randomcontent 1.0.1

A library for generating random text, numbers, and structured data.

This library provides utilities to generate mock data for testing purposes, including numbers, text, identifiers, and structured data.

Modules Overview

Installation

!pip install randomcontentgen

1. Number Generator

   • Generate random integers, floats, or numbers with custom ranges.
   • Example:

     from randomcontent import generate_number
     generate_number(type="int", min=1, max=100)  # Generates an random integer between 1 and 100
     generate_number(type="probability") # Generates an random probability between 0 and 1
     generate_number(type="gaussian",mean=0, std_dev=1) # Generates an random number from Gaussian distribution
     

2. Identifier Generator

   • Generate unique identifiers like UUIDs, credit card numbers, or custom IDs.
   • Example:

     from randomcontent import generate_identifier
     generate_identifier(type="uuid")  # Generates and random UUID-like string
     generate_identifier(type="email") # Generates an email address
     

3. Text Generator

   • Create random names, email addresses, or custom text strings.
   • Examples:

     from randomcontent import generate_text
     generate_text(type="sentence", length=12)  # Generates a sentence
     generate_text(type="poem", num_lines=4)   # Generates a poem
     

4. Structured Data Generator

   • Generate structured mock data based on a schema definition.
   • Example:

     from randomcontent import generate_structured_data, format_data
     schema = {"name": "random_name", "email": "random_email","age": "random_int(min=18, max=60)"}
     generate_structured_data(schema, count=5)  # List of 5 data rows
     

Formatting Data

Structured data can be saved in JSON, CSV, or Parquet formats:

• Example:

  from randomcontent import format_data
  format_data(data, format_type="json", file_name="data")  # Save as data.json
  format_data(data, format_type="csv", file_name="data")   # Save as data.csv
  format_data(data, format_type="parquet", file_name="data")  # Save as data.parquet