I get data in JSON from an API and it may be that the received data is not complete (= some fields are missing). I am not sure either that the structure of the data follows JSON standards.
The solution for the second problem is simple: I will try: to decode the JSON and act accordingly on ValueError and TypeError exceptions.
For the first problem, my solution would also be to
d = {'a': 1}
try:
d['a']
d['b']
d['x']['shouldbethere']
except KeyError:
(...)
that is to list all the keys I need to have in the dict created from a successful JSON conversion.
This made me think that there may be a method to declare the expected keys (and possibly values types) and match the retrieved JSON against it, an unsuccessful match raising a specific exception?
Standard way to validate JSON structure is to use JSON Schema. Basic characteristics (quoted from official webpage) are:
JSON Schema:
- describes your existing data format
- clear, human- and machine-readable documentation
- complete structural validation, useful for
- automated testing
- validating client-submitted data
There is no built-in package to validate JSON object against schema, although you may use jsonschema from pypi.
Sample usage (paraphrased from official docs) may be:
import jsonschema
schema = {
"type": "object",
"properties": {
"price": {"type": "number"},
"name": {"type": "string"},
},
}
jsonschema.validate({"name": "Eggs", "price": 34.99}, schema)
# No exception from line above - document is valid
jsonschema.validate({"name": "Eggs", "price": "Invalid"}, schema)
# ValidationError: 'Invalid' is not of type 'number'
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