In order to avoid updating every one of our existing functions with
explicit support for sensitive values, there's a default rule in the
functions system which makes the result of a function sensitive if any
of its arguments contain sensitive values.
We were applying that default to the various type conversion functions,
like tomap and tolist, which meant that converting a complex-typed value
with a sensitive value anywhere inside it would result in a
wholly-sensitive result.
That's unnecessarily conservative because the cty conversion layer (which
these functions are wrapping) already knows how to handle sensitivity
in a more precise way. Therefore we can opt in to handling marked values
(which Terraform uses for sensitivity) here and the only special thing
we need to do is handle errors related to sensitive values differently,
so we won't print their values out literally in case of an error (and so
that the attempt to print them out literally won't panic trying to
extract the marked values).
In the Terraform language we typically use lists of zero or one values in
some sense interchangably with single values that might be null, because
various Terraform language constructs are designed to work with
collections rather than with nullable values.
In Terraform v0.12 we made the splat operator [*] have a "special power"
of concisely converting from a possibly-null single value into a
zero-or-one list as a way to make that common operation more concise.
In a sense this "one" function is the opposite operation to that special
power: it goes from a zero-or-one collection (list, set, or tuple) to a
possibly-null single value.
This is a concise alternative to the following clunky conditional
expression, with the additional benefit that the following expression is
also not viable for set values, and it also properly handles the case
where there's unexpectedly more than one value:
length(var.foo) != 0 ? var.foo[0] : null
Instead, we can write:
one(var.foo)
As with the splat operator, this is a tricky tradeoff because it could be
argued that it's not something that'd be immediately intuitive to someone
unfamiliar with Terraform. However, I think that's justified given how
often zero-or-one collections arise in typical Terraform configurations.
Unlike the splat operator, it should at least be easier to search for its
name and find its documentation the first time you see it in a
configuration.
My expectation that this will become a common pattern is also my
justification for giving it a short, concise name. Arguably it could be
better named something like "oneornull", but that's a pretty clunky name
and I'm not convinced it really adds any clarity for someone who isn't
already familiar with it.
Calling the nonsensitive function with values which are not sensitive
will result in an error. This restriction was added with the goal of
preventing confusingly redundant use of this function.
Unfortunately, this breaks when using nonsensitive to reveal the value of
sensitive resource attributes. This is because the validate walk does
not (and cannot) mark attributes as sensitive based on the schema,
because the resource value itself is unknown.
This commit therefore alters this restriction such that it permits
nonsensitive unknown values, and adds a test case to cover this specific
scenario.
These aim to allow hinting to Terraform about situations where it's not
able to automatically infer value sensitivity.
"nonsensitive" is for situations where Terraform's behavior is too
conservative, such as when a new value is derived from a sensitive value
in such a way that all of the sensitive content is removed.
"sensitive", on the other hand, is for situations where Terraform can't
otherwise infer that a value is sensitive. These situations should be
pretty rare in a module that's making effective use of sensitive input
variables and output values, but the documentation shows one example of
an uncommon situation where a more direct hint via this function would
be needed.
Both of these functions are aimed at only occasional use in unusual
situations. They are here for reasons of pragmatism, not because we
expect them to be used routinely or recommend their use.
If no default is specified for a nested optional structural typed
attribute, the defaults function should just pass through its input.
Before this commit the function assumed that the fallback value was
always of the correct type, which would panic.
When using defaults with a value which contains null objects or tuples,
we cannot continue to traverse the value and apply defaults. Instead,
when we find an attribute which is null, we return early and stop
processing this branch.
We allow primitive fallback values which have mismatched types, but only
if there is a conversion to the target type. Previously we would allow
unsafe conversions (e.g. string to bool), but later had no capacity to
return an error if the conversion failed due to the value of the
fallback being unable to convert to the target type.
This commit makes the more conservative requirement that default
fallback values must have a safe conversion.
Fixes error when calling sum with values not known until apply time.
Also allows sum to cope with numbers too large to represent in float64,
along with correctly handling errors when trying to sum opposing
infinities.
The alltrue/anytrue functions did not correctly handle unknown values.
This commit changes these functions so that the result is unknown if:
- The list argument is unknown
- For alltrue: any elements are unknown
- For anytrue: any elements are unknown and no known elements are true
The last change is a little subtle, so there are test cases to cover it
specifically. Examples:
- anytrue(unknown) -> unknown
- anytrue(false, unknown) -> unknown
- anytrue(false, unknown, true) -> true
This is a new part of the existing module_variable_optional_attrs
experiment, because it's intended to complement the ability to declare
an input variable whose type constraint is an object type with optional
attributes. Module authors can use this to replace null values (that were
either explicitly set or implied by attribute omission) with other
non-null values of the same type.
This function is a bit more type-fussy than our functions typically are
because it's intended for use primarily with input variables that have
fully-specified type constraints, and thus it uses that type information
to help inform how the defaults data structure should be interpreted.
Other uses of this function will probably be harder today because it takes
a lot of extra annotation to build a value of a specific type if it isn't
passing through a variable type constraint. Perhaps later language
features for more general type conversion will make this more applicable,
but for now the more general form of this problem is better solved other
ways.
So far all of our language experiments have been new constructs handled
statically up in the configs package, but functions are another common
extention point where experiments could be useful to gather feedback and
so this intends to pass the information down into the right place to allow
for that to happen, even though as of this commit there are no
experimental functions to use it.
Prior to Terraform 0.12 these two functions were the only way to construct
literal lists and maps (respectively) in HIL expressions. Terraform 0.12,
by switching to HCL 2, introduced first-class syntax for constructing
tuple and object values, which can then be converted into list and map
values using the tolist and tomap type conversion functions.
We marked both of these functions as deprecated in the Terraform v0.12
release and have since then mentioned in the docs that they will be
removed in a future Terraform version. The "terraform 0.12upgrade" tool
from Terraform v0.12 also included a rule to automatically rewrite uses
of these functions into equivalent new syntax.
The main motivation for removing these now is just to get this change made
prior to Terraform 1.0. as we'll be doing with various other deprecations.
However, a specific reason for these two functions in particular is that
their existence is what caused us to invent the idea of a "type expression"
as a distinct kind of expression in Terraform v0.12, and so removing them
now would allow potentially unifying type expressions with value
expressions in a future release.
We do not have any current specific plans to make that change, but one
potential motivation for doing so would be to take another attempt at a
generalized "convert" function which takes a type as one of its arguments.
Our previous attempt to implement such a function was foiled by the fact
that Terraform's expression validator doesn't have any way to know to
treat one argument of a particular function as special, and so it was
generating incorrect error messages. We won't necessarily do that, but
having these "list" and "map" functions out of the way leaves the option
open.
Our diagnostics model allows for optionally annotating an error or warning
with information about the expression and eval context it was generated
from, which the diagnostic renderer for the UI will then use to give the
user some additional hints about what values may have contributed to the
error.
We previously didn't have those annotations on the results of evaluating
for_each expressions though, because in that case we were using the helper
function to evaluate an expression in one shot and thus we didn't ever
have a reference to the EvalContext in order to include it in the
diagnostic values.
Now, at the expense of having to handle the evaluation at a slightly lower
level of abstraction, we'll annotate all of the for_each error messages
with source expression information. This is valuable because we see users
often confused as to how their complex for_each expressions ended up being
invalid, and hopefully giving some information about what the inputs were
will allow more users to self-solve.
This is an analog to the "alltrue" function, using OR as the reduce
operator rather than AND.
This also includes some simplification of the "alltrue" implementation
to implement it similarly as a sort of reduce operation with AND
as the reduce operator, but with the same effective behavior.
These were initially introduced as functions with "encode" and "decode"
prefixes, but that doesn't match with our existing convention of putting
the encoding format first so that the encode and decode functions will
group together in a alphabetically-ordered function list.
"text" is not really a defined serialization format, but it's a short word
that hopefully represents well enough what these functions are aiming to
encode and decode, while being consistent with existing functions like
jsonencode/jsondecode, yamlencode/yamldecode, etc.
The "base64" at the end here is less convincing because there is precedent
for that modifier to appear both at the beginning and the end in our
existing function names. I chose to put it at the end here because that
seems to be our emergent convention for situations where the base64
encoding is a sort of secondary modifier alongside the primary purpose
of the function, as we see with "filebase64". (base64gzip is an exception
here, but it seems outvoted by the others.)
Fix for issue #26320 - this allows us to derive known values from
partially known maps where we can, and may prevent unnecessary
destroy/rebuild cycles during apply in some cases.
In order to properly evaluate a destroy provisioner, we cannot rely on
the usual evaluation context, because the resource has already been
removed from the state.
EvalSelfBlock evaluates an hcl.Body in the limited scope of a single
object as "self", with the added values of "count.index" and "each.key".
This commit adds an `alltrue` function to Terraform configuration. A
reason we might want this function is because it will enable more
powerful custom variable validations. For example:
```hcl
variable "amis" {
type = list(object({
id = string
}))
validation {
condition = (alltrue([
for a in var.amis : length(a.id) > 4 && substr(a.id, 0, 4) == "ami-"
]))
error_message = "The ID of at least one AMI was invalid."
}
}
```
The encoding/json package escapes some HTML-specific characters to
prevent JSON from being misinterpreted when in the context of an HTML
document. Terraform 0.11 used this behaviour, and to preserve backwards
compatibility we are continuing to do so moving forward.
This commit adds an explicit test to document that this is intentional,
not a bug.
The functions that interact with the filesystem are, by design, restricted
to reading files that are distributed as a static part of the
configuration, and cannot be used to interact with files that are
generated dynamically by resources in the configuration.
However, new users have often yet developed a correct mental model of how
Terraform execution works and are confused by the terse error messages
these functions return. As an interim step to help some of those users,
this just adds some more commentary to the error message which gives a
vague, generic directive to look to attributes of the resource that is
generating the file, which should (if it's designed well) export
attributes that allow the resulting file to be used effectively with
common patterns, such as checksums of the content of the generated file.
The error message here is not particularly attractive due to the
limitations of the context where it's being returned from, but I'm
accepting that here in the interest of keeping this change simple, so we
can give a hint about a case that seems to frequently generate new-user
questions. We may iterate further on the presentation of this message
later.
Previously this function only supported the x509 RSA private key format.
More recent versions of OpenSSH default to generating a new PEM key
format, which this commit now supports using the x/crypto/ssh package.
Also improve the returned error messages for various invalid ciphertext
or invalid private key errors.
There is no codepath that can use this any longer, since we need to
evaluate the modules as whole objects.
This means we're going to have to live for now with invalid module
output references returning "object" errors rather that "module".
In order to be able to use module values, and handle operations like
possibly invalid module indexes in conditional statements, whole modules
must always be returned during evaluation.
The map function assumed that the key arguments were strings, and would
panic if they were not.
After this commit, calling `map(1, 2)` will result in a map `{"1" = 1}`,
and calling `map(null, 1)` will result in a syntax error.
Fixes#23346, fixes#23043
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.
This function has a number of different error cases with hopefully-helpful
error messages for each, so it's good to test we're getting the error
message we were actually expecting in each case.
* 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 PR implements 2 changes to the merge function.
- Rather than always defining the merge return type as dynamic, return
a precise type when all argument types match, or all possible object
attributes are known.
- Always return a value containing all keys when the keys are known.
This allows the use of merge output in for_each, even when keys are yet
to be determined.
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.
Martin Atkins