| Name | spacytextblob JSON |
| Version |
5.0.0
JSON |
| download |
| home_page | None |
| Summary | A TextBlob sentiment analysis pipeline component for spaCy. |
| upload_time | 2024-10-12 20:19:46 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
nlp
python
spacy
textblob
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
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No Travis.
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| coveralls test coverage |
No coveralls.
|
# spacytextblob
[](https://badge.fury.io/py/spacytextblob)
[](https://github.com/SamEdwardes/spacytextblob/actions/workflows/pytest.yml)
[](https://app.netlify.com/sites/spacytextblob/deploys)
A TextBlob sentiment analysis pipeline component for spaCy.
- [Docs](https://spacytextblob.netlify.app/)
- [GitHub](https://github.com/SamEdwardes/spacytextblob)
- [PyPi](https://pypi.org/project/spacytextblob/)
- [spaCy Universe](https://spacy.io/universe/project/spacy-textblob)
## Install
Install *spacytextblob* from PyPi.
```bash
pip install spacytextblob
```
TextBlob requires additional data to be downloaded before getting started.
```bash
python -m textblob.download_corpora
```
spaCy also requires that you download a model to get started.
```bash
python -m spacy download en_core_web_sm
```
## Quick Start
*spacytextblob* allows you to access all of the attributes created of the `textblob.TextBlob` class but within the spaCy framework. The code below will demonstrate how to use *spacytextblob* on a simple string.
```python
import spacy
from spacytextblob.spacytextblob import SpacyTextBlob
nlp = spacy.load('en_core_web_sm')
text = "I had a really horrible day. It was the worst day ever! But every now and then I have a really good day that makes me happy."
nlp.add_pipe("spacytextblob")
doc = nlp(text)
print(doc._.blob.polarity)
# -0.125
print(doc._.blob.subjectivity)
# 0.9
print(doc._.blob.sentiment_assessments.assessments)
# [(['really', 'horrible'], -1.0, 1.0, None), (['worst', '!'], -1.0, 1.0, None), (['really', 'good'], 0.7, 0.6000000000000001, None), (['happy'], 0.8, 1.0, None)]
```
In comparison, here is how the same code would look using `TextBlob`:
```python
from textblob import TextBlob
text = "I had a really horrible day. It was the worst day ever! But every now and then I have a really good day that makes me happy."
blob = TextBlob(text)
print(blob.sentiment_assessments.polarity)
# -0.125
print(blob.sentiment_assessments.subjectivity)
# 0.9
print(blob.sentiment_assessments.assessments)
# [(['really', 'horrible'], -1.0, 1.0, None), (['worst', '!'], -1.0, 1.0, None), (['really', 'good'], 0.7, 0.6000000000000001, None), (['happy'], 0.8, 1.0, None)]
```
## Quick Reference
*spacytextblob* performs sentiment analysis using the [TextBlob](https://textblob.readthedocs.io/en/dev/quickstart.html) library. Adding *spacytextblob* to a spaCy nlp pipeline creates a new extension attribute for the `Doc`, `Span`, and `Token` classes from spaCy.
- `Doc._.blob`
- `Span._.blob`
- `Token._.blob`
The `._.blob` attribute contains all of the methods and attributes that belong to the `textblob.TextBlob` class Some of the common methods and attributes include:
- **`._.blob.polarity`**: a float within the range [-1.0, 1.0].
- **`._.blob.subjectivity`**: a float within the range [0.0, 1.0] where 0.0 is very objective and 1.0 is very subjective.
- **`._.blob.sentiment_assessments.assessments`**: a list of polarity and subjectivity scores for the assessed tokens.
See the [textblob docs](https://textblob.readthedocs.io/en/dev/api_reference.html#textblob.blob.TextBlob) for the complete listing of all attributes and methods that are available in `._.blob`.
## Reference and Attribution
- TextBlob
- [https://github.com/sloria/TextBlob](https://github.com/sloria/TextBlob)
- [https://textblob.readthedocs.io/en/latest/](https://textblob.readthedocs.io/en/latest/)
- negspaCy (for inspiration in writing pipeline and organizing repo)
- [https://github.com/jenojp/negspacy](https://github.com/jenojp/negspacy)
- spaCy custom components
- [https://spacy.io/usage/processing-pipelines#custom-components](https://spacy.io/usage/processing-pipelines#custom-components)
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"description": "# spacytextblob\n\n[](https://badge.fury.io/py/spacytextblob)\n[](https://github.com/SamEdwardes/spacytextblob/actions/workflows/pytest.yml)\n\n[](https://app.netlify.com/sites/spacytextblob/deploys)\n\nA TextBlob sentiment analysis pipeline component for spaCy. \n\n- [Docs](https://spacytextblob.netlify.app/)\n- [GitHub](https://github.com/SamEdwardes/spacytextblob)\n- [PyPi](https://pypi.org/project/spacytextblob/)\n- [spaCy Universe](https://spacy.io/universe/project/spacy-textblob)\n\n## Install\n\nInstall *spacytextblob* from PyPi.\n\n```bash\npip install spacytextblob\n```\n\nTextBlob requires additional data to be downloaded before getting started.\n\n```bash\npython -m textblob.download_corpora\n```\n\nspaCy also requires that you download a model to get started.\n\n```bash\npython -m spacy download en_core_web_sm\n```\n\n## Quick Start\n\n*spacytextblob* allows you to access all of the attributes created of the `textblob.TextBlob` class but within the spaCy framework. The code below will demonstrate how to use *spacytextblob* on a simple string.\n\n```python\nimport spacy\nfrom spacytextblob.spacytextblob import SpacyTextBlob\n\nnlp = spacy.load('en_core_web_sm')\ntext = \"I had a really horrible day. It was the worst day ever! But every now and then I have a really good day that makes me happy.\"\nnlp.add_pipe(\"spacytextblob\")\ndoc = nlp(text)\n\nprint(doc._.blob.polarity)\n# -0.125\n\nprint(doc._.blob.subjectivity)\n# 0.9\n\nprint(doc._.blob.sentiment_assessments.assessments)\n# [(['really', 'horrible'], -1.0, 1.0, None), (['worst', '!'], -1.0, 1.0, None), (['really', 'good'], 0.7, 0.6000000000000001, None), (['happy'], 0.8, 1.0, None)]\n```\n\nIn comparison, here is how the same code would look using `TextBlob`:\n\n```python\nfrom textblob import TextBlob\n\ntext = \"I had a really horrible day. It was the worst day ever! But every now and then I have a really good day that makes me happy.\"\nblob = TextBlob(text)\n\nprint(blob.sentiment_assessments.polarity)\n# -0.125\n\nprint(blob.sentiment_assessments.subjectivity)\n# 0.9\n\nprint(blob.sentiment_assessments.assessments)\n# [(['really', 'horrible'], -1.0, 1.0, None), (['worst', '!'], -1.0, 1.0, None), (['really', 'good'], 0.7, 0.6000000000000001, None), (['happy'], 0.8, 1.0, None)]\n```\n\n## Quick Reference\n\n*spacytextblob* performs sentiment analysis using the [TextBlob](https://textblob.readthedocs.io/en/dev/quickstart.html) library. Adding *spacytextblob* to a spaCy nlp pipeline creates a new extension attribute for the `Doc`, `Span`, and `Token` classes from spaCy.\n\n- `Doc._.blob`\n- `Span._.blob`\n- `Token._.blob`\n\nThe `._.blob` attribute contains all of the methods and attributes that belong to the `textblob.TextBlob` class Some of the common methods and attributes include: \n\n- **`._.blob.polarity`**: a float within the range [-1.0, 1.0].\n- **`._.blob.subjectivity`**: a float within the range [0.0, 1.0] where 0.0 is very objective and 1.0 is very subjective. \n- **`._.blob.sentiment_assessments.assessments`**: a list of polarity and subjectivity scores for the assessed tokens.\n\nSee the [textblob docs](https://textblob.readthedocs.io/en/dev/api_reference.html#textblob.blob.TextBlob) for the complete listing of all attributes and methods that are available in `._.blob`.\n\n## Reference and Attribution\n\n- TextBlob\n - [https://github.com/sloria/TextBlob](https://github.com/sloria/TextBlob)\n - [https://textblob.readthedocs.io/en/latest/](https://textblob.readthedocs.io/en/latest/)\n- negspaCy (for inspiration in writing pipeline and organizing repo)\n - [https://github.com/jenojp/negspacy](https://github.com/jenojp/negspacy)\n- spaCy custom components\n - [https://spacy.io/usage/processing-pipelines#custom-components](https://spacy.io/usage/processing-pipelines#custom-components)\n",
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