https://github.com/tuokaikyle/1000-fake-users
Put 1000 fake users into a db to test your starting project
https://github.com/tuokaikyle/1000-fake-users
bun login login-system mock-data mock-data-generator mongodb mysql postgres postgresql react reactjs register sqlite typescript user user-name
Last synced: 2 months ago
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Put 1000 fake users into a db to test your starting project
- Host: GitHub
- URL: https://github.com/tuokaikyle/1000-fake-users
- Owner: tuokaikyle
- License: mit
- Created: 2025-10-27T14:40:51.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2025-11-08T10:53:50.000Z (7 months ago)
- Last Synced: 2025-11-08T12:21:30.830Z (7 months ago)
- Topics: bun, login, login-system, mock-data, mock-data-generator, mongodb, mysql, postgres, postgresql, react, reactjs, register, sqlite, typescript, user, user-name
- Language: TypeScript
- Homepage:
- Size: 316 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 1000-fake-users
Put these 1000 or even more fake users into a db to test your starter project.
You can easily add or modify the attributes.
Uses Faker.js.
Uses weighted values and normal distribution algorithm to generate realistic data.
## How to run
To install dependencies:
```bash
bun install
```
## 1000-fake-users
```bash
bun run src/index.ts
```
Generic user data without being localized.
| Attributes | Description |
| ------------------ | ----------------------------------------------- |
| \_id | uuid |
| email | no duplicates, contains first name |
| password | not encrypted |
| username | first name only, can tell sex, allow duplidates |
| sex | two values, male and female |
| dob | yyyy-mm-dd, has range, but no normalization |
| height | cm, with normal distribution, related to sex |
| weight | kg, with normal distribution, related to sex |
| currentLocation | countries |
| fromLocation | countries |
| jobTitle | random |
| bloodType | weighted |
| mbti | random |
| relationshipStatus | weighted |
| zodiacSign | computed from dob |
## 1000-fake-users-usa
```bash
bun run src/usa.ts
```
Localized, different from _1000-fake-users_ in the following:
| Attributes | Description |
| --------------- | ------------------------------------------------ |
| email | no duplicates, contains first name and last name |
| firstname | has firstname, can tell sex |
| lastname | has lastname |
| gender | male, female, other |
| dob | US styled, has range, but no normalization |
| height | foot, with normal distribution, related to sex |
| weight | pound, with normal distribution, related to sex |
| currentLocation | US state names or abroad |
## 1000-fake-users-china
```bash
bun run src/china.ts
```
经过本地化处理，与 _1000-fake-users_ 的不同处在于：
| Attributes | Description |
| --------------- | ------------------------------------ |
| email | 随机，不包含名字 |
| username | 中文姓和随机数字 |
| currentLocation | 省市区，包含港澳台地区，部分海外地区 |
| fromLocation | 省市区，包含港澳台地区，部分海外地区 |
## Considerations
Ways of creating weighted data:
1. Plain
```
const currentLocation = Math.random() > 0.2 ? faker.location.state() : 'Abroad'
```
2. Create const and type together
```
export const relationshipStatusWeighted = [
{ value: 'Single', weight: 80 },
{ value: 'Divorced', weight: 15 },
{ value: 'Widowed', weight: 5 },
] as const
export type RelationshipStatus = (typeof relationshipStatusWeighted)[number]['value']
const relationshipStatus = faker.helpers.weightedArrayElement(relationshipStatusWeighted)
```
3. faker inside faker
```
const sex = faker.person.sexType()
const gender = faker.helpers.weightedArrayElement([
{ weight: 90, value: sex },
{ weight: 10, value: 'other' },
])
```
## Todos:
- [x] us, china emails can have duplicates
- [ ] add empty values
- [x] 中文用户名方案 - 汉字数字混合？
- [ ] 海外地区方案 包含所有国家？
- [ ] re arrange column order
- [ ] add test
## Change logs
index - create emails seperately - no duplicates - does not match name
usa - fn+ln+random - low chance duplicates
china
email
一定要唯一
名字一定能看出性别
email unique 问题：跟 username 不合拍
email unique + username 从 email 中来 问题：username 跟性别不一致
email uuid 问题：不完全 unique - 检查