stricto 0.0.2

Strict Dict (json) with schema validation embedded

stricto

Strict json structure with schema validation

The way to use is very simple, see Quickstart for a basic setup.

The main difference with jsonschema is that the schema is directly in types of data. You don't have to validate them.

Installation

pip install git+https://github.com/bwallrich/stricto

Quickstart

from stricto import Dict, Int, String, List

a=Dict({
    "name" : String(),
    "address" : Dict({
        "num" : Int(),
        "street" : String()
    }),
    "nicknames" : List( String() )
})


a.set({ 
    "name" : "Edward",
    "address" : {
        "num" : 22, 
        "street" : "acacia avenue"
    },
    "nicknames" : [ "Ed" ]
})


print(a.address.num) # 22
print(a.address) # { "num" : 22, "street" : "acacia avenue" }

a.name = 666 # -> raise a typeError (must be a string)

print (a) # { "name" : "Edward", ... }

a.nicknames.append(666) # -> raise a typeError (must be a string)
a.nicknames.append("Eddy")
a.nickname[1] # -> Eddy

b=a # b is a reference on a
c=a.copy() # c is a different object : c is a copy

c == b # return True (you can test and do operators directly on objects)
b.nicknames.pop()
c == b # return False

Basic types

All basic class from python are implemented in stricto.

python class	type in stricto
bool	Bool()
int	Int()
float	Float()
string	String()
list	List()
dict	Dict()
	In()

# example
from stricto import Dict, Int

a = Int()
a.set(22) # -> ok
a.set(23.1) # raise an error
a.set("the number of the beast") # raise an error

# WARNING
a = "the number of the beast" # works ! the affectation of "a" change. Now it is a string. This is python.

# Inside a Dict().
test=Dict({
    "a" : Int()
})

test.a = 22 # -> ok
test.a = 23.1 # raise an error
test.a = "the number of the beast" # raise an error

json

use .get_value() to extract a dict from a Dict and do the json.dumps like usual.

# example
from stricto import Int, List, String, Dict, Error
import json

model={
    "b" : Int(),
    "e" : List( String())
}
a=Dict(model)
b=Dict(model)
a.set({ "b" : 1, "e" : [ "aa", "bb"]})

sa = json.dumps(a.get_value()) # json dumps 
b.set( json.loads(sa) ) 
b == a # return True

Types and options

All types

available options for all types ares :

Option	Default	Description
notNone=True|False	False	cannot be None
required=True|False	False	similar to notNone
description="whatever you want"	None	a description of this object
default=666	None	the default value
in=[ 1, 2, 3, 5 ]|func	None	the value must be one of those elements
union=[ 1, 2, 3, 5 ]|func	None	similar to in
transform=func	None	a function to transform the value before setting it
constraint=func	None	a constraints to check the value before setting it
constraints=[func]	None	a list of constraints to check the value before setting it
onchange=func	None	a onchange function trigged when the value change
onChange=func	None	similar to onchange
set=func	None	a read only value, calculated from other .See set or compute function
compute=func	None	similar to set
exists=func	True	a function to say if the object "exists", depending on values from other attributs. See exists for details

See functions for mor details and examples how to use them.

Int()

Int( options ) is for integer.

Int( options ) use generic options.

available specific options for Int() ares :

Option	Default	Description
min=	None	minimum value
minimum=21	None	similar to min
max=99	None	maximum value
maximum=99	None	similar to max=99

# example
from stricto import Dict, Int, String

client = Dict{
    "age" : Int( min=21, max=120)
}

client.age = 12  # -> raise an error
client.age = 120  # -> Ok

newAge = client.age+1 # -> raise an Error ( > max ) newAge is implicitly an Int( min=21, max=120))
newAge = 1+client.age # -> Ok (newAge is implicitly an int)

String()

String( options ) is for strings.

String( options ) use generic options.

available specific options for Int() ares :

Option	Default	Description
pattern=regexp	None	must match this regexp
patterns=[reg1, reg2]	None	must match all regexps
regexp=	None	similar to pattern

Examples

a=String( pattern='^A' )
a.set('Foo')        # -> raise an error
a.set('AZERTY')     # OK

# list of regexp
a=String( patterns=[ '^A', r'.*Z$' ] )
a.set('Allo')        # -> raise an error
a.set('AtoZ')        # OK

# function return a regexp
a=String( pattern=lambda self, value, root : r'.*Z$')
a.set('Allo')        # -> raise an error
a.set('AtoZ')        # OK

In()

In( [ Array of types ] ) is not a type, but an union of diffferent types.

In( options ) use generic options.

# example
from stricto import In, Int, String

a = In( [ Int(), String() ] )

a.set("hello") # -> OK
a.count('h') # -> return 1

a.set(12) # -> OK
a.bit_length() # -> return 4
a.count('h') # -> return None

a.set(3.14) # -> raise an error

Functions

a func can return a value to adapt the result. It can bee a lambda too.

transform

Please see transform function

# example
from stricto import Dict, Int, String

def upper(value, o):
    """
    transform the value into upper

    value : the current value given ("worldcompagny" in this example).
    o     : the full object
    """
    return value.upper()

company=Dict({
    "name" : String( transform=upper ),
})

company.name="worldcompagny"
print(company.name) # -> "WORLDCOMPAGNY"

set or compute

# example
from stricto import Dict, Int, String

a=Dict({
    "b" : Int( default = 0, set=lambda o: o.c+1 ),
    "d" : Int( default = 0, set=lambda o: o.b+1 ),
    "c" : Int( ),
})

# "b" and "d" cannot be modified by hand. the are recalculated every time another value 
# change in the Dict.

a.b = 3 # -> raise an error

a.c = 2
print(a.b) # -> 3
print(a.d) # -> 4

constraints

# example
from stricto import Dict, Int, String



def check_pair(value, o): # pylint: disable=unused-argument
    """
    return true if pair
    """
    return not value % 2

a=Dict({
    "b" : Int( default = 0, constraint=check_pair ),        # check before setting
    "d" : Int( constraint=lambda value, o : not value % 2 ), # same as above, with a lambda
    "c" : Int( constraints=[ check_pair ] ),                # A list of constraints
})

a.b = 2 # OK
a.c = 3 # -> raise an error

onchange

# example
from stricto import Dict, Int, String



def change_test(old_value, value, o): # pylint: disable=unused-argument
    """
    just a change option
    old_value   -> The previous value
    value       -> the new one
    o           -> the root object = a in our example
    """
    print(f"The value of b as changed from {old_value} to {value}")

a=Dict({
    "b" : Int( default = 0, onchange=change_test )
})

a.b = 2     # -> output "The value of b as changed from 0 to 2"
a.b = 3-1   # -> nothing displayed

exists

A function wich must return True|False to say if this key exists.

# example
from stricto import Dict, Int, String

def check_if_female(value, o):
    """
    return true if Female
    """
    if o.gender == "Male":
        return False
    return True

cat=Dict({
    "name" : String(),
    "gender" : String( default = 'Male', in=[ 'Male', 'Female' ]),
    "female_infos" : Dict(
        {
        "number_of_litter" : Int(default=0, required=True)
        # ... some other attributes

    }, exists=check_if_female )
})

a.set({ "name" : "Felix", "gender" : "Male" }
a.female_infos   # -> None
a.female_infos.number_of_litter = 2 # -> Raise an Error

a.gender = "Female"
a.female_infos.number_of_litter = 2 # -> Ok
a.female_infos # -> { "number_of_litter" : 2 }

Tests

python -m unittest