## 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
## Changes
Before this change, the fileset library would take a single root path
and list all files in it. To support an allowlist of paths to list (much
like a Git `pathspec` without patterns; see [pathspec](pathspec)), this
change introduces an optional argument to `fileset.New` where the caller
can specify paths to list. If not specified, this argument defaults to
list `.` (i.e. list all files in the root).
The motivation for this change is that we wish to expose this pattern in
bundles. Users should be able to specify which paths to synchronize
instead of always only synchronizing the bundle root directory.
[pathspec]:
https://git-scm.com/docs/gitglossary#Documentation/gitglossary.txt-aiddefpathspecapathspec
## Tests
New and existing unit tests.
## Changes
This PR removes the dependency to the `databricks-sdk-go/openapi`
package by copying the struct and functions that are needed in a new
`schema/spec.go` file.
The reason to remove this dependency is that it is being deprecated.
Copying the code in the `cli` repo seems reasonable given that it only
uses a couple of very small structs.
## Tests
Verified that CLI code can be properly generated after this change.
## Changes
Previously for all the libraries referenced in configuration DABs made
sure that there is corresponding artifact section.
But this is not really necessary and flexible, because local libraries
might be built outside of dabs context.
It also created difficult to follow logic in code where we back
referenced libraries to artifacts which was difficult to fllow
This PR does 3 things:
1. Allows all local libraries referenced in DABs config to be uploaded
to remote
2. Simplifies upload and glob references expand logic by doing this in
single place
3. Speed things up by uploading library only once and doing this in
parallel
## Tests
Added unit + integration tests + made sure that change is backward
compatible (no changes in existing tests)
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Since locations are already tracked in the dynamic value tree, we no
longer need to track it at the resource/artifact level. This PR:
1. Removes use of `paths.Paths`. Uses dyn.Location instead.
2. Refactors the validation of resources not being empty valued to be
generic across all resource types.
## Tests
Existing unit tests.
## Changes
This didn't work as expected because the generic build mutator called
into the type-specific build mutator in the middle of the function. This
invalidated the `config.Artifact` pointer that was being mutated later
on, effectively hiding these mutations from its caller.
To fix this, I turned glob expansion into its own mutator. It now works
as expected, _and_ produces better errors if the glob patterns are
invalid or do not match files.
## Tests
Unit tests.
Manual verification:
```
% databricks bundle deploy
Building sbt_example...
Error: target/scala-2.12/sbt-e[xam22ple*.jar: syntax error in pattern
at artifacts.sbt_example.files[1].source
in databricks.yml:15:17
```
## Changes
This change enables overriding the default value of job parameters in
target overrides.
This is the same approach we already take for job clusters and job
tasks.
Closes#1620.
## Tests
Mutator unit tests and lightweight end-to-end tests.
## Changes
In https://github.com/databricks/cli/pull/1618 we introduced prepare
step in which Python wheel folder was cleaned. Now it was cleaned
everytime instead of only when there is a build command how it is used
to work.
This PR fixes it by only cleaning up dist folder when there is a build
command for wheels.
Fixes#1638
## Tests
Added regression test
# Changes
With https://github.com/databricks/cli/pull/1413 we started to compute
and partially print the plan if it contained deletion of UC schemas.
This PR uses the precomputed plan to avoid double planning when actually
doing the terraform plan.
This fixes a performance regression introduced in
https://github.com/databricks/cli/pull/1413.
# Tests
Tested manually.
1. Verified bundle deployment still works and deploys resources.
2. Verified that the precomputed plan is indeed being used by attaching
a debugger and removing the plan file right before the terraform apply
process is spawned and asserting that terraform apply fails because the
plan is not found.
## Changes
This PR adds support for UC Schemas to DABs. This allows users to define
schemas for tables and other assets their pipelines/workflows create as
part of the DAB, thus managing the life-cycle in the DAB.
The first version has a couple of intentional limitations:
1. The owner of the schema will be the deployment user. Changing the
owner of the schema is not allowed (yet). `run_as` will not be
restricted for DABs containing UC schemas. Let's limit the scope of
run_as to the compute identity used instead of ownership of data assets
like UC schemas.
2. API fields that are present in the update API but not the create API.
For example: enabling predictive optimization is not supported in the
create schema API and thus is not available in DABs at the moment.
## Tests
Manually and integration test. Manually verified the following work:
1. Development mode adds a "dev_" prefix.
2. Modified status is correctly computed in the `bundle summary`
command.
3. Grants work as expected, for assigning privileges.
4. Variable interpolation works for the schema ID.
Shreyas Goenka
dependabot[bot]
Andrew Nester
Lennart Kats (databricks)
Pieter Noordhuis
shreyas-goenka
Witold Czaplewski
Gleb Kanterov
Renaud Hartert
Alex Moschos