rbloom
Highly optimized Bloom filter that mimics the Python set API, written in Rust
Decision gist · record as of 2026-08-14
Yes, if you need fast probabilistic membership testing and can tolerate a small, tunable false positive rate. The library is actively maintained, has no dependencies, and offers significantly better performance than pure-Python alternatives. The main caveat is the unclear license—verify it meets your use case before committing to production. Install friction is moderate but manageable for common platforms.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.7 or later.
- On uncommon platforms without prebuilt wheels, installation requires the Rust toolchain.
- Medium friction due to compiled wheels; prebuilt binaries available for common platforms (x86_64, ARM, PowerPC, s390x on Linux; x86_64 and ARM on macOS; x86 and x64 on Windows), but uncommon platforms require Rust toolchain.
License · maintenance · safety
(unclear) — License status is unclear—no SPDX identifier or raw license text provided in package metadata. Before production use, verify the actual license by checking the repository directly.
last release 2025-09-09 (339 days) · last repo commit 2025-11-23 · 318 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 386,080 downloads/mo, #7,053 on PyPI
Alternatives
Verify before relying
pip install rbloom
from rbloom import Bloom
bf = Bloom(200, 0.01) # 200 items max, 1% false positive rate
bf.add("hello")
print("hello" in bf) # True
print("world" in bf) # False- Whether the unclear license permits commercial or proprietary use without restriction
- Performance characteristics on very large filters (millions of items) in production workloads
- Memory overhead compared to pure-Python alternatives or C-based implementations
What it is and what it does
rBloom is a Bloom filter library written in Rust and exposed to Python, designed to provide fast probabilistic membership testing with a set-like API. It takes two parameters—expected item count and desired false positive rate—and creates a compact bit array that can quickly answer "is this item in the set?" with a tunable error rate. Unlike exact set membership (which requires storing all items), a Bloom filter trades a small, configurable false positive rate for dramatic space savings and speed.
The library mimics Python's built-in set type where possible, supporting operations like add, contains, union, intersection, and subset comparisons. It works with any hashable Python object (strings, numbers, tuples, etc.) and includes methods to serialize filters to bytes or disk for persistence. The implementation is compiled against a stable ABI for portability across Python versions, and prebuilt wheels cover most common architectures.
Use it for
- Check membership in large datasets (IP blocklists, URL filters, spam detection) where exact storage is impractical
- Deduplicate items in streaming data pipelines where occasional false positives are acceptable
- Cache negative results: quickly rule out items not in a database before expensive lookups
- Combine multiple filters using set operations (union, intersection) to aggregate or refine membership rules
- Persist membership state across application restarts by serializing filters to disk or bytes
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need fast probabilistic membership testing and can tolerate a small, tunable false positive rate.
The library is actively maintained, has no dependencies, and offers significantly better performance than pure-Python alternatives. The main caveat is the unclear license—verify it meets your use case before committing to production. Install friction is moderate but manageable for common platforms.
Install
rbloom on PyPI
Before you install
Medium friction due to compiled wheels; prebuilt binaries available for common platforms (x86_64, ARM, PowerPC, s390x on Linux; x86_64 and ARM on macOS; x86 and x64 on Windows), but uncommon platforms require Rust toolchain. No runtime dependencies. Last release 339 days ago; repository active and well-maintained.
Requires Python 3.7 or later. On uncommon platforms without prebuilt wheels, installation requires the Rust toolchain.
License in practice
License status is unclear—no SPDX identifier or raw license text provided in package metadata. Before production use, verify the actual license by checking the repository directly.
Quickstart
pip install rbloom
from rbloom import Bloom
bf = Bloom(200, 0.01) # 200 items max, 1% false positive rate
bf.add("hello")
print("hello" in bf) # True
print("world" in bf) # FalseVerify before relying
- Whether the unclear license permits commercial or proprietary use without restriction
- Performance characteristics on very large filters (millions of items) in production workloads
- Memory overhead compared to pure-Python alternatives or C-based implementations
Package facts
| License | Not declared unclear |
| Python support | Supports the current Python release >=3.7 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | None |
| Maintenance | Aging 339 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 386,080 / month, #7,053 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Programming Language :: Python :: Implementation :: CPythonProgramming Language :: Python :: Implementation :: PyPyProgramming Language :: Rust |
Evidence: rbloom-1.5.4-cp37-abi3-macosx_10_12_x86_64.whl; rbloom-1.5.4-cp37-abi3-macosx_11_0_arm64.whl; rbloom-1.5.4-cp37-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl; rbloom-1.5.4-cp37-abi3-manylinux_2_17_armv7l.manylinux2014_armv7l.whl; rbloom-1.5.4-cp37-abi3-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl; rbloom-1.5.4-cp37-abi3-manylinux_2_17_s390x.manylinux2014_s390x.whl; rbloom-1.5.4-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl; rbloom-1.5.4-cp37-abi3-manylinux_2_5_i686.manylinux1_i686.whl; rbloom-1.5.4-cp37-abi3-win32.whl; rbloom-1.5.4-cp37-abi3-win_amd64.whl
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See also pybloom-live · bloomfilter-py · bloom-filter2 · eth-bloom · preshed · pyprobables · ignore-python · immutables · blake3 · floret