Work In Progress (Mainly AI Generated)
Tests were copied from the IntervalTree package and are passing, but still use with caution.
Manzanita
A high-performance interval tree library implemented in Rust with Python bindings via PyO3. Drop-in alternative to intervaltree with significantly better performance.
Installation
pip install manzanita
From source
pip install maturin
git clone https://github.com/pgarrett-scripps/manzanita.git
cd manzanita
maturin develop --release
Quick Start
from manzanita import Interval, IntervalTree
# Create a tree and add intervals
tree = IntervalTree()
tree.add(Interval(1.0, 5.0, "alpha"))
tree.add(Interval(3.0, 8.0, "beta"))
tree.add(Interval(10.0, 15.0, "gamma"))
# Or use shorthand
tree.addi(20.0, 25.0, "delta")
# Query by point
tree.at(4.0) # intervals containing point 4.0
tree[4.0] # same thing, using indexing syntax
# Query by range
tree.overlap(2.0, 6.0) # intervals overlapping [2, 6)
tree[2.0:6.0] # same thing, using slice syntax
# Find intervals completely contained in a range
tree.envelop(0.0, 9.0)
# Check for overlaps
tree.overlaps(4.0) # True - any interval contains 4.0?
tree.overlaps(2.0, 6.0) # True - any interval overlaps [2, 6)?
# Create from tuples
tree = IntervalTree.from_tuples([
(1, 3),
(2, 4, "with data"),
(5, 7),
])
Interval Operations
iv = Interval(1.0, 5.0, "data")
iv.begin # 1.0
iv.end # 5.0
iv.data # "data"
# Tuple unpacking
begin, end, data = iv
# Overlap checks
iv.overlaps(3.0) # point overlap
iv.overlaps_range(2.0, 4.0) # range overlap
iv.overlaps_interval(other_iv) # interval overlap
Deletion
tree.remove(interval) # raises ValueError if not found
tree.discard(interval) # silent if not found
tree.removei(1.0, 5.0, "data")
tree.discardi(1.0, 5.0, "data")
# Remove by overlap
tree.remove_overlap(4.0) # remove all containing point
tree.remove_overlap(2.0, 6.0) # remove all overlapping range
tree.remove_envelop(2.0, 6.0) # remove all enveloped by range
# Indexing syntax
del tree[4.0] # remove all containing point
del tree[2.0:6.0] # remove all overlapping range
tree.clear() # remove everything
iv = tree.pop() # remove and return an arbitrary interval
Set Operations
tree1 | tree2 # union
tree1 & tree2 # intersection
tree1 - tree2 # difference
tree1 ^ tree2 # symmetric difference
tree1 |= tree2 # in-place union
tree1 &= tree2 # in-place intersection
tree1 -= tree2 # in-place difference
tree1 ^= tree2 # in-place symmetric difference
tree1 <= tree2 # subset
tree1 >= tree2 # superset
tree1 == tree2 # equality
Restructuring
# Split all intervals at their mutual boundary points
tree.split_overlaps()
# Merge overlapping intervals
tree.merge_overlaps()
tree.merge_overlaps(strict=False) # also merge touching intervals
# Merge intervals with identical ranges
tree.merge_equals()
# Merge adjacent/nearby intervals
tree.merge_neighbors()
tree.merge_neighbors(max_dist=1.0)
# Chop out a range (split intervals at boundaries, remove the middle)
tree.chop(3.0, 7.0)
# Slice all intervals at a point
tree.slice(5.0)
All restructuring methods accept an optional datafunc parameter to control how data is combined or transformed.
Boundary Inclusivity
By default, intervals are half-open [begin, end) (inclusive start, exclusive end). This can be configured per-interval or as a tree default:
# Per-interval
iv = Interval(1.0, 5.0, "data", start_inclusive=True, end_inclusive=True) # [1, 5]
iv = Interval(1.0, 5.0, "data", start_inclusive=False, end_inclusive=False) # (1, 5)
# Tree default (applies to addi, from_tuples)
tree = IntervalTree(start_inclusive=True, end_inclusive=True)
tree.addi(1.0, 5.0, "data") # creates [1, 5]
Tree Information
len(tree) # number of intervals
bool(tree) # True if non-empty
tree.is_empty() # True if empty
tree.begin() # minimum begin value
tree.end() # maximum end value
tree.items() # list of all intervals
# Membership
interval in tree
tree.containsi(1.0, 5.0, "data")
# Iteration
for interval in tree:
print(interval.begin, interval.end, interval.data)
Performance
Manzanita is implemented in Rust and compiled as a native Python extension. Key operations have the following time complexity:
| Operation | Time Complexity |
|---|---|
add / addi |
O(log n) |
at / overlap / envelop |
O(log n + k) |
remove / discard |
O(n) |
len |
O(n) |
begin |
O(log n) |
end |
O(1) |
Where n is the number of intervals and k is the number of results.
Benchmarks vs intervaltree
Measured with python benchmarks/bench.py (see benchmarks/ for the full script).
10,000 intervals, 10,000 queries:
| Operation | manzanita | intervaltree | Speedup |
|---|---|---|---|
| Insertion | 19.0ms | 87.2ms | 4.6x |
| Point query | 294.7ms | 315.7ms | 1.1x |
| Range query | 433.9ms | 13.90s | 32x |
| Merge overlaps | 4.0ms | 28.8ms | 7.2x |
| Removal | 27.4ms | 61.8ms | 2.3x |
100,000 intervals, 1,000 queries:
| Operation | manzanita | intervaltree | Speedup |
|---|---|---|---|
| Insertion | 294.2ms | 1.12s | 3.8x |
| Point query | 310.6ms | 453.1ms | 1.5x |
| Range query | 437.1ms | 168.01s | 384x |
| Merge overlaps | 76.7ms | 416.9ms | 5.4x |
Results will vary by machine. Run python benchmarks/bench.py to reproduce.
License
MIT
1 maintainer
Metadata
1 maintainer
Release files for manzanita 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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