :nil_value to specify a value that will replace each field that is null (no text):

CSV.parse_line('a,,b,,c', nil_value: 0) # => ["a", 0, "b", 0, "c"]
Recipe: Handle Empty Fields ↑

Use option :empty_value to specify a value that will replace each field that is empty (String of length 0);

CSV.parse_line('a,"",b,"",c', empty_value: 'x') # => ["a", "x", "b", "x", "c"]

Converting Fields ↑

You can use field converters to change parsed String fields into other objects, or to otherwise modify the String fields.

Converting Fields to Objects ↑

Use field converters to change parsed String objects into other, more specific, objects.

There are built-in field converters for converting to objects of certain classes:

Other built-in field converters include:

You can also define field converters to convert to objects of other classes.

Recipe: Convert Fields to Integers ↑

Convert fields to Integer objects using built-in converter :integer:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, converters: :integer)
parsed.map {|row| row['Value'].class} # => [Integer, Integer, Integer]
Recipe: Convert Fields to Floats ↑

Convert fields to Float objects using built-in converter :float:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, converters: :float)
parsed.map {|row| row['Value'].class} # => [Float, Float, Float]
Recipe: Convert Fields to Numerics ↑

Convert fields to Integer and Float objects using built-in converter :numeric:

source = "Name,Value\nfoo,0\nbar,1.1\nbaz,2.2\n"
parsed = CSV.parse(source, headers: true, converters: :numeric)
parsed.map {|row| row['Value'].class} # => [Integer, Float, Float]
Recipe: Convert Fields to Dates ↑

Convert fields to Date objects using built-in converter :date:

source = "Name,Date\nfoo,2001-02-03\nbar,2001-02-04\nbaz,2001-02-03\n"
parsed = CSV.parse(source, headers: true, converters: :date)
parsed.map {|row| row['Date'].class} # => [Date, Date, Date]
Recipe: Convert Fields to DateTimes ↑

Convert fields to DateTime objects using built-in converter :date_time:

source = "Name,DateTime\nfoo,2001-02-03\nbar,2001-02-04\nbaz,2020-05-07T14:59:00-05:00\n"
parsed = CSV.parse(source, headers: true, converters: :date_time)
parsed.map {|row| row['DateTime'].class} # => [DateTime, DateTime, DateTime]
Recipe: Convert Assorted Fields to Objects ↑

Convert assorted fields to objects using built-in converter :all:

source = "Type,Value\nInteger,0\nFloat,1.0\nDateTime,2001-02-04\n"
parsed = CSV.parse(source, headers: true, converters: :all)
parsed.map {|row| row['Value'].class} # => [Integer, Float, DateTime]
Recipe: Convert Fields to Other Objects ↑

Define a custom field converter to convert String fields into other objects. This example defines and uses a custom field converter that converts each column-1 value to a Rational object:

rational_converter = proc do |field, field_context|
  field_context.index == 1 ? field.to_r : field
end
source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, converters: rational_converter)
parsed.map {|row| row['Value'].class} # => [Rational, Rational, Rational]

Recipe: Filter Field Strings ↑

Define a custom field converter to modify String fields. This example defines and uses a custom field converter that strips whitespace from each field value:

strip_converter = proc {|field| field.strip }
source = "Name,Value\n foo , 0 \n bar , 1 \n baz , 2 \n"
parsed = CSV.parse(source, headers: true, converters: strip_converter)
parsed['Name'] # => ["foo", "bar", "baz"]
parsed['Value'] # => ["0", "1", "2"]

Recipe: Register Field Converters ↑

Register a custom field converter, assigning it a name; then refer to the converter by its name:

rational_converter = proc do |field, field_context|
  field_context.index == 1 ? field.to_r : field
end
CSV::Converters[:rational] = rational_converter
source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, converters: :rational)
parsed['Value'] # => [(0/1), (1/1), (2/1)]

Using Multiple Field Converters ↑

You can use multiple field converters in either of these ways:

Recipe: Specify Multiple Field Converters in Option :converters ↑

Apply multiple field converters by specifying them in option :converters:

source = "Name,Value\nfoo,0\nbar,1.0\nbaz,2.0\n"
parsed = CSV.parse(source, headers: true, converters: [:integer, :float])
parsed['Value'] # => [0, 1.0, 2.0]
Recipe: Specify Multiple Field Converters in a Custom Converter List ↑

Apply multiple field converters by defining and registering a custom converter list:

strip_converter = proc {|field| field.strip }
CSV::Converters[:strip] = strip_converter
CSV::Converters[:my_converters] = [:integer, :float, :strip]
source = "Name,Value\n foo , 0 \n bar , 1.0 \n baz , 2.0 \n"
parsed = CSV.parse(source, headers: true, converters: :my_converters)
parsed['Name'] # => ["foo", "bar", "baz"]
parsed['Value'] # => [0, 1.0, 2.0]

Converting Headers ↑

You can use header converters to modify parsed String headers.

Built-in header converters include:

You can also define header converters to otherwise modify header Strings.

Recipe: Convert Headers to Lowercase ↑

Convert headers to lowercase using built-in converter :downcase:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, header_converters: :downcase)
parsed.headers # => ["name", "value"]

Recipe: Convert Headers to Symbols ↑

Convert headers to downcased Symbols using built-in converter :symbol:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, header_converters: :symbol)
parsed.headers # => [:name, :value]
parsed.headers.map {|header| header.class} # => [Symbol, Symbol]

Recipe: Filter Header Strings ↑

Define a custom header converter to modify String fields. This example defines and uses a custom header converter that capitalizes each header String:

capitalize_converter = proc {|header| header.capitalize }
source = "NAME,VALUE\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, header_converters: capitalize_converter)
parsed.headers # => ["Name", "Value"]

Recipe: Register Header Converters ↑

Register a custom header converter, assigning it a name; then refer to the converter by its name:

capitalize_converter = proc {|header| header.capitalize }
CSV::HeaderConverters[:capitalize] = capitalize_converter
source = "NAME,VALUE\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, headers: true, header_converters: :capitalize)
parsed.headers # => ["Name", "Value"]

Using Multiple Header Converters ↑

You can use multiple header converters in either of these ways:

Recipe: Specify Multiple Header Converters in Option :header_converters ↑

Apply multiple header converters by specifying them in option :header_converters:

source = "Name,Value\nfoo,0\nbar,1.0\nbaz,2.0\n"
parsed = CSV.parse(source, headers: true, header_converters: [:downcase, :symbol])
parsed.headers # => [:name, :value]
Recipe: Specify Multiple Header Converters in a Custom Header Converter List ↑

Apply multiple header converters by defining and registering a custom header converter list:

CSV::HeaderConverters[:my_header_converters] = [:symbol, :downcase]
source = "NAME,VALUE\nfoo,0\nbar,1.0\nbaz,2.0\n"
parsed = CSV.parse(source, headers: true, header_converters: :my_header_converters)
parsed.headers # => [:name, :value]

Diagnostics ↑

Recipe: Capture Unconverted Fields ↑

To capture unconverted field values, use option :unconverted_fields:

source = "Name,Value\nfoo,0\nbar,1\nbaz,2\n"
parsed = CSV.parse(source, converters: :integer, unconverted_fields: true)
parsed # => [["foo", "0"], ["bar", "1"], ["baz", "2"]]
parsed.each {|row| p row.unconverted_fields }

Output:

["Name", "Value"]
["foo", "0"]
["bar", "1"]
["baz", "2"]

Recipe: Capture Field Info ↑

To capture field info in a custom converter, accept two block arguments. The first is the field value; the second is a CSV::FieldInfo object:

strip_converter = proc {|field, field_info| p field_info; field.strip }
source = " foo , 0 \n bar , 1 \n baz , 2 \n"
parsed = CSV.parse(source, converters: strip_converter)
parsed # => [["foo", "0"], ["bar", "1"], ["baz", "2"]]

Output:

#<struct CSV::FieldInfo index=0, line=1, header=nil>
#<struct CSV::FieldInfo index=1, line=1, header=nil>
#<struct CSV::FieldInfo index=0, line=2, header=nil>
#<struct CSV::FieldInfo index=1, line=2, header=nil>
#<struct CSV::FieldInfo index=0, line=3, header=nil>
#<struct CSV::FieldInfo index=1, line=3, header=nil>
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