Synthetic Data Generator#
Python Faker Pandas JSON Postman
Overview#
A Python tool for generating realistic fake shareholder data at scale. Designed for API testing and prototyping workflows, the tool produces configurable datasets in CSV and JSON formats, suitable for use with tools like Postman.
Sample Output#
CSV Output (shareholder_data_name_id_1000.csv)
name,shareholder_id,email,address,phone
John Smith,SH-001,jsmith@example.com,"123 Main St, Portland OR",503-555-0142
Jane Doe,SH-002,jdoe@example.com,"456 Oak Ave, Salem OR",503-555-0198
...
JSON Output (Postman-compatible)
[
{
"name": "John Smith",
"shareholder_id": "SH-001",
"email": "jsmith@example.com",
"address": "123 Main St, Portland OR",
"phone": "503-555-0142"
}
]
Key Features#
Generate datasets from 1,000 to 10,000+ records
Output to CSV and JSON formats
Postman-compatible JSON for API testing
Realistic names, addresses, emails, and phone numbers via the Faker library
Reproducible results with seed control
Code Highlights#
from faker import Faker
import pandas as pd
fake = Faker()
def generate_shareholders(n=1000):
"""Generate n fake shareholder records."""
data = []
for i in range(n):
data.append({
'name': fake.name(),
'shareholder_id': f'SH-{i+1:04d}',
'email': fake.email(),
'address': fake.address(),
'phone': fake.phone_number()
})
return pd.DataFrame(data)
Technologies#
Category |
Tools |
|---|---|
Data Generation |
Faker |
Data Processing |
Pandas |
Output Formats |
CSV, JSON |
API Testing |
Postman |