- 01Environment Setup (what you'll need)
- 02Variables and print()
- 03Conditionals (if statements)
- 04Loops (for statements)
- 05Writing Your First Function
- 06Working with Lists
- 07Working with Dictionaries (dict)
- 08Loops (while statements)
- 09Working with Strings
- 10Introducing Classes (Object-Oriented Programming)
- 11Error Handling (try...except)
- 12List Comprehensions
- 13Generators and yield
- 14File Handling Basics
- 15The match Statement (Python's switch)
- 16The Conditional (Ternary) Expression
- 17Inheritance (Extending a Class)
- 18Writing Comments
- 19Logical Operators (and, or, not)
- 20Constants (values you agree not to change)
- 21Splitting and Joining Strings (split, join)
- 22Writing None-Safe Code
- 23Searching a List (in and finding the next match)
- 24Transforming a List with map()
- 25Two-Dimensional Lists (grid-shaped data)
- 26Writing a Custom Exception Class
- 27Default Arguments (initial parameter values)
- 28Working with Sets
- 29Checking Correctness with assert (your first step into testing)
- 30Higher-Order Functions (passing a function as an argument)
- 31Stacks and Queues (basic data structures)
- 32Type Conversion (casting) Basics
- 33Intro to Regular Expressions (pattern matching)
- 34The Binary Search Algorithm
- 35Building a Caesar Cipher (a character-shifting cipher)
- 36Understanding How Bubble Sort Works
- 37Building and Displaying Dates (basic year/month/day operations)
- 38Writing Multiple Test Cases Together
- 39Speeding Up Calculations with Memoization (caching)
- 40Normalizing Strings (strip, unifying case)
- 41Shallow Copy vs. Deep Copy
- 42Enum (Enumerated Types) Basics
- 43Flattening a List
- 44Reversing a String and Checking for Palindromes
- 45Pairing Up Two Lists (the zip operation)
- 46Rounding Numbers (floor, ceil, round)
- 47Multi-Line Strings (triple quotes)
- 48Functions That Return Multiple Values (tuples)
- 49Finding the GCD and LCM (the Euclidean algorithm)
- 50Formatting Numbers (padding digits, decimal places)
- 51Cleanup Logic with try/except/finally
- 52Writing Type-Agnostic Functions
- 53The with Statement (Context Managers) Basics
- 54Generating Random Numbers
- 55Bitwise Operators (AND, OR, XOR, shifts)
- 56Class Variables and @staticmethod Basics
- 57Waiting for a Fixed Amount of Time (time.sleep)
- 58Watch Out for Floating-Point Rounding Errors
- 59Type Hints Basics
- 60FizzBuzz (the classic practice problem)
- 61Checking Whether a Number Is Prime
- 62Set Operations (union, intersection, difference)
- 63Converting Number Bases (binary, hex)
- 64Checking Balanced Parentheses (an application of stacks)
- 65Checking Whether Two Words Are Anagrams
- 66Checking Whether a Year Is a Leap Year
- 67Converting Temperature (Celsius to Fahrenheit)
- 68Prime Factorization
- 69[Applied] Build a Household Budget Tool
Checking Whether a Number Is Prime
This lesson covers an algorithm for checking whether a number is prime, so you can understand an efficient way to test it. It's written for anyone who searched "Python prime number check" and landed here.
Whether a number is prime (only divisible by 1 and itself) can be determined by checking whether it's divisible by any number from 2 up to "its square root." If none of them divide it evenly, it's prime. The key insight is that stopping at the square root, rather than checking every single number, dramatically reduces the amount of computation needed.
The sample code uses the range range(2, int(n ** 0.5) + 1), effectively looping only "up to the square root." n ** 0.5 is one way to compute a square root in Python — math.sqrt() is another option. Compare the results for 17 and 18.
A common beginner mistake is not understanding the reasoning behind why checking only up to the square root is sufficient. This relies on the fact that in any pair of numbers that divide a given number evenly, one is always less than or equal to the square root and the other is always greater than or equal to it — so checking the smaller range is enough.
This is an important mathematical property that also underlies cryptographic techniques, and coming up with an efficient checking algorithm is one of the fundamentals of computer science. There's also a more advanced technique for finding many primes at once, called the Sieve of Eratosthenes.
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