Metadata-Version: 1.1
Name: yschema
Version: 1.0.0
Summary: A YAML/JSON/dictionary schema validator with terse schema definitions
Home-page: https://bitbucket.org/trlandet/yschema
Author: Tormod Landet
Author-email: tormod@landet.net
License: Apache 2.0
Description: YSchema
        =======
        
        YSchema is a terse and simple schema format with a reference validator
        implementation for YAML, JSON and other dictionary based data structures.
        
        YSchema is quite minimal (in terms of lines of code) and is continuously tested
        against a set of of valid and invalid example data (see the ``examples``
        directory). The code works nicely for its intended purpose, but may not be the
        most powerful or popular, even if it does what it was intended for very well.
        The main assumption (at least for now) is that all keys are strings without
        whitespace.
        
        YSchema is written in Python (v. 3) and validates dictionaries containing basic
        datatypes like strings, ints, floats, lists and nested dictionaries. The schema
        is also a dictionary, so both the data and the schema can be written in Python,
        JSON, YAML, TOML, ... formats. YSchema cannot validate all possible YAML / JSON
        data, in fact it cannot even validate its own schema files since those use
        significant white space in dictionary keys to describe expected data types and
        whether the data is required or not.
        
        To install the YSchema Python library along with the ``yschema`` command line
        program run:
        
        .. code:: bash
        
            python3 -m pip install -U yschema
        
        Consider using a virtual environment or adding ``--user`` to the ``pip`` command
        if you do not want to install into the system's site-packages directory. PS: You
        may also want to look at older and more established schema and validators such
        as Yamale_ or json-schema_ in case those serve your needs better.
        
        .. _Yamale: https://github.com/23andMe/Yamale
        .. _json-schema: http://json-schema.org
        
        
        .. contents::
        
        
        Introduction to YSchema
        -----------------------
        
        A simple example schema:
        
        .. code:: yaml
        
            # There must be a key "name" that maps to a string
            required name: str
            
            # There can be an integer age, but it is not required
            optional age: int
            
            # The optional height must be above 0
            optional height: float(min_val=0)
        
        To validate this, first load the schema above into a dictionary, then load the
        data to validate into another dictionary, and finally run:
        
        .. code:: python
        
            import yschema
            
            # possibly loaded from json or yaml or just a plain old dict
            schema = my_load_schema_function()
            data_dict = {'name': 'Tormod'}
            
            yschema.validate(data_dict, schema_dict)
        
        If the function does not raise ``yschema.ValidationError`` then the data is
        valid according to the given schema. You can also use the ``yschema`` command
        to validate YAML files from the command line.
        
        A more complicated example, showing constants and nested dictionaries:
        
        .. code:: yaml
        
            # Example of a constant that can be used in validation functions
            constant minimum_string_length: 5
            
            # A sub-dictionary
            type Whale: 
                # The name is a string of a given minimum length
                required name: str(min_len=minimum_string_length)
                
                # The length must be between 0 and 500 meters
                optional length: float(min_val=0, max_val=500.0)
            
            required whales: list(type=Whale)
        
        The above schema validates data like this:
        
        .. code:: yaml
        
            whales:
              - name: Unknown Whale
              - name: Enormous Whale
                length: 200.0
        
        Note that when working with aliases and types the order of the keys in the
        dictionary starts to matter. Either use a Python 3.6 or later, or load your
        data into an OrderedDict. For PyYAML this means:
        
        .. code:: python
        
            from collections import OrderedDict
            import yaml
            yaml.add_constructor(yaml.resolver.BaseResolver.DEFAULT_MAPPING_TAG,
                                 lambda loader, node: OrderedDict(loader.construct_pairs(node)))
        
        More advanced features
        ----------------------
        
        **Built in types**: the following types are implemented. Optional parameters
        are listed below each type:
        
        * Any
        * bool
        * str
            - min_len
            - max_len
            - equals - e.g. ``str(equals='Hi!')`` or matching one of several
              pissibilities with ``str(equals=('a', 'b', 'c'))``
            - prefix
        * int
            - min_val
            - max_val
            - equals - e.g. ``int(equals=3)`` or ``int(equals=(2, 4, 6))``
        * float
            - min_val
            - max_val
            - equals - e.g. ``float(equals=3.2)`` or ``float(equals=(2.1, 4.4))``
        * list
            - min_len
            - max_len
            - type - e.g. ``list(type=int)`` or ``list(type=Whale)``
        * one_of
            - types - e.g. ``one_of(types=(int, str))`` or
              ``one_of(types=(str(prefix='Moby'), Whale))``
        * any_of
            - types - see ``one_of`` (``any_of`` matches if any of the types match, 
              ``one_of`` requires exactly one match)
        
        **Alias**: you can give an alias to avoid typing the same type definition over
        and over again:
        
        .. code:: yaml
        
            alias Cat: one_of(types=(HouseCat, Tiger, Lynx))
            alias Cats: list(type=Cat)
        
        **Glob**: you can allow undefined keys by using a glob. The following will
        validate OK for all documents
        
        .. code:: yaml
        
            optional *: Any
        
        **Inherit**: a sub-schema introduced by ``type`` can contain a key ``inherit``
        with the name of a previously defined sub-schema to avoid repeating 
        definitions that are shared among several types:
        
        .. code:: yaml
        
            type MeshBase:
                optional move: list(type=str)
                optional sort_order: list(type=int)
                optional mesh_file: str
            type MeshDolfinFile:
                inherit: MeshBase
                required type: str(equals=('XML', 'XDMF', 'HDF5'))
                required mesh_file: str
                optional facet_region_file: str
            type MeshMeshio:
                inherit: MeshBase
                required type: str(equals='meshio')
                required mesh_file: str
                optional meshio_type: str
            required mesh: one_of(types=(MeshMeshio, MeshDolfinFile))
         
        
        Releases
        --------
        
        Version 1.0.0 - June 7. 2018
        ............................
        
        Completed v 1.0 implementation goals. The YSchema language is powerful enough to
        express most of what I wanted for validating Ocallaris_ input files. The code
        base is decently tested (using the fantastic CircleCI service) and a command
        line tool is also included for validating YAML files from the shell.
        
        There may not be a large number of additional releases if no more features are
        found to be necessary for the author's uses. It is relatively easy to add new
        type validators from user code, but feel free to submit a pull request if you
        are finding YSchema useful and have implemented some general purpose validators.
        YSchema does not intend to compete with complex and more fully featured schema
        languages like json-schema_.
        
        .. _Ocellaris: https://bitbucket.org/trlandet/ocellaris
        
        Copyright and license
        ---------------------
        
        YSchema is copyright Tormod Landet, 2018. YSchema is licensed under the Apache
        2.0 license, a permissive free software license compatible with version 3 of
        the GNU GPL. See the file LICENSE for the details.
        
Keywords: yaml json schema validation
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Pre-processors
Classifier: Topic :: Software Development :: Quality Assurance
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
