## Changes
The assertions on the output made are now captured in the `output.*`
files. These don't capture intent like actual assertions do, but we
still have regular test coverage in the path translation tests under
`bundle/config/mutator`.
## Tests
Tests pass.
## Changes
This came up in #2122 where relative library paths showed up with
backslashes on Windows. It's hard to run acceptance tests where paths
may be in either form. This change updates path translation logic to
always use forward slash-separated paths, including for absolute paths.
## Tests
* Unit tests pass.
* Confirmed that code where library paths are used uses the `filepath`
package for path manipulation. The functions in this package always
normalize their inputs to be platform-native paths.
* Confirmed that code that uses absolute paths works with forward
slash-separated paths on Windows.
## Changes
The materialized templates included in #2146 include Python code that we
require to be formatted. Instead of running ruff as part of the
testcase, we can enforce that all Python code in the repository is
formatted. It won't be possible to have a passing acceptance test for
template initialization with unformatted code.
## Changes
- Instead of doing 2 passes on variable resolution, do a loop until
there are no more updates (or we reach count 100).
- Stacked on top of #2163 which is a regression test for this:
acceptance/bundle/variables/complex-transitive-deep
## Tests
Existing tests, new regression tests.
These tests already passed before, added for completeness:
- acceptance/bundle/variables/cycle
- acceptance/bundle/variables/complex-cross-ref
## Changes
Fixes https://github.com/databricks/cli/issues/1977.
This PR modifies the bundle configuration to capture the dependency that
a UC Volume or a DLT pipeline might have on a UC schema at deployment
time. It does so by replacing the schema name with a reference of the
form `${resources.schemas.foo.name}`.
For example:
The following UC Volume definition depends on the UC schema with the
name `schema_name`. This mutator converts this configuration
from:
```
resources:
volumes:
bar:
catalog_name: catalog_name
name: volume_name
schema_name: schema_name
schemas:
foo:
catalog_name: catalog_name
name: schema_name
```
to:
```
resources:
volumes:
bar:
catalog_name: catalog_name
name: volume_name
schema_name: ${resources.schemas.foo.name}`
schemas:
foo:
catalog_name: catalog_name
name: schema_name
```
## Tests
Unit tests and manually.
## Changes
When users create one or more Databricks apps in their bundle it can
lead to initial bundle deployment being slower because apps need to wait
until their compute is fully provisioned and started.
This PR adds a message to warn about it. This message will be removed
when `no_compute` option becomes available in TF provider and used in
DABs (https://github.com/databricks/cli/pull/2144)
## Changes
- Remove ResolveVariableReferencesInComplexVariables - it blocked
complex-within-complex for no good reason.
- Repeat regular resolution twice, it helps with a couple test cases we
have.
There may be a case for running it 3 times or more in a loop, but there
is no test case for that, so this PR is simple incremental improvement.
## Tests
Existing acceptance tests. Previously all unit tests for complex
variables were converted to acceptance tests, to capture this change and
ensure nothing breaks.
## Changes
If before running an app, the app was stopped with an active deployment,
then Apps backend start it and does the auto-deploy of the last active
deployment. In such cases StartApp API won't return any active or
pending deployments in its response but doing the deploy immediately
after the start might result in the error `Cannot deploy app *** as
there is an active deployment in progress`.
From DABs side, we have to do a new deployment on every `bundle run`
(command which start the app and does deployment) because local files in
bundle might have been changed and users expect to have the app running
with new code.
Thus this PR works around the error by catching “deployment in progress”
error, getting any active / pending deployments, waits for them to
finish and start the new deployment again. If 2nd attempts fails, the
whole command fails.
## Tests
Added unit test.
## Changes
We perform a check during path translation that the path being
referenced is contained in the bundle's sync root. If it isn't, it's not
a valid remote reference. However, this doesn't apply to paths that are
_always_ local, such as the artifact path. An artifact's build command
is executed in its path. Files created by the artifact build (e.g.
wheels or JARs) don't need to be in the sync root because they have a
dedicated and different upload path into `${workspace.artifact_path}`.
Therefore, this check that a path is contained in the bundle's sync root
doesn't apply to artifact paths. This change modifies the structure of
path translation to allow opting out of this check.
Fixes#1927.
## Tests
* Existing and new tests pass.
* Manually confirmed that building and using a wheel built outside the
sync root path works as expected.
* No acceptance tests because we don't run build as part of validate.
## Changes
Now it's possible to configure new `app` resource in bundle and point it
to the custom `source_code_path` location where Databricks App code is
defined.
On `databricks bundle deploy` DABs will create an app. All consecutive
`databricks bundle deploy` execution will update an existing app if
there are any updated
On `databricks bundle run <my_app>` DABs will execute app deployment. If
the app is not started yet, it will start the app first.
### Bundle configuration
```
bundle:
name: apps
variables:
my_job_id:
description: "ID of job to run app"
lookup:
job: "My Job"
databricks_name:
description: "Name for app user"
additional_flags:
description: "Additional flags to run command app"
default: ""
my_app_config:
type: complex
description: "Configuration for my Databricks App"
default:
command:
- flask
- --app
- hello
- run
- ${var.additional_flags}
env:
- name: DATABRICKS_NAME
value: ${var.databricks_name}
resources:
apps:
my_app:
name: "anester-app" # required and has to be unique
description: "My App"
source_code_path: ./app # required and points to location of app code
config: ${var.my_app_config}
resources:
- name: "my-job"
description: "A job for app to be able to run"
job:
id: ${var.my_job_id}
permission: "CAN_MANAGE_RUN"
permissions:
- user_name: "foo@bar.com"
level: "CAN_VIEW"
- service_principal_name: "my_sp"
level: "CAN_MANAGE"
targets:
dev:
variables:
databricks_name: "Andrew (from dev)"
additional_flags: --debug
prod:
variables:
databricks_name: "Andrew (from prod)"
```
### Execution
1. `databricks bundle deploy -t dev`
2. `databricks bundle run my_app -t dev`
**If app is started**
```
✓ Getting the status of the app my-app
✓ App is in RUNNING state
✓ Preparing source code for new app deployment.
✓ Deployment is pending
✓ Starting app with command: flask --app hello run --debug
✓ App started successfully
You can access the app at <app-url>
```
**If app is not started**
```
✓ Getting the status of the app my-app
✓ App is in UNAVAILABLE state
✓ Starting the app my-app
✓ App is starting...
....
✓ App is starting...
✓ App is started!
✓ Preparing source code for new app deployment.
✓ Downloading source code from /Workspace/Users/...
✓ Starting app with command: flask --app hello run --debug
✓ App started successfully
You can access the app at <app-url>
```
## Tests
Added unit and config tests + manual test.
```
--- PASS: TestAccDeployBundleWithApp (404.59s)
PASS
coverage: 36.8% of statements in ./...
ok github.com/databricks/cli/internal/bundle 405.035s coverage: 36.8% of statements in ./...
```
## Changes
Move mutator.Merge{JobClusters,JobParameters,JobTasks,PipelineClusters}
after variable resolution. This helps with the case when key contains a
variable.
@pietern mentioned here
https://github.com/databricks/cli/pull/2101#pullrequestreview-2539168762
it should be safe.
## Tests
Existing acceptance that was capturing the bug is updated with corrected
output.
## Changes
This updates `mode: production` to allow `root_path` to indicate
uniqueness. Historically, we required `run_as` for this, which isn't
actually very effective for that purpose. `run_as` also had the problem
that it doesn't work for pipelines.
This is a cherry-pick from https://github.com/databricks/cli/pull/1387
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>