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Validation and serialization library for Python designed to be used with JSON REST frameworks

License: MIT License

Python 100.00%

cleancat's Introduction

CleanCat

Validation library for Python designed to be used with JSON REST frameworks

Basic example in Flask

class JobApplication(Schema):
    first_name = String()
    last_name = String()
    email = Email()
    urls = List(URL(default_scheme='http://'))

@app.route('/job_application', methods=['POST'])
def test_view():
    schema = JobApplication(request.json)
    try:
        data = schema.full_clean()
    except SchemaValidationError:
        return jsonify({'field-errors': schema.field_errors, 'errors': schema.errors }), 400
        
    # Now "data" has the validated data

cleancat's People

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jnrowe-retired-forks domenicosolazzo gordol saurabh1e whelp-inc mbdaryanto tinvaan

cleancat's Issues

PhoneNumber schema

Rather than having to rely on a Mongoengine field for validating phone numbers, this should be handled at the schema level

Make error messaging consistent

Some of the error messages start with "Value" (e.g. "Value cannot be changed." or "Value must be of int type.") whereas others start with "The value" (e.g. "The value must be at least X characters long.").

Discovered via #42

Email validation accepts invalid addresses

See #36 for some examples of invalid email addresses that CleanCat considers valid.

DateTime should always return a `datetime.datetime`

Currently, DateTime will return a datetime.date for ISO8601 dates like 2000-01-01 and a datetime.datetime for ISO8601 datetimes like 2000-01-01T00:00:00Z. This is not expected behavior. Date should return a date, DateTime should return a datetime, and something like Union(Date, Datetime) should do what the current DateTime does.

Provide CleanCat schema with a context

There should be a way to provide a CleanCat schema not only with the data we want to validate, but also the context in which we want to validate it.

Currently, you have to rely on global variables (like Flask's g and request) to determine the context you're working in, which is bad for readability, testing, separation of concerns, etc.

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