| Name | slimpy JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | |
| Summary | Custom String Slicing and Matching in Python |
| upload_time | 2023-05-27 09:04:45 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.6 |
| license | MIT License Copyright (c) 2023 Jibril Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
matching
mismatch
slicing
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# slimpy
A simple library that provides custom string slicing and matching.
slimpy provides a convenient solution for searching and identifying strings
that may have unexpected characters. It is useful for searching and identifying
an expected string but has mismatched characters, for example, strings
extracted from OCR tools like pytesseract. In fact, that is the reason behind
the creation of this library.
For example, suppose there is a script that extracts text from an image
and there is an expected word to be present in the extracted text:
```python
expected_word = "character"
extracted_text = "This sentence has one typo word that has two mismatch oharaoter"
expected_word in extracted_text
>>> False
# We can use this library to tackle this kind of occasion
from slimpy import Fragment, REM
word_Fragment = Fragment(expected_word)
matching = REM()
matching.set_reference(extracted_text)
match = matching.perform_matching(word_Fragment)
match
>>>
Fragmented string: character
Pattern match : .{0,1}hara.*?ter
List of match : ['oharaoter']
match.match
>>> oharaoter
match.pattern
>>> .{0,1}hara.*?ter
```
That's it! As mentioned earlier, searching and identifying strings that may
have unexpected characters.
For more information, visit the GitHub [page](https://github.com/max-efort/slimpy).
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