stringlifier VS PolyFuzz

Compare stringlifier vs PolyFuzz and see what are their differences.

stringlifier

Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data. (by adobe)
Machine Learning Python3 API Analysis unsupervised-machine-learning Clustering tf-idf raw-text Pytorch convolutional-networks long-short-term-memory Classification
Source Code
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PolyFuzz

Fuzzy string matching, grouping, and evaluation. (by MaartenGr)
levenshtein-distance Embeddings Bert tf-idf string-matching edit-distance
Source Code
maartengr.github.io
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stringlifier PolyFuzz
1 2
157 713
0.6% -
0.0 4.1
about 1 year ago 8 days ago
Python Python
Apache License 2.0 MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

stringlifier

Posts with mentions or reviews of stringlifier. We have used some of these posts to build our list of alternatives and similar projects.

PolyFuzz

Posts with mentions or reviews of PolyFuzz. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-08.

What are some alternatives?

When comparing stringlifier and PolyFuzz you can also consider the following projects:

torchextractor - Feature extraction made simple with torchextractor

RapidFuzz - Rapid fuzzy string matching in Python using various string metrics

pyDenStream - Implementation of the DenStream algorithm in Python.

go-edlib - 📚 String comparison and edit distance algorithms library, featuring : Levenshtein, LCS, Hamming, Damerau levenshtein (OSA and Adjacent transpositions algorithms), Jaro-Winkler, Cosine, etc...

muzero-general - MuZero

contextualized-topic-models - A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.

DBCV - Python implementation of Density-Based Clustering Validation

simplematch - Minimal, super readable string pattern matching for python.

woodKubernetes - LXD wood cluster

string_grouper - Super Fast String Matching in Python

stringlifier vs torchextractor PolyFuzz vs RapidFuzz stringlifier vs pyDenStream PolyFuzz vs go-edlib stringlifier vs muzero-general PolyFuzz vs contextualized-topic-models stringlifier vs DBCV PolyFuzz vs simplematch stringlifier vs woodKubernetes PolyFuzz vs string_grouper