Generating an interval set in hypothesis

I have some code that works with intervals, which are really just python dicts with the following structure:

{
    "name": "some utf8 string",
    "start": 0.0,  # 0.0 <= start < 1.0
    "end": 1.0,    # start < end <= 1.0
    "size": 1.0,   # size == end - start
}

Writing a strategy for a single interval is relatively straightforward. I'd like to write a strategy to generate interval sets. An interval set is a list of intervals, such that:

The list contains an arbitrary number of intervals.
The interval names are unique.
The intervals do not overlap.
All intervals are contained within the range (0.0, 1.0).
Each interval's size is correct.
The intervals do not have to be contiguous and the entire range doesn't need to be covered.

How would you write this strategy?

Solution

I managed to get this working with the following strategies. This is almost certainly sub-optimal but does produce the desired object state.

import math
import sys

from hypothesis import strategies as st

@composite
def range_strategy(draw):
    """Produces start-end pairs within the 0.0–1.0 interval"""
    start = 0.0
    end = 1.0
    ranges = []

    while draw(st.booleans()):
        range_start = draw(st.floats(min_value=start, max_value=end, exclude_max=True)
        range_end = draw(st.floats(min_value=range_start, max_value=end, exclude_min=True)
        ranges.append((range_start, range_end))

        if math.isclose(range_end, end, abs_tol=sys.float_info.epsilon):
            # We hit the ceiling so we're done
            break
        start = math.nextafter(range_end, float("inf"))
    return ranges


@composite
def interval_set_strategy(draw):
    ranges = draw(range_strategy())
    intervals = st.just(
        map(
            lambda range: {
                "name": draw(st.text()),
                "start": range[0],
                "end": range[1],
                "size": range[1] - range[0],
            }
        ),
        ranges
    )

    return draw(st.builds(list, intervals))