ckanext-transmute 1.1.5

Converts a dataset based on a specific schema

ckanext-transmute

The extension helps to validate and converts a dataset based on a specific schema.

Working with transmute

ckanext-transmute provides an action tsm_transmute It helps us to transmute data with the provided convertion scheme. The action doesn't change the original data, but creates a new data dict. There are two mandatory arguments - data and schema. data is a data dict you have and schema helps you to validate/change data in it.

Example: We have a data dict:

{
            "title": "Test-dataset",
            "email": "[e-mail]",
            "metadata_created": "",
            "metadata_modified": "",
            "metadata_reviewed": "",
            "resources": [
                {
                    "title": "test-res",
                    "extension": "xml",
                    "web": "https://stackoverflow.com/",
                    "sub-resources": [
                        {
                            "title": "sub-res",
                            "extension": "csv",
                            "extra": "should-be-removed",
                        }
                    ],
                },
                {
                    "title": "test-res2",
                    "extension": "csv",
                    "web": "https://stackoverflow.com/",
                },
            ],
        }

And we want to achieve this:

{
            "name": "test-dataset",
            "email": "[e-mail]",
            "metadata_created": datetime.datetime(2022, 2, 3, 15, 54, 26, 359453),
            "metadata_modified": datetime.datetime(2022, 2, 3, 15, 54, 26, 359453),
            "metadata_reviewed": datetime.datetime(2022, 2, 3, 15, 54, 26, 359453),
            "attachments": [
                {
                    "name": "test-res",
                    "format": "XML",
                    "url": "https://stackoverflow.com/",
                    "sub-resources": [{"name": "SUB-RES", "format": "CSV"}],
                },
                {
                    "name": "test-res2",
                    "format": "CSV",
                    "url": "https://stackoverflow.com/",
                },
            ],
        }

Then, our schema must be something like that:

{
        "root": "Dataset",
        "types": {
            "Dataset": {
                "fields": {
                    "title": {
                        "validators": [
                            "tsm_string_only",
                            "tsm_to_lowercase",
                            "tsm_name_validator",
                        ],
                        "map": "name",
                    },
                    "resources": {
                        "type": "Resource",
                        "multiple": True,
                        "map": "attachments",
                    },
                    "metadata_created": {
                        "validators": ["tsm_isodate"],
                        "default": "2022-02-03T15:54:26.359453",
                    },
                    "metadata_modified": {
                        "validators": ["tsm_isodate"],
                        "default_from": "metadata_created",
                    },
                    "metadata_reviewed": {
                        "validators": ["tsm_isodate"],
                        "replace_from": "metadata_modified",
                    },
                }
            },
            "Resource": {
                "fields": {
                    "title": {
                        "validators": ["tsm_string_only"],
                        "map": "name",
                    },
                    "extension": {
                        "validators": ["tsm_string_only", "tsm_to_uppercase"],
                        "map": "format",
                    },
                    "web": {
                        "validators": ["tsm_string_only"],
                        "map": "url",
                    },
                    "sub-resources": {
                        "type": "Sub-Resource",
                        "multiple": True,
                    },
                },
            },
            "Sub-Resource": {
                "fields": {
                    "title": {
                        "validators": ["tsm_string_only", "tsm_to_uppercase"],
                        "map": "name",
                    },
                    "extension": {
                        "validators": ["tsm_string_only", "tsm_to_uppercase"],
                        "map": "format",
                    },
                    "extra": {
                        "remove": True,
                    },
                }
            },
        },
    }

There is an example of schema with nested types. The root field is mandatory, it's must contain a main type name, from which the scheme starts. As you can see, Dataset type contains Resource type which contans Sub-Resource.

Transmutators

There are few default transmutators you can use in your schema. Of course, you can define a custom transmutator with the CKAN IValidators interface.

• tsm_name_validator - Wrapper over CKAN default name_validator validator
• tsm_to_lowercase - Casts string value to a lowercase
• tsm_to_uppercase - Casts string value to a uppercase
• tsm_string_only - Validates if field.value is string
• tsm_isodate - Wrapper over CKAN default isodate validator. Mutates an iso-like string to datetime object
• tsm_to_string - Casts a field.value to str
• tsm_get_nested - Allows you to pick up a value from a nested structure. Example:

data = "title_translated": [
    {"nested_field": {"en": "en title", "ar": "العنوان ar"}},
]

schema = ...
    "title": {
        "replace_from": "title_translated",
        "validators": [
            ["tsm_get_nested", 0, "nested_field", "en"],
            "tsm_to_uppercase",
        ],
    },
    ...

This will take a value for a title field from title_translated field. Because title_translated is an array with nested objects, we are using the tsm_get_nested transmutator to achieve the value from it.

The default transmutator must receive at least one mandatory argument - field object. Field contains few properties: field_name, value and type.

There is a possibility to provide more arguments to a validator like in tsm_get_nested. For this use a nested array with first item transmutator and other - arguments to it.

Installation

To install ckanext-transmute:

1. Activate your CKAN virtual environment, for example:

   . /usr/lib/ckan/default/bin/activate

2. Clone the source and install it on the virtualenv

   git clone https://github.com/mutantsan/ckanext-transmute.git cd ckanext-transmute pip install -e . pip install -r requirements.txt

3. Add transmute to the ckan.plugins setting in your CKAN config file (by default the config file is located at /etc/ckan/default/ckan.ini).

4. Restart CKAN. For example if you've deployed CKAN with Apache on Ubuntu:

   sudo service apache2 reload

Developer installation

To install ckanext-transmute for development, activate your CKAN virtualenv and do:

git clone https://github.com/mutantsan/ckanext-transmute.git
cd ckanext-transmute
python setup.py develop
pip install -r dev-requirements.txt

Tests

I've used TDD to write this extension, so if you changing something be sure that all the tests are valid. To run the tests, do:

pytest --ckan-ini=test.ini

License

AGPL