semvec/pypi-packages huggingface dataset:
Python-Directory-Compiler 0.1.0
A wrapper for Nuitka that walks through a directory tree and compiles all .py Python source files into (.so/.pyd) files.
License: MIT

# python-directory-compiler
[Github Repository](https://github.com/KrazyKirby99999/python-directory-compiler)

A wrapper for Nuitka that walks through a directory tree and compiles all .py Python source files into (.so/.pyd) files.

usage: py-dir-compiler [-h] [-e EXCLUDE [EXCLUDE ...]] [-ds]

optional arguments:

  -h, --help            show this help message and exit

  -e EXCLUDE [EXCLUDE ...], --exclude EXCLUDE [EXCLUDE ...]
                        (Usage: -e <filename>) (Usage: -e <foldername>)
                        Exclude folder(s)/file(s) from compilation. Use
                        absolute path if multiple folders share the same name.

  -ds, --delete_source  (Usage: -ds) Removes source .py files after
                        compilation. Preserves folder structure.
ngram-search 0.1.2
Ngram-based indexing of strings into a binary file
License: MIT
Keywords: ngram,indexing,full-text,text-search,full-text-search

This library allows indexing many strings into a file, and then efficiently fuzzy-matching strings against what's been indexed.

Currently, the structure is built from the Rust program in memory before being written to the file, so that phase uses a lot of RAM. You cannot create/change an index from Python.

String search is done from the file and requires little memory.

The index is a trie structure in which trigrams can be looked up; results for each trigrams of the input are matched and sorted to get the most similar strings.

Example::

    >>> from ngram_search import Ngrams
    >>> ngrams = Ngrams(path)
    >>> ngrams.search("ham", 0.24)
    [(0, 1.0), (2, 0.25)]
    >>> ngrams.search("spa", 0.2)
    [(0, 0.375)]