Skip to content

Latest commit

 

History

History
197 lines (139 loc) · 6.28 KB

README.rst

File metadata and controls

197 lines (139 loc) · 6.28 KB

tblfaker

Summary

tblfaker is a Python library to generate fake tabular data.

PyPI package version Supported Python versions CI status of Linux/macOS/Windows Test coverage CodeQL

Installation

pip install tblfaker

Install all the extra dependencies:

pip install tblfaker[all]

Usage

Basic Usage

Generate tabular data at random

Sample Code:
from tblfaker import TableFaker

faker = TableFaker()

print("[1]")
for row in faker.generate(["name", "address"], rows=4).as_tuple():
    print(row)

print("\n[2]")
for row in faker.generate(["name", "address"], rows=4).as_tuple():
    print(row)
Output:
[1]
Row(name='Jonathan Hendrix', address='368 Melanie Inlet Suite 890\nLake Stephanie, MT 17441')
Row(name='Kristina Simmons', address='3867 Perry Alley Suite 957\nLindafurt, FL 12507')
Row(name='Rebecca Velasquez', address='107 Karla Forges Apt. 925\nEast Jonathan, NC 85462')
Row(name='Jordan Morris', address='6341 Jessica Walks\nReynoldsshire, MD 05131')

[2]
Row(name='Caitlin Bush', address='87380 Barbara Haven Suite 042\nHutchinsonburgh, IA 39544')
Row(name='Jennifer King', address='39729 Gray Inlet Apt. 693\nPort Peter, AL 80733')
Row(name='Stephanie Smith', address='256 Emily Street\nCooperhaven, MS 70299')
Row(name='Nicholas Miller', address='59845 Daniel Ford Suite 729\nDamontown, UT 19811

Reproduce the same tabular data

Fake tabular data can reproduce by passing the same seed value to TableFaker constructor.

Sample Code:
from tblfaker import TableFaker

seed = 1

print("[1]")
faker = TableFaker(seed=seed)
for row in faker.generate(["name", "address"], rows=4).as_tuple():
    print(row)

print("\n[2]")
faker = TableFaker(seed=seed)
for row in faker.generate(["name", "address"], rows=4).as_tuple():
    print(row)
Output:
[1]
Row(name='Ryan Gallagher', address='6317 Mary Light\nSmithview, HI 13900')
Row(name='Amanda Johnson', address='3608 Samuel Mews Apt. 337\nHousebury, WA 13608')
Row(name='Willie Heath', address='868 Santiago Grove\nNicolehaven, NJ 05026')
Row(name='Dr. Jared Ortega', address='517 Rodriguez Divide Suite 570\nWest Melinda, NH 85325')

[2]
Row(name='Ryan Gallagher', address='6317 Mary Light\nSmithview, HI 13900')
Row(name='Amanda Johnson', address='3608 Samuel Mews Apt. 337\nHousebury, WA 13608')
Row(name='Willie Heath', address='868 Santiago Grove\nNicolehaven, NJ 05026')
Row(name='Dr. Jared Ortega', address='517 Rodriguez Divide Suite 570\nWest Melinda, NH 85325')

Set locale for fake data

Sample Code:
from tblfaker import TableFaker

faker = TableFaker(locale="ja_JP")

for row in faker.generate(["name", "address"], rows=4).as_tuple():
    print(row)
Output:
Row(name='工藤 健一', address='宮崎県武蔵村山市六番町19丁目15番11号')
Row(name='井上 聡太郎', address='愛媛県長生郡白子町豊町33丁目7番20号 戸島コート620')
Row(name='大垣 美加子', address='京都府山武郡芝山町三ノ輪34丁目15番8号 クレスト所野560')
Row(name='宇野 くみ子', address='宮城県八街市西浅草20丁目24番6号')

Generate data in other data formats

Generate data in dict

Sample Code:
from tblfaker import TableFaker
import json

faker = TableFaker(seed=1)

print(json.dumps(faker.generate(["name", "address"], rows=2, table_name="dict").as_dict(), indent=4))
Output:
{
    "dict": [
        {
            "name": "Ryan Gallagher",
            "address": "6317 Mary Light\nSmithview, HI 13900"
        },
        {
            "name": "Amanda Johnson",
            "address": "3608 Samuel Mews Apt. 337\nHousebury, WA 13608"
        }
    ]
}

Generate data in pandas.DataFrame

Sample Code:
from tblfaker import TableFaker

faker = TableFaker(seed=seed)

print(faker.generate(["name", "address"], rows=4).as_dataframe())
Output:
               name                                            address
0    Ryan Gallagher               6317 Mary Light\nSmithview, HI 13900
1    Amanda Johnson     3608 Samuel Mews Apt. 337\nHousebury, WA 13608
2      Willie Heath          868 Santiago Grove\nNicolehaven, NJ 05026
3  Dr. Jared Ortega  517 Rodriguez Divide Suite 570\nWest Melinda, ...

Dependencies