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PatternOmatic-0.2.3
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مشاهده بیشترتوضیحات
AI/NLP (Spacy) Rule Based Matcher pattern finder
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | PatternOmatic-0.2.3 |
| نام | PatternOmatic |
| نسخه کتابخانه | 0.2.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Miguel Revuelta Espinosa |
| ایمیل نویسنده | revuel22@hotmail.com |
| آدرس صفحه اصلی | https://github.com/revuel/PatternOmatic |
| آدرس اینترنتی | https://pypi.org/project/PatternOmatic/ |
| مجوز | - |
<img src="https://svgshare.com/i/R3P.svg" width="200" height="200" align="right"/>
# PatternOmatic 0.2.*
**\#AI · \#EvolutionaryComputation · \#NLP**
[](https://spacy.io)
[](https://www.gnu.org/licenses/lgpl-3.0)
[](https://travis-ci.org/revuel/PatternOmatic)
[](https://sonarcloud.io/dashboard?id=revuel_PatternOmatic)
[](https://sonarcloud.io/dashboard?id=revuel_PatternOmatic)
[](https://sonarcloud.io/dashboard?id=revuel_PatternOmatic)
[](#)
[](https://libraries.io/pypi/PatternOmatic/sourcerank)
[](https://pypistats.org/packages/PatternOmatic)
[](https://badge.fury.io/py/PatternOmatic)
_Discover spaCy's linguistic patterns matching a given set of string samples_
## Requirements
- [Python 3.7.3](https://www.python.org/downloads/release/python-373/)
- [Spacy 2.3.*](https://spacy.io/usage/v2-3)
## Basic usage
### From sources
*[Clone SCM official repository](https://github.com/revuel/PatternOmatic)*
`git clone git@github.com:revuel/PatternOmatic.git`
*Play with Makefile*
- `make venv` to activate project's [Virtual Environment*](https://docs.python.org/3.7/library/venv.html)
- `make libs` to install dependencies
- `make test` to run Unit Tests
- `make coverage` to run Code Coverage
- `make run` to run PatternOmatic's script with example parameters
<sub>* you must have one first</sub>
### From package
*Install package*
`pip install PatternOmatic`
*Play with the CLI*
```
# Show help
patternomatic.py -h
# Usage example 1: Basic
patternomatic.py -s Hello world -s Goodbye world
# Usage example 2: Using a different language
python -m spacy download es_core_news_sm
patternomatic.py -s Me llamo Miguel -s Se llama PatternOmatic -l es_core_news_sm
```
*Play with the library*
```
"""
PatternOmatic library client example.
Find linguistic patterns to be used by the spaCy Rule Based Matcher
"""
from PatternOmatic.api import find_patterns, Config
if __name__ == '__main__':
my_samples = ['I am a cat!', 'You are a dog!', 'She is an owl!']
# Optionally, let it evolve a little bit more!
config = Config()
config.max_generations = 150
config.max_runs = 3
patterns_found, _ = find_patterns(my_samples)
print(f'Patterns found: {patterns_found}')
```
---
## Features
### Generic
✅ No OS dependencies, no storage or database required!
✅ Lightweight package with just a little direct pip dependencies
- [spaCy](https://pypi.org/project/spacy/2.3.2/)
- [spaCy's en_core_web_sm Language Model](https://github.com/explosion/spacy-models/releases/tag/en_core_web_sm-2.3.0)
✅ Easy and highly configurable to boost clever searches
✅ Includes basic logging mechanism
✅ Includes basic reporting, JSON and CSV format supported. Report file path is configurable
✅ Configuration file example provided (config.ini)
✅ Default configuration is run if no configuration file provided
✅ Provides rollback actions against several possible misconfiguration scenarios
### Evolutionary
✅ Basic Evolutionary (Grammatical Evolution) parameters available and configurable
✅ Supports two different Evolutionary Fitness functions
✅ Supports Binary Tournament Evolutionary Selection Type
✅ Supports Random One Point Crossover Evolutionary Recombination Type
✅ Supports "µ + λ" Evolutionary Replacement Type
✅ Supports "µ ∪ λ" with elitism Evolutionary Replacement Type
✅ Supports "µ ∪ λ" without elitism Evolutionary Replacement Type
✅ Typical evolutionary performance metrics included:
- Success Rate (SR)
- Mean Best Fitness (MBF)
- Average Evaluations to Solution (AES)
### Linguistic
✅ [Compatible with any spaCy Language Model](https://spacy.io/usage/models#languages)
✅ [Supports all spaCy's Rule Based Matcher standard Token attributes](https://spacy.io/usage/rule-based-matching#adding-patterns-attributes)
✅ [Supports the following spaCy's Rule Based Matcher non standard Token attributes](https://spacy.io/api/token#attributes) [(via underscore)](https://spacy.io/usage/processing-pipelines#custom-components-attributes)
- ent_id
- ent_iob
- ent_kb_id
- has_vector
- is_bracket
- is_currency
- is_left_punct
- is_oov
- is_quote
- is_right_punct
- lang
- norm
- prefix
- sentiment
- string
- suffix
- text_with_ws
- whitespace
✅ Supports skipping boolean Token attributes
✅ [Supports spaCy's Rule Based Matcher Extended Pattern Syntax](https://spacy.io/usage/rule-based-matching#adding-patterns-attributes-extended)
✅ [Supports spaCy's Rule Based Matcher Grammar Operators and Quantifiers](https://spacy.io/usage/rule-based-matching#quantifiers)
✅ [Supports Token Wildcard](https://spacy.io/usage/rule-based-matching#adding-patterns-wildcard)
✅ Supports defining the number of attributes per token within searched patterns
✅ Supports usage of non repeated token attribute values
---
Author: [Miguel Revuelta Espinosa _(revuel)_](mailto:revuel22@hotmail.com "Contact author"), a humble AI enthusiastic
نیازمندی
| مقدار | نام |
|---|---|
| ==2.3.0 | spacy |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl PatternOmatic-0.2.3:
pip install PatternOmatic-0.2.3.whl
نصب پکیج tar.gz PatternOmatic-0.2.3:
pip install PatternOmatic-0.2.3.tar.gz