Add alias support to model URI parsing and disallow reserved aliases #8164
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Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
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harupy
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harupy
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harupy
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harupy
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Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
BenWilson2
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harupy
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harupy
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harupy
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harupy
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| suffix = m.group("suffix") if "suffix" in m.groupdict() else None | ||
| alias = m.group("alias") if "alias" in m.groupdict() else None | ||
| if ( | ||
| (model_name is None or model_name == "") |
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Suggested change
| (model_name is None or model_name == "") |
I think this line can be removed because the model_name group is not optional.
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Yeah I replaced it with model_name.strip() to make sure the name isn't just whitespace
harupy
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Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
smurching
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Basically LGTM, just had minor comments. Thanks @arpitjasa-db !
Signed-off-by: Arpit Jasapara <arpit.jasapara@databricks.com>
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This was referenced May 16, 2023
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Related Issues/PRs
#8001
#8055
#8094
What changes are proposed in this pull request?
This PR adds alias support to model URI parsing and disallows reserved aliases for
latestand version numbers (v###).How is this patch tested?
Does this PR change the documentation?
Release Notes
Is this a user-facing change?
This PR adds alias support to model URI parsing and disallows reserved aliases for
latestand version numbers (v###).What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes