Data Format Tools¶

9 endpoints for validating and inspecting structured data formats. Check syntax, diff JSON objects, run JSONPath queries, generate JSON Schemas, and lint CSV.

Python SDK Examples¶

Validate JSON syntax¶

from toolkitapi import DevTools

with DevTools(api_key="tk_...") as dt:
    result = dt.json_validate('{"name": "test", "value": 42}')
    print(result["valid"])   # True or False
    print(result["error"])   # None or error description

Diff two JSON objects¶

from toolkitapi import DevTools

with DevTools(api_key="tk_...") as dt:
    result = dt.json_diff(
        {"name": "Alice", "age": 30},
        {"name": "Alice", "age": 31, "city": "London"},
    )
    # result contains added, removed, changed keys

Validate XML against an XSD schema¶

from toolkitapi import DevTools

xsd = """
<xs:schema xmlns:xs="http://www.w3.org/2001/XMLSchema">
  <xs:element name="note" type="xs:string"/>
</xs:schema>
"""
xml = "<note>Hello</note>"

with DevTools(api_key="tk_...") as dt:
    result = dt.xml_validate(xml, xsd=xsd)
    print(result["valid"])

Query JSON with JSONPath¶

from toolkitapi import DevTools

data = {
    "store": {
        "books": [
            {"title": "Python Cookbook", "price": 29.99},
            {"title": "Clean Code", "price": 34.99},
        ]
    }
}

with DevTools(api_key="tk_...") as dt:
    result = dt.jsonpath(data, "$.store.books[*].title")
    print(result["matches"])  # ["Python Cookbook", "Clean Code"]

Validate JSON against a JSON Schema¶

from toolkitapi import DevTools

schema = {
    "type": "object",
    "properties": {
        "name": {"type": "string"},
        "age": {"type": "integer", "minimum": 0},
    },
    "required": ["name"],
}

with DevTools(api_key="tk_...") as dt:
    result = dt.json_schema_validate({"name": "Alice", "age": 30}, schema)
    print(result["valid"])
    print(result["errors"])   # List of validation error messages

Generate a JSON Schema from sample data¶

from toolkitapi import DevTools

sample = [
    {"id": 1, "name": "Widget A", "active": True, "price": 9.99},
    {"id": 2, "name": "Widget B", "active": False, "price": 14.99},
]

with DevTools(api_key="tk_...") as dt:
    result = dt.json_to_schema(sample)
    print(result["schema"])

Lint CSV¶

from toolkitapi import DevTools

csv_data = """id,name,email
1,Alice,[email protected]
2,Bob
3,Charlie,[email protected]"""

with DevTools(api_key="tk_...") as dt:
    result = dt.csv_lint(csv_data, has_header=True)
    print(result["valid"])
    print(result["issues"])   # e.g. "row 2 has 2 columns, expected 3"