CLI for semantic string similarity
Semantic String Similarity CLI
simil is a CLI interface to
spacy's string similarity engine. It uses the
en_vectors_web_lg dataset to compare strings for their English semantic similarity. Given two words, phrases, or sentences,
simil will tell you how similar their meanings are.
$ pip3 install --user -U simil
Now install one of spacy's web_vector models:
$ python3 -m spacy download en_vectors_web_lg
You can choose between
en_core_web_sm don't include word vectors at all, and can't be used with
simil will use the largest model that you have installed, with preference for the
vectors model over a
I suggest using the large vectors model (
en_vectors_web_lg), but you might want to use a smaller model in order to save on disk space or memory usage.
$ sim first_file.txt second_file.txt # compare two files $ sim -s "first string" "second string" # compare two strings
The output is a number between 0 and 1, representing how similar the two strings are.
This can be a large dataset, which makes for long startup times. So
simil spins off a process in the background to hold the model, and works under a client-server model with it. This means that if you run
simil a number of times in a row, only the first run is slow.
This background process does take up a fair bit of memory, typically around 2GB (for the
en_vectors_web_lg model). After 10 minutes of inactivity it will automatically be killed, in order not to take up memory indefinitely. You can change the length of this timeout with the
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size simil-0.0.2-py3-none-any.whl (17.9 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size simil-0.0.2.tar.gz (4.4 kB)||File type Source||Python version None||Upload date||Hashes View|