Why Python Sets Treat 1, 1.0, and True as the Same Element – The Hidden Pitfall Explained

Introduction

In a recent Python community discussion, a user asked about an unexpected result when working with Python sets. The author shares the question and provides a detailed explanation.

Problem Statement

The confusion arises from how Python compares objects using is (identity, comparing memory addresses) versus == (value equality). This distinction is crucial when dealing with sets, which automatically remove duplicate elements.

Solution Process

Python sets deduplicate based on value equality ( ==) for immutable types such as int, float, bool, and complex. Consequently, expressions like True == 1 evaluate to True, and the set {1, 1.0, 1.00, True} collapses to {1}.

Example: print({1, 1.0, 1.00, True}) # Output: {1} The article also references a previous tutorial where boolean values were used in string slicing, linking to additional resources.

Data Type Overview

Python’s basic data types are divided into immutable and mutable categories:

Immutable: Number (int, float, bool, complex), String , Tuple

Mutable: List , Dictionary , Set

All numeric types belong to the Number category and are compared using ==. Therefore, True == 1 == 1.0 == 1e0 evaluates to True.

Practical Example with pandas

A pandas snippet demonstrates extracting region information based on specific province names:

df['地区2'] = df.地区.apply(lambda s: s[:(s in ("黑龙江省", "内蒙古自治区"))] + 2])

This logic showcases how Python’s comparison operators can be leveraged in data processing.

Conclusion

The article summarizes the set “gotcha”, reinforces understanding of Python’s data type comparisons, and thanks contributors who helped clarify the concepts.