## 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.
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)
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## 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
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
The commit where resource lookup was factored out into a separate
package (#1858) didn't take into account the use of `args` further down
in the code.
This change fixes that oversight by returning the tail arguments when
determining which resource to run. The later call no longer has to index
the `args` slice.
## Tests
Manually confirmed that the command works when being prompted for the
resource to run.
## Changes
Added E2E test to run python wheels on interactive cluster created in
bundle.
We had a gap in testing wheel on all purpose clusters, so this PR
addresses the gap
## Changes
This PR adds the `cmd-exec-id` field to the user agent. This allows us
to correlate multiple HTTP requests made from the CLI.
### Why Not Use HTTP traceparent?
We considered using the traceparent header in HTTP as an alternative,
but it's not a good fit for our use case. Here's why:
1. Purpose of traceparent: It's designed to trace a single HTTP request
across a distributed system as it moves through subsystems and proxies.
2. Our requirement: We need to trace multiple HTTP requests made during
a single command execution in the CLI.
For more details about how traceparent itself works and how it's used in
the Go SDK, see
https://github.com/databricks/databricks-sdk-go/pull/914.
## Tests
Unit test
## Changes
Old script could not be run from master due to security restrictions and
there is no reliable way to detect if a user as secrets.
## Tests
Opened a PR in SDK Java from fork
https://github.com/databricks/databricks-sdk-java/pull/375
## Changes
This was released 2+ months ago so it has baked enough.
Blog post: https://go.dev/blog/go1.23.
## Tests
None other than unit and integration tests.
This patch release fixes the following error observed when deploying to
/Shared root folder
"Error: Path (/Shared/.bundle/.../resources) doesn't exist"
Bundles:
* Fixed adding /Workspace prefix for resource paths
([#1866](https://github.com/databricks/cli/pull/1866)).
## 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
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).
Bumps [github.com/fatih/color](https://github.com/fatih/color) from
1.17.0 to 1.18.0.
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<h2>v1.18.0</h2>
<h2>What's Changed</h2>
<ul>
<li>Add RGB API support by <a
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## Changes
Adding this notice allows us to collect telemetry for the CLI from the
next CLI version onwards.
---------
Co-authored-by: Julia Crawford (Databricks) <julia.crawford@databricks.com>
## Changes
Automatically trigger integration tests when a PR is opened or updated
## Tests
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---------
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>