A comprehensive fake data generator built specifically for Taiwan (zh_TW). Zero dependencies.
- 16 generators covering personal, contact, business, finance, date/time, and vehicle data
- Taiwan-specific: National IDs with valid checksums, 統一編號, ROC calendar dates, 09XX mobile numbers, real city/district/road addresses
- Checksum validation: generated IDs, tax IDs, and credit cards pass real validation algorithms
- Reproducible: seed support for deterministic output
- Zero dependencies: stdlib only, installs in seconds
- CLI included: generate data from the command line
- Export: JSON, CSV, SQL INSERT out of the box
classDiagram
class BaseGenerator {
<<abstract>>
+_rng: Random
+_load_lines(filename) list~str~
+_load_weighted(filename) tuple
+_weighted_choice(items, weights) str
+generate()* str
}
class NlpFaker {
+_rng: Random
+name() str
+id_number() str
+mobile() str
+address() str
+email() str
+company() str
+landline() str
+date() str
+date_roc() str
+credit_card() str
+profile() dict
+batch(field, n) list
}
BaseGenerator <|-- NameGenerator
BaseGenerator <|-- IDNumberGenerator
BaseGenerator <|-- MobileGenerator
BaseGenerator <|-- AddressGenerator
BaseGenerator <|-- EmailGenerator
BaseGenerator <|-- CompanyGenerator
BaseGenerator <|-- LandlineGenerator
BaseGenerator <|-- DateTimeGenerator
BaseGenerator <|-- LicensePlateGenerator
BaseGenerator <|-- TaxIDGenerator
BaseGenerator <|-- InvoiceGenerator
BaseGenerator <|-- CreditCardGenerator
BaseGenerator <|-- BankAccountGenerator
BaseGenerator <|-- JobGenerator
BaseGenerator <|-- CredentialGenerator
NlpFaker --> NameGenerator : lazy init
NlpFaker --> IDNumberGenerator : lazy init
NlpFaker --> MobileGenerator : lazy init
NlpFaker --> AddressGenerator : lazy init
NlpFaker --> EmailGenerator : lazy init
NlpFaker --> CompanyGenerator : lazy init
NlpFaker --> LandlineGenerator : lazy init
NlpFaker --> DateTimeGenerator : lazy init
NlpFaker --> LicensePlateGenerator : lazy init
NlpFaker --> TaxIDGenerator : lazy init
NlpFaker --> InvoiceGenerator : lazy init
NlpFaker --> CreditCardGenerator : lazy init
NlpFaker --> BankAccountGenerator : lazy init
NlpFaker --> JobGenerator : lazy init
NlpFaker --> CredentialGenerator : lazy init
class Exporter {
+to_json(records, path)$
+to_csv(records, path)$
+to_sql(records, table, path)$
}
class Validators {
+validate_id_number(id_str)$ bool
+validate_tax_id(tax_str)$ bool
+validate_mobile(mobile_str)$ bool
+validate_credit_card(card_str)$ bool
}
pip install nlpFakerOr with uv:
uv add nlpFakerfrom nlpFaker import NlpFaker
fake = NlpFaker(seed=42)
fake.name() # "陳怡君"
fake.id_number() # "A123456789"
fake.mobile() # "0912345678"
fake.address() # "台北市大安區和平東路二段42號3樓"
fake.email() # "ming.chen@gmail.com"
fake.company() # "台灣科技股份有限公司"
fake.date_roc() # "民國113年03月15日"
fake.credit_card() # "4539123456789012"| Method | Description | Example |
|---|---|---|
name() |
Full name (last + first) | 陳怡君 |
first_name() |
First name (1-2 chars) | 怡君 |
last_name() |
Last name | 陳 |
id_number() |
National ID with valid checksum | A123456789 |
username() |
Random username | coolstar42 |
password(length=12) |
Mixed-character password | xK9#mP2qLf!3 |
| Method | Description | Example |
|---|---|---|
mobile() |
Mobile phone (09XX format) | 0912345678 |
landline() |
Landline with area code | (02) 27481234 |
email() |
Email with TW domains | ming.chen@gmail.com |
address() |
Full Taiwan address | 台北市大安區和平東路二段42號3樓 |
postal_code() |
3-digit postal code | 106 |
| Method | Description | Example |
|---|---|---|
company() |
Company name | 台灣科技股份有限公司 |
job_title() |
Job title | 軟體工程師 |
tax_id() |
統一編號 with valid checksum | 12345670 |
invoice() |
統一發票 number | AB-12345678 |
| Method | Description | Example |
|---|---|---|
credit_card(card_type=None) |
Luhn-valid (Visa/MC/JCB) | 4539123456789012 |
bank_account() |
Bank code + account number | 812-1234567890 |
bank_code() |
3-digit bank code | 812 |
| Method | Description | Example |
|---|---|---|
date(start, end) |
Date (YYYY/MM/DD) | 2024/03/15 |
date_roc(start, end) |
ROC calendar (民國) | 民國113年03月15日 |
time() |
Time (HH:MM:SS) | 14:30:22 |
datetime(start, end) |
Full datetime | 2024/03/15 14:30:22 |
| Method | Description | Example |
|---|---|---|
license_plate(vehicle="car") |
TW license plate | ABC-1234 |
# Complete fake person profile
profile = fake.profile()
# {'name': '陳怡君', 'id_number': 'A123456789', 'email': '...',
# 'mobile': '...', 'landline': '...', 'address': '...',
# 'postal_code': '...', 'company': '...', 'job_title': '...',
# 'birthday': '...', 'credit_card': '...', 'bank_account': '...',
# 'username': '...'}
# Batch generation
names = fake.batch("name", 100)
ids = fake.batch("id_number", 50)Validate real or generated Taiwan data:
from nlpFaker import validate_id_number, validate_tax_id, validate_mobile, validate_credit_card
validate_id_number("A123456789") # True/False — checksum verification
validate_tax_id("12345670") # True/False — 統一編號 checksum
validate_mobile("0912345678") # True/False — format check
validate_credit_card("4539...") # True/False — Luhn algorithmfrom nlpFaker import NlpFaker, Exporter
fake = NlpFaker(seed=1)
records = [fake.profile() for _ in range(1000)]
Exporter.to_json(records, "data.json")
Exporter.to_csv(records, "data.csv")
Exporter.to_sql(records, "people", "data.sql")nlpfaker name -n 10 # 10 random names
nlpfaker profile -n 5 -f json # 5 profiles as JSON
nlpfaker id_number -s 42 # reproducible with seed
nlpfaker mobile -n 100 -o phones.txt # output to filegit clone https://github.com/danghoangnhan/nlpFaker.git
cd nlpFaker
uv sync --group dev
uv run python -m pytest -v
uv run ruff check nlpFaker/MIT
nlpFaker 是一個專為 台灣 (zh_TW) 設計的假資料產生器，零外部相依套件。
提供 16 種產生器，涵蓋個人資料、聯絡方式、商業、金融、日期時間及車輛資訊，所有產生的身分證字號、統一編號、信用卡號碼皆通過真實的校驗演算法驗證。
- 台灣專屬：身分證字號（含檢查碼）、統一編號、民國年曆、09XX 手機號碼、真實縣市/區/路名地址
- 16 種產生器：姓名、身分證、手機、地址、電子郵件、公司名稱、市話、日期時間、車牌、郵遞區號、統一編號、統一發票、信用卡、銀行帳號、職稱、帳號密碼
- 可重現：支援 seed 參數，輸出結果可重現
- 零相依：僅使用 Python 標準函式庫
- 內建 CLI：可從命令列直接產生資料
- 匯出功能：支援 JSON、CSV、SQL INSERT
from nlpFaker import NlpFaker
fake = NlpFaker(seed=42)
fake.name() # 產生姓名，例如 "陳怡君"
fake.id_number() # 產生身分證字號（含有效檢查碼）
fake.mobile() # 產生手機號碼，例如 "0912345678"
fake.address() # 產生完整地址
fake.company() # 產生公司名稱
fake.date_roc() # 產生民國日期，例如 "民國113年03月15日"
fake.tax_id() # 產生統一編號（含有效檢查碼）
fake.credit_card() # 產生信用卡號碼（通過 Luhn 演算法）
# 產生完整個人資料
profile = fake.profile()
# 批次產生
names = fake.batch("name", 100) # 產生 100 個姓名from nlpFaker import validate_id_number, validate_tax_id
validate_id_number("A123456789") # 驗證身分證字號檢查碼
validate_tax_id("12345670") # 驗證統一編號檢查碼nlpfaker name -n 10 # 產生 10 個隨機姓名
nlpfaker profile -n 5 -f json # 產生 5 筆完整個人資料（JSON 格式）
nlpfaker id_number -s 42 # 使用固定種子產生身分證字號