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4.7 Defining Fields by Content

This section discusses an advanced feature of gawk. If you are a novice awk user, you might want to skip it on the first reading.

Normally, when using FS, gawk defines the fields as the parts of the record that occur in between each field separator. In other words, FS defines what a field is not, instead of what a field is. However, there are times when you really want to define the fields by what they are, and not by what they are not.

The most notorious such case is so-called comma-separated values (CSV) data. Many spreadsheet programs, for example, can export their data into text files, where each record is terminated with a newline, and fields are separated by commas. If commas only separated the data, there wouldn’t be an issue. The problem comes when one of the fields contains an embedded comma. In such cases, most programs embed the field in double quotes.24 So, we might have data like this:

Robbins,Arnold,"1234 A Pretty Street, NE",MyTown,MyState,12345-6789,USA

The FPAT variable offers a solution for cases like this. The value of FPAT should be a string that provides a regular expression. This regular expression describes the contents of each field.

In the case of CSV data as presented here, each field is either “anything that is not a comma,” or “a double quote, anything that is not a double quote, and a closing double quote.” If written as a regular expression constant (see Regexp), we would have /([^,]+)|("[^"]+")/. Writing this as a string requires us to escape the double quotes, leading to:

FPAT = "([^,]+)|(\"[^\"]+\")"

Putting this to use, here is a simple program to parse the data:

BEGIN {
    FPAT = "([^,]+)|(\"[^\"]+\")"
}

{
    print "NF = ", NF
    for (i = 1; i <= NF; i++) {
        printf("$%d = <%s>\n", i, $i)
    }
}

When run, we get the following:

$ gawk -f simple-csv.awk addresses.csv
NF =  7
$1 = <Robbins>
$2 = <Arnold>
$3 = <"1234 A Pretty Street, NE">
$4 = <MyTown>
$5 = <MyState>
$6 = <12345-6789>
$7 = <USA>

Note the embedded comma in the value of $3.

A straightforward improvement when processing CSV data of this sort would be to remove the quotes when they occur, with something like this:

if (substr($i, 1, 1) == "\"") {
    len = length($i)
    $i = substr($i, 2, len - 2)    # Get text within the two quotes
}

As with FS, the IGNORECASE variable (see User-modified) affects field splitting with FPAT.

Assigning a value to FPAT overrides field splitting with FS and with FIELDWIDTHS. Similar to FIELDWIDTHS, the value of PROCINFO["FS"] will be "FPAT" if content-based field splitting is being used.

NOTE: Some programs export CSV data that contains embedded newlines between the double quotes. gawk provides no way to deal with this. Even though a formal specification for CSV data exists, there isn’t much more to be done; the FPAT mechanism provides an elegant solution for the majority of cases, and the gawk developers are satisfied with that.

As written, the regexp used for FPAT requires that each field contain at least one character. A straightforward modification (changing the first ‘+’ to ‘*’) allows fields to be empty:

FPAT = "([^,]*)|(\"[^\"]+\")"

Finally, the patsplit() function makes the same functionality available for splitting regular strings (see String Functions).

To recap, gawk provides three independent methods to split input records into fields. The mechanism used is based on which of the three variables—FS, FIELDWIDTHS, or FPAT—was last assigned to.


Footnotes

(24)

The CSV format lacked a formal standard definition for many years. RFC 4180 standardizes the most common practices.


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