## Changes
Currently, when the CLI run a list API call (like list jobs), it uses
the `List*All` methods from the SDK, which list all resources in the
collection. This is very slow for large collections: if you need to list
all jobs from a workspace that has 10,000+ jobs, you'll be waiting for
at least 100 RPCs to complete before seeing any output.
Instead of using List*All() methods, the SDK recently added an iterator
data structure that allows traversing the collection without needing to
completely list it first. New pages are fetched lazily if the next
requested item belongs to the next page. Using the List() methods that
return these iterators, the CLI can proactively print out some of the
response before the complete collection has been fetched.
This involves a pretty major rewrite of the rendering logic in `cmdio`.
The idea there is to define custom rendering logic based on the type of
the provided resource. There are three renderer interfaces:
1. textRenderer: supports printing something in a textual format (i.e.
not JSON, and not templated).
2. jsonRenderer: supports printing something in a pretty-printed JSON
format.
3. templateRenderer: supports printing something using a text template.
There are also three renderer implementations:
1. readerRenderer: supports printing a reader. This only implements the
textRenderer interface.
2. iteratorRenderer: supports printing a `listing.Iterator` from the Go
SDK. This implements jsonRenderer and templateRenderer, buffering 20
resources at a time before writing them to the output.
3. defaultRenderer: supports printing arbitrary resources (the previous
implementation).
Callers will either use `cmdio.Render()` for rendering individual
resources or `io.Reader` or `cmdio.RenderIterator()` for rendering an
iterator. This separate method is needed to safely be able to match on
the type of the iterator, since Go does not allow runtime type matches
on generic types with an existential type parameter.
One other change that needs to happen is to split the templates used for
text representation of list resources into a header template and a row
template. The template is now executed multiple times for List API
calls, but the header should only be printed once. To support this, I
have added `headerTemplate` to `cmdIO`, and I have also changed
`RenderWithTemplate` to include a `headerTemplate` parameter everywhere.
## Tests
- [x] Unit tests for text rendering logic
- [x] Unit test for reflection-based iterator construction.
---------
Co-authored-by: Andrew Nester <andrew.nester@databricks.com>
## Changes
This is a fundamental change to how we load and process bundle
configuration. We now depend on the configuration being represented as a
`dyn.Value`. This representation is functionally equivalent to Go's
`any` (it is variadic) and allows us to capture metadata associated with
a value, such as where it was defined (e.g. file, line, and column). It
also allows us to represent Go's zero values properly (e.g. empty
string, integer equal to 0, or boolean false).
Using this representation allows us to let the configuration model
deviate from the typed structure we have been relying on so far
(`config.Root`). We need to deviate from these types when using
variables for fields that are not a string themselves. For example,
using `${var.num_workers}` for an integer `workers` field was impossible
until now (though not implemented in this change).
The loader for a `dyn.Value` includes functionality to capture any and
all type mismatches between the user-defined configuration and the
expected types. These mismatches can be surfaced as validation errors in
future PRs.
Given that many mutators expect the typed struct to be the source of
truth, this change converts between the dynamic representation and the
typed representation on mutator entry and exit. Existing mutators can
continue to modify the typed representation and these modifications are
reflected in the dynamic representation (see `MarkMutatorEntry` and
`MarkMutatorExit` in `bundle/config/root.go`).
Required changes included in this change:
* The existing interpolation package is removed in favor of
`libs/dyn/dynvar`.
* Functionality to merge job clusters, job tasks, and pipeline clusters
are now all broken out into their own mutators.
To be implemented later:
* Allow variable references for non-string types.
* Surface diagnostics about the configuration provided by the user in
the validation output.
* Some mutators use a resource's configuration file path to resolve
related relative paths. These depend on `bundle/config/paths.Path` being
set and populated through `ConfigureConfigFilePath`. Instead, they
should interact with the dynamically typed configuration directly. Doing
this also unlocks being able to differentiate different base paths used
within a job (e.g. a task override with a relative path defined in a
directory other than the base job).
## Tests
* Existing unit tests pass (some have been modified to accommodate)
* Integration tests pass
## Changes
The JSON logger is excellent as a machine-readable logger with lots of
metadata, but the resulting logs are difficult to read:
<img width="1601" alt="Image_from_Databricks"
src="https://github.com/databricks/cli/assets/1850319/76aa852f-756f-4e0a-bc00-3a6e3224296a">
Currently, we only use the friendly log printer when run from a TTY.
This PR removes that restriction, so logs will be pretty-printed by
default, regardless of TTY or not. If a user needs machine-readable
logs, they can still use `--log-format JSON`.
## Tests
Manual test: `databricks current-user me --debug | cat` uses the
pretty-printing logger.
## Changes
Allow account client auth with environment variables when no
.databrickscfg file present
Makes the behaviour to be in line with WorkspaceClient auth.
## Tests
Added regression test
## Changes
It wasn't working because it deferred to the regular `slog.TextHandler`
for the `WithAttr` and `WithGroup` functions. Both of these functions
don't mutate the handler but return a new one. When the top-level logger
called one of these, log records in that context used the standard
handler instead of ours.
To implement tracking of attributes and groups, I followed the guide at
https://github.com/golang/example/blob/master/slog-handler-guide/README.md
for writing custom handlers.
## Tests
The new tests demonstrate formatting through `t.Log` and look good.
## Changes
We didn't return the error upon creating a workspace or account client.
If there is an error, it must always propagate up the stack. The result
of this bug was that we were setting a `nil` account or workspace
client, which in turn caused SIGSEGVs.
Fixes#913.
## Tests
Manually confirmed this fixes the linked issue. The CLI now correctly
returns an error when the client cannot be constructed.
The issue was reproducible using a `.databrickscfg` with a single,
incorrectly configured profile.
## Changes
`os.Getenv(..)` is not friendly with `libs/env`. This PR makes the
relevant changes to places where we need to read user home directory.
## Tests
Mainly done in https://github.com/databricks/cli/pull/914
## Changes
This will help differentiate multiple cli commands that write to the
same log file.
Noticed that the root module wasn't using the common log utilities,
refactored it to avoid missing log arguments.
Relevant PR on the databricks vscode extension side:
https://github.com/databricks/databricks-vscode/pull/923
## Tests
Tested manually for sdk and cli loggers
## Changes
If a bundle configuration specifies a workspace host, and the user
specifies a profile to use, we perform a check to confirm that the
workspace host in the bundle configuration and the workspace host from
the profile are identical. If they are not, we return an error. The
check was introduced in #571.
Previously, the code included an assumption that the client
configuration was already loaded from the environment prior to
performing the check. This was not the case, and as such if the user
intended to use a non-default path to `.databrickscfg`, this path was
not used when performing the check.
The fix does the following:
* Resolve the configuration prior to performing the check.
* Don't treat the configuration file not existing as an error.
* Add unit tests.
Fixes#884.
## Tests
Unit tests and manual confirmation.
## Changes
This is used for the sync command, where we need to ensure that a bundle
configuration never taints the authentication setup as prepared in the
environment (by our VS Code extension). Once the VS Code extension fully
builds on bundles, we can remove this check again.
## Tests
Manually confirmed that calling `databricks sync` from a bundle
directory no longer picks up its authentication configuration.
## Changes
The first stab at this was added in #837 but only included the
`NoPrompt` check in `MustAccountClient`. I renamed it to `SkipPrompt`
(in preparation for another option that skips bundle load) and made it
work for `MustWorkspaceClient` as well.
## Tests
Manually confirmed that the completion hook no longer prompts for a
profile (when called directly with `databricks __complete`).
## Changes
Fixes#836
## Tests
Manually running `sync` command with and without the flag
Integration tests pass as well
```
--- PASS: TestAccSyncFullFileSync (13.38s)
PASS
coverage: 39.1% of statements in ./...
ok github.com/databricks/cli/internal 14.148s coverage: 39.1% of statements in ./...
--- PASS: TestAccSyncIncrementalFileSync (11.38s)
PASS
coverage: 39.1% of statements in ./...
ok github.com/databricks/cli/internal 11.674s coverage: 39.1% of statements in ./...
```
## Changes
If the caller running the test has one or more environment variables
that are used in the test already set, they can interfere and make tests
fail.
## Tests
Ran tests in `./cmd/root` with Databricks related environment variables
set.
## Changes
The previous implementation ran the risk of infinite looping for the
account client due to a mismatch in determining what constitutes an
account client between the CLI and SDK (see
[here](83443bae8d/libs/databrickscfg/profiles.go (L61))
and
[here](0fdc5165e5/config/config.go (L160))).
Ultimately, this code must never infinite loop. If a user is prompted
and selects a profile that cannot be used, they should receive that
feedback immediately and try again, instead of being prompted again.
Related to #726.
## Tests
<!-- How is this tested? -->
## Changes
There are a couple places throughout the code base where interaction
with environment variables takes place. Moreover, more than one of these
would try to read a value from more than one environment variable as
fallback (for backwards compatibility). This change consolidates those
accesses.
The majority of diffs in this change are mechanical (i.e. add an
argument or replace a call).
This change:
* Moves common environment variable lookups for bundles to
`bundles/env`.
* Adds a `libs/env` package that wraps `os.LookupEnv` and `os.Getenv`
and allows for overrides to take place in a `context.Context`. By
scoping overrides to a `context.Context` we can avoid `t.Setenv` in
testing and unlock parallel test execution for integration tests.
* Updates call sites to pass through a `context.Context` where needed.
* For bundles, introduces `DATABRICKS_BUNDLE_ROOT` as new primary
variable instead of `BUNDLE_ROOT`. This was the last environment
variable that did not use the `DATABRICKS_` prefix.
## Tests
Unit tests pass.
## Changes
This reduces the latency of every workspace command by the duration of a
single API call to retrieve the current user (which can take up to a
full second).
Note: the better place to verify that a request can be authenticated is
the SDK itself.
## Tests
* Unit test to confirm an the empty `*http.Request` can be constructed
* Manually confirmed that the additional API call no longer happens
## Changes
This pull request extends the templating support in preparation of a
new, default template (WIP, https://github.com/databricks/cli/pull/686):
* builtin templates that can be initialized using e.g. `databricks
bundle init default-python`
* builtin templates are embedded into the executable using go's `embed`
functionality, making sure they're co-versioned with the CLI
* new helpers to get the workspace name, current user name, etc. help
craft a complete template
* (not enabled yet) when the user types `databricks bundle init` they
can interactively select the `default-python` template
And makes two tangentially related changes:
* IsServicePrincipal now uses the "users" API rather than the
"principals" API, since the latter is too slow for our purposes.
* mode: prod no longer requires the 'target.prod.git' setting. It's hard
to set that from a template. (Pieter is planning an overhaul of warnings
support; this would be one of the first warnings we show.)
The actual `default-python` template is maintained in a separate PR:
https://github.com/databricks/cli/pull/686
## Tests
Unit tests, manual testing
## Changes
Renamed Environments to Targets in bundle.yml.
The change is backward-compatible and customers can continue to use
`environments` in the time being.
## Tests
Added tests which checks that both `environments` and `targets` sections
in bundle.yml works correctly
## Changes
#629 introduced a change to autopopulate the host from .databrickscfg if
the user is logging back into a host they were previously using. This
did not respect the DATABRICKS_CONFIG_FILE env variable, causing the
flow to stop working for users with no .databrickscfg file in their home
directory.
This PR refactors all config file loading to go through one interface,
`databrickscfg.GetDatabricksCfg()`, and an auxiliary
`databrickscfg.GetDatabricksCfgPath()` to get the configured file path.
Closes#655.
## Tests
```
$ databricks auth login --profile abc
Error: open /Users/miles/.databrickscfg: no such file or directory
$ ./cli auth login --profile abc
Error: cannot load Databricks config file: open /Users/miles/.databrickscfg: no such file or directory
$ DATABRICKS_CONFIG_FILE=~/.databrickscfg.bak ./cli auth login --profile abc
Databricks Host: https://asdf
```
## Changes
This removes the remaining dependency on global state and unblocks work
to parallelize integration tests. As is, we can already uncomment an
integration test that had to be skipped because of other tests tainting
global state. This is no longer an issue.
Also see #595 and #606.
## Tests
* Unit and integration tests pass.
* Manually confirmed the help output is the same.
## Changes
This change is another step towards a CLI without globals. Also see #595.
The flags for the root command are now encapsulated in struct types.
## Tests
Unit tests pass.
## Changes
Generated commands relied on global variables for flags and request
payloads. This is difficult to test if a sequence of tests tries to run
the same command with various arguments because the global state causes
test interference. Moreover, it is impossible to run tests in parallel.
This change modifies the approach and turns every command group and
command itself into a function that returns a `*cobra.Command`. All
flags and request payloads are variables scoped to the command's
initialization function. This means it is possible to construct
independent copies of the CLI structure and fixes the test isolation
issue.
The scope of this change is only the generated commands. The other
commands will be changed accordingly in subsequent changes.
## Tests
Unit and integration tests pass.
## Changes
Correctly use --profile flag passed for all bundle commands.
Also adds a validation that if bundle configured host mismatches
provided profile, it throws an error.
Co-authored-by: Pieter Noordhuis <pieter.noordhuis@databricks.com>
## Changes
Currently, `databricks --profile <TAB>` autocompletes with the shell
default behavior, listing files in the local directory. This is not a
great experience. Especially given that the suggested profile names for
accounts are so long, it can be cumbersome to type them out by hand.
This PR configures autocompletion for `--profile` to inspect the
profiles of ~/.databrickscfg.
One potential improvement is to filter the response based on whether the
command is known to be account-level or workspace-level.
## Tests
Manual test.
<img width="579" alt="Screenshot_11_07_2023__18_31"
src="https://github.com/databricks/cli/assets/1850319/d7a3acd0-2511-45ac-bd82-95567775c10a">
## Changes
This includes the following changes:
* Move profile loading code to libs/databrickscfg and add tests
* Update prompt label to reflect workspace/account profiles
* Start prompt in search mode by default
* Custom error if `~/.databrickscfg` doesn't exist
* Custom error if `~/.databrickscfg` doesn't contain profiles
* Use stderr for prompt so that stdout redirection works (e.g. with `jq` or `jless`)
## Tests
* New unit tests pass
* Manual tests for both workspace and account commands
* Search-by-default is really nice if you have many profiles
## Changes
Added support for `bundle.Seq`, simplified `Mutator.Apply` interface by
removing list of mutators from return values/
## Tests
1. Ran `cli bundle deploy` and interrupted it with Cmd + C mid execution
so lock is not released
2. Ran `cli bundle deploy` top make sure that CLI is not trying to
release lock when it fail to acquire it
```
andrew.nester@HFW9Y94129 multiples-tasks % cli bundle deploy
Starting upload of bundle files
Uploaded bundle files at /Users/andrew.nester@databricks.com/.bundle/simple-task/development/files!
^C
andrew.nester@HFW9Y94129 multiples-tasks % cli bundle deploy
Error: deploy lock acquired by andrew.nester@databricks.com at 2023-05-24 12:10:23.050343 +0200 CEST. Use --force to override
```
## Changes
With this PR, all of the command below print version and exit:
```
$ databricks -v
Databricks CLI v0.100.1-dev+4d3fa76
$ databricks --version
Databricks CLI v0.100.1-dev+4d3fa76
$ databricks version
Databricks CLI v0.100.1-dev+4d3fa76
```
## Tests
Added integration test for each flag or command.
## Changes
Rename all instances of "bricks" to "databricks".
## Tests
* Confirmed the goreleaser build works, uses the correct new binary
name, and produces the right archives.
* Help output is confirmed to be correct.
* Output of `git grep -w bricks` is minimal with a couple changes
remaining for after the repository rename.
This PR adds the following command groups:
## Workspace-level command groups
* `bricks alerts` - The alerts API can be used to perform CRUD operations on alerts.
* `bricks catalogs` - A catalog is the first layer of Unity Catalog’s three-level namespace.
* `bricks cluster-policies` - Cluster policy limits the ability to configure clusters based on a set of rules.
* `bricks clusters` - The Clusters API allows you to create, start, edit, list, terminate, and delete clusters.
* `bricks current-user` - This API allows retrieving information about currently authenticated user or service principal.
* `bricks dashboards` - In general, there is little need to modify dashboards using the API.
* `bricks data-sources` - This API is provided to assist you in making new query objects.
* `bricks experiments` - MLflow Experiment tracking.
* `bricks external-locations` - An external location is an object that combines a cloud storage path with a storage credential that authorizes access to the cloud storage path.
* `bricks functions` - Functions implement User-Defined Functions (UDFs) in Unity Catalog.
* `bricks git-credentials` - Registers personal access token for Databricks to do operations on behalf of the user.
* `bricks global-init-scripts` - The Global Init Scripts API enables Workspace administrators to configure global initialization scripts for their workspace.
* `bricks grants` - In Unity Catalog, data is secure by default.
* `bricks groups` - Groups simplify identity management, making it easier to assign access to Databricks Workspace, data, and other securable objects.
* `bricks instance-pools` - Instance Pools API are used to create, edit, delete and list instance pools by using ready-to-use cloud instances which reduces a cluster start and auto-scaling times.
* `bricks instance-profiles` - The Instance Profiles API allows admins to add, list, and remove instance profiles that users can launch clusters with.
* `bricks ip-access-lists` - IP Access List enables admins to configure IP access lists.
* `bricks jobs` - The Jobs API allows you to create, edit, and delete jobs.
* `bricks libraries` - The Libraries API allows you to install and uninstall libraries and get the status of libraries on a cluster.
* `bricks metastores` - A metastore is the top-level container of objects in Unity Catalog.
* `bricks model-registry` - MLflow Model Registry commands.
* `bricks permissions` - Permissions API are used to create read, write, edit, update and manage access for various users on different objects and endpoints.
* `bricks pipelines` - The Delta Live Tables API allows you to create, edit, delete, start, and view details about pipelines.
* `bricks policy-families` - View available policy families.
* `bricks providers` - Databricks Providers REST API.
* `bricks queries` - These endpoints are used for CRUD operations on query definitions.
* `bricks query-history` - Access the history of queries through SQL warehouses.
* `bricks recipient-activation` - Databricks Recipient Activation REST API.
* `bricks recipients` - Databricks Recipients REST API.
* `bricks repos` - The Repos API allows users to manage their git repos.
* `bricks schemas` - A schema (also called a database) is the second layer of Unity Catalog’s three-level namespace.
* `bricks secrets` - The Secrets API allows you to manage secrets, secret scopes, and access permissions.
* `bricks service-principals` - Identities for use with jobs, automated tools, and systems such as scripts, apps, and CI/CD platforms.
* `bricks serving-endpoints` - The Serving Endpoints API allows you to create, update, and delete model serving endpoints.
* `bricks shares` - Databricks Shares REST API.
* `bricks storage-credentials` - A storage credential represents an authentication and authorization mechanism for accessing data stored on your cloud tenant.
* `bricks table-constraints` - Primary key and foreign key constraints encode relationships between fields in tables.
* `bricks tables` - A table resides in the third layer of Unity Catalog’s three-level namespace.
* `bricks token-management` - Enables administrators to get all tokens and delete tokens for other users.
* `bricks tokens` - The Token API allows you to create, list, and revoke tokens that can be used to authenticate and access Databricks REST APIs.
* `bricks users` - User identities recognized by Databricks and represented by email addresses.
* `bricks volumes` - Volumes are a Unity Catalog (UC) capability for accessing, storing, governing, organizing and processing files.
* `bricks warehouses` - A SQL warehouse is a compute resource that lets you run SQL commands on data objects within Databricks SQL.
* `bricks workspace` - The Workspace API allows you to list, import, export, and delete notebooks and folders.
* `bricks workspace-conf` - This API allows updating known workspace settings for advanced users.
## Account-level command groups
* `bricks account billable-usage` - This API allows you to download billable usage logs for the specified account and date range.
* `bricks account budgets` - These APIs manage budget configuration including notifications for exceeding a budget for a period.
* `bricks account credentials` - These APIs manage credential configurations for this workspace.
* `bricks account custom-app-integration` - These APIs enable administrators to manage custom oauth app integrations, which is required for adding/using Custom OAuth App Integration like Tableau Cloud for Databricks in AWS cloud.
* `bricks account encryption-keys` - These APIs manage encryption key configurations for this workspace (optional).
* `bricks account groups` - Groups simplify identity management, making it easier to assign access to Databricks Account, data, and other securable objects.
* `bricks account ip-access-lists` - The Accounts IP Access List API enables account admins to configure IP access lists for access to the account console.
* `bricks account log-delivery` - These APIs manage log delivery configurations for this account.
* `bricks account metastore-assignments` - These APIs manage metastore assignments to a workspace.
* `bricks account metastores` - These APIs manage Unity Catalog metastores for an account.
* `bricks account networks` - These APIs manage network configurations for customer-managed VPCs (optional).
* `bricks account o-auth-enrollment` - These APIs enable administrators to enroll OAuth for their accounts, which is required for adding/using any OAuth published/custom application integration.
* `bricks account private-access` - These APIs manage private access settings for this account.
* `bricks account published-app-integration` - These APIs enable administrators to manage published oauth app integrations, which is required for adding/using Published OAuth App Integration like Tableau Cloud for Databricks in AWS cloud.
* `bricks account service-principals` - Identities for use with jobs, automated tools, and systems such as scripts, apps, and CI/CD platforms.
* `bricks account storage` - These APIs manage storage configurations for this workspace.
* `bricks account storage-credentials` - These APIs manage storage credentials for a particular metastore.
* `bricks account users` - User identities recognized by Databricks and represented by email addresses.
* `bricks account vpc-endpoints` - These APIs manage VPC endpoint configurations for this account.
* `bricks account workspace-assignment` - The Workspace Permission Assignment API allows you to manage workspace permissions for principals in your account.
* `bricks account workspaces` - These APIs manage workspaces for this account.
## Changes
<!-- Summary of your changes that are easy to understand -->
1. Log os.Args and bricks version before every command execution
2. After a command execution, logs the error and exit code
## Tests
<!-- How is this tested? -->
Manually,
case 1: Run `bricks version` successfully
```
shreyas.goenka@THW32HFW6T bricks % bricks version --log-level=info --log-file stderr
time=2023-04-12T00:15:04.011+02:00 level=INFO source=root.go:34 msg="process args: [bricks, version, --log-level=info, --log-file, stderr]"
time=2023-04-12T00:15:04.011+02:00 level=INFO source=root.go:35 msg="version: 0.0.0-dev+375eb1c50283"
0.0.0-dev+375eb1c50283
time=2023-04-12T00:15:04.011+02:00 level=INFO source=root.go:68 msg="exit code: 0"
```
case 2: Run `bricks bundle deploy` in a working dir where `bundle.yml`
does not exist
```
shreyas.goenka@THW32HFW6T bricks % bricks bundle deploy --log-level=info --log-file=stderr
time=2023-04-12T00:19:16.783+02:00 level=INFO source=root.go:34 msg="process args: [bricks, bundle, deploy, --log-level=info, --log-file=stderr]"
time=2023-04-12T00:19:16.784+02:00 level=INFO source=root.go:35 msg="version: 0.0.0-dev+375eb1c50283"
Error: unable to locate bundle root: bundle.yml not found
time=2023-04-12T00:19:16.784+02:00 level=ERROR source=root.go:64 msg="unable to locate bundle root: bundle.yml not found"
time=2023-04-12T00:19:16.784+02:00 level=ERROR source=root.go:65 msg="exit code: 1"
```
New global flags:
* `--log-file FILE`: can be literal `stdout`, `stderr`, or a file name (default `stderr`)
* `--log-level LEVEL`: can be `error`, `warn`, `info`, `debug`, `trace`, or `disabled` (default `disabled`)
* `--log-format TYPE`: can be `text` or `json` (default `text`)
New functions in the `log` package take a `context.Context` and retrieve
the logger from said context.
Because we carry the logger in a context, adding
[attributes](https://pkg.go.dev/golang.org/x/exp/slog#hdr-Attrs_and_Values)
to the logger can be done as follows:
```go
ctx = log.NewContext(ctx, log.GetLogger(ctx).With("foo", "bar"))
```
Andrew Nester
Miles Yucht
Pieter Noordhuis
shreyas-goenka
Serge Smertin
Ilia Babanov
Lennart Kats (databricks)
Fabian Jakobs
