distance

library0.1.3pypypi✓ verified 23d ago

The `distance` library provides utilities for comparing arbitrary sequences, implementing metrics such as Levenshtein, Hamming, Jaccard, and Sorensen distances. It offers both pure Python implementations and C extensions for performance. The library's last release was in 2013, indicating it is no longer actively maintained.

data ai-ml

pip install Distance

github ↗package ↗

INSTALL

IMPORT

SIG · DISTANCE

distance

datapythonv0.1.3

Install

3.9s avg

Import

—

Disk

12MB

Pass rate

2/ 10

Env Coverage2 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.1.3 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

1/2 runs

py 3.11

1/2 runs

py 3.12

✓ —

✓ 3.9s

py 3.13

1/2 runs

py 3.9

1/2 runs

12MB installed

● package 12MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

levenshtein

✓ import distance distance.levenshtein('string1', 'string2')

hamming

✓ import distance distance.hamming('string1', 'string2')

jaccard

✓ import distance distance.jaccard('seq1', 'seq2')

sorensen

✓ import distance distance.sorensen('seq1', 'seq2')

Calculates Levenshtein, Hamming, and Jaccard distances between sequences using the primary functions provided by the library.

import distance # Levenshtein Distance word1 = "kitten" word2 = "sitting" lev_dist = distance.levenshtein(word1, word2) print(f"Levenshtein distance between '{word1}' and '{word2}': {lev_dist}") # Hamming Distance (for sequences of equal length) seq1 = "karolin" seq2 = "kathrin" ham_dist = distance.hamming(seq1, seq2) print(f"Hamming distance between '{seq1}' and '{seq2}': {ham_dist}") # Jaccard Distance set1 = "apple" set2 = "apply" jacc_dist = distance.jaccard(set1, set2) print(f"Jaccard distance between '{set1}' and '{set2}': {jacc_dist}")

Debug

Known issues

breakingThe `distance` library has not been updated since November 2013 (version 0.1.3). It is considered unmaintained, and may have compatibility issues or unaddressed bugs with modern Python versions (beyond Python 3.3, which it nominally supported) and newer system architectures. Other libraries like `textdistance` have explicitly removed support for 'distance' due to its unmaintained status.

fix

Consider using actively maintained alternatives such as `textdistance`, `python-Levenshtein` (now `Levenshtein`), `editdistance`, or `scipy.spatial.distance` for similar functionality, which offer better compatibility and performance with current Python environments.

affects: <=0.1.3

gotchaInstalling the optional C extension requires a C compiler and Python development headers to be present on your system. Without these, the `pip install` command with `--with-c` will fail. The benefit of the C extension for performance might be negligible or detrimental on modern Python versions due to potential inefficiencies in old C API usage.

fix

If C extension installation fails, remove the `--global-option="--with-c"` flag and use the pure Python implementation. For better performance with C extensions, consider modern libraries that are actively maintained and provide optimized C/Cython implementations (e.g., `Levenshtein` for string distances).

affects: <=0.1.3

gotchaThe library's changelog from 2013 mentions switching 'back to using the to-be-deprecated Python unicode api' for Python 2.7+ compatibility and fixing 'variable interversions in (C) levenshtein which produced sometimes strange results'. This indicates potential historical issues with string handling, especially Unicode, which could resurface or behave unexpectedly in certain edge cases with modern Python 3.x string types.

fix

Thoroughly test distance calculations with diverse string inputs, especially those involving non-ASCII characters or complex Unicode, if you choose to use this library. Prefer modern libraries for robust Unicode support.

affects: <=0.1.3

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'distance'

The 'distance' Python package has not been installed in the current Python environment or the interpreter cannot find it in its search paths.

fix

Install the package using pip: `pip install distance`

error: command 'gcc' failed with exit status 1

The `distance` library includes C extensions, and its installation requires a C compiler (like GCC on Linux/macOS or Microsoft Visual C++ on Windows) and Python development headers, which are missing from the system.

fix

Install a C compiler and Python development files for your operating system. For Debian/Ubuntu, use `sudo apt-get install build-essential python3-dev`. For macOS, use `xcode-select --install`. For Windows, install Microsoft Visual C++ Build Tools.

ImportError: cannot import name 'levenshtein' from 'distance'

The `distance` library exposes functions like `levenshtein` as attributes of the main `distance` module, not as direct imports from the module itself.

fix

Import the `distance` module and then access the function as an attribute: `import distance` followed by `distance.levenshtein(...)`.

Upgrade

Version history

0.1.3latest on PyPI · released Nov 21, 2013

Audit

Dependencies

No dependency data recorded yet.

Agent activity

18 hits · last 30 days

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OpenAI (training)

Resources

githubhttps://github.com/doukremt/distance ↗

packagehttps://pypi.org/project/distance/ ↗