| Name | sentimental-onix JSON |
| Version |
0.0.2
JSON |
| download |
| home_page | |
| Summary | spacy pipeline component for sentiment analysis using onnx |
| upload_time | 2023-03-15 21:56:53 |
| maintainer | |
| docs_url | None |
| author | |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2023 sloev / Johannes Valbjørn 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 |
spacy
onnx
sentiment
english
nlp
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
 <a href="https://www.buymeacoffee.com/sloev" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/default-pink.png" alt="Buy Me A Coffee" height="51px" width="217px"></a>
 [](https://pypi.python.org/pypi/sentimental-onix) [](https://pypi.python.org/pypi/sentimental-onix)
# Sentimental Onix
Sentiment Analysis using [onnx](https://github.com/onnx/onnx) for python with a focus on being [spacy](https://github.com/explosion/spaCy) compatible *and EEEEEASY to use*.
**Features**
- [x] English sentiment analysis
- [x] Spacy pipeline component
- [x] Sentiment model downloading from github
## Install
```bash
$ pip install sentimental_onix
# download english sentiment model
$ python -m sentimental_onix download en
```
## Usage
```python
import spacy
from sentimental_onix import pipeline
nlp = spacy.load("en_core_web_sm")
nlp.add_pipe("sentencizer")
nlp.add_pipe("sentimental_onix", after="sentencizer")
sentences = [
(sent.text, sent._.sentiment)
for doc in nlp.pipe(
[
"i hate pasta on tuesdays",
"i like movies on wednesdays",
"i find your argument ridiculous",
"soda with straws are my favorite",
]
)
for sent in doc.sents
]
assert sentences == [
("i hate pasta on tuesdays", "Negative"),
("i like movies on wednesdays", "Positive"),
("i find your argument ridiculous", "Negative"),
("soda with straws are my favorite", "Positive"),
]
```
# Benchmark
| library| result|
|----------------|---------|
| spacytextblob| 58.9%|
|sentimental_onix| 69%|
See [./benchmark/](./benchmark/) for info
## Dev setup / testing
<details><summary>expand</summary>
### Install
install the dev package and pyenv versions
```bash
$ pip install -e ".[dev]"
$ python -m spacy download en_core_web_sm
$ python -m sentimental_onix download en
```
### Run tests
```bash
$ black .
$ pytest -vvl
```
### Packaging and publishing
```bash
python3 -m pip install --upgrade build twine
python3 -m build
python3 -m twine upload dist/*
```
</details>
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