# 5 Best Ways to Check if One Interval Completely Overlaps Another in Python

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π‘ Problem Formulation: In computational tasks, itβs often necessary to determine whether one interval (a contiguous range of numbers) completely overlaps another. For instance, given two intervals, such as (5, 10) and (6, 8), the latter is completely overlapped by the former. The goal is to detect this complete overlap using various methods in Python.

## Method 1: Using Comparison Operators

In this approach, we simply compare the start and end points of each interval. If interval A starts before interval B and ends after interval B, then interval A completely overlaps interval B. This method is straightforward and does not require additional Python modules.

Here’s an example:

```def is_overlapped(a, b):
return a[0] = b[1]

interval_a = (5, 10)
interval_b = (6, 8)

print(is_overlapped(interval_a, interval_b))```

Output: `True`

This function, `is_overlapped()`, takes two tuples representing the intervals. It returns `True` if the first interval completely overlaps the second one, and `False` otherwise.

## Method 2: Using the Python interval Library

The interval library in Python provides a more abstract way to work with intervals. After defining two interval objects, we can check for an overlap using the library’s built-in methods. This method is more powerful for complex interval operations but requires an additional library.

Here’s an example:

```from interval import Interval

def is_overlapped(a, b):
return Interval(a[0], a[1]).contains(Interval(b[0], b[1]))

interval_a = (5, 10)
interval_b = (6, 8)

print(is_overlapped(interval_a, interval_b))```

Output: `True`

In this snippet, we use the `Interval` class to create interval objects. The method `contains` checks for a complete overlap between the intervals.

## Method 3: Using Mathematics

Checking interval overlap can be determined mathematically. For complete overlap, the start of the first interval must be less than or equal to the start of the second interval, and the end of the first interval must be greater than or equal to the end of the second.

Here’s an example:

```interval_a = (5, 10)
interval_b = (6, 8)

is_overlapped = interval_a[0] = interval_b[1]

print(is_overlapped)```

Output: `True`

This simple mathematical operation bypasses the need for a function and directly evaluates the relationship between the two intervals, resulting in a boolean value indicating if there’s a complete overlap.

## Method 4: Utilizing Sets

Sets in Python can also be used to determine interval overlaps. By creating a set of all elements in each interval, we can check if the set of the second interval is a subset of the set of the first interval, which would indicate a complete overlap.

Here’s an example:

```interval_a = set(range(5, 11))
interval_b = set(range(6, 9))

is_overlapped = interval_b.issubset(interval_a)

print(is_overlapped)```

Output: `True`

The code uses the `issubset` method on sets to determine if one set is entirely contained within another. However, this method is not recommended for large intervals due to potential memory inefficiency.

## Bonus One-Liner Method 5: Lambda Function

For a more concise approach, a lambda function can be employed. It allows us to embed the overlap check directly into the code where needed, and it’s a single line solution that uses comparison operators similar to method 1.

Here’s an example:

```is_overlapped = lambda a, b: a[0] = b[1]

interval_a = (5, 10)
interval_b = (6, 8)

print(is_overlapped(interval_a, interval_b))```

Output: `True`

This one-liner uses a lambda function that takes two intervals and returns `True` if there is a complete overlap. It’s elegant and compact for inline usage.

## Summary/Discussion

• Method 1: Comparison Operators. Simple and no dependencies. Not suitable for complex interval operations.
• Method 2: Python interval Library. Abstract and powerful for more complex needs. Requires additional library installation.
• Method 3: Mathematics. Straightforward and functional without additional code. Not the most elegant or Pythonic approach.
• Method 4: Utilizing Sets. Pythonic and readable. Inefficient for large intervals due to memory usage.
• Bonus Method 5: Lambda Function. Concise and great for inline use. Not as readable for those unfamiliar with lambdas.