## Changes
This PR adds the `bundle_uuid` helper function that'll return a stable
identifier for the bundle for the duration of the `bundle init` command.
This is also the UUID that'll be set in the telemetry event sent during
`databricks bundle init` and would be used to correlate revenue from
bundle init with resource deployments.
Template authors should add the uuid field to their `databricks.yml`
file they generate:
```
bundle:
# A stable identified for your DAB project. We use this UUID in the Databricks backend
# to correlate and identify multiple deployments of the same DAB project.
uuid: {{ bundle_uuid }}
```
## Tests
Unit test
This will require API call when run inside a workspace, which will
require workspace client (we don't have one at the current point). We
want to keep Load phase quick, since it's common across all commands.
## Changes
This PR introduces use of new `isNil` method. It allows to ensure we
filter out all improperly defined resources in `bundle summary` command.
This includes deleted resources or resources with incorrect
configuration such as only defining key of the resource and nothing
else.
Fixes#1919, #1913
## Tests
Added regression unit test case
## Changes
The built-in template contains a reference to `${bundle.environment}`.
This property has been deprecated in favor of `${bundle.target}` a long
time ago (#670), so we should no longer emit it. The environment field
will continue to be usable until we cut a new major version in some far
away future.
## Tests
* Unit tests
* The test `TestInterpolationWithTarget` still covers correct
interpolation of `${bundle.environment}`
## Changes
This PR adds a warning validating that the configuration for a single
node cluster is valid for interactive, job, job-task, and pipeline
clusters.
Note: We skip the validation if a cluster policy is configured because
the policy is likely to configure `spark_conf` / `custom_tags` itself.
Note: Terrform originally only had validation for interactive, job, and
job-task clusters. This PR adding the validation for pipeline clusters
as well is new.
This PR follows the same logic as we used to have in Terraform. The
validation was removed from Terraform because we had no way to demote
the error to a warning:
https://github.com/databricks/terraform-provider-databricks/pull/4222
### Background
Single-node clusters require `spark_conf` and `custom_tags` to be
correctly set in the cluster definition for them to function optimally.
The cluster will be created even if incorrectly configured, but its
performance will not be great.
For example, if both `spark_conf` and `custom_tags` are not set and
`num_workers` is 0, then only the driver process will be launched on the
cluster compute instance thus leading to sub-optimal utilization of
available compute resources and no parallelization across worker
processes when processing a spark query.
### Issue
This PR addresses some issues reported in
https://github.com/databricks/cli/issues/1546
## Tests
Unit tests and manually.
Example output of the warning:
```
➜ bundle-playground git:(master) ✗ cli bundle validate
Warning: Single node cluster is not correctly configured
at resources.pipelines.bar.clusters[0]
in databricks.yml:29:11
num_workers should be 0 only for single-node clusters. To create a
valid single node cluster please ensure that the following properties
are correctly set in the cluster specification:
spark_conf:
spark.databricks.cluster.profile: singleNode
spark.master: local[*]
custom_tags:
ResourceClass: SingleNode
Name: foobar
Target: default
Workspace:
User: shreyas.goenka@databricks.com
Path: /Workspace/Users/shreyas.goenka@databricks.com/.bundle/foobar/default
Found 1 warning
```
## Changes
Users can configure the bundle to not synchronize any files with:
```yaml
sync:
paths: []
```
If it is explicitly configured as an empty list, the validate command
must not warn about not having any files to synchronize. The warning
exists to alert users who are unintentionally not synchronizing any
files (they might have a `.gitignore` pattern that matches everything).
Closes#1663.
## Tests
* New unit test.
## Changes
The full workspace path for a notebook does not contain the notebook's
extension. If a user converts that file path to a relative path (like
`/Workspace/bundle_root/bar/nb` -> `./bar/nb`), they can be confused as
to why the new file path does not work.
The changes in this PR nudge them to add the appropriate file extension
(e.g., `./bar/nb.py` or `./bar/nb.ipynb`).
One common way users can end up in this scenario is by using the view
job as YAML functionality in the Databricks UI.
## Tests
Unit test and manually.
```
(.venv) ➜ bundle-playground git:(master) ✗ cli bundle validate
Error: notebook ./foo not found. Local notebook references are expected
to contain one of the following file extensions: [.py, .r, .scala, .sql, .ipynb]
```
## Changes
While looking into adding variable lookups for notification destinations
([API][API]), I found the codegen approach for different classes of
variable lookups a bit complex. The template had a custom field override
(for service principals), the package had an override for the cluster
lookup, and it didn't produce tests.
The notification destinations API uses a default page size of 20 for
listing. I want to use a larger page size to limit the number of API
calls, so that would imply another customization on the template or a
manual override.
This code being rather mechanical, I used copilot to produce all
instances of the resolvers and their tests (after writing one of them
manually).
[api]: https://docs.databricks.com/api/workspace/notificationdestinations
## Tests
* Unit tests pass
* Manual confirmation that lookups of warehouses still work
## Changes
This change adds a preset for source-linked deployments. It is enabled
by default for targets in `development` mode **if** the Databricks CLI
is running from the `/Workspace` directory on DBR. It does not have an
effect when running the CLI anywhere else.
Key highlights:
1. Files in this mode won't be uploaded to workspace
2. Created resources will use references to source files instead of
their workspace copies
## Tests
1. Apply preset unit test covering conditional logic
2. High-level process target mode unit test for testing integration
between mutators
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This field was special-cased in #1307 because it's not part of the JSON
payload in the SDK struct.
This approach, while pragmatic, meant it didn't show up in the JSON
schema. While debugging an issue with quality monitors in #1900, I
couldn't figure out why I was getting schema errors on this field, or
how it was passed through to the TF representation. This commit removes
the special case and makes it behave like everything else.
## Tests
* Unit tests pass.
* Confirmed that the updated schema failed validation before this
change.
## Changes
Whether or not the CLI is running on DBR can be detected once and stored
in the command's context.
By storing it in the context, it can easily be mocked for testing.
This builds on the simpler approach and conversation in #1744. It
unblocks testing of the DBR-specific paths while not compromising on the
checks we can perform to test if the CLI is running on DBR.
## Tests
* Unit tests for the new `dbr` package
* New unit test for the `ConfigureWSFS` mutator
Known issues:
- [ ] _(non-blocking with a command override)_ `apps.Update` requires 2
`name` params (one from path, one from request body)
- [ ] _(non-blocking)_ `lakeview.Create` does not require positional
argument `display_name` anymore because it's not marked as required in
request body
Bumps
[github.com/databricks/databricks-sdk-go](https://github.com/databricks/databricks-sdk-go)
from 0.49.0 to 0.51.0.
---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
The file presence check for dashboard files was missing a
`filepath.ToSlash`.
This means it didn't work on Windows unless the dashboard was located at
a path without slashes (i.e. the bundle root).
Closes#1875.
## Tests
* Added a unit test to cover this case (failed before the fix).
* Manually ran a dashboard deployment on Windows.
## Changes
This change adds the `databricks bundle generate dashboard` command.
The command requires one of three flags:
* `--existing-id` to generate configuration for an existing dashboard by
its ID.
* `--existing-path` to generate configuration for an existing dashboard
by its path in the workspace file system.
* `--resource` to generate the `.lvdash.json` dashboard file for a
dashboard that's already defined in the bundle. This option does not
impact the YAML configuration.
A typical workflow could look like this:
1. Use the command with `--existing-id` or `--existing-path` for a
starting point
2. Run `bundle deploy` to deploy a copy of the dashboard
3. Run `bundle open` to open this copy in your browser
4. Navigate to the draft mode and make modifications
5. Run `bundle generate dashboard` with `--resource` to update the local
`.lvdash.json` file with the remote modifications
## Tests
* Unit tests.
* Manual walkthrough as documented in the [Dashboard for NYC Taxi Trip
Analysis
example](https://github.com/databricks/bundle-examples/tree/main/knowledge_base/dashboard_nyc_taxi).
## Changes
As of #1846 we have a generalized package for doing resource lookups and
completion.
This change updates the run command to use this instead of more specific
code under `bundle/run`.
## Tests
* Unit tests pass
* Manually confirmed that completion and prompting works
## Changes
This validator checks permissions defined in top-level bundle config and
permissions set in workspace for the folders bundle is deployed to. It
raises the warning if the permissions defined in the workspace are not
defined in bundle.
This validator is executed only during `bundle validate` command.
## Tests
```
Warning: untracked permissions apply to target workspace path
The following permissions apply to the workspace folder at "/Workspace/Users/andrew.nester@databricks.com/.bundle/clusters/default" but are not configured in the bundle:
- level: CAN_MANAGE, user_name: andrew.nester@databricks.com
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This builds on the functionality added in #1731 that produces a URL for
every resource.
Adds `bundle/resources` package to deal with resource lookups and
command completion. The new functionality is similar to the lookup and
command completion functionality located in `bundle/run`. It differs in
that it doesn't gracefully deal with ambiguous references to resources,
now that we explicitly validate this doesn't occur in the bundle
configuration. It still allows resources to be looked up with their
fully qualified key, `<plural type>.<key>`.
## Tests
* Added unit tests for resource lookup and completion
* Manually confirmed that `bundle open` prompts, accepts a key argument,
and opens a browser
## Changes
We don't need to cancel existing runs when the job is continuous and
unpaused. The `/jobs/run-now` command will cancel the existing run and
trigger a new one automatically.
Cancelling the job manually can cause a race condition where both the
manual trigger from the CLI and the continuous trigger from the job
configuration happens at the same time. This PR prevents that from
happening.
## Tests
Unit tests and manually
## Changes
In #1218, the `BundleToTerraform` function was replaced by a version
based on the dynamic configuration tree. Since then, it has only been
used in tests to confirm that the output of the old function was equal
to the output of the new function. We no longer need this and can
exclusively rely on the version based on the dynamic configuration tree.
## Tests
Tests pass.
## Changes
Added a warning when incorrect permissions used for `/Workspace/Shared`
bundle root
## Tests
Added unit test
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Adds a textual output to the `databricks bundle summary` command, which
includes URLs of deployed resources.
Example usage:
```
$ databricks bundle summary
Name: my_pipeline
Target: dev
Workspace:
Host: https://domain.databricks.com
User: user@databricks.com
Path: /Users/user@databricks.com/.bundle/my_pipeline/dev
Resources:
Jobs:
my_project_job:
Name: [dev lennart] my_project_job
URL: https://domain.databricks.com/jobs/206899209187287?o=6051921418418893
Pipelines:
my_project_pipeline:
Name: [dev lennart] my_project_pipeline
URL: https://domain.databricks.com/pipelines/3f849fd5-ba7d-47fa-a34c-c6bf034b4f58?o=6051921418418893
```
Notes:
* The top headers of the output are the same as those from the existing
`bundle validate` command
* URLs are colored light blue in the output
* For resources that haven't been deployed yet, we show `(not deployed)`
in place of the URL
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
The issue reported in #1828 illustrates how using a YAML timestamp-like
value (a date in this case) causes an issue during conversion to and
from the typed configuration tree.
We use the `AsAny()` function on the `dyn.Value` when normalizing for
the `any` type. We only use the `any` type for variable values, because
they can assume every type. The `AsAny()` function returns a `time.Time`
for the time value during conversion **to** the typed configuration
tree. Upon conversion **from** the typed configuration tree back into
the dynamic configuration tree, we cannot distinguish a `time.Time`
struct from any other struct.
To address this, we use the underlying string value of the time value
when we normalize for the `any` type.
Fixes#1828.
## Tests
Existing unit tests pass
## Changes
Added JSON input validation for CLI commands. Now when invalid JSON
passed as a payload to CLI commands, CLI performs input normalisation
and detects if there are any mismatches such as incorrect types, unknown
fields and etc.
This diagnostic information is printed in standard error output and does
not block command execution, so the change is backward compatible.
Fixes#1769#1764#1625#1560
## Tests
Added unit tests
```
andrew.nester@HFW9Y94129 ~ % databricks jobs create --json '{"seeti}'
Error: error decoding JSON at (inline):1:2: unexpected EOF
andrew.nester@HFW9Y94129 ~ % databricks jobs create --json '{"seeti": true}'
Warning: unknown field: seeti
in (inline):1:9
Error: Job settings must be specified.
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
The two functions `GetShortUserName` and `IsServicePrincipal` are
unrelated to auth or the purpose of the auth package. This change moves
them into their own package and updates `IsServicePrincipal` to take an
`*iam.User` argument instead of a string username.
## Tests
Tests pass.
## Changes
This adds diagnostics for collaborative (production) deployment
scenarios, including:
- Bob deploys a bundle that is normally deployed by Alice, but this
fails because Bob can't write to `/Users/Alice/.bundle`.
- Charlie deploys a bundle that is normally deployed by Alice, but this
fails because he can't create a new pipeline where Alice would be the
owner.
- Alice deploys a bundle where she didn't list herself as one of the
CAN_MANAGE users in permissions. That can work, but is probably a
mistake.
## Tests
Unit tests, manual testing.
## Changes
We do not need the user to specify these fields in their bundle
configuration, so we remove them from the JSON schema.
## Tests
Manually and end to end tests. The JSON schema has also been regenerated
after these changes.
## Changes
We want to encourage a pattern of specifying only a single resource in a
YAML file when the `.(resource-type).yml` extension is used (for
example, `.job.yml`). This convention could allow us to bijectively map
a resource YAML file to its corresponding resource in the Databricks
workspace.
This PR:
1. Emits a recommendation diagnostic when we detect this convention is
being violated. We can promote this to a warning when we want to
encourage this pattern more strongly.
2. Visualises the recommendation diagnostics in the `bundle validate`
command.
**NOTE:** While this PR also shows the recommendation for `.yaml` files,
we do not encourage users to use this extension. We only support it here
since it's part of the YAML standard and some existing users might
already be using `.yaml`.
## Tests
Unit tests and manually. Here's what an example output looks like:
```
Recommendation: define a single job in a file with the .job.yml extension.
at resources.jobs.bar
resources.jobs.foo
in foo.job.yml:13:7
foo.job.yml:5:7
The following resources are defined or configured in this file:
- bar (job)
- foo (job)
```
---------
Co-authored-by: Lennart Kats (databricks) <lennart.kats@databricks.com>
## Changes
Due to platform changes, all libraries, notebooks and etc. paths used in
Databricks must be started with either /Workspace or /Volumes prefix.
This PR makes sure that all bundle paths are correctly prefixed.
Note: this change is a breaking change if user previously configured and
used `/Workspace/Workspace` folder in their workspace file system or
having `/Workspace/${workspace.root_path}...` pattern configured
anywhere in their bundle config
Fixes: #1751
AI:
- [x] Scan DABs config and error out on
`/Workspace/${workspace.root_path}...` pattern usage
## Tests
Added unit tests
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Default workspace path for resources with a presence in the workspace
tree.
Note: this path is **not** created automatically (yet). We need this
only for dashboards (so far), so can take care of creation if one or
more dashboards are part of a deployment. This saves an API call for
deployments where this is not necessary.
## Tests
Expanded existing tests.
## Changes
Currently API limits on exporting files from workspaces are set at 10
MBs while uploading to is 500 MBs. We want to prevent users running into
deadlock when they won't be able to pull state file anymore so we
prevent from uploading large state files (over 10 MBs) to Databricks
workspace.
## Changes
This fixes the user-reported panic in `apply_presets.go`. I'm still
unsure how to reproduce this, since the CLI just reports `ob broken_job
is not defined` when I try to use `bundle deploy` with an empty job.
That said — we may as well be defensive here and I see we have lots of
checks for empty job/cluster/etc. settings scattered throughout our code
base so at least we're somewhat consistent.
## Changes
After introducing the `SyncRootPath` field on the bundle (#1694), the
previous `RootPath` became ambiguous. Does it mean the bundle root path
or the sync root path? This PR renames to field to `BundleRootPath` to
remove the ambiguity.
## Tests
n/a
---------
Co-authored-by: shreyas-goenka <88374338+shreyas-goenka@users.noreply.github.com>
## Changes
Sort the tasks in the resultant `bundle.tf.json`. This is important
because configuration from one task can leak into another if the tasks
are not sorted.
For more details see:
1.
https://github.com/databricks/terraform-provider-databricks/issues/3951
2.
https://github.com/databricks/terraform-provider-databricks/issues/4011
## Tests
Unit test and manually.
For manual testing I used the following configuration:
```
resources:
jobs:
foo:
tasks:
- task_key: task-Z
notebook_task:
notebook_path: nb.py
source: GIT
existing_cluster_id: 0715-133738-ju0ma84z
- task_key: task-1
notebook_task:
notebook_path: ${workspace.file_path}/local.py
source: WORKSPACE
existing_cluster_id: 0715-133738-ju0ma84z
depends_on:
- task_key: task-Z
git_source:
git_provider: gitHub
git_url: https://github.com/shreyas-goenka/job-source-tmp.git
git_branch: main
```
Steps (1):
1. Deploy this bundle.
2. Comment out "source: GIT"
3. Deploy again
Before:
Deploying this bundle twice would fail. This is because the "source:
GIT" would carry over to the next deployment.
After:
There was no error on the subsequent deployment.
Steps (2):
1. Deploy once
2. Deploy again
Before:
Works correctly but leads to a update API call every time.
After:
No diff is detected by terraform.
I plan to use this in https://github.com/databricks/cli/pull/1780, to
set the line and column numbers as well for the locations.
gopatch file used:
```
@@
var x expression
var y expression
var z expression
@@
-bundletest.SetLocation(x, y, z)
+bundletest.SetLocation(x, y, []dyn.Location{{File: z}})
```
## Changes
Add JobTaskClusterSpec validate mutator. It catches the case when tasks
don't which cluster to use.
For example, we can get this error with minor modifications to
`default-python` template:
```yaml
tasks:
- task_key: python_file_task
spark_python_task:
python_file: ../src/my_project_10/main.py
```
```
% databricks bundle validate
Error: Missing required cluster or environment settings
at resources.jobs.my_project_10_job.tasks[0]
in resources/my_project_10_job.yml:17:11
Task "print_github_stars" requires a cluster or an environment to run.
Specify one of the following fields: job_cluster_key, environment_key, existing_cluster_id, new_cluster.
```
We implicitly rely on "one of" validation, which does not exist. Many
bundle fields can't co-exist, for instance, specifying:
`JobTask.{existing_cluster_id,job_cluster_key}`, `Library.{whl,pypi}`,
`JobTask.{notebook_task,python_wheel_task}`, etc.
## Tests
Unit tests
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
- Extract sync output logic from `cmd/sync` into `lib/sync`
- Add hidden `verbose` flag to the `bundle deploy` command, it's false
by default and hidden from the `--help` output
- Pass output handler to the `deploy/files/upload` mutator if the
verbose option is true
The was an idea to use in-place output overriding each past file sync
event in the output, bit that wont work for the extension, since it
doesn't display deploy logs in the terminal.
Example output:
```
~/tmp/defpy: ~/cli/cli bundle deploy --sync-progress
Building defpy...
Uploading defpy-0.0.1+20240917.112755-py3-none-any.whl...
Uploading bundle files to /Users/ilia.babanov@databricks.com/.bundle/defpy/dev/files...
Action: PUT: requirements-dev.txt, resources/defpy_pipeline.yml, pytest.ini, src/defpy/main.py, src/defpy/__init__.py, src/dlt_pipeline.ipynb, tests/main_test.py, src/notebook.ipynb, setup.py, resources/defpy_job.yml, .vscode/extensions.json, .vscode/settings.json, fixtures/.gitkeep, .vscode/__builtins__.pyi, README.md, .gitignore, databricks.yml
Uploaded tests
Uploaded resources
Uploaded fixtures
Uploaded .vscode
Uploaded src/defpy
Uploaded requirements-dev.txt
Uploaded .gitignore
Uploaded fixtures/.gitkeep
Uploaded src/defpy/__init__.py
Uploaded databricks.yml
Uploaded README.md
Uploaded setup.py
Uploaded .vscode/__builtins__.pyi
Uploaded .vscode/extensions.json
Uploaded src/dlt_pipeline.ipynb
Uploaded .vscode/settings.json
Uploaded resources/defpy_job.yml
Uploaded pytest.ini
Uploaded src/defpy/main.py
Uploaded tests/main_test.py
Uploaded resources/defpy_pipeline.yml
Uploaded src/notebook.ipynb
Initial Sync Complete
Deploying resources...
Updating deployment state...
Deployment complete!
```
Output example in the extension:
<img width="1843" alt="Screenshot 2024-09-19 at 11 07 48"
src="https://github.com/user-attachments/assets/0fafd095-cdc6-44b8-b482-27a38ada0330">
## Tests
Manually for the `sync` and `bundle deploy` commands + vscode extension
sync and deploy flows
## Changes
Upgrade to TF provider 1.52
We also temporarily skip generating plugin framework structs to unblock
upgrade as generation does not work yet and need to be fixed separately
## Summary
Use the friendly name of service principals when shortening their name.
This change is helpful for the prefix in development mode. Instead of
adding a prefix like `[dev 1706906c-c0a2-4c25-9f57-3a7aa3cb8123]`, we'll
prefix like `[dev my_principal]`.
## Changes
This PR aliases and overrides the schema associated with the variables
block in `target` to allow for directly specifying a variable value in
the JSON schema (without an levels of nesting). This is needed because
this direct value is resolved by dynamically parsing the configuration
tree.
ca6332a5a4/bundle/config/root.go (L424)
## Tests
Existing unit tests.
## Changes
This PR makes sweeping changes to the way we generate and test the
bundle JSON schema. The main benefits are:
1. More modular JSON schema. Every definition in the schema now is one
level deep and points to references instead of inlining the entire
schema for a field. This unblocks PyDABs from taking a dependency on the
JSON schema.
2. Generate the JSON schema during CLI code generation. Directly stream
it instead of computing it at runtime whenever a user calls `databricks
bundle schema`. This is nice because we no longer need to embed a
partial OpenAPI spec in the CLI. Down the line, we can add a `Schema()`
method to every struct in the Databricks Go SDK and remove the
dependency on the OpenAPI spec altogether. It'll become more important
once we decouple Go SDK structs and methods from the underlying APIs.
3. Add enum values for Go SDK fields in the JSON schema. Better
autocompletion and validation for these fields. As a follow-up, we can
add enum values for non-Go SDK enums as well (created internal ticket to
track).
4. Use "packageName.structName" as a key to read JSON schemas from the
OpenAPI spec for Go SDK structs. Before, we would use an unrolled
presentation of the JSON schema (stored in `bundle_descriptions.json`),
which was complex to parse and include in the final JSON schema output.
This also means loading values from the OpenAPI spec for `target` schema
works automatically and no longer needs custom code.
5. Support recursive types (eg: `for_each_task`). With us now using
$refs everywhere it's trivial to support.
6. Using complex variables would be invalid according to the schema
generated before this PR. Now that bug is fixed. In the future adding
more custom rules will be easier as well due to the single level nature
of the JSON schema.
Since this is a complete change of approach in how we generate the JSON
schema, there are a few (very minor) regressions worth calling out.
1. We'll lose a few custom descriptions for non Go SDK structs that were
a part of `bundle_descriptions.json`. Support for those can be added in
the future as a followup.
2. Since now the final JSON schema is a static artefact, we lose some
lead time for the signal that JSON schema integration tests are failing.
It's okay though since we have a lot of coverage via the existing unit
tests.
## Tests
Unit tests. End to end tests are being added in this PR:
https://github.com/databricks/cli/pull/1726
Previous unit tests were all deleted because they were bloated. Effort
was made to make the new unit tests provide (almost) equivalent
coverage.
## Changes
Library glob expansion happens during deployment. Before that, all
entries that refer to local paths in resource definitions are made
relative to the _sync root_. Before #1694, they were made relative to
the _bundle root_. This PR didn't update the library glob expansion code
to use the sync root path.
If you were using the sync paths setting with library globs, the CLI
would fail to expand the globs because the code was using the wrong path
to anchor those globs.
This change fixes the issue.
## Tests
Manually confirmed that this fixes the issue reported in #1755.
## Changes
We added a custom resolver for the cluster to add filtering for the
cluster source when we list all clusters.
Without the filtering listing could take a very long time (5-10 mins)
which leads to lookup timeouts.
## Tests
Existing unit tests passing
## Changes
Some call sites hold on to the `dyn.Path` provided to them by the
callback. It must therefore never be mutated after the callback returns,
or these mutations leak out into unknown scope.
This change means it is no longer possible for this failure mode to
happen.
## Tests
Unit test.
## Changes
Fixes an `Error: no value assigned to required variable <variable>.`
when the main complex variable definition is defined in one file but
target override is defined in separate file which is included in the
main one.
## Tests
Added regression test
## Changes
DLT pipeline recreations are destructive. They can lead to lost history
of previous updates, outage of the tables temporarily and are
potentially computationally expensive. Thus we make a breaking change
where a prompt is shown to the user if there configuration changes will
lead to a DLT recreation.
Users can skip the prompt by specifying the `--auto-approve` flag.
This PR also fixes an issue with our test runner where logs from the
cmdio.Logger would not get propagated to the reader returned by our
cobra test runner.
## Tests
Manually, and new unit and integration tests.
```
➜ bundle-playground-3 cli bundle deploy
Uploading bundle files to /Users/63ec021d-b0c6-49c0-93a0-5123953a1cb2/.bundle/test/development/files...
The following DLT pipelines will be recreated. Underlying tables will be unavailable for a transient period until the newly recreated pipelines are run once successfully. History of previous pipeline update runs will be lost because of recreation:
recreate pipeline foo
Would you like to proceed? [y/n]: n
Deployment cancelled!
```
## Changes
We were not using the readers and writers set in the test fixtures in
the progress logger. This PR fixes that. It also modifies
`TestAccAbortBind`, which was implicitly relying on the bug.
I encountered this bug while working on
https://github.com/databricks/cli/pull/1672.
## Tests
Manually.
From non-tty:
```
Error: failed to bind the resource, err: This bind operation requires user confirmation, but the current console does not support prompting. Please specify --auto-approve if you would like to skip prompts and proceed.
```
From tty, bind works as expected.
```
Confirm import changes? Changes will be remotely applied only after running 'bundle deploy'. [y/n]: y
Updating deployment state...
Successfully bound databricks_pipeline with an id '9d2dedbb-f522-4503-96ba-4bc4d5bfa77d'. Run 'bundle deploy' to deploy changes to your workspace
```
## Changes
Explain the error when the `databricks-pydabs` package is not installed
or the Python environment isn't correctly activated.
Example output:
```
Error: python mutator process failed: ".venv/bin/python3 -m databricks.bundles.build --phase load --input .../input.json --output .../output.json --diagnostics .../diagnostics.json: exit status 1", use --debug to enable logging
.../.venv/bin/python3: Error while finding module specification for 'databricks.bundles.build' (ModuleNotFoundError: No module named 'databricks')
Explanation: 'databricks-pydabs' library is not installed in the Python environment.
If using Python wheels, ensure that 'databricks-pydabs' is included in the dependencies,
and that the wheel is installed in the Python environment:
$ .venv/bin/pip install -e .
If using a virtual environment, ensure it is specified as the venv_path property in databricks.yml,
or activate the environment before running CLI commands:
experimental:
pydabs:
venv_path: .venv
```
## Tests
Unit tests
## Changes
Preserve diagnostics if there are any errors or warnings when
PythonMutator normalizes output. If anything goes wrong during
conversion, diagnostics contain the relevant location and path.
## Tests
Unit tests
## Changes
This ensures that the CLI and Terraform can both use an Azure CLI
session configured under a non-standard path. This is the default
behavior on Azure DevOps when using the AzureCLI@2 task.
Fixes#1722.
## Tests
Unit test.
## Changes
Consider serverless clusters as compatible for Python wheel tasks.
Fixes a `Python wheel tasks require compute with DBR 13.3+ to include
local libraries` warning shown for serverless clusters
## Changes
* Provide a more helpful error when using an artifact_path based on
/Volumes
* Allow the use of short_names in /Volumes paths
## Example cases
Example of a valid /Volumes artifact_path:
* `artifact_path:
/Volumes/catalog/schema/${workspace.current_user.short_name}/libs`
Example of an invalid /Volumes path (when using `mode: development`):
* `artifact_path: /Volumes/catalog/schema/libs`
* Resulting error: `artifact_path should contain the current username or
${workspace.current_user.short_name} to ensure uniqueness when using
'mode: development'`
## Changes
Fixes issue introduced here https://github.com/databricks/cli/pull/1699
where PyPi packages were treated as local library.
The reason is that `libraryPath` returns an empty string as a path for
PyPi packages and then `IsLibraryLocal` treated empty string as local
path.
Both of these functions are fixed in this PR.
## Tests
Added regression test
## Changes
This changes makes sure we ignore CLI version check on development
builds of the CLI.
Before:
```
$ cat databricks.yml | grep cli_version
databricks_cli_version: ">= 0.223.1"
$ cli bundle deploy
Error: Databricks CLI version constraint not satisfied. Required: >= 0.223.1, current: 0.0.0-dev+06b169284737
```
after
```
...
$ cli bundle deploy
...
Warning: Ignoring Databricks CLI version constraint for development build. Required: >= 0.223.1, current: 0.0.0-dev+d52d6f08fcd5
```
## Tests
<!-- How is this tested? -->
## Changes
This field allows a user to configure paths to synchronize to the
workspace.
Allowed values are relative paths to files and directories anchored at
the directory where the field is set. If one or more values traverse up
the directory tree (to an ancestor of the bundle root directory), the
CLI will dynamically determine the root path to use to ensure that the
file tree structure remains intact.
For example, given a `databricks.yml` in `my_bundle` that includes:
```yaml
sync:
paths:
- ../common
- .
```
Then upon synchronization, the workspace will look like:
```
.
├── common
│ └── lib.py
└── my_bundle
├── databricks.yml
└── notebook.py
```
If not set behavior remains identical.
## Tests
* Newly added unit tests for the mutators and under `bundle/tests`.
* Manually confirmed a bundle without this configuration works the same.
* Manually confirmed a bundle with this configuration works.
## Changes
In https://github.com/databricks/cli/pull/1490 we regressed and started
using the development mode prefix for UC schemas regardless of the mode
of the bundle target.
This PR fixes the regression and adds a regression test
## Tests
Failing integration tests pass now.
## Changes
While experimenting with DAB I discovered that requirements libraries
are being ignored.
One thing worth mentioning is that `bundle validate` runs successfully,
but `bundle deploy` fails. This PR only covers the second part.
## Tests
<!-- How is this tested? -->
Added a unit test
## Changes
Make `pydabs/venv_path` optional. When not specified, CLI detects the
Python interpreter using `python.DetectExecutable`, the same way as for
`artifacts`. `python.DetectExecutable` works correctly if a virtual
environment is activated or `python3` is available on PATH through other
means.
Extract the venv detection code from PyDABs into `libs/python/detect`.
This code will be used when we implement the `python/venv_path` section
in `databricks.yml`.
## Tests
Unit tests and manually
---------
Co-authored-by: Pieter Noordhuis <pcnoordhuis@gmail.com>
## Changes
These tests inadvertently re-ran mutators, the first time through
`loadTarget` and the second time by running `phases.Initialize()`
themselves. Some of the mutators that are executed in
`phases.Initialize()` are also run as part of `loadTarget`. This is
overdue a refactor to make it unambiguous what runs when. Until then,
this removes the duplicated execution.
## Tests
Unit tests pass.
## Changes
This PR addressed post-merge feedback from
https://github.com/databricks/cli/pull/1673.
## Tests
Unit tests, and manually.
```
Error: experiment undefined-experiment is not defined
at resources.experiments.undefined-experiment
in databricks.yml:11:26
Error: job undefined-job is not defined
at resources.jobs.undefined-job
in databricks.yml:6:19
Error: pipeline undefined-pipeline is not defined
at resources.pipelines.undefined-pipeline
in databricks.yml:14:24
Name: undefined-job
Target: default
Found 3 errors
```
## Changes
This adds configurable transformations based on the transformations
currently seen in `mode: development`.
Example databricks.yml showcasing how some transformations:
```
bundle:
name: my_bundle
targets:
dev:
presets:
prefix: "myprefix_" # prefix all resource names with myprefix_
pipelines_development: true # set development to true by default for pipelines
trigger_pause_status: PAUSED # set pause_status to PAUSED by default for all triggers and schedules
jobs_max_concurrent_runs: 10 # set max_concurrent runs to 10 by default for all jobs
tags:
dev: true
```
## Tests
* Existing process_target_mode tests that were adapted to use this new
code
* Unit tests specific for the new mutator
* Unit tests for config loading and merging
* Manual e2e testing
shreyas-goenka
Denis Bilenko
Lennart Kats
dependabot[bot]
Andrew Nester
Pieter Noordhuis
Ilya Kuznetsov
Gleb Kanterov
Ilia Babanov
Witold Czaplewski