Specify function operations is JSON
Project description
json-operations
Specify complex conditional operations in JSON. The conditional operations can be run securely against a JSON value (Python dictionary) and will return a boolean.
from json_operations import execute
operations = [">", ["key", "items"], 30]
data1 = {
"items": 31
}
data2 = {
"items": 29
}
execute(operations, data1) # -> True
execute(operations, data2) # -> False
Security
All operations are safe (no use of eval). It's good to enforce a length limit if you are taking input from an untrusted source.
API
execute
Run the json operations against a data dictionary. Return True/False. Can raise a JsonOperationError if operations are invalid or keys don't exist
from json_operations import execute
execute(<operations>, <data_dictionary>) -> bool
get_json_schema
Returns the JSON Schema for json operations. This is useful for validating operations before running them
from json_operations import get_json_schema
get_json_schema() -> Dict
get_keys
Returns the keys inside json operations. This is useful for getting a list of keys necessary for the json operations and validating that all keys are inside the data dictionary
from json_operations import get_keys
get_keys(<operations>) -> List[Dict]
# [{"name": "key1", "type": "number", "index": 0}, ...]
Operators
== (Equal operator)
Check whether one value equal to another.
Syntax
["==", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = ["==", ["key", "items"], 30]
data1 = {
"items": 30
}
data2 = {
"items": 31
}
execute(operations, data1) # -> True
execute(operations, data2) # -> False
!= (Not equal operator)
Check whether one value is not equal to another.
Syntax
["!=", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = ["!=", ["key", "items"], 30]
data1 = {
"items": 30
}
data2 = {
"items": 31
}
execute(operations, data1) # -> False
execute(operations, data2) # -> True
> (Greater than operator)
Check whether one value is greater than another.
Syntax
[">", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = [">", ["key", "items"], 30]
data1 = {
"items": 31
}
data2 = {
"items": 29
}
execute(operations, data1) # -> True
execute(operations, data2) # -> False
>= (Greater than or equal operator)
Check whether one value is greater than or equal to another.
Syntax
[">=", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = [">=", ["key", "items"], 30]
data1 = {
"items": 30
}
data2 = {
"items": 29
}
execute(operations, data1) # -> True
execute(operations, data2) # -> False
< (Less than operator)
Check whether one value is less than another.
Syntax
["<", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = ["<", ["key", "items"], 30]
data1 = {
"items": 31
}
data2 = {
"items": 29
}
execute(operations, data1) # -> False
execute(operations, data2) # -> True
< (Less than or equal operator)
Check whether one value is less or equal to than another.
Syntax
["<=", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = ["<=", ["key", "items"], 30]
data1 = {
"items": 31
}
data2 = {
"items": 30
}
execute(operations, data1) # -> False
execute(operations, data2) # -> True
in (In operator)
Check whether one value is contained in another.
Syntax
["in", <operator_or_literal>, <operator_or_literal>]
Example
from json_operations import execute
operations = ["in", "my_type", ["key", "types"]]
data1 = {
"types": [
"type1", "type2"
]
}
data2 = {
"types": [
"my_type", "type1"
]
}
execute(operations, data1) # -> False
execute(operations, data2) # -> True
and (And operator)
Check whether all values are True. and
supports nesting other operation inside
it (See complex example).
Syntax
["and", ...<operators_or_literals>]
Examples
from json_operations import execute
operations = ["and", ["key", "a"], ["key", "b"]]
data1 = {
"a": True,
"b": False,
}
data2 = {
"a": True,
"b": True,
}
execute(operations, data1) # -> False
execute(operations, data2) # -> True
or (Or operator)
Check whether any values are True. or
supports nesting other operation inside
it (See complex example).
Syntax
["or", ...<operators_or_literals>]
Examples
from json_operations import execute
operations = ["or", ["key", "a"], ["key", "b"]]
data1 = {
"a": False,
"b": False,
}
data2 = {
"a": False,
"b": True,
}
execute(operations, data1) # -> False
execute(operations, data2) # -> True
Complex Operator Example
from json_operations import execute
# (a > 1 or b < 5) and (c == 0 or d != 10) and (val in e or f >= 0)
operations = ["and",
["or", [">", ["key", "a"], 1], ["<", ["key", "b"], 5]],
["or", ["==", ["key", "c"], 0], ["!=", ["key", "d"], 10]],
["or", ["in", "val", ["key", "e"]], [">=", ["key", "f"], 0]],
]
data1 = {
"a": 0,
"b": 5,
"c": 0,
"d": 9,
"e": ["val", "another_val"],
"f": 0,
}
data2 = {
"a": 0,
"b": 4,
"c": 0,
"d": 9,
"e": ["val", "another_val"],
"f": -1,
}
# (0 > 1 or 5 < 5) and (0 == 0 or 9 != 10) and (val in ["val", "another_val"] or 0 >= 0)
execute(operations, data1) # -> False
# (0 > 1 or 4 < 5) and (0 == 0 or 9 != 10) and (val in ["val", "another_val"] or -1 >= 0)
execute(operations, data2) # -> True
Differences from json-logic
- Operations are always type safe (cannot compare different types). json-logic will automatically convert different types and compare them, which can lead to issues that are tough to find
- Invalid operations are errors instead of ignored. json-logic tries to avoid all errors and instead continues with unexpected input. This can lead to issues
- More compact and intuitive syntax:
["or", ["key", "a"], ["key", "b"]]
vs
{"or": [{"var": ["a"]}, {"var": ["b"]}]}
- Only supports boolean logic. json-logic supports all types of operations (addition, subtraction, etc.), not just boolean logic
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