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An utility library that generates OARepo required data model files from a JSON specification file

Project description

OARepo model builder

Work in progress

A library and command-line tool to generate invenio model project from a single model file.

CLI Usage

To use the model builder client, you first have to install the model builder somewhere.

Installing model builder as dev dependency

Initialize your new project with poetry create and then add model builder with poetry add --dev oarepo-model-builder. This is the simplest solution but has a disadvantage - as poetry always installs dev dependencies in build & test, but not in production, in your development environment you will have extra packages installed. If you happen to use them, you will break your production build.

Installing model builder in a separate virtualenv

Create a separate virtualenv and install model builder into it:

python3.10 -m venv .venv-builder
(source .venv-builder/bin/activate; pip install -U pip setuptools wheel; pip install oarepo-model-builder)

Then for ease of use add the following aliases

alias oarepo-compile-model="$PWD/.venv-builder/bin/oarepo-compile-model"
alias oarepo-model-builder-pip="$PWD/.venv-builder/bin/pip"

Use the oarepo-model-builder-pip if you need to install plugins to the model builder.

Running model builder

oarepo-compile-model model.yaml

will compile the model.yaml into the current directory. Options:

  --output-directory <dir> Output directory where the generated files will be
                           placed. Defaults to "."
  --package <name>         Package into which the model is generated. If not
                           passed, the name of the current directory,
                           converted into python package name, is used.
  --set <name=value>       Overwrite option in the model file. 
                           Example --set settings.elasticsearch.keyword-ignore-above=20
  -v                       Increase the verbosity. This option can be used
                           multiple times.
  --config <filename>      Load a config file and replace parts of the model
                           with it. The config file can be a json, yaml or a
                           python file. If it is a python file, it is
                           evaluated with the current model stored in the
                           "oarepo_model" global variable and after the
                           evaluation all globals are set on the model.
  --isort / --skip-isort   Call isort on generated sources (default: yes)
  --black / --skip-black   Call black on generated sources (default: yes)

Model file

A model is a json/yaml file including description of the model and processing settings. Example:

version: 1.0.0
oarepo:use: invenio
model:
  properties:
    metadata:
      properties:
        title:
          type: fulltext+keyword
          oarepo:ui:
            label: Title
          oarepo:mapping:
          # anything in here will be put into the mapping file
          # fulltext+keyword type automatically creates "type: text" 
          # with subfield 'keyword' of type keyword
settings:
  package: uct.titled_model 

Model file structure

A model is a json/yaml file with the following structure:

version: 1.0.0
model:
  properties:
    title:
      type: fulltext+keyword
settings:
  <generic settings here>
  python: ...
  elasticsearch: ...
plugins: ...

There might be more sections (documentation etc.), but only the settings, model and plugins are currently processed.

"model" section

This section is described in model.md

"settings" section

The settings section contains various configuration settings. In most cases you want to set only the package option as in above because all other settings are derived from it. Even the package option might be omitted - in this case the package name will be the last component of the output directory (with dashes converted to underscores).

The rest of the settings are described in model-generic-settings.md

Advanced use cases might require to modify the python settings or elasticsearch settings (for example, to define custom analyzers).

"plugins" section

See plugins and the processing order for details.

Builder as a library (using via API)

To invoke the builder programmatically, see using the API.

Writing custom plugins

See writing plugins if you want to extend the building process with your own plugins.

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