tablefaker 1.0.1

A Python package for generating fake table data. Get data in pandas dataframe & pyarrow table or export to Csv, Json, Excel or Parquet

Table Faker

tablefaker is a versatile Python package that empowers you to effortlessly create realistic but synthetic table data for a wide range of applications. If you need to generate test data for software development, this tool simplifies the process with an intuitive schema definition in YAML format.

Key Features

Schema Definition: Define your target schema using a simple YAML file. Specify the structure of your tables, column names, fake data generation function, and relationships.

Faker and Randomization: Leverage the power of the Faker library and random data generation to create authentic-looking fake data that mimics real-world scenarios.

Multiple Output Formats: Generate fake data in various formats to suit your needs

• Pandas Dataframe
• CSV File
• Parquet File
• JSON File
• Excel File

Installation

pip install tablefaker

Sample Yaml File

version: 1
config:
  locale: en_US
tables:
  - table_name: person
    row_count: 10
    columns:
      - column_name: id
        data: row_id
      - column_name: first_name
        data: fake.first_name()
      - column_name: last_name
        data: fake.last_name()
      - column_name: age
        data: fake.random_int(18, 90)
      - column_name: dob
        data: fake.date_of_birth()
        null_percentage: 0.20
      - column_name: salary
        data: None                # NULL
      - column_name: height
        data: "\"170 cm\""        # string
      - column_name: weight
        data: 150                 # number
  - table_name: employee
    row_count: 5
    columns:
      - column_name: id
        data: row_id
      - column_name: person_id
        data: fake.random_int(1, 10)
      - column_name: hire_date
        data: fake.date_between()
      - column_name: school
        data: fake.school_name()  # custom provider

full yml example

Sample Code

import tablefaker

tablefaker.to_csv("test_table.yaml") # exports to current folder in csv format
tablefaker.to_json("test_table.yaml", "./target_folder") # exports all tables in json format
tablefaker.to_parquet("test_table.yaml", "./target_folder") # exports all tables in parquet format
tablefaker.to_excel("test_table.yaml", "./target_folder/target_file.csv") # exports only the first table in excel format

#you can use customer faker provider
from faker_education import SchoolProvider

tablefaker.to_csv("tests/test_table.yaml", "./tests/exports", fake_provider=SchoolProvider)

Sample CLI Command

tablefaker --config test_table.yaml # exports to current folder in csv format
tablefaker --config test_table.yaml --file_type excel # exports to current folder in excel format
tablefaker --config test_table.yaml --file_type json --target ./target_folder # exports all tables in json format
tablefaker --config test_table.yaml --file_type parquet --target ./target_folder/target_file.parquet # exports only the first table

Sample CSV Output

id,first_name,last_name,age,dob,salary,height,weight
1,John,Smith,35,1992-01-11,,170 cm,150
2,Charles,Shepherd,27,1987-01-02,,170 cm,150
3,Troy,Johnson,42,,170 cm,150
4,Joshua,Hill,86,1985-07-11,,170 cm,150
5,Matthew,Johnson,31,1940-03-31,,170 cm,150

Faker Functions List

https://faker.readthedocs.io/en/master/providers.html#

Bug Report & New Feature Request

https://github.com/necatiarslan/table-faker/issues/new

TODO

• Custom fake data creation function
• Foreign key
• Parquet Column Types

Nice To Have

• Export To PostgreSQL
• Inline schema definition
• Json schema file
• Pyarrow table
• Use Logging package
• Exception Management

Follow me on linkedin to get latest news
https://www.linkedin.com/in/necati-arslan/

Thanks,
Necati ARSLAN
[e-mail]