Understanding Python Operator Precedence: A Comprehensive Guide
Python Operator Precedence
Understanding operator precedence is crucial in Python as it determines the order in which operations are performed in an expression. This can significantly affect the results of your code.
Key Concepts
- Operator Precedence: The rules that define the hierarchy of operations. Higher precedence operators are evaluated before lower precedence ones.
- Associativity: The rule that defines the order in which operators of the same precedence are evaluated (left to right or right to left).
Operator Precedence Levels
Here are the main categories of operators in Python, listed from highest to lowest precedence:
- Parentheses
()- Used to override the default precedence.
- Example:
result = (3 + 5) * 2 # Evaluates to 16, not 11 - Exponentiation
**- Right associative.
- Example:
result = 2 ** 3 ** 2 # Evaluates to 256 (2^(3^2)) - Unary Plus and Minus
+,-- Used to indicate positive or negative values.
- Example:
result = -5 + 3 # Evaluates to -2 - Multiplication, Division, and Modulus
*,/,%- Left associative.
- Example:
result = 10 / 2 * 3 # Evaluates to 15.0 - Addition and Subtraction
+,-- Left associative.
- Example:
result = 5 + 2 - 1 # Evaluates to 6 - Comparison Operators
==,!=,>,<,>=,<=- Used for comparing values.
- Example:
result = (5 > 3) and (2 < 4) # Evaluates to True - Logical Operators
and,or,not- Used for logical operations.
- Example:
result = True and False # Evaluates to False - Assignment Operators
=,+=,-=,*=, etc.- Used to assign values to variables.
- Example:
a = 5; a += 2 # a is now 7
Summary
When writing Python expressions, remember that operators with higher precedence will be evaluated first. You can use parentheses to ensure operations are performed in the order you intend. Understanding these rules can help you avoid errors and write clearer code.