## Changes
The `Setenv` helper function configures an environment variable and
resets it to its original value when exiting the test scope. It is
incompatible with running tests in parallel because it modifies
process-wide state. The `libs/env` package defines functions to interact
with the environment but records `Setenv` calls on a `context.Context`.
This enables us to override/specialize the environment scoped to a
context.
Pre-requisites for removing the `t.Setenv` calls:
* Make `cmdio.NewIO` accept a context and use it with `libs/env`
* Make all `internal/testcli` functions use a context
The rest of this change:
* Modifies integration tests to initialize a context to use if there
wasn't already one
* Updates `t.Setenv` calls to use `env.Set`
## Tests
n/a
## Changes
VSCode extension no longer uses `databricks.python.envFile ` setting.
And older extension versions will use the same default value anyway.
## Tests
None
## Changes
Enable gofumpt and goimports in golangci-lint and apply autofix.
This makes 'make fmt' redundant, will be cleaned up in follow up diff.
## Tests
Existing tests.
## Changes
Enable errcheck linter for the whole codebase.
Fix remaining complaints:
- If we can propagate error to caller, do that
- If we writing to stdout, continue ignoring errors (to avoid crashing
in "cli | head" case)
- Add exception for cobra non-critical API such as
MarkHidden/MarkDeprecated/RegisterFlagCompletionFunc. This keeps current
code and behaviour, to be decided later if we want to change this.
- Continue ignoring errors where that is desired behaviour (e.g.
git.loadConfig).
- Continue ignoring errors where panicking seems riskier than ignoring
the error.
- Annotate cases in libs/dyn with //nolint:errcheck - to be addressed
later.
Note, this PR is not meant to come up with the best strategy for each
case, but to be a relative safe change to enable errcheck linter.
## Tests
Existing tests.
## Changes
Remove two duplicate implementations of the same logic, switch
everywhere to folders.FindDirWithLeaf.
Add Abs() call to FindDirWithLeaf, it cannot really work on relative
paths.
## Tests
Existing tests.
## Changes
Fix all errcheck-found issues in tests and test helpers. Mostly this
done by adding require.NoError(t, err), sometimes panic() where t object
is not available).
Initial change is obtained with aider+claude, then manually reviewed and
cleaned up.
## Tests
Existing tests.
## Changes
The `any` alias for `interface{}` has been around since Go 1.18.
Now that we're using golangci-lint (#1953), we can lint on it.
Existing commits can be updated with:
```
gofmt -w -r 'interface{} -> any' .
```
## Tests
n/a
## Changes
Since there is no .git directory in Workspace file system, we need to
make an API call to api/2.0/workspace/get-status?return_git_info=true to
fetch git the root of the repo, current branch, commit and origin.
Added new function FetchRepositoryInfo that either looks up and parses
.git or calls remote API depending on env.
Refactor Repository/View/FileSet to accept repository root rather than
calculate it. This helps because:
- Repository is currently created in multiple places and finding the
repository root is becoming relatively expensive (API call needed).
- Repository/FileSet/View do not have access to current Bundle which is
where WorkplaceClient is stored.
## Tests
- Tested manually by running "bundle validate --json" inside web
terminal within Databricks env.
- Added integration tests for the new API.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This PR adds support for UC volumes to DABs.
### Can I use a UC volume managed by DABs in `artifact_path`?
Yes, but we require the volume to exist before being referenced in
`artifact_path`. Otherwise you'll see an error that the volume does not
exist. For this case, this PR also adds a warning if we detect that the
UC volume is defined in the DAB itself, which informs the user to deploy
the UC volume in a separate deployment first before using it in
`artifact_path`.
We cannot create the UC volume and then upload the artifacts to it in
the same `bundle deploy` because `bundle deploy` always uploads the
artifacts to `artifact_path` before materializing any resources defined
in the bundle. Supporting this in a single deployment requires us to
migrate away from our dependency on the Databricks Terraform provider to
manage the CRUD lifecycle of DABs resources.
### Why do we not support `preset.name_prefix` for UC volumes?
UC volumes will not have a `dev_shreyas_goenka` prefix added in `mode:
development`. Configuring `presets.name_prefix` will be a no-op for UC
volumes. We have decided not to support prefixing for UC resources. This
is because:
1. UC provides its own namespace hierarchy that is independent of DABs.
2. Users can always manually use `${workspace.current_user.short_name}`
to configure the prefixes manually.
Customers often manually set up a UC hierarchy for dev and prod,
including a schema or catalog per developer. Thus, it's often
unnecessary for us to add prefixing in `mode: development` by default
for UC resources.
In retrospect, supporting prefixing for UC schemas and registered models
was a mistake and will be removed in a future release of DABs.
## Tests
Unit, integration test, and manually.
### Manual Testing cases:
1. UC volume does not exist:
```
➜ bundle-playground git:(master) ✗ cli bundle deploy
Error: failed to fetch metadata for the UC volume /Volumes/main/caps/my_volume that is configured in the artifact_path: Not Found
```
2. UC Volume does not exist, but is defined in the DAB
```
➜ bundle-playground git:(master) ✗ cli bundle deploy
Error: failed to fetch metadata for the UC volume /Volumes/main/caps/managed_by_dab that is configured in the artifact_path: Not Found
Warning: You might be using a UC volume in your artifact_path that is managed by this bundle but which has not been deployed yet. Please deploy the UC volume in a separate bundle deploy before using it in the artifact_path.
at resources.volumes.bar
in databricks.yml:24:7
```
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## 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
## 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
When running the CLI on Databricks Runtime (DBR), use the
extension-aware filer to write an instantiated template if the instance
path is located in the workspace filesystem.
Notebooks cannot be written through the workspace filesystem's FUSE
mount. As a result, this is the only method for initializing templates
that contain notebooks when running the CLI on DBR and writing to the
workspace filesystem.
Depends on #1910 and #1911.
Supersedes #1744.
## Tests
* Manually confirmed I can initialize a template with notebooks when
running the CLI from the web terminal.
## Changes
Prior to this change, the output directory was part of the `renderer`
type and passed down to every `file` it produced. Every file knew its
absolute destination path. This is incompatible with the use of a filer,
where all operations are automatically anchored to some base path.
To make this compatible, this change updates:
* the `file` type to only know its own path relative to the instantiation root,
* the `renderer` type to no longer require or pass along the output directory,
* the `persistToDisk` function to take a context and filer argument,
* the `filer.WriteMode` to represent permission bits
## Tests
* Existing tests pass.
* Manually confirmed template initialization works as expected.
## Changes
While working on the v2 of #1744, I found that:
* Template initialization first copies built-in templates to a temporary
directory before initializing them
* Reading a template's contents goes through a `filer.Filer` but is
hardcoded to a local one
This change updates the interface for reading templates to be `fs.FS`.
This is compatible with the `embed.FS` type for the built-in templates,
so they no longer have to be copied to a temporary directory before
being used.
The alternative is to use a `filer.Filer` throughout, but this would
have required even more plumbing, and we don't need to _read_ templates,
including notebooks, from the workspace filesystem (yet?).
As part of making `template.Materialize` take an `fs.FS` argument, the
logic to match a given argument to a particular built-in template in the
`init` command has moved to sit next to its implementation.
## Tests
Existing tests pass.
## Changes
The workspace extensions filer should not read or stat a notebook called
`foo` if the user calls `.Stat(ctx, "foo")`.
Instead, the filer should return a file not found error. This is because
the contract for the workspace extensions filer is to only work for
notebooks when the file path / name includes the extension (example:
`foo.ipynb` or `foo.sql` instead of just `foo`)
## Tests
Integration tests.
## Changes
We had a number of copies of test helpers for `io/fs` in the repository.
This change consolidates all of them to use the `libs/fakefs` package.
## Tests
Unit tests pass.
## 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
## Changes
### Background
The workspace import APIs recently added support for importing Jupyter
notebooks written in R, Scala, or SQL, that is non-Python notebooks.
This now works for the `/import-file` API which we leverage in the CLI.
Note: We do not need any changes in `databricks sync`. It works out of
the box because any state mapping of local names to remote names that we
store is only scoped to the notebook extension (i.e., `.ipynb` in this
case) and is agnostic of the notebook's specific language.
### Problem this PR addresses
The extension-aware filer previously did not function because it checks
that a `.ipynb` notebook is written in Python. This PR relaxes that
constraint and adds integration tests for both the normal workspace
filer and extensions aware filer writing and reading non-Python `.ipynb`
notebooks.
This implies that after this PR DABs in the workspace / CLI from DBR
will work for non-Python notebooks as well. non-Python notebooks for
DABs deployment from local machines already works after the platform
side changes to the API landed, this PR just adds integration tests for
that bit of functionality.
Note: Any platform side changes we needed for the import API have
already been rolled out to production.
### Before
DABs deploy would work fine for non-Python notebooks. But DABs
deployments from DBR would not.
### After
DABs deploys both from local machines and DBR will work fine.
## Testing
For creating the `.ipynb` notebook fixtures used in the integration
tests I created them directly from the VSCode UI. This ensures high
fidelity with how users will create their non-Python notebooks locally.
For Python notebooks this is supported out of the box by VSCode but for
R and Scala notebooks this requires installing the Jupyter kernel for R
and Scala on my local machine and using that from VSCode.
For SQL, I ended up directly modifying the `language_info` field in the
Jupyter metadata to create the test fixture.
### Discussion: Issues with configuring language at the cell level
The language metadata for a Jupyter notebook is standardized at the
notebook level (in the `language_info` field). Unfortunately, it's not
standardized at the cell level. Thus, for example, if a user changes the
language for their cell in VSCode (which is supported by the standard
Jupyter VSCode integration), it'll cause a runtime error when the user
actually attempts to run the notebook. This is because the cell-level
metadata is encoded in a format specific to VSCode:
```
cells: []{
"vscode": {
"languageId": "sql"
}
}
```
Supporting cell level languages is thus out of scope for this PR and can
be revisited along with the workspace files team if there's strong
customer interest.
## Changes
The host URL for databricks workspaces includes the workspaceId by
default as a positional arg. Eg:
https://e2-dogfood.staging.cloud.databricks.com/?o=1234
Thus a user can't simply copy paste the URL today to the auth login
command. They'll see a runtime error:
```
➜ cli git:(main) ✗ databricks auth login --host https://e2-dogfood.staging.cloud.databricks.com/\?o\=xxx --profile new-dg
Error: oidc: fetch .well-known: failed to unmarshal response body: invalid character '<' looking for beginning of value. This is likely a bug in the Databricks SDK for Go or the underlying REST API. Please report this issue with the following debugging information to the SDK issue tracker at https://github.com/databricks/databricks-sdk-go/issues. Request log:
GET /login.html
...
```
## Tests
Unit tests and manually. Now auth login works even when the workspace_id
is included in the URL.
## Changes
This package can be used to marshal a `dyn.Value` as JSON and retain the
ordering of keys in a mapping. Unlike the default behavior of
`json.Marshal,` the output does not encode HTML characters.
Otherwise, this is no different from using `JSON.Marshal` with
`v.AsAny().`
## Tests
Unit tests.
## Changes
Test failures indicate that both stdout and stderr are consumed, yet the
content of stdout doesn't end up in the intended output. This can happen
if the goroutines responsible for writing to the combined output buffer
attempt to write to the same underlying buffer concurrently.
Example failure:
```
=== RUN TestBackgroundCombinedOutput
background_test.go:65:
Error Trace: D:/a/cli/cli/libs/process/background_test.go:65
Error: elements differ
extra elements in list A:
([]interface {}) (len=1) {
(string) (len=1) "2"
}
listA:
([]string) (len=2) {
(string) (len=1) "1",
(string) (len=1) "2"
}
listB:
([]string) (len=1) {
(string) (len=1) "1"
}
Test: TestBackgroundCombinedOutput
```
With the test body:
ca45e53f42/libs/process/background_test.go (L48-L66)
With the implementation of `WithCombinedOutput`:
ca45e53f42/libs/process/opts.go (L72-L78)
Notice that `c.Stdout` does get the "2", or the test failure would have
included the relevant assertion error. This leads me to believe that
there is a race on writing to `buf` from the two goroutines writing to
`c.Stdout` and `c.Stderr`.
## Tests
The test passes. If this PR has the intended effect remains to be
seen...
Change the default-python template to not set the `catalog` field for
the pipeline for workspaces that set `hive_metastore` as the default
catalog. The Pipelines service currently returns an error when that
value is used for the `catalog` field.
This is the most simple fix for this issue, which was reported by a
customer. As a followup, we should look at whether we want to prompt for
a catalog instead, possibly just for this specific scenario.
## Changes
This change allows the `sync` command to work from [git
worktrees](https://git-scm.com/docs/git-worktree).
## Tests
* Added unit tests for traversal of worktree related files.
* Manually confirmed that synchronization of files from a main checkout,
as well as a worktree, observed the same ignore rules (both locally
defined as well as from `$GIT_DIR/info/exclude`).
---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
This file is at `info/exclude`, and not `info/excludes`.
Also see https://git-scm.com/docs/gitignore.
## Tests
Manually confirmed that these ignore patterns are now picked up. I
created a repository with a pattern in this file and ran `sync` to
confirm it ignores files matching the pattern.
## Changes
I took the examples from https://yaml.org/spec/1.2.2.
The required modifications to the loader are:
* Correctly parse floating point infinities and NaN
* Correctly parse octal numbers per the YAML 1.2 spec
* Treat "null" keys in a map as valid
## Tests
Existing and new unit tests pass.
## 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
Fixed unmarshalling json input into `interface{}` type
Commands like `api post` support free form request input, so it should
be unmarshaled correctly
## Tests
Added regression test + E2E test 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
This extends the `{{default_catalog}}` helper in templates to ignore any
`PERMISSION_DENIED` error. We're still reviewing when exactly this error
occurs, but if it does, it should not break templates. We should fall
back to assuming there's no default catalog (and no UC) instead.
## Testing
I have not been able to reproduce this issue, but there is a customer
report about "access denied to clusters that don't have unity catalog
enabled" being returned on a non-UC workspace. The error code in this PR
corresponds to that message.
## Next steps
We'll work together with the UC team to review if this error even makes
sense for this API. If that discussion leads to a behavior change in the
API we can update the CLI code again.
## 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 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
We want to encourage a pattern of only specifying a single resource in a
YAML file when an `.<resource-type>.yml` (like `.job.yml`) is used. This
convention could allow us to bijectively map a resource YAML file to
it's corresponding resource in the Databricks workspace.
This PR simply makes the built-in templates compliant to this format.
## Tests
Existing tests.
## 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
## Summary
Enables Unity Catalog for pipelines in the default template. Pipelines
will default to non-Unity Catalog pipelines if a catalog is not
specified.
*Small caveat*: there are cases where admins lock down the default
catalog of a workspace and don't allow the creation of a new schema
there. If that happens, the pipeline would fail at runtime with a clear
error indicating what happened. ("PERMISSION_DENIED: User does not have
CREATE SCHEMA on Catalog 'main'."). I've seen this with an internal
Databricks workspace, where creating new non-UC schemas wasn't locked
down, but creation in the `main` was.
## Testing
- Validated on a non-UC + UC workspace. The catalog selection logic here
is the same as applied for the SQL templates.
## 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]`.
## Summary
Simplifies template by using the periodic trigger syntax instead of the
cron schedule syntax. Periodic triggers are simpler to configure,
simpler to read, and make sure that workloads are spread out through the
day. We only recommend cron syntax for advanced cases or when more
control is needed.
## Testing
* Templates validation via unit tests
* Manual validation that the new triggers work as expected in dev/prod
## 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
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.
Andrew Nester
Pieter Noordhuis
Ilia Babanov
Denis Bilenko
shreyas-goenka
Denis Bilenko
Lennart Kats (databricks)
Stephen Macke