Metadata-Version: 2.2
Name: esanalyzer
Version: 1.2.0
Summary: Emotion("fear", "anger", "surprise", "sadness", "disgust", "joy") and Sentiment("Positive","Negative","Neutral") Analysis
Home-page: https://github.com/ajaysingh111444/python/tree/esanalyzer/esanalyzer/version/1.2.0
Author: Ajay Singh Rajput
Requires-Python: >=3.12.3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: nrclex==3.0.0
Requires-Dist: datasets==2.16.1
Requires-Dist: scikit-learn==1.3.2
Requires-Dist: pandas==2.1.4
Requires-Dist: numpy==1.26.3
Requires-Dist: googletrans==4.0.0-rc1
Requires-Dist: transformers==4.36.2
Requires-Dist: nltk==3.8.1
Requires-Dist: torch==2.3.0
Requires-Dist: torchvision==0.18.0
Requires-Dist: torchaudio==2.3.0
Requires-Dist: tensorflow==2.16.1
Requires-Dist: flax==0.8.3
Requires-Dist: textblob==0.18.0.post0
Requires-Dist: emoji==2.14.0
Dynamic: author
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# esanalyzer

    The Python Emotion Analysis and Sentiment Analysis library you've been looking for.

    ## Services
    - Emotion Analysis("fear", "anger", "surprise", "sadness", "disgust", "joy")
    - Sentiment Analysis("Positive","Negative","Neutral")
    - Multi Language Support
    - Emoji Support
    - Unicodedata Support
    - Filter Out Special Characters
    
    ## Supported Python Version
    - 3.12.3

    ## Usage
    - Install using `pip install esanalyzer`

    ```python
    from esanalyzer import EmotionAnalyzer

    #Instance Config
	#default requiredOnly = {"sentiment":True,"emotions":False,"googleTranslate":False}
	requiredOnly = {"sentiment":True,"emotions":True,"googleTranslate":True}

	# Create an instance of EmotionAnalyzer
	analyzer = EmotionAnalyzer(requiredOnly)

    # Call the analyze method with the text
    text = "Wow, I am so happy"
    result = analyzer.analyze(text)

    # Use the result as needed
    print(result)
    
    
    {'library': 'default', 'result': {'surprise': 80}, 'max_prediction': {'label': 'surprise', 'percentage': 80}, 'sentiment': 'Positive', 'sentiment_score': 0.999592125415802, 'threshold_value': 0.8}
    
    ```
    
    
