predict-data-types
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A simple npm package that predicts data types for comma-separated values, including JSON objects, and validates URLs, phone numbers, email addresses, IP addresses, colors, percentages, and currency within string values.
A lightweight and robust npm package that automatically predicts data types for comma-separated values, including JSON objects, and validates URLs, phone numbers, email addresses, UUIDs, dates, and more within string values.
npm install predict-data-types
| Type | Description | Examples |
|---|---|---|
string | Plain text values | 'John', 'Hello World' |
number | Integers and decimals | 42, 3.14, -17, 1e10 |
boolean | Boolean representations | true, false, yes, no |
email | Valid email addresses | user@example.com, test+tag@domain.co.uk |
phone | Phone numbers | 555-555-5555, (555) 555-5555, +1 555-555-5555 |
url | Web URLs | https://example.com, http://subdomain.site.co.uk/path |
uuid | UUID v1-v5 | 550e8400-e29b-41d4-a716-446655440000 |
date | Various date formats | 2023-12-31, 31/12/2023, 2023-12-31T23:59:59Z |
ip | IPv4 and IPv6 addresses | 192.168.1.1, 2001:0db8::1 |
color | Hex color codes | #FF0000, #fff, #00ff00 |
percentage | Percentage values | 50%, 0.5%, -25% |
currency | Currency amounts | $100, €50.99, £25, ¥1000 |
array | JSON arrays | [1, 2, 3], ["apple", "banana"] |
object | JSON objects | {"name": "John", "age": 30} |
const predictDataTypes = require("predict-data-types");
const text = "John, 30, true, john@example.com, 2023-01-01";
const types = predictDataTypes(text);
console.log(types);
// Output:
// {
// 'John': 'string',
// '30': 'number',
// 'true': 'boolean',
// 'john@example.com': 'email',
// '2023-01-01': 'date'
// }
const csvData = `name,age,active,email,signup_date
John,30,true,john@example.com,2023-01-01
Jane,25,false,jane@example.com,2023-02-15`;
const types = predictDataTypes(csvData, true); // true = first row is header
console.log(types);
// Output:
// {
// 'name': 'string',
// 'age': 'number',
// 'active': 'boolean',
// 'email': 'email',
// 'signup_date': 'date'
// }
const complexData = `
user@test.com,
555-123-4567,
https://github.com/user/repo,
550e8400-e29b-41d4-a716-446655440000,
{"settings": {"theme": "dark"}},
[1, 2, 3, 4, 5]
`;
const types = predictDataTypes(complexData);
console.log(types);
// Output:
// {
// 'user@test.com': 'email',
// '555-123-4567': 'phone',
// 'https://github.com/user/repo': 'url',
// '550e8400-e29b-41d4-a716-446655440000': 'uuid',
// '{"settings": {"theme": "dark"}}': 'object',
// '[1, 2, 3, 4, 5]': 'array'
// }
const dates = "2023-12-31, 31/12/2023, 2023-12-31T23:59:59Z, Dec-31-2023";
const types = predictDataTypes(dates);
console.log(types);
// Output:
// {
// '2023-12-31': 'date',
// '31/12/2023': 'date',
// '2023-12-31T23:59:59Z': 'date',
// 'Dec-31-2023': 'date'
// }
predictDataTypes(input, firstRowIsHeader)Parameters:
input (string): The comma-separated string to analyzefirstRowIsHeader (boolean, optional): Whether to treat the first row as column headers (default: false)Returns:
Object<string, string>: Mapping of field names/values to their predicted data typesThrows:
Error: When input is null, undefined, or not a stringSupported Date Formats:
2023-12-31T23:59:59ZYYYY-MM-DD, DD/MM/YYYY, MM/DD/YYYYYYYY-MM-DD HH:mm:ssDD-MMM-YYYY, MMM-DD-YYYYThe package includes robust error handling:
// These will throw errors
try {
predictDataTypes(null); // Error: Input cannot be null or undefined
predictDataTypes(123); // Error: Input must be a string
predictDataTypes([1, 2, 3]); // Error: Input must be a string
} catch (error) {
console.error(error.message);
}
// These will return empty object or appropriate results
predictDataTypes(""); // Returns: {}
predictDataTypes(" "); // Returns: { '': 'string' }
npm test # Run all tests
npm run lint # Check code quality
npm run lint:fix # Auto-fix lint issues
The package includes comprehensive tests covering:
Contributions are welcome! Please read our Contributing Guidelines for details on our code of conduct and development process.
git checkout -b feature/amazing-feature)npm test)git commit -m 'Add amazing feature')git push origin feature/amazing-feature)This project is licensed under the MIT License - see the LICENSE file for details.
Made with ❤️ by Melih Birim
FAQs
A lightweight, zero-dependency npm package that predicts data types for comma-separated values, including JSON objects, and validates URLs, phone numbers, email addresses, IP addresses, colors, percentages, and currency within string values.
The npm package predict-data-types receives a total of 20 weekly downloads. As such, predict-data-types popularity was classified as not popular.
We found that predict-data-types demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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