maykin-json-logic-py 0.9.0

Build complex rules, serialize them as JSON, and execute them in Python

This parser accepts JsonLogic rules and executes them in Python.

This is a fork of json-logic-py by nadir.izr, which is a Python porting of the GitHub project by jwadhams for JavaScript: json-logic-js.

The JsonLogic format is designed to allow you to share rules (logic) between front-end and back-end code (regardless of language difference), even to store logic along with a record in a database. JsonLogic is documented extensively at JsonLogic.com, including examples of every supported operation and a place to try out rules in your browser.

The same format can also be executed in PHP by the library json-logic-php

Examples

Simple

from json_logic import jsonLogic
jsonLogic( { "==" : [1, 1] } )
# True

This is a simple test, equivalent to 1 == 1. A few things about the format:

1. The operator is always in the “key” position. There is only one key per JsonLogic rule.

2. The values are typically an array.

3. Each value can be a string, number, boolean, array (non-associative), or null

Compound

Here we’re beginning to nest rules.

jsonLogic(
  {"and" : [
    { ">" : [3,1] },
    { "<" : [1,3] }
  ] }
)
# True

In an infix language (like Python) this could be written as:

( (3 > 1) and (1 < 3) )

Data-Driven

Obviously these rules aren’t very interesting if they can only take static literal data. Typically jsonLogic will be called with a rule object and a data object. You can use the var operator to get attributes of the data object:

jsonLogic(
  { "var" : ["a"] }, # Rule
  { a : 1, b : 2 }   # Data
)
# 1

If you like, we support syntactic sugar on unary operators to skip the array around values:

jsonLogic(
  { "var" : "a" },
  { a : 1, b : 2 }
)
# 1

You can also use the var operator to access an array by numeric index:

jsonLogic(
  {"var" : 1 },
  [ "apple", "banana", "carrot" ]
)
# "banana"

Here’s a complex rule that mixes literals and data. The pie isn’t ready to eat unless it’s cooler than 110 degrees, and filled with apples.

rules = { "and" : [
  {"<" : [ { "var" : "temp" }, 110 ]},
  {"==" : [ { "var" : "pie.filling" }, "apple" ] }
] }

data = { "temp" : 100, "pie" : { "filling" : "apple" } }

jsonLogic(rules, data)
# True

Dates

You can use the date operator to include dates in the json logic. The dates are internally converted to datetime.date objects, and then the comparison is performed.

rule = {"<=": [{"date": {"var": "testDate"}}, {"date": "2021-01-01"}]}
data = {"testDate": "2020-01-01"}

jsonLogic(rule, data)
# True

The operator {"today": []} gets the current date. It is also possible to add/subtract years to a date. This makes use of relativedelta from dateutils.

rule = {"-": [{"date": "2021-01-01"}, {"years": 18}]}

jsonLogic(rule)
# date(2003, 1, 1)

Datetimes

You can use the datetime operator to include datetimes in the json logic. The datetimes are internally converted to datetime.datetime objects, and then the comparison is performed.

rule = {
    "<=": [
        {"datetime": {"var": "testDatetime"}},
        {"datetime": "2022-12-01T10:00:00.000+02:00"},
    ]
}
data = {"testDatetime": "2022-11-01T10:00:00.000+02:00"}

jsonLogic(rule, data)
# True

Always and Never

Sometimes the rule you want to process is “Always” or “Never.” If the first parameter passed to jsonLogic is a non-object, non-associative-array, it is returned immediately.

#Always
jsonLogic(True, data_will_be_ignored);
# True

#Never
jsonLogic(False, i_wasnt_even_supposed_to_be_here);
# False

Installation

The best way to install this library is via PIP:

pip install json-logic

If that doesn’t suit you, and you want to manage updates yourself, the entire library is self-contained in json_logic.py and you can download it straight into your project as you see fit.

curl -O https://raw.githubusercontent.com/nadirizr/json-logic-py/master/json_logic.py