A library for generating random text, numbers, and structured data.
Project description
This library provides utilities to generate mock data for testing purposes, including numbers, text, identifiers, and structured data.
Modules Overview
Installation
!pip install randomcontent
-
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
-
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
-
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
-
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
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