1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
|
%global _empty_manifest_terminate_build 0
Name: python-rita-dsl
Version: 0.7.4
Release: 1
Summary: DSL for building language rules
License: MIT
URL: https://github.com/zaibacu/rita-dsl
Source0: https://mirrors.aliyun.com/pypi/web/packages/57/02/23f3c8717ce24ca373b448165c743ea314832f1f8fa1533e939f11b4c3ef/rita-dsl-0.7.4.tar.gz
BuildArch: noarch
Requires: python3-ply
%description
# 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/)
- [Live Demo](https://rita-dsl.io/#demo)
- [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)
## 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'}]
```
%package -n python3-rita-dsl
Summary: DSL for building language rules
Provides: python-rita-dsl
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-rita-dsl
# 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/)
- [Live Demo](https://rita-dsl.io/#demo)
- [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)
## 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'}]
```
%package help
Summary: Development documents and examples for rita-dsl
Provides: python3-rita-dsl-doc
%description help
# 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/)
- [Live Demo](https://rita-dsl.io/#demo)
- [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)
## 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'}]
```
%prep
%autosetup -n rita-dsl-0.7.4
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-rita-dsl -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.4-1
- Package Spec generated
|
