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Update doc requirements and guide to install pandoc #10348
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CONTRIBUTING.md
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([dev-env-setup.sh](https://github.com/mlflow/mlflow/blob/master/dev/dev-env-setup.sh)), | ||
but if you manually installing dependencies, | ||
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- Pip package: run `pip install pandoc --upgrade` |
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Is this really required?
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I don't have the python pandoc but can build the docs.
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Hmm good catch, I just tried same and suceeded building now. Don't quite remember where it came from.... tho I think it's good to remove. Supposedly the library is just python binding of it's functionaliry.
CONTRIBUTING.md
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- Pip package: run `pip install pandoc --upgrade` | ||
- Haskel project: please follow [official instruction](https://pandoc.org/installing.html). | ||
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Also check you are the version of your installation via `pandoc --version`. If using Mac |
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Any version requirement?
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2.2.1 or above, will add
dev/dev-env-setup.sh
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@@ -130,7 +130,7 @@ if [ -z "$pyenv_exist" ]; then | |||
sudo apt-get update -y | |||
sudo apt-get install -y make build-essential libssl-dev zlib1g-dev \ | |||
libbz2-dev libreadline-dev libsqlite3-dev wget curl llvm \ | |||
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev | |||
libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev pandoc \ |
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what's the version installed by apt-get?
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yea it's older than 2, just found these lines: https://github.com/mlflow/mlflow/blame/master/mlflow/R/mlflow/Dockerfile.dev#L14-L18
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Can we use wget
and dpkg
to make sure pandoc is not old?
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yup, just pushed the new revision with updated script:)
dev/dev-env-setup.sh
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echo "Homebrew is required to install $1 on MacOS. Installing in your home directory." | ||
bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" | ||
fi | ||
echo "Updating brew and installing pyenv..." |
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do we need installing pyenv
?
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auch, will fix
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LGTM
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dev/dev-env-setup.sh
installs many tools = harder to succeed. We might need to consider how to make it easier to resume.
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For pandoc, I think it's fine to just document it on CONTRIBUTING.md
.
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Agreed, I think one way is to split it to a few logical steps and create scripts for each. Created backlog item for this.
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LGTM!
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com>
Signed-off-by: B-Step62 <yuki.watanabe@databricks.com> Signed-off-by: Yuki Watanabe <31463517+B-Step62@users.noreply.github.com> Co-authored-by: Ben Wilson <39283302+BenWilson2@users.noreply.github.com> Signed-off-by: swathi <konakanchi.swathi@gmail.com>
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Pandoc is not required for building docs, not R docs only. This changes modify requirements and set-up scripts, as well as CONTRIBUTION.md.
The set up script is tested on both Mac and Linux (Ubuntu).
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
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/gateway
: AI Gateway service, Gateway client APIs, third-party Gateway integrationsarea/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/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change
- The PR will be mentioned in the "Breaking Changes" 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