csvdecode Function
csvdecode
decodes a string containing CSV-formatted data and produces a
list of maps representing that data.
CSV is Comma-separated Values, an encoding format for tabular data. There are many variants of CSV, but this function implements the format defined in RFC 4180.
The first line of the CSV data is interpreted as a "header" row: the values given are used as the keys in the resulting maps. Each subsequent line becomes a single map in the resulting list, matching the keys from the header row with the given values by index. All lines in the file must contain the same number of fields, or this function will produce an error.
Examples
Use with the for_each
meta-argument
You can use the result of csvdecode
with
the for_each
meta-argument
to describe a collection of similar objects whose differences are
described by the rows in the given CSV file.
There must be one column in the CSV file that can serve as a unique ID for each
row, which we can then use as the tracking key for the individual instances in
the for_each
expression. For example:
The for
expression in our for_each
argument transforms the list produced
by csvdecode
into a map using the local_id
as a key, which tells
Packer to use the local_id
value to track each instance it creates.
Packer will create and manage the following instance addresses:
aws_instance.example["foo1"]
aws_instance.example["foo2"]
aws_instance.example["foo3"]
aws_instance.example["bar1"]
If you modify a row in the CSV on a subsequent plan, Packer will interpret
that as an update to the existing object as long as the local_id
value is
unchanged. If you add or remove rows from the CSV then Packer will plan to
create or destroy associated instances as appropriate.
If there is no reasonable value you can use as a unique identifier in your CSV
then you could instead use
the count
meta-argument
to define an object for each CSV row, with each one identified by its index into
the list returned by csvdecode
. However, in that case any future updates to
the CSV may be disruptive if they change the positions of particular objects in
the list. We recommend using for_each
with a unique ID column to make
behavior more predictable on future changes.