How to use range() in Python

Python's range() function is a powerful tool to create sequences of numbers. It's essential for loops and iterations and offers a memory-efficient way to handle numerical progressions.

In this article, we'll cover techniques and tips for range(). You'll find real-world applications and debugging advice to help you master this fundamental function for your Python projects.

Basic usage of range()

for i in range(5):
   print(i, end=' ')--OUTPUT--0 1 2 3 4

When you provide a single number to range(), like range(5), it defines the "stop" value for a sequence. Here's what's happening under the hood:

• The sequence starts at 0 by default.
• It increments by 1 with each step.
• It stops before reaching the specified value, 5.

This is why the output is 0 1 2 3 4. This zero-based approach is consistent with Python's indexing for lists and other iterables, which is a key reason for its design.

Alternative ways to use range()

But range() isn't just for simple sequences starting from zero; you can customize the start, stop, and step size or even convert the sequence.

Using range() with start, stop, and step parameters

for i in range(2, 10, 2):
   print(i, end=' ')--OUTPUT--2 4 6 8

You can gain more control by providing three arguments to range(): a start value, a stop value, and a step size. In the expression range(2, 10, 2), the sequence is customized.

• It starts at 2.
• It increments by 2 for each number.
• It stops before it reaches 10.

This is why the loop prints 2 4 6 8. It's a straightforward way to generate more complex numerical sequences, like all even numbers or specific intervals for your loops.

Using range() with negative step

for i in range(10, 0, -1):
   print(i, end=' ')--OUTPUT--10 9 8 7 6 5 4 3 2 1

The range() function isn't limited to counting up; you can also count down by providing a negative step value. For range(10, 0, -1), the function generates a sequence in reverse.

• The count begins at 10.
• It decrements by 1 with each step.
• The sequence stops before it reaches 0.

This is how you get a countdown from 10 to 1, which is useful for iterating through sequences in reverse order without needing to reverse the data first.

Converting range() to other data types

numbers_list = list(range(1, 6))
numbers_tuple = tuple(range(1, 6))
numbers_set = set(range(1, 6))
print(numbers_list, numbers_tuple, numbers_set)--OUTPUT--[1, 2, 3, 4, 5] (1, 2, 3, 4, 5) {1, 2, 3, 4, 5}

A range() object is an iterable, not a list. It generates numbers as you need them, which saves memory. To work with the numbers as a complete collection, you can convert the range object into other data types.

• list(range(1, 6)) creates the list [1, 2, 3, 4, 5].
• tuple(range(1, 6)) produces the tuple (1, 2, 3, 4, 5).
• set(range(1, 6)) gives you the set {1, 2, 3, 4, 5}.

This is handy when you need to store the sequence or use methods specific to lists, tuples, or sets.

Advanced techniques with range()

Now that you've grasped the fundamentals, you can use range() in more complex patterns to write cleaner and more efficient code.

Using range() in list comprehensions

squares = [x**2 for x in range(1, 6)]
print(squares)

cubes = [x**3 for x in range(1, 6)]
print(cubes)--OUTPUT--[1, 4, 9, 16, 25]
[1, 8, 27, 64, 125]

List comprehensions offer a compact syntax for creating lists from other iterables. When you combine them with range(), you can apply an expression to each number in a sequence and collect the results in a single, readable line.

• The expression [x**2 for x in range(1, 6)] iterates through the numbers 1 to 5.
• For each number x, it calculates its square using x**2.
• The results are automatically gathered into a new list, making this a clean alternative to a traditional for loop.

Using range() with enumerate()

fruits = ["apple", "banana", "cherry"]
for index, fruit in enumerate(fruits, start=1):
   print(f"Fruit {index}: {fruit}")--OUTPUT--Fruit 1: apple
Fruit 2: banana
Fruit 3: cherry

While you could use range(len(fruits)) to get indices, Python's enumerate() function offers a much cleaner way to access both an item and its index. It pairs each fruit with a counter, simplifying your loop and making your code more direct and easier to read.

• By default, enumerate() starts counting from 0.
• You can change this with the start argument; using start=1 gives you a 1-based index, which is often more natural for numbered lists.

Memory efficiency of range()

large_range = range(1, 1000000)
size_in_bytes = large_range.__sizeof__()
print(f"Size: {size_in_bytes} bytes")
print(f"First: {large_range[0]}, Last: {large_range[-1]}")--OUTPUT--Size: 48 bytes
First: 1, Last: 999999

The range() function is incredibly memory-efficient, which is why an object representing a million numbers takes up so little space. It doesn't store every number in the sequence. Instead, it's a much smarter object.

• It only remembers its start, stop, and step values.
• Numbers are generated on the fly as you iterate, rather than being stored in memory all at once.
• This makes range() perfect for loops over large sequences where creating an actual list would consume significant resources.

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Common errors and challenges

Even with its simple syntax, range() can lead to some common trip-ups if you're not careful.

• Forgetting that range() is exclusive of the end value. A frequent mistake is expecting an expression like range(5) to include the number 5. Remember, the sequence always stops before reaching the stop value, so you'll need to set the argument one number higher than your desired end point. To get numbers from 1 through 5, you'd use range(1, 6).
• Using non-integer arguments with range(). The function is strict and only accepts integers for its start, stop, and step values. If you try to use a floating-point number, such as range(2.5, 10.0), Python will raise a TypeError. This is because range() is designed for discrete, whole-number steps, not continuous values.
• Off-by-one errors when using range() with indices. This classic programming headache often appears when iterating over a list. For example, using range(len(my_list)) correctly generates indices from 0 to the final index. A small mistake, however—like using range(1, len(my_list))—will cause your loop to skip the first item, while range(len(my_list) + 1) will cause an IndexError by trying to access an element that doesn't exist.

Forgetting that range() is exclusive of the end value

It's a classic off-by-one error. You write range(1, 10) expecting to get numbers up to 10, but the loop stops short. Because the function excludes the stop value, your sequence ends at 9. The code below shows this in action.

for i in range(1, 10):
   print(i, end=' ')

The loop produces numbers from 1 to 9 because the sequence stops before reaching the stop value of 10. The fix is a small adjustment to ensure the number 10 is included. See how it's done below.

for i in range(1, 11):
   print(i, end=' ')

By changing the expression to range(1, 11), you're telling Python to generate numbers up to, but not including, 11. This simple adjustment ensures the number 10 is part of the sequence, fixing the off-by-one error.

• This is the standard way to create a sequence with an inclusive upper bound.
• You'll need this fix whenever your logic depends on including the final number, like when counting items or iterating through a specific number of days.

Using non-integer arguments with range()

The range() function works exclusively with integers, meaning you can't use floating-point numbers for its start, stop, or step values. Attempting to do so, for instance with range(0, 5.5), will result in a TypeError. See what happens in the following code.

for i in range(0, 5.5):
   print(i, end=' ')

Python raises a TypeError because range() requires integer arguments. The stop value 5.5 is a float, which the function can't handle. The following example shows how you can adapt your code to achieve a similar result.

for i in range(0, int(5.5)):
   print(i, end=' ')

By wrapping the float in the int() function, you can resolve the TypeError. The expression int(5.5) truncates the decimal, turning it into 5 and making the argument valid for range().

• This is a common fix when your loop boundaries are derived from calculations or external data that might not be whole numbers, so it's a good pattern to remember.

Off-by-one errors when using range() with indices

When you use range() to loop through list indices, a small miscalculation can cause you to miss the last item. This off-by-one error is a common pitfall, especially when you adjust the length inside the range() function. The code below demonstrates how subtracting one from the length results in an incomplete loop.

items = ["apple", "banana", "cherry", "date", "elderberry"]
for i in range(len(items) - 1):
   print(items[i])

The expression range(len(items) - 1) generates indices from 0 to 3, but the list's final index is 4. This causes the loop to miss the last item entirely. See how a simple change corrects this behavior.

items = ["apple", "banana", "cherry", "date", "elderberry"]
for i in range(len(items)):
   print(items[i])

The fix is to use range(len(items)) directly. This generates a sequence from 0 up to the list's length, which perfectly aligns with Python's zero-based indexing. For a list of five items, range(5) produces indices 0 through 4, ensuring no item is missed.

• This is the standard, safest way to iterate over list indices; it's best to avoid manual adjustments like - 1 unless you intentionally want to skip items.

Real-world applications

Now that you can navigate its common pitfalls, you can use range() for practical tasks like processing data in batches or generating coordinate grids.

Using range() for batch processing data

When you're working with a large dataset, the step parameter in range() lets you process the data in smaller, more manageable chunks.

data = list(range(1, 21))  # Sample data with 20 items
batch_size = 5

for i in range(0, len(data), batch_size):
   batch = data[i:i+batch_size]
   print(f"Processing batch {i//batch_size + 1}: {batch}")

The loop uses the step argument in range() to control the starting index for each slice. By setting the step to the batch_size, the loop variable i jumps to the beginning of each new chunk on every iteration.

• The values for i will be 0, 5, 10, and 15.
• For each of these values, the expression data[i:i+batch_size] slices the list to create a batch. For example, the first batch is created from data[0:5].

This ensures the entire dataset is covered in non-overlapping segments.

Creating a simple coordinate grid with range()

You can create a 2D coordinate grid by nesting two range() loops, a common pattern for any task that involves iterating over rows and columns.

grid_size = 3
for y in range(grid_size):
   for x in range(grid_size):
       coordinate = (x, y)
       print(f"{coordinate}", end=" ")
   print()  # New line after each row

This pattern generates a 3x3 grid by running one loop inside another. The outer loop controls the y coordinate. For each y value, the inner loop completes its full cycle for the x coordinate, creating a full row of points.

• A new (x, y) coordinate tuple is created in every inner loop iteration.
• The end=" " argument keeps all coordinates for a single row on the same line.
• Once a row is complete, the final print() call adds a line break, neatly stacking the rows into a grid.

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