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Display all details about a specific MLEM Object from an existing MLEM project.


usage: mlem pprint [-p <path>] [--rev <commitish>] [-f]
                   [--json] [-h]

  path             Path to object


All MLEM objects can be printed to view their metadata. This includes generic information such as requirements, type of object, hash, size, as well as object specific information such as methods for a model or reader for data.

Since only one specific object is printed, a PATH to the specific MLEM object is always required.


  • -p <path>, --project <path> - Path to MLEM project [default: (none)]
  • --rev <commitish> - Repo revision to use [default: (none)]
  • -f, --follow-links - If specified, follow the link to the actual object.
  • --json - Output as json
  • -h, --help - Show this message and exit.

Example: Showing local model

$ mlem pprint rf
⏳️ Loading meta from rf.mlem
{'artifacts': {'data': {'hash': 'a61a1fa54893dcebe6fa448df81a1418',
                        'size': 163651,
                        'type': 'dvc',
                        'uri': 'rf'}},
 'model_type': {'methods': {'predict': {'args': [{'name': 'data',
                                                  'type_': {'columns': ['sepal '
                                                                        'length '

Example: Showing remote data

$ mlem pprint https://github.com/iterative/example-mlem-get-started/iris.csv --rev 4-pack
⏳️ Loading meta from https://github.com/iterative/example-mlem-get-started/tree/4-pack/data/iris.csv.mlem
{'artifacts': {'data': {'hash': '45109f850511f9474665f2c26f4c79f3',
                        'size': 2470,
                        'uri': 'iris.csv'}},
 'data_type': {'columns': ['sepal length (cm)',
                           'sepal width (cm)',
                           'petal length (cm)',
                           'petal width (cm)'],
               'dtypes': ['float64', 'float64', 'float64', 'float64'],
               'index_cols': [],
               'type': 'dataframe'},
 'object_type': 'data',
 'reader': {'data_type': {'columns': ['sepal length (cm)',
                                      'sepal width (cm)',
                                      'petal length (cm)',
                                      'petal width (cm)'],
                          'dtypes': ['float64',
                          'index_cols': [],
                          'type': 'dataframe'},
            'format': 'csv',
            'type': 'pandas'},
 'requirements': [{'module': 'pandas', 'version': '1.4.2'}]}

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