69 lines
2.1 KiB
Markdown
69 lines
2.1 KiB
Markdown
---
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layout: "functions"
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page_title: "csvdecode - Functions - Configuration Language"
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sidebar_current: "docs-funcs-encoding-csvdecode"
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description: |-
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The csvdecode function decodes CSV data into a list of maps.
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---
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# `csvdecode` Function
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`csvdecode` decodes a string containing CSV-formatted data and produces a
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list of maps representing that data.
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CSV is _Comma-separated Values_, an encoding format for tabular data. There
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are many variants of CSV, but this function implements the format defined
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in [RFC 4180](https://tools.ietf.org/html/rfc4180).
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The first line of the CSV data is interpreted as a "header" row: the values
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given are used as the keys in the resulting maps. Each subsequent line becomes
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a single map in the resulting list, matching the keys from the header row
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with the given values by index. All lines in the file must contain the same
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number of fields, or this function will produce an error.
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## Examples
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```
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> csvdecode("a,b,c\n1,2,3\n4,5,6")
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[
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{
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"a" = 1
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"b" = 2
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"c" = 3
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},
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{
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"a" = 4
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"b" = 5
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"c" = 6
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}
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]
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```
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## Use with the `count` meta-argument
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It can be tempting to use `csvdecode` to generate a set of similar resources
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using the `count` meta-argument, as in this example:
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```hcl
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locals {
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instances = csvdecode(file("${path.module}/instances.csv"))
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}
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resource "aws_instance" "example" {
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count = len(local.instances) # Beware! (see below)
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instance_type = local.instances[count.index].instance_type
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ami = local.instances[count.index].ami
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}
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```
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The above example will work on initial creation, but if any rows are removed
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from the CSV file, or if the records in the CSV file are re-ordered, Terraform
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will not understand that the ordering has changed and will instead interpret
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this as requests for changes to many or all of the instances, which will in
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turn force these instances to be destroyed and re-created.
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The above pattern can be used with care in situations where, for example, the
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CSV file is only ever appended to, or if mass-updating the resources would
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not be harmful, but in general we recommend avoiding the above pattern.
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