Build complex rules, serialize them as JSON, and execute them in Python
Project description
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:
The operator is always in the “key” position. There is only one key per JsonLogic rule.
The values are typically an array.
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
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