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.
-
Column separator.
-
Quote character.
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:
-
Float
-
Integer
-
Date
-
DateTime
Other built-in field converters include:
-
:numeric
: converts to Integer and Float. -
:all
: converts to DateTime, Integer, Float.
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:
-
Specify converters in option
:converters
. -
Specify converters in a custom converter list.
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:
-
:symbol
: converts String header to Symbol. -
:downcase
: converts String header to lowercase.
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:
-
Specify header converters in option
:header_converters
. -
Specify header converters in a custom header converter list.
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>