abhidg/infer-schema

Infer JSON Schema from CSV

Infer schema

Infer JSON schema from CSV files.

Installation

The script can be installed via pip

pip install infer-schema

Currently, infer-schema is a single Python 3 script without any external dependencies, so you can download it to somewhere in your PATH and make it executable:

curl https://raw.githubusercontent.com/abhidg/infer-schema/main/infer_schema.py -o infer-schema
chmod +x infer-schema
./infer-schema file

Usage

See infer-schema(1) (from a local clone, use man ./infer-schema.1)

For the Python library interface, see below.

Examples

With a data file like

date,count
2023-11-20,10
2023-11-21,23

Running infer-schema will produce a JSON Schema that the CSV conforms to:

{
  "$schema": "https://json-schema.org/draft-07/schema",
  "description": "Description of data.csv",
  "properties": {
    "count": {
      "description": "Description for column count",
      "maximum": 23,
      "minimum": 10,
      "type": "integer"
    },
    "date": {
      "description": "Description for column date",
      "format": "date",
      "type": "string"
    }
  },
  "required": [
    "date",
    "count"
  ],
  "title": "JSON Schema for data.csv"
}

Python library

The same result can be obtained using the Python module:

from infer_schema import infer_schema

schema = infer_schema("data.csv")
print(schema)

Parameters

infer_schema(file: Union[Path, str], enum_threshold: int = 10, enum_fields: List[str] = [], bound_types: Set[DType] = {"integer", "number"}, explicit_nulls: bool = False)

Here DType is one of number, integer or string.

• file (Path or str): CSV file

• enum_threshold (int, default = 10): Threshold of number of unique values in column below which the field is typed enum

• enum_fields (List[str], default = []): Forces a certain field to be classed as an enum, useful for including fields that do not meet enum-threshold criteria

• bound_types (Set[DType], default = {"integer", "number"}): Types for which bounds should be encoded into the schema, default is numbers, for which minimum / maximum are determined. For strings minLength and maxLength are determined. Set to None to disable bound detection

• explicit_nulls (bool, default = False): By default, fields that have null and another type are typed as non-required with the non-null type. Another interpretation is to assume the field will be present and allow it to dual-typed with null.

Returns: JSON Schema as a dictionary

Development

Install pre-commit to setup ruff linting and formatting.

To generate the man page, scdoc is required:

scdoc < infer-schema.1.scd > infer-schema.1