Metadata-Version: 2.1
Name: stocksent
Version: 0.1.5
Summary: A Python library for sentiment analysis of various tickers from the latest news from trusted sources and tools to plot results.
Home-page: https://stocksent.readthedocs.io/
Author: Arya Manjaramkar
Author-email: aryagm01@email.com
License: Mozilla Public License 2.0 (MPL 2.0)
Description: 
        # Stocksent
        
        <a href="https://github.com/Aryagm/Stocksent" target="blank"><img align="center" src="https://img.shields.io/badge/Stocksent-100000?style=for-the-badge&logo=github&logoColor=white" /></a>
        
        <p align="center">
        <img src="https://raw.githubusercontent.com/Aryagm/Stocksent/main/logo.png" alt="logo" width="100"/>
        </p>
        
        Stocksent is a Python library for sentiment analysis of various tickers from the latest news from trusted sources. It also has options for plotting results.
        
        ## Installation
        
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install stocksent.
        
        ```bash
        pip install stocksent
        ```
        <br />
        <br />
        
        ## Usage
        
        <br />
        
        ### Get Sentiment of single stock
        
        ```python 
        from stocksent import StockSent
        stock = StockSent('AAPL')
        sentiment_score = stock.get_sentiment()
        print(sentiment_score)  # Returns a float with the sentiment score.
        ```
        
        ```python
        0.189
        ```
        <br />
        
        ### Get Sentiment of multiple stocks
        
        ```python
        from stocksent import StockSent
        stocks = StockSent(['AAPL','TSLA','GOOG'])
        sentiment_score = stocks.get_sentiment(days=4) # Get the sentiment for the past 4 days.
        print(sentiment_score)  # Returns a float with the sentiment score.
        ```
        
        ```python
        0.237
        ```
        
        <br />
        
        ### Get plot of sentiment scores
        
        ```python
        from stocksent import StockSent
        stocks = StockSent(['AAPL','TSLA','GOOG'])
        sentiment_score = stocks.plot()
        ```
        <img src="https://raw.githubusercontent.com/Aryagm/Stocksent/main/plot.png" alt="plot" width=450/>
        
        <br />
        <br />
        
        ### Get word cloud of headlines
        
        ```python
        from stocksent import StockSent
        stocks = StockSent(['AAPL','AMZN','GOOG','TSLA'])
        sentiment_score = stocks.word_cloud(days=5) #Create a word cloud from news from the past 5 days.
        ```
        <img src="https://raw.githubusercontent.com/Aryagm/Stocksent/main/word_cloud.png" alt="word cloud" width=450/>
        
        <br />
        <br />
        
        ## Contributing
        Pull requests are welcome on [GitHub](https://github.com/Aryagm/Stocksent) !
        
        <br />
        
        ## License
        [Mozilla Public License
        Version 2.0](https://www.mozilla.org/en-US/MPL/2.0/)
        
        <br />
        
        ## Author
        **Arya Manjaramkar**
        
        <a href="https://www.linkedin.com/in/arya-manjaramkar" target="blank"><img align="center" src="https://img.shields.io/badge/Arya Manjaramkar-0077B5?style=for-the-badge&logo=linkedin&logoColor=white" /></a>  &nbsp;&nbsp;&nbsp;       <a href="https://www.github.com/Aryagm" target="blank"><img align="center" src="https://img.shields.io/badge/Aryagm-100000?style=for-the-badge&logo=github&logoColor=white" /></a>
Platform: UNKNOWN
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
Classifier: Natural Language :: English
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
