philiprehberger-schema-infer 0.3.1

Infer JSON schemas from sample data

philiprehberger-schema-infer

Infer JSON schemas from sample data.

Installation

pip install philiprehberger-schema-infer

Usage

Infer schema from samples

from philiprehberger_schema_infer import infer

samples = [
    {"name": "Alice", "age": 30, "active": True},
    {"name": "Bob", "age": 25, "email": "[e-mail]"},
]

schema = infer(samples)
# {
#   "type": "object",
#   "properties": {
#     "name": {"type": "string", "minLength": 3, "maxLength": 5},
#     "age": {"type": "integer", "minimum": 25, "maximum": 30},
#     "active": {"type": "boolean"},
#     "email": {"type": "string", "format": "email", ...}
#   },
#   "required": ["age", "name"]
# }

Full JSON Schema output

from philiprehberger_schema_infer import to_json_schema

schema = to_json_schema(samples)
# {
#   "$schema": "https://json-schema.org/draft/2020-12/schema",
#   "type": "object",
#   "properties": { ... },
#   "required": [...]
# }

Single value type inference

from philiprehberger_schema_infer import infer_type

infer_type([1, 2, 3])
# {"type": "array", "items": {"type": "integer"}}

Schema strictness levels

Control how aggressively fields are marked required and constraints are applied:

from philiprehberger_schema_infer import infer

# Loose: no required fields, no numeric/string constraints
schema = infer(samples, strictness="loose")

# Normal (default): fields in all samples are required, constraints included
schema = infer(samples, strictness="normal")

# Strict: all fields required, additionalProperties set to False
schema = infer(samples, strictness="strict")

Custom format detection

Register domain-specific regex patterns for format detection:

from philiprehberger_schema_infer import register_format, infer_type

register_format("phone", r"^\+\d{1,3}-\d{3,14}$")
register_format("credit-card", r"^\d{4}-\d{4}-\d{4}-\d{4}$")

infer_type("[phone]")
# {"type": "string", "format": "phone"}

Merge schemas

Combine multiple inferred schemas with union/intersection logic for required fields:

from philiprehberger_schema_infer import merge_schemas

merged = merge_schemas(schema_a, schema_b, schema_c)

API

Function	Description
infer(samples, *, strictness="normal")	Infer JSON Schema from a list of dicts. Supports "loose", "normal", and "strict" levels.
infer_type(value)	Infer schema type for a single value
merge_schemas(*schemas)	Merge two or more schemas into one accepting any of them
register_format(name, pattern)	Register a custom regex pattern for string format detection
to_json_schema(samples, *, strictness="normal")	Wraps infer() output with $schema URI for draft 2020-12

Development

pip install -e .
python -m pytest tests/ -v

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License

MIT