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Basic schema inference for arbitrary JavaScript data objects

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multiprocessio/shape

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Shape

This library provides an inference of object shape given a JavaScript data object. It probably won't work well with circular references. But any object that comes from JSON will not have circular references.

It works well on very small or very large objects due to sampling (which can be turned off if requested).

You can try it out online in the DataStation app.

screenshot

Install

$ yarn add @multiprocess/shape

Examples

import { shape, toString } from '@multiprocess/shape';

const schema = shape({
  "results": [
    { "name": "Kevin", "score": "1" },
    { "name": "Moira", "score": 1 },
    { "name": "Alexei", "score": 2 },
    { "name": "Tia", "score": 2, "admin": true }
  ],
  "pageSize": 5,
  "total": 100,
  "nextPage": "https://myapi.com/p=2",
});
console.log(JSON.stringify(schema, null, 2), toString(schema));

Will print out:

{    
  "kind": "object",
  "children": {
    "results": {
      "kind": "array",
      "children": {
        "kind": "object",
        "children": {
          "name": {
            "kind": "scalar",
            "name": "string"
          },      
          "score": {
            "kind": "varied",
            "children": [
              {
                "kind": "scalar",
                "name": "string"
              },
              {
                "kind": "scalar",
                "name": "number"
              }
            ]
          },
          "admin": {
            "kind": "scalar",
            "name": "boolean"
          }
        }
      }
    },
    "pageSize": {
      "kind": "scalar",
      "name": "number"
    },
    "total": {
      "kind": "scalar",
      "name": "number"
    },
    "nextPage": {
      "kind": "scalar",
      "name": "string"
    },
  }
} Object with
  'results' of
    Array of
      Object with
        'name' of
          string,
        'score' of
          string or
          number,
        'admin' of
          boolean,
  'pageSize' of
    number,
  'total' of
    number,
  'nextPage' of
    string

Sampling

This library defaults to checking up to only 5000 elements at any level which allows the inferrence to scale to very large datasets. It will pick up to N elements randomly with the object to sample. To disable this, pass null, undefined, or false as the second argument to shape. For example shape(data, false).

However, turning off sampling will eventually wreck your stack as you pass bigger objects to shape.

Users

License

Apache-2.0, see ./LICENSE.md.

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