required 0.3.4.post1

A easy dependency validator

required: Easy multi-field validation

Required is a simple library which allows you to validate dependencies across multiple fields. The goal is to make writing things like Forms and Seralizers much easier by providing a declarative way to encode your complex validation logic.

Most Forms and Serializers limit you to doing validation on a single field, and then have one single clean method where you can do muti-field validation logic. The problem with this is that if you have a large number of optional fields which depend on each other, your validation code can quickly become unreadable, unmaintainable and non-reusable.

The aim of Required is to do the following:

• To have a declarative way to encode validation logic
• Allow you to maintain extremely complex multi field validation logic
• Allow you to reuse your validation logic easily
• Be flexible with what you want to validate

If this all sounds good. Read On!

Installation

Install using pip

pip install required

Quickstart

Lets start with a quick example.

You want to validate some business rules on some optional input parameters (for example to a API endpoint or function). They are start_date and end_date.

The business rules:

• start_date

  • Only valid with end_date
  • Must be after 2017
  • Must be before 2018

• end_date - filter events which start before this date

  • Only valid with start_date
  • Must be before 2018
  • Must be after start_date

Theses rules can be written with required as follows:

import datetime
from required import Requires, R

# start_date requirements
start_requires_end = Requires("start_date", "end_date")
start_after_2017 = Requires("start_date", R("start_date") > datetime.date(2017, 1, 1))
start_before_2018 = Requires("start_date", R("start_date") < datetime.date(2018, 1, 1))

# end_date requirements
end_requires_start = Requires("end_date", "start_date")
end_before_2018 = Requires("end_date", R("end_date") < datetime.date(2018, 1, 1))
end_after_start = Requires("end_date", R("end_date") > R("start_date"))

The above introduces the two important concepts of required; the Requires and R objects.

The Requires object is used to define pair-wise dependencies. It has two non-optional arguments, the first one is the target (key) of the constraint, and the second argument is the constraint itself. Requires("start_date", "end_date") means "start_date requires end_date to be present".

The R object acts as a placeholder for a future value. If you require a future value of end_date to be more than start_date, you would write it as R("end_date") > R("start_date). Any such expression can be used as the constraint for the Requires object.

The last step is simply summing all the Requires together in order to combine the rules:

# combine all the rules
all_rules = (
    start_requires_end + 
    start_after_2017 +
    start_before_2018 +
    end_requires_start +
    end_before_2018 +
    end_after_start
)

Once you have combined all the rules, you can simply call validate on the all_rules object with a dict of your data you want to validate.

data = {
    "start_date": datetime.date(2017, 10, 10),
    "end_date": datetime.date(2017, 10, 9),
}

all_rules.validate(data)  
# RequirementError: end_date requires end_date to be greater than start_date

The above not only tells you that the data was invalid, but which rule it broke. The following correct data passes validation:

data = {
    "start_date": datetime.date(2017, 10, 10),
    "end_date": datetime.date(2017, 10, 11),
}

all_rules.validate(data)  

Cookbook

The following shows some recipes for forming validation rules with the R object.

# Arithmetic on the `R` object follows normal maths rules.
R("x", R("x") + 1 < 1)
R("x", R("x") - R("y") == 1)

# A value `x` needs to be in an array
R("x", R("x").in_(array))

# The length of x must be 10
R("x", R("x").length() == 10)

# The length of x and y must be the same
R("x", R("x").length() == R("y").length())

# when x is present y must not be present
# from required import empty
R("x", R("y") == empty)

# x must be equal to the return value of a function
# this is useful if what you are checking is against
# is non-pure eg. current time

f = lambda x: 1
Requires("x", R("x") == Func(f, R("x")))

# the above can be used to ensure that a value is not in the past
R("start_date", R("start_date") > Func(datetime.now))

# Partial dependencies can be also specified with R objects

# x requires y when x is equal to 1
Requires(R("x") == 1, "y")

Contributing

If you want to contribute you are most welcome! This project is distributed under the MIT licence. It is tested using tox against Python 2.7 and 3.4+