The Humanize Package in Python provides utility functions for converting numbers, dates, times, and file sizes into human-readable formats. It’s a must-have tool for developers building user-friendly applications where data representation matters.
In this guide, we’ll explore the features, installation, examples, advantages, disadvantages, and top interview questions with answers about the Humanize package.

Why Use the Humanize Package in Python?
- Improved Readability: Converts raw data into a format users can easily understand.
- Enhanced User Experience: Makes application interfaces more intuitive by displaying human-readable numbers, dates, and units.
- Time-Saving: Simplifies tasks like formatting file sizes, time differences, and numeric values.
Key Features of the Humanize Package in Python
- Human-Readable Time Differences
Convert time differences into phrases like “2 days ago” or “in 5 minutes.” - Readable File Sizes
Display file sizes in formats such as “10 MB” or “2.5 GB.” - Ordinal Numbers
Convert numbers into ordinals like “1st,” “2nd,” and “3rd.” - Comma-Separated Numbers
Format large numbers with commas for better readability (e.g., 1,000,000). - Custom Localization
Supports various languages and locales for displaying data in a culturally appropriate format.
Installing the Humanize Package in Python
To use the Humanize package, install it via pip:
pip install humanize
This command installs the latest version of the package from PyPI.
Examples of Using Humanize Package in Python
Here are some practical examples demonstrating the package’s versatility:
1. Human-Readable Time Differences
import humanize from datetime import datetime, timedelta # Time difference now = datetime.now() past = now - timedelta(days=2, hours=5) future = now + timedelta(hours=3) print(humanize.naturaltime(past)) # Output: "2 days ago" print(humanize.naturaltime(future)) # Output: "in 3 hours"
2.Readable File Sizes
import humanize # Convert bytes to a readable format file_size = 10485760 # 10 MB in bytes print(humanize.naturalsize(file_size)) # Output: "10.0 MB"
3.Ordinal Numbers
import humanize # Ordinal representation print(humanize.ordinal(1)) # Output: "1st" print(humanize.ordinal(22)) # Output: "22nd"
4.Comma-Separated Numbers
import humanize # Format large numbers print(humanize.intcomma(1000000)) # Output: "1,000,000" print(humanize.intcomma(123456789)) # Output: "123,456,789"
5.Custom Localization
import humanize import locale # Change locale for specific formatting locale.setlocale(locale.LC_ALL, 'fr_FR') print(humanize.intword(12345678)) # Output: "12.3 millions" (French locale)
Advantages of the Humanize Package
- Ease of Use: Provides ready-to-use functions for common formatting tasks.
- Versatility: Works with numbers, dates, times, and sizes seamlessly.
- Localization Support: Adapts output based on the user’s locale.
- Enhanced UI: Improves readability in applications, especially for non-technical users.
Disadvantages of the Humanize Package
- Limited Scope: Focused on human-readable formatting; doesn’t support advanced customization.
- Dependency Overhead: Adds a dependency, which might be unnecessary for basic applications.
- Performance: May introduce minor overhead for large-scale data processing.
Conclusion
The Humanize Package in Python is a powerful yet simple tool for making your application data more user-friendly. By converting raw data into human-readable formats, it enhances usability and improves user interaction.
Mastering this package allows developers to create intuitive interfaces and meet global standards for readability.
Interview Questions
1. What is the primary purpose of the Humanize Package in Python?
Company: Google
Answer: The Humanize package is designed to convert raw data such as numbers, dates, and file sizes into human-readable formats, improving user experience.
2. How can you display file sizes in a readable format using Humanize?
Company: Amazon
Answer: Use the naturalsize()
function to convert file sizes from bytes to a human-readable format like “KB,” “MB,” or “GB.”
Example:
humanize.naturalsize(1048576) # Output: "1.0 MB"
3. How does the naturaltime()
function work in Humanize?
Company: Microsoft
Answer: The naturaltime()
function takes a datetime
object and converts it into a human-readable time difference, like “2 days ago” or “in 5 minutes.”
4. What is the use of the intword()
function in Humanize?
Company: Meta (Facebook)
Answer: The intword()
function converts large numbers into words, such as “1 million” or “2.3 billion,” making them easier to read.
5. Can the Humanize Package in Python support different languages?
Company: Oracle
Answer: Yes, the Humanize package supports localization. By setting the appropriate locale, you can display data in a format suitable for different languages or regions.
Example:
import locale locale.setlocale(locale.LC_ALL, 'es_ES') # Spanish locale
QUIZZES
Humanize Package Quiz
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