Skip to main content

A practical system for organizing validation rules

Project description

pylidator

pylidator is a validation framework for Python projects.

Many business systems have complex validation rules. This library provides a method of organizing those rules for convenience and testability. A validator method is written for each rule (or group of rules), which simply returns a list of errors if any are found.

Validators

A validator method checks the validity of one or a closely-related group of assertions about a piece of data. They all look basically like this:

@pylidator.validator(of="child")
def child_is_valid(child):
    messages = []

    if child['age'] >= 18:
        messages.append({"age": "Child is too old."}

    if child['type'] != 'human':
        messages.append({"type": "Only humans allowed."}

    return messages

(Alternately, you can return just a dict of {field: message} items.)

Validating Something

Once you have authored some @pylidator.validator methods as above, you can use them! Try this:

objs = {
    'name': "Mrs. Teacher's Class",
    'children': [
        {'name': "Joe", 'age': 15, 'type': 'human'},
        {'name': "Sarah", 'age': 19, 'type': 'human'},
    ]
}

# Define a provider
def _provide_child(obj):
    for i, c in enumerate(obj['children']):
        yield c, {"description": "Child {}".format(i)}

providers = {"child": _provide_something}  # "child" matches the `of` argument of the `@pylidator.validator`.
ret = pylidator.validate(objs, {"ERROR": [some_values_are_valid]}, providers=providers)

child_is_valid will be invoked once per child, and any that return something truthy will show as an ERROR.

Function Reference

@pylidator.validator decorates any method that will be passed to pylidator.validate, and takes several optional parameters:

@pylidator.validator(of, requires=None, affects=None)

`of` specifies what provider the validator should use.   The `validate` call needs an item in `providers`
     that matches `of`.
`requires` (optional) can add additional context items, such as the current time or other services that can supply
     data or settings to the validator.  The requirement is fulfilled by passing `extra_context` to the `validate`
     call, containing any items that are used in a `requires`.
`affects` (optional) is simply passed through to results.  It can be used as guidance for UI/error reporting for
     helping to resolve any resultant errors.
pylidator.validate(obj, validators=None, providers=None, extra_context=None, field_name_mapper=None, validation_type=None)

`obj` is the top-level object requiring validation.
`validators` is a dict of {level: list of `@pylidator.validator` objects}
`providers` is a dict of {of: func that takes obj and returns an iterable of some subobjects}
`extra_context` is a dict of other data that can be injected into `@pylidator.validator` with `requires`.
`field_name_mapper` is a string->string func that converts field names given in returned errors into verbose names.
`validation_type` is added as documentation into the error object.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pylidator-1.0.3.tar.gz (9.6 kB view hashes)

Uploaded Source

Built Distribution

pylidator-1.0.3-py2.py3-none-any.whl (10.8 kB view hashes)

Uploaded Python 2 Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page