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Welcome to Cerberus — Cerberus is a lightweight and extensible data validation library for Python

N The watch-dog of Hades, whose duty it was to guard the entrance; everybody, sooner or later, had to go there, and nobody wanted to carry off the entrance. -. Ambrose Bierce, The Devil’s Dictionary. Cerberus provides powerful yet simple and lightweight data validation functionality out of the box and is designed to be easily extensible, allowing for custom validation. It has no dependencies and is thoroughly tested from Python 2.6 up to 3.5, PyPy and PyPy3. Then you simply invoke the.

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Welcome to Cerberus — Cerberus is a lightweight and extensible data validation library for Python | docs.python-cerberus.org Reviews
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N The watch-dog of Hades, whose duty it was to guard the entrance; everybody, sooner or later, had to go there, and nobody wanted to carry off the entrance. -. Ambrose Bierce, The Devil’s Dictionary. Cerberus provides powerful yet simple and lightweight data validation functionality out of the box and is designed to be easily extensible, allowing for custom validation. It has no dependencies and is thoroughly tested from Python 2.6 up to 3.5, PyPy and PyPy3. Then you simply invoke the.
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Welcome to Cerberus — Cerberus is a lightweight and extensible data validation library for Python | docs.python-cerberus.org Reviews

https://docs.python-cerberus.org

N The watch-dog of Hades, whose duty it was to guard the entrance; everybody, sooner or later, had to go there, and nobody wanted to carry off the entrance. -. Ambrose Bierce, The Devil’s Dictionary. Cerberus provides powerful yet simple and lightweight data validation functionality out of the box and is designed to be easily extensible, allowing for custom validation. It has no dependencies and is thoroughly tested from Python 2.6 up to 3.5, PyPy and PyPy3. Then you simply invoke the.

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Authors — Cerberus is a lightweight and extensible data validation library for Python

http://docs.python-cerberus.org/en/stable/authors.html

Cerberus is written and maintained by Nicola Iarocci and various contributors:. Nicola Iarocci nicola @. Bryan W. Weber. Harro van der Klauw. Cerberus is a lightweight and extensible data validation library for Python. Receive updates on new releases and upcoming projects. Cerberus @ Stack Overflow. Cerberus @ Google Groups. Cerberus @ Nicola Iarocci. Errors and Error Handling. Upgrading to Cerberus 1.0. Previous: Upgrading to Cerberus 1.0. 2012-2016, Nicola Iarocci. Page source.

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Extending Cerberus — Cerberus is a lightweight and extensible data validation library for Python

http://docs.python-cerberus.org/en/stable/customize.html

Though you can use functions in conjunction with the. Rules, you can easily extend the. While the function-based style is more suitable for special and one-off uses, a custom class leverages these possibilities:. Custom rules can be defined with constrains in a schema. Extending the available type. Use additional contextual data. The references in schemas to these custom methods can use space characters instead of underscores, e.g. Is an alias for. Rule to our validation schema:. Must be an odd number.

3

Errors & Error Handling — Cerberus is a lightweight and extensible data validation library for Python

http://docs.python-cerberus.org/en/stable/errors.html

Errors and Error Handling. Errors can be evaluated via Python interfaces or be processed to different output formats with error handlers. Error handlers will return different output via the. Property of a validator after the processing of a document. The error handler to be used can be passed as keyword-argument. The following handlers are available:. This is the default. An error is represented as. That has the following properties:. The path within the schema. That rule’s constraint. This tuple contain...

4

Validation Schemas — Cerberus is a lightweight and extensible data validation library for Python

http://docs.python-cerberus.org/en/stable/schemas.html

A validation schema is a mapping. Schema keys are the keys allowed in the target dictionary. Schema values express the rules that must be matched by the corresponding target values. In the example above we define a target dictionary with only one key,. Which is expected to be a string not longer than 10 characters. Something like. Would validate, while something like. By default all keys in a document are optional unless the required. Rule is set for a key. Objects and bind them to the. Foo: {allowed: mu...

5

Cerberus Installation — Cerberus is a lightweight and extensible data validation library for Python

http://docs.python-cerberus.org/en/stable/install.html

This part of the documentation covers the installation of Cerberus. The first step to using any software package is getting it properly installed. Cerberus is on PyPI. So all you need to do is:. Cerberus is actively developed on GitHub, where the code is always available. If you want to work with the development version, there are two ways: you can either let. Pull in the development version, or you can tell it to operate on a git checkout. Either way, virtualenv is recommended. And you’re done! 2012-201...

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Trying to merge the best research in Text Analytics with practical and commercial perspectives. I have recently come back from my first ever Python Conference (PyCon), and in fact, my first ever generalistic development conference. This was quite a new experience as I am used to either academic (e.g., ECIR. Or data-centric (e.g., Strata. Conferences. PyConUK was quite different in many ways to the events I am used to, and I could not be happier I have attended it. The main reason is that Marco Bonzanini.

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Welcome to Cerberus — Cerberus is a lightweight and extensible data validation library for Python

N The watch-dog of Hades, whose duty it was to guard the entrance; everybody, sooner or later, had to go there, and nobody wanted to carry off the entrance. -. Ambrose Bierce, The Devil’s Dictionary. Cerberus provides powerful yet simple and lightweight data validation functionality out of the box and is designed to be easily extensible, allowing for custom validation. It has no dependencies and is thoroughly tested from Python 2.6 up to 3.5, PyPy and PyPy3. Then you simply invoke the.

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