Compare commits

..

9 Commits

Author SHA1 Message Date
Nathaniel May
42d71f5a97 fmt 2021-09-22 10:33:46 -04:00
Nathaniel May
58dc3b1829 remove comment nonsense 2021-09-22 10:30:29 -04:00
Nathaniel May
bb9a400d77 make scale more useful 2021-09-22 10:30:29 -04:00
Nathaniel May
01366be246 plots all detected metrics 2021-09-22 10:30:29 -04:00
Nathaniel May
b034e2bc66 it graphs, but poorly for now. 2021-09-22 10:30:29 -04:00
Nathaniel May
3bc9f49f7a add plot subcommand exceptions to hierarchy 2021-09-22 10:30:29 -04:00
Nathaniel May
09a61177b4 don't commit plots 2021-09-22 10:27:36 -04:00
Nathaniel May
e8d3efef9f doesn't compile. saving. 2021-09-22 10:27:36 -04:00
Nathaniel May
f9a46c15b9 sample plot runs 2021-09-22 10:27:09 -04:00
6246 changed files with 93138 additions and 201814 deletions

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@@ -1,19 +1,13 @@
[bumpversion]
current_version = 1.7.18
parse = (?P<major>[\d]+) # major version number
\.(?P<minor>[\d]+) # minor version number
\.(?P<patch>[\d]+) # patch version number
(?P<prerelease> # optional pre-release - ex: a1, b2, rc25
(?P<prekind>a|b|rc) # pre-release type
(?P<num>[\d]+) # pre-release version number
current_version = 0.21.0b2
parse = (?P<major>\d+)
\.(?P<minor>\d+)
\.(?P<patch>\d+)
((?P<prekind>a|b|rc)
(?P<pre>\d+) # pre-release version num
)?
( # optional nightly release indicator
\.(?P<nightly>dev[0-9]+) # ex: .dev02142023
)? # expected matches: `1.15.0`, `1.5.0a11`, `1.5.0a1.dev123`, `1.5.0.dev123457`, expected failures: `1`, `1.5`, `1.5.2-a1`, `text1.5.0`
serialize =
{major}.{minor}.{patch}{prekind}{num}.{nightly}
{major}.{minor}.{patch}.{nightly}
{major}.{minor}.{patch}{prekind}{num}
serialize =
{major}.{minor}.{patch}{prekind}{pre}
{major}.{minor}.{patch}
commit = False
tag = False
@@ -21,27 +15,36 @@ tag = False
[bumpversion:part:prekind]
first_value = a
optional_value = final
values =
values =
a
b
rc
final
[bumpversion:part:num]
[bumpversion:part:pre]
first_value = 1
[bumpversion:part:nightly]
[bumpversion:file:setup.py]
[bumpversion:file:core/setup.py]
[bumpversion:file:core/dbt/version.py]
[bumpversion:file:core/scripts/create_adapter_plugins.py]
[bumpversion:file:plugins/postgres/setup.py]
[bumpversion:file:plugins/redshift/setup.py]
[bumpversion:file:plugins/snowflake/setup.py]
[bumpversion:file:plugins/bigquery/setup.py]
[bumpversion:file:plugins/postgres/dbt/adapters/postgres/__version__.py]
[bumpversion:file:docker/Dockerfile]
[bumpversion:file:plugins/redshift/dbt/adapters/redshift/__version__.py]
[bumpversion:file:tests/adapter/setup.py]
[bumpversion:file:plugins/snowflake/dbt/adapters/snowflake/__version__.py]
[bumpversion:file:plugins/bigquery/dbt/adapters/bigquery/__version__.py]
[bumpversion:file:tests/adapter/dbt/tests/adapter/__version__.py]

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@@ -1,23 +0,0 @@
## Previous Releases
For information on prior major and minor releases, see their changelogs:
* [1.6](https://github.com/dbt-labs/dbt-core/blob/1.6.latest/CHANGELOG.md)
* [1.5](https://github.com/dbt-labs/dbt-core/blob/1.5.latest/CHANGELOG.md)
* [1.4](https://github.com/dbt-labs/dbt-core/blob/1.4.latest/CHANGELOG.md)
* [1.3](https://github.com/dbt-labs/dbt-core/blob/1.3.latest/CHANGELOG.md)
* [1.2](https://github.com/dbt-labs/dbt-core/blob/1.2.latest/CHANGELOG.md)
* [1.1](https://github.com/dbt-labs/dbt-core/blob/1.1.latest/CHANGELOG.md)
* [1.0](https://github.com/dbt-labs/dbt-core/blob/1.0.latest/CHANGELOG.md)
* [0.21](https://github.com/dbt-labs/dbt-core/blob/0.21.latest/CHANGELOG.md)
* [0.20](https://github.com/dbt-labs/dbt-core/blob/0.20.latest/CHANGELOG.md)
* [0.19](https://github.com/dbt-labs/dbt-core/blob/0.19.latest/CHANGELOG.md)
* [0.18](https://github.com/dbt-labs/dbt-core/blob/0.18.latest/CHANGELOG.md)
* [0.17](https://github.com/dbt-labs/dbt-core/blob/0.17.latest/CHANGELOG.md)
* [0.16](https://github.com/dbt-labs/dbt-core/blob/0.16.latest/CHANGELOG.md)
* [0.15](https://github.com/dbt-labs/dbt-core/blob/0.15.latest/CHANGELOG.md)
* [0.14](https://github.com/dbt-labs/dbt-core/blob/0.14.latest/CHANGELOG.md)
* [0.13](https://github.com/dbt-labs/dbt-core/blob/0.13.latest/CHANGELOG.md)
* [0.12](https://github.com/dbt-labs/dbt-core/blob/0.12.latest/CHANGELOG.md)
* [0.11 and earlier](https://github.com/dbt-labs/dbt-core/blob/0.11.latest/CHANGELOG.md)

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@@ -1,157 +0,0 @@
## dbt-core 1.7.0 - November 02, 2023
### Breaking Changes
- Removed the FirstRunResultError and AfterFirstRunResultError event types, using the existing RunResultError in their place. ([#7963](https://github.com/dbt-labs/dbt-core/issues/7963))
### Features
- add log file of installed packages via dbt deps ([#6643](https://github.com/dbt-labs/dbt-core/issues/6643))
- Enable re-population of metadata vars post-environment change during programmatic invocation ([#8010](https://github.com/dbt-labs/dbt-core/issues/8010))
- Added support to configure a delimiter for a seed file, defaults to comma ([#3990](https://github.com/dbt-labs/dbt-core/issues/3990))
- Allow specification of `create_metric: true` on measures ([#8125](https://github.com/dbt-labs/dbt-core/issues/8125))
- Add node attributes related to compilation to run_results.json ([#7519](https://github.com/dbt-labs/dbt-core/issues/7519))
- Add --no-inject-ephemeral-ctes flag for `compile` command, for usage by linting. ([#8480](https://github.com/dbt-labs/dbt-core/issues/8480))
- Support configuration of semantic models with the addition of enable/disable and group enablement. ([#7968](https://github.com/dbt-labs/dbt-core/issues/7968))
- Accept a `dbt-cloud` config in dbt_project.yml ([#8438](https://github.com/dbt-labs/dbt-core/issues/8438))
- Support atomic replace in the global replace macro ([#8539](https://github.com/dbt-labs/dbt-core/issues/8539))
- Use translate_type on data_type in model.columns in templates by default, remove no op `TYPE_LABELS` ([#8007](https://github.com/dbt-labs/dbt-core/issues/8007))
- Add an option to generate static documentation ([#8614](https://github.com/dbt-labs/dbt-core/issues/8614))
- Allow setting "access" as a config in addition to as a property ([#8383](https://github.com/dbt-labs/dbt-core/issues/8383))
- Loosen typing requirement on renameable/replaceable relations to Iterable to allow adapters more flexibility in registering relation types, include docstrings as suggestions ([#8647](https://github.com/dbt-labs/dbt-core/issues/8647))
- Add support for optional label in semantic_models, measures, dimensions and entities. ([#8595](https://github.com/dbt-labs/dbt-core/issues/8595), [#8755](https://github.com/dbt-labs/dbt-core/issues/8755))
- Allow adapters to include package logs in dbt standard logging ([#7859](https://github.com/dbt-labs/dbt-core/issues/7859))
- Support storing test failures as views ([#6914](https://github.com/dbt-labs/dbt-core/issues/6914))
- resolve packages with same git repo and unique subdirectory ([#5374](https://github.com/dbt-labs/dbt-core/issues/5374))
- Add new ResourceReport event to record memory/cpu/io metrics ([#8342](https://github.com/dbt-labs/dbt-core/issues/8342))
- Adding `date_spine` macro (and supporting macros) from dbt-utils to dbt-core ([#8172](https://github.com/dbt-labs/dbt-core/issues/8172))
- Support `fill_nulls_with` and `join_to_timespine` for metric nodes ([#8593](https://github.com/dbt-labs/dbt-core/issues/8593), [#8755](https://github.com/dbt-labs/dbt-core/issues/8755))
- Raise a warning when a contracted model has a numeric field without scale defined ([#8183](https://github.com/dbt-labs/dbt-core/issues/8183))
- Added support for retrieving partial catalog information from a schema ([#8521](https://github.com/dbt-labs/dbt-core/issues/8521))
- Add meta attribute to SemanticModels config ([#8511](https://github.com/dbt-labs/dbt-core/issues/8511))
- Selectors with docs generate limits catalog generation ([#6014](https://github.com/dbt-labs/dbt-core/issues/6014))
- Allow freshness to be determined via DBMS metadata for supported adapters ([#8704](https://github.com/dbt-labs/dbt-core/issues/8704))
- Add support semantic layer SavedQuery node type ([#8594](https://github.com/dbt-labs/dbt-core/issues/8594))
- Add exports to SavedQuery spec ([#8892](https://github.com/dbt-labs/dbt-core/issues/8892))
### Fixes
- Copy dir during `dbt deps` if symlink fails ([#7428](https://github.com/dbt-labs/dbt-core/issues/7428), [#8223](https://github.com/dbt-labs/dbt-core/issues/8223))
- If --profile specified with dbt-init, create the project with the specified profile ([#6154](https://github.com/dbt-labs/dbt-core/issues/6154))
- Fixed double-underline ([#5301](https://github.com/dbt-labs/dbt-core/issues/5301))
- Copy target_schema from config into snapshot node ([#6745](https://github.com/dbt-labs/dbt-core/issues/6745))
- Enable converting deprecation warnings to errors ([#8130](https://github.com/dbt-labs/dbt-core/issues/8130))
- Add status to Parse Inline Error ([#8173](https://github.com/dbt-labs/dbt-core/issues/8173))
- Ensure `warn_error_options` get serialized in `invocation_args_dict` ([#7694](https://github.com/dbt-labs/dbt-core/issues/7694))
- Stop detecting materialization macros based on macro name ([#6231](https://github.com/dbt-labs/dbt-core/issues/6231))
- Update `dbt deps` download retry logic to handle `EOFError` exceptions ([#6653](https://github.com/dbt-labs/dbt-core/issues/6653))
- Improve handling of CTE injection with ephemeral models ([#8213](https://github.com/dbt-labs/dbt-core/issues/8213))
- Fix unbound local variable error in `checked_agg_time_dimension_for_measure` ([#8230](https://github.com/dbt-labs/dbt-core/issues/8230))
- Ensure runtime errors are raised for graph runnable tasks (compile, show, run, etc) ([#8166](https://github.com/dbt-labs/dbt-core/issues/8166))
- Fix retry not working with log-file-max-bytes ([#8297](https://github.com/dbt-labs/dbt-core/issues/8297))
- Add explicit support for integers for the show command ([#8153](https://github.com/dbt-labs/dbt-core/issues/8153))
- Detect changes to model access, version, or latest_version in state:modified ([#8189](https://github.com/dbt-labs/dbt-core/issues/8189))
- Add connection status into list of statuses for dbt debug ([#8350](https://github.com/dbt-labs/dbt-core/issues/8350))
- fix fqn-selection for external versioned models ([#8374](https://github.com/dbt-labs/dbt-core/issues/8374))
- Fix: DbtInternalError after model that previously ref'd external model is deleted ([#8375](https://github.com/dbt-labs/dbt-core/issues/8375))
- Fix using list command with path selector and project-dir ([#8385](https://github.com/dbt-labs/dbt-core/issues/8385))
- Remedy performance regression by only writing run_results.json once. ([#8360](https://github.com/dbt-labs/dbt-core/issues/8360))
- Add support for swapping materialized views with tables/views and vice versa ([#8449](https://github.com/dbt-labs/dbt-core/issues/8449))
- Turn breaking changes to contracted models into warnings for unversioned models ([#8384](https://github.com/dbt-labs/dbt-core/issues/8384), [#8282](https://github.com/dbt-labs/dbt-core/issues/8282))
- Ensure parsing does not break when `window_groupings` is not specified for `non_additive_dimension` ([#8453](https://github.com/dbt-labs/dbt-core/issues/8453))
- fix ambiguous reference error for tests and versions when model name is duplicated across packages ([#8327](https://github.com/dbt-labs/dbt-core/issues/8327), [#8493](https://github.com/dbt-labs/dbt-core/issues/8493))
- Fix "Internal Error: Expected node <unique-id> not found in manifest" when depends_on set on ModelNodeArgs ([#8506](https://github.com/dbt-labs/dbt-core/issues/8506))
- Fix snapshot success message ([#7583](https://github.com/dbt-labs/dbt-core/issues/7583))
- Parse the correct schema version from manifest ([#8544](https://github.com/dbt-labs/dbt-core/issues/8544))
- make version comparison insensitive to order ([#8571](https://github.com/dbt-labs/dbt-core/issues/8571))
- Update metric helper functions to work with new semantic layer metrics ([#8134](https://github.com/dbt-labs/dbt-core/issues/8134))
- Disallow cleaning paths outside current working directory ([#8318](https://github.com/dbt-labs/dbt-core/issues/8318))
- Warn when --state == --target ([#8160](https://github.com/dbt-labs/dbt-core/issues/8160))
- update dbt show to include limit in DWH query ([#8496,](https://github.com/dbt-labs/dbt-core/issues/8496,), [#8417](https://github.com/dbt-labs/dbt-core/issues/8417))
- Support quoted parameter list for MultiOption CLI options. ([#8598](https://github.com/dbt-labs/dbt-core/issues/8598))
- Support global flags passed in after subcommands ([#6497](https://github.com/dbt-labs/dbt-core/issues/6497))
- Lower bound of `8.0.2` for `click` ([#8683](https://github.com/dbt-labs/dbt-core/issues/8683))
- Fixes test type edges filter ([#8692](https://github.com/dbt-labs/dbt-core/issues/8692))
- semantic models in graph selection ([#8589](https://github.com/dbt-labs/dbt-core/issues/8589))
- Support doc blocks in nested semantic model YAML ([#8509](https://github.com/dbt-labs/dbt-core/issues/8509))
- avoid double-rendering sql_header in dbt show ([#8739](https://github.com/dbt-labs/dbt-core/issues/8739))
- Fix tag selection for projects with semantic models ([#8749](https://github.com/dbt-labs/dbt-core/issues/8749))
- Foreign key constraint on incremental model results in Database Error ([#8022](https://github.com/dbt-labs/dbt-core/issues/8022))
- Support docs blocks on versioned model column descriptions ([#8540](https://github.com/dbt-labs/dbt-core/issues/8540))
- Enable seeds to be handled from stored manifest data ([#6875](https://github.com/dbt-labs/dbt-core/issues/6875))
- Override path-like args in dbt retry ([#8682](https://github.com/dbt-labs/dbt-core/issues/8682))
- Group updates on unmodified nodes are handled gracefully for state:modified ([#8371](https://github.com/dbt-labs/dbt-core/issues/8371))
- Partial parsing fix for adding groups and updating models at the same time ([#8697](https://github.com/dbt-labs/dbt-core/issues/8697))
- Fix partial parsing not working for semantic model change ([#8859](https://github.com/dbt-labs/dbt-core/issues/8859))
- Rework get_catalog implementation to retain previous adapter interface semantics ([#8846](https://github.com/dbt-labs/dbt-core/issues/8846))
- Add back contract enforcement for temporary tables on postgres ([#8857](https://github.com/dbt-labs/dbt-core/issues/8857))
- Add version to fqn when version==0 ([#8836](https://github.com/dbt-labs/dbt-core/issues/8836))
- Fix cased comparison in catalog-retrieval function. ([#8939](https://github.com/dbt-labs/dbt-core/issues/8939))
- Catalog queries now assign the correct type to materialized views ([#8864](https://github.com/dbt-labs/dbt-core/issues/8864))
- Make relation filtering None-tolerant for maximal flexibility across adapters. ([#8974](https://github.com/dbt-labs/dbt-core/issues/8974))
### Docs
- Corrected spelling of "Partiton" ([dbt-docs/#8100](https://github.com/dbt-labs/dbt-docs/issues/8100))
- Remove static SQL codeblock for metrics ([dbt-docs/#436](https://github.com/dbt-labs/dbt-docs/issues/436))
- fixed comment util.py ([dbt-docs/#None](https://github.com/dbt-labs/dbt-docs/issues/None))
- Fix newline escapes and improve formatting in docker README ([dbt-docs/#8211](https://github.com/dbt-labs/dbt-docs/issues/8211))
- Display contract and column constraints on the model page ([dbt-docs/#433](https://github.com/dbt-labs/dbt-docs/issues/433))
- Display semantic model details in docs ([dbt-docs/#431](https://github.com/dbt-labs/dbt-docs/issues/431))
### Under the Hood
- Switch from hologram to mashumaro jsonschema ([#8426](https://github.com/dbt-labs/dbt-core/issues/8426))
- Refactor flaky test pp_versioned_models ([#7781](https://github.com/dbt-labs/dbt-core/issues/7781))
- format exception from dbtPlugin.initialize ([#8152](https://github.com/dbt-labs/dbt-core/issues/8152))
- A way to control maxBytes for a single dbt.log file ([#8199](https://github.com/dbt-labs/dbt-core/issues/8199))
- Ref expressions with version can now be processed by the latest version of the high-performance dbt-extractor library. ([#7688](https://github.com/dbt-labs/dbt-core/issues/7688))
- Bump manifest schema version to v11, freeze manifest v10 ([#8333](https://github.com/dbt-labs/dbt-core/issues/8333))
- add tracking for plugin.get_nodes calls ([#8344](https://github.com/dbt-labs/dbt-core/issues/8344))
- add internal flag: --no-partial-parse-file-diff to inform whether to compute a file diff during partial parsing ([#8363](https://github.com/dbt-labs/dbt-core/issues/8363))
- Add return values to a number of functions for mypy ([#8389](https://github.com/dbt-labs/dbt-core/issues/8389))
- Fix mypy warnings for ManifestLoader.load() ([#8401](https://github.com/dbt-labs/dbt-core/issues/8401))
- Use python version 3.10.7 in Docker image. ([#8444](https://github.com/dbt-labs/dbt-core/issues/8444))
- Re-organize jinja macros: relation-specific in /macros/adapters/relations/<relation>, relation agnostic in /macros/relations ([#8449](https://github.com/dbt-labs/dbt-core/issues/8449))
- Update typing to meet mypy standards ([#8396](https://github.com/dbt-labs/dbt-core/issues/8396))
- Mypy errors - adapters/factory.py ([#8387](https://github.com/dbt-labs/dbt-core/issues/8387))
- Added more type annotations. ([#8537](https://github.com/dbt-labs/dbt-core/issues/8537))
- Audit potential circular dependencies ([#8349](https://github.com/dbt-labs/dbt-core/issues/8349))
- Add functional test for advanced ref override ([#8566](https://github.com/dbt-labs/dbt-core/issues/8566))
- Add typing to __init__ in base.py ([#8398](https://github.com/dbt-labs/dbt-core/issues/8398))
- Fix untyped functions in task/runnable.py (mypy warning) ([#8402](https://github.com/dbt-labs/dbt-core/issues/8402))
- add a test for ephemeral cte injection ([#8225](https://github.com/dbt-labs/dbt-core/issues/8225))
- Fix test_numeric_values to look for more specific strings ([#8470](https://github.com/dbt-labs/dbt-core/issues/8470))
- Pin types-requests<2.31.0 in `dev-requirements.txt` ([#8789](https://github.com/dbt-labs/dbt-core/issues/8789))
- Add warning_tag to UnversionedBreakingChange ([#8827](https://github.com/dbt-labs/dbt-core/issues/8827))
- Update v10 manifest schema to match 1.6 for testing schema compatibility ([#8835](https://github.com/dbt-labs/dbt-core/issues/8835))
- Add a no-op runner for Saved Qeury ([#8893](https://github.com/dbt-labs/dbt-core/issues/8893))
### Dependencies
- Bump mypy from 1.3.0 to 1.4.0 ([#7912](https://github.com/dbt-labs/dbt-core/pull/7912))
- Bump mypy from 1.4.0 to 1.4.1 ([#8219](https://github.com/dbt-labs/dbt-core/pull/8219))
- Update pin for click<9 ([#8232](https://github.com/dbt-labs/dbt-core/pull/8232))
- Add upper bound to sqlparse pin of <0.5 ([#8236](https://github.com/dbt-labs/dbt-core/pull/8236))
- Support dbt-semantic-interfaces 0.2.0 ([#8250](https://github.com/dbt-labs/dbt-core/pull/8250))
- Bump docker/build-push-action from 4 to 5 ([#8783](https://github.com/dbt-labs/dbt-core/pull/8783))
- Upgrade dbt-semantic-interfaces dep to 0.3.0 ([#8819](https://github.com/dbt-labs/dbt-core/pull/8819))
- Begin using DSI 0.4.x ([#8892](https://github.com/dbt-labs/dbt-core/pull/8892))
### Contributors
- [@anjutiwari](https://github.com/anjutiwari) ([#7428](https://github.com/dbt-labs/dbt-core/issues/7428), [#8223](https://github.com/dbt-labs/dbt-core/issues/8223))
- [@benmosher](https://github.com/benmosher) ([#8480](https://github.com/dbt-labs/dbt-core/issues/8480))
- [@d-kaneshiro](https://github.com/d-kaneshiro) ([#None](https://github.com/dbt-labs/dbt-core/issues/None))
- [@dave-connors-3](https://github.com/dave-connors-3) ([#8153](https://github.com/dbt-labs/dbt-core/issues/8153), [#8589](https://github.com/dbt-labs/dbt-core/issues/8589))
- [@dylan-murray](https://github.com/dylan-murray) ([#8683](https://github.com/dbt-labs/dbt-core/issues/8683))
- [@ezraerb](https://github.com/ezraerb) ([#6154](https://github.com/dbt-labs/dbt-core/issues/6154))
- [@gem7318](https://github.com/gem7318) ([#8010](https://github.com/dbt-labs/dbt-core/issues/8010))
- [@jamezrin](https://github.com/jamezrin) ([#8211](https://github.com/dbt-labs/dbt-core/issues/8211))
- [@jusbaldw](https://github.com/jusbaldw) ([#6643](https://github.com/dbt-labs/dbt-core/issues/6643))
- [@lllong33](https://github.com/lllong33) ([#5301](https://github.com/dbt-labs/dbt-core/issues/5301))
- [@marcodamore](https://github.com/marcodamore) ([#436](https://github.com/dbt-labs/dbt-core/issues/436))
- [@mescanne](https://github.com/mescanne) ([#8614](https://github.com/dbt-labs/dbt-core/issues/8614))
- [@pgoslatara](https://github.com/pgoslatara) ([#8100](https://github.com/dbt-labs/dbt-core/issues/8100))
- [@philippeboyd](https://github.com/philippeboyd) ([#5374](https://github.com/dbt-labs/dbt-core/issues/5374))
- [@ramonvermeulen](https://github.com/ramonvermeulen) ([#3990](https://github.com/dbt-labs/dbt-core/issues/3990))
- [@renanleme](https://github.com/renanleme) ([#8692](https://github.com/dbt-labs/dbt-core/issues/8692))

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@@ -1,8 +0,0 @@
## dbt-core 1.7.1 - November 07, 2023
### Fixes
- Fix compilation exception running empty seed file and support new Integer agate data_type ([#8895](https://github.com/dbt-labs/dbt-core/issues/8895))
- Update run_results.json from previous versions of dbt to support deferral and rerun from failure ([#9010](https://github.com/dbt-labs/dbt-core/issues/9010))
- Use MANIFEST.in to recursively include all jinja templates; fixes issue where some templates were not included in the distribution ([#9016](https://github.com/dbt-labs/dbt-core/issues/9016))
- Fix git repository with subdirectory for Deps ([#9000](https://github.com/dbt-labs/dbt-core/issues/9000))

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@@ -1,11 +0,0 @@
## dbt-core 1.7.10 - March 14, 2024
### Fixes
- Do not add duplicate input_measures ([#9360](https://github.com/dbt-labs/dbt-core/issues/9360))
- Fix partial parsing `KeyError` on deleted schema files ([#8860](https://github.com/dbt-labs/dbt-core/issues/8860))
- Support saved queries in `dbt list` ([#9532](https://github.com/dbt-labs/dbt-core/issues/9532))
### Dependencies
- Restrict protobuf to 4.* versions ([#9566](https://github.com/dbt-labs/dbt-core/pull/9566))

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@@ -1,6 +0,0 @@
## dbt-core 1.7.11 - March 28, 2024
### Fixes
- Tighten exception handling to avoid worker thread hangs. ([#9583](https://github.com/dbt-labs/dbt-core/issues/9583))
- Add field wrapper to BaseRelation members that were missing it. ([#9681](https://github.com/dbt-labs/dbt-core/issues/9681))

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## dbt-core 1.7.12 - April 16, 2024
### Fixes
- Fix assorted source freshness edgecases so check is run or actionable information is given ([#9078](https://github.com/dbt-labs/dbt-core/issues/9078))
- Exclude password-like fields for considering reparse ([#9795](https://github.com/dbt-labs/dbt-core/issues/9795))

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@@ -1,8 +0,0 @@
## dbt-core 1.7.13 - April 18, 2024
### Security
- Bump sqlparse to >=0.5.0, <0.6.0 to address GHSA-2m57-hf25-phgg ([#9951](https://github.com/dbt-labs/dbt-core/pull/9951))
### Contributors
- [@emmoop](https://github.com/emmoop) ([#9951](https://github.com/dbt-labs/dbt-core/pull/9951))

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## dbt-core 1.7.14 - May 02, 2024
### Features
- Move flags from UserConfig in profiles.yml to flags in dbt_project.yml ([#9183](https://github.com/dbt-labs/dbt-core/issues/9183))
- Add require_explicit_package_overrides_for_builtin_materializations to dbt_project.yml flags, which can be used to opt-out of overriding built-in materializations from packages ([#10007](https://github.com/dbt-labs/dbt-core/issues/10007))
### Fixes
- remove materialized views from renambeable relation and remove a quote ([#127](https://github.com/dbt-labs/dbt-core/issues/127))
- Replace usage of `Set` with `List` to fix issue with index updates intermittently happening out of order ([#72](https://github.com/dbt-labs/dbt-core/issues/72))
### Under the Hood
- Raise deprecation warning if installed package overrides built-in materialization ([#9971](https://github.com/dbt-labs/dbt-core/issues/9971))
- Remove the final underscore from secret environment variable constants. ([#10052](https://github.com/dbt-labs/dbt-core/issues/10052))

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@@ -1,9 +0,0 @@
## dbt-core 1.7.15 - May 22, 2024
### Fixes
- Fix the semicolon semantics for indexes while respecting other bug fix ([#85](https://github.com/dbt-labs/dbt-core/issues/85))
### Security
- Explicitly bind to localhost in docs serve ([#10209](https://github.com/dbt-labs/dbt-core/issues/10209))

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## dbt-core 1.7.16 - June 05, 2024
### Features
- Add --host flag to dbt docs serve, defaulting to '127.0.0.1' ([#10229](https://github.com/dbt-labs/dbt-core/issues/10229))

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@@ -1,5 +0,0 @@
## dbt-core 1.7.17 - June 20, 2024
### Docs
- Fix npm security vulnerabilities as of June 2024 ([dbt-docs/#513](https://github.com/dbt-labs/dbt-docs/issues/513))

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@@ -1,5 +0,0 @@
## dbt-core 1.7.18 - August 07, 2024
### Fixes
- respect --quiet and --warn-error-options for flag deprecations ([#10105](https://github.com/dbt-labs/dbt-core/issues/10105))

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@@ -1,16 +0,0 @@
## dbt-core 1.7.2 - November 16, 2023
### Features
- Support setting export configs hierarchically via saved query and project configs ([#8956](https://github.com/dbt-labs/dbt-core/issues/8956))
### Fixes
- Fix formatting of tarball information in packages-lock.yml ([#9062](https://github.com/dbt-labs/dbt-core/issues/9062))
### Under the Hood
- Treat SystemExit as an interrupt if raised during node execution. ([#n/a](https://github.com/dbt-labs/dbt-core/issues/n/a))
### Contributors
- [@benmosher](https://github.com/benmosher) ([#n/a](https://github.com/dbt-labs/dbt-core/issues/n/a))

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@@ -1,7 +0,0 @@
## dbt-core 1.7.3 - November 29, 2023
### Fixes
- deps: Lock git packages to commit SHA during resolution ([#9050](https://github.com/dbt-labs/dbt-core/issues/9050))
- deps: Use PackageRenderer to read package-lock.json ([#9127](https://github.com/dbt-labs/dbt-core/issues/9127))
- Get sources working again in dbt docs generate ([#9119](https://github.com/dbt-labs/dbt-core/issues/9119))

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@@ -1,12 +0,0 @@
## dbt-core 1.7.4 - December 14, 2023
### Features
- Adds support for parsing conversion metric related properties for the semantic layer. ([#9203](https://github.com/dbt-labs/dbt-core/issues/9203))
### Fixes
- Ensure we produce valid jsonschema schemas for manifest, catalog, run-results, and sources ([#8991](https://github.com/dbt-labs/dbt-core/issues/8991))
### Contributors
- [@WilliamDee](https://github.com/WilliamDee) ([#9203](https://github.com/dbt-labs/dbt-core/issues/9203))

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## dbt-core 1.7.5 - January 18, 2024
### Fixes
- Preserve the value of vars and the --full-refresh flags when using retry. ([#9112](https://github.com/dbt-labs/dbt-core/issues/9112))
### Contributors
- [@peterallenwebb,](https://github.com/peterallenwebb,) ([#9112](https://github.com/dbt-labs/dbt-core/issues/9112))

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@@ -1,6 +0,0 @@
## dbt-core 1.7.6 - January 25, 2024
### Fixes
- Handle unknown `type_code` for model contracts ([#8877](https://github.com/dbt-labs/dbt-core/issues/8877), [#8353](https://github.com/dbt-labs/dbt-core/issues/8353))
- Fix retry command run from CLI ([#9444](https://github.com/dbt-labs/dbt-core/issues/9444))

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@@ -1,6 +0,0 @@
## dbt-core 1.7.7 - February 01, 2024
### Fixes
- Fix seed and source selection in `dbt docs generate` ([#9161](https://github.com/dbt-labs/dbt-core/issues/9161))
- Add TestGenerateCatalogWithExternalNodes, include empty nodes in node selection during docs generate ([#9456](https://github.com/dbt-labs/dbt-core/issues/9456))

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## dbt-core 1.7.8 - February 14, 2024
### Fixes
- When patching versioned models, set constraints after config ([#9364](https://github.com/dbt-labs/dbt-core/issues/9364))
- Store node_info in node associated logging events ([#9557](https://github.com/dbt-labs/dbt-core/issues/9557))

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@@ -1,18 +0,0 @@
## dbt-core 1.7.9 - February 28, 2024
### Fixes
- Fix node_info contextvar handling so incorrect node_info doesn't persist ([#8866](https://github.com/dbt-labs/dbt-core/issues/8866))
- Add target-path to retry ([#8948](https://github.com/dbt-labs/dbt-core/issues/8948))
### Under the Hood
- Make dbt-core compatible with Python 3.12 ([#9007](https://github.com/dbt-labs/dbt-core/issues/9007))
- Restrict protobuf to major version 4. ([#9566](https://github.com/dbt-labs/dbt-core/issues/9566))
### Security
- Update Jinja2 to >= 3.1.3 to address CVE-2024-22195 ([#CVE-2024-22195](https://github.com/dbt-labs/dbt-core/pull/CVE-2024-22195))
### Contributors
- [@l1xnan](https://github.com/l1xnan) ([#9007](https://github.com/dbt-labs/dbt-core/issues/9007))

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@@ -1,53 +0,0 @@
# CHANGELOG Automation
We use [changie](https://changie.dev/) to automate `CHANGELOG` generation. For installation and format/command specifics, see the documentation.
### Quick Tour
- All new change entries get generated under `/.changes/unreleased` as a yaml file
- `header.tpl.md` contains the contents of the entire CHANGELOG file
- `0.0.0.md` contains the contents of the footer for the entire CHANGELOG file. changie looks to be in the process of supporting a footer file the same as it supports a header file. Switch to that when available. For now, the 0.0.0 in the file name forces it to the bottom of the changelog no matter what version we are releasing.
- `.changie.yaml` contains the fields in a change, the format of a single change, as well as the format of the Contributors section for each version.
### Workflow
#### Daily workflow
Almost every code change we make associated with an issue will require a `CHANGELOG` entry. After you have created the PR in GitHub, run `changie new` and follow the command prompts to generate a yaml file with your change details. This only needs to be done once per PR.
The `changie new` command will ensure correct file format and file name. There is a one to one mapping of issues to changes. Multiple issues cannot be lumped into a single entry. If you make a mistake, the yaml file may be directly modified and saved as long as the format is preserved.
Note: If your PR has been cleared by the Core Team as not needing a changelog entry, the `Skip Changelog` label may be put on the PR to bypass the GitHub action that blacks PRs from being merged when they are missing a `CHANGELOG` entry.
#### Prerelease Workflow
These commands batch up changes in `/.changes/unreleased` to be included in this prerelease and move those files to a directory named for the release version. The `--move-dir` will be created if it does not exist and is created in `/.changes`.
```
changie batch <version> --move-dir '<version>' --prerelease 'rc1'
changie merge
```
Example
```
changie batch 1.0.5 --move-dir '1.0.5' --prerelease 'rc1'
changie merge
```
#### Final Release Workflow
These commands batch up changes in `/.changes/unreleased` as well as `/.changes/<version>` to be included in this final release and delete all prereleases. This rolls all prereleases up into a single final release. All `yaml` files in `/unreleased` and `<version>` will be deleted at this point.
```
changie batch <version> --include '<version>' --remove-prereleases
changie merge
```
Example
```
changie batch 1.0.5 --include '1.0.5' --remove-prereleases
changie merge
```
### A Note on Manual Edits & Gotchas
- Changie generates markdown files in the `.changes` directory that are parsed together with the `changie merge` command. Every time `changie merge` is run, it regenerates the entire file. For this reason, any changes made directly to `CHANGELOG.md` will be overwritten on the next run of `changie merge`.
- If changes need to be made to the `CHANGELOG.md`, make the changes to the relevant `<version>.md` file located in the `/.changes` directory. You will then run `changie merge` to regenerate the `CHANGELOG.MD`.
- Do not run `changie batch` again on released versions. Our final release workflow deletes all of the yaml files associated with individual changes. If for some reason modifications to the `CHANGELOG.md` are required after we've generated the final release `CHANGELOG.md`, the modifications need to be done manually to the `<version>.md` file in the `/.changes` directory.
- changie can modify, create and delete files depending on the command you run. This is expected. Be sure to commit everything that has been modified and deleted.

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@@ -1,6 +0,0 @@
# dbt Core Changelog
- This file provides a full account of all changes to `dbt-core` and `dbt-postgres`
- Changes are listed under the (pre)release in which they first appear. Subsequent releases include changes from previous releases.
- "Breaking changes" listed under a version may require action from end users or external maintainers when upgrading to that version.
- Do not edit this file directly. This file is auto-generated using [changie](https://github.com/miniscruff/changie). For details on how to document a change, see [the contributing guide](https://github.com/dbt-labs/dbt-core/blob/main/CONTRIBUTING.md#adding-changelog-entry)

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@@ -1,6 +0,0 @@
kind: Under the Hood
body: Remove support and testing for Python 3.8, which is now EOL.
time: 2024-10-16T14:40:56.451972-04:00
custom:
Author: gshank peterallenwebb
Issue: "10861"

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@@ -1,96 +0,0 @@
changesDir: .changes
unreleasedDir: unreleased
headerPath: header.tpl.md
versionHeaderPath: ""
changelogPath: CHANGELOG.md
versionExt: md
envPrefix: "CHANGIE_"
versionFormat: '## dbt-core {{.Version}} - {{.Time.Format "January 02, 2006"}}'
kindFormat: '### {{.Kind}}'
changeFormat: |-
{{- $IssueList := list }}
{{- $changes := splitList " " $.Custom.Issue }}
{{- range $issueNbr := $changes }}
{{- $changeLink := "[#nbr](https://github.com/dbt-labs/dbt-core/issues/nbr)" | replace "nbr" $issueNbr }}
{{- $IssueList = append $IssueList $changeLink }}
{{- end -}}
- {{.Body}} ({{ range $index, $element := $IssueList }}{{if $index}}, {{end}}{{$element}}{{end}})
kinds:
- label: Breaking Changes
- label: Features
- label: Fixes
- label: Docs
changeFormat: |-
{{- $IssueList := list }}
{{- $changes := splitList " " $.Custom.Issue }}
{{- range $issueNbr := $changes }}
{{- $changeLink := "[dbt-docs/#nbr](https://github.com/dbt-labs/dbt-docs/issues/nbr)" | replace "nbr" $issueNbr }}
{{- $IssueList = append $IssueList $changeLink }}
{{- end -}}
- {{.Body}} ({{ range $index, $element := $IssueList }}{{if $index}}, {{end}}{{$element}}{{end}})
- label: Under the Hood
- label: Dependencies
- label: Security
newlines:
afterChangelogHeader: 1
afterKind: 1
afterChangelogVersion: 1
beforeKind: 1
endOfVersion: 1
custom:
- key: Author
label: GitHub Username(s) (separated by a single space if multiple)
type: string
minLength: 3
- key: Issue
label: GitHub Issue Number (separated by a single space if multiple)
type: string
minLength: 1
footerFormat: |
{{- $contributorDict := dict }}
{{- /* ensure all names in this list are all lowercase for later matching purposes */}}
{{- $core_team := splitList " " .Env.CORE_TEAM }}
{{- /* ensure we always skip snyk and dependabot in addition to the core team */}}
{{- $maintainers := list "dependabot[bot]" "snyk-bot"}}
{{- range $team_member := $core_team }}
{{- $team_member_lower := lower $team_member }}
{{- $maintainers = append $maintainers $team_member_lower }}
{{- end }}
{{- range $change := .Changes }}
{{- $authorList := splitList " " $change.Custom.Author }}
{{- /* loop through all authors for a single changelog */}}
{{- range $author := $authorList }}
{{- $authorLower := lower $author }}
{{- /* we only want to include non-core team contributors */}}
{{- if not (has $authorLower $maintainers)}}
{{- $changeList := splitList " " $change.Custom.Author }}
{{- $IssueList := list }}
{{- $changeLink := $change.Kind }}
{{- $changes := splitList " " $change.Custom.Issue }}
{{- range $issueNbr := $changes }}
{{- $changeLink := "[#nbr](https://github.com/dbt-labs/dbt-core/issues/nbr)" | replace "nbr" $issueNbr }}
{{- $IssueList = append $IssueList $changeLink }}
{{- end }}
{{- /* check if this contributor has other changes associated with them already */}}
{{- if hasKey $contributorDict $author }}
{{- $contributionList := get $contributorDict $author }}
{{- $contributionList = concat $contributionList $IssueList }}
{{- $contributorDict := set $contributorDict $author $contributionList }}
{{- else }}
{{- $contributionList := $IssueList }}
{{- $contributorDict := set $contributorDict $author $contributionList }}
{{- end }}
{{- end}}
{{- end}}
{{- end }}
{{- /* no indentation here for formatting so the final markdown doesn't have unneeded indentations */}}
{{- if $contributorDict}}
### Contributors
{{- range $k,$v := $contributorDict }}
- [@{{$k}}](https://github.com/{{$k}}) ({{ range $index, $element := $v }}{{if $index}}, {{end}}{{$element}}{{end}})
{{- end }}
{{- end }}

12
.flake8
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@@ -1,12 +0,0 @@
[flake8]
select =
E
W
F
ignore =
W503 # makes Flake8 work like black
W504
E203 # makes Flake8 work like black
E741
E501 # long line checking is done in black
exclude = test/

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@@ -1,2 +0,0 @@
# Reformatting dbt-core via black, flake8, mypy, and assorted pre-commit hooks.
43e3fc22c4eae4d3d901faba05e33c40f1f1dc5a

6
.gitattributes vendored
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@@ -1,6 +0,0 @@
core/dbt/include/index.html binary
tests/functional/artifacts/data/state/*/manifest.json binary
core/dbt/docs/build/html/searchindex.js binary
core/dbt/docs/build/html/index.html binary
performance/runner/Cargo.lock binary
core/dbt/events/types_pb2.py binary

43
.github/CODEOWNERS vendored
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@@ -1,43 +0,0 @@
# This file contains the code owners for the dbt-core repo.
# PRs will be automatically assigned for review to the associated
# team(s) or person(s) that touches any files that are mapped to them.
#
# A statement takes precedence over the statements above it so more general
# assignments are found at the top with specific assignments being lower in
# the ordering (i.e. catch all assignment should be the first item)
#
# Consult GitHub documentation for formatting guidelines:
# https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-code-owners#example-of-a-codeowners-file
# As a default for areas with no assignment,
# the core team as a whole will be assigned
* @dbt-labs/core-team
### ADAPTERS
# Adapter interface ("base" + "sql" adapter defaults, cache)
/core/dbt/adapters @dbt-labs/core-adapters
# Global project (default macros + materializations), starter project
/core/dbt/include @dbt-labs/core-adapters
# Postgres plugin
/plugins/ @dbt-labs/core-adapters
/plugins/postgres/setup.py @dbt-labs/core-adapters
# Functional tests for adapter plugins
/tests/adapter @dbt-labs/core-adapters
### TESTS
# Overlapping ownership for vast majority of unit + functional tests
# Perf regression testing framework
# This excludes the test project files itself since those aren't specific
# framework changes (excluded by not setting an owner next to it- no owner)
/performance @nathaniel-may
/performance/projects
### ARTIFACTS
/schemas/dbt @dbt-labs/cloud-artifacts

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@@ -0,0 +1,27 @@
---
name: Beta minor version release
about: Creates a tracking checklist of items for a Beta minor version release
title: "[Tracking] v#.##.#B# release "
labels: 'release'
assignees: ''
---
### Release Core
- [ ] [Engineering] Follow [dbt-release workflow](https://www.notion.so/dbtlabs/Releasing-b97c5ea9a02949e79e81db3566bbc8ef#03ff37da697d4d8ba63d24fae1bfa817)
- [ ] [Engineering] Verify new release branch is created in the repo
- [ ] [Product] Finalize migration guide (next.docs.getdbt.com)
### Release Cloud
- [ ] [Engineering] Create a platform issue to update dbt Cloud and verify it is completed. [Example issue](https://github.com/dbt-labs/dbt-cloud/issues/3481)
- [ ] [Engineering] Determine if schemas have changed. If so, generate new schemas and push to schemas.getdbt.com
### Announce
- [ ] [Product] Announce in dbt Slack
### Post-release
- [ ] [Engineering] [Bump plugin versions](https://www.notion.so/dbtlabs/Releasing-b97c5ea9a02949e79e81db3566bbc8ef#f01854e8da3641179fbcbe505bdf515c) (dbt-spark + dbt-presto), add compatibility as needed
- [ ] [Spark](https://github.com/dbt-labs/dbt-spark)
- [ ] [Presto](https://github.com/dbt-labs/dbt-presto)
- [ ] [Engineering] Create a platform issue to update dbt-spark versions to dbt Cloud. [Example issue](https://github.com/dbt-labs/dbt-cloud/issues/3481)
- [ ] [Engineering] Create an epic for the RC release

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@@ -1,97 +0,0 @@
name: 🐞 Bug
description: Report a bug or an issue you've found with dbt
title: "[Bug] <title>"
labels: ["bug", "triage"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
- type: checkboxes
attributes:
label: Is this a new bug in dbt-core?
description: >
In other words, is this an error, flaw, failure or fault in our software?
If this is a bug that broke existing functionality that used to work, please open a regression issue.
If this is a bug in an adapter plugin, please open an issue in the adapter's repository.
If this is a bug experienced while using dbt Cloud, please report to [support](mailto:support@getdbt.com).
If this is a request for help or troubleshooting code in your own dbt project, please join our [dbt Community Slack](https://www.getdbt.com/community/join-the-community/) or open a [Discussion question](https://github.com/dbt-labs/docs.getdbt.com/discussions).
Please search to see if an issue already exists for the bug you encountered.
options:
- label: I believe this is a new bug in dbt-core
required: true
- label: I have searched the existing issues, and I could not find an existing issue for this bug
required: true
- type: textarea
attributes:
label: Current Behavior
description: A concise description of what you're experiencing.
validations:
required: true
- type: textarea
attributes:
label: Expected Behavior
description: A concise description of what you expected to happen.
validations:
required: true
- type: textarea
attributes:
label: Steps To Reproduce
description: Steps to reproduce the behavior.
placeholder: |
1. In this environment...
2. With this config...
3. Run '...'
4. See error...
validations:
required: true
- type: textarea
id: logs
attributes:
label: Relevant log output
description: |
If applicable, log output to help explain your problem.
render: shell
validations:
required: false
- type: textarea
attributes:
label: Environment
description: |
examples:
- **OS**: Ubuntu 20.04
- **Python**: 3.9.12 (`python3 --version`)
- **dbt-core**: 1.1.1 (`dbt --version`)
value: |
- OS:
- Python:
- dbt:
render: markdown
validations:
required: false
- type: dropdown
id: database
attributes:
label: Which database adapter are you using with dbt?
description: If the bug is specific to the database or adapter, please open the issue in that adapter's repository instead
multiple: true
options:
- postgres
- redshift
- snowflake
- bigquery
- spark
- other (mention it in "Additional Context")
validations:
required: false
- type: textarea
attributes:
label: Additional Context
description: |
Links? References? Anything that will give us more context about the issue you are encountering!
Tip: You can attach images or log files by clicking this area to highlight it and then dragging files in.
validations:
required: false

41
.github/ISSUE_TEMPLATE/bug_report.md vendored Normal file
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@@ -0,0 +1,41 @@
---
name: Bug report
about: Report a bug or an issue you've found with dbt
title: ''
labels: bug, triage
assignees: ''
---
### Describe the bug
A clear and concise description of what the bug is. What command did you run? What happened?
### Steps To Reproduce
In as much detail as possible, please provide steps to reproduce the issue. Sample data that triggers the issue, example model code, etc is all very helpful here.
### Expected behavior
A clear and concise description of what you expected to happen.
### Screenshots and log output
If applicable, add screenshots or log output to help explain your problem.
### System information
**Which database are you using dbt with?**
- [ ] postgres
- [ ] redshift
- [ ] bigquery
- [ ] snowflake
- [ ] other (specify: ____________)
**The output of `dbt --version`:**
```
<output goes here>
```
**The operating system you're using:**
**The output of `python --version`:**
### Additional context
Add any other context about the problem here.

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@@ -1,23 +0,0 @@
blank_issues_enabled: false
contact_links:
- name: Ask the community for help
url: https://github.com/dbt-labs/docs.getdbt.com/discussions
about: Need help troubleshooting? Check out our guide on how to ask
- name: Contact dbt Cloud support
url: mailto:support@getdbt.com
about: Are you using dbt Cloud? Contact our support team for help!
- name: Participate in Discussions
url: https://github.com/dbt-labs/dbt-core/discussions
about: Do you have a Big Idea for dbt? Read open discussions, or start a new one
- name: Create an issue for dbt-redshift
url: https://github.com/dbt-labs/dbt-redshift/issues/new/choose
about: Report a bug or request a feature for dbt-redshift
- name: Create an issue for dbt-bigquery
url: https://github.com/dbt-labs/dbt-bigquery/issues/new/choose
about: Report a bug or request a feature for dbt-bigquery
- name: Create an issue for dbt-snowflake
url: https://github.com/dbt-labs/dbt-snowflake/issues/new/choose
about: Report a bug or request a feature for dbt-snowflake
- name: Create an issue for dbt-spark
url: https://github.com/dbt-labs/dbt-spark/issues/new/choose
about: Report a bug or request a feature for dbt-spark

View File

@@ -1,59 +0,0 @@
name: ✨ Feature
description: Propose a straightforward extension of dbt functionality
title: "[Feature] <title>"
labels: ["enhancement", "triage"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this feature request!
- type: checkboxes
attributes:
label: Is this your first time submitting a feature request?
description: >
We want to make sure that features are distinct and discoverable,
so that other members of the community can find them and offer their thoughts.
Issues are the right place to request straightforward extensions of existing dbt functionality.
For "big ideas" about future capabilities of dbt, we ask that you open a
[discussion](https://github.com/dbt-labs/dbt-core/discussions) in the "Ideas" category instead.
options:
- label: I have read the [expectations for open source contributors](https://docs.getdbt.com/docs/contributing/oss-expectations)
required: true
- label: I have searched the existing issues, and I could not find an existing issue for this feature
required: true
- label: I am requesting a straightforward extension of existing dbt functionality, rather than a Big Idea better suited to a discussion
required: true
- type: textarea
attributes:
label: Describe the feature
description: A clear and concise description of what you want to happen.
validations:
required: true
- type: textarea
attributes:
label: Describe alternatives you've considered
description: |
A clear and concise description of any alternative solutions or features you've considered.
validations:
required: false
- type: textarea
attributes:
label: Who will this benefit?
description: |
What kind of use case will this feature be useful for? Please be specific and provide examples, this will help us prioritize properly.
validations:
required: false
- type: input
attributes:
label: Are you interested in contributing this feature?
description: Let us know if you want to write some code, and how we can help.
validations:
required: false
- type: textarea
attributes:
label: Anything else?
description: |
Links? References? Anything that will give us more context about the feature you are suggesting!
validations:
required: false

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@@ -0,0 +1,23 @@
---
name: Feature request
about: Suggest an idea for dbt
title: ''
labels: enhancement, triage
assignees: ''
---
### Describe the feature
A clear and concise description of what you want to happen.
### Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
### Additional context
Is this feature database-specific? Which database(s) is/are relevant? Please include any other relevant context here.
### Who will this benefit?
What kind of use case will this feature be useful for? Please be specific and provide examples, this will help us prioritize properly.
### Are you interested in contributing this feature?
Let us know if you want to write some code, and how we can help.

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@@ -0,0 +1,28 @@
---
name: Final minor version release
about: Creates a tracking checklist of items for a final minor version release
title: "[Tracking] v#.##.# final release "
labels: 'release'
assignees: ''
---
### Release Core
- [ ] [Engineering] Verify all necessary changes exist on the release branch
- [ ] [Engineering] Follow [dbt-release workflow](https://www.notion.so/dbtlabs/Releasing-b97c5ea9a02949e79e81db3566bbc8ef#03ff37da697d4d8ba63d24fae1bfa817)
- [ ] [Product] Merge `next` into `current` for docs.getdbt.com
### Release Cloud
- [ ] [Engineering] Create a platform issue to update dbt Cloud and verify it is completed. [Example issue](https://github.com/dbt-labs/dbt-cloud/issues/3481)
- [ ] [Engineering] Determine if schemas have changed. If so, generate new schemas and push to schemas.getdbt.com
### Announce
- [ ] [Product] Update discourse
- [ ] [Product] Announce in dbt Slack
### Post-release
- [ ] [Engineering] [Bump plugin versions](https://www.notion.so/dbtlabs/Releasing-b97c5ea9a02949e79e81db3566bbc8ef#f01854e8da3641179fbcbe505bdf515c) (dbt-spark + dbt-presto), add compatibility as needed
- [ ] [Spark](https://github.com/dbt-labs/dbt-spark)
- [ ] [Presto](https://github.com/dbt-labs/dbt-presto)
- [ ] [Engineering] Create a platform issue to update dbt-spark versions to dbt Cloud. [Example issue](https://github.com/dbt-labs/dbt-cloud/issues/3481)
- [ ] [Product] Release new version of dbt-utils with new dbt version compatibility. If there are breaking changes requiring a minor version, plan upgrades of other packages that depend on dbt-utils.

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@@ -1,58 +0,0 @@
name: 🛠️ Implementation
description: This is an implementation ticket intended for use by the maintainers of dbt-core
title: "[<project>] <title>"
labels: ["user docs"]
body:
- type: markdown
attributes:
value: This is an implementation ticket intended for use by the maintainers of dbt-core
- type: checkboxes
attributes:
label: Housekeeping
description: >
A couple friendly reminders:
1. Remove the `user docs` label if the scope of this work does not require changes to https://docs.getdbt.com/docs: no end-user interface (e.g. yml spec, CLI, error messages, etc) or functional changes
2. Link any blocking issues in the "Blocked on" field under the "Core devs & maintainers" project.
options:
- label: I am a maintainer of dbt-core
required: true
- type: textarea
attributes:
label: Short description
description: |
Describe the scope of the ticket, a high-level implementation approach and any tradeoffs to consider
validations:
required: true
- type: textarea
attributes:
label: Acceptance criteria
description: |
What is the definition of done for this ticket? Include any relevant edge cases and/or test cases
validations:
required: true
- type: textarea
attributes:
label: Impact to Other Teams
description: |
Will this change impact other teams? Include details of the kinds of changes required (new tests, code changes, related tickets) and _add the relevant `Impact:[team]` label_.
placeholder: |
Example: This change impacts `dbt-redshift` because the tests will need to be modified. The `Impact:[Adapter]` label has been added.
validations:
required: true
- type: textarea
attributes:
label: Will backports be required?
description: |
Will this change need to be backported to previous versions? Add details, possible blockers to backporting and _add the relevant backport labels `backport 1.x.latest`_
placeholder: |
Example: Backport to 1.6.latest, 1.5.latest and 1.4.latest. Since 1.4 isn't using click, the backport may be complicated. The `backport 1.6.latest`, `backport 1.5.latest` and `backport 1.4.latest` labels have been added.
validations:
required: true
- type: textarea
attributes:
label: Context
description: |
Provide the "why", motivation, and alternative approaches considered -- linking to previous refinement issues, spikes, Notion docs as appropriate
validations:
validations:
required: false

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@@ -0,0 +1,29 @@
---
name: RC minor version release
about: Creates a tracking checklist of items for a RC minor version release
title: "[Tracking] v#.##.#RC# release "
labels: 'release'
assignees: ''
---
### Release Core
- [ ] [Engineering] Verify all necessary changes exist on the release branch
- [ ] [Engineering] Follow [dbt-release workflow](https://www.notion.so/dbtlabs/Releasing-b97c5ea9a02949e79e81db3566bbc8ef#03ff37da697d4d8ba63d24fae1bfa817)
- [ ] [Product] Update migration guide (next.docs.getdbt.com)
### Release Cloud
- [ ] [Engineering] Create a platform issue to update dbt Cloud and verify it is completed. [Example issue](https://github.com/dbt-labs/dbt-cloud/issues/3481)
- [ ] [Engineering] Determine if schemas have changed. If so, generate new schemas and push to schemas.getdbt.com
### Announce
- [ ] [Product] Publish discourse
- [ ] [Product] Announce in dbt Slack
### Post-release
- [ ] [Engineering] [Bump plugin versions](https://www.notion.so/dbtlabs/Releasing-b97c5ea9a02949e79e81db3566bbc8ef#f01854e8da3641179fbcbe505bdf515c) (dbt-spark + dbt-presto), add compatibility as needed
- [ ] [Spark](https://github.com/dbt-labs/dbt-spark)
- [ ] [Presto](https://github.com/dbt-labs/dbt-presto)
- [ ] [Engineering] Create a platform issue to update dbt-spark versions to dbt Cloud. [Example issue](https://github.com/dbt-labs/dbt-cloud/issues/3481)
- [ ] [Product] Release new version of dbt-utils with new dbt version compatibility. If there are breaking changes requiring a minor version, plan upgrades of other packages that depend on dbt-utils.
- [ ] [Engineering] Create an epic for the final release

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@@ -1,93 +0,0 @@
name: ☣️ Regression
description: Report a regression you've observed in a newer version of dbt
title: "[Regression] <title>"
labels: ["bug", "regression", "triage"]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this regression report!
- type: checkboxes
attributes:
label: Is this a regression in a recent version of dbt-core?
description: >
A regression is when documented functionality works as expected in an older version of dbt-core,
and no longer works after upgrading to a newer version of dbt-core
options:
- label: I believe this is a regression in dbt-core functionality
required: true
- label: I have searched the existing issues, and I could not find an existing issue for this regression
required: true
- type: textarea
attributes:
label: Current Behavior
description: A concise description of what you're experiencing.
validations:
required: true
- type: textarea
attributes:
label: Expected/Previous Behavior
description: A concise description of what you expected to happen.
validations:
required: true
- type: textarea
attributes:
label: Steps To Reproduce
description: Steps to reproduce the behavior.
placeholder: |
1. In this environment...
2. With this config...
3. Run '...'
4. See error...
validations:
required: true
- type: textarea
id: logs
attributes:
label: Relevant log output
description: |
If applicable, log output to help explain your problem.
render: shell
validations:
required: false
- type: textarea
attributes:
label: Environment
description: |
examples:
- **OS**: Ubuntu 20.04
- **Python**: 3.9.12 (`python3 --version`)
- **dbt-core (working version)**: 1.1.1 (`dbt --version`)
- **dbt-core (regression version)**: 1.2.0 (`dbt --version`)
value: |
- OS:
- Python:
- dbt (working version):
- dbt (regression version):
render: markdown
validations:
required: true
- type: dropdown
id: database
attributes:
label: Which database adapter are you using with dbt?
description: If the regression is specific to the database or adapter, please open the issue in that adapter's repository instead
multiple: true
options:
- postgres
- redshift
- snowflake
- bigquery
- spark
- other (mention it in "Additional Context")
validations:
required: false
- type: textarea
attributes:
label: Additional Context
description: |
Links? References? Anything that will give us more context about the issue you are encountering!
Tip: You can attach images or log files by clicking this area to highlight it and then dragging files in.
validations:
required: false

216
.github/_README.md vendored
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@@ -1,216 +0,0 @@
<!-- GitHub will publish this readme on the main repo page if the name is `README.md` so we've added the leading underscore to prevent this -->
<!-- Do not rename this file `README.md` -->
<!-- See https://docs.github.com/en/repositories/managing-your-repositorys-settings-and-features/customizing-your-repository/about-readmes -->
## What are GitHub Actions?
GitHub Actions are used for many different purposes. We use them to run tests in CI, validate PRs are in an expected state, and automate processes.
- [Overview of GitHub Actions](https://docs.github.com/en/actions/learn-github-actions/understanding-github-actions)
- [What's a workflow?](https://docs.github.com/en/actions/using-workflows/about-workflows)
- [GitHub Actions guides](https://docs.github.com/en/actions/guides)
___
## Where do actions and workflows live
We try to maintain actions that are shared across repositories in a single place so that necesary changes can be made in a single place.
[dbt-labs/actions](https://github.com/dbt-labs/actions/) is the central repository of actions and workflows we use across repositories.
GitHub Actions also live locally within a repository. The workflows can be found at `.github/workflows` from the root of the repository. These should be specific to that code base.
Note: We are actively moving actions into the central Action repository so there is currently some duplication across repositories.
___
## Basics of Using Actions
### Viewing Output
- View the detailed action output for your PR in the **Checks** tab of the PR. This only shows the most recent run. You can also view high level **Checks** output at the bottom on the PR.
- View _all_ action output for a repository from the [**Actions**](https://github.com/dbt-labs/dbt-core/actions) tab. Workflow results last 1 year. Artifacts last 90 days, unless specified otherwise in individual workflows.
This view often shows what seem like duplicates of the same workflow. This occurs when files are renamed but the workflow name has not changed. These are in fact _not_ duplicates.
You can see the branch the workflow runs from in this view. It is listed in the table between the workflow name and the time/duration of the run. When blank, the workflow is running in the context of the `main` branch.
### How to view what workflow file is being referenced from a run
- When viewing the output of a specific workflow run, click the 3 dots at the top right of the display. There will be an option to `View workflow file`.
### How to manually run a workflow
- If a workflow has the `on: workflow_dispatch` trigger, it can be manually triggered
- From the [**Actions**](https://github.com/dbt-labs/dbt-core/actions) tab, find the workflow you want to run, select it and fill in any inputs requied. That's it!
### How to re-run jobs
- Some actions cannot be rerun in the GitHub UI. Namely the snyk checks and the cla check. Snyk checks are rerun by closing and reopening the PR. You can retrigger the cla check by commenting on the PR with `@cla-bot check`
___
## General Standards
### Permissions
- By default, workflows have read permissions in the repository for the contents scope only when no permissions are explicitly set.
- It is best practice to always define the permissions explicitly. This will allow actions to continue to work when the default permissions on the repository are changed. It also allows explicit grants of the least permissions possible.
- There are a lot of permissions available. [Read up on them](https://docs.github.com/en/actions/using-jobs/assigning-permissions-to-jobs) if you're unsure what to use.
```yaml
permissions:
contents: read
pull-requests: write
```
### Secrets
- When to use a [Personal Access Token (PAT)](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token) vs the [GITHUB_TOKEN](https://docs.github.com/en/actions/security-guides/automatic-token-authentication) generated for the action?
The `GITHUB_TOKEN` is used by default. In most cases it is sufficient for what you need.
If you expect the workflow to result in a commit to that should retrigger workflows, you will need to use a Personal Access Token for the bot to commit the file. When using the GITHUB_TOKEN, the resulting commit will not trigger another GitHub Actions Workflow run. This is due to limitations set by GitHub. See [the docs](https://docs.github.com/en/actions/security-guides/automatic-token-authentication#using-the-github_token-in-a-workflow) for a more detailed explanation.
For example, we must use a PAT in our workflow to commit a new changelog yaml file for bot PRs. Once the file has been committed to the branch, it should retrigger the check to validate that a changelog exists on the PR. Otherwise, it would stay in a failed state since the check would never retrigger.
### Triggers
You can configure your workflows to run when specific activity on GitHub happens, at a scheduled time, or when an event outside of GitHub occurs. Read more details in the [GitHub docs](https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows).
These triggers are under the `on` key of the workflow and more than one can be listed.
```yaml
on:
push:
branches:
- "main"
- "*.latest"
- "releases/*"
pull_request:
# catch when the PR is opened with the label or when the label is added
types: [opened, labeled]
workflow_dispatch:
```
Some triggers of note that we use:
- `push` - Runs your workflow when you push a commit or tag.
- `pull_request` - Runs your workflow when activity on a pull request in the workflow's repository occurs. Takes in a list of activity types (opened, labeled, etc) if appropriate.
- `pull_request_target` - Same as `pull_request` but runs in the context of the PR target branch.
- `workflow_call` - used with reusable workflows. Triggered by another workflow calling it.
- `workflow_dispatch` - Gives the ability to manually trigger a workflow from the GitHub API, GitHub CLI, or GitHub browser interface.
### Basic Formatting
- Add a description of what your workflow does at the top in this format
```
# **what?**
# Describe what the action does.
# **why?**
# Why does this action exist?
# **when?**
# How/when will it be triggered?
```
- Leave blank lines between steps and jobs
```yaml
jobs:
dependency_changelog:
runs-on: ubuntu-latest
steps:
- name: Get File Name Timestamp
id: filename_time
uses: nanzm/get-time-action@v1.1
with:
format: 'YYYYMMDD-HHmmss'
- name: Get File Content Timestamp
id: file_content_time
uses: nanzm/get-time-action@v1.1
with:
format: 'YYYY-MM-DDTHH:mm:ss.000000-05:00'
- name: Generate Filepath
id: fp
run: |
FILEPATH=.changes/unreleased/Dependencies-${{ steps.filename_time.outputs.time }}.yaml
echo "FILEPATH=$FILEPATH" >> $GITHUB_OUTPUT
```
- Print out all variables you will reference as the first step of a job. This allows for easier debugging. The first job should log all inputs. Subsequent jobs should reference outputs of other jobs, if present.
When possible, generate variables at the top of your workflow in a single place to reference later. This is not always strictly possible since you may generate a value to be used later mid-workflow.
Be sure to use quotes around these logs so special characters are not interpreted.
```yaml
job1:
- name: "[DEBUG] Print Variables"
run: |
echo "all variables defined as inputs"
echo "The last commit sha in the release: ${{ inputs.sha }}"
echo "The release version number: ${{ inputs.version_number }}"
echo "The changelog_path: ${{ inputs.changelog_path }}"
echo "The build_script_path: ${{ inputs.build_script_path }}"
echo "The s3_bucket_name: ${{ inputs.s3_bucket_name }}"
echo "The package_test_command: ${{ inputs.package_test_command }}"
# collect all the variables that need to be used in subsequent jobs
- name: Set Variables
id: variables
run: |
echo "important_path='performance/runner/Cargo.toml'" >> $GITHUB_OUTPUT
echo "release_id=${{github.event.inputs.release_id}}" >> $GITHUB_OUTPUT
echo "open_prs=${{github.event.inputs.open_prs}}" >> $GITHUB_OUTPUT
job2:
needs: [job1]
- name: "[DEBUG] Print Variables"
run: |
echo "all variables defined in job1 > Set Variables > outputs"
echo "important_path: ${{ needs.job1.outputs.important_path }}"
echo "release_id: ${{ needs.job1.outputs.release_id }}"
echo "open_prs: ${{ needs.job1.outputs.open_prs }}"
```
- When it's not obvious what something does, add a comment!
___
## Tips
### Context
- The [GitHub CLI](https://cli.github.com/) is available in the default runners
- Actions run in your context. ie, using an action from the marketplace that uses the GITHUB_TOKEN uses the GITHUB_TOKEN generated by your workflow run.
### Actions from the Marketplace
- Dont use external actions for things that can easily be accomplished manually.
- Always read through what an external action does before using it! Often an action in the GitHub Actions Marketplace can be replaced with a few lines in bash. This is much more maintainable (and wont change under us) and clear as to whats actually happening. It also prevents any
- Pin actions _we don't control_ to tags.
### Connecting to AWS
- Authenticate with the aws managed workflow
```yaml
- name: Configure AWS credentials from Test account
uses: aws-actions/configure-aws-credentials@v2
with:
aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
aws-region: us-east-1
```
- Then access with the aws command that comes installed on the action runner machines
```yaml
- name: Copy Artifacts from S3 via CLI
run: aws s3 cp ${{ env.s3_bucket }} . --recursive
```
### Testing
- Depending on what your action does, you may be able to use [`act`](https://github.com/nektos/act) to test the action locally. Some features of GitHub Actions do not work with `act`, among those are reusable workflows. If you can't use `act`, you'll have to push your changes up before being able to test. This can be slow.

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@@ -1,14 +0,0 @@
FROM python:3-slim AS builder
ADD . /app
WORKDIR /app
# We are installing a dependency here directly into our app source dir
RUN pip install --target=/app requests packaging
# A distroless container image with Python and some basics like SSL certificates
# https://github.com/GoogleContainerTools/distroless
FROM gcr.io/distroless/python3-debian10
COPY --from=builder /app /app
WORKDIR /app
ENV PYTHONPATH /app
CMD ["/app/main.py"]

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@@ -1,50 +0,0 @@
# Github package 'latest' tag wrangler for containers
## Usage
Plug in the necessary inputs to determine if the container being built should be tagged 'latest; at the package level, for example `dbt-redshift:latest`.
## Inputs
| Input | Description |
| - | - |
| `package` | Name of the GH package to check against |
| `new_version` | Semver of new container |
| `gh_token` | GH token with package read scope|
| `halt_on_missing` | Return non-zero exit code if requested package does not exist. (defaults to false)|
## Outputs
| Output | Description |
| - | - |
| `latest` | Wether or not the new container should be tagged 'latest'|
| `minor_latest` | Wether or not the new container should be tagged major.minor.latest |
## Example workflow
```yaml
name: Ship it!
on:
workflow_dispatch:
inputs:
package:
description: The package to publish
required: true
version_number:
description: The version number
required: true
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- name: Wrangle latest tag
id: is_latest
uses: ./.github/actions/latest-wrangler
with:
package: ${{ github.event.inputs.package }}
new_version: ${{ github.event.inputs.new_version }}
gh_token: ${{ secrets.GITHUB_TOKEN }}
- name: Print the results
run: |
echo "Is it latest? Survey says: ${{ steps.is_latest.outputs.latest }} !"
echo "Is it minor.latest? Survey says: ${{ steps.is_latest.outputs.minor_latest }} !"
```

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@@ -1,20 +0,0 @@
name: "Github package 'latest' tag wrangler for containers"
description: "Determines wether or not a given dbt container should be given a bare 'latest' tag (I.E. dbt-core:latest)"
inputs:
package_name:
description: "Package to check (I.E. dbt-core, dbt-redshift, etc)"
required: true
new_version:
description: "Semver of the container being built (I.E. 1.0.4)"
required: true
gh_token:
description: "Auth token for github (must have view packages scope)"
required: true
outputs:
latest:
description: "Wether or not built container should be tagged latest (bool)"
minor_latest:
description: "Wether or not built container should be tagged minor.latest (bool)"
runs:
using: "docker"
image: "Dockerfile"

View File

@@ -1,26 +0,0 @@
name: Ship it!
on:
workflow_dispatch:
inputs:
package:
description: The package to publish
required: true
version_number:
description: The version number
required: true
jobs:
build:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Wrangle latest tag
id: is_latest
uses: ./.github/actions/latest-wrangler
with:
package: ${{ github.event.inputs.package }}
new_version: ${{ github.event.inputs.new_version }}
gh_token: ${{ secrets.GITHUB_TOKEN }}
- name: Print the results
run: |
echo "Is it latest? Survey says: ${{ steps.is_latest.outputs.latest }} !"

View File

@@ -1,6 +0,0 @@
{
"inputs": {
"version_number": "1.0.1",
"package": "dbt-redshift"
}
}

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@@ -1,98 +0,0 @@
import os
import sys
import requests
from distutils.util import strtobool
from typing import Union
from packaging.version import parse, Version
if __name__ == "__main__":
# get inputs
package = os.environ["INPUT_PACKAGE"]
new_version = parse(os.environ["INPUT_NEW_VERSION"])
gh_token = os.environ["INPUT_GH_TOKEN"]
halt_on_missing = strtobool(os.environ.get("INPUT_HALT_ON_MISSING", "False"))
# get package metadata from github
package_request = requests.get(
f"https://api.github.com/orgs/dbt-labs/packages/container/{package}/versions",
auth=("", gh_token),
)
package_meta = package_request.json()
# Log info if we don't get a 200
if package_request.status_code != 200:
print(f"Call to GH API failed: {package_request.status_code} {package_meta['message']}")
# Make an early exit if there is no matching package in github
if package_request.status_code == 404:
if halt_on_missing:
sys.exit(1)
# everything is the latest if the package doesn't exist
github_output = os.environ.get("GITHUB_OUTPUT")
with open(github_output, "at", encoding="utf-8") as gh_output:
gh_output.write("latest=True")
gh_output.write("minor_latest=True")
sys.exit(0)
# TODO: verify package meta is "correct"
# https://github.com/dbt-labs/dbt-core/issues/4640
# map versions and tags
version_tag_map = {
version["id"]: version["metadata"]["container"]["tags"] for version in package_meta
}
# is pre-release
pre_rel = True if any(x in str(new_version) for x in ["a", "b", "rc"]) else False
# semver of current latest
for version, tags in version_tag_map.items():
if "latest" in tags:
# N.B. This seems counterintuitive, but we expect any version tagged
# 'latest' to have exactly three associated tags:
# latest, major.minor.latest, and major.minor.patch.
# Subtracting everything that contains the string 'latest' gets us
# the major.minor.patch which is what's needed for comparison.
current_latest = parse([tag for tag in tags if "latest" not in tag][0])
else:
current_latest = False
# semver of current_minor_latest
for version, tags in version_tag_map.items():
if f"{new_version.major}.{new_version.minor}.latest" in tags:
# Similar to above, only now we expect exactly two tags:
# major.minor.patch and major.minor.latest
current_minor_latest = parse([tag for tag in tags if "latest" not in tag][0])
else:
current_minor_latest = False
def is_latest(
pre_rel: bool, new_version: Version, remote_latest: Union[bool, Version]
) -> bool:
"""Determine if a given contaier should be tagged 'latest' based on:
- it's pre-release status
- it's version
- the version of a previously identified container tagged 'latest'
:param pre_rel: Wether or not the version of the new container is a pre-release
:param new_version: The version of the new container
:param remote_latest: The version of the previously identified container that's
already tagged latest or False
"""
# is a pre-release = not latest
if pre_rel:
return False
# + no latest tag found = is latest
if not remote_latest:
return True
# + if remote version is lower than current = is latest, else not latest
return True if remote_latest <= new_version else False
latest = is_latest(pre_rel, new_version, current_latest)
minor_latest = is_latest(pre_rel, new_version, current_minor_latest)
github_output = os.environ.get("GITHUB_OUTPUT")
with open(github_output, "at", encoding="utf-8") as gh_output:
gh_output.write(f"latest={latest}")
gh_output.write(f"minor_latest={minor_latest}")

View File

@@ -11,11 +11,26 @@ updates:
schedule:
interval: "daily"
rebase-strategy: "disabled"
- package-ecosystem: "pip"
directory: "/plugins/bigquery"
schedule:
interval: "daily"
rebase-strategy: "disabled"
- package-ecosystem: "pip"
directory: "/plugins/postgres"
schedule:
interval: "daily"
rebase-strategy: "disabled"
- package-ecosystem: "pip"
directory: "/plugins/redshift"
schedule:
interval: "daily"
rebase-strategy: "disabled"
- package-ecosystem: "pip"
directory: "/plugins/snowflake"
schedule:
interval: "daily"
rebase-strategy: "disabled"
# docker dependencies
- package-ecosystem: "docker"
@@ -28,10 +43,3 @@ updates:
schedule:
interval: "weekly"
rebase-strategy: "disabled"
# github dependencies
- package-ecosystem: "github-actions"
directory: "/"
schedule:
interval: "weekly"
rebase-strategy: "disabled"

View File

@@ -5,29 +5,17 @@ resolves #
PRs for code changes without an associated issue *will not be merged*.
See CONTRIBUTING.md for more information.
Add the `user docs` label to this PR if it will need docs changes. An
issue will get opened in docs.getdbt.com upon successful merge of this PR.
Example:
resolves #1234
-->
### Problem
### Description
<!---
Describe the problem this PR is solving. What is the application state
before this PR is merged?
-->
### Solution
<!---
Describe the way this PR solves the above problem. Add as much detail as you
can to help reviewers understand your changes. Include any alternatives and
tradeoffs you considered.
-->
<!--- Describe the Pull Request here -->
### Checklist
- [ ] I have read [the contributing guide](https://github.com/dbt-labs/dbt-core/blob/main/CONTRIBUTING.md) and understand what's expected of me
- [ ] I have run this code in development and it appears to resolve the stated issue
- [ ] I have signed the [CLA](https://docs.getdbt.com/docs/contributor-license-agreements)
- [ ] I have run this code in development and it appears to resolve the stated issue
- [ ] This PR includes tests, or tests are not required/relevant for this PR
- [ ] This PR has no interface changes (e.g. macros, cli, logs, json artifacts, config files, adapter interface, etc) or this PR has already received feedback and approval from Product or DX
- [ ] This PR includes [type annotations](https://docs.python.org/3/library/typing.html) for new and modified functions
- [ ] I have updated the `CHANGELOG.md` and added information about my change to the "dbt next" section.

View File

@@ -0,0 +1,95 @@
module.exports = ({ context }) => {
const defaultPythonVersion = "3.8";
const supportedPythonVersions = ["3.6", "3.7", "3.8", "3.9"];
const supportedAdapters = ["snowflake", "postgres", "bigquery", "redshift"];
// if PR, generate matrix based on files changed and PR labels
if (context.eventName.includes("pull_request")) {
// `changes` is a list of adapter names that have related
// file changes in the PR
// ex: ['postgres', 'snowflake']
const changes = JSON.parse(process.env.CHANGES);
const labels = context.payload.pull_request.labels.map(({ name }) => name);
console.log("labels", labels);
console.log("changes", changes);
const testAllLabel = labels.includes("test all");
const include = [];
for (const adapter of supportedAdapters) {
if (
changes.includes(adapter) ||
testAllLabel ||
labels.includes(`test ${adapter}`)
) {
for (const pythonVersion of supportedPythonVersions) {
if (
pythonVersion === defaultPythonVersion ||
labels.includes(`test python${pythonVersion}`) ||
testAllLabel
) {
// always run tests on ubuntu by default
include.push({
os: "ubuntu-latest",
adapter,
"python-version": pythonVersion,
});
if (labels.includes("test windows") || testAllLabel) {
include.push({
os: "windows-latest",
adapter,
"python-version": pythonVersion,
});
}
if (labels.includes("test macos") || testAllLabel) {
include.push({
os: "macos-latest",
adapter,
"python-version": pythonVersion,
});
}
}
}
}
}
console.log("matrix", { include });
return {
include,
};
}
// if not PR, generate matrix of python version, adapter, and operating
// system to run integration tests on
const include = [];
// run for all adapters and python versions on ubuntu
for (const adapter of supportedAdapters) {
for (const pythonVersion of supportedPythonVersions) {
include.push({
os: 'ubuntu-latest',
adapter: adapter,
"python-version": pythonVersion,
});
}
}
// additionally include runs for all adapters, on macos and windows,
// but only for the default python version
for (const adapter of supportedAdapters) {
for (const operatingSystem of ["windows-latest", "macos-latest"]) {
include.push({
os: operatingSystem,
adapter: adapter,
"python-version": defaultPythonVersion,
});
}
}
console.log("matrix", { include });
return {
include,
};
};

View File

@@ -1,40 +0,0 @@
# **what?**
# When a PR is merged, if it has the backport label, it will create
# a new PR to backport those changes to the given branch. If it can't
# cleanly do a backport, it will comment on the merged PR of the failure.
#
# Label naming convention: "backport <branch name to backport to>"
# Example: backport 1.0.latest
#
# You MUST "Squash and merge" the original PR or this won't work.
# **why?**
# Changes sometimes need to be backported to release branches.
# This automates the backporting process
# **when?**
# Once a PR is "Squash and merge"'d, by adding a backport label, this is triggered
name: Backport
on:
pull_request:
types:
- labeled
permissions:
contents: write
pull-requests: write
jobs:
backport:
name: Backport
runs-on: ubuntu-latest
# Only react to merged PRs for security reasons.
# See https://docs.github.com/en/actions/using-workflows/events-that-trigger-workflows#pull_request_target.
if: >
github.event.pull_request.merged
&& contains(github.event.label.name, 'backport')
steps:
- uses: tibdex/backport@v2.0.3
with:
github_token: ${{ secrets.GITHUB_TOKEN }}

View File

@@ -1,61 +0,0 @@
# **what?**
# When bots create a PR, this action will add a corresponding changie yaml file to that
# PR when a specific label is added.
#
# The file is created off a template:
#
# kind: <per action matrix>
# body: <PR title>
# time: <current timestamp>
# custom:
# Author: <PR User Login (generally the bot)>
# Issue: 4904
# PR: <PR number>
#
# **why?**
# Automate changelog generation for more visability with automated bot PRs.
#
# **when?**
# Once a PR is created, label should be added to PR before or after creation. You can also
# manually trigger this by adding the appropriate label at any time.
#
# **how to add another bot?**
# Add the label and changie kind to the include matrix. That's it!
#
name: Bot Changelog
on:
pull_request:
# catch when the PR is opened with the label or when the label is added
types: [labeled]
permissions:
contents: write
pull-requests: read
jobs:
generate_changelog:
strategy:
matrix:
include:
- label: "dependencies"
changie_kind: "Dependencies"
- label: "snyk"
changie_kind: "Security"
runs-on: ubuntu-latest
steps:
- name: Create and commit changelog on bot PR
if: ${{ contains(github.event.pull_request.labels.*.name, matrix.label) }}
id: bot_changelog
uses: emmyoop/changie_bot@v1.1.0
with:
GITHUB_TOKEN: ${{ secrets.FISHTOWN_BOT_PAT }}
commit_author_name: "Github Build Bot"
commit_author_email: "<buildbot@fishtownanalytics.com>"
commit_message: "Add automated changelog yaml from template for bot PR"
changie_kind: ${{ matrix.changie_kind }}
label: ${{ matrix.label }}
custom_changelog_string: "custom:\n Author: ${{ github.event.pull_request.user.login }}\n Issue: ${{ github.event.pull_request.number }}"

View File

@@ -1,38 +0,0 @@
# **what?**
# Checks that a file has been committed under the /.changes directory
# as a new CHANGELOG entry. Cannot check for a specific filename as
# it is dynamically generated by change type and timestamp.
# This workflow runs on pull_request_target because it requires
# secrets to post comments.
# **why?**
# Ensure code change gets reflected in the CHANGELOG.
# **when?**
# This will run for all PRs going into main and *.latest. It will
# run when they are opened, reopened, when any label is added or removed
# and when new code is pushed to the branch. The action will then get
# skipped if the 'Skip Changelog' label is present is any of the labels.
name: Check Changelog Entry
on:
pull_request_target:
types: [opened, reopened, labeled, unlabeled, synchronize]
workflow_dispatch:
defaults:
run:
shell: bash
permissions:
contents: read
pull-requests: write
jobs:
changelog:
uses: dbt-labs/actions/.github/workflows/changelog-existence.yml@main
with:
changelog_comment: 'Thank you for your pull request! We could not find a changelog entry for this change. For details on how to document a change, see [the contributing guide](https://github.com/dbt-labs/dbt-core/blob/main/CONTRIBUTING.md#adding-changelog-entry).'
skip_label: 'Skip Changelog'
secrets: inherit

View File

@@ -1,41 +0,0 @@
# **what?**
# Cuts a new `*.latest` branch
# Also cleans up all files in `.changes/unreleased` and `.changes/previous verion on
# `main` and bumps `main` to the input version.
# **why?**
# Generally reduces the workload of engineers and reduces error. Allow automation.
# **when?**
# This will run when called manually.
name: Cut new release branch
on:
workflow_dispatch:
inputs:
version_to_bump_main:
description: 'The alpha version main should bump to (ex. 1.6.0a1)'
required: true
new_branch_name:
description: 'The full name of the new branch (ex. 1.5.latest)'
required: true
defaults:
run:
shell: bash
permissions:
contents: write
jobs:
cut_branch:
name: "Cut branch and clean up main for dbt-core"
uses: dbt-labs/actions/.github/workflows/cut-release-branch.yml@main
with:
version_to_bump_main: ${{ inputs.version_to_bump_main }}
new_branch_name: ${{ inputs.new_branch_name }}
PR_title: "Cleanup main after cutting new ${{ inputs.new_branch_name }} branch"
PR_body: "All adapter PRs will fail CI until the dbt-core PR has been merged due to release version conflicts."
secrets:
FISHTOWN_BOT_PAT: ${{ secrets.FISHTOWN_BOT_PAT }}

View File

@@ -1,43 +0,0 @@
# **what?**
# Open an issue in docs.getdbt.com when a PR is labeled `user docs`
# **why?**
# To reduce barriers for keeping docs up to date
# **when?**
# When a PR is labeled `user docs` and is merged. Runs on pull_request_target to run off the workflow already merged,
# not the workflow that existed on the PR branch. This allows old PRs to get comments.
name: Open issues in docs.getdbt.com repo when a PR is labeled
run-name: "Open an issue in docs.getdbt.com for PR #${{ github.event.pull_request.number }}"
on:
pull_request_target:
types: [labeled, closed]
defaults:
run:
shell: bash
permissions:
issues: write # opens new issues
pull-requests: write # comments on PRs
jobs:
open_issues:
# we only want to run this when the PR has been merged or the label in the labeled event is `user docs`. Otherwise it runs the
# risk of duplicaton of issues being created due to merge and label both triggering this workflow to run and neither having
# generating the comment before the other runs. This lives here instead of the shared workflow because this is where we
# decide if it should run or not.
if: |
(github.event.pull_request.merged == true) &&
((github.event.action == 'closed' && contains( github.event.pull_request.labels.*.name, 'user docs')) ||
(github.event.action == 'labeled' && github.event.label.name == 'user docs'))
uses: dbt-labs/actions/.github/workflows/open-issue-in-repo.yml@main
with:
issue_repository: "dbt-labs/docs.getdbt.com"
issue_title: "Docs Changes Needed from ${{ github.event.repository.name }} PR #${{ github.event.pull_request.number }}"
issue_body: "At a minimum, update body to include a link to the page on docs.getdbt.com requiring updates and what part(s) of the page you would like to see updated."
secrets: inherit

266
.github/workflows/integration.yml vendored Normal file
View File

@@ -0,0 +1,266 @@
# **what?**
# This workflow runs all integration tests for supported OS
# and python versions and core adapters. If triggered by PR,
# the workflow will only run tests for adapters related
# to code changes. Use the `test all` and `test ${adapter}`
# label to run all or additional tests. Use `ok to test`
# label to mark PRs from forked repositories that are safe
# to run integration tests for. Requires secrets to run
# against different warehouses.
# **why?**
# This checks the functionality of dbt from a user's perspective
# and attempts to catch functional regressions.
# **when?**
# This workflow will run on every push to a protected branch
# and when manually triggered. It will also run for all PRs, including
# PRs from forks. The workflow will be skipped until there is a label
# to mark the PR as safe to run.
name: Adapter Integration Tests
on:
# pushes to release branches
push:
branches:
- "main"
- "develop"
- "*.latest"
- "releases/*"
# all PRs, important to note that `pull_request_target` workflows
# will run in the context of the target branch of a PR
pull_request_target:
# manual tigger
workflow_dispatch:
# explicitly turn off permissions for `GITHUB_TOKEN`
permissions: read-all
# will cancel previous workflows triggered by the same event and for the same ref for PRs or same SHA otherwise
concurrency:
group: ${{ github.workflow }}-${{ github.event_name }}-${{ contains(github.event_name, 'pull_request') && github.event.pull_request.head.ref || github.sha }}
cancel-in-progress: true
# sets default shell to bash, for all operating systems
defaults:
run:
shell: bash
jobs:
# generate test metadata about what files changed and the testing matrix to use
test-metadata:
# run if not a PR from a forked repository or has a label to mark as safe to test
if: >-
github.event_name != 'pull_request_target' ||
github.event.pull_request.head.repo.full_name == github.repository ||
contains(github.event.pull_request.labels.*.name, 'ok to test')
runs-on: ubuntu-latest
outputs:
matrix: ${{ steps.generate-matrix.outputs.result }}
steps:
- name: Check out the repository (non-PR)
if: github.event_name != 'pull_request_target'
uses: actions/checkout@v2
with:
persist-credentials: false
- name: Check out the repository (PR)
if: github.event_name == 'pull_request_target'
uses: actions/checkout@v2
with:
persist-credentials: false
ref: ${{ github.event.pull_request.head.sha }}
- name: Check if relevant files changed
# https://github.com/marketplace/actions/paths-changes-filter
# For each filter, it sets output variable named by the filter to the text:
# 'true' - if any of changed files matches any of filter rules
# 'false' - if none of changed files matches any of filter rules
# also, returns:
# `changes` - JSON array with names of all filters matching any of the changed files
uses: dorny/paths-filter@v2
id: get-changes
with:
token: ${{ secrets.GITHUB_TOKEN }}
filters: |
postgres:
- 'core/**'
- 'plugins/postgres/**'
- 'dev-requirements.txt'
snowflake:
- 'core/**'
- 'plugins/snowflake/**'
bigquery:
- 'core/**'
- 'plugins/bigquery/**'
redshift:
- 'core/**'
- 'plugins/redshift/**'
- 'plugins/postgres/**'
- name: Generate integration test matrix
id: generate-matrix
uses: actions/github-script@v4
env:
CHANGES: ${{ steps.get-changes.outputs.changes }}
with:
script: |
const script = require('./.github/scripts/integration-test-matrix.js')
const matrix = script({ context })
console.log(matrix)
return matrix
test:
name: ${{ matrix.adapter }} / python ${{ matrix.python-version }} / ${{ matrix.os }}
# run if not a PR from a forked repository or has a label to mark as safe to test
# also checks that the matrix generated is not empty
if: >-
needs.test-metadata.outputs.matrix &&
fromJSON( needs.test-metadata.outputs.matrix ).include[0] &&
(
github.event_name != 'pull_request_target' ||
github.event.pull_request.head.repo.full_name == github.repository ||
contains(github.event.pull_request.labels.*.name, 'ok to test')
)
runs-on: ${{ matrix.os }}
needs: test-metadata
strategy:
fail-fast: false
matrix: ${{ fromJSON(needs.test-metadata.outputs.matrix) }}
env:
TOXENV: integration-${{ matrix.adapter }}
PYTEST_ADDOPTS: "-v --color=yes -n4 --csv integration_results.csv"
DBT_INVOCATION_ENV: github-actions
steps:
- name: Check out the repository
if: github.event_name != 'pull_request_target'
uses: actions/checkout@v2
with:
persist-credentials: false
# explicity checkout the branch for the PR,
# this is necessary for the `pull_request_target` event
- name: Check out the repository (PR)
if: github.event_name == 'pull_request_target'
uses: actions/checkout@v2
with:
persist-credentials: false
ref: ${{ github.event.pull_request.head.sha }}
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Set up postgres (linux)
if: |
matrix.adapter == 'postgres' &&
runner.os == 'Linux'
uses: ./.github/actions/setup-postgres-linux
- name: Set up postgres (macos)
if: |
matrix.adapter == 'postgres' &&
runner.os == 'macOS'
uses: ./.github/actions/setup-postgres-macos
- name: Set up postgres (windows)
if: |
matrix.adapter == 'postgres' &&
runner.os == 'Windows'
uses: ./.github/actions/setup-postgres-windows
- name: Install python dependencies
run: |
pip install --upgrade pip
pip install tox
pip --version
tox --version
- name: Run tox (postgres)
if: matrix.adapter == 'postgres'
run: tox
- name: Run tox (redshift)
if: matrix.adapter == 'redshift'
env:
REDSHIFT_TEST_DBNAME: ${{ secrets.REDSHIFT_TEST_DBNAME }}
REDSHIFT_TEST_PASS: ${{ secrets.REDSHIFT_TEST_PASS }}
REDSHIFT_TEST_USER: ${{ secrets.REDSHIFT_TEST_USER }}
REDSHIFT_TEST_PORT: ${{ secrets.REDSHIFT_TEST_PORT }}
REDSHIFT_TEST_HOST: ${{ secrets.REDSHIFT_TEST_HOST }}
run: tox
- name: Run tox (snowflake)
if: matrix.adapter == 'snowflake'
env:
SNOWFLAKE_TEST_ACCOUNT: ${{ secrets.SNOWFLAKE_TEST_ACCOUNT }}
SNOWFLAKE_TEST_PASSWORD: ${{ secrets.SNOWFLAKE_TEST_PASSWORD }}
SNOWFLAKE_TEST_USER: ${{ secrets.SNOWFLAKE_TEST_USER }}
SNOWFLAKE_TEST_WAREHOUSE: ${{ secrets.SNOWFLAKE_TEST_WAREHOUSE }}
SNOWFLAKE_TEST_OAUTH_REFRESH_TOKEN: ${{ secrets.SNOWFLAKE_TEST_OAUTH_REFRESH_TOKEN }}
SNOWFLAKE_TEST_OAUTH_CLIENT_ID: ${{ secrets.SNOWFLAKE_TEST_OAUTH_CLIENT_ID }}
SNOWFLAKE_TEST_OAUTH_CLIENT_SECRET: ${{ secrets.SNOWFLAKE_TEST_OAUTH_CLIENT_SECRET }}
SNOWFLAKE_TEST_ALT_DATABASE: ${{ secrets.SNOWFLAKE_TEST_ALT_DATABASE }}
SNOWFLAKE_TEST_ALT_WAREHOUSE: ${{ secrets.SNOWFLAKE_TEST_ALT_WAREHOUSE }}
SNOWFLAKE_TEST_DATABASE: ${{ secrets.SNOWFLAKE_TEST_DATABASE }}
SNOWFLAKE_TEST_QUOTED_DATABASE: ${{ secrets.SNOWFLAKE_TEST_QUOTED_DATABASE }}
SNOWFLAKE_TEST_ROLE: ${{ secrets.SNOWFLAKE_TEST_ROLE }}
run: tox
- name: Run tox (bigquery)
if: matrix.adapter == 'bigquery'
env:
BIGQUERY_TEST_SERVICE_ACCOUNT_JSON: ${{ secrets.BIGQUERY_TEST_SERVICE_ACCOUNT_JSON }}
BIGQUERY_TEST_ALT_DATABASE: ${{ secrets.BIGQUERY_TEST_ALT_DATABASE }}
run: tox
- uses: actions/upload-artifact@v2
if: always()
with:
name: logs
path: ./logs
- name: Get current date
if: always()
id: date
run: echo "::set-output name=date::$(date +'%Y-%m-%dT%H_%M_%S')" #no colons allowed for artifacts
- uses: actions/upload-artifact@v2
if: always()
with:
name: integration_results_${{ matrix.python-version }}_${{ matrix.os }}_${{ matrix.adapter }}-${{ steps.date.outputs.date }}.csv
path: integration_results.csv
require-label-comment:
runs-on: ubuntu-latest
needs: test
permissions:
pull-requests: write
steps:
- name: Needs permission PR comment
if: >-
needs.test.result == 'skipped' &&
github.event_name == 'pull_request_target' &&
github.event.pull_request.head.repo.full_name != github.repository
uses: unsplash/comment-on-pr@master
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
with:
msg: |
"You do not have permissions to run integration tests, @dbt-labs/core "\
"needs to label this PR with `ok to test` in order to run integration tests!"
check_for_duplicate_msg: true

View File

@@ -1,26 +0,0 @@
# **what?**
# Mirrors issues into Jira. Includes the information: title,
# GitHub Issue ID and URL
# **why?**
# Jira is our tool for tracking and we need to see these issues in there
# **when?**
# On issue creation or when an issue is labeled `Jira`
name: Jira Issue Creation
on:
issues:
types: [opened, labeled]
permissions:
issues: write
jobs:
call-creation-action:
uses: dbt-labs/actions/.github/workflows/jira-creation-actions.yml@main
secrets:
JIRA_BASE_URL: ${{ secrets.JIRA_BASE_URL }}
JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}

View File

@@ -1,26 +0,0 @@
# **what?**
# Calls mirroring Jira label Action. Includes adding a new label
# to an existing issue or removing a label as well
# **why?**
# Jira is our tool for tracking and we need to see these labels in there
# **when?**
# On labels being added or removed from issues
name: Jira Label Mirroring
on:
issues:
types: [labeled, unlabeled]
permissions:
issues: read
jobs:
call-label-action:
uses: dbt-labs/actions/.github/workflows/jira-label-actions.yml@main
secrets:
JIRA_BASE_URL: ${{ secrets.JIRA_BASE_URL }}
JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}

View File

@@ -1,27 +0,0 @@
# **what?**
# Transition a Jira issue to a new state
# Only supports these GitHub Issue transitions:
# closed, deleted, reopened
# **why?**
# Jira needs to be kept up-to-date
# **when?**
# On issue closing, deletion, reopened
name: Jira Issue Transition
on:
issues:
types: [closed, deleted, reopened]
# no special access is needed
permissions: read-all
jobs:
call-transition-action:
uses: dbt-labs/actions/.github/workflows/jira-transition-actions.yml@main
secrets:
JIRA_BASE_URL: ${{ secrets.JIRA_BASE_URL }}
JIRA_USER_EMAIL: ${{ secrets.JIRA_USER_EMAIL }}
JIRA_API_TOKEN: ${{ secrets.JIRA_API_TOKEN }}

View File

@@ -1,8 +1,9 @@
# **what?**
# Runs code quality checks, unit tests, integration tests and
# verifies python build on all code commited to the repository. This workflow
# should not require any secrets since it runs for PRs from forked repos. By
# default, secrets are not passed to workflows running from a forked repos.
# Runs code quality checks, unit tests, and verifies python build on
# all code commited to the repository. This workflow should not
# require any secrets since it runs for PRs from forked repos.
# By default, secrets are not passed to workflows running from
# a forked repo.
# **why?**
# Ensure code for dbt meets a certain quality standard.
@@ -17,6 +18,7 @@ on:
push:
branches:
- "main"
- "develop"
- "*.latest"
- "releases/*"
pull_request:
@@ -33,223 +35,85 @@ defaults:
run:
shell: bash
# top-level adjustments can be made here
env:
# number of parallel processes to spawn for python integration testing
PYTHON_INTEGRATION_TEST_WORKERS: 5
jobs:
code-quality:
name: code-quality
name: ${{ matrix.toxenv }}
runs-on: ubuntu-latest
timeout-minutes: 10
strategy:
fail-fast: false
matrix:
toxenv: [flake8, mypy]
env:
TOXENV: ${{ matrix.toxenv }}
PYTEST_ADDOPTS: "-v --color=yes"
steps:
- name: Check out the repository
uses: actions/checkout@v4
uses: actions/checkout@v2
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: '3.9'
uses: actions/setup-python@v2
- name: Install python dependencies
run: |
python -m pip install --user --upgrade pip
python -m pip --version
make dev
mypy --version
dbt --version
pip install --upgrade pip
pip install tox
pip --version
tox --version
- name: Run pre-commit hooks
run: pre-commit run --all-files --show-diff-on-failure
- name: Run tox
run: tox
unit:
name: unit test / python ${{ matrix.python-version }}
runs-on: ubuntu-latest
timeout-minutes: 10
strategy:
fail-fast: false
matrix:
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
python-version: [3.6, 3.7, 3.8] # TODO: support unit testing for python 3.9 (https://github.com/dbt-labs/dbt/issues/3689)
env:
TOXENV: "unit"
PYTEST_ADDOPTS: "-v --color=yes --csv unit_results.csv"
steps:
- name: Check out the repository
uses: actions/checkout@v4
uses: actions/checkout@v2
with:
persist-credentials: false
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install python dependencies
run: |
python -m pip install --user --upgrade pip
python -m pip --version
python -m pip install tox
pip install --upgrade pip
pip install tox
pip --version
tox --version
- name: Run unit tests
uses: nick-fields/retry@v3
with:
timeout_minutes: 10
max_attempts: 3
command: tox -e unit
- name: Run tox
run: tox
- name: Get current date
if: always()
id: date
run: |
CURRENT_DATE=$(date +'%Y-%m-%dT%H_%M_%S') # no colons allowed for artifacts
echo "date=$CURRENT_DATE" >> $GITHUB_OUTPUT
run: echo "::set-output name=date::$(date +'%Y-%m-%dT%H_%M_%S')" #no colons allowed for artifacts
- name: Upload Unit Test Coverage to Codecov
if: ${{ matrix.python-version == '3.11' }}
uses: codecov/codecov-action@v4
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: unit
integration-metadata:
name: integration test metadata generation
runs-on: ubuntu-latest
outputs:
split-groups: ${{ steps.generate-split-groups.outputs.split-groups }}
include: ${{ steps.generate-include.outputs.include }}
steps:
- name: generate split-groups
id: generate-split-groups
run: |
MATRIX_JSON="["
for B in $(seq 1 ${{ env.PYTHON_INTEGRATION_TEST_WORKERS }}); do
MATRIX_JSON+=$(sed 's/^/"/;s/$/"/' <<< "${B}")
done
MATRIX_JSON="${MATRIX_JSON//\"\"/\", \"}"
MATRIX_JSON+="]"
echo "split-groups=${MATRIX_JSON}"
echo "split-groups=${MATRIX_JSON}" >> $GITHUB_OUTPUT
- name: generate include
id: generate-include
run: |
INCLUDE=('"python-version":"3.9","os":"windows-latest"' '"python-version":"3.9","os":"macos-12"' )
INCLUDE_GROUPS="["
for include in ${INCLUDE[@]}; do
for group in $(seq 1 ${{ env.PYTHON_INTEGRATION_TEST_WORKERS }}); do
INCLUDE_GROUPS+=$(sed 's/$/, /' <<< "{\"split-group\":\"${group}\",${include}}")
done
done
INCLUDE_GROUPS=$(echo $INCLUDE_GROUPS | sed 's/,*$//g')
INCLUDE_GROUPS+="]"
echo "include=${INCLUDE_GROUPS}"
echo "include=${INCLUDE_GROUPS}" >> $GITHUB_OUTPUT
integration:
name: (${{ matrix.split-group }}) integration test / python ${{ matrix.python-version }} / ${{ matrix.os }}
runs-on: ${{ matrix.os }}
timeout-minutes: 30
needs:
- integration-metadata
strategy:
fail-fast: false
matrix:
python-version: [ "3.9", "3.10", "3.11", "3.12" ]
os: [ubuntu-20.04]
split-group: ${{ fromJson(needs.integration-metadata.outputs.split-groups) }}
include: ${{ fromJson(needs.integration-metadata.outputs.include) }}
env:
TOXENV: integration
DBT_INVOCATION_ENV: github-actions
DBT_TEST_USER_1: dbt_test_user_1
DBT_TEST_USER_2: dbt_test_user_2
DBT_TEST_USER_3: dbt_test_user_3
DD_CIVISIBILITY_AGENTLESS_ENABLED: true
DD_API_KEY: ${{ secrets.DATADOG_API_KEY }}
DD_SITE: datadoghq.com
DD_ENV: ci
DD_SERVICE: ${{ github.event.repository.name }}
steps:
- name: Check out the repository
uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Set up postgres (linux)
if: runner.os == 'Linux'
uses: ./.github/actions/setup-postgres-linux
- name: Set up postgres (macos)
if: runner.os == 'macOS'
uses: ./.github/actions/setup-postgres-macos
- name: Set up postgres (windows)
if: runner.os == 'Windows'
uses: ./.github/actions/setup-postgres-windows
- name: Install python tools
run: |
python -m pip install --user --upgrade pip
python -m pip --version
python -m pip install tox
tox --version
- name: Run integration tests
uses: nick-fields/retry@v3
with:
timeout_minutes: 30
max_attempts: 3
command: tox -- --ddtrace
env:
PYTEST_ADDOPTS: ${{ format('--splits {0} --group {1}', env.PYTHON_INTEGRATION_TEST_WORKERS, matrix.split-group) }}
- name: Get current date
if: always()
id: date
run: |
CURRENT_DATE=$(date +'%Y-%m-%dT%H_%M_%S') # no colons allowed for artifacts
echo "date=$CURRENT_DATE" >> $GITHUB_OUTPUT
- uses: actions/upload-artifact@v4
- uses: actions/upload-artifact@v2
if: always()
with:
name: logs_${{ matrix.python-version }}_${{ matrix.os }}_${{ matrix.split-group }}_${{ steps.date.outputs.date }}
path: ./logs
- name: Upload Integration Test Coverage to Codecov
if: ${{ matrix.python-version == '3.11' }}
uses: codecov/codecov-action@v4
with:
token: ${{ secrets.CODECOV_TOKEN }}
flags: integration
integration-report:
if: ${{ always() }}
name: Integration Test Suite
runs-on: ubuntu-latest
needs: integration
steps:
- name: "Integration Tests Failed"
if: ${{ contains(needs.integration.result, 'failure') || contains(needs.integration.result, 'cancelled') }}
# when this is true the next step won't execute
run: |
echo "::notice title='Integration test suite failed'"
exit 1
- name: "Integration Tests Passed"
run: |
echo "::notice title='Integration test suite passed'"
name: unit_results_${{ matrix.python-version }}-${{ steps.date.outputs.date }}.csv
path: unit_results.csv
build:
name: build packages
@@ -258,18 +122,20 @@ jobs:
steps:
- name: Check out the repository
uses: actions/checkout@v4
uses: actions/checkout@v2
with:
persist-credentials: false
- name: Set up Python
uses: actions/setup-python@v5
uses: actions/setup-python@v2
with:
python-version: '3.9'
python-version: 3.8
- name: Install python dependencies
run: |
python -m pip install --user --upgrade pip
python -m pip install --upgrade setuptools wheel twine check-wheel-contents
python -m pip --version
pip install --upgrade pip
pip install --upgrade setuptools wheel twine check-wheel-contents
pip --version
- name: Build distributions
run: ./scripts/build-dist.sh
@@ -285,18 +151,55 @@ jobs:
run: |
check-wheel-contents dist/*.whl --ignore W007,W008
- uses: actions/upload-artifact@v2
with:
name: dist
path: dist/
test-build:
name: verify packages / python ${{ matrix.python-version }} / ${{ matrix.os }}
needs: build
runs-on: ${{ matrix.os }}
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, macos-latest, windows-latest]
python-version: [3.6, 3.7, 3.8, 3.9]
steps:
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- name: Install python dependencies
run: |
pip install --upgrade pip
pip install --upgrade wheel
pip --version
- uses: actions/download-artifact@v2
with:
name: dist
path: dist/
- name: Show distributions
run: ls -lh dist/
- name: Install wheel distributions
run: |
find ./dist/*.whl -maxdepth 1 -type f | xargs python -m pip install --force-reinstall --find-links=dist/
find ./dist/*.whl -maxdepth 1 -type f | xargs pip install --force-reinstall --find-links=dist/
- name: Check wheel distributions
run: |
dbt --version
- name: Install source distributions
# ignore dbt-1.0.0, which intentionally raises an error when installed from source
run: |
find ./dist/*.gz -maxdepth 1 -type f | xargs python -m pip install --force-reinstall --find-links=dist/
find ./dist/*.gz -maxdepth 1 -type f | xargs pip install --force-reinstall --find-links=dist/
- name: Check source distributions
run: |

View File

@@ -1,265 +0,0 @@
# **what?**
# This workflow models the performance characteristics of a point in time in dbt.
# It runs specific dbt commands on committed projects multiple times to create and
# commit information about the distribution to the current branch. For more information
# see the readme in the performance module at /performance/README.md.
#
# **why?**
# When developing new features, we can take quick performance samples and compare
# them against the commited baseline measurements produced by this workflow to detect
# some performance regressions at development time before they reach users.
#
# **when?**
# This is only run once directly after each release (for non-prereleases). If for some
# reason the results of a run are not satisfactory, it can also be triggered manually.
name: Model Performance Characteristics
on:
# runs after non-prereleases are published.
release:
types: [released]
# run manually from the actions tab
workflow_dispatch:
inputs:
release_id:
description: 'dbt version to model (must be non-prerelease in Pypi)'
type: string
required: true
env:
RUNNER_CACHE_PATH: performance/runner/target/release/runner
# both jobs need to write
permissions:
contents: write
pull-requests: write
jobs:
set-variables:
name: Setting Variables
runs-on: ubuntu-latest
outputs:
cache_key: ${{ steps.variables.outputs.cache_key }}
release_id: ${{ steps.semver.outputs.base-version }}
release_branch: ${{ steps.variables.outputs.release_branch }}
steps:
# explicitly checkout the performance runner from main regardless of which
# version we are modeling.
- name: Checkout
uses: actions/checkout@v4
with:
ref: main
- name: Parse version into parts
id: semver
uses: dbt-labs/actions/parse-semver@v1
with:
version: ${{ github.event.inputs.release_id || github.event.release.tag_name }}
# collect all the variables that need to be used in subsequent jobs
- name: Set variables
id: variables
run: |
# create a cache key that will be used in the next job. without this the
# next job would have to checkout from main and hash the files itself.
echo "cache_key=${{ runner.os }}-${{ hashFiles('performance/runner/Cargo.toml')}}-${{ hashFiles('performance/runner/src/*') }}" >> $GITHUB_OUTPUT
branch_name="${{steps.semver.outputs.major}}.${{steps.semver.outputs.minor}}.latest"
echo "release_branch=$branch_name" >> $GITHUB_OUTPUT
echo "release branch is inferred to be ${branch_name}"
latest-runner:
name: Build or Fetch Runner
runs-on: ubuntu-latest
needs: [set-variables]
env:
RUSTFLAGS: "-D warnings"
steps:
- name: '[DEBUG] print variables'
run: |
echo "all variables defined in set-variables"
echo "cache_key: ${{ needs.set-variables.outputs.cache_key }}"
echo "release_id: ${{ needs.set-variables.outputs.release_id }}"
echo "release_branch: ${{ needs.set-variables.outputs.release_branch }}"
# explicitly checkout the performance runner from main regardless of which
# version we are modeling.
- name: Checkout
uses: actions/checkout@v4
with:
ref: main
# attempts to access a previously cached runner
- uses: actions/cache@v4
id: cache
with:
path: ${{ env.RUNNER_CACHE_PATH }}
key: ${{ needs.set-variables.outputs.cache_key }}
- name: Fetch Rust Toolchain
if: steps.cache.outputs.cache-hit != 'true'
uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- name: Add fmt
if: steps.cache.outputs.cache-hit != 'true'
run: rustup component add rustfmt
- name: Cargo fmt
if: steps.cache.outputs.cache-hit != 'true'
uses: actions-rs/cargo@v1
with:
command: fmt
args: --manifest-path performance/runner/Cargo.toml --all -- --check
- name: Test
if: steps.cache.outputs.cache-hit != 'true'
uses: actions-rs/cargo@v1
with:
command: test
args: --manifest-path performance/runner/Cargo.toml
- name: Build (optimized)
if: steps.cache.outputs.cache-hit != 'true'
uses: actions-rs/cargo@v1
with:
command: build
args: --release --manifest-path performance/runner/Cargo.toml
# the cache action automatically caches this binary at the end of the job
model:
# depends on `latest-runner` as a separate job so that failures in this job do not prevent
# a successfully tested and built binary from being cached.
needs: [set-variables, latest-runner]
name: Model a release
runs-on: ubuntu-latest
steps:
- name: '[DEBUG] print variables'
run: |
echo "all variables defined in set-variables"
echo "cache_key: ${{ needs.set-variables.outputs.cache_key }}"
echo "release_id: ${{ needs.set-variables.outputs.release_id }}"
echo "release_branch: ${{ needs.set-variables.outputs.release_branch }}"
- name: Setup Python
uses: actions/setup-python@v5
with:
python-version: "3.9"
- name: Install dbt
run: pip install dbt-postgres==${{ needs.set-variables.outputs.release_id }}
- name: Install Hyperfine
run: wget https://github.com/sharkdp/hyperfine/releases/download/v1.11.0/hyperfine_1.11.0_amd64.deb && sudo dpkg -i hyperfine_1.11.0_amd64.deb
# explicitly checkout main to get the latest project definitions
- name: Checkout
uses: actions/checkout@v4
with:
ref: main
# this was built in the previous job so it will be there.
- name: Fetch Runner
uses: actions/cache@v4
id: cache
with:
path: ${{ env.RUNNER_CACHE_PATH }}
key: ${{ needs.set-variables.outputs.cache_key }}
- name: Move Runner
run: mv performance/runner/target/release/runner performance/app
- name: Change Runner Permissions
run: chmod +x ./performance/app
- name: '[DEBUG] ls baseline directory before run'
run: ls -R performance/baselines/
# `${{ github.workspace }}` is used to pass the absolute path
- name: Create directories
run: |
mkdir ${{ github.workspace }}/performance/tmp/
mkdir -p performance/baselines/${{ needs.set-variables.outputs.release_id }}/
# Run modeling with taking 20 samples
- name: Run Measurement
run: |
performance/app model -v ${{ needs.set-variables.outputs.release_id }} -b ${{ github.workspace }}/performance/baselines/ -p ${{ github.workspace }}/performance/projects/ -t ${{ github.workspace }}/performance/tmp/ -n 20
- name: '[DEBUG] ls baseline directory after run'
run: ls -R performance/baselines/
- uses: actions/upload-artifact@v4
with:
name: baseline
path: performance/baselines/${{ needs.set-variables.outputs.release_id }}/
create-pr:
name: Open PR for ${{ matrix.base-branch }}
# depends on `model` as a separate job so that the baseline can be committed to more than one branch
# i.e. release branch and main
needs: [set-variables, latest-runner, model]
runs-on: ubuntu-latest
strategy:
matrix:
include:
- base-branch: refs/heads/main
target-branch: performance-bot/main_${{ needs.set-variables.outputs.release_id }}_${{GITHUB.RUN_ID}}
- base-branch: refs/heads/${{ needs.set-variables.outputs.release_branch }}
target-branch: performance-bot/release_${{ needs.set-variables.outputs.release_id }}_${{GITHUB.RUN_ID}}
steps:
- name: '[DEBUG] print variables'
run: |
echo "all variables defined in set-variables"
echo "cache_key: ${{ needs.set-variables.outputs.cache_key }}"
echo "release_id: ${{ needs.set-variables.outputs.release_id }}"
echo "release_branch: ${{ needs.set-variables.outputs.release_branch }}"
- name: Checkout
uses: actions/checkout@v4
with:
ref: ${{ matrix.base-branch }}
- name: Create PR branch
run: |
git checkout -b ${{ matrix.target-branch }}
git push origin ${{ matrix.target-branch }}
git branch --set-upstream-to=origin/${{ matrix.target-branch }} ${{ matrix.target-branch }}
- uses: actions/download-artifact@v4
with:
name: baseline
path: performance/baselines/${{ needs.set-variables.outputs.release_id }}
- name: '[DEBUG] ls baselines after artifact download'
run: ls -R performance/baselines/
- name: Commit baseline
uses: EndBug/add-and-commit@v9
with:
add: 'performance/baselines/*'
author_name: 'Github Build Bot'
author_email: 'buildbot@fishtownanalytics.com'
message: 'adding performance baseline for ${{ needs.set-variables.outputs.release_id }}'
push: 'origin origin/${{ matrix.target-branch }}'
- name: Create Pull Request
uses: peter-evans/create-pull-request@v5
with:
author: 'Github Build Bot <buildbot@fishtownanalytics.com>'
base: ${{ matrix.base-branch }}
branch: '${{ matrix.target-branch }}'
title: 'Adding performance modeling for ${{needs.set-variables.outputs.release_id}} to ${{ matrix.base-branch }}'
body: 'Committing perf results for tracking for the ${{needs.set-variables.outputs.release_id}}'
labels: |
Skip Changelog
Performance

View File

@@ -1,109 +0,0 @@
# **what?**
# Nightly releases to GitHub and PyPI. This workflow produces the following outcome:
# - generate and validate data for night release (commit SHA, version number, release branch);
# - pass data to release workflow;
# - night release will be pushed to GitHub as a draft release;
# - night build will be pushed to test PyPI;
#
# **why?**
# Ensure an automated and tested release process for nightly builds
#
# **when?**
# This workflow runs on schedule or can be run manually on demand.
name: Nightly Test Release to GitHub and PyPI
on:
workflow_dispatch: # for manual triggering
schedule:
- cron: 0 9 * * *
permissions:
contents: write # this is the permission that allows creating a new release
defaults:
run:
shell: bash
env:
RELEASE_BRANCH: "main"
jobs:
aggregate-release-data:
runs-on: ubuntu-latest
outputs:
commit_sha: ${{ steps.resolve-commit-sha.outputs.release_commit }}
version_number: ${{ steps.nightly-release-version.outputs.number }}
release_branch: ${{ steps.release-branch.outputs.name }}
steps:
- name: "Checkout ${{ github.repository }} Branch ${{ env.RELEASE_BRANCH }}"
uses: actions/checkout@v4
with:
ref: ${{ env.RELEASE_BRANCH }}
- name: "Resolve Commit To Release"
id: resolve-commit-sha
run: |
commit_sha=$(git rev-parse HEAD)
echo "release_commit=$commit_sha" >> $GITHUB_OUTPUT
- name: "Get Current Version Number"
id: version-number-sources
run: |
current_version=`awk -F"current_version = " '{print $2}' .bumpversion.cfg | tr '\n' ' '`
echo "current_version=$current_version" >> $GITHUB_OUTPUT
- name: "Audit Version And Parse Into Parts"
id: semver
uses: dbt-labs/actions/parse-semver@v1.1.0
with:
version: ${{ steps.version-number-sources.outputs.current_version }}
- name: "Get Current Date"
id: current-date
run: echo "date=$(date +'%m%d%Y')" >> $GITHUB_OUTPUT
- name: "Generate Nightly Release Version Number"
id: nightly-release-version
run: |
number="${{ steps.semver.outputs.version }}.dev${{ steps.current-date.outputs.date }}"
echo "number=$number" >> $GITHUB_OUTPUT
- name: "Audit Nightly Release Version And Parse Into Parts"
uses: dbt-labs/actions/parse-semver@v1.1.0
with:
version: ${{ steps.nightly-release-version.outputs.number }}
- name: "Set Release Branch"
id: release-branch
run: |
echo "name=${{ env.RELEASE_BRANCH }}" >> $GITHUB_OUTPUT
log-outputs-aggregate-release-data:
runs-on: ubuntu-latest
needs: [aggregate-release-data]
steps:
- name: "[DEBUG] Log Outputs"
run: |
echo commit_sha : ${{ needs.aggregate-release-data.outputs.commit_sha }}
echo version_number: ${{ needs.aggregate-release-data.outputs.version_number }}
echo release_branch: ${{ needs.aggregate-release-data.outputs.release_branch }}
release-github-pypi:
needs: [aggregate-release-data]
uses: ./.github/workflows/release.yml
with:
sha: ${{ needs.aggregate-release-data.outputs.commit_sha }}
target_branch: ${{ needs.aggregate-release-data.outputs.release_branch }}
version_number: ${{ needs.aggregate-release-data.outputs.version_number }}
build_script_path: "scripts/build-dist.sh"
env_setup_script_path: "scripts/env-setup.sh"
s3_bucket_name: "core-team-artifacts"
package_test_command: "dbt --version"
test_run: true
nightly_release: true
secrets: inherit

176
.github/workflows/performance.yml vendored Normal file
View File

@@ -0,0 +1,176 @@
name: Performance Regression Tests
# Schedule triggers
on:
# runs twice a day at 10:05am and 10:05pm
schedule:
- cron: "5 10,22 * * *"
# Allows you to run this workflow manually from the Actions tab
workflow_dispatch:
jobs:
# checks fmt of runner code
# purposefully not a dependency of any other job
# will block merging, but not prevent developing
fmt:
name: Cargo fmt
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v2
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- run: rustup component add rustfmt
- uses: actions-rs/cargo@v1
with:
command: fmt
args: --manifest-path performance/runner/Cargo.toml --all -- --check
# runs any tests associated with the runner
# these tests make sure the runner logic is correct
test-runner:
name: Test Runner
runs-on: ubuntu-latest
env:
# turns errors into warnings
RUSTFLAGS: "-D warnings"
steps:
- uses: actions/checkout@v2
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- uses: actions-rs/cargo@v1
with:
command: test
args: --manifest-path performance/runner/Cargo.toml
# build an optimized binary to be used as the runner in later steps
build-runner:
needs: [test-runner]
name: Build Runner
runs-on: ubuntu-latest
env:
RUSTFLAGS: "-D warnings"
steps:
- uses: actions/checkout@v2
- uses: actions-rs/toolchain@v1
with:
profile: minimal
toolchain: stable
override: true
- uses: actions-rs/cargo@v1
with:
command: build
args: --release --manifest-path performance/runner/Cargo.toml
- uses: actions/upload-artifact@v2
with:
name: runner
path: performance/runner/target/release/runner
# run the performance measurements on the current or default branch
measure-dev:
needs: [build-runner]
name: Measure Dev Branch
runs-on: ubuntu-latest
steps:
- name: checkout dev
uses: actions/checkout@v2
- name: Setup Python
uses: actions/setup-python@v2.2.2
with:
python-version: "3.8"
- name: install dbt
run: pip install -r dev-requirements.txt -r editable-requirements.txt
- name: install hyperfine
run: wget https://github.com/sharkdp/hyperfine/releases/download/v1.11.0/hyperfine_1.11.0_amd64.deb && sudo dpkg -i hyperfine_1.11.0_amd64.deb
- uses: actions/download-artifact@v2
with:
name: runner
- name: change permissions
run: chmod +x ./runner
- name: run
run: ./runner measure -b dev -p ${{ github.workspace }}/performance/projects/
- uses: actions/upload-artifact@v2
with:
name: dev-results
path: performance/results/
# run the performance measurements on the release branch which we use
# as a performance baseline. This part takes by far the longest, so
# we do everything we can first so the job fails fast.
# -----
# we need to checkout dbt twice in this job: once for the baseline dbt
# version, and once to get the latest regression testing projects,
# metrics, and runner code from the develop or current branch so that
# the calculations match for both versions of dbt we are comparing.
measure-baseline:
needs: [build-runner]
name: Measure Baseline Branch
runs-on: ubuntu-latest
steps:
- name: checkout latest
uses: actions/checkout@v2
with:
ref: "0.20.latest"
- name: Setup Python
uses: actions/setup-python@v2.2.2
with:
python-version: "3.8"
- name: move repo up a level
run: mkdir ${{ github.workspace }}/../baseline/ && cp -r ${{ github.workspace }} ${{ github.workspace }}/../baseline
- name: "[debug] ls new dbt location"
run: ls ${{ github.workspace }}/../baseline/dbt/
# installation creates egg-links so we have to preserve source
- name: install dbt from new location
run: cd ${{ github.workspace }}/../baseline/dbt/ && pip install -r dev-requirements.txt -r editable-requirements.txt
# checkout the current branch to get all the target projects
# this deletes the old checked out code which is why we had to copy before
- name: checkout dev
uses: actions/checkout@v2
- name: install hyperfine
run: wget https://github.com/sharkdp/hyperfine/releases/download/v1.11.0/hyperfine_1.11.0_amd64.deb && sudo dpkg -i hyperfine_1.11.0_amd64.deb
- uses: actions/download-artifact@v2
with:
name: runner
- name: change permissions
run: chmod +x ./runner
- name: run runner
run: ./runner measure -b baseline -p ${{ github.workspace }}/performance/projects/
- uses: actions/upload-artifact@v2
with:
name: baseline-results
path: performance/results/
# detect regressions on the output generated from measuring
# the two branches. Exits with non-zero code if a regression is detected.
calculate-regressions:
needs: [measure-dev, measure-baseline]
name: Compare Results
runs-on: ubuntu-latest
steps:
- uses: actions/download-artifact@v2
with:
name: dev-results
- uses: actions/download-artifact@v2
with:
name: baseline-results
- name: "[debug] ls result files"
run: ls
- uses: actions/download-artifact@v2
with:
name: runner
- name: change permissions
run: chmod +x ./runner
- name: make results directory
run: mkdir ./final-output/
- name: run calculation
run: ./runner calculate -r ./ -o ./final-output/
# always attempt to upload the results even if there were regressions found
- uses: actions/upload-artifact@v2
if: ${{ always() }}
with:
name: final-calculations
path: ./final-output/*

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@@ -1,31 +0,0 @@
# **what?**
# The purpose of this workflow is to trigger CI to run for each
# release branch and main branch on a regular cadence. If the CI workflow
# fails for a branch, it will post to #dev-core-alerts to raise awareness.
# **why?**
# Ensures release branches and main are always shippable and not broken.
# Also, can catch any dependencies shifting beneath us that might
# introduce breaking changes (could also impact Cloud).
# **when?**
# Mainly on a schedule of 9:00, 13:00, 18:00 UTC everyday.
# Manual trigger can also test on demand
name: Release branch scheduled testing
on:
schedule:
- cron: '0 9,13,18 * * *' # 9:00, 13:00, 18:00 UTC
workflow_dispatch: # for manual triggering
# no special access is needed
permissions: read-all
jobs:
run_tests:
uses: dbt-labs/actions/.github/workflows/release-branch-tests.yml@main
with:
workflows_to_run: '["main.yml"]'
secrets: inherit

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@@ -1,118 +0,0 @@
# **what?**
# This workflow will generate a series of docker images for dbt and push them to the github container registry
# **why?**
# Docker images for dbt are used in a number of important places throughout the dbt ecosystem. This is how we keep those images up-to-date.
# **when?**
# This is triggered manually
# **next steps**
# - build this into the release workflow (or conversly, break out the different release methods into their own workflow files)
name: Docker release
permissions:
packages: write
on:
workflow_dispatch:
inputs:
package:
description: The package to release. _One_ of [dbt-core, dbt-redshift, dbt-bigquery, dbt-snowflake, dbt-spark, dbt-postgres]
required: true
version_number:
description: The release version number (i.e. 1.0.0b1). Do not include `latest` tags or a leading `v`!
required: true
jobs:
get_version_meta:
name: Get version meta
runs-on: ubuntu-latest
outputs:
major: ${{ steps.version.outputs.major }}
minor: ${{ steps.version.outputs.minor }}
patch: ${{ steps.version.outputs.patch }}
latest: ${{ steps.latest.outputs.latest }}
minor_latest: ${{ steps.latest.outputs.minor_latest }}
steps:
- uses: actions/checkout@v4
- name: Split version
id: version
run: |
IFS="." read -r MAJOR MINOR PATCH <<< ${{ github.event.inputs.version_number }}
echo "major=$MAJOR" >> $GITHUB_OUTPUT
echo "minor=$MINOR" >> $GITHUB_OUTPUT
echo "patch=$PATCH" >> $GITHUB_OUTPUT
- name: Is pkg 'latest'
id: latest
uses: ./.github/actions/latest-wrangler
with:
package: ${{ github.event.inputs.package }}
new_version: ${{ github.event.inputs.version_number }}
gh_token: ${{ secrets.GITHUB_TOKEN }}
halt_on_missing: False
setup_image_builder:
name: Set up docker image builder
runs-on: ubuntu-latest
needs: [get_version_meta]
steps:
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
build_and_push:
name: Build images and push to GHCR
runs-on: ubuntu-latest
needs: [setup_image_builder, get_version_meta]
steps:
- name: Get docker build arg
id: build_arg
run: |
BUILD_ARG_NAME=$(echo ${{ github.event.inputs.package }} | sed 's/\-/_/g')
BUILD_ARG_VALUE=$(echo ${{ github.event.inputs.package }} | sed 's/postgres/core/g')
echo "build_arg_name=$BUILD_ARG_NAME" >> $GITHUB_OUTPUT
echo "build_arg_value=$BUILD_ARG_VALUE" >> $GITHUB_OUTPUT
- name: Log in to the GHCR
uses: docker/login-action@v2
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Build and push MAJOR.MINOR.PATCH tag
uses: docker/build-push-action@v5
with:
file: docker/Dockerfile
push: True
target: ${{ github.event.inputs.package }}
build-args: |
${{ steps.build_arg.outputs.build_arg_name }}_ref=${{ steps.build_arg.outputs.build_arg_value }}@v${{ github.event.inputs.version_number }}
tags: |
ghcr.io/dbt-labs/${{ github.event.inputs.package }}:${{ github.event.inputs.version_number }}
- name: Build and push MINOR.latest tag
uses: docker/build-push-action@v5
if: ${{ needs.get_version_meta.outputs.minor_latest == 'True' }}
with:
file: docker/Dockerfile
push: True
target: ${{ github.event.inputs.package }}
build-args: |
${{ steps.build_arg.outputs.build_arg_name }}_ref=${{ steps.build_arg.outputs.build_arg_value }}@v${{ github.event.inputs.version_number }}
tags: |
ghcr.io/dbt-labs/${{ github.event.inputs.package }}:${{ needs.get_version_meta.outputs.major }}.${{ needs.get_version_meta.outputs.minor }}.latest
- name: Build and push latest tag
uses: docker/build-push-action@v5
if: ${{ needs.get_version_meta.outputs.latest == 'True' }}
with:
file: docker/Dockerfile
push: True
target: ${{ github.event.inputs.package }}
build-args: |
${{ steps.build_arg.outputs.build_arg_name }}_ref=${{ steps.build_arg.outputs.build_arg_value }}@v${{ github.event.inputs.version_number }}
tags: |
ghcr.io/dbt-labs/${{ github.event.inputs.package }}:latest

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@@ -1,229 +0,0 @@
# **what?**
# Release workflow provides the following steps:
# - checkout the given commit;
# - validate version in sources and changelog file for given version;
# - bump the version and generate a changelog if needed;
# - merge all changes to the target branch if needed;
# - run unit and integration tests against given commit;
# - build and package that SHA;
# - release it to GitHub and PyPI with that specific build;
#
# **why?**
# Ensure an automated and tested release process
#
# **when?**
# This workflow can be run manually on demand or can be called by other workflows
name: Release to GitHub and PyPI
on:
workflow_dispatch:
inputs:
sha:
description: "The last commit sha in the release"
type: string
required: true
target_branch:
description: "The branch to release from"
type: string
required: true
version_number:
description: "The release version number (i.e. 1.0.0b1)"
type: string
required: true
build_script_path:
description: "Build script path"
type: string
default: "scripts/build-dist.sh"
required: true
env_setup_script_path:
description: "Environment setup script path"
type: string
default: "scripts/env-setup.sh"
required: false
s3_bucket_name:
description: "AWS S3 bucket name"
type: string
default: "core-team-artifacts"
required: true
package_test_command:
description: "Package test command"
type: string
default: "dbt --version"
required: true
test_run:
description: "Test run (Publish release as draft)"
type: boolean
default: true
required: false
nightly_release:
description: "Nightly release to dev environment"
type: boolean
default: false
required: false
workflow_call:
inputs:
sha:
description: "The last commit sha in the release"
type: string
required: true
target_branch:
description: "The branch to release from"
type: string
required: true
version_number:
description: "The release version number (i.e. 1.0.0b1)"
type: string
required: true
build_script_path:
description: "Build script path"
type: string
default: "scripts/build-dist.sh"
required: true
env_setup_script_path:
description: "Environment setup script path"
type: string
default: "scripts/env-setup.sh"
required: false
s3_bucket_name:
description: "AWS S3 bucket name"
type: string
default: "core-team-artifacts"
required: true
package_test_command:
description: "Package test command"
type: string
default: "dbt --version"
required: true
test_run:
description: "Test run (Publish release as draft)"
type: boolean
default: true
required: false
nightly_release:
description: "Nightly release to dev environment"
type: boolean
default: false
required: false
permissions:
contents: write # this is the permission that allows creating a new release
defaults:
run:
shell: bash
jobs:
log-inputs:
name: Log Inputs
runs-on: ubuntu-latest
steps:
- name: "[DEBUG] Print Variables"
run: |
echo The last commit sha in the release: ${{ inputs.sha }}
echo The branch to release from: ${{ inputs.target_branch }}
echo The release version number: ${{ inputs.version_number }}
echo Build script path: ${{ inputs.build_script_path }}
echo Environment setup script path: ${{ inputs.env_setup_script_path }}
echo AWS S3 bucket name: ${{ inputs.s3_bucket_name }}
echo Package test command: ${{ inputs.package_test_command }}
echo Test run: ${{ inputs.test_run }}
echo Nightly release: ${{ inputs.nightly_release }}
bump-version-generate-changelog:
name: Bump package version, Generate changelog
uses: dbt-labs/dbt-release/.github/workflows/release-prep.yml@main
with:
sha: ${{ inputs.sha }}
version_number: ${{ inputs.version_number }}
target_branch: ${{ inputs.target_branch }}
env_setup_script_path: ${{ inputs.env_setup_script_path }}
test_run: ${{ inputs.test_run }}
nightly_release: ${{ inputs.nightly_release }}
secrets: inherit
log-outputs-bump-version-generate-changelog:
name: "[Log output] Bump package version, Generate changelog"
if: ${{ !failure() && !cancelled() }}
needs: [bump-version-generate-changelog]
runs-on: ubuntu-latest
steps:
- name: Print variables
run: |
echo Final SHA : ${{ needs.bump-version-generate-changelog.outputs.final_sha }}
echo Changelog path: ${{ needs.bump-version-generate-changelog.outputs.changelog_path }}
build-test-package:
name: Build, Test, Package
if: ${{ !failure() && !cancelled() }}
needs: [bump-version-generate-changelog]
uses: dbt-labs/dbt-release/.github/workflows/build.yml@main
with:
sha: ${{ needs.bump-version-generate-changelog.outputs.final_sha }}
version_number: ${{ inputs.version_number }}
changelog_path: ${{ needs.bump-version-generate-changelog.outputs.changelog_path }}
build_script_path: ${{ inputs.build_script_path }}
s3_bucket_name: ${{ inputs.s3_bucket_name }}
package_test_command: ${{ inputs.package_test_command }}
test_run: ${{ inputs.test_run }}
nightly_release: ${{ inputs.nightly_release }}
secrets:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
github-release:
name: GitHub Release
if: ${{ !failure() && !cancelled() }}
needs: [bump-version-generate-changelog, build-test-package]
uses: dbt-labs/dbt-release/.github/workflows/github-release.yml@main
with:
sha: ${{ needs.bump-version-generate-changelog.outputs.final_sha }}
version_number: ${{ inputs.version_number }}
changelog_path: ${{ needs.bump-version-generate-changelog.outputs.changelog_path }}
test_run: ${{ inputs.test_run }}
pypi-release:
name: PyPI Release
needs: [github-release]
uses: dbt-labs/dbt-release/.github/workflows/pypi-release.yml@main
with:
version_number: ${{ inputs.version_number }}
test_run: ${{ inputs.test_run }}
secrets:
PYPI_API_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
TEST_PYPI_API_TOKEN: ${{ secrets.TEST_PYPI_API_TOKEN }}
slack-notification:
name: Slack Notification
if: ${{ failure() && (!inputs.test_run || inputs.nightly_release) }}
needs:
[
bump-version-generate-changelog,
build-test-package,
github-release,
pypi-release,
]
uses: dbt-labs/dbt-release/.github/workflows/slack-post-notification.yml@main
with:
status: "failure"
secrets:
SLACK_WEBHOOK_URL: ${{ secrets.SLACK_DEV_CORE_ALERTS }}

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@@ -1,30 +0,0 @@
# **what?**
# Cleanup branches left over from automation and testing. Also cleanup
# draft releases from release testing.
# **why?**
# The automations are leaving behind branches and releases that clutter
# the repository. Sometimes we need them to debug processes so we don't
# want them immediately deleted. Running on Saturday to avoid running
# at the same time as an actual release to prevent breaking a release
# mid-release.
# **when?**
# Mainly on a schedule of 12:00 Saturday.
# Manual trigger can also run on demand
name: Repository Cleanup
on:
schedule:
- cron: '0 12 * * SAT' # At 12:00 on Saturday - details in `why` above
workflow_dispatch: # for manual triggering
permissions:
contents: write
jobs:
cleanup-repo:
uses: dbt-labs/actions/.github/workflows/repository-cleanup.yml@main
secrets: inherit

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@@ -1,76 +0,0 @@
# **what?**
# Compares the schema of the dbt version of the given ref vs
# the latest official schema releases found in schemas.getdbt.com.
# If there are differences, the workflow will fail and upload the
# diff as an artifact. The metadata team should be alerted to the change.
#
# **why?**
# Reaction work may need to be done if artifact schema changes
# occur so we want to proactively alert to it.
#
# **when?**
# On pushes to `develop` and release branches. Manual runs are also enabled.
name: Artifact Schema Check
on:
workflow_dispatch:
pull_request: #TODO: remove before merging
push:
branches:
- "develop"
- "*.latest"
- "releases/*"
# no special access is needed
permissions: read-all
env:
LATEST_SCHEMA_PATH: ${{ github.workspace }}/new_schemas
SCHEMA_DIFF_ARTIFACT: ${{ github.workspace }}//schema_schanges.txt
DBT_REPO_DIRECTORY: ${{ github.workspace }}/dbt
SCHEMA_REPO_DIRECTORY: ${{ github.workspace }}/schemas.getdbt.com
jobs:
checking-schemas:
name: "Checking schemas"
runs-on: ubuntu-latest
steps:
- name: Set up Python
uses: actions/setup-python@v5
with:
python-version: 3.9
- name: Checkout dbt repo
uses: actions/checkout@v4
with:
path: ${{ env.DBT_REPO_DIRECTORY }}
- name: Checkout schemas.getdbt.com repo
uses: actions/checkout@v4
with:
repository: dbt-labs/schemas.getdbt.com
ref: 'main'
path: ${{ env.SCHEMA_REPO_DIRECTORY }}
- name: Generate current schema
run: |
cd ${{ env.DBT_REPO_DIRECTORY }}
python3 -m venv env
source env/bin/activate
pip install --upgrade pip
pip install -r dev-requirements.txt -r editable-requirements.txt
python scripts/collect-artifact-schema.py --path ${{ env.LATEST_SCHEMA_PATH }}
- name: Compare schemas
run: |
cp -r ${{ env.LATEST_SCHEMA_PATH }}/dbt ${{ env.SCHEMA_REPO_DIRECTORY }}
cd ${{ env.SCHEMA_REPO_DIRECTORY }}
git diff -I='*[0-9]{4}-[0-9]{2}-[0-9]{2}' -I='*[0-9]+\.[0-9]+\.[0-9]+' --exit-code > ${{ env.SCHEMA_DIFF_ARTIFACT }}
- name: Upload schema diff
uses: actions/upload-artifact@v4
if: ${{ failure() }}
with:
name: 'schema_schanges.txt'
path: '${{ env.SCHEMA_DIFF_ARTIFACT }}'

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@@ -1,12 +0,0 @@
name: "Close stale issues and PRs"
on:
schedule:
- cron: "30 1 * * *"
permissions:
issues: write
pull-requests: write
jobs:
stale:
uses: dbt-labs/actions/.github/workflows/stale-bot-matrix.yml@main

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@@ -1,112 +0,0 @@
# This Action checks makes a dbt run to sample json structured logs
# and checks that they conform to the currently documented schema.
#
# If this action fails it either means we have unintentionally deviated
# from our documented structured logging schema, or we need to bump the
# version of our structured logging and add new documentation to
# communicate these changes.
name: Structured Logging Schema Check
on:
push:
branches:
- "main"
- "*.latest"
- "releases/*"
pull_request:
workflow_dispatch:
permissions: read-all
# top-level adjustments can be made here
env:
# number of parallel processes to spawn for python testing
PYTHON_INTEGRATION_TEST_WORKERS: 5
jobs:
integration-metadata:
name: integration test metadata generation
runs-on: ubuntu-latest
outputs:
split-groups: ${{ steps.generate-split-groups.outputs.split-groups }}
steps:
- name: generate split-groups
id: generate-split-groups
run: |
MATRIX_JSON="["
for B in $(seq 1 ${{ env.PYTHON_INTEGRATION_TEST_WORKERS }}); do
MATRIX_JSON+=$(sed 's/^/"/;s/$/"/' <<< "${B}")
done
MATRIX_JSON="${MATRIX_JSON//\"\"/\", \"}"
MATRIX_JSON+="]"
echo "split-groups=${MATRIX_JSON}" >> $GITHUB_OUTPUT
# run the performance measurements on the current or default branch
test-schema:
name: Test Log Schema
runs-on: ubuntu-20.04
timeout-minutes: 30
needs:
- integration-metadata
strategy:
fail-fast: false
matrix:
split-group: ${{ fromJson(needs.integration-metadata.outputs.split-groups) }}
env:
# turns warnings into errors
RUSTFLAGS: "-D warnings"
# points tests to the log file
LOG_DIR: "/home/runner/work/dbt-core/dbt-core/logs"
# tells integration tests to output into json format
DBT_LOG_FORMAT: "json"
# tell eventmgr to convert logging events into bytes
DBT_TEST_BINARY_SERIALIZATION: "true"
# Additional test users
DBT_TEST_USER_1: dbt_test_user_1
DBT_TEST_USER_2: dbt_test_user_2
DBT_TEST_USER_3: dbt_test_user_3
steps:
- name: checkout dev
uses: actions/checkout@v4
with:
persist-credentials: false
- name: Setup Python
uses: actions/setup-python@v5
with:
python-version: "3.9"
- name: Install python dependencies
run: |
pip install --user --upgrade pip
pip --version
pip install tox
tox --version
- name: Set up postgres
uses: ./.github/actions/setup-postgres-linux
- name: ls
run: ls
# integration tests generate a ton of logs in different files. the next step will find them all.
# we actually care if these pass, because the normal test run doesn't usually include many json log outputs
- name: Run integration tests
uses: nick-fields/retry@v3
with:
timeout_minutes: 30
max_attempts: 3
command: tox -e integration -- -nauto
env:
PYTEST_ADDOPTS: ${{ format('--splits {0} --group {1}', env.PYTHON_INTEGRATION_TEST_WORKERS, matrix.split-group) }}
test-schema-report:
name: Log Schema Test Suite
runs-on: ubuntu-latest
needs: test-schema
steps:
- name: "[Notification] Log test suite passes"
run: |
echo "::notice title="Log test suite passes""

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@@ -1,154 +0,0 @@
# **what?**
# This workflow will test all test(s) at the input path given number of times to determine if it's flaky or not. You can test with any supported OS/Python combination.
# This is batched in 10 to allow more test iterations faster.
# **why?**
# Testing if a test is flaky and if a previously flaky test has been fixed. This allows easy testing on supported python versions and OS combinations.
# **when?**
# This is triggered manually from dbt-core.
name: Flaky Tester
on:
workflow_dispatch:
inputs:
branch:
description: 'Branch to check out'
type: string
required: true
default: 'main'
test_path:
description: 'Path to single test to run (ex: tests/functional/retry/test_retry.py::TestRetry::test_fail_fast)'
type: string
required: true
default: 'tests/functional/...'
python_version:
description: 'Version of Python to Test Against'
type: choice
options:
- '3.9'
- '3.10'
- '3.11'
os:
description: 'OS to run test in'
type: choice
options:
- 'ubuntu-latest'
- 'macos-12'
- 'windows-latest'
num_runs_per_batch:
description: 'Max number of times to run the test per batch. We always run 10 batches.'
type: number
required: true
default: '50'
permissions: read-all
defaults:
run:
shell: bash
jobs:
debug:
runs-on: ubuntu-latest
steps:
- name: "[DEBUG] Output Inputs"
run: |
echo "Branch: ${{ inputs.branch }}"
echo "test_path: ${{ inputs.test_path }}"
echo "python_version: ${{ inputs.python_version }}"
echo "os: ${{ inputs.os }}"
echo "num_runs_per_batch: ${{ inputs.num_runs_per_batch }}"
pytest:
runs-on: ${{ inputs.os }}
strategy:
# run all batches, even if one fails. This informs how flaky the test may be.
fail-fast: false
# using a matrix to speed up the jobs since the matrix will run in parallel when runners are available
matrix:
batch: ["1", "2", "3", "4", "5", "6", "7", "8", "9", "10"]
env:
PYTEST_ADDOPTS: "-v --color=yes -n4 --csv integration_results.csv"
DBT_TEST_USER_1: dbt_test_user_1
DBT_TEST_USER_2: dbt_test_user_2
DBT_TEST_USER_3: dbt_test_user_3
DD_CIVISIBILITY_AGENTLESS_ENABLED: true
DD_API_KEY: ${{ secrets.DATADOG_API_KEY }}
DD_SITE: datadoghq.com
DD_ENV: ci
DD_SERVICE: ${{ github.event.repository.name }}
steps:
- name: "Checkout code"
uses: actions/checkout@v4
with:
ref: ${{ inputs.branch }}
- name: "Setup Python"
uses: actions/setup-python@v5
with:
python-version: "${{ inputs.python_version }}"
- name: "Setup Dev Environment"
run: make dev
- name: "Set up postgres (linux)"
if: inputs.os == 'ubuntu-latest'
run: make setup-db
# mac and windows don't use make due to limitations with docker with those runners in GitHub
- name: "Set up postgres (macos)"
if: inputs.os == 'macos-12'
uses: ./.github/actions/setup-postgres-macos
- name: "Set up postgres (windows)"
if: inputs.os == 'windows-latest'
uses: ./.github/actions/setup-postgres-windows
- name: "Test Command"
id: command
run: |
test_command="python -m pytest ${{ inputs.test_path }}"
echo "test_command=$test_command" >> $GITHUB_OUTPUT
- name: "Run test ${{ inputs.num_runs_per_batch }} times"
id: pytest
run: |
set +e
for ((i=1; i<=${{ inputs.num_runs_per_batch }}; i++))
do
echo "Running pytest iteration $i..."
python -m pytest --ddtrace ${{ inputs.test_path }}
exit_code=$?
if [[ $exit_code -eq 0 ]]; then
success=$((success + 1))
echo "Iteration $i: Success"
else
failure=$((failure + 1))
echo "Iteration $i: Failure"
fi
echo
echo "==========================="
echo "Successful runs: $success"
echo "Failed runs: $failure"
echo "==========================="
echo
done
echo "failure=$failure" >> $GITHUB_OUTPUT
- name: "Success and Failure Summary: ${{ inputs.os }}/Python ${{ inputs.python_version }}"
run: |
echo "Batch: ${{ matrix.batch }}"
echo "Successful runs: ${{ steps.pytest.outputs.success }}"
echo "Failed runs: ${{ steps.pytest.outputs.failure }}"
- name: "Error for Failures"
if: ${{ steps.pytest.outputs.failure }}
run: |
echo "Batch ${{ matrix.batch }} failed ${{ steps.pytest.outputs.failure }} of ${{ inputs.num_runs_per_batch }} tests"
exit 1

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@@ -1 +0,0 @@
-P ubuntu-latest=ghcr.io/catthehacker/ubuntu:act-latest

View File

@@ -1 +0,0 @@
.secrets

View File

@@ -1 +0,0 @@
GITHUB_TOKEN=GH_PERSONAL_ACCESS_TOKEN_GOES_HERE

View File

@@ -1,6 +0,0 @@
{
"inputs": {
"version_number": "1.0.1",
"package": "dbt-postgres"
}
}

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@@ -1,31 +0,0 @@
# **what?**
# When the core team triages, we sometimes need more information from the issue creator. In
# those cases we remove the `triage` label and add the `awaiting_response` label. Once we
# recieve a response in the form of a comment, we want the `awaiting_response` label removed
# in favor of the `triage` label so we are aware that the issue needs action.
# **why?**
# To help with out team triage issue tracking
# **when?**
# This will run when a comment is added to an issue and that issue has to `awaiting_response` label.
name: Update Triage Label
on: issue_comment
defaults:
run:
shell: bash
permissions:
issues: write
jobs:
triage_label:
if: contains(github.event.issue.labels.*.name, 'awaiting_response')
uses: dbt-labs/actions/.github/workflows/swap-labels.yml@main
with:
add_label: "triage"
remove_label: "awaiting_response"
secrets: inherit

View File

@@ -1,28 +0,0 @@
# **what?**
# This workflow will take the new version number to bump to. With that
# it will run versionbump to update the version number everywhere in the
# code base and then run changie to create the corresponding changelog.
# A PR will be created with the changes that can be reviewed before committing.
# **why?**
# This is to aid in releasing dbt and making sure we have updated
# the version in all places and generated the changelog.
# **when?**
# This is triggered manually
name: Version Bump
on:
workflow_dispatch:
inputs:
version_number:
description: 'The version number to bump to (ex. 1.2.0, 1.3.0b1)'
required: true
jobs:
version_bump_and_changie:
uses: dbt-labs/actions/.github/workflows/version-bump.yml@main
with:
version_number: ${{ inputs.version_number }}
secrets: inherit # ok since what we are calling is internally maintained

21
.gitignore vendored
View File

@@ -11,8 +11,6 @@ __pycache__/
env*/
dbt_env/
build/
!tests/functional/build
!core/dbt/docs/build
develop-eggs/
dist/
downloads/
@@ -26,11 +24,8 @@ var/
*.egg-info/
.installed.cfg
*.egg
.mypy_cache/
.dmypy.json
*.mypy_cache/
logs/
.user.yml
profiles.yml
# PyInstaller
# Usually these files are written by a python script from a template
@@ -54,9 +49,9 @@ coverage.xml
*,cover
.hypothesis/
test.env
makefile.test.env
*.pytest_cache/
# Mypy
.mypy_cache/
# Translations
*.mo
@@ -71,10 +66,10 @@ docs/_build/
# PyBuilder
target/
# Ipython Notebook
#Ipython Notebook
.ipynb_checkpoints
# Emacs
#Emacs
*~
# Sublime Text
@@ -83,7 +78,6 @@ target/
# Vim
*.sw*
# Pyenv
.python-version
# Vim
@@ -96,12 +90,7 @@ venv/
# AWS credentials
.aws/
# MacOS
.DS_Store
# vscode
.vscode/
*.code-workspace
# poetry
poetry.lock

View File

@@ -1,62 +0,0 @@
# Configuration for pre-commit hooks (see https://pre-commit.com/).
# Eventually the hooks described here will be run as tests before merging each PR.
exclude: ^(core/dbt/docs/build/|core/dbt/events/types_pb2.py)
# Force all unspecified python hooks to run python 3.9
default_language_version:
python: python3
repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.2.0
hooks:
- id: check-yaml
args: [--unsafe]
- id: check-json
- id: end-of-file-fixer
- id: trailing-whitespace
exclude_types:
- "markdown"
- id: check-case-conflict
- repo: https://github.com/psf/black
rev: 22.3.0
hooks:
- id: black
- id: black
alias: black-check
stages: [manual]
args:
- "--check"
- "--diff"
- repo: https://github.com/pycqa/flake8
rev: 4.0.1
hooks:
- id: flake8
- id: flake8
alias: flake8-check
stages: [manual]
- repo: https://github.com/pre-commit/mirrors-mypy
rev: v1.4.1
hooks:
- id: mypy
# N.B.: Mypy is... a bit fragile.
#
# By using `language: system` we run this hook in the local
# environment instead of a pre-commit isolated one. This is needed
# to ensure mypy correctly parses the project.
# It may cause trouble
# in that it adds environmental variables out of our control to the
# mix. Unfortunately, there's nothing we can do about per pre-commit's
# author.
# See https://github.com/pre-commit/pre-commit/issues/730 for details.
args: [--show-error-codes]
files: ^core/dbt/
language: system
- id: mypy
alias: mypy-check
stages: [manual]
args: [--show-error-codes, --pretty]
files: ^core/dbt/
language: system

View File

@@ -1,39 +1,34 @@
The core function of dbt is SQL compilation and execution. Users create projects of dbt resources (models, tests, seeds, snapshots, ...), defined in SQL and YAML files, and they invoke dbt to create, update, or query associated views and tables. Today, dbt makes heavy use of Jinja2 to enable the templating of SQL, and to construct a DAG (Directed Acyclic Graph) from all of the resources in a project. Users can also extend their projects by installing resources (including Jinja macros) from other projects, called "packages."
The core function of dbt is SQL compilation and execution. Users create projects of dbt resources (models, tests, seeds, snapshots, ...), defined in SQL and YAML files, and they invoke dbt to create, update, or query associated views and tables. Today, dbt makes heavy use of Jinja2 to enable the templating of SQL, and to construct a DAG (Directed Acyclic Graph) from all of the resources in a project. Users can also extend their projects by installing resources (including Jinja macros) from other projects, called "packages."
## dbt-core
Most of the python code in the repository is within the `core/dbt` directory.
- [`single python files`](core/dbt/README.md): A number of individual files, such as 'compilation.py' and 'exceptions.py'
The main subdirectories of core/dbt:
- [`adapters`](core/dbt/adapters/README.md): Define base classes for behavior that is likely to differ across databases
- [`clients`](core/dbt/clients/README.md): Interface with dependencies (agate, jinja) or across operating systems
- [`config`](core/dbt/config/README.md): Reconcile user-supplied configuration from connection profiles, project files, and Jinja macros
- [`context`](core/dbt/context/README.md): Build and expose dbt-specific Jinja functionality
- [`contracts`](core/dbt/contracts/README.md): Define Python objects (dataclasses) that dbt expects to create and validate
- [`deps`](core/dbt/deps/README.md): Package installation and dependency resolution
- [`events`](core/dbt/events/README.md): Logging events
- [`graph`](core/dbt/graph/README.md): Produce a `networkx` DAG of project resources, and selecting those resources given user-supplied criteria
- [`include`](core/dbt/include/README.md): The dbt "global project," which defines default implementations of Jinja2 macros
- [`parser`](core/dbt/parser/README.md): Read project files, validate, construct python objects
- [`task`](core/dbt/task/README.md): Set forth the actions that dbt can perform when invoked
Legacy tests are found in the 'test' directory:
- [`unit tests`](core/dbt/test/unit/README.md): Unit tests
- [`integration tests`](core/dbt/test/integration/README.md): Integration tests
Most of the python code in the repository is within the `core/dbt` directory. Currently the main subdirectories are:
- [`adapters`](core/dbt/adapters): Define base classes for behavior that is likely to differ across databases
- [`clients`](core/dbt/clients): Interface with dependencies (agate, jinja) or across operating systems
- [`config`](core/dbt/config): Reconcile user-supplied configuration from connection profiles, project files, and Jinja macros
- [`context`](core/dbt/context): Build and expose dbt-specific Jinja functionality
- [`contracts`](core/dbt/contracts): Define Python objects (dataclasses) that dbt expects to create and validate
- [`deps`](core/dbt/deps): Package installation and dependency resolution
- [`graph`](core/dbt/graph): Produce a `networkx` DAG of project resources, and selecting those resources given user-supplied criteria
- [`include`](core/dbt/include): The dbt "global project," which defines default implementations of Jinja2 macros
- [`parser`](core/dbt/parser): Read project files, validate, construct python objects
- [`rpc`](core/dbt/rpc): Provide remote procedure call server for invoking dbt, following JSON-RPC 2.0 spec
- [`task`](core/dbt/task): Set forth the actions that dbt can perform when invoked
### Invoking dbt
The "tasks" map to top-level dbt commands. So `dbt run` => task.run.RunTask, etc. Some are more like abstract base classes (GraphRunnableTask, for example) but all the concrete types outside of task should map to tasks. Currently one executes at a time. The tasks kick off their “Runners” and those do execute in parallel. The parallelism is managed via a thread pool, in GraphRunnableTask.
There are two supported ways of invoking dbt: from the command line and using an RPC server.
The "tasks" map to top-level dbt commands. So `dbt run` => task.run.RunTask, etc. Some are more like abstract base classes (GraphRunnableTask, for example) but all the concrete types outside of task/rpc should map to tasks. Currently one executes at a time. The tasks kick off their “Runners” and those do execute in parallel. The parallelism is managed via a thread pool, in GraphRunnableTask.
core/dbt/include/index.html
This is the docs website code. It comes from the dbt-docs repository, and is generated when a release is packaged.
## Adapters
dbt uses an adapter-plugin pattern to extend support to different databases, warehouses, query engines, etc. For testing and development purposes, the dbt-postgres plugin lives alongside the dbt-core codebase, in the [`plugins`](plugins) subdirectory. Like other adapter plugins, it is a self-contained codebase and package that builds on top of dbt-core.
dbt uses an adapter-plugin pattern to extend support to different databases, warehouses, query engines, etc. The four core adapters that are in the main repository, contained within the [`plugins`](plugins) subdirectory, are: Postgres Redshift, Snowflake and BigQuery. Other warehouses use adapter plugins defined in separate repositories (e.g. [dbt-spark](https://github.com/dbt-labs/dbt-spark), [dbt-presto](https://github.com/dbt-labs/dbt-presto)).
Each adapter is a mix of python, Jinja2, and SQL. The adapter code also makes heavy use of Jinja2 to wrap modular chunks of SQL functionality, define default implementations, and allow plugins to override it.
Each adapter is a mix of python, Jinja2, and SQL. The adapter code also makes heavy use of Jinja2 to wrap modular chunks of SQL functionality, define default implementations, and allow plugins to override it.
Each adapter plugin is a standalone python package that includes:
@@ -51,4 +46,4 @@ The [`test/`](test/) subdirectory includes unit and integration tests that run a
- [docker](docker/): All dbt versions are published as Docker images on DockerHub. This subfolder contains the `Dockerfile` (constant) and `requirements.txt` (one for each version).
- [etc](etc/): Images for README
- [scripts](scripts/): Helper scripts for testing, releasing, and producing JSON schemas. These are not included in distributions of dbt, nor are they rigorously tested—they're just handy tools for the dbt maintainers :)
- [scripts](scripts/): Helper scripts for testing, releasing, and producing JSON schemas. These are not included in distributions of dbt, not are they rigorously tested—they're just handy tools for the dbt maintainers :)

3414
CHANGELOG.md Executable file → Normal file

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@@ -1,77 +1,116 @@
# Contributing to `dbt-core`
`dbt-core` is open source software. It is what it is today because community members have opened issues, provided feedback, and [contributed to the knowledge loop](https://www.getdbt.com/dbt-labs/values/). Whether you are a seasoned open source contributor or a first-time committer, we welcome and encourage you to contribute code, documentation, ideas, or problem statements to this project.
# Contributing to `dbt`
1. [About this document](#about-this-document)
2. [Getting the code](#getting-the-code)
3. [Setting up an environment](#setting-up-an-environment)
4. [Running dbt-core in development](#running-dbt-core-in-development)
5. [Testing dbt-core](#testing)
6. [Debugging](#debugging)
7. [Adding or modifying a changelog entry](#adding-or-modifying-a-changelog-entry)
8. [Submitting a Pull Request](#submitting-a-pull-request)
2. [Proposing a change](#proposing-a-change)
3. [Getting the code](#getting-the-code)
4. [Setting up an environment](#setting-up-an-environment)
5. [Running `dbt` in development](#running-dbt-in-development)
6. [Testing](#testing)
7. [Submitting a Pull Request](#submitting-a-pull-request)
## About this document
There are many ways to contribute to the ongoing development of `dbt-core`, such as by participating in discussions and issues. We encourage you to first read our higher-level document: ["Expectations for Open Source Contributors"](https://docs.getdbt.com/docs/contributing/oss-expectations).
This document is a guide intended for folks interested in contributing to `dbt`. Below, we document the process by which members of the community should create issues and submit pull requests (PRs) in this repository. It is not intended as a guide for using `dbt`, and it assumes a certain level of familiarity with Python concepts such as virtualenvs, `pip`, python modules, filesystems, and so on. This guide assumes you are using macOS or Linux and are comfortable with the command line.
The rest of this document serves as a more granular guide for contributing code changes to `dbt-core` (this repository). It is not intended as a guide for using `dbt-core`, and some pieces assume a level of familiarity with Python development (virtualenvs, `pip`, etc). Specific code snippets in this guide assume you are using macOS or Linux and are comfortable with the command line.
If you're new to python development or contributing to open-source software, we encourage you to read this document from start to finish. If you get stuck, drop us a line in the `#dbt-core-development` channel on [slack](https://community.getdbt.com).
If you get stuck, we're happy to help! Drop us a line in the `#dbt-core-development` channel in the [dbt Community Slack](https://community.getdbt.com).
### Signing the CLA
### Notes
Please note that all contributors to `dbt` must sign the [Contributor License Agreement](https://docs.getdbt.com/docs/contributor-license-agreements) to have their Pull Request merged into the `dbt` codebase. If you are unable to sign the CLA, then the `dbt` maintainers will unfortunately be unable to merge your Pull Request. You are, however, welcome to open issues and comment on existing ones.
- **Adapters:** Is your issue or proposed code change related to a specific [database adapter](https://docs.getdbt.com/docs/available-adapters)? If so, please open issues, PRs, and discussions in that adapter's repository instead. The sole exception is Postgres; the `dbt-postgres` plugin lives in this repository (`dbt-core`).
- **CLA:** Please note that anyone contributing code to `dbt-core` must sign the [Contributor License Agreement](https://docs.getdbt.com/docs/contributor-license-agreements). If you are unable to sign the CLA, the `dbt-core` maintainers will unfortunately be unable to merge any of your Pull Requests. We welcome you to participate in discussions, open issues, and comment on existing ones.
- **Branches:** All pull requests from community contributors should target the `main` branch (default). If the change is needed as a patch for a minor version of dbt that has already been released (or is already a release candidate), a maintainer will backport the changes in your PR to the relevant "latest" release branch (`1.0.latest`, `1.1.latest`, ...). If an issue fix applies to a release branch, that fix should be first committed to the development branch and then to the release branch (rarely release-branch fixes may not apply to `main`).
- **Releases**: Before releasing a new minor version of Core, we prepare a series of alphas and release candidates to allow users (especially employees of dbt Labs!) to test the new version in live environments. This is an important quality assurance step, as it exposes the new code to a wide variety of complicated deployments and can surface bugs before official release. Releases are accessible via pip, homebrew, and dbt Cloud.
## Proposing a change
`dbt` is Apache 2.0-licensed open source software. `dbt` is what it is today because community members like you have opened issues, provided feedback, and contributed to the knowledge loop for the entire communtiy. Whether you are a seasoned open source contributor or a first-time committer, we welcome and encourage you to contribute code, documentation, ideas, or problem statements to this project.
### Defining the problem
If you have an idea for a new feature or if you've discovered a bug in `dbt`, the first step is to open an issue. Please check the list of [open issues](https://github.com/dbt-labs/dbt/issues) before creating a new one. If you find a relevant issue, please add a comment to the open issue instead of creating a new one. There are hundreds of open issues in this repository and it can be hard to know where to look for a relevant open issue. **The `dbt` maintainers are always happy to point contributors in the right direction**, so please err on the side of documenting your idea in a new issue if you are unsure where a problem statement belongs.
> **Note:** All community-contributed Pull Requests _must_ be associated with an open issue. If you submit a Pull Request that does not pertain to an open issue, you will be asked to create an issue describing the problem before the Pull Request can be reviewed.
### Discussing the idea
After you open an issue, a `dbt` maintainer will follow up by commenting on your issue (usually within 1-3 days) to explore your idea further and advise on how to implement the suggested changes. In many cases, community members will chime in with their own thoughts on the problem statement. If you as the issue creator are interested in submitting a Pull Request to address the issue, you should indicate this in the body of the issue. The `dbt` maintainers are _always_ happy to help contributors with the implementation of fixes and features, so please also indicate if there's anything you're unsure about or could use guidance around in the issue.
### Submitting a change
If an issue is appropriately well scoped and describes a beneficial change to the `dbt` codebase, then anyone may submit a Pull Request to implement the functionality described in the issue. See the sections below on how to do this.
The `dbt` maintainers will add a `good first issue` label if an issue is suitable for a first-time contributor. This label often means that the required code change is small, limited to one database adapter, or a net-new addition that does not impact existing functionality. You can see the list of currently open issues on the [Contribute](https://github.com/dbt-labs/dbt/contribute) page.
Here's a good workflow:
- Comment on the open issue, expressing your interest in contributing the required code change
- Outline your planned implementation. If you want help getting started, ask!
- Follow the steps outlined below to develop locally. Once you have opened a PR, one of the `dbt` maintainers will work with you to review your code.
- Add a test! Tests are crucial for both fixes and new features alike. We want to make sure that code works as intended, and that it avoids any bugs previously encountered. Currently, the best resource for understanding `dbt`'s [unit](test/unit) and [integration](test/integration) tests is the tests themselves. One of the maintainers can help by pointing out relevant examples.
In some cases, the right resolution to an open issue might be tangential to the `dbt` codebase. The right path forward might be a documentation update or a change that can be made in user-space. In other cases, the issue might describe functionality that the `dbt` maintainers are unwilling or unable to incorporate into the `dbt` codebase. When it is determined that an open issue describes functionality that will not translate to a code change in the `dbt` repository, the issue will be tagged with the `wontfix` label (see below) and closed.
### Using issue labels
The `dbt` maintainers use labels to categorize open issues. Some labels indicate the databases impacted by the issue, while others describe the domain in the `dbt` codebase germane to the discussion. While most of these labels are self-explanatory (eg. `snowflake` or `bigquery`), there are others that are worth describing.
| tag | description |
| --- | ----------- |
| [triage](https://github.com/dbt-labs/dbt/labels/triage) | This is a new issue which has not yet been reviewed by a `dbt` maintainer. This label is removed when a maintainer reviews and responds to the issue. |
| [bug](https://github.com/dbt-labs/dbt/labels/bug) | This issue represents a defect or regression in `dbt` |
| [enhancement](https://github.com/dbt-labs/dbt/labels/enhancement) | This issue represents net-new functionality in `dbt` |
| [good first issue](https://github.com/dbt-labs/dbt/labels/good%20first%20issue) | This issue does not require deep knowledge of the `dbt` codebase to implement. This issue is appropriate for a first-time contributor. |
| [help wanted](https://github.com/dbt-labs/dbt/labels/help%20wanted) / [discussion](https://github.com/dbt-labs/dbt/labels/discussion) | Conversation around this issue in ongoing, and there isn't yet a clear path forward. Input from community members is most welcome. |
| [duplicate](https://github.com/dbt-labs/dbt/issues/duplicate) | This issue is functionally identical to another open issue. The `dbt` maintainers will close this issue and encourage community members to focus conversation on the other one. |
| [snoozed](https://github.com/dbt-labs/dbt/labels/snoozed) | This issue describes a good idea, but one which will probably not be addressed in a six-month time horizon. The `dbt` maintainers will revist these issues periodically and re-prioritize them accordingly. |
| [stale](https://github.com/dbt-labs/dbt/labels/stale) | This is an old issue which has not recently been updated. Stale issues will periodically be closed by `dbt` maintainers, but they can be re-opened if the discussion is restarted. |
| [wontfix](https://github.com/dbt-labs/dbt/labels/wontfix) | This issue does not require a code change in the `dbt` repository, or the maintainers are unwilling/unable to merge a Pull Request which implements the behavior described in the issue. |
#### Branching Strategy
`dbt` has three types of branches:
- **Trunks** are where active development of the next release takes place. There is one trunk named `develop` at the time of writing this, and will be the default branch of the repository.
- **Release Branches** track a specific, not yet complete release of `dbt`. Each minor version release has a corresponding release branch. For example, the `0.11.x` series of releases has a branch called `0.11.latest`. This allows us to release new patch versions under `0.11` without necessarily needing to pull them into the latest version of `dbt`.
- **Feature Branches** track individual features and fixes. On completion they should be merged into the trunk branch or a specific release branch.
## Getting the code
### Installing git
You will need `git` in order to download and modify the `dbt-core` source code. On macOS, the best way to download git is to just install [Xcode](https://developer.apple.com/support/xcode/).
You will need `git` in order to download and modify the `dbt` source code. On macOS, the best way to download git is to just install [Xcode](https://developer.apple.com/support/xcode/).
### External contributors
If you are not a member of the `dbt-labs` GitHub organization, you can contribute to `dbt-core` by forking the `dbt-core` repository. For a detailed overview on forking, check out the [GitHub docs on forking](https://help.github.com/en/articles/fork-a-repo). In short, you will need to:
If you are not a member of the `dbt-labs` GitHub organization, you can contribute to `dbt` by forking the `dbt` repository. For a detailed overview on forking, check out the [GitHub docs on forking](https://help.github.com/en/articles/fork-a-repo). In short, you will need to:
1. Fork the `dbt-core` repository
2. Clone your fork locally
3. Check out a new branch for your proposed changes
4. Push changes to your fork
5. Open a pull request against `dbt-labs/dbt-core` from your forked repository
1. fork the `dbt` repository
2. clone your fork locally
3. check out a new branch for your proposed changes
4. push changes to your fork
5. open a pull request against `dbt-labs/dbt` from your forked repository
### dbt Labs contributors
### Core contributors
If you are a member of the `dbt-labs` GitHub organization, you will have push access to the `dbt-core` repo. Rather than forking `dbt-core` to make your changes, just clone the repository, check out a new branch, and push directly to that branch. Branch names should be fixed by `CT-XXX/` where:
* CT stands for 'core team'
* XXX stands for a JIRA ticket number
If you are a member of the `dbt-labs` GitHub organization, you will have push access to the `dbt` repo. Rather than forking `dbt` to make your changes, just clone the repository, check out a new branch, and push directly to that branch.
## Setting up an environment
There are some tools that will be helpful to you in developing locally. While this is the list relevant for `dbt-core` development, many of these tools are used commonly across open-source python projects.
There are some tools that will be helpful to you in developing locally. While this is the list relevant for `dbt` development, many of these tools are used commonly across open-source python projects.
### Tools
These are the tools used in `dbt-core` development and testing:
A short list of tools used in `dbt` testing that will be helpful to your understanding:
- [`tox`](https://tox.readthedocs.io/en/latest/) to manage virtualenvs across python versions. We currently target the latest patch releases for Python 3.8, 3.9, 3.10 and 3.11
- [`pytest`](https://docs.pytest.org/en/latest/) to define, discover, and run tests
- [`tox`](https://tox.readthedocs.io/en/latest/) to manage virtualenvs across python versions. We currently target the latest patch releases for Python 3.6, Python 3.7, Python 3.8, and Python 3.9
- [`pytest`](https://docs.pytest.org/en/latest/) to discover/run tests
- [`make`](https://users.cs.duke.edu/~ola/courses/programming/Makefiles/Makefiles.html) - but don't worry too much, nobody _really_ understands how make works and our Makefile is super simple
- [`flake8`](https://flake8.pycqa.org/en/latest/) for code linting
- [`black`](https://github.com/psf/black) for code formatting
- [`mypy`](https://mypy.readthedocs.io/en/stable/) for static type checking
- [`pre-commit`](https://pre-commit.com) to easily run those checks
- [`changie`](https://changie.dev/) to create changelog entries, without merge conflicts
- [`make`](https://users.cs.duke.edu/~ola/courses/programming/Makefiles/Makefiles.html) to run multiple setup or test steps in combination. Don't worry too much, nobody _really_ understands how `make` works, and our Makefile aims to be super simple.
- [GitHub Actions](https://github.com/features/actions) for automating tests and checks, once a PR is pushed to the `dbt-core` repository
- [CircleCI](https://circleci.com/product/) and [Azure Pipelines](https://azure.microsoft.com/en-us/services/devops/pipelines/)
A deep understanding of these tools in not required to effectively contribute to `dbt-core`, but we recommend checking out the attached documentation if you're interested in learning more about each one.
A deep understanding of these tools in not required to effectively contribute to `dbt`, but we recommend checking out the attached documentation if you're interested in learning more about them.
#### Virtual environments
#### virtual environments
We strongly recommend using virtual environments when developing code in `dbt-core`. We recommend creating this virtualenv
in the root of the `dbt-core` repository. To create a new virtualenv, run:
We strongly recommend using virtual environments when developing code in `dbt`. We recommend creating this virtualenv
in the root of the `dbt` repository. To create a new virtualenv, run:
```sh
python3 -m venv env
source env/bin/activate
@@ -79,12 +118,12 @@ source env/bin/activate
This will create and activate a new Python virtual environment.
#### Docker and `docker-compose`
#### docker and docker-compose
Docker and `docker-compose` are both used in testing. Specific instructions for you OS can be found [here](https://docs.docker.com/get-docker/).
Docker and docker-compose are both used in testing. Specific instructions for you OS can be found [here](https://docs.docker.com/get-docker/).
#### Postgres (optional)
#### postgres (optional)
For testing, and later in the examples in this document, you may want to have `psql` available so you can poke around in the database and see what happened. We recommend that you use [homebrew](https://brew.sh/) for that on macOS, and your package manager on Linux. You can install any version of the postgres client that you'd like. On macOS, with homebrew setup, you can run:
@@ -92,41 +131,35 @@ For testing, and later in the examples in this document, you may want to have `p
brew install postgresql
```
## Running `dbt-core` in development
## Running `dbt` in development
### Installation
First make sure that you set up your `virtualenv` as described in [Setting up an environment](#setting-up-an-environment). Also ensure you have the latest version of pip installed with `pip install --upgrade pip`. Next, install `dbt-core` (and its dependencies):
First make sure that you set up your `virtualenv` as described in [Setting up an environment](#setting-up-an-environment). Also ensure you have the latest version of pip installed with `pip install --upgrade pip`. Next, install `dbt` (and its dependencies) with:
```sh
make dev
```
or, alternatively:
```sh
# or
pip install -r dev-requirements.txt -r editable-requirements.txt
pre-commit install
```
When installed in this way, any changes you make to your local copy of the source code will be reflected immediately in your next `dbt` run.
When `dbt` is installed this way, any changes you make to the `dbt` source code will be reflected immediately in your next `dbt` run.
### Running `dbt-core`
### Running `dbt`
With your virtualenv activated, the `dbt` script should point back to the source code you've cloned on your machine. You can verify this by running `which dbt`. This command should show you a path to an executable in your virtualenv.
Configure your [profile](https://docs.getdbt.com/docs/configure-your-profile) as necessary to connect to your target databases. It may be a good idea to add a new profile pointing to a local Postgres instance, or a specific test sandbox within your data warehouse if appropriate. Make sure to create a profile before running integration tests.
Configure your [profile](https://docs.getdbt.com/docs/configure-your-profile) as necessary to connect to your target databases. It may be a good idea to add a new profile pointing to a local postgres instance, or a specific test sandbox within your data warehouse if appropriate.
## Testing
Once you're able to manually test that your code change is working as expected, it's important to run existing automated tests, as well as adding some new ones. These tests will ensure that:
- Your code changes do not unexpectedly break other established functionality
- Your code changes can handle all known edge cases
- The functionality you're adding will _keep_ working in the future
Getting the `dbt` integration tests set up in your local environment will be very helpful as you start to make changes to your local version of `dbt`. The section that follows outlines some helpful tips for setting up the test environment.
Although `dbt-core` works with a number of different databases, you won't need to supply credentials for every one of these databases in your test environment. Instead, you can test most `dbt-core` code changes with Python and Postgres.
Since `dbt` works with a number of different databases, you will need to supply credentials for one or more of these databases in your test environment. Most organizations don't have access to each of a BigQuery, Redshift, Snowflake, and Postgres database, so it's likely that you will be unable to run every integration test locally. Fortunately, dbt Labs provides a CI environment with access to sandboxed Redshift, Snowflake, BigQuery, and Postgres databases. See the section on [_Submitting a Pull Request_](#submitting-a-pull-request) below for more information on this CI setup.
### Initial setup
Postgres offers the easiest way to test most `dbt-core` functionality today. They are the fastest to run, and the easiest to set up. To run the Postgres integration tests, you'll have to do one extra step of setting up the test database:
We recommend starting with `dbt`'s Postgres tests. These tests cover most of the functionality in `dbt`, are the fastest to run, and are the easiest to set up. To run the Postgres integration tests, you'll have to do one extra step of setting up the test database:
```sh
make setup-db
@@ -137,6 +170,17 @@ docker-compose up -d database
PGHOST=localhost PGUSER=root PGPASSWORD=password PGDATABASE=postgres bash test/setup_db.sh
```
Note that you may need to run the previous command twice as it does not currently wait for the database to be running before attempting to run commands against it. This will be fixed with [#3876](https://github.com/dbt-labs/dbt/issues/3876).
`dbt` uses test credentials specified in a `test.env` file in the root of the repository for non-Postgres databases. This `test.env` file is git-ignored, but please be _extra_ careful to never check in credentials or other sensitive information when developing against `dbt`. To create your `test.env` file, copy the provided sample file, then supply your relevant credentials. This step is only required to use non-Postgres databases.
```
cp test.env.sample test.env
$EDITOR test.env
```
> In general, it's most important to have successful unit and Postgres tests. Once you open a PR, `dbt` will automatically run integration tests for the other three core database adapters. Of course, if you are a BigQuery user, contributing a BigQuery-only feature, it's important to run BigQuery tests as well.
### Test commands
There are a few methods for running tests locally.
@@ -152,79 +196,38 @@ make test
# Runs postgres integration tests with py38 in "fail fast" mode.
make integration
```
> These make targets assume you have a local installation of a recent version of [`tox`](https://tox.readthedocs.io/en/latest/) for unit/integration testing and pre-commit for code quality checks,
> These make targets assume you have a recent version of [`tox`](https://tox.readthedocs.io/en/latest/) installed locally,
> unless you use choose a Docker container to run tests. Run `make help` for more info.
Check out the other targets in the Makefile to see other commonly used test
suites.
#### `pre-commit`
[`pre-commit`](https://pre-commit.com) takes care of running all code-checks for formatting and linting. Run `make dev` to install `pre-commit` in your local environment (we recommend running this command with a python virtual environment active). This command installs several pip executables including black, mypy, and flake8. Once this is done you can use any of the linter-based make targets as well as a git pre-commit hook that will ensure proper formatting and linting.
#### `tox`
[`tox`](https://tox.readthedocs.io/en/latest/) takes care of managing virtualenvs and install dependencies in order to run tests. You can also run tests in parallel, for example, you can run unit tests for Python 3.8, Python 3.9, Python 3.10 and Python 3.11 checks in parallel with `tox -p`. Also, you can run unit tests for specific python versions with `tox -e py38`. The configuration for these tests in located in `tox.ini`.
[`tox`](https://tox.readthedocs.io/en/latest/) takes care of managing virtualenvs and install dependencies in order to run
tests. You can also run tests in parallel, for example, you can run unit tests
for Python 3.6, Python 3.7, Python 3.8, `flake8` checks, and `mypy` checks in
parallel with `tox -p`. Also, you can run unit tests for specific python versions
with `tox -e py36`. The configuration for these tests in located in `tox.ini`.
#### `pytest`
Finally, you can also run a specific test or group of tests using [`pytest`](https://docs.pytest.org/en/latest/) directly. With a virtualenv active and dev dependencies installed you can do things like:
Finally, you can also run a specific test or group of tests using [`pytest`](https://docs.pytest.org/en/latest/) directly. With a virtualenv
active and dev dependencies installed you can do things like:
```sh
# run specific postgres integration tests
python -m pytest -m profile_postgres test/integration/001_simple_copy_test
# run all unit tests in a file
python3 -m pytest tests/unit/test_graph.py
python -m pytest test/unit/test_graph.py
# run a specific unit test
python3 -m pytest tests/unit/test_graph.py::GraphTest::test__dependency_list
# run specific Postgres functional tests
python3 -m pytest tests/functional/sources
python -m pytest test/unit/test_graph.py::GraphTest::test__dependency_list
```
> See [pytest usage docs](https://docs.pytest.org/en/6.2.x/usage.html) for an overview of useful command-line options.
### Unit, Integration, Functional?
Here are some general rules for adding tests:
* unit tests (`tests/unit`) dont need to access a database; "pure Python" tests should be written as unit tests
* functional tests (`tests/functional`) cover anything that interacts with a database, namely adapter
## Debugging
1. The logs for a `dbt run` have stack traces and other information for debugging errors (in `logs/dbt.log` in your project directory).
2. Try using a debugger, like `ipdb`. For pytest: `--pdb --pdbcls=IPython.terminal.debugger:pdb`
3. Sometimes, its easier to debug on a single thread: `dbt --single-threaded run`
4. To make print statements from Jinja macros: `{{ log(msg, info=true) }}`
5. You can also add `{{ debug() }}` statements, which will drop you into some auto-generated code that the macro wrote.
6. The dbt “artifacts” are written out to the target directory of your dbt project. They are in unformatted json, which can be hard to read. Format them with:
> python -m json.tool target/run_results.json > run_results.json
### Assorted development tips
* Append `# type: ignore` to the end of a line if you need to disable `mypy` on that line.
* Sometimes flake8 complains about lines that are actually fine, in which case you can put a comment on the line such as: # noqa or # noqa: ANNN, where ANNN is the error code that flake8 issues.
* To collect output for `CProfile`, run dbt with the `-r` option and the name of an output file, i.e. `dbt -r dbt.cprof run`. If you just want to profile parsing, you can do: `dbt -r dbt.cprof parse`. `pip` install `snakeviz` to view the output. Run `snakeviz dbt.cprof` and output will be rendered in a browser window.
## Adding or modifying a CHANGELOG Entry
We use [changie](https://changie.dev) to generate `CHANGELOG` entries. **Note:** Do not edit the `CHANGELOG.md` directly. Your modifications will be lost.
Follow the steps to [install `changie`](https://changie.dev/guide/installation/) for your system.
Once changie is installed and your PR is created for a new feature, simply run the following command and changie will walk you through the process of creating a changelog entry:
```shell
changie new
```
Commit the file that's created and your changelog entry is complete!
If you are contributing to a feature already in progress, you will modify the changie yaml file in dbt/.changes/unreleased/ related to your change. If you need help finding this file, please ask within the discussion for the pull request!
You don't need to worry about which `dbt-core` version your change will go into. Just create the changelog entry with `changie`, and open your PR against the `main` branch. All merged changes will be included in the next minor version of `dbt-core`. The Core maintainers _may_ choose to "backport" specific changes in order to patch older minor versions. In that case, a maintainer will take care of that backport after merging your PR, before releasing the new version of `dbt-core`.
> [Here](https://docs.pytest.org/en/reorganize-docs/new-docs/user/commandlineuseful.html)
> is a list of useful command-line options for `pytest` to use while developing.
## Submitting a Pull Request
Code can be merged into the current development branch `main` by opening a pull request. A `dbt-core` maintainer will review your PR. They may suggest code revision for style or clarity, or request that you add unit or integration test(s). These are good things! We believe that, with a little bit of help, anyone can contribute high-quality code.
dbt Labs provides a sandboxed Redshift, Snowflake, and BigQuery database for use in a CI environment. When pull requests are submitted to the `dbt-labs/dbt` repo, GitHub will trigger automated tests in CircleCI and Azure Pipelines.
Automated tests run via GitHub Actions. If you're a first-time contributor, all tests (including code checks and unit tests) will require a maintainer to approve. Changes in the `dbt-core` repository trigger integration tests against Postgres. dbt Labs also provides CI environments in which to test changes to other adapters, triggered by PRs in those adapters' repositories, as well as periodic maintenance checks of each adapter in concert with the latest `dbt-core` code changes.
A `dbt` maintainer will review your PR. They may suggest code revision for style or clarity, or request that you add unit or integration test(s). These are good things! We believe that, with a little bit of help, anyone can contribute high-quality code.
Once all tests are passing and your PR has been approved, a `dbt-core` maintainer will merge your changes into the active development branch. And that's it! Happy developing :tada:
Sometimes, the content license agreement auto-check bot doesn't find a user's entry in its roster. If you need to force a rerun, add `@cla-bot check` in a comment on the pull request.
Once all tests are passing and your PR has been approved, a `dbt` maintainer will merge your changes into the active development branch. And that's it! Happy developing :tada:

View File

@@ -1,15 +1,10 @@
##
# This dockerfile is used for local development and adapter testing only.
# See `/docker` for a generic and production-ready docker file
##
FROM ubuntu:22.04
FROM ubuntu:20.04
ENV DEBIAN_FRONTEND noninteractive
RUN apt-get update \
&& apt-get install -y --no-install-recommends \
software-properties-common gpg-agent \
software-properties-common \
&& add-apt-repository ppa:git-core/ppa -y \
&& apt-get dist-upgrade -y \
&& apt-get install -y --no-install-recommends \
@@ -30,18 +25,22 @@ RUN apt-get update \
unixodbc-dev \
&& add-apt-repository ppa:deadsnakes/ppa \
&& apt-get install -y \
python-is-python3 \
python-dev-is-python3 \
python \
python-dev \
python-pip \
python3.6 \
python3.6-dev \
python3-pip \
python3.6-venv \
python3.7 \
python3.7-dev \
python3.7-venv \
python3.8 \
python3.8-dev \
python3.8-venv \
python3.9 \
python3.9-dev \
python3.9-venv \
python3.10 \
python3.10-dev \
python3.10-venv \
python3.11 \
python3.11-dev \
python3.11-venv \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*

151
Makefile
View File

@@ -6,97 +6,71 @@ ifeq ($(USE_DOCKER),true)
DOCKER_CMD := docker-compose run --rm test
endif
#
# To override CI_flags, create a file at this repo's root dir named `makefile.test.env`. Fill it
# with any ENV_VAR overrides required by your test environment, e.g.
# DBT_TEST_USER_1=user
# LOG_DIR="dir with a space in it"
#
# Warn: Restrict each line to one variable only.
#
ifeq (./makefile.test.env,$(wildcard ./makefile.test.env))
include ./makefile.test.env
endif
CI_FLAGS =\
DBT_TEST_USER_1=$(if $(DBT_TEST_USER_1),$(DBT_TEST_USER_1),dbt_test_user_1)\
DBT_TEST_USER_2=$(if $(DBT_TEST_USER_2),$(DBT_TEST_USER_2),dbt_test_user_2)\
DBT_TEST_USER_3=$(if $(DBT_TEST_USER_3),$(DBT_TEST_USER_3),dbt_test_user_3)\
RUSTFLAGS=$(if $(RUSTFLAGS),$(RUSTFLAGS),"-D warnings")\
LOG_DIR=$(if $(LOG_DIR),$(LOG_DIR),./logs)\
DBT_LOG_FORMAT=$(if $(DBT_LOG_FORMAT),$(DBT_LOG_FORMAT),json)
.PHONY: dev_req
dev_req: ## Installs dbt-* packages in develop mode along with only development dependencies.
@\
pip install -r dev-requirements.txt
pip install -r editable-requirements.txt
.PHONY: dev
dev: dev_req ## Installs dbt-* packages in develop mode along with development dependencies and pre-commit.
@\
pre-commit install
.PHONY: proto_types
proto_types: ## generates google protobuf python file from types.proto
protoc -I=./core/dbt/events --python_out=./core/dbt/events ./core/dbt/events/types.proto
dev: ## Installs dbt-* packages in develop mode along with development dependencies.
pip install -r dev-requirements.txt -r editable-requirements.txt
.PHONY: mypy
mypy: .env ## Runs mypy against staged changes for static type checking.
@\
$(DOCKER_CMD) pre-commit run --hook-stage manual mypy-check | grep -v "INFO"
mypy: .env ## Runs mypy for static type checking.
$(DOCKER_CMD) tox -e mypy
.PHONY: flake8
flake8: .env ## Runs flake8 against staged changes to enforce style guide.
@\
$(DOCKER_CMD) pre-commit run --hook-stage manual flake8-check | grep -v "INFO"
.PHONY: black
black: .env ## Runs black against staged changes to enforce style guide.
@\
$(DOCKER_CMD) pre-commit run --hook-stage manual black-check -v | grep -v "INFO"
flake8: .env ## Runs flake8 to enforce style guide.
$(DOCKER_CMD) tox -e flake8
.PHONY: lint
lint: .env ## Runs flake8 and mypy code checks against staged changes.
@\
$(DOCKER_CMD) pre-commit run flake8-check --hook-stage manual | grep -v "INFO"; \
$(DOCKER_CMD) pre-commit run mypy-check --hook-stage manual | grep -v "INFO"
lint: .env ## Runs all code checks in parallel.
$(DOCKER_CMD) tox -p -e flake8,mypy
.PHONY: unit
unit: .env ## Runs unit tests with py
@\
$(DOCKER_CMD) tox -e py
unit: .env ## Runs unit tests with py38.
$(DOCKER_CMD) tox -e py38
.PHONY: test
test: .env ## Runs unit tests with py and code checks against staged changes.
@\
$(DOCKER_CMD) tox -e py; \
$(DOCKER_CMD) pre-commit run black-check --hook-stage manual | grep -v "INFO"; \
$(DOCKER_CMD) pre-commit run flake8-check --hook-stage manual | grep -v "INFO"; \
$(DOCKER_CMD) pre-commit run mypy-check --hook-stage manual | grep -v "INFO"
test: .env ## Runs unit tests with py38 and code checks in parallel.
$(DOCKER_CMD) tox -p -e py38,flake8,mypy
.PHONY: integration
integration: .env ## Runs postgres integration tests with py-integration
@\
$(CI_FLAGS) $(DOCKER_CMD) tox -e py-integration -- -nauto
integration: .env integration-postgres ## Alias for integration-postgres.
.PHONY: integration-fail-fast
integration-fail-fast: .env ## Runs postgres integration tests with py-integration in "fail fast" mode.
@\
$(DOCKER_CMD) tox -e py-integration -- -x -nauto
integration-fail-fast: .env integration-postgres-fail-fast ## Alias for integration-postgres-fail-fast.
.PHONY: interop
interop: clean
@\
mkdir $(LOG_DIR) && \
$(CI_FLAGS) $(DOCKER_CMD) tox -e py-integration -- -nauto && \
LOG_DIR=$(LOG_DIR) cargo run --manifest-path test/interop/log_parsing/Cargo.toml
.PHONY: integration-postgres
integration-postgres: .env ## Runs postgres integration tests with py38.
$(DOCKER_CMD) tox -e py38-postgres -- -nauto
.PHONY: integration-postgres-fail-fast
integration-postgres-fail-fast: .env ## Runs postgres integration tests with py38 in "fail fast" mode.
$(DOCKER_CMD) tox -e py38-postgres -- -x -nauto
.PHONY: integration-redshift
integration-redshift: .env ## Runs redshift integration tests with py38.
$(DOCKER_CMD) tox -e py38-redshift -- -nauto
.PHONY: integration-redshift-fail-fast
integration-redshift-fail-fast: .env ## Runs redshift integration tests with py38 in "fail fast" mode.
$(DOCKER_CMD) tox -e py38-redshift -- -x -nauto
.PHONY: integration-snowflake
integration-snowflake: .env ## Runs snowflake integration tests with py38.
$(DOCKER_CMD) tox -e py38-snowflake -- -nauto
.PHONY: integration-snowflake-fail-fast
integration-snowflake-fail-fast: .env ## Runs snowflake integration tests with py38 in "fail fast" mode.
$(DOCKER_CMD) tox -e py38-snowflake -- -x -nauto
.PHONY: integration-bigquery
integration-bigquery: .env ## Runs bigquery integration tests with py38.
$(DOCKER_CMD) tox -e py38-bigquery -- -nauto
.PHONY: integration-bigquery-fail-fast
integration-bigquery-fail-fast: .env ## Runs bigquery integration tests with py38 in "fail fast" mode.
$(DOCKER_CMD) tox -e py38-bigquery -- -x -nauto
.PHONY: setup-db
setup-db: ## Setup Postgres database with docker-compose for system testing.
@\
docker-compose up -d database && \
docker-compose up -d database
PGHOST=localhost PGUSER=root PGPASSWORD=password PGDATABASE=postgres bash test/setup_db.sh
# This rule creates a file named .env that is used by docker-compose for passing
@@ -112,30 +86,27 @@ endif
.PHONY: clean
clean: ## Resets development environment.
@echo 'cleaning repo...'
@rm -f .coverage
@rm -f .coverage.*
@rm -rf .eggs/
@rm -f .env
@rm -rf .tox/
@rm -rf build/
@rm -rf dbt.egg-info/
@rm -f dbt_project.yml
@rm -rf dist/
@rm -f htmlcov/*.{css,html,js,json,png}
@rm -rf logs/
@rm -rf target/
@find . -type f -name '*.pyc' -delete
@find . -type d -name '__pycache__' -depth -delete
@echo 'done.'
rm -f .coverage
rm -rf .eggs/
rm -f .env
rm -rf .tox/
rm -rf build/
rm -rf dbt.egg-info/
rm -f dbt_project.yml
rm -rf dist/
rm -f htmlcov/*.{css,html,js,json,png}
rm -rf logs/
rm -rf target/
find . -type f -name '*.pyc' -delete
find . -type d -name '__pycache__' -depth -delete
.PHONY: help
help: ## Show this help message.
@echo 'usage: make [target] [USE_DOCKER=true]'
@echo
@echo 'targets:'
@grep -E '^[8+a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'
@echo
@echo 'options:'
@echo 'use USE_DOCKER=true to run target in a docker container'

View File

@@ -1,15 +1,18 @@
<p align="center">
<img src="https://raw.githubusercontent.com/dbt-labs/dbt-core/fa1ea14ddfb1d5ae319d5141844910dd53ab2834/etc/dbt-core.svg" alt="dbt logo" width="750"/>
<img src="https://raw.githubusercontent.com/dbt-labs/dbt/ec7dee39f793aa4f7dd3dae37282cc87664813e4/etc/dbt-logo-full.svg" alt="dbt logo" width="500"/>
</p>
<p align="center">
<a href="https://github.com/dbt-labs/dbt-core/actions/workflows/main.yml">
<img src="https://github.com/dbt-labs/dbt-core/actions/workflows/main.yml/badge.svg?event=push" alt="CI Badge"/>
<a href="https://github.com/dbt-labs/dbt/actions/workflows/main.yml">
<img src="https://github.com/dbt-labs/dbt/actions/workflows/main.yml/badge.svg?event=push" alt="Unit Tests Badge"/>
</a>
<a href="https://github.com/dbt-labs/dbt/actions/workflows/integration.yml">
<img src="https://github.com/dbt-labs/dbt/actions/workflows/integration.yml/badge.svg?event=push" alt="Integration Tests Badge"/>
</a>
</p>
**[dbt](https://www.getdbt.com/)** enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
![architecture](https://github.com/dbt-labs/dbt-core/blob/202cb7e51e218c7b29eb3b11ad058bd56b7739de/etc/dbt-transform.png)
![architecture](https://raw.githubusercontent.com/dbt-labs/dbt/6c6649f9129d5d108aa3b0526f634cd8f3a9d1ed/etc/dbt-arch.png)
## Understanding dbt
@@ -17,11 +20,11 @@ Analysts using dbt can transform their data by simply writing select statements,
These select statements, or "models", form a dbt project. Models frequently build on top of one another dbt makes it easy to [manage relationships](https://docs.getdbt.com/docs/ref) between models, and [visualize these relationships](https://docs.getdbt.com/docs/documentation), as well as assure the quality of your transformations through [testing](https://docs.getdbt.com/docs/testing).
![dbt dag](https://raw.githubusercontent.com/dbt-labs/dbt-core/6c6649f9129d5d108aa3b0526f634cd8f3a9d1ed/etc/dbt-dag.png)
![dbt dag](https://raw.githubusercontent.com/dbt-labs/dbt/6c6649f9129d5d108aa3b0526f634cd8f3a9d1ed/etc/dbt-dag.png)
## Getting started
- [Install dbt](https://docs.getdbt.com/docs/get-started/installation)
- [Install dbt](https://docs.getdbt.com/docs/installation)
- Read the [introduction](https://docs.getdbt.com/docs/introduction/) and [viewpoint](https://docs.getdbt.com/docs/about/viewpoint/)
## Join the dbt Community
@@ -31,8 +34,8 @@ These select statements, or "models", form a dbt project. Models frequently buil
## Reporting bugs and contributing code
- Want to report a bug or request a feature? Let us know on [Slack](http://community.getdbt.com/), or open [an issue](https://github.com/dbt-labs/dbt-core/issues/new)
- Want to help us build dbt? Check out the [Contributing Guide](https://github.com/dbt-labs/dbt-core/blob/HEAD/CONTRIBUTING.md)
- Want to report a bug or request a feature? Let us know on [Slack](http://community.getdbt.com/), or open [an issue](https://github.com/dbt-labs/dbt/issues/new)
- Want to help us build dbt? Check out the [Contributing Guide](https://github.com/dbt-labs/dbt/blob/HEAD/CONTRIBUTING.md)
## Code of Conduct

View File

@@ -1,13 +0,0 @@
ignore:
- ".github"
- ".changes"
coverage:
status:
project:
default:
target: auto
threshold: 0.1% # Reduce noise by ignoring rounding errors in coverage drops
patch:
default:
target: auto
threshold: 80%

View File

@@ -1,2 +1 @@
recursive-include dbt/include *.py *.sql *.yml *.html *.md .gitkeep .gitignore
include dbt/py.typed

View File

@@ -1,39 +0,0 @@
<p align="center">
<img src="https://raw.githubusercontent.com/dbt-labs/dbt-core/fa1ea14ddfb1d5ae319d5141844910dd53ab2834/etc/dbt-core.svg" alt="dbt logo" width="750"/>
</p>
<p align="center">
<a href="https://github.com/dbt-labs/dbt-core/actions/workflows/main.yml">
<img src="https://github.com/dbt-labs/dbt-core/actions/workflows/main.yml/badge.svg?event=push" alt="CI Badge"/>
</a>
</p>
**[dbt](https://www.getdbt.com/)** enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
![architecture](https://raw.githubusercontent.com/dbt-labs/dbt-core/6c6649f9129d5d108aa3b0526f634cd8f3a9d1ed/etc/dbt-arch.png)
## Understanding dbt
Analysts using dbt can transform their data by simply writing select statements, while dbt handles turning these statements into tables and views in a data warehouse.
These select statements, or "models", form a dbt project. Models frequently build on top of one another dbt makes it easy to [manage relationships](https://docs.getdbt.com/docs/ref) between models, and [visualize these relationships](https://docs.getdbt.com/docs/documentation), as well as assure the quality of your transformations through [testing](https://docs.getdbt.com/docs/testing).
![dbt dag](https://raw.githubusercontent.com/dbt-labs/dbt-core/6c6649f9129d5d108aa3b0526f634cd8f3a9d1ed/etc/dbt-dag.png)
## Getting started
- [Install dbt](https://docs.getdbt.com/docs/installation)
- Read the [introduction](https://docs.getdbt.com/docs/introduction/) and [viewpoint](https://docs.getdbt.com/docs/about/viewpoint/)
## Join the dbt Community
- Be part of the conversation in the [dbt Community Slack](http://community.getdbt.com/)
- Read more on the [dbt Community Discourse](https://discourse.getdbt.com)
## Reporting bugs and contributing code
- Want to report a bug or request a feature? Let us know on [Slack](http://community.getdbt.com/), or open [an issue](https://github.com/dbt-labs/dbt-core/issues/new)
- Want to help us build dbt? Check out the [Contributing Guide](https://github.com/dbt-labs/dbt-core/blob/HEAD/CONTRIBUTING.md)
## Code of Conduct
Everyone interacting in the dbt project's codebases, issue trackers, chat rooms, and mailing lists is expected to follow the [dbt Code of Conduct](https://community.getdbt.com/code-of-conduct).

View File

@@ -1,60 +0,0 @@
# core/dbt directory README
## The following are individual files in this directory.
### compilation.py
### constants.py
### dataclass_schema.py
### deprecations.py
### exceptions.py
### flags.py
### helper_types.py
### hooks.py
### lib.py
### links.py
### logger.py
### main.py
### node_types.py
### profiler.py
### selected_resources.py
### semver.py
### tracking.py
### ui.py
### utils.py
### version.py
## The subdirectories will be documented in a README in the subdirectory
* adapters
* cli
* clients
* config
* context
* contracts
* deps
* docs
* events
* graph
* include
* parser
* task
* tests

View File

@@ -1,7 +0,0 @@
# N.B.
# This will add to the packages __path__ all subdirectories of directories on sys.path named after the package which effectively combines both modules into a single namespace (dbt.adapters)
# The matching statement is in plugins/postgres/dbt/__init__.py
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)

View File

@@ -1,30 +0,0 @@
# Adapters README
The Adapters module is responsible for defining database connection methods, caching information from databases, how relations are defined, and the two major connection types we have - base and sql.
# Directories
## `base`
Defines the base implementation Adapters can use to build out full functionality.
## `sql`
Defines a sql implementation for adapters that initially inherits the above base implementation and comes with some premade methods and macros that can be overwritten as needed per adapter. (most common type of adapter.)
# Files
## `cache.py`
Cached information from the database.
## `factory.py`
Defines how we generate adapter objects
## `protocol.py`
Defines various interfaces for various adapter objects. Helps mypy correctly resolve methods.
## `reference_keys.py`
Configures naming scheme for cache elements to be universal.

View File

@@ -1,7 +0,0 @@
# N.B.
# This will add to the packages __path__ all subdirectories of directories on sys.path named after the package which effectively combines both modules into a single namespace (dbt.adapters)
# The matching statement is in plugins/postgres/dbt/adapters/__init__.py
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)

View File

@@ -1,10 +0,0 @@
## Base adapters
### impl.py
The class `SQLAdapter` in [base/imply.py](https://github.com/dbt-labs/dbt-core/blob/main/core/dbt/adapters/base/impl.py) is a (mostly) abstract object that adapter objects inherit from. The base class scaffolds out methods that every adapter project usually should implement for smooth communication between dbt and database.
Some target databases require more or fewer methods--it all depends on what the warehouse's featureset is.
Look into the class for function-level comments.

View File

@@ -1,19 +1,14 @@
# these are all just exports, #noqa them so flake8 will be happy
# TODO: Should we still include this in the `adapters` namespace?
from dbt.contracts.connection import Credentials # noqa: F401
from dbt.adapters.base.meta import available # noqa: F401
from dbt.adapters.base.connections import BaseConnectionManager # noqa: F401
from dbt.adapters.base.relation import ( # noqa: F401
from dbt.contracts.connection import Credentials # noqa
from dbt.adapters.base.meta import available # noqa
from dbt.adapters.base.connections import BaseConnectionManager # noqa
from dbt.adapters.base.relation import ( # noqa
BaseRelation,
RelationType,
SchemaSearchMap,
)
from dbt.adapters.base.column import Column # noqa: F401
from dbt.adapters.base.impl import ( # noqa: F401
AdapterConfig,
BaseAdapter,
PythonJobHelper,
ConstraintSupport,
)
from dbt.adapters.base.plugin import AdapterPlugin # noqa: F401
from dbt.adapters.base.column import Column # noqa
from dbt.adapters.base.impl import AdapterConfig, BaseAdapter # noqa
from dbt.adapters.base.plugin import AdapterPlugin # noqa

View File

@@ -2,17 +2,16 @@ from dataclasses import dataclass
import re
from typing import Dict, ClassVar, Any, Optional
from dbt.exceptions import DbtRuntimeError
from dbt.exceptions import RuntimeException
@dataclass
class Column:
# Note: This is automatically used by contract code
# No-op conversions (INTEGER => INT) have been removed.
# Any adapter that wants to take advantage of "translate_type"
# should create a ClassVar with the appropriate conversions.
TYPE_LABELS: ClassVar[Dict[str, str]] = {
"STRING": "TEXT",
'STRING': 'TEXT',
'TIMESTAMP': 'TIMESTAMP',
'FLOAT': 'FLOAT',
'INTEGER': 'INT'
}
column: str
dtype: str
@@ -25,7 +24,7 @@ class Column:
return cls.TYPE_LABELS.get(dtype.upper(), dtype)
@classmethod
def create(cls, name, label_or_dtype: str) -> "Column":
def create(cls, name, label_or_dtype: str) -> 'Column':
column_type = cls.translate_type(label_or_dtype)
return cls(name, column_type)
@@ -40,14 +39,16 @@ class Column:
@property
def data_type(self) -> str:
if self.is_string():
return self.string_type(self.string_size())
return Column.string_type(self.string_size())
elif self.is_numeric():
return self.numeric_type(self.dtype, self.numeric_precision, self.numeric_scale)
return Column.numeric_type(self.dtype, self.numeric_precision,
self.numeric_scale)
else:
return self.dtype
def is_string(self) -> bool:
return self.dtype.lower() in ["text", "character varying", "character", "varchar"]
return self.dtype.lower() in ['text', 'character varying', 'character',
'varchar']
def is_number(self):
return any([self.is_integer(), self.is_numeric(), self.is_float()])
@@ -55,46 +56,33 @@ class Column:
def is_float(self):
return self.dtype.lower() in [
# floats
"real",
"float4",
"float",
"double precision",
"float8",
"double",
'real', 'float4', 'float', 'double precision', 'float8'
]
def is_integer(self) -> bool:
return self.dtype.lower() in [
# real types
"smallint",
"integer",
"bigint",
"smallserial",
"serial",
"bigserial",
'smallint', 'integer', 'bigint',
'smallserial', 'serial', 'bigserial',
# aliases
"int2",
"int4",
"int8",
"serial2",
"serial4",
"serial8",
'int2', 'int4', 'int8',
'serial2', 'serial4', 'serial8',
]
def is_numeric(self) -> bool:
return self.dtype.lower() in ["numeric", "decimal"]
return self.dtype.lower() in ['numeric', 'decimal']
def string_size(self) -> int:
if not self.is_string():
raise DbtRuntimeError("Called string_size() on non-string field!")
raise RuntimeException("Called string_size() on non-string field!")
if self.dtype == "text" or self.char_size is None:
if self.dtype == 'text' or self.char_size is None:
# char_size should never be None. Handle it reasonably just in case
return 256
else:
return int(self.char_size)
def can_expand_to(self, other_column: "Column") -> bool:
def can_expand_to(self, other_column: 'Column') -> bool:
"""returns True if this column can be expanded to the size of the
other column"""
if not self.is_string() or not other_column.is_string():
@@ -122,10 +110,12 @@ class Column:
return "<Column {} ({})>".format(self.name, self.data_type)
@classmethod
def from_description(cls, name: str, raw_data_type: str) -> "Column":
match = re.match(r"([^(]+)(\([^)]+\))?", raw_data_type)
def from_description(cls, name: str, raw_data_type: str) -> 'Column':
match = re.match(r'([^(]+)(\([^)]+\))?', raw_data_type)
if match is None:
raise DbtRuntimeError(f'Could not interpret data type "{raw_data_type}"')
raise RuntimeException(
f'Could not interpret data type "{raw_data_type}"'
)
data_type, size_info = match.groups()
char_size = None
numeric_precision = None
@@ -133,12 +123,12 @@ class Column:
if size_info is not None:
# strip out the parentheses
size_info = size_info[1:-1]
parts = size_info.split(",")
parts = size_info.split(',')
if len(parts) == 1:
try:
char_size = int(parts[0])
except ValueError:
raise DbtRuntimeError(
raise RuntimeException(
f'Could not interpret data_type "{raw_data_type}": '
f'could not convert "{parts[0]}" to an integer'
)
@@ -146,16 +136,18 @@ class Column:
try:
numeric_precision = int(parts[0])
except ValueError:
raise DbtRuntimeError(
raise RuntimeException(
f'Could not interpret data_type "{raw_data_type}": '
f'could not convert "{parts[0]}" to an integer'
)
try:
numeric_scale = int(parts[1])
except ValueError:
raise DbtRuntimeError(
raise RuntimeException(
f'Could not interpret data_type "{raw_data_type}": '
f'could not convert "{parts[1]}" to an integer'
)
return cls(name, data_type, char_size, numeric_precision, numeric_scale)
return cls(
name, data_type, char_size, numeric_precision, numeric_scale
)

View File

@@ -1,59 +1,25 @@
import abc
import os
from time import sleep
import sys
import traceback
# multiprocessing.RLock is a function returning this type
from multiprocessing.synchronize import RLock
from threading import get_ident
from typing import (
Any,
Dict,
Tuple,
Hashable,
Optional,
ContextManager,
List,
Type,
Union,
Iterable,
Callable,
Dict, Tuple, Hashable, Optional, ContextManager, List, Union
)
import agate
import dbt.exceptions
from dbt.contracts.connection import (
Connection,
Identifier,
ConnectionState,
AdapterRequiredConfig,
LazyHandle,
AdapterResponse,
Connection, Identifier, ConnectionState,
AdapterRequiredConfig, LazyHandle, AdapterResponse
)
from dbt.contracts.graph.manifest import Manifest
from dbt.adapters.base.query_headers import (
MacroQueryStringSetter,
)
from dbt.events import AdapterLogger
from dbt.events.functions import fire_event
from dbt.events.types import (
NewConnection,
ConnectionReused,
ConnectionLeftOpenInCleanup,
ConnectionLeftOpen,
ConnectionClosedInCleanup,
ConnectionClosed,
Rollback,
RollbackFailed,
)
from dbt.events.contextvars import get_node_info
from dbt.logger import GLOBAL_LOGGER as logger
from dbt import flags
from dbt.utils import cast_to_str
SleepTime = Union[int, float] # As taken by time.sleep.
AdapterHandle = Any # Adapter connection handle objects can be any class.
class BaseConnectionManager(metaclass=abc.ABCMeta):
@@ -69,10 +35,9 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
You must also set the 'TYPE' class attribute with a class-unique constant
string.
"""
TYPE: str = NotImplemented
def __init__(self, profile: AdapterRequiredConfig) -> None:
def __init__(self, profile: AdapterRequiredConfig):
self.profile = profile
self.thread_connections: Dict[Hashable, Connection] = {}
self.lock: RLock = flags.MP_CONTEXT.RLock()
@@ -91,14 +56,16 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
key = self.get_thread_identifier()
with self.lock:
if key not in self.thread_connections:
raise dbt.exceptions.InvalidConnectionError(key, list(self.thread_connections))
raise dbt.exceptions.InvalidConnectionException(
key, list(self.thread_connections)
)
return self.thread_connections[key]
def set_thread_connection(self, conn: Connection) -> None:
key = self.get_thread_identifier()
if key in self.thread_connections:
raise dbt.exceptions.DbtInternalError(
"In set_thread_connection, existing connection exists for {}"
raise dbt.exceptions.InternalException(
'In set_thread_connection, existing connection exists for {}'
)
self.thread_connections[key] = conn
@@ -137,148 +104,60 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
:return: A context manager that handles exceptions raised by the
underlying database.
"""
raise dbt.exceptions.NotImplementedError(
"`exception_handler` is not implemented for this adapter!"
)
raise dbt.exceptions.NotImplementedException(
'`exception_handler` is not implemented for this adapter!')
def set_connection_name(self, name: Optional[str] = None) -> Connection:
"""Called by 'acquire_connection' in BaseAdapter, which is called by
'connection_named', called by 'connection_for(node)'.
Creates a connection for this thread if one doesn't already
exist, and will rename an existing connection."""
conn_name: str
if name is None:
# if a name isn't specified, we'll re-use a single handle
# named 'master'
conn_name = 'master'
else:
if not isinstance(name, str):
raise dbt.exceptions.CompilerException(
f'For connection name, got {name} - not a string!'
)
assert isinstance(name, str)
conn_name = name
conn_name: str = "master" if name is None else name
# Get a connection for this thread
conn = self.get_if_exists()
if conn and conn.name == conn_name and conn.state == "open":
# Found a connection and nothing to do, so just return it
return conn
if conn is None:
# Create a new connection
conn = Connection(
type=Identifier(self.TYPE),
name=conn_name,
name=None,
state=ConnectionState.INIT,
transaction_open=False,
handle=None,
credentials=self.profile.credentials,
credentials=self.profile.credentials
)
conn.handle = LazyHandle(self.open)
# Add the connection to thread_connections for this thread
self.set_thread_connection(conn)
fire_event(
NewConnection(conn_name=conn_name, conn_type=self.TYPE, node_info=get_node_info())
)
else: # existing connection either wasn't open or didn't have the right name
if conn.state != "open":
conn.handle = LazyHandle(self.open)
if conn.name != conn_name:
orig_conn_name: str = conn.name or ""
conn.name = conn_name
fire_event(ConnectionReused(orig_conn_name=orig_conn_name, conn_name=conn_name))
return conn
if conn.name == conn_name and conn.state == 'open':
return conn
@classmethod
def retry_connection(
cls,
connection: Connection,
connect: Callable[[], AdapterHandle],
logger: AdapterLogger,
retryable_exceptions: Iterable[Type[Exception]],
retry_limit: int = 1,
retry_timeout: Union[Callable[[int], SleepTime], SleepTime] = 1,
_attempts: int = 0,
) -> Connection:
"""Given a Connection, set its handle by calling connect.
The calls to connect will be retried up to retry_limit times to deal with transient
connection errors. By default, one retry will be attempted if retryable_exceptions is set.
:param Connection connection: An instance of a Connection that needs a handle to be set,
usually when attempting to open it.
:param connect: A callable that returns the appropiate connection handle for a
given adapter. This callable will be retried retry_limit times if a subclass of any
Exception in retryable_exceptions is raised by connect.
:type connect: Callable[[], AdapterHandle]
:param AdapterLogger logger: A logger to emit messages on retry attempts or errors. When
handling expected errors, we call debug, and call warning on unexpected errors or when
all retry attempts have been exhausted.
:param retryable_exceptions: An iterable of exception classes that if raised by
connect should trigger a retry.
:type retryable_exceptions: Iterable[Type[Exception]]
:param int retry_limit: How many times to retry the call to connect. If this limit
is exceeded before a successful call, a FailedToConnectError will be raised.
Must be non-negative.
:param retry_timeout: Time to wait between attempts to connect. Can also take a
Callable that takes the number of attempts so far, beginning at 0, and returns an int
or float to be passed to time.sleep.
:type retry_timeout: Union[Callable[[int], SleepTime], SleepTime] = 1
:param int _attempts: Parameter used to keep track of the number of attempts in calling the
connect function across recursive calls. Passed as an argument to retry_timeout if it
is a Callable. This parameter should not be set by the initial caller.
:raises dbt.exceptions.FailedToConnectError: Upon exhausting all retry attempts without
successfully acquiring a handle.
:return: The given connection with its appropriate state and handle attributes set
depending on whether we successfully acquired a handle or not.
"""
timeout = retry_timeout(_attempts) if callable(retry_timeout) else retry_timeout
if timeout < 0:
raise dbt.exceptions.FailedToConnectError(
"retry_timeout cannot be negative or return a negative time."
)
if retry_limit < 0 or retry_limit > sys.getrecursionlimit():
# This guard is not perfect others may add to the recursion limit (e.g. built-ins).
connection.handle = None
connection.state = ConnectionState.FAIL
raise dbt.exceptions.FailedToConnectError("retry_limit cannot be negative")
try:
connection.handle = connect()
connection.state = ConnectionState.OPEN
return connection
except tuple(retryable_exceptions) as e:
if retry_limit <= 0:
connection.handle = None
connection.state = ConnectionState.FAIL
raise dbt.exceptions.FailedToConnectError(str(e))
logger.debug(
'Acquiring new {} connection "{}".'.format(self.TYPE, conn_name))
if conn.state == 'open':
logger.debug(
f"Got a retryable error when attempting to open a {cls.TYPE} connection.\n"
f"{retry_limit} attempts remaining. Retrying in {timeout} seconds.\n"
f"Error:\n{e}"
'Re-using an available connection from the pool (formerly {}).'
.format(conn.name)
)
else:
conn.handle = LazyHandle(self.open)
sleep(timeout)
return cls.retry_connection(
connection=connection,
connect=connect,
logger=logger,
retry_limit=retry_limit - 1,
retry_timeout=retry_timeout,
retryable_exceptions=retryable_exceptions,
_attempts=_attempts + 1,
)
except Exception as e:
connection.handle = None
connection.state = ConnectionState.FAIL
raise dbt.exceptions.FailedToConnectError(str(e))
conn.name = conn_name
return conn
@abc.abstractmethod
def cancel_open(self) -> Optional[List[str]]:
"""Cancel all open connections on the adapter. (passable)"""
raise dbt.exceptions.NotImplementedError(
"`cancel_open` is not implemented for this adapter!"
raise dbt.exceptions.NotImplementedException(
'`cancel_open` is not implemented for this adapter!'
)
@classmethod
@abc.abstractmethod
@abc.abstractclassmethod
def open(cls, connection: Connection) -> Connection:
"""Open the given connection on the adapter and return it.
@@ -288,7 +167,9 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
This should be thread-safe, or hold the lock if necessary. The given
connection should not be in either in_use or available.
"""
raise dbt.exceptions.NotImplementedError("`open` is not implemented for this adapter!")
raise dbt.exceptions.NotImplementedException(
'`open` is not implemented for this adapter!'
)
def release(self) -> None:
with self.lock:
@@ -308,10 +189,12 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
def cleanup_all(self) -> None:
with self.lock:
for connection in self.thread_connections.values():
if connection.state not in {"closed", "init"}:
fire_event(ConnectionLeftOpenInCleanup(conn_name=cast_to_str(connection.name)))
if connection.state not in {'closed', 'init'}:
logger.debug("Connection '{}' was left open."
.format(connection.name))
else:
fire_event(ConnectionClosedInCleanup(conn_name=cast_to_str(connection.name)))
logger.debug("Connection '{}' was properly closed."
.format(connection.name))
self.close(connection)
# garbage collect these connections
@@ -320,12 +203,16 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
@abc.abstractmethod
def begin(self) -> None:
"""Begin a transaction. (passable)"""
raise dbt.exceptions.NotImplementedError("`begin` is not implemented for this adapter!")
raise dbt.exceptions.NotImplementedException(
'`begin` is not implemented for this adapter!'
)
@abc.abstractmethod
def commit(self) -> None:
"""Commit a transaction. (passable)"""
raise dbt.exceptions.NotImplementedError("`commit` is not implemented for this adapter!")
raise dbt.exceptions.NotImplementedException(
'`commit` is not implemented for this adapter!'
)
@classmethod
def _rollback_handle(cls, connection: Connection) -> None:
@@ -333,52 +220,55 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
try:
connection.handle.rollback()
except Exception:
fire_event(
RollbackFailed(
conn_name=cast_to_str(connection.name),
exc_info=traceback.format_exc(),
node_info=get_node_info(),
)
logger.debug(
'Failed to rollback {}'.format(connection.name),
exc_info=True
)
@classmethod
def _close_handle(cls, connection: Connection) -> None:
"""Perform the actual close operation."""
# On windows, sometimes connection handles don't have a close() attr.
if hasattr(connection.handle, "close"):
fire_event(
ConnectionClosed(conn_name=cast_to_str(connection.name), node_info=get_node_info())
)
if hasattr(connection.handle, 'close'):
logger.debug(f'On {connection.name}: Close')
connection.handle.close()
else:
fire_event(
ConnectionLeftOpen(
conn_name=cast_to_str(connection.name), node_info=get_node_info()
)
)
logger.debug(f'On {connection.name}: No close available on handle')
@classmethod
def _rollback(cls, connection: Connection) -> None:
"""Roll back the given connection."""
if flags.STRICT_MODE:
if not isinstance(connection, Connection):
raise dbt.exceptions.CompilerException(
f'In _rollback, got {connection} - not a Connection!'
)
if connection.transaction_open is False:
raise dbt.exceptions.DbtInternalError(
f"Tried to rollback transaction on connection "
raise dbt.exceptions.InternalException(
f'Tried to rollback transaction on connection '
f'"{connection.name}", but it does not have one open!'
)
fire_event(Rollback(conn_name=cast_to_str(connection.name), node_info=get_node_info()))
logger.debug(f'On {connection.name}: ROLLBACK')
cls._rollback_handle(connection)
connection.transaction_open = False
@classmethod
def close(cls, connection: Connection) -> Connection:
if flags.STRICT_MODE:
if not isinstance(connection, Connection):
raise dbt.exceptions.CompilerException(
f'In close, got {connection} - not a Connection!'
)
# if the connection is in closed or init, there's nothing to do
if connection.state in {ConnectionState.CLOSED, ConnectionState.INIT}:
return connection
if connection.transaction_open and connection.handle:
fire_event(Rollback(conn_name=cast_to_str(connection.name), node_info=get_node_info()))
logger.debug('On {}: ROLLBACK'.format(connection.name))
cls._rollback_handle(connection)
connection.transaction_open = False
@@ -400,36 +290,17 @@ class BaseConnectionManager(metaclass=abc.ABCMeta):
@abc.abstractmethod
def execute(
self, sql: str, auto_begin: bool = False, fetch: bool = False, limit: Optional[int] = None
) -> Tuple[AdapterResponse, agate.Table]:
self, sql: str, auto_begin: bool = False, fetch: bool = False
) -> Tuple[Union[str, AdapterResponse], agate.Table]:
"""Execute the given SQL.
:param str sql: The sql to execute.
:param bool auto_begin: If set, and dbt is not currently inside a
transaction, automatically begin one.
:param bool fetch: If set, fetch results.
:param int limit: If set, limits the result set
:return: A tuple of the query status and results (empty if fetch=False).
:rtype: Tuple[AdapterResponse, agate.Table]
:return: A tuple of the status and the results (empty if fetch=False).
:rtype: Tuple[Union[str, AdapterResponse], agate.Table]
"""
raise dbt.exceptions.NotImplementedError("`execute` is not implemented for this adapter!")
def add_select_query(self, sql: str) -> Tuple[Connection, Any]:
"""
This was added here because base.impl.BaseAdapter.get_column_schema_from_query expects it to be here.
That method wouldn't work unless the adapter used sql.impl.SQLAdapter, sql.connections.SQLConnectionManager
or defined this method on <Adapter>ConnectionManager before passing it in to <Adapter>Adapter.
See https://github.com/dbt-labs/dbt-core/issues/8396 for more information.
"""
raise dbt.exceptions.NotImplementedError(
"`add_select_query` is not implemented for this adapter!"
)
@classmethod
def data_type_code_to_name(cls, type_code: Union[int, str]) -> str:
"""Get the string representation of the data type from the type_code."""
# https://peps.python.org/pep-0249/#type-objects
raise dbt.exceptions.NotImplementedError(
"`data_type_code_to_name` is not implemented for this adapter!"
raise dbt.exceptions.NotImplementedException(
'`execute` is not implemented for this adapter!'
)

File diff suppressed because it is too large Load Diff

View File

@@ -30,11 +30,9 @@ class _Available:
x.update(big_expensive_db_query())
return x
"""
def inner(func):
func._parse_replacement_ = parse_replacement
return self(func)
return inner
def deprecated(
@@ -59,14 +57,13 @@ class _Available:
The optional parse_replacement, if provided, will provide a parse-time
replacement for the actual method (see `available.parse`).
"""
def wrapper(func):
func_name = func.__name__
renamed_method(func_name, supported_name)
@wraps(func)
def inner(*args, **kwargs):
warn("adapter:{}".format(func_name))
warn('adapter:{}'.format(func_name))
return func(*args, **kwargs)
if parse_replacement:
@@ -74,7 +71,6 @@ class _Available:
else:
available_function = self
return available_function(inner)
return wrapper
def parse_none(self, func: Callable) -> Callable:
@@ -93,13 +89,15 @@ class AdapterMeta(abc.ABCMeta):
_available_: FrozenSet[str]
_parse_replacements_: Dict[str, Callable]
def __new__(mcls, name, bases, namespace, **kwargs) -> "AdapterMeta":
def __new__(mcls, name, bases, namespace, **kwargs):
# mypy does not like the `**kwargs`. But `ABCMeta` itself takes
# `**kwargs` in its argspec here (and passes them to `type.__new__`.
# I'm not sure there is any benefit to it after poking around a bit,
# but having it doesn't hurt on the python side (and omitting it could
# hurt for obscure metaclass reasons, for all I know)
cls = abc.ABCMeta.__new__(mcls, name, bases, namespace, **kwargs) # type: ignore
cls = abc.ABCMeta.__new__( # type: ignore
mcls, name, bases, namespace, **kwargs
)
# this is very much inspired by ABCMeta's own implementation
@@ -111,14 +109,14 @@ class AdapterMeta(abc.ABCMeta):
# collect base class data first
for base in bases:
available.update(getattr(base, "_available_", set()))
replacements.update(getattr(base, "_parse_replacements_", set()))
available.update(getattr(base, '_available_', set()))
replacements.update(getattr(base, '_parse_replacements_', set()))
# override with local data if it exists
for name, value in namespace.items():
if getattr(value, "_is_available_", False):
if getattr(value, '_is_available_', False):
available.add(name)
parse_replacement = getattr(value, "_parse_replacement_", None)
parse_replacement = getattr(value, '_parse_replacement_', None)
if parse_replacement is not None:
replacements[name] = parse_replacement

View File

@@ -1,17 +1,18 @@
from typing import List, Optional, Type
from dbt.adapters.base import Credentials
from dbt.exceptions import CompilationError
from dbt.exceptions import CompilationException
from dbt.adapters.protocol import AdapterProtocol
def project_name_from_path(include_path: str) -> str:
# avoid an import cycle
from dbt.config.project import PartialProject
partial = PartialProject.from_project_root(include_path)
from dbt.config.project import Project
partial = Project.partial_load(include_path)
if partial.project_name is None:
raise CompilationError(f"Invalid project at {include_path}: name not set!")
raise CompilationException(
f'Invalid project at {include_path}: name not set!'
)
return partial.project_name
@@ -22,14 +23,13 @@ class AdapterPlugin:
:param dependencies: A list of adapter names that this adapter depends
upon.
"""
def __init__(
self,
adapter: Type[AdapterProtocol],
credentials: Type[Credentials],
include_path: str,
dependencies: Optional[List[str]] = None,
) -> None:
dependencies: Optional[List[str]] = None
):
self.adapter: Type[AdapterProtocol] = adapter
self.credentials: Type[Credentials] = credentials

View File

@@ -5,17 +5,17 @@ from dbt.clients.jinja import QueryStringGenerator
from dbt.context.manifest import generate_query_header_context
from dbt.contracts.connection import AdapterRequiredConfig, QueryComment
from dbt.contracts.graph.nodes import ResultNode
from dbt.contracts.graph.compiled import CompileResultNode
from dbt.contracts.graph.manifest import Manifest
from dbt.exceptions import DbtRuntimeError
from dbt.exceptions import RuntimeException
class NodeWrapper:
def __init__(self, node) -> None:
def __init__(self, node):
self._inner_node = node
def __getattr__(self, name):
return getattr(self._inner_node, name, "")
return getattr(self._inner_node, name, '')
class _QueryComment(local):
@@ -24,10 +24,9 @@ class _QueryComment(local):
- the current thread's query comment.
- a source_name indicating what set the current thread's query comment
"""
def __init__(self, initial) -> None:
def __init__(self, initial):
self.query_comment: Optional[str] = initial
self.append: bool = False
self.append = False
def add(self, sql: str) -> str:
if not self.query_comment:
@@ -36,19 +35,21 @@ class _QueryComment(local):
if self.append:
# replace last ';' with '<comment>;'
sql = sql.rstrip()
if sql[-1] == ";":
if sql[-1] == ';':
sql = sql[:-1]
return "{}\n/* {} */;".format(sql, self.query_comment.strip())
return '{}\n/* {} */;'.format(sql, self.query_comment.strip())
return "{}\n/* {} */".format(sql, self.query_comment.strip())
return '{}\n/* {} */'.format(sql, self.query_comment.strip())
return "/* {} */\n{}".format(self.query_comment.strip(), sql)
return '/* {} */\n{}'.format(self.query_comment.strip(), sql)
def set(self, comment: Optional[str], append: bool):
if isinstance(comment, str) and "*/" in comment:
if isinstance(comment, str) and '*/' in comment:
# tell the user "no" so they don't hurt themselves by writing
# garbage
raise DbtRuntimeError(f'query comment contains illegal value "*/": {comment}')
raise RuntimeException(
f'query comment contains illegal value "*/": {comment}'
)
self.query_comment = comment
self.append = append
@@ -57,22 +58,20 @@ QueryStringFunc = Callable[[str, Optional[NodeWrapper]], str]
class MacroQueryStringSetter:
def __init__(self, config: AdapterRequiredConfig, manifest: Manifest) -> None:
def __init__(self, config: AdapterRequiredConfig, manifest: Manifest):
self.manifest = manifest
self.config = config
comment_macro = self._get_comment_macro()
self.generator: QueryStringFunc = lambda name, model: ""
self.generator: QueryStringFunc = lambda name, model: ''
# if the comment value was None or the empty string, just skip it
if comment_macro:
assert isinstance(comment_macro, str)
macro = "\n".join(
(
"{%- macro query_comment_macro(connection_name, node) -%}",
comment_macro,
"{% endmacro %}",
)
)
macro = '\n'.join((
'{%- macro query_comment_macro(connection_name, node) -%}',
comment_macro,
'{% endmacro %}'
))
ctx = self._get_context()
self.generator = QueryStringGenerator(macro, ctx)
self.comment = _QueryComment(None)
@@ -88,9 +87,9 @@ class MacroQueryStringSetter:
return self.comment.add(sql)
def reset(self):
self.set("master", None)
self.set('master', None)
def set(self, name: str, node: Optional[ResultNode]):
def set(self, name: str, node: Optional[CompileResultNode]):
wrapped: Optional[NodeWrapper] = None
if node is not None:
wrapped = NodeWrapper(node)

View File

@@ -1,29 +1,22 @@
from collections.abc import Hashable
from dataclasses import dataclass, field
from typing import Optional, TypeVar, Any, Type, Dict, Iterator, Tuple, Set, Union, FrozenSet
from dataclasses import dataclass
from typing import (
Optional, TypeVar, Any, Type, Dict, Union, Iterator, Tuple, Set
)
from dbt.contracts.graph.nodes import SourceDefinition, ManifestNode, ResultNode, ParsedNode
from dbt.contracts.graph.compiled import CompiledNode
from dbt.contracts.graph.parsed import ParsedSourceDefinition, ParsedNode
from dbt.contracts.relation import (
RelationType,
ComponentName,
HasQuoting,
FakeAPIObject,
Policy,
Path,
)
from dbt.exceptions import (
ApproximateMatchError,
DbtInternalError,
MultipleDatabasesNotAllowedError,
RelationType, ComponentName, HasQuoting, FakeAPIObject, Policy, Path
)
from dbt.exceptions import InternalException
from dbt.node_types import NodeType
from dbt.utils import filter_null_values, deep_merge, classproperty
import dbt.exceptions
Self = TypeVar("Self", bound="BaseRelation")
SerializableIterable = Union[Tuple, FrozenSet]
Self = TypeVar('Self', bound='BaseRelation')
@dataclass(frozen=True, eq=False, repr=False)
@@ -31,24 +24,10 @@ class BaseRelation(FakeAPIObject, Hashable):
path: Path
type: Optional[RelationType] = None
quote_character: str = '"'
# Python 3.11 requires that these use default_factory instead of simple default
# ValueError: mutable default <class 'dbt.contracts.relation.Policy'> for field include_policy is not allowed: use default_factory
include_policy: Policy = field(default_factory=lambda: Policy())
quote_policy: Policy = field(default_factory=lambda: Policy())
include_policy: Policy = Policy()
quote_policy: Policy = Policy()
dbt_created: bool = False
# register relation types that can be renamed for the purpose of replacing relations using stages and backups
# adding a relation type here also requires defining the associated rename macro
# e.g. adding RelationType.View in dbt-postgres requires that you define:
# include/postgres/macros/relations/view/rename.sql::postgres__get_rename_view_sql()
renameable_relations: SerializableIterable = field(default_factory=frozenset)
# register relation types that are atomically replaceable, e.g. they have "create or replace" syntax
# adding a relation type here also requires defining the associated replace macro
# e.g. adding RelationType.View in dbt-postgres requires that you define:
# include/postgres/macros/relations/view/replace.sql::postgres__get_replace_view_sql()
replaceable_relations: SerializableIterable = field(default_factory=frozenset)
def _is_exactish_match(self, field: ComponentName, value: str) -> bool:
if self.dbt_created and self.quote_policy.get_part(field) is False:
return self.path.get_lowered_part(field) == value.lower()
@@ -57,11 +36,11 @@ class BaseRelation(FakeAPIObject, Hashable):
@classmethod
def _get_field_named(cls, field_name):
for f, _ in cls._get_fields():
if f.name == field_name:
return f
for field, _ in cls._get_fields():
if field.name == field_name:
return field
# this should be unreachable
raise ValueError(f"BaseRelation has no {field_name} field!")
raise ValueError(f'BaseRelation has no {field_name} field!')
def __eq__(self, other):
if not isinstance(other, self.__class__):
@@ -70,18 +49,20 @@ class BaseRelation(FakeAPIObject, Hashable):
@classmethod
def get_default_quote_policy(cls) -> Policy:
return cls._get_field_named("quote_policy").default_factory()
return cls._get_field_named('quote_policy').default
@classmethod
def get_default_include_policy(cls) -> Policy:
return cls._get_field_named("include_policy").default_factory()
return cls._get_field_named('include_policy').default
def get(self, key, default=None):
"""Override `.get` to return a metadata object so we don't break
dbt_utils.
"""
if key == "metadata":
return {"type": self.__class__.__name__}
if key == 'metadata':
return {
'type': self.__class__.__name__
}
return super().get(key, default)
def matches(
@@ -90,19 +71,16 @@ class BaseRelation(FakeAPIObject, Hashable):
schema: Optional[str] = None,
identifier: Optional[str] = None,
) -> bool:
search = filter_null_values(
{
ComponentName.Database: database,
ComponentName.Schema: schema,
ComponentName.Identifier: identifier,
}
)
search = filter_null_values({
ComponentName.Database: database,
ComponentName.Schema: schema,
ComponentName.Identifier: identifier
})
if not search:
# nothing was passed in
raise dbt.exceptions.DbtRuntimeError(
"Tried to match relation, but no search path was passed!"
)
raise dbt.exceptions.RuntimeException(
"Tried to match relation, but no search path was passed!")
exact_match = True
approximate_match = True
@@ -110,14 +88,15 @@ class BaseRelation(FakeAPIObject, Hashable):
for k, v in search.items():
if not self._is_exactish_match(k, v):
exact_match = False
if str(self.path.get_lowered_part(k)).strip(self.quote_character) != v.lower().strip(
self.quote_character
):
approximate_match = False # type: ignore[union-attr]
if self.path.get_lowered_part(k) != v.lower():
approximate_match = False
if approximate_match and not exact_match:
target = self.create(database=database, schema=schema, identifier=identifier)
raise ApproximateMatchError(target, self)
target = self.create(
database=database, schema=schema, identifier=identifier
)
dbt.exceptions.approximate_relation_match(target, self)
return exact_match
@@ -130,13 +109,11 @@ class BaseRelation(FakeAPIObject, Hashable):
schema: Optional[bool] = None,
identifier: Optional[bool] = None,
) -> Self:
policy = filter_null_values(
{
ComponentName.Database: database,
ComponentName.Schema: schema,
ComponentName.Identifier: identifier,
}
)
policy = filter_null_values({
ComponentName.Database: database,
ComponentName.Schema: schema,
ComponentName.Identifier: identifier
})
new_quote_policy = self.quote_policy.replace_dict(policy)
return self.replace(quote_policy=new_quote_policy)
@@ -147,18 +124,16 @@ class BaseRelation(FakeAPIObject, Hashable):
schema: Optional[bool] = None,
identifier: Optional[bool] = None,
) -> Self:
policy = filter_null_values(
{
ComponentName.Database: database,
ComponentName.Schema: schema,
ComponentName.Identifier: identifier,
}
)
policy = filter_null_values({
ComponentName.Database: database,
ComponentName.Schema: schema,
ComponentName.Identifier: identifier
})
new_include_policy = self.include_policy.replace_dict(policy)
return self.replace(include_policy=new_include_policy)
def information_schema(self, view_name=None) -> "InformationSchema":
def information_schema(self, view_name=None) -> 'InformationSchema':
# some of our data comes from jinja, where things can be `Undefined`.
if not isinstance(view_name, str):
view_name = None
@@ -168,10 +143,10 @@ class BaseRelation(FakeAPIObject, Hashable):
info_schema = InformationSchema.from_relation(self, view_name)
return info_schema.incorporate(path={"schema": None})
def information_schema_only(self) -> "InformationSchema":
def information_schema_only(self) -> 'InformationSchema':
return self.information_schema()
def without_identifier(self) -> "BaseRelation":
def without_identifier(self) -> 'BaseRelation':
"""Return a form of this relation that only has the database and schema
set to included. To get the appropriately-quoted form the schema out of
the result (for use as part of a query), use `.render()`. To get the
@@ -181,7 +156,10 @@ class BaseRelation(FakeAPIObject, Hashable):
"""
return self.include(identifier=False).replace_path(identifier=None)
def _render_iterator(self) -> Iterator[Tuple[Optional[ComponentName], Optional[str]]]:
def _render_iterator(
self
) -> Iterator[Tuple[Optional[ComponentName], Optional[str]]]:
for key in ComponentName:
path_part: Optional[str] = None
if self.include_policy.get_part(key):
@@ -192,22 +170,27 @@ class BaseRelation(FakeAPIObject, Hashable):
def render(self) -> str:
# if there is nothing set, this will return the empty string.
return ".".join(part for _, part in self._render_iterator() if part is not None)
return '.'.join(
part for _, part in self._render_iterator()
if part is not None
)
def quoted(self, identifier):
return "{quote_char}{identifier}{quote_char}".format(
return '{quote_char}{identifier}{quote_char}'.format(
quote_char=self.quote_character,
identifier=identifier,
)
@classmethod
def create_from_source(cls: Type[Self], source: SourceDefinition, **kwargs: Any) -> Self:
def create_from_source(
cls: Type[Self], source: ParsedSourceDefinition, **kwargs: Any
) -> Self:
source_quoting = source.quoting.to_dict(omit_none=True)
source_quoting.pop("column", None)
source_quoting.pop('column', None)
quote_policy = deep_merge(
cls.get_default_quote_policy().to_dict(omit_none=True),
source_quoting,
kwargs.get("quote_policy", {}),
kwargs.get('quote_policy', {}),
)
return cls.create(
@@ -215,18 +198,18 @@ class BaseRelation(FakeAPIObject, Hashable):
schema=source.schema,
identifier=source.identifier,
quote_policy=quote_policy,
**kwargs,
**kwargs
)
@staticmethod
def add_ephemeral_prefix(name: str):
return f"__dbt__cte__{name}"
return f'__dbt__cte__{name}'
@classmethod
def create_ephemeral_from_node(
cls: Type[Self],
config: HasQuoting,
node: ManifestNode,
node: Union[ParsedNode, CompiledNode],
) -> Self:
# Note that ephemeral models are based on the name.
identifier = cls.add_ephemeral_prefix(node.name)
@@ -239,7 +222,7 @@ class BaseRelation(FakeAPIObject, Hashable):
def create_from_node(
cls: Type[Self],
config: HasQuoting,
node,
node: Union[ParsedNode, CompiledNode],
quote_policy: Optional[Dict[str, bool]] = None,
**kwargs: Any,
) -> Self:
@@ -253,27 +236,27 @@ class BaseRelation(FakeAPIObject, Hashable):
schema=node.schema,
identifier=node.alias,
quote_policy=quote_policy,
**kwargs,
)
**kwargs)
@classmethod
def create_from(
cls: Type[Self],
config: HasQuoting,
node: ResultNode,
node: Union[CompiledNode, ParsedNode, ParsedSourceDefinition],
**kwargs: Any,
) -> Self:
if node.resource_type == NodeType.Source:
if not isinstance(node, SourceDefinition):
raise DbtInternalError(
"type mismatch, expected SourceDefinition but got {}".format(type(node))
if not isinstance(node, ParsedSourceDefinition):
raise InternalException(
'type mismatch, expected ParsedSourceDefinition but got {}'
.format(type(node))
)
return cls.create_from_source(node, **kwargs)
else:
# Can't use ManifestNode here because of parameterized generics
if not isinstance(node, (ParsedNode)):
raise DbtInternalError(
f"type mismatch, expected ManifestNode but got {type(node)}"
if not isinstance(node, (ParsedNode, CompiledNode)):
raise InternalException(
'type mismatch, expected ParsedNode or CompiledNode but '
'got {}'.format(type(node))
)
return cls.create_from_node(config, node, **kwargs)
@@ -286,26 +269,16 @@ class BaseRelation(FakeAPIObject, Hashable):
type: Optional[RelationType] = None,
**kwargs,
) -> Self:
kwargs.update(
{
"path": {
"database": database,
"schema": schema,
"identifier": identifier,
},
"type": type,
}
)
kwargs.update({
'path': {
'database': database,
'schema': schema,
'identifier': identifier,
},
'type': type,
})
return cls.from_dict(kwargs)
@property
def can_be_renamed(self) -> bool:
return self.type in self.renameable_relations
@property
def can_be_replaced(self) -> bool:
return self.type in self.replaceable_relations
def __repr__(self) -> str:
return "<{} {}>".format(self.__class__.__name__, self.render())
@@ -348,10 +321,6 @@ class BaseRelation(FakeAPIObject, Hashable):
def is_view(self) -> bool:
return self.type == RelationType.View
@property
def is_materialized_view(self) -> bool:
return self.type == RelationType.MaterializedView
@classproperty
def Table(cls) -> str:
return str(RelationType.Table)
@@ -368,16 +337,12 @@ class BaseRelation(FakeAPIObject, Hashable):
def External(cls) -> str:
return str(RelationType.External)
@classproperty
def MaterializedView(cls) -> str:
return str(RelationType.MaterializedView)
@classproperty
def get_relation_type(cls) -> Type[RelationType]:
return RelationType
Info = TypeVar("Info", bound="InformationSchema")
Info = TypeVar('Info', bound='InformationSchema')
@dataclass(frozen=True, eq=False, repr=False)
@@ -386,16 +351,18 @@ class InformationSchema(BaseRelation):
def __post_init__(self):
if not isinstance(self.information_schema_view, (type(None), str)):
raise dbt.exceptions.CompilationError(
"Got an invalid name: {}".format(self.information_schema_view)
raise dbt.exceptions.CompilationException(
'Got an invalid name: {}'.format(self.information_schema_view)
)
@classmethod
def get_path(cls, relation: BaseRelation, information_schema_view: Optional[str]) -> Path:
def get_path(
cls, relation: BaseRelation, information_schema_view: Optional[str]
) -> Path:
return Path(
database=relation.database,
schema=relation.schema,
identifier="INFORMATION_SCHEMA",
identifier='INFORMATION_SCHEMA',
)
@classmethod
@@ -426,7 +393,9 @@ class InformationSchema(BaseRelation):
relation: BaseRelation,
information_schema_view: Optional[str],
) -> Info:
include_policy = cls.get_include_policy(relation, information_schema_view)
include_policy = cls.get_include_policy(
relation, information_schema_view
)
quote_policy = cls.get_quote_policy(relation, information_schema_view)
path = cls.get_path(relation, information_schema_view)
return cls(
@@ -448,7 +417,6 @@ class SchemaSearchMap(Dict[InformationSchema, Set[Optional[str]]]):
search for what schemas. The schema values are all lowercased to avoid
duplication.
"""
def add(self, relation: BaseRelation):
key = relation.information_schema_only()
if key not in self:
@@ -458,28 +426,31 @@ class SchemaSearchMap(Dict[InformationSchema, Set[Optional[str]]]):
schema = relation.schema.lower()
self[key].add(schema)
def search(self) -> Iterator[Tuple[InformationSchema, Optional[str]]]:
for information_schema, schemas in self.items():
def search(
self
) -> Iterator[Tuple[InformationSchema, Optional[str]]]:
for information_schema_name, schemas in self.items():
for schema in schemas:
yield information_schema, schema
yield information_schema_name, schema
def flatten(self, allow_multiple_databases: bool = False) -> "SchemaSearchMap":
def flatten(self, allow_multiple_databases: bool = False):
new = self.__class__()
# make sure we don't have multiple databases if allow_multiple_databases is set to False
if not allow_multiple_databases:
seen = {r.database.lower() for r in self if r.database}
if len(seen) > 1:
raise MultipleDatabasesNotAllowedError(seen)
dbt.exceptions.raise_compiler_error(str(seen))
for information_schema_name, schema in self.search():
path = {"database": information_schema_name.database, "schema": schema}
new.add(
information_schema_name.incorporate(
path=path,
quote_policy={"database": False},
include_policy={"database": False},
)
)
path = {
'database': information_schema_name.database,
'schema': schema
}
new.add(information_schema_name.incorporate(
path=path,
quote_policy={'database': False},
include_policy={'database': False},
))
return new

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