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https://github.com/zaibacu/rita-dsl
A Domain Specific Language (DSL) for building language patterns. These can be later compiled into spaCy patterns, pure regex, or any other format
https://github.com/zaibacu/rita-dsl
dsl language natural-language-processing nlp parsing python regex rule-based spacy
Last synced: 3 months ago
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A Domain Specific Language (DSL) for building language patterns. These can be later compiled into spaCy patterns, pure regex, or any other format
- Host: GitHub
- URL: https://github.com/zaibacu/rita-dsl
- Owner: zaibacu
- License: mit
- Created: 2019-07-06T15:07:26.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2022-10-07T10:45:55.000Z (over 2 years ago)
- Last Synced: 2024-09-29T13:01:18.066Z (3 months ago)
- Topics: dsl, language, natural-language-processing, nlp, parsing, python, regex, rule-based, spacy
- Language: Python
- Homepage:
- Size: 860 KB
- Stars: 65
- Watchers: 4
- Forks: 3
- Open Issues: 7
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Funding: .github/FUNDING.yml
- License: LICENSE
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README
# RITA DSL
[](http://rita-dsl.readthedocs.io/?badge=latest)
[](https://codecov.io/gh/zaibacu/rita-dsl)
[](https://www.python.org/)
[](https://github.com/zaibacu/rita-dsl/graphs/commit-activity)
[](https://pypi.python.org/pypi/rita-dsl/)
[](https://pypi.python.org/pypi/rita-dsl/)
[](https://github.com/zaibacu/rita-dsl/blob/master/LICENSE)
This is a language, loosely based on language [Apache UIMA RUTA](https://uima.apache.org/ruta.html), focused on writing manual language rules, which compiles into either [spaCy](https://github.com/explosion/spaCy) compatible patterns, or pure regex. These patterns can be used for doing [manual NER](https://spacy.io/api/entityruler) as well as used in other processes, like retokenizing and pure matching
## An Introduction Video
[](https://www.youtube.com/watch?v=GScerMeWz68)
## Links
- [Website](https://rita-dsl.io/)
- [Simple Chat bot example](https://repl.it/talk/share/Simple-chatbot-done-with-Rita/53471)
- [Documentation](http://rita-dsl.readthedocs.io/)
- [QuickStart](https://rita-dsl.readthedocs.io/en/latest/quickstart/)
- [Language Syntax Plugin for IntelijJ based IDEs](https://plugins.jetbrains.com/plugin/15011-rita-language)
## Support
[](https://www.reddit.com/r/ritaDSL/)
[](https://gitter.im/rita-dsl/community?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
If you need consulting or some custom work done, you can [Contact Us](mailto:[email protected])
## Install
`pip install rita-dsl`
## Simple Rules example
```python
rules = """
cuts = {"fitted", "wide-cut"}
lengths = {"short", "long", "calf-length", "knee-length"}
fabric_types = {"soft", "airy", "crinkled"}
fabrics = {"velour", "chiffon", "knit", "woven", "stretch"}
{IN_LIST(cuts)?, IN_LIST(lengths), WORD("dress")}->MARK("DRESS_TYPE")
{IN_LIST(lengths), IN_LIST(cuts), WORD("dress")}->MARK("DRESS_TYPE")
{IN_LIST(fabric_types)?, IN_LIST(fabrics)}->MARK("DRESS_FABRIC")
"""
```
### Loading in spaCy
```python
import spacy
from rita.shortcuts import setup_spacy
nlp = spacy.load("en")
setup_spacy(nlp, rules_string=rules)
```
And using it:
```python
>>> r = nlp("She was wearing a short wide-cut dress")
>>> [{"label": e.label_, "text": e.text} for e in r.ents]
[{'label': 'DRESS_TYPE', 'text': 'short wide-cut dress'}]
```
### Loading using Regex (standalone)
```python
import rita
patterns = rita.compile_string(rules, use_engine="standalone")
```
And using it:
```python
>>> list(patterns.execute("She was wearing a short wide-cut dress"))
[{'end': 38, 'label': 'DRESS_TYPE', 'start': 18, 'text': 'short wide-cut dress'}]
```