* Add `batch_id` to jinja context of microbatch batches
* Add changie doc
* Update `format_batch_start` to assume `batch_start` is always provided
* Add "runtime only" property `batch_context` to `ModelNode`
By it being "runtime only" we mean that it doesn't exist on the artifact
and thus won't be written out to the manifest artifact.
* Begin populating `batch_context` during materialization execution for microbatch batches
* Fix circular import
* Fixup MicrobatchBuilder.batch_id property method
* Ensure MicrobatchModelRunner doesn't double compile batches
We were compiling the node for each batch _twice_. Besides making microbatch
models more expensive than they needed to be, double compiling wasn't
causing any issue. However the first compilation was happening _before_ we
had added the batch context information to the model node for the batch. This
was leading to models which try to access the `batch_context` information on the
model to blow up, which was undesirable. As such, we've now gone and skipped
the first compilation. We've done this similar to how SavedQuery nodes skip
compilation.
* Add `__post_serialize__` method to `BatchContext` to ensure correct dict shape
This is weird, but necessary, I apologize. Mashumaro handles the
dictification of this class via a compile time generated `to_dict`
method based off of the _typing_ of th class. By default `datetime`
types are converted to strings. We don't want that, we want them to
stay datetimes.
* Update tests to check for `batch_context`
* Update `resolve_event_time_filter` to use new `batch_context`
* Stop testing for batchless compiled code for microbatch models
In 45daec72f4 we stopped an extra compilation
that was happening per batch prior to the batch_context being loaded. Stopping
this extra compilation means that compiled sql for the microbatch model without
the event time filter / batch context is no longer produced. We have discussed
this and _believe_ it is okay given that this is a new node type that has not
hit GA yet.
* Rename `ModelNode.batch_context` to `ModelNode.batch`
* Rename `build_batch_context` to `build_jinja_context_for_batch`
The name `build_batch_context` was confusing as
1) We have a `BatchContext` object, which the method was not building
2) The method builds the jinja context for the batch
As such it felt appropriate to rename the method to more accurately
communicate what it does.
* Rename test macro `invalid_batch_context_macro_sql` to `invalid_batch_jinja_context_macro_sql`
This rename was to make it more clear that the jinja context for a
batch was being checked, as a batch_context has a slightly different
connotation.
* Update changie doc
* Rename `batch_info` to `previous_batch_results`
* Exclude `previous_batch_results` from serialization of model node to avoid jinja context bloat
* Drop `previous_batch_results` key from `test_manifest.py` unit tests
In 4050e377ec01c2f14dd9600fe704ddb34adb66fa we began excluding
`previous_batch_results` from the serialized representation of the
ModelNode. As such, we no longer need to check for it in `test_manifest.py`.
* Clean up changelog on main
* Bumping version to 1.10.0a1
* Code quality cleanup
* add 1.8,1.9 link
---------
Co-authored-by: Emily Rockman <emily.rockman@dbtlabs.com>
* Allow `dbt show` and `dbt compile` to output JSON without extra logs
* Add `quiet` attribute for ShowNode and CompiledNode messages
* Output of protoc compiler
* Utilize the `quiet` attribute for ShowNode and CompiledNode
* Reuse the `dbt list` approach when the `--quiet` flag is used
* Use PrintEvent to get to stdout even if the logger is set to ERROR
* Functional tests for quiet compile
* Functional tests for quiet show
* Fire event same way regardless if LOG_FORMAT is json or not
* Switch back to firing ShowNode and CompiledNode events
* Make `--inline-direct` to be quiet-compatible
* Temporarily change to dev branch for dbt-common
* Remove extraneous newline
* Functional test for `--quiet` for `--inline-direct` flag
* Update changelog entry
* Update `core_types_pb2.py`
* Restore the original branch in `dev-requirements.txt`
---------
Co-authored-by: Kshitij Aranke <kshitij.aranke@dbtlabs.com>
This is needed for dbt-core + dbt-adapters to work properly in regards to
the microbatch project_flag/behavior flag `require_batched_execution_for_custom_microbatch_strategy`
* first pass: replace os env with project flag
* Fix `TestMicrobatchMultipleRetries` to not use `os.env`
* Turn off microbatch project flag for `TestMicrobatchCustomUserStrategyDefault` as it was prior to a9df50f
* Update `BaseMicrobatchTest` to turn on microbatch via project flags
* Add changie doc
* Fix functional tests after merging in main
* Add function to that determines whether the new microbatch functionality should be used
The new microbatch functionality is, unfortunately, potentially dangerous. That is
it adds a new materalization strategy `microbatch` which an end user could have
defined as a custom strategy previously. Additionally we added config keys to nodes,
and as `config` is just a Dict[str, Any], it could contain anything, thus meaning
people could already be using the configs we're adding for different purposes. Thus
we need some intellegent gating. Specifically something that adheres to the following:
cms = Custom Microbatch Strategy
abms = Adapter Builtin Microbatch Strategy
bf = Behavior flag
umb = Use Microbatch Batching
t/f/e = True/False/Error
| cms | abms | bf | umb |
| t | t | t | t |
| f | t | t | t |
| t | f | t | t |
| f | f | t | e |
| t | t | f | f |
| f | t | f | t |
| t | f | f | f |
| f | f | f | e |
(The above table assumes that there is a microbatch model present in the project)
In order to achieve this we need to check that either the microbatch behavior
flag is set to true OR microbatch materializaion being used is the _root_ microbatch
materialization (i.e. not custom). The function we added in this commit,
`use_microbatch_batches`, does just that.
* Gate microbatch functionality by `use_microbatch_batches` manifest function
* Rename microbatch behavior flag to `require_batched_execution_for_custom_microbatch_strategy`
* Extract logic of `find_macro_by_name` to `find_macro_candiate_by_name`
In 0349968c615444de05360509ddeaf6d75d41d826 I had done this for the function
`find_materialization_macro_by_name`, but that wasn't the right function to
do it to, and will be reverted shortly. `find_materialization_macro_by_name`
is used for finding the general materialization macro, whereas `find_macro_by_name`
is more general. For the work we're doing, we need to find the microbatch
macro, which is not a materialization macro.
* Use `find_macro_candidate_by_name` to find the microbatch macro
* Fix microbatch macro locality check to search for `core` locality instead of `root`
Previously were were checking for a locality of `root`. However, a locality
of `root` means it was provided by a `package`. We wnt to check for locality
of `core` which basically means `builtin via dbt-core/adapters`. There is
another locality `imported` which I beleive means it comes from another
package.
* Move the evaluation of `use_microbatch_batches` to the last position in boolean checks
The method `use_microbatch_batches` is always invoked to evaluate an `if`
statement. In most instances, it is part of a logic chain (i.e. there are
multiple things being evaluated in the `if` statement). In `if` statements
where there are multiple things being evaulated, `use_microbatch_batches`
should come _last_ (or as late as possible). This is because it is likely
the most costly thing to evaluate in the logic chain, and thus any shortcuts
cuts via other evaluations in the if statement failing (and thus avoiding
invoking `use_microbatch_batches) is desirable.
* Drop behavior flag setting for BaseMicrobatchTest tests
* Rename 'env_var' to 'project_flag' in test_microbatch.py
* Update microbatch tests to assert when we are/aren't running with batches
* Update `test_resolve_event_time_filter` to use `use_microbatch_batches`
* Fire deprecation warning for custom microbatch macros
* Add microbatch deprecation events to test_events.py
---------
Co-authored-by: Quigley Malcolm <quigley.malcolm@dbtlabs.com>
* Add new `ArtifactWritten` event
* Emit ArtifactWritten event whenever an artifact is written
* Get artifact_type from class name for ArtifactWritten event
* Add changie docs
* Add test to check that ArtifactWritten events are being emitted
* Regenerate core_types_pb2.py using correct protobuf version
* Regen core_types_pb2 again, using a more correct protoc version
* Add unit tests to check how `safe_run_hooks` handles exceptions
* Improve exception handling in `get_execution_status`
Previously in `get_execution_status` if a non `DbtRuntimeError` exception was
raised, the finally would be entered, but the `status`/`message` would not be
set, and thus a `status not defined` exception would get raised on attempting
to return. Tangentially, there is another issue where somehow the `node_status`
is becoming `None`. In all my playing with `get_execution_status` I found that
trying to return an undefined variable in the `finally` caused an undefined
variable exception. However, if in some python version, it instead just handed
back `None`, then this fix should also solve that.
* Add changie docs
* Ensure run_results get written if KeyboardInterrupt happens during end run hooks
* Bump minimum dbt-adpaters to 1.8.0
In https://github.com/dbt-labs/dbt-core/pull/10859 we started using the
`get_adapter_run_info` method provided by `dbt-adapters`. However that
function is only available in dbt-adapters >= 1.8.0. Thus 1.8.0 is our
new minimum for dbt-adapters.
* Add changie doc
* Add function to MicrobatchBuilder to get ceiling of timestamp by batch_size
* Update `MicrobatchBuilder.build_end_time` to use `ceiling_timestamp`
* fix TestMicrobatchBuilder.test_build_end_time by specifying a BatchSize + asserting actual is a ceiling timestamp
* Add changie
---------
Co-authored-by: Michelle Ark <michelle.ark@dbtlabs.com>
* Stop validating that `--event-time-start` is before "current" time
In the next commit we'll be adding a validation that requires that `--event-time-start`
and `--event-time-end` are mutually required. That is, whenever one is specified,
the other is required. In that world, `--event-time-start` will never need to be compared
against the "current" time, because it'll never be run in conjunction with the "current"
time.
* Validate that `--event-time-start` and `--event-time-end` are mutually present
* Add changie doc for validation changes
* Alter functional microbatch tests to work with updated `event_time_start/end` reqs
We made it such that when `event_time_start` is specified, `event_time_end` must also
be specified (and vice versa). This broke numerous tests, in a few different ways:
1. There were tests that used `--event-time-start` without `--event-time-end` butg
were using event_time_start essentially as the `begin` time for models being initially
built or full refreshed. These tests could simply drop the `--event-time-start` and
instead rely on the `begin` value.
2. There was a test that was trying to load a subset of the data _excluding_ some
data which would be captured by using `begin`. In this test we added an appropriate
`--event-time-end` as the `--event-time-start` was necessary to statisfy what the
test was testing
3. There was a test which was trying to ensure that two microbatch models would be
given the same "current" time. Because we wanted to ensure the "current" time code
path was used, we couldn't add `--event-time-end` to resolve the problem, thus we
needed to remove the `--event-time-start` that was being used. However, this led to
the test being incredibly slow. This was resolved by switching the relevant microbatch
models from having `batch_size`s of `day` to instead have `year`. This solution should
be good enough for roughly ~40 years? We'll figure out a better solution then, so see ya
in 2064. Assuming I haven't died before my 70th birthday, feel free to ping me to get
this taken care of.
---------
Co-authored-by: Michelle Ark <michelle.ark@dbtlabs.com>
* Add adapter telemetry to snowplow event.
* Temporary dev branch switch.
* Set tracking for overrideable adapter method.
* Do safer adapter ref.
* Improve comment.
* Code review comments.
* Don't call the asdict on a dict.
* Bump ci to pull in fix from base adapter.
* Add unit tests for coverage.
* Update field name from base adapter/schema change.
* remove breakpoint.
* Change `lookback` default from `0` to `1`
* Regen jsonschema manifest v12 to include `lookback` default change
* Regen saved state of v12 manifest for functional artifact testing
* Add changie doc for lookback default change
* Avoid a KeyError if `child_unique_id` is not found in the dictionary
* Changelog entry
* Functional test when an exposure references a deprecated model
dbt-adapters updated the incremental_strategy validation of incremental models such that
the validation now _always_ happens when an incremental model is executed. A test in dbt-core
`TestMicrobatchCustomUserStrategyEnvVarTrueInvalid` was previously set to _expect_ buggy behavior
where an incremental model would succeed on it's "first"/"refresh" run even if it had an invalid
incremental strategy. Thus we needed to update this test in dbt-core to expect the now correct
behavior of incremental model execution time validation
* [Tidy-First]: Fix `timings` object for hooks and macros, and make types of timings explicit
* cast literal to str
* change test
* change jsonschema to enum
* Discard changes to schemas/dbt/manifest/v12.json
* nits
---------
Co-authored-by: Chenyu Li <chenyu.li@dbtlabs.com>
* Add `order_by` and `limit` fields to saved queries.
* Update JSON schema
* Add change log for #10531.
* Check order by / limit in saved-query parsing test.
* Add test that checks microbatch models are all operating with the same `current_time`
* Set an `invocated_at` on the `RuntimeConfig` and plumb to `MicrobatchBuilder`
* Add changie doc
* Rename `invocated_at` to `invoked_at`
* Simply conditional logic for setting MicrobatchBuilder.batch_current_time
* Rename `batch_current_time` to `default_end_time` for MicrobatchBuilder
* Begin testing that microbatch execution times are being tracked and set
* Begin tracking the execution time of batches for microbatch models
* Add changie doc
* Additional assertions in microbatch testing
* Validate that `event_time_start` is before `event_time_end` when passed from CLI
Sometimes CLI options have restrictions based on other CLI options. This is the case
for `--event-time-start` and `--event-time-end`. Unfortunately, click doesn't provide
a good way for validating this, at least not that I found. Additionaly I'm not sure
if we have had anything like this previously. In any case, I couldn't find a
centralized validation area for such occurances. Thus I've gone and added one,
`validate_option_interactions`. Long term if more validations are added, we should
add this wrapper to each CLI command. For now I've only added it to the commands that
support `event_time_start` and `event_time_end`, specifically `build` and `run`.
* Add changie doc
* If `--event-time-end` is not specififed, ensure `--event-time-start` is less than the current time
* Fixup error message about event_time_start and event_time_end
* Move logic to validate `event_time` cli flags to `flags.py`
* Update validation of `--event-time-start` against `datetime.now` to use UTC
* When retrying microbatch models, propagate prior successful state
* Changie doc for microbatch dbt retry fixes
* Fix test_manifest unit tests for batch_info key
* Add functional test for when a microbatch model has multiple retries
* Add comment about when batch_info will be something other than None
* Add tests to check how microbatch models respect `full_refresh` model configs
* Fix `_is_incremental` to properly respect `full_refresh` model config
In dbt-core, it is generally expected that values passed via CLI flags take
precedence over model level configs. However, `full_refresh` on a model is an
exception to this rule, where in the model config takes precedence. This
config exists specifically to _prevent_ accidental full refreshes of large
incremental models, as doing so can be costly. **_It is actually best
practice_** to set `full_refresh=False` on incremental models.
Prior to this commit, for microbatch models, the above was not happening. The
CLI flag `--full-refresh` was taking precedence over the model config
`full_refresh`. That meant that if `--full-refresh` was supplied, then the
microbatch model **_would full refresh_** even if `full_refresh=False` was
set on the model. This commit solves that problem.
* Add changie doc for microbatch `full_refresh` config handling
* Add `PartialSuccess` status type and use it for microbatch models with mixed results
* Handle `PartialSuccess` in `interpret_run_result`
* Add `BatchResults` object to `BaseResult` and begin tracking during microbatch runs
* Ensure batch_results being propagated to `run_results` artifact
* Move `batch_results` from `BaseResult` class to `RunResult` class
* Move `BatchResults` and `BatchType` to separate arifacts file to avoid circular imports
In our next commit we're gonna modify `dbt/contracts/graph/nodes.py` to import the
`BatchType` as part of our work to implement dbt retry for microbatch model nodes.
Unfortunately, the import in `nodes.py` creates a circular dependency because
`dbt/artifacts/schemas/results.py` imports from `nodes.py` and `dbt/artifacts/schemas/run/v5/run.py`
imports from that `results.py`. Thus the new import creates a circular import. Now this
_shouldn't_ be necessary as nothing in artifacts should import from the rest of dbt-core.
However, we do. We should fix this, but this is also out of scope for this segement of work.
* Add `PartialSuccess` as a retry-able status, and use batches to retry microbatch models
* Fix BatchType type so that the first datetime is no longer Optional
* Ensure `PartialSuccess` causes skipping of downstream nodes
* Alter `PartialSuccess` status to be considered an error in `interpret_run_result`
* Update schemas and test artifacts to include new batch_results run results key
* Add functional test to check that 'dbt retry' retries 'PartialSuccess' models
* Update partition failure test to assert downstream models are skipped
* Improve `success`/`error`/`partial success` messaging for microbatch models
* Include `PartialSuccess` in status that `--fail-fast` counts as a failure
* Update `LogModelResult` to handle partial successes
* Update `EndOfRunSummary` to handle partial successes
* Cleanup TODO comment
* Raise a DbtInternalError if we get a batch run result without `batch_results`
* When running a microbatch model with supplied batches, force non full-refresh behavior
This is necessary because of retry. Say on the initial run the microbatch model
succeeds on 97% of it's batches. Then on retry it does the last 3%. If the retry
of the microbatch model executes in full refresh mode it _might_ blow away the
97% of work that has been done. This edge case seems to be adapter specific.
* Only pass batches to retry for microbatch model when there was a PartialSuccess
In the previous commit we made it so that retries of microbatch models wouldn't
run in full refresh mode when the microbatch model to retry has batches already
specified from the prior run. This is only problematic when the run being retried
was a full refresh AND all the batches for a given microbatch model failed. In
that case WE DO want to do a full refresh for the given microbatch model. To better
outline the problem, consider the following:
* a microbatch model had a begin of `2020-01-01` and has been running this way for awhile
* the begin config has changed to `2024-01-01` and dbt run --full-refresh gets run
* every batch for an microbatch model fails
* on dbt retry the the relation is said to exist, and the now out of range data (2020-01-01 through 2023-12-31) is never purged
To avoid this, all we have to do is ONLY pass the batch information for partially successful microbatch
models. Note: microbatch models only have a partially successful status IFF they have both
successful and failed batches.
* Fix test_manifest unit tests to know about model 'batches' key
* Add some console output assertions to microbatch functional tests
* add batch_results: None to expected_run_results
* Add changie doc for microbatch retry functionality
* maintain protoc version 5.26.1
* Cleanup extraneous comment in LogModelResult
---------
Co-authored-by: Michelle Ark <michelle.ark@dbtlabs.com>
* Test case for `merge_exclude_columns`
* Update expected output for `merge_exclude_columns`
* Skip TestMergeExcludeColumns test
* Enable this test since PostgreSQL 15+ is available in CI now
* Undo modification to expected output
* Remove duplicated constructor for `ResourceTypeSelector`
* Add type annotation for `ResourceTypeSelector`
* Standardize on constructor for `ResourceTypeSelector` where `include_empty_nodes=True`
* Changelog entry
* Adding logic to TestSelector to remove unit tests if they are in excluded_resource_types
* Adding change log
* Respect `--resource-type` and `--exclude-resource-type` CLI flags and associated environment variables
* Test CLI flag for excluding unit tests for the `dbt test` command
* Satisy isort pre-commit hook
* Fix mypy for positional argument "resource_types" in call to "TestSelector"
* Replace `TestSelector` with `ResourceTypeSelector`
* Add co-author
* Update changelog description
* Add functional tests for new feature
* Compare the actual results, not just the count
* Remove test case covered elsewhere
* Test for `DBT_EXCLUDE_RESOURCE_TYPES` environment variable for `dbt test`
* Update per pre-commit hook
* Restore to original form (until we refactor extraneous `ResourceTypeSelector` references later)
---------
Co-authored-by: Matthew Cooper <asimov.1st@gmail.com>
* initial rough-in with CLI flags
* dbt-adapters testing against event-time-ref-filtering
* fix TestList
* Checkpoint
* fix tests
* add event_time_start params to build
* rename configs
* Gate resolve_event_time_filter via micro batch strategy and fix strptime usage
* Add unit test for resolve_event_time_filter
* Additional unit tests for `resolve_event_time_filter` to ensure lookback + batch_size work
* Remove extraneous comments and print statements from resolve_event_time_filter
* Fixup microbatch functional tests to use microbatch strategy
* Gate microbatch functionality behind env_var while in beta
* Add comment about how _is_incremental should be removed
* Improve `event_time_start/end` cli parameters to auto convert to datetime objects
* for testing: dbt-postgres 'microbatch' strategy
* rough in: chunked backfills
* partial failure of microbatch runs
* decouple run result methods
* initial refactor
* rename configs to __dbt_internal
* update compiled_code in context after re-compilation
* finish rename of context vars
* changelog entry
* fix patch_microbatch_end_time
* refactor into MicrobatchBuilder
* fix provider unit tests + add unit tests for MicrobatchBuilder
* add TestMicrobatchJinjaContextVarsAvailable
* unit test offset + truncate timestamp methods
* Remove pairing.md file
* Add tying to microbatch specific functions added in `task/run.py`
* Add doc strings to microbatch.py functions and classes
* Set microbatch node status to `ERROR` if all batches for node failed
* Fire an event for batch exceptions instead of directly printing
* Fix firing of failed microbatch log event
---------
Co-authored-by: Quigley Malcolm <quigley.malcolm@dbtlabs.com>
* Update functional tests to cover this case
* Revert "Update functional tests to cover this case"
This reverts commit 4c78e816f6c370b7a39df774f2fab7328db5312b.
* New functional tests to cover the resource_type config
* Separate data tests from unit tests for `resource_types` config of `dbt list` and `dbt build`
* Changelog entry
* Add functional tests for custom incremental strategies names 'microbatch'
* Point dev-requirement of `dbt-adapters` back to the main branch
The associated branch/PR in `dbt-adapters` that we were previously
pointing to has been merged. Thus we can point back to `main` again.
---------
Co-authored-by: Quigley Malcolm <quigley.malcolm@dbtlabs.com>
* made class changing directory a context manager.
* add change log
* fix conflict
* made base as a context manager
* add assertion
* Remove index.html
* add it test to testDbtRunner
* fix deps args order
* fix test
---------
Co-authored-by: Doug Beatty <doug.beatty@dbtlabs.com>
Co-authored-by: Chenyu Li <chenyu.li@dbtlabs.com>
* use full manifest in adapter instead of macro_manifest
* Add test case
* Add changelog entry
* Remove commented code.
---------
Co-authored-by: Peter Allen Webb <peter.webb@dbtlabs.com>
* Tests for calling a macro in a pre- or post-hook config in properties.yml
* Late render pre- and post-hooks configs in properties / schema YAML files
* Changelog entry
* Use alias instead of name when adding ephemeral model prefixes
* Adjust TestCustomSchemaWithCustomMacroFromModelName to test ephemeral models
* Add changelog entry for ephemeral model CTE identifier fix
* Reference model.identifier and model.name where appropriate to resolve typing errors
* Move test for ephemeral model with alias to dedicated test in test_compile.py
* update children search
* update search to include children in original selector
* add changie
* remove unused function
* fix wrong function call
* fix depth
* sketch
* Bring back the happy path fixture snapshot file
The commit c783a86 removed the snapshot file from the happy path fixture.
This was done because the snapshot was breaking the tests we were adding,
`test_run_commands`. However this broke `test_ls` in `test_list.py`. In order
to move forward, we need everything to be working. Maybe the idea was to delete
the `test_list.py` file, however that is not noted anywhere, and was not done.
Thus this commit ensures that test is not broken nor or new tests.
* Create conftest for `functional` tests so that happy path fixtures are accessible
* Format `test_commands.py` and update imports to appease pre-commit hooks
* Parametrize `test_run_command` to make it easier to see which command is failing (if any)
* Update the setup for `TestRunCommands.test_run_command` to be more formulaic
* Add test to ensure resource types are selectable
* Fix docstring formatting in TestRunCommands
* Fixup documentation for test_commands.py
---------
Co-authored-by: Chenyu Li <chenyu.li@dbtlabs.com>
* Add breakpoint.
* Move breakpoint.
* Add fix
* Add changelog.
* Avoid sorting for the string case.
* Add unit test.
* Fix test.
* add good unit tests for coverage of sort method.
* add sql format coverage.
* Modify behavior to log a warning and proceed.
* code review comments.
---------
Co-authored-by: Mila Page <versusfacit@users.noreply.github.com>
* Fix exclusive_primary_alt_value_setting to set warn_error_options correctly
* Add test
* Changie
* Fix unit test
* Replace conversion method
* Refactor normalize_warn_error_options
* Add changelog.
* Avoid sorting for the string case.
* add good unit tests for coverage of sort method.
* add sql format coverage.
---------
Co-authored-by: Mila Page <versusfacit@users.noreply.github.com>
* Correct `isort` configuration to include dbt-semantic-interfaces as internal
We thought we were already doing this. However, we accidentally missed the last
`s` of `dbt-semantic-interfaces`, so imports from dbt-semantic-interfaces were not
being identified as an internal package by isort. This fixes that.
* Run isort using updated configs to mark `dbt-semantic-interfaces` as included
* Fix `test_can_silence` tests in `test_warn_error_options.py` to ensure silencing
We're fixing an issue wherein `silence` specifications in the `dbt_project.yaml`
weren't being respected. This was odd since we had tests specifically for this.
It turns out the tests were broken. Essentially the warning was instead being raised
as an error due to `include: 'all'`. Then because it was being raised as an error,
the event wasn't going through the logger. We were only asserting in these tests that
the silenced event wasn't going through the logger (which it wasn't) so everything
"appeared" to be working. Unfortunately everything wasn't actually working. This is now
highlighted because `test_warn_error_options::TestWarnErrorOptionsFromProject:test_can_silence`
is now failing with this commit.
* Fix setting `warn_error_options` via `dbt_project.yaml` flags.
Back when I did the work for #10058 (specifically c52d6531) I thought that
the `warn_error_options` would automatically be converted from the yaml
to the `WarnErrorOptions` object as we were building the `ProjectFlags` object,
which holds `warn_error_options`, via `ProjectFlags.from_dict`. And I thought
this was validated by the `test_can_silence` test added in c52d6531. However,
there were two problems:
1. The definition of `warn_error_options` on `PrjectFlags` is a dict, not a
`WarnErrorOptions` object
2. The `test_can_silence` test was broken, and not testing what I thought
The quick fix (this commit) is to ensure `silence` is passed to `WarnErrorOptions`
instantiation in `dbt.cli.flags.convert_config`. The better fix would be to make
the `warn_error_options` of `ProjectFlags` a `WarnErrorOptions` object instead of
a dict. However, to do this we first need to update dbt-common's `WarnErrorOptions`
definition to default `include` to an empty list. Doing so would allow us to get rid
of `convert_config` entirely.
* Add unit test for `ModelRunner.print_result_line`
* Add (and skip) unit test for `ModelRunner.execute`
An attempt at testing `ModelRunner.execute`. We should probably also be
asserting that the model has been executed. However before we could get there,
we're running into runtime errors during `ModelRunner.execute`. Currently the
struggle is ensuring the adapter exists in the global factory when `execute`
goes looking for. The error we're getting looks like the following:
```
def test_execute(self, table_model: ModelNode, manifest: Manifest, model_runner: ModelRunner) -> None:
> model_runner.execute(model=table_model, manifest=manifest)
tests/unit/task/test_run.py:121:
----
core/dbt/task/run.py:259: in execute
context = generate_runtime_model_context(model, self.config, manifest)
core/dbt/context/providers.py:1636: in generate_runtime_model_context
ctx = ModelContext(model, config, manifest, RuntimeProvider(), None)
core/dbt/context/providers.py:834: in __init__
self.adapter = get_adapter(self.config)
venv/lib/python3.10/site-packages/dbt/adapters/factory.py:207: in get_adapter
return FACTORY.lookup_adapter(config.credentials.type)
---`
self = <dbt.adapters.factory.AdapterContainer object at 0x106e73280>, adapter_name = 'postgres'
def lookup_adapter(self, adapter_name: str) -> Adapter:
> return self.adapters[adapter_name]
E KeyError: 'postgres'
venv/lib/python3.10/site-packages/dbt/adapters/factory.py:132: KeyError
```
* Add `postgres_adapter` fixture for use in `TestModelRunner`
Previously we were running into an issue where the during `ModelRunner.execute`
the mock_adapter we were using wouldn't be found in the global adapter
factory. We've gotten past this error by supply a "real" adapter, a
`PostgresAdapter` instance. However we're now running into a new error
in which the materialization macro can't be found. This error looks like
```
model_runner = <dbt.task.run.ModelRunner object at 0x106746650>
def test_execute(
self, table_model: ModelNode, manifest: Manifest, model_runner: ModelRunner
) -> None:
> model_runner.execute(model=table_model, manifest=manifest)
tests/unit/task/test_run.py:129:
----
self = <dbt.task.run.ModelRunner object at 0x106746650>
model = ModelNode(database='dbt', schema='dbt_schema', name='table_model', resource_type=<NodeType.Model: 'model'>, package_na...ected'>, constraints=[], version=None, latest_version=None, deprecation_date=None, defer_relation=None, primary_key=[])
manifest = Manifest(nodes={'seed.pkg.seed': SeedNode(database='dbt', schema='dbt_schema', name='seed', resource_type=<NodeType.Se...s(show=True, node_color=None), patch_path=None, arguments=[], created_at=1718229810.21914, supported_languages=None)}})
def execute(self, model, manifest):
context = generate_runtime_model_context(model, self.config, manifest)
materialization_macro = manifest.find_materialization_macro_by_name(
self.config.project_name, model.get_materialization(), self.adapter.type()
)
if materialization_macro is None:
> raise MissingMaterializationError(
materialization=model.get_materialization(), adapter_type=self.adapter.type()
)
E dbt.adapters.exceptions.compilation.MissingMaterializationError: Compilation Error
E No materialization 'table' was found for adapter postgres! (searched types 'default' and 'postgres')
core/dbt/task/run.py:266: MissingMaterializationError
```
* Add spoofed macro fixture `materialization_table_default` for `test_execute` test
Previously the `TestModelRunner:test_execute` test was running into a runtime error
do to the macro `materialization_table_default` macro not existing in the project. This
commit adds that macro to the project (though it should ideally get loaded via interactions
between the manifest and adapter). Manually adding it resolved our previous issue, but created
a new one. The macro appears to not be properly loaded into the manifest, and thus isn't
discoverable later on when getting the macros for the jinja context. This leads to an error
that looks like the following:
```
model_runner = <dbt.task.run.ModelRunner object at 0x1080a4f70>
def test_execute(
self, table_model: ModelNode, manifest: Manifest, model_runner: ModelRunner
) -> None:
> model_runner.execute(model=table_model, manifest=manifest)
tests/unit/task/test_run.py:129:
----
core/dbt/task/run.py:287: in execute
result = MacroGenerator(
core/dbt/clients/jinja.py:82: in __call__
return self.call_macro(*args, **kwargs)
venv/lib/python3.10/site-packages/dbt_common/clients/jinja.py:294: in call_macro
macro = self.get_macro()
---
self = <dbt.clients.jinja.MacroGenerator object at 0x1080f3130>
def get_macro(self):
name = self.get_name()
template = self.get_template()
# make the module. previously we set both vars and local, but that's
# redundant: They both end up in the same place
# make_module is in jinja2.environment. It returns a TemplateModule
module = template.make_module(vars=self.context, shared=False)
> macro = module.__dict__[get_dbt_macro_name(name)]
E KeyError: 'dbt_macro__materialization_table_default'
venv/lib/python3.10/site-packages/dbt_common/clients/jinja.py:277: KeyError
```
It's becoming apparent that we need to find a better way to either mock or legitimately
load the default and adapter macros. At this point I think I've exausted the time box
I should be using to figure out if testing the `ModelRunner` class is possible currently,
with the result being more work has yet to be done.
* Begin adding the `LogModelResult` event catcher to event manager class fixture
* init push for issue 10198
* add changelog
* add unit tests based on michelle example
* add data_tests, and post_hook unit tests
* pull creating macro_func out of try call
* revert last commit
* pull macro_func definition back out of try
* update code formatting
* Add basic semantic layer fixture nodes to unit test `manifest` fixture
We're doing this in preperation to a for a unit test which will be testing
these nodes (as well as others) and thus we want them in the manifest.
* Add `WhereFilterInteresection` to `QueryParams` of `saved_query` fixture
In the previous commit, 58990aa450, we added
the `saved_query` fixture to the `manifest` fixture. This broke the test
`tests/unit/parser/test_manifest.py::TestPartialParse::test_partial_parse_by_version`.
It broke because the `Manifest.deepcopy` manifest basically dictifies things. When we were
dictifying the `QueryParams` of the `saved_query` before, the `where` key was getting
dropped because it was `None`. We'd then run into a runtime error on instantiation of the
`QueryParams` because although `where` is declared as _optional_, we don't set a default
value for it. And thus, kaboom :(
We should probably provide a default value for `where`. However that is out of scope
for this branch of work.
* Fix `test_select_fqn` to account for newly included semantic model
In 58990aa450 we added a semantic model
to the `manifest` fixture. This broke the test
`tests/unit/graph/test_selector_methods.py::test_select_fqn` because in
the test it selects nodes based on the string `*.*.*_model`. The newly
added semantic model matches this, and thus needed to be added to the
expected results.
* Add unit tests for `_warn_for_unused_resource_config_paths` method
Note: At this point the test when run with for a `unit_test` config
taht should be considered used, fails. This is because it is not being
properly identified as used.
* Include `unit_tests` in `Manifest.get_resouce_fqns`
Because `unit_tests` weren't being included in calls to `Manifest.get_resource.fqns`,
it always appeared to `_warn_for_unused_resource_config_paths` that there were no
unit tests in the manifest. Because of this `_warn_for_unused_resource_config_paths` thought
that _any_ `unit_test` config in `dbt_project.yaml` was unused.
* Rename `maniest` fixture in `test_selector` to `mock_manifest`
We have a globally available `manifest` fixture in our unit tests. In the
coming commits we're going to add tests to the file which use the gloablly
available `manifest` fixture. Prior to this commit, the locally defined
`manifest` fixture was taking precidence. To get around this, the easiest
solution was to rename the locally defined fixture.
I had tried to isolate the locally defined fixture by moving it, and the relevant
tests to a test class like `TestNodeSelector`. However because of _how_ the relevant
tests were parameterized, this proved difficult. Basically for readability we define
a variable which holds a list of all the parameterization variables. By moving to a
test class, the definition of the variables would have had to be defined directly in
the parameterization macro call. Although possible, it made the readability slighty
worse. It might be worth doing anyway in the long run, but instead I used a less heavy
handed alternative (already described)
* Improve type hinting in `tests/unit/utils/manifest.py`
* Ensure `args` get set from global flags for `runtime_config` fixture in unit tests
The `Compiler.compile` method accesses `self.config.args.which`. The `config`
is the `RuntimeConfig` the `Compiler` was instantiated with. Our `runtime_config`
fixture was being instatiated with an empty dict for the `args` property. Thus
a `which` property of the args wasn't being made avaiable, and if `compile` was run
a runtime error would occur. To solve this, we've begun instantiating the args from
the global flags via `get_flags()`. This works because we ensure the `set_test_flags`
fixture is run first which calls `set_from_args`.
* Create a `make_manifest` utility function for use in unit tests and fixture creation
* Refactor `Compiler` and `NodeSelector` tests in `test_selector.py` to use pytesting methodology
* Remove parsing tests that exist in `test_selector.py`
We had some tests in `test_selector.py::GraphTest` that didn't add
anything ontop of what was already being tested else where in the file
except the parsing of models. However, the tests in `test_parser.py::ModelParserTest`
cover everything being tested here (and then some). Thus these tests
in `test_selector.py::GraphTest` are unnecessary and can be deleted.
* Move `test__partial_parse` from `test_selector.py` to `test_manifest.py`
There was a test `test__partial_parse` in `test_selector.py` which tested
the functionality of `is_partial_parsable` of the `ManifestLoader`. This
doesn't really make sense to exist in `test_selector.py` where we are
testing selectors. We test the `ManifestLoader` class in `test_manifest.py`
which seemed like a more appropriate place for the test. Additionally we
renamed the test to `test_is_partial_parsable_by_version` to more accurately
describe what is being tested.
* Make `test_selector`'s manifest fixture name even more specific
* Add type hint to `expected_nodes` in `test_selector.py` tests
In the test `tests/unit/graph/test_selector.py::TestCompiler::test_two_models_simple_ref`
we have a variable `expected_nodes` that we are setting via a list comprehension.
At a glance it isn't immediately obvious what `expected_nodes` actually is. It's a
list, but a list of what? One suggestion was to explicitly write out the list of strings.
However, I worry about the brittleness of doing so. That might be the way we head long
term, but as a compromise for now, I've added a type hint the the variable definition.
* Fire skipped events at debug level
Closes https://github.com/dbt-labs/dbt-core/issues/8774
* add changelog entry
* Update to work with 1.9.*.
* Add tests for --fail-fast not showing skip messages unless --debug.
* Update test that works by itself, but assumes to much to work in integration tests.
---------
Co-authored-by: Scott Gigante <scottgigante@users.noreply.github.com>
* init push arbitrary configs for generic tests pr
* iterative work
* initial test design attempts
* test reformatting
* test rework, have basic structure for 3 of 4 passing, need to figure out how to best represent same key error, failing correctly though
* swap up test formats for new config dict and mixed varitey to run of dbt parse and inspecting the manifest
* modify tests to get passing, then modify the TestBuilder class work from earlier to be more dry
* add changelog
* modify code to match suggested changes around seperate methods and test id fix
* add column_name reference to init for deeper nested _render_values can use the input
* add type annotations
* feedback based on mike review
* Create `runtime_config` fixture and necessary upstream fixtures
* Check for better scoped `ProjectContractError` in test_runtime tests
Previously in `test_unsupported_version_extra_config` and
`test_archive_not_allowed` we were checking for `DbtProjectError`. This
worked because `ProjectContractError` is a subclass of `DbtProjectError`.
However, if we check for `DbtProjectError` in these tests than, some tangential
failure which raises a `DbtProejctError` type error would go undetected. As
we plan on modifying these tests to be pytest in the coming commits, we want to
ensure that the tests are succeeding for the right reason.
* Convert `test_str` of `TestRuntimeConfig` to a pytest test using fixtures
* Convert `test_from_parts` of `TestRuntimeConfig` to a pytest test using fixtures
While converting `test_from_parts` I noticed the comment
> TODO(jeb): Adapters must assert that quoting is populated?
This led me to beleive that `quoting` shouldn't be "fully" realized
in our project fixture unless we're saying that it's gone through
adapter instantiation. Thus I update the `quoting` on our project
fixture to be an empty dict. This change affected `test__str__` in
`test_project.py` which we thus needed to update accordingly.
* Convert runtime version specifier tests to pytest tests and move to test_project
We've done two things in this commit, which arguably _should_ have been done in
two commits. First we moved the version specifier tests from `test_runtime.py::TestRuntimeConfig`
to `test_project.py::TestGetRequiredVersion` this is because what is really being
tested is the `_get_required_version` method. Doing it via `RuntimeConfig.from_parts` method
made actually testing it a lot harder as it requires setting up more of the world and
running with a _full_ project config dict.
The second thing we did was convert it from the old unittest implementation to a pytest
implementation. This saves us from having to create most of the world as we were doing
previously in these tests.
Of note, I did not move the test `test_unsupported_version_range_bad_config`. This test
is a bit different from the rest of the version specifier tests. It was introduced in
[1eb5857811](1eb5857811)
of [#2726](https://github.com/dbt-labs/dbt-core/pull/2726) to resolve [#2638](https://github.com/dbt-labs/dbt-core/issues/2638).
The focus of #2726 was to ensure the version specifier checks were run _before_ the validation
of the `dbt_project.yml`. Thus what this test is actually testing for is order of
operations at parse time. As such, this is really more a _functional_ test than a
unit test. In the next commit we'll get this test moved (and renamed)
* Create a better test for checking that version checks come before project schema validation
* Convert `test_get_metadata` to pytest test
* Refactor `test_archive_not_allowed` to functional test
We do already have tests that ensure "extra" keys aren't allowed in
the dbt_project.yaml. This test is different because it's checking that
a specific key, `archive`, isn't allowed. We do this because at one point
in time `archive` _was_ an allowed key. Specifically, we stopped allowing
`archive` in dbt-core 0.15.0 via commit [f26948dd](f26948dde2).
Given that it's been 5 years and a major version, we could probably remove
this test, but let's keep it around unless we start supporting `archive` again.
* Convert `warn_for_unused_resource_config_paths` tests to use pytest
* Add fixtures for setting and resettign flags for unit tests
* Remove unnecessary `set_from_args` in non `unittest.TestCase` based unit tests
In the previous commit we added a pytest fixture which sets and tears down
the global flags arg via `set_from_args` for every pytest based unit test.
Previously we had added a `set_from_args` in tests or test files to reset
the global flags from if they were modified by a previous test. This is no
longer necessary because of the work done in the previous commit.
Note: We did not modify any tests that use the `unittest.TestCase` class
because they don't use pytest fixtures. Thus those tests need to continue
operating as they currently do until we shift them to pytest unit tests.
* Utilize the new `args_for_flags` fixture for setting of flags in `test_contracts_graph_parsed.py`
* Convert `test_compilation.py` from `TestCase` tests to pytest tests
We did this so in the next commit we can drop the unnecessary `set_from_args`
in the next commit. That will be it's own commit because converting these
tests is a restructuring that doing separately makes things easier to follow.
That is to say, all changes in this commit were just to convert the tests to
pytest, no other changes were made.
* Drop unnecessary `set_from_args` in `test_compilation.py`
* Add return types to all methods in `test_compilation.py`
* Reduce imports from `compilation` in `test_compilation.py`
* Update `test_logging.py` now that we don't need to worry about global flags
* Conditionally import `Generator` type for python 3.8
In python 3.9 `Generator` was moved to `collections.abc` and deprecated
in `typing`. We still support 3.8 and thus need to be conditionally
importing `Generator`. We should remove this in the future when we drop
support for 3.8.
* Add more accurate RSS high water mark measurement for Linux
* Add changelog entry.
* Checks to avoid exception based flow control, per review.
* Fix review nit.
* Add unit test to assert `setup_config_logger` clears the event manager state
* Move `setup_event_logger` tests from `test_functions.py` to `test_logging.py`
* Move `EventCatcher` to `tests.utils` for use in unit and functional tests
* Update fixture mocking global event manager to instead clear it
Previously we had started _mocking_ the global event manager. We did this
because we though that meant anything we did to the global event manager,
including modifying it via things like `setup_event_logger`, would be
automatically cleaned up at the end of any test using the fixture because
the mock would go away. However, this understanding of fixtures and mocking
was incorrect, and the global event manager wouldn't be properly isolated/reset.
Thus we changed to fixture to instead cleanup the global event manager before
any test that uses it and by using `autouse=True` in the fixture definition
we made it so that every unit test uses the fixture.
Note this will no longer be viabled if we every multi-thread our unit testing as
the event manager isn't actually isolated, and thus two tests could both modify
the event manager at the same time.
* Add test for different `write_perf_info` values to `get_full_manifest`
* Add test for different `reset` values to `get_full_manifest`
* Abstract required mocks for `get_full_manifest` tests to reduce duplication
There are a set of required mocks that `get_full_manifest` unit tests need.
Instead of doing these mocks in each test, we've abstracted these mocks into
a reusable function. I did try to do this as a fixture, but for some reaosn
the mocks didn't actually propagate when I did that.
* Add test for different `PARTIAL_PARSE_FILE_DIFF` values to `get_full_manifest`
* Refactor mock fixtures in `test_manifest.py` to make them more widely available
* Convert `set_required_mocks` of `TestGetFullManifest` into a fixture
This wasn't working before, but it does now. Not sure why.
This was done by running `pre-commit run --all`. That this was needed
is a temporary glitch in how our `Tests and Code Checks` github action
works on PRs. Basically we added `isort` to the pre-commit hooks recently, and
this does additional linting/formatting on our imports.
People reasonably have branches which were started prior to `isort` being
part of the pre-commit hooks on main. Thus, unless those branches get caught
up to main, the github action on associated PRs won't run `isort` because
it doesn't exist on those branchs. Once everyone gets their local `main`
branch updated (I suspect this might take a few days) this problem will go
away.
* Add `isort` as a dev-req and pre-commit hook
The tool `isort` reorders imports to be in alphabetical order. I've
added it because our imports in most files are in random order. The lack
of order meant that:
- sometimes the same module would be imported from twice
- figuring out if a a module was already being imported from took
longer
In the next commit I'll actually run isort to order everything. The best
part is that when developing, we don't have to put them in correct order.
Though you can if you want. However, `isort` will take care of re-ordering
things at commit time :)
* Improve isort functionality by setting initial `.isort.cfg`
Specifically we set two config values: `extend_skip_glob` and `known_first_party`.
The `extend_skip_glob` extends the default skipped paths. The defaults can be seen
here https://pycqa.github.io/isort/docs/configuration/options.html#skip. We are skipping
third party stubs because these are more so provided (I believe). We are skipping
`.github` and `scripts` as they feel out of scope and things we can be less strict with.
The `known_first_party` setting makes it so that these imports get grouped separately from
all other imports, which is useful visually of "this comes from us" vs "this comes from
someone/somewhere else".
* Add profile `black` to isort config
I was seeing some odd behavior where running pre-commit, adding the modified
files, and then running pre-commit again would result making more modifications
to some of the same files. This felt odd. You shouldn't have to run pre-commit
more multiple times for it to eventually come to a final "solution". I believe
the problem was because we are using the tool `black` to format things, but weren't
registering the black profile with `isort` this lead to some conflicting formatting
rules, and the two tools had to negotiate a few times before being both satisfied.
Registering the profile `black` with `isort` resolved this problem.
* Reorder, merge-duplicate, and format module imports using `isort`
This was done by running `pre-commit run --all`. I ran it separately from
the commit process itself because I wanted to run it against all files
instead of only changed files.
Of note, this not only reordered and formatted our imports. But we also
had 60 distinct duplicate module import paths across 50 files, which this
took care of. When I say "distinct duplicate module import paths" I mean
when `from x.y.z import` was imported more than once in a single file.
* add support for explicit nulls for loaded_at_field
* add test
* changelog
* add parsing for tests
* centralize logic a bit
* account for sources being None
* fix bug
* remove new field from SourceDefinition
* add validation for empty string, mroe tests
* Move deferral from task to manifest loading + RefResolver
* dbt clone must specify --defer
* Fix deferral for unit test type deteection
* Add changelog
* Move merge_from_artifact from end of parsing back to task before_run to reduce scope of refactor
* PR review. DeferRelation conforms to RelationConfig protocol
* Add test case for #10017
* Update manifest v12 in test_previous_version_state
---------
Co-authored-by: Michelle Ark <michelle.ark@dbtlabs.com>
* Change agate upper bound to v1.10
* Add changelog.
* update lower pin
* for testing
* put back dev requirement
* move the lower pin back to 1.7
---------
Co-authored-by: Emily Rockman <emily.rockman@dbtlabs.com>
* Refactor test class `EventCatcher` into utils to make accessible to other tests
* Raise minimum version of dbt_common to 1.0.2
We're going to start depending on `silence` existing as a attr of
`WarnErrorOptions`. The `silence` attr was only added in dbt_common
1.0.2, thus that is our new minimum.
* Add ability to silence warnings from `warn_error_options` CLI arguments
* Add `flush` to `EventCatcher` test util, and use in `test_warn_error_options`
* Add tests to `TestWarnErrorOptionsFromCLI` for `include` and `exclude`
* Test support for setting `silence` of `warn_error_options` in `dbt_project` flags
Support for `silence` was _automatically_ added when we upgraded to dbt_common 1.0.2.
This is because we build the project flags in a `.from_dict` style, which is cool. In
this case it was _automatically_ handled in `read_project_flags` in `project.py`. More
specifically here bcbde3ac42/core/dbt/config/project.py (L839)
* Add tests to `TestWarnErrorOptionsFromProject` for `include` and `exclude`
Typically we can't have multiple tests in the same `test class` if they're
utilizing/modifying file system fixtures. That is because the file system
fixtures are scoped to test classes, so they don't reset inbetween tests within
the same test class. This problem _was_ affectin these tests as they modify the
`dbt_project.yml` file which is set by a class based fixture. To get around this,
because I find it annoying to create multiple test classes when the tests really
should be grouped, I created a "function" scoped fixture to reset the `dbt_project.yml`.
* Update `warn_error_options` in CLI args to support `error` and `warn` options
Setting `error` is the same as setting `include`, but only one can be specified.
Setting `warn` is the same as setting `exclude`, but only one can be specified.
* Update `warn_error_options` in Project flags to support `error` and `warn` options
As part of this I refactored `exclusive_primary_alt_value_setting` into an upstream
location `/config/utils`. That is because importing it in `/config/project.py` from
`cli/option_types.py` caused some circular dependency issues.
* Use `DbtExclusivePropertyUseError` in `exclusive_primary_alt_value_setting` instead of `DbtConfigError`
Using `DbtConfigError` seemed reasonable. However in order to make sure the error
got raised in `read_project_flags` we had to mark it to be `DbtConfigError`s to be
re-raised. This had the uninteded consequence of reraising a smattering of errors
which were previously being swallowed. I'd argue that if those are errors we're
swallowing, the functions that raise those errors should be modified perhaps to
conditionally not raise them, but that's not the world we live in and is out of
scope for this branch of work. Thus instead we've created a error specific to
`WarnErrorOptions` issues, and now use, and catch for re-raising.
* Add unit tests for `exclusive_primary_alt_value_setting` method
I debated about parametrizing these tests, and it can be done. However,
I found that the resulting code ended up being about the same number of
lines and slightly less readable (in my opinion). Given the simplicity of
these tests, I think not parametrizing them is okay.
Letting the dbt version be dynamic in the project fixture previously was
causing some tests to break whenever the version of dbt actually got updated,
which isn't great. It'd be super annoying to have to always update tests
affected by this. To get around this we've gone and hard coded the dbt version
in the profile. The alternative was to interpolate the version during comparison
during the relevant tests, which felt less appealing.
* Move `tests/unit/test_yaml_renderer.py` to `tests/unit/parser/test_schema_renderer.py`
* Move `tests/unit/test_unit_test_parser.py` to `tests/unit/parser/test_unit_tests.py`
* Convert `tests/unit/test_tracking.py` to use pytest fixtures
* Delete `tests/unit/test_sql_result.py` as it was moved to `dbt-adapters`
* Move `tests/unit/test_semantic_models.py` to `tests/unit/graph/test_nodes.py
* Group tests of `SemanticModel` in `test_nodes.py` into a `TestSemanticModel` class
* Move `tests/unit/test_selector_errors.py` to `tests/unit/config/test_selectors.py`
* Add `Project` fixture for unit tests and test `Project` class methods
* Move `Project.__eq__` unit tests to new pytest class testing
* Move `Project.hashed_name` unit test to pytest testing class
* Rename some testing class in `test_project.py` to align with testing split
* Refactor `project` fixture to make accessible to other unit tests
* simplify dockerfile, eliminate references to adapter repos as they will be handled in those repos
* keep dbt-postgres target for historical releases of dbt-postgres
* update third party image to pip install conditionally
* Add event type for deprecation of spaces in model names
* Begin emitting deprecation warning for spaces in model names
* Only warn on first model name with spaces unless `--debug` is specified
For projects with a lot of models that have spaces in their names, the
warning about this deprecation would be incredibly annoying. Now we instead
only log the first model name issue and then a count of how many models
have the issue, unless `--debug` is specified.
* Refactor `EventCatcher` so that the event to catch is setable
We want to be able to catch more than just `SpacesInModelNameDeprecation`
events, and in the next commit we will alter our tests to do so. Thus
instead of writing a new catcher for each event type, a slight modification
to the existing `EventCatcher` makes this much easier.
* Add project flag to control whether spaces are allowed in model names
* Log errors and raise exception when `allow_spaces_in_model_names` is `False`
* Use custom event for output invalid name counts instead of `Note` events
Using `Note` events was causing test flakiness when run in a multi
worker environment using `pytest -nauto`. This is because the event
manager is currently a global. So in a situation where test `A` starts
and test `tests_debug_when_spaces_in_name` starts shortly there after,
the event manager for both tests will have the callbacks set in
`tests_debug_when_spaces_in_name`. Then if something in test `A` fired
a `Note` event, this would affect the count of `Note` events that
`tests_debug_when_spaces_in_name` sees, causing assertion failures. By
creating a custom event, `TotalModelNamesWithSpacesDeprecation`, we limit
the possible flakiness to only tests that fire the custom event. Thus
we didn't _eliminate_ all possibility of flakiness, but realistically
only the tests in `test_check_for_spaces_in_model_names.py` can now
interfere with each other. Which still isn't great, but to fully
resolve the problem we need to work on how the event manager is
handled (preferably not globally).
* Always log total invalid model names if at least one
Previously we only logged out the count of how many invalid model names
there were if there was two or more invalid names (and not in debug mode).
However this message is important if there is even one invalid model
name and regardless of whether you are running debug mode. That is because
automated tools might be looking for the event type to track if anything
is wrong.
A related change in this commit is that we now only output the debug hint
if it wasn't run with debug mode. The idea being that if they are already
running it in debug mode, the hint could come accross as somewhat
patronizing.
* Reduce duplicate `if` logic in `check_for_spaces_in_model_names`
* Improve readability of logs related to problematic model names
We want people running dbt to be able to at a glance see warnings/errors
with running their project. In this case we are focused specifically on
errors/warnings in regards to model names containing spaces. Previously
we were only ever emitting the `warning_tag` in the message even if the
event itself was being emitted at an `ERROR` level. We now properly have
`[ERROR]` or `[WARNING]` in the message depending on the level. Unfortunately
we couldn't just look what level the event was being fired at, because that
information doesn't exist on the event itself.
Additionally, we're using events that base off of `DynamicEvents` which
unfortunately hard coded to `DEBUG`. Changing this would involve still
having a `level` property on the definition in `core_types.proto` and
then having `DynamicEvent`s look to `self.level` in the `level_tag`
method. Then we could change how firing events works based on the an
event's `level_tag` return value. This all sounds like a bit of tech
debt suited for PR, possibly multiple, and thus is not being done here.
* Alter `TotalModelNamesWithSpacesDeprecation` message to handle singular and plural
* Remove duplicate import in `test_graph.py` introduced from merging in main
---------
Co-authored-by: Emily Rockman <emily.rockman@dbtlabs.com>
* Expect that the `args` variable is un-modified by `dbt.invoke(args)`
* Make `args` variable un-modified by `dbt.invoke(args)`
* Changelog entry
* Expect that the `args` variable is un-modified by `make_dbt_context`
* Make the `args` variable is un-modified by `make_dbt_context`
* Make a copy of `args` passed to `make_dbt_context`
* Revert "Make a copy of `args` passed to `make_dbt_context`"
This reverts commit 79227b4d346b505f9f6abcbd0921074e8fe365e9.
* Ensure BaseRunner handles nodes without `build_path`
Some nodes, like SourceDefinition nodes, don't have a `build_path` property.
This is problematic because we take in nodes with no type checking, and
assume they have properties sometimes, like `build_path`. This was just
the case in BaseRunner's `_handle_generic_exception` and
`_handle_interal_exception` methods. Thus to stop dbt from crashing when
trying to handle an exception related to a node without a `build_path`,
we added an private method to the BaseRunner class for safely trying
to get `build_path`.
* Use keyword arguments when instantiating `Note` events in freshness.py
Previously we were passing arguments during the `Note` event instantiations
in freshness.py as positional arguments. This would cause not the desired
`Note` event to be emitted, but instead get the message
```
[Note] Don't use positional arguments when constructing logging events
```
which was our fault, not the users'. Additionally, we were passing the
level for the event in the `Note` instantiation when we needed to be
passing it to the `fire_event` method.
* Raise error when `loaded_at_field` is `None` and metadata check isn't possible
Previously if a source freshness check didn't have a `loaded_at_field` and
metadata source freshness wasn't supported by the adapter, then we'd log
a warning message and let the source freshness check continue. This was problematic
because the source freshness check couldn't actually continue and the process
would raise an error in the form
```
type object argument after ** must be a mapping, not NoneType
```
because the `freshness` variable was never getting set. This error wasn't particularly
helpful for any person running into it. So instead of letting that error
happen we now deliberately raise an error with helpful information.
* Add test which ensures bad source freshness checks raise appropriate error
This test directly tests that when a source freshness check doesn't have a
`loaded_at_field` and the adapter in use doesn't support metadata checks,
then the appropriate error message gets raised. That is, it directly tests
the change made in a162d53a8. This test indirectly tests the changes in both
7ec2f82a9 and 7b0ff3198 as the appropriate error can only be raised because
we've fixed other upstream issues via those commits.
* Add changelog entry for source freshness edgecase fixes
* Add @p.profile and @p.target to the list of "global" CLI flags
* Add env vars (DBT_PROFILE, DBT_TARGET) to the params
* Add unit test
* Simplify unit test
* changie
* Update .changes/unreleased/Features-20231115-092005.yaml
Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com>
* Fix incorrect envvar names
* Realign environment variable names
* Remove from specific subcommands
* Add test_global_flags_not_on_subcommands
* Remove one unnecessary test case
* Remove other unnecessary test case
---------
Co-authored-by: Doug Beatty <doug.beatty@dbtlabs.com>
Co-authored-by: Doug Beatty <44704949+dbeatty10@users.noreply.github.com>
Our `protobuf` dep was in the section of `setup.py` which we delineate
as expecting all future versions of it to be compatible. However, this
is no longer actually the case, and in e4fe839e45
we restricted it to major vesion 4.
* [#9570] Fix fixtures in fixtures/subfolders throwing parsing error
* Fast-forward imports to match upstream
* Re-introduce doc strings on traceback info handling
* [#9570] Changelog update for fix of fixtures in fixtures/subfolders throwing parsing error
* [#9570] Improve testability and coverage for partial parsing
* Transform skip_parsing (private variable of ManifestLoader.load()) into instance-attribute of ManifestLoader(), with default value False
(to enable splitting of ManifestLoader.load())
* Split ManifestLoader.load(), to extract operation of PartialParsing into new method called ManifestLoader.safe_update_project_parser_files_partially()
(to simplify both cognitive complexity in the codebase and mocking in unittestest)
* Add "ignore" type-comments in new ManifestLoader.safe_update_project_parser_files_partially()
(to silence mypy warnings regarding instance-attributes which can be initialized as None or as something else, e.g. self.saved_manifest)[1]
[1] Although I wanted avoid "ignore" type-comments, it seems like addressing these mypy warnings in a stricter sense requires technical alignment and broader code changes.
For example, might need to initialize self.saved_manifest as Manifest, instead of Optional[Manifest], so that PartialParsing gets inputs with type it currently expects.
... perhaps too far beyond the scope of this fix?
* Check for equality with existing input_measures when adding input_measures
* Changie
* Add type annotation
* Move add_input_measure to metric from type_params
* Add tests to check that saved queries show in `dbt list`
* Update `list` task to support saved queries
This is built off of @jtcohen6 work in d6e7cda on jerco/fix-9532.
I didn't directly cherry pick because there was more work to do as
well as merge conflicts. That is to say @jtcohen6 should be credited
with some of the work.
* Update error message when iterating over nodes during list command errors
This was originally suggested by @jtcohen6 in d6e7cda of jerco/fix-9532.
This commit just makes sure the change gets included because I didn't
cherry-pick that commit into this work.
* Add test around deleting a YAML file containing semantic models and metrics
It was raised in https://github.com/dbt-labs/dbt-core/issues/8860 that an
error is being raised during partial parsing when files containing
metrics/semantic models are deleted. In further testing it looks like this
error specifically happens when a file containing both semantic models and
metrics is deleted. If the deleted file contains just semantic models or
metrics there seems to be no issue. The next commit should contain the fix.
* Skip deleted schema files when scheduling files during partial parsing
Waaaay back (in 7563b99) deleted schema files started being separated out
from deleted non-schema files. However ever since, when it came to scheduling
files for reparsing, we've only done so for deleted non-schema files. We even
missed this when we refactored the scheduling code in b37e5b5. This change
updates `_schedule_for_parsing` which is used by `schedule_nodes_for_parsing`
to begin skipping deleted schema files in addition to deleted non schema files.
* Update `add_to_pp_files` to ignore `deleted_schema_files`
As noted in the previous commit, we started separating out deleted
schema files from deleted non-schema files a looong time ago. However,
this whole time we've been adding `deleted_schema_files` to the list
of files to be parsed. This change corrects for that.
* Add changie doc for partial parsing KeyError fix
Protobuf v5 has breaking changes. Here we are limiting the protobuf
dependency to one major version, 4, so that we don't have to patch
over handling 2 different major versions of protobuf.
* Clearer no-op logging in stubbed SavedQueryRunner
* Add changelog entry
* Fix unit test
* More logging touchups
* Fix failing test
* Rename flag + refactor per #9629
* Fix failing test
* regenerate core_proto_types with libprotoc 25.3
---------
Co-authored-by: Michelle Ark <michelle.ark@dbtlabs.com>
A recent update to the version ranges for our internally
maintained support packages quite reasonably expanded the
allowed versions for dbt-semantic-interfaces to all minor versions
after 0.5.0, under the assumption that subsequent releases will
generally be backwards-compatible.
Unfortunately, dbt-semantic-interfaces is not yet in that state.
So we update the version range accordingly, and include some
comments around version range expectations for dependencies
listed in this section of dbt-core's package configuration.
CVE-2024-22195 identified an issue in Jinja2 versions <= 3.1.2. As such
we've gone and changed our dependency requirement specification to be
3.1.3 or greater (but less than 4).
Note: Preivously we were using the `~=` version specifier. However due
to some issues with the `~=` we've moved to using `>=` in combination
with `<`. This gives us the same range that `~=` gave us, but avoids
a pip resolution issue when multiple packages in an environment use `~=`
for the same dependency.
* Remove extraneous `/` in `schema-check.yml`
We have hypothesis that the extra `/` in `schema-check` is causing
issues we're seeing currently in the artifact check failing. It may
not be the final solution, but we should fix it anyway.
* Move `artifact_minor_upgrade` label check to job level of `Check Artifact Changes`
Previously the checking for `artifact_minor_upgrade` was happening in each job
step of `Check Artifact Changes`. By moving it up to the job level instead of
in the job steps we make it so the check for the label only happens once and
it simplifies the job steps.
* Update `Check Artifact Changes` to use `dorny/paths-filter`
Previously we were using `git diff` to check if any files had changed
in `core/dbt/artifacts`. However, our `git diff` usage was including any
changes that happened on `main` which the PR branch did not have. This
commit switches the check from using `git diff` to `dorny/paths-filter`,
which is what we use for checking for changelog existence as well. The
`dorny/paths-fitler` includes logic for excluding changes that are on main
but not the PR branch (which is what want to happen).
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