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Don't use pip in R install_mlflow function #4898

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merged 1 commit into from
Oct 14, 2021

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@apurva-koti apurva-koti commented Oct 14, 2021

Signed-off-by: apurva-koti apurva.koti@databricks.com

What changes are proposed in this pull request?

The install_mlflow function is currently broken as it uses conda and pip in conjunction to install dependencies. Using conda and pip together isn't great and in this case a version conflict between a default conda-forge library and an attempted uninstallation by pop is causing the function to error out. It's unclear why this was configured in the first place, so this PR sets pip to FALSE.

How is this patch tested?

Manual + Databricks testing

Release Notes

Is this a user-facing change?

  • No. You can skip the rest of this section.
  • Yes. Give a description of this change to be included in the release notes for MLflow users.

(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger change.)

What component(s), interfaces, languages, and integrations does this PR affect?

Components

  • area/artifacts: Artifact stores and artifact logging
  • area/build: Build and test infrastructure for MLflow
  • area/docs: MLflow documentation pages
  • area/examples: Example code
  • area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
  • area/models: MLmodel format, model serialization/deserialization, flavors
  • area/projects: MLproject format, project running backends
  • area/scoring: MLflow Model server, model deployment tools, Spark UDFs
  • area/server-infra: MLflow Tracking server backend
  • area/tracking: Tracking Service, tracking client APIs, autologging

Interface

  • area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
  • area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
  • area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
  • area/windows: Windows support

Language

  • language/r: R APIs and clients
  • language/java: Java APIs and clients
  • language/new: Proposals for new client languages

Integrations

  • integrations/azure: Azure and Azure ML integrations
  • integrations/sagemaker: SageMaker integrations
  • integrations/databricks: Databricks integrations

How should the PR be classified in the release notes? Choose one:

  • rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
  • rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
  • rn/feature - A new user-facing feature worth mentioning in the release notes
  • rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
  • rn/documentation - A user-facing documentation change worth mentioning in the release notes

Signed-off-by: apurva-koti <apurva.koti@databricks.com>
@github-actions github-actions bot added language/r R APIs and clients rn/none List under Small Changes in Changelogs. labels Oct 14, 2021
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lgtm!

@apurva-koti apurva-koti merged commit 6fcb4d6 into mlflow:master Oct 14, 2021
@apurva-koti apurva-koti deleted the no-conda-pip branch October 14, 2021 21:50
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