Validation and parsing library
Project description
Trafaret
========
Trafaret is validation library with support to convert data structures.
Sample of usage::
import datetime
import trafaret as t
date = t.Dict(year=t.Int, month=t.Int, day=t.Int) >> (lambda d: datetime.datetime(**d))
assert task.check({'year': 2012, 'month': 1, 'day': 12}) == datetime.datetime(2012, 1, 12)
``t.Dict`` creates new dict structure validator with three ``t.Int`` elements.
``>>`` operation adds lambda function to the converters of given checker.
Obviously every checker have any default converter, but when you use ``>>`` or ``.append``,
you disable default converter.
DataError
-----------------------
Exception class that used in library. Exception hold errors in ``error`` attribute.
For simple checkers it will be just a string. For nested structures it will be `dict`
instance.
Trafaret
--------
Base class for trafarets. Use it to make new trafarets.
In derrived classes you need to implement `_check` or `_check_val`
methods. `_check_val` must return value, `_check` must return `None` on success.
You can implement `converter` method, if you want to convert value somehow, but
want to make free for developer to apply his own converters to raw data.
Type
----
Just instantitate it with any class, like int, float, str::
>>> Type(int).check(4)
4
Any
---
Will match any element.
Or
--
Get other converters as args, and this samples are equivalent::
>>> Or(t.Int, t.Null).check(None)
None
>>> (t.Int | t.Null).check(5)
5
Null
----
Value must be `None`.
Simple checkers
---------------
``Bool``
``Float``
``Int``
``Atom`` - value must be exactly equal to Atom first arg - ``t.Atom('this_key_must_be_this')``.
String
------
``regex`` param - will return ``re.Match`` object. Default converter will return ``match.group()``.
``Email`` and ``URL`` just provide regular expressions and a bit of logic for IDNA domains.
List
----
Just List of elements of one type. In converter you will get ``list`` instance of converted elements.
Dict
----
Dict include named params. You can use for keys plain strings and ``Key`` instances.
Methods:
``allow_extra(*names)`` : where ``names`` can be key names or ``*`` to allow any additional keys.
``make_optional(*names)`` : where ``names`` can be key names or ``*`` to make all options optional.
Key
...
Special class to create dict keys. Parameters are:
* name - key name
* default - default if key is not present
* optional - if True allow to not provide arg
* to_name - instead of key name will be returned this key
You can provide ``to_name`` with ``>>`` operation::
Key('javaStyleData') >> 'plain_cool_data'
Mapping
-------
Enum
----
This checker check that value one from provided. Like::
>>> Enum(1, 2, 'error').check('2')
2
Callable
--------
Call
----
Forward
-------
This checker is container for any checker, that you can provide later.
To provide container use ``provide`` method or ``<<`` operation::
>> node = Forward()
>> node << Dict(name=String, children=List[node])
guard
-----
Decorator
GuardValidationError
....................
Derived from DataError.
========
Trafaret is validation library with support to convert data structures.
Sample of usage::
import datetime
import trafaret as t
date = t.Dict(year=t.Int, month=t.Int, day=t.Int) >> (lambda d: datetime.datetime(**d))
assert task.check({'year': 2012, 'month': 1, 'day': 12}) == datetime.datetime(2012, 1, 12)
``t.Dict`` creates new dict structure validator with three ``t.Int`` elements.
``>>`` operation adds lambda function to the converters of given checker.
Obviously every checker have any default converter, but when you use ``>>`` or ``.append``,
you disable default converter.
DataError
-----------------------
Exception class that used in library. Exception hold errors in ``error`` attribute.
For simple checkers it will be just a string. For nested structures it will be `dict`
instance.
Trafaret
--------
Base class for trafarets. Use it to make new trafarets.
In derrived classes you need to implement `_check` or `_check_val`
methods. `_check_val` must return value, `_check` must return `None` on success.
You can implement `converter` method, if you want to convert value somehow, but
want to make free for developer to apply his own converters to raw data.
Type
----
Just instantitate it with any class, like int, float, str::
>>> Type(int).check(4)
4
Any
---
Will match any element.
Or
--
Get other converters as args, and this samples are equivalent::
>>> Or(t.Int, t.Null).check(None)
None
>>> (t.Int | t.Null).check(5)
5
Null
----
Value must be `None`.
Simple checkers
---------------
``Bool``
``Float``
``Int``
``Atom`` - value must be exactly equal to Atom first arg - ``t.Atom('this_key_must_be_this')``.
String
------
``regex`` param - will return ``re.Match`` object. Default converter will return ``match.group()``.
``Email`` and ``URL`` just provide regular expressions and a bit of logic for IDNA domains.
List
----
Just List of elements of one type. In converter you will get ``list`` instance of converted elements.
Dict
----
Dict include named params. You can use for keys plain strings and ``Key`` instances.
Methods:
``allow_extra(*names)`` : where ``names`` can be key names or ``*`` to allow any additional keys.
``make_optional(*names)`` : where ``names`` can be key names or ``*`` to make all options optional.
Key
...
Special class to create dict keys. Parameters are:
* name - key name
* default - default if key is not present
* optional - if True allow to not provide arg
* to_name - instead of key name will be returned this key
You can provide ``to_name`` with ``>>`` operation::
Key('javaStyleData') >> 'plain_cool_data'
Mapping
-------
Enum
----
This checker check that value one from provided. Like::
>>> Enum(1, 2, 'error').check('2')
2
Callable
--------
Call
----
Forward
-------
This checker is container for any checker, that you can provide later.
To provide container use ``provide`` method or ``<<`` operation::
>> node = Forward()
>> node << Dict(name=String, children=List[node])
guard
-----
Decorator
GuardValidationError
....................
Derived from DataError.
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