https://github.com/fizzyelt/fakerator
generate fake data fn
https://github.com/fizzyelt/fakerator
fake-data fake-data-generator javascript typescript
Last synced: 10 months ago
JSON representation
generate fake data fn
- Host: GitHub
- URL: https://github.com/fizzyelt/fakerator
- Owner: FizzyElt
- License: mit
- Created: 2024-03-21T16:16:38.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-08-18T16:28:53.000Z (10 months ago)
- Last Synced: 2025-08-18T16:53:37.624Z (10 months ago)
- Topics: fake-data, fake-data-generator, javascript, typescript
- Language: TypeScript
- Homepage: https://www.npmjs.com/package/struct-fakerator
- Size: 269 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 假資料結構產生器
- [假資料結構產生器](#假資料結構產生器)
- [Wrapping fakerjs Functions](#wrapping-fakerjs-functions)
- [用途](#用途)
- [Value](#value)
- [Selection](#selection)
- [Object](#object)
- [Array](#array)
- [Tuple](#tuple)
- [BoundedSeries](#boundedseries)
- [擴充](#擴充)
## Wrapping fakerjs Functions
- [X] Airline
- [X] Animal
- [X] Color
- [X] Commerce
- [X] Company
- [X] Database
- [X] Datatype
- [X] Date(Datetime)
- [X] Finance
- [X] Food
- [X] Git
- [X] Hacker
- [X] Image
- [X] Internet
- [X] Location
- [X] Lorem
- [X] Music
- [X] Number
- [X] Person
- [X] Phone
- [X] Science
- [X] String
- [X] System
- [X] Vehicle
## 用途
使用 faker js 時是單一純值不能產生結構，需要自己手動組合結構，此專案利用撰寫設定檔的方式來產生一個特定的假資料函數，減少手動組合結構的麻煩。
```typescript
import { StructConfig } from 'struct-fakerator'
const scheme = StructConfig.object({
name: StructConfig.value(() => 'hello'),
enum: StructConfig.select([1, 2, 3]),
list: StructConfig.array(StructConfig.value(() => 10), 5),
tuple: StructConfig.tuple([StructConfig.value(() => 'tuple1'), StructConfig.value(() => '100')])
})
// or
import {
createObjectConfig,
createArrayConfig,
createValueConfig,
createTupleConfig,
createSelectionConfig
} from 'struct-fakerator';
const scheme = createObjectConfig({
name: createValueConfig(() => 'hello'),
enum: createSelectionConfig([1, 2, 3]),
list: createArrayConfig(
createValueConfig(() => 10),
5
),
tuple: createTupleConfig([
createValueConfig(() => 'tuple1'),
createValueConfig(() => 100),
createValueConfig(() => false),
])
});
// or
const scheme = {
type: 'obj',
content: {
name: {
type: 'value',
generateFn: () => 'hello',
},
enum: {
type: 'select',
items: [1, 2, 3],
},
list: {
type: 'arr',
item: {
type: 'value',
generateFn: () => 10,
},
len: 5,
},
tuple: {
type: 'tuple',
configItems: [
{
type: 'value',
generateFn: () => 'tuple1',
},
{
type: 'value',
generateFn: () => 100,
},
{
type: 'value',
generateFn: () => false,
},
],
},
},
};
```
```typescript
import { StructGenerator } from 'struct-fakerator';
const result = StructGenerator.genFn(scheme)()
console.log(result);
// {
// name: 'hello',
// enum: 1, // or 2 or 3
// list: [10, 10, 10, 10, 10],
// tuple: ['tuple1', 100, false]
// }
```
### Value
```typescript
const generateFn = StructGenerator.genFn(StructConfig.value(() => 10));
console.log(generateFn());
// 10
```
### Selection
```typescript
const generateFn = StructGenerator.genFn(StructConfig.select([1, 2, 3, 4, 5]))
console.log(generateFn());
// 1 or 2 or 3 or 4 or 5
```
### Object
```typescript
const generateFn = StructGenerator.genFn(StructConfig.object({
name: StructConfig.value(() => 'hello'),
list: StructConfig.array(StructConfig.value(() => 10), 5),
}));
console.log(generateFn());
// {
// name: 'hello',
// list: [10, 10, 10, 10, 10]
// }
// with transformer function
const generateFn = StructGenerator.genFn(
StructConfig.object(
{
name: StructConfig.value(() => 'hello'),
list: StructConfig.array(
StructConfig.value(() => 10),
5
),
},
({ name, list }) => list.map((item) => `${name} ${item}`)
)
);
console.log(generateFn());
// ["hello 10", "hello 10", "hello 10", "hello 10", "hello 10"]
```
### Array
```typescript
const generateFn = StructGenerator.genFn(
StructConfig.array(
StructConfig.value(() => 10),
5
)
);
console.log(generateFn());
// [10, 10, 10, 10, 10]
// with next function
const generateFn = StructGenerator.genFn(
StructConfig.array(
StructConfig.value(() => 10),
5,
(prev, current) => prev + 1 + current
)
);
console.log(generateFn());
// [21, 32, 43, 54, 65]
```
### Tuple
```typescript
const generateFn = StructGenerator.genFn(
StructConfig.tuple([
StructConfig.value(() => 'tuple1'),
StructConfig.value(() => 100),
StructConfig.value(() => false),
])
);
console.log(generateFn());
// ['tuple1', 100, false]
```
### BoundedSeries
```typescript
const generateFn = StructGenerator.genFn(
StructConfig.boundedSeries({
upperLimit: 1.1,
lowerLimit: 0.9,
createInitValue: () => 100,
count: 20,
})
);
console.log(generateFn());
// [100 * 0.9 <= num <= 100 * 1.1,
// prev * 0.9 <= num <= prev * 1.1,
// prev * 0.9 <= num <= prev * 1.1,
// ...]
```
## 擴充
一切的值皆由 `value` 產生，可以自己創建各種不同亂數函數
```mermaid
flowchart TB
value --> int
value --> float
value --> string
value --> email
value --> other[...]
```
但並不是所有人情況都能自己手動建立函數，有可能是開放給別人使用的服務，沒辦法在使用方建立函數，這時 `createGeneratorByType` 第二個可以讓製作服務的人帶入自己的擴充，這樣這個函數就能接受更多種型態。
```typescript
const createIntValueConfig = (option) => createValueConfig(() => faker.number.int(option));
const createEmailValueConfig = (option) => createValueConfig(() => faker.internet.email(option));
const customTypeMatch = (config) => {
if (config.type === "int") {
return createIntValueConfig(config.option);
}
if (config.type === "email") {
return createEmailValueConfig(config.option);
}
throw Error("error");
};
const config = {
type: "obj",
content: {
name: { type: "value", generateFn: () => "John" },
age: { type: "int" },
email: { type: "email" },
},
};
const result = createGeneratorByType(config, customTypeMatch)();
console.log(result);
/*
{
name: "John",
age: 50,
email: "xxx@example.com",
}
*/
```