Check attributes on null objects, and fill in unknowns. If we're
evaluating the object, it either means we are at the top level, or a
NestingSingle block was present, and in either case we need to treat the
attributes as null rather than the entire object.
Switch on the block types rather than Nesting, so we don't need add any
logic to change between List/Tuple or Map/Object when DynamicPseudoType
is involved.
The shim layer for the legacy SDK type system is not precise enough to
guarantee it will produce identical results between plan and apply. In
particular, values that are null during plan will often become zero-valued
during apply.
To avoid breaking those existing providers while still allowing us to
introduce this check in the future, we'll introduce a rather-hacky new
flag that allows the legacy SDK to signal that it is the legacy SDK and
thus disable the check.
Once we start phasing out the legacy SDK in favor of one that natively
understands our new type system, we can stop setting this flag and thus
get the additional safety of this check without breaking any
previously-released providers.
No other SDK is permitted to set this flag, and we will remove it if we
ever introduce protocol version 6 in future, assuming that any provider
supporting that protocol will always produce consistent results.
This turns it on at the last moment, and in one place for all uses of
helper/schema. There's no way to use the new protocol without calling
GetSchema, so we can be sure that any subsequent api calls have this set
when required.
Previously we were using the type name requested in the import to select
the schema, but a provider is free to return additional objects of other
types as part of an import result, and so it's important that we perform
schema selection separately for each returned object.
If we don't do this, we get confusing downstream errors where the
resulting object decodes to the wrong type and breaks various invariants
expected by Terraform Core.
The testResourceImportOther test in the test provider didn't catch this
previously because it happened to have an identical schema to the other
resource type being imported. Now the schema is changed and also there's
a computed attribute we can set as part of the refresh phase to make sure
we're completing the Read call properly during import. Refresh was working
correctly, but we didn't have any tests for it as part of the import flow.
While copyMissingValues was meant to re-insert empty values that were
null after apply, it turns out plan is sometimes not predictable as
well.
normalizeNullValue is meant to fix up any null/empty transitions between
to values, and be useful during plan as well. For plan the function only
concerns itself with individual, known values, and skips sets entirely.
The result of running with plan == true is that only changes between
empty and null collections should be fixed.
With the new diff.Apply we can keep the diff mostly intact, but we need
turn off all RequiresNew flags so that the prior state is not removed
from the apply.
One quirky aspect of our import feature is that we allow the importer to
produce additional resources alongside the one that was imported, such as
to create separate rules for each rule of an imported security group.
Providers need to be able to set the types of these other resources since
they may not match the "main" resource type. They do this by calling
ResourceData.SetType, which in turn sets InstanceState.Ephemeral.Type.
In our shims here we therefore need to copy that out into our new TypeName
field so that the new core import code can see it and create the right
type in the state.
Testing this required a minor change to the test harness to allow the
ImportStateCheck function to see the resource type.
Our new diff handling no longer requires stripping the empty diffs out,
and provider may be relying on some of the empty-value quirks in
helper/schema.
Due to various inprecisions in the old SDK implementation, applying the
generated diff can potentially make changes to the data structure that
have no real effect, such as replacing an empty list with a null list or
vice-versa.
Although we can't totally eliminate such diff noise, here we attempt to
avoid it in situations where there are _only_ meaningless changes -- where
the prior state and planned state are equivalent -- by just echoing back
the prior state verbatim to ensure that Terraform will treat it as a noop
change.
If there _are_ some legitimate changes then the result may still contain
meaningless changes alongside it, but that is just a cosmetic problem for
the diff renderer, because the meaningless changes will be ignored
altogether during a subsequent apply anyway. The primary goal here is just
to ensure we can converge on a fixpoint when there are no explicit changes
in the configuration.
This adds unexpected values in some cases, and since the case this
handles is only within set objects, we'll deal woth this when tackling
the sets themselves.
Cycle through the shim operations after Apply, to ensure that we can
converge on a stable value for for Plan. While the shims produce valid
values in both directions, helper/schema sometimes does not agree on
which containers should be empty or null.
Zero values and empty containers can be lost during the shimming
process, and during the provider's Apply step.
If we have known zero value containers and primitives in the source,
which appear as null values in the destination, we copy over the zero
value. Sets (and lists to an extent) are more difficult, since there
before and after indexes may not correlate. In that case we take the
entire container if it's wholly known, expecting the provider to have
correctly handled the value.
Any state modifying functions can only be run once during the plan-apply
cycle. When regenerating the Diff during ApplyResourceChange, strip out
all StateFunc and CustomizeDiff functions from the schema.
Thew NewExtra diff field was where config data that was modified by a
StateFunc was stored, and needs to be maintained between plan and apply.
During PlanResourceChange, store any NewExtra data from the Diff in the
PlannedPrivate data, and re-insert the NewExtra data into the Diff
generated during ApplyResourceChange.
Errors were being ignore with the intention that they would be caught
later in validation, but it turns out we nee dto catch those earlier.
The legacy schemas also allowed providers to set and empty string for a
bool value, which we need to handle here, since it's not being handled
from user input like a normal config value.
When normalizing flatmapped containers, compare the attributes to the
prior state and preserve pre-existing zero-length or unknown values. A
zero-length value that was previously unknown is preserved as a
zero-length value, as that may have been computed as such by the
provider.
The main significant change here is that the package name for the proto
definition is "tfplugin5", which is important because this name is part
of the wire protocol for references to types defined in our package.
Along with that, we also move the generated package into "internal" to
make it explicit that importing the generated Go package from elsewhere is
not the right approach for externally-implemented SDKs, which should
instead vendor the proto definition they are using and generate their
own stubs to ensure that the wire protocol is the only hard dependency
between Terraform Core and plugins.
After this is merged, any provider binaries built against our
helper/schema package will need to be rebuilt so that they use the new
"tfplugin5" package name instead of "proto".
In a future commit we will include more elaborate and organized
documentation on how an external codebase might make use of our RPC
interface definition to implement an SDK, but the primary concern here
is to ensure we have the right wire package name before release.
In order to prevent mismatched states between read/plan/apply, we need
to ensure that the attributes are generated consistently each time.
Because of the various ways in which helper/schema and the hcl2 shims
interpret empty values, the only way to ensure consistency is to always
remove them altogether.
helper/schema will remove "timeouts" from the config, and stash them in
the diff.Meta map. Terraform sees "timeouts" as a regular config block,
so needs them to be present in the state in order to not show a diff.
Have the GRPCProviderServer shim copy all timeout values into any state
it returns to provide consistent diffs in core.
Resource timeouts were a separate config block, but did not exist in the
resource schema. Insert any defined timeouts when generating the
configshema.Block so that the fields can be accepted and validated by
core.
Use the new SimpleDiff method of the provider so that the diff isn't
altered by ForceNew attributes.
Always set an "id" as RequiresReplace so core knows an instance will be
replaced, even if all ForceNew attributes are filtered out due to
ignore_changes.
While the schema Diff fucntion returns a nil diff when creating an empty
(except for id) resource, the Apply function expects the diff to be
initialized and ampty.
PlanResourceChange isn't returning the diff, but rather it is returning
the destired state. If the propsed state results in a nil diff, then,
the propsed state is what should be returned.
Make sure Meta fields are not nil, as the schema package expects those
to be initialised.
Previously we just left these out of the plan altogether, but in the new
plan types we intentionally include change information for every resource
instance, even if no changes are actually planned, to allow alternative
plan file viewers to show what isn't changing as well as what is.
Managing which function need to be shared between the terraform plugin
and the helper plugin without creating cycles was becoming difficult.
Move all functions related to converting between terraform and proto
type into plugin/convert.
The new helper/plugin package contains the grpc servers for handling the
new plugin protocol
The GRPCProviderServer and GRPCProvisionerServer handle the grpc plugin
protocol, and convert the requests to the legacy schema.Provider and
schema.Provisioner methods.
James Bardin