If you haven't check jsonschema library, it can be useful to validate data. JSON Schema is a way to describe the content of JSON. The library just uses the format to make validations based on the given schema.
I made a simple example from basic usage.
import json
from jsonschema import validate
# Describe what kind of json you expect.
schema = {
"type" : "object",
"properties" : {
"description" : {"type" : "string"},
"status" : {"type" : "boolean"},
"value_a" : {"type" : "number"},
"value_b" : {"type" : "number"},
},
}
# Convert json to python object.
my_json = json.loads('{"description": "Hello world!", "status": true, "value_a": 1, "value_b": 3.14}')
# Validate will raise exception if given json is not
# what is described in schema.
validate(instance=my_json, schema=schema)
# print for debug
print(my_json)
Answer from T.Nylund on Stack OverflowIf you haven't check jsonschema library, it can be useful to validate data. JSON Schema is a way to describe the content of JSON. The library just uses the format to make validations based on the given schema.
I made a simple example from basic usage.
import json
from jsonschema import validate
# Describe what kind of json you expect.
schema = {
"type" : "object",
"properties" : {
"description" : {"type" : "string"},
"status" : {"type" : "boolean"},
"value_a" : {"type" : "number"},
"value_b" : {"type" : "number"},
},
}
# Convert json to python object.
my_json = json.loads('{"description": "Hello world!", "status": true, "value_a": 1, "value_b": 3.14}')
# Validate will raise exception if given json is not
# what is described in schema.
validate(instance=my_json, schema=schema)
# print for debug
print(my_json)
As you're using a JSON file, you can use this example:
import json
def validate(filename):
with open(filename) as file:
try:
data = json.load(file) # put JSON-data to a variable
print("Valid JSON") # in case json is valid
return data
except json.decoder.JSONDecodeError:
print("Invalid JSON") # in case json is invalid
Videos
» pip install json-checker
I had a requirement to process and validate large payloads of JSON concurrently for a web service, initially I implemented it using jsonschema and fastjsonschema but I found the whole JSON Schema Specification to be confusing at times and on top of that wanted better performance. Albeit there are ways to compile/cache the schema, I wanted to move away from the schema specification so I wrote a validation library inspired by the design of tiangolo/sqlmodel (type hints) to solve this problem easier.
Here is a simple example:
from okjson import JSONValidator
schema = { 'name': str, 'age': int }
json_string = '{ "name": "Charly Gordon", "age": 32 }'
assert JSONValidator().is_valid(instance=json_string, schema=schema)There is an example covering all the features in the README.
It also has well defined exceptions for each error case when you want to get the reason for the validation failure. (Helpful when you want to show user facing error messages)
GitHub: https://github.com/mufeedvh/okjson
This is my first time publishing a Python library, please share your feedback/suggestions. :)
You can try to do json.loads(), which will throw a ValueError if the string you pass can't be decoded as JSON.
In general, the "Pythonic" philosophy for this kind of situation is called EAFP, for Easier to Ask for Forgiveness than Permission.
Example Python script returns a boolean if a string is valid json:
import json
def is_json(myjson):
try:
json.loads(myjson)
except ValueError as e:
return False
return True
Which prints:
print is_json("{}") #prints True
print is_json("{asdf}") #prints False
print is_json('{ "age":100}') #prints True
print is_json("{'age':100 }") #prints False
print is_json("{\"age\":100 }") #prints True
print is_json('{"age":100 }') #prints True
print is_json('{"foo":[5,6.8],"foo":"bar"}') #prints True
Convert a JSON string to a Python dictionary:
import json
mydict = json.loads('{"foo":"bar"}')
print(mydict['foo']) #prints bar
mylist = json.loads("[5,6,7]")
print(mylist)
[5, 6, 7]
Convert a python object to JSON string:
foo = {}
foo['gummy'] = 'bear'
print(json.dumps(foo)) #prints {"gummy": "bear"}
If you want access to low-level parsing, don't roll your own, use an existing library: http://www.json.org/
Great tutorial on python JSON module: https://pymotw.com/2/json/
Is String JSON and show syntax errors and error messages:
sudo cpan JSON::XS
echo '{"foo":[5,6.8],"foo":"bar" bar}' > myjson.json
json_xs -t none < myjson.json
Prints:
, or } expected while parsing object/hash, at character offset 28 (before "bar}
at /usr/local/bin/json_xs line 183, <STDIN> line 1.
json_xs is capable of syntax checking, parsing, prittifying, encoding, decoding and more:
https://metacpan.org/pod/json_xs