Implement a new provider_meta block in the terraform block of modules, allowing provider-keyed metadata to be communicated from HCL to provider binaries.
Bundled in this change for minimal protocol version bumping is the addition of markdown support for attribute descriptions and the ability to indicate when an attribute is deprecated, so this information can be shown in the schema dump.
Co-authored-by: Paul Tyng <paul@paultyng.net>
Previously the templatefile function would permit any arbitrary string as
a variable name, but due to the HCL template syntax it would be impossible
to refer to one that isn't a valid HCL identifier without causing an
HCL syntax error.
The HCL syntax errors are correct, but don't really point to the root
cause of the problem. Instead, we'll pre-verify that the variable names
are valid before we even try to render the template, and given a
specialized error message that refers to the vars argument expression as
the problematic part, which will hopefully make the resolution path
clearer for a user encountering this situation.
The syntax error still remains for situations where all of the variable
names are correct but e.g. the user made a typo referring to one, which
makes sense because in that case the problem _is_ inside the template.
* add setdifference and setsubtract functions and docs
* remove setdifference as it is not implemented correct in underlying lib
* Update setintersection.html.md
* Update setproduct.html.md
* Update setunion.html.md
This guide now lives at:
- https://learn.hashicorp.com/terraform#getting-started
...and terraform.io has been redirecting to there for quite a while. This commit
removes the extra copy so that the text of the two versions doesn't drift, and
updates existing links to point to the new location.
The existing "type" argument allows specifying a type constraint that
allows for some basic validation, but often there are more constraints on
a variable value than just its type.
This new feature (requiring an experiment opt-in for now, while we refine
it) allows specifying arbitrary validation rules for any variable which
can then cause custom error messages to be returned when a caller provides
an inappropriate value.
variable "example" {
validation {
condition = var.example != "nope"
error_message = "Example value must not be \"nope\"."
}
}
The core parts of this are designed to do as little new work as possible
when no validations are specified, and thus the main new checking codepath
here can therefore only run when the experiment is enabled in order to
permit having validations.
These are intended to make it easier to work with arbitrary data
structures whose shape might not be known statically, such as the result
of jsondecode(...) or yamldecode(...) of data from a separate system.
For example, in an object value which has attributes that may or may not
be set we can concisely provide a fallback value to use when the attribute
isn't set:
try(local.example.foo, "fallback-foo")
Using a "try to evaluate" model rather than explicit testing fits better
with the usual programming model of the Terraform language where values
are normally automatically converted to the necessary type where possible:
the given expression is subject to all of the same normal type conversions,
which avoids inadvertently creating a more restrictive evaluation model
as might happen if this were handled using checks like a hypothetical
isobject(...) function, etc.
It's a common source of errors to try to produce JSON or YAML syntax
using string concatenation via our template language but to miss some
details like correct string escaping, quoting, required commas, etc.
The jsonencode and yamlencode functions are a better way to generate JSON
and YAML, but it's not immediately obvious that both of these functions
are available for use in external templates (via templatefile) too.
Given that questions related to this come up a lot in our community forum
and elsewhere, it seems worth having a documentation section to show the
pattern of having a template that consists only of a single function call.
A very common question since we launched the two repetition constructs
is how to deal with situations where the input data structure doesn't
match one-to-one with the desired configuration.
This adds some full worked examples of two common situations that have
come up in questions. To avoid adding a lot of extra content to the
already-large "expressions" and "resources" pages, the main bulk of this
new content lives with the relevant functions themselves as a full example
of one thing they are good for, and then we'll link to them from the two
general documentation sections where folks are likely to be reading when
they encounter the problem.
Previously we were using the experimental HCL 2 repository, but now we'll
shift over to the v2 import path within the main HCL repository as part of
actually releasing HCL 2.0 as stable.
This is a mechanical search/replace to the new import paths. It also
switches to the v2.0.0 release of HCL, which includes some new code that
Terraform didn't previously have but should not change any behavior that
matters for Terraform's purposes.
For the moment the experimental HCL2 repository is still an indirect
dependency via terraform-config-inspect, so it remains in our go.sum and
vendor directories for the moment. Because terraform-config-inspect uses
a much smaller subset of the HCL2 functionality, this does still manage
to prune the vendor directory a little. A subsequent release of
terraform-config-inspect should allow us to completely remove that old
repository in a future commit.
The cidrsubnets function signature is intentionally very low-level and
focused on the core requirement of generating addresses. This registry
module then wraps it with some additional functionality to make it more
convenient to generate and use subnet address ranges.
This is a companion to cidrsubnet that allows bulk-allocation of multiple
subnet addresses at once, with automatic numbering.
Unlike cidrsubnet, cidrsubnets allows each of the allocations to have a
different prefix length, and will pack the networks consecutively into the
given address space. cidrsubnets can potentially create more complicated
addressing schemes than cidrsubnet alone can, because it's able to take
into account the full set of requested prefix lengths rather than just
one at a time.