Text::CSV::Hashify(3p)

NAME
Text::CSV::Hashify - Turn a CSV file into a Perl hash

VERSION
This document refers to version 0.10 of Text::CSV::Hashify. This version was released Janaury 21 2018.

SYNOPSIS
    # Simple functional interface
    use Text::CSV::Hashify;
    $hash_ref = hashify('/path/to/file.csv', 'primary_key');

    # Object-oriented interface
    use Text::CSV::Hashify;
    $obj = Text::CSV::Hashify->new( {
        file        => '/path/to/file.csv',
        format      => 'hoh', # hash of hashes, which is default
        key         => 'id',  # needed except when format is 'aoh'
        max_rows    => 20,    # number of records to read; defaults to all
        ... # other key-value pairs possible for Text::CSV
    } );

    # all records requested
    $hash_ref       = $obj->all;

    # arrayref of fields input
    $fields_ref     = $obj->fields;

    # hashref of specified record
    $record_ref     = $obj->record('value_of_key');

    # value of one field in one record
    $datum          = $obj->datum('value_of_key', 'field');

    # arrayref of all unique keys seen
    $keys_ref       = $obj->keys;

DESCRIPTION
The Comma-Separated-Value ('CSV') format is the most common way to store spreadsheets or the output of relational database queries in plain-text format. However, since commas (or other designated field-separator characters) may be embedded within data entries, the parsing of delimited records is non-trivial. Fortunately, in Perl this parsing is well handled by CPAN distribution Text::CSV <http://search.cpan.org/dist/Text-CSV/>. This permits us to address more specific data manipulation problems by building modules on top of Text::CSV.

Note: In this document we will use CSV as a catch-all for tab-delimited files, pipe-delimited files, and so forth. Please refer to the documentation for Text::CSV to learn how to handle field separator characters other than the comma.

Text::CSV::Hashify is designed for the case where you simply want to turn a CSV file into a Perl hash. In particular, it is designed for the case where:

•   the CSV file's first record is a list of fields in the ancestral database table; and

•   one field (column) functions as a primary key, i.e., each record's entry in that field is non-null and is distinct from every other record's entry therein.

Text::CSV::Hashify turns that kind of CSV file into one big hash of hashes.

Text::CSV::Hashify can now take gzip-compressed (.gz) files as input as well as uncompressed files.

  Primary Case: CSV (with primary key) to Hash of Hashes
Text::CSV::Hashify is designed for the case where you simply want to turn a CSV file into a Perl hash. In particular, it is designed for the case where (a) the CSV file's first record is a list of fields in the ancestral database table and (b) one field (column) functions as a primary key, i.e., each record's entry in that field is non-null and is distinct from every other record's entry therein.

Text::CSV::Hashify turns that kind of CSV file into one big hash of hashes. Elements of this hash are keyed on the entries in the designated primary key field and the value for each element is a hash reference of all the data in a particular database record (including the primary key field and its value).

  Secondary Case: CSV (lacking primary key) to Array of Hashes
You may, however, encounter cases where a CSV file's header row contains the list of database fields but no field is capable of serving as a primary key, i.e., there is no field in which the entry for that field in any record is guaranteed to be distinct from the entries in that field for all other records.

In this case, while an individual record can be turned into a hash, the CSV file as a whole cannot accurately be turned into a hash of hashes. As a fallback, Text::CSV::Hashify can, upon request, turn this into an array of hashes. In this case, you will not be able to look up a particular record by its primary key. You will instead have to know its index position within the array (which is equivalent to knowing its record number in the original CSV file minus 1).

  Interfaces
Text::CSV::Hashify provides two interfaces: one functional, one object-oriented.

Use the functional interface when all you want is to turn a CSV file with a primary key field into a hash of hashes.

Use the object-oriented interface for any more sophisticated manipulation of the CSV file. This includes:

•   Text::CSV options

    Access to any of the options available to Text::CSV, such as use of a separator character other than a comma.

•   Limit number of records

    Selection of a limited number of records from the CSV file, rather than slurping the whole file into your in-memory hash.

•   Array of hash references format

    Probably better than the default hash of hash references format when the CSV file has no field able to serve as a primary key.

•   Metadata

    Access to the list of fields, the list of all primary key values, the values in an individual record, or the value of an individual field in an individual record.

Note: On the recommendation of the authors/maintainers of Text::CSV, Text::CSV::Hashify will internally always set Text::CSV's "binary => 1" option.

FUNCTIONAL INTERFACE
Text::CSV::Hashify by default exports one function: hashify().

    $hash_ref = hashify('/path/to/file.csv', 'primary_key');

or

    $hash_ref = hashify('/path/to/file.csv.gz', 'primary_key');

Function takes two arguments: path to CSV file; field in that file which serves as primary key. If the path to the input file ends in .gz, it is assumed to be compressed by gzip. If the file name ends in .psv (or .psv.gz), the separator character is assumed to be a pipe ("|"). If the file name ends in .tsv (or .tsv.gz), the separator character is assumed to be a tab (" "). Otherwise, the separator character will be assumed to be a comma (",").

Returns a reference to a hash of hash references.

OBJECT-ORIENTED INTERFACE

  new()

•   Purpose

    Text::CSV::Hashify constructor.

•   Arguments

        $obj = Text::CSV::Hashify->new( {
            file        => '/path/to/file.csv',
            format      => 'hoh', # hash of hashes, which is default
            key         => 'id',  # needed except when format is 'aoh'
            max_rows    => 20,    # number of records to read; defaults to all
            ... # other key-value pairs possible for Text::CSV
        } );

    Single hash reference. Required element is:

    •   "file"

        String: path to CSV file serving as input. If the path to the input file ends in .gz, it is assumed to be compressed by gzip.

    Element usually needed:

    •   "key"

        String: name of field in CSV file serving as unique key. Needed except when optional element "format" is "aoh".

    Optional elements are:

    •   "format"

        String: possible values are "hoh" and "aoh". Defaults to "hoh" (hash of hashes). new() will fail if the same value is encountered in more than one record's entry in the "key" column. So if you know in advance that your data cannot meet this condition, explicitly select "format => aoh".

    •   "max_rows"

        Number: provide this if you do not wish to populate the hash with all data records from the CSV file. (Will have no effect if the number provided is greater than or equal to the number of data records in the CSV file.)

    •   Any option available to Text::CSV

        See documentation for either Text::CSV or Text::CSV_XS.

•   Return Value

    Text::CSV::Hashify object.

•   Comment

  all()

•   Purpose

    Get a representation of all data found in a CSV input file.

•   Arguments

        $hash_ref   = $obj->all; # when format is default or 'hoh'
        $array_ref  = $obj->all; # when format is 'aoh'

•   Return Value

    Reference representing all data records in the CSV input file. In the default case, or if you have specifically requested "format =" 'hoh'>, the return value is a hash reference. When you have requested "format =" 'aoh'>, the return value is an array reference.

•   Comment

    In the default ("hoh") case, the return value is equivalent to that of hashify().

  fields()

•   Purpose

    Get a list of the fields in the CSV source.

•   Arguments

        $fields_ref = $obj->fields;

•   Return Value

    Array reference.

•   Comment

    If any field names are duplicate, you will not get this far, as new() would have died.

  record()

•   Purpose

    Get a hash representing one record in the CSV input file.

•   Arguments

        $record_ref = $obj->record('value_of_key');

    One argument. In the default case ("format => 'hoh'"), this argument is the value in the record in the column serving as unique key.

    In the "format => 'aoh'" case, this will be index position of the data record in the array. (The header row will be at index 0.)

•   Return Value

    Hash reference.

  datum()

•   Purpose

    Get value of one field in one record.

•   Arguments

        $datum = $obj->datum('value_of_key', 'field');

    List of two arguments: the value in the record in the column serving as unique key; the name of the field.

•   Return Value

    Scalar.

  keys()

•   Purpose

    Get a list of all unique keys found in the input file.

•   Arguments

        $keys_ref = $obj->keys;

•   Return Value

    Array reference.

•   Comment

    If you have selected "format => 'aoh'" in the options to new(), the "keys" method is inappropriate and will cause your program to die.

AUTHOR
    James E Keenan
    CPAN ID: jkeenan
    jkeenan@cpan.org
    http://thenceforward.net/perl/modules/Text-CSV-Hashify

COPYRIGHT
This program is free software; you can redistribute it and/or modify it under the same terms as Perl itself.

The full text of the license can be found in the LICENSE file included with this module.

Copyright 2012-2018, James E Keenan. All rights reserved.

BUGS
There are no bug reports outstanding on Text::CSV::Hashify as of the most recent CPAN upload date of this distribution.

SUPPORT
To report any bugs or make any feature requests, please send mail to "bug-Text-CSV-Hashify@rt.cpan.org" or use the web interface at <http://rt.cpan.org>.

ACKNOWLEDGEMENTS
Thanks to Christine Shieh for serving as the alpha consumer of this library's output.

OTHER CPAN DISTRIBUTIONS

  Text-CSV and Text-CSV_XS
These distributions underlie Text-CSV-Hashify and provide all of its file-parsing functionality. Where possible, install both. That will enable you to process a file with a single, shared interface but have access to the faster processing speeds of XS where available.

  Text-CSV-Slurp
Like Text-CSV-Hashify, Text-CSV-Slurp slurps an entire CSV file into memory, but stores it as an array of hashes instead.

  Text-CSV-Auto
This distribution inspired the "max_rows" option to new().