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Use a for loop when you want a fixed number of Fibonacci terms, a while loop when you want terms below a value limit, and recursion to express the mathematical definition. Each version below uses the convention fib(0) = 0, fib(1) = 1, producing 0, 1, 1, 2, 3, 5, 8.
How the Fibonacci sequence is generated
Every term after the first two is the sum of the two before it. Starting with 0 and 1, the next term is 0 + 1 = 1, then 1 + 1 = 2, then 1 + 2 = 3.
In the loop examples, a and b hold two consecutive values. After using the current value, update both variables together:
a, b = b, a + b
Python evaluates the right-hand side before assigning either variable, so the old b becomes the new a, and the sum of the old pair becomes the new b. This is the pattern in the Python 3.11 tutorial’s Fibonacci example.
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Generate a fixed number of terms with a for loop
Use a for loop when the number of terms is known in advance. range(n) provides exactly n iterations, so the loop prints exactly that many values.
def fibonacci_terms(n):
a, b = 0, 1
for _ in range(n):
print(a, end=" ")
a, b = b, a + b
fibonacci_terms(7)
Output:
0 1 1 2 3 5 8
The underscore in for _ in range(n) signals that the loop needs to repeat a fixed number of times but does not use the iteration number. Python’s control-flow tutorial describes for as iterating over the items of a sequence; here, range(n) supplies the count.
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Generate values below a limit with a while loop
Use a while loop when the stopping rule is a condition on the current value, not a term count. This example prints each Fibonacci value while it is less than limit:
def fibonacci_below(limit):
a, b = 0, 1
while a < limit:
print(a)
a, b = b, a + b
fibonacci_below(10)
Output:
0
1
1
2
3
5
8
The Python tutorial explains that a while loop executes as long as its condition remains true; its Fibonacci example uses a < 10. When the current value reaches or exceeds the limit, the loop stops. The final update may calculate that next value even though it is not printed, because the condition is checked before the next iteration.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallA value limit and a term count are different requests. For example, “print seven terms” is a count-based task for range(7); “print values below 10” is a boundary-based task for while a < 10.
Calculate one indexed value with recursion
Recursion defines a Fibonacci value in terms of smaller Fibonacci values. The base cases stop the calls; without them, the function would keep calling itself.
def fib(n):
if n == 0:
return 0
if n == 1:
return 1
return fib(n - 1) + fib(n - 2)
print(fib(6)) # 8
This follows the recurrence fib(n) = fib(n - 1) + fib(n - 2) for n greater than 1. The base cases establish fib(0) = 0 and fib(1) = 1, matching the sequence convention used above. OpenStax presents this recurrence in its lesson on mathematical recursion in Python.
To display a series with this single-value function, call it for successive indices:
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for n in range(7):
print(fib(n), end=" ")
This combines recursion for each value with a loop to choose the indices. It returns or prints the same sequence, but it is not the same implementation as a loop that carries the current pair forward.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Return values when another part of your program needs the sequence
The examples above print values for display. Printing sends text to output; returning makes data available to the caller. For reusable results, build and return a list:
def fibonacci_list(n):
values = []
a, b = 0, 1
for _ in range(n):
values.append(a)
a, b = b, a + b
return values
terms = fibonacci_list(7)
print(terms)
Output:
[0, 1, 1, 2, 3, 5, 8]
The Python control-flow tutorial contrasts a print-oriented fib example with fib2, which builds and returns a list. Returning values lets the caller inspect, transform, or reuse the sequence instead of only displaying it.
Which Fibonacci method should you use?
| Method | Stopping rule | Best fit | What it demonstrates |
|---|---|---|---|
for loop |
A fixed iteration count such as range(n) |
You know how many terms to produce | Repeating a fixed number of times while updating a pair |
while loop |
A condition such as a < limit |
You want terms below a value boundary | Continuing until a condition becomes false |
| Recursion | Base cases for n == 0 and n == 1 |
You are learning recurrence and function calls | Defining a value using smaller instances of the same problem |
The loop versions provide direct ways to generate a sequence by carrying forward two values. The recursive version makes the mathematical definition visible. The cited Python and OpenStax materials establish these patterns, but do not provide a benchmark comparing their speeds or a practical input cutoff; choose based on the stopping rule and the concept you want to express.
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