pystoxx 0.1.2
Search and retrieve current data and historical information for publicly traded companies
Requires Python: >3.6
Keywords: stock,prices,sentiment,historical,news,dataset,api

# PyStoxx: 

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  <img src="https://github.com/recursivllc/external-facing-images/blob/master/stoxx/stoxxByRecursiv_blue.png?raw=true" width="100" alt="accessibility text">
</p>


PyStoxx is a Python library of [Stoxx by Recursiv](https://recursiv.tech/) that allows users to retrieve current data and historical information for publicly traded companies with our JSON API.

## Features Include:
- Current & Historical Company Sentiment
- Company News Articles
- Pricing History
- Price Quotes
- Company Data
- Company Competition

## Quick Start Guide

1. Install Stoxx using Pip

        pip install pystoxx

2. Import Stoxx

        from pystoxx import Stoxx

3. Add your API Token using the RapidAPI extension. Sign up for a free plan without a credit card by visiting [Stoxx By Recursiv hosted at RapidAPI.](https://rapidapi.com/recursivllc/api/stoxx-by-recursiv)

        stoxx = Stoxx()
        stoxx.RapidAPI("add-your-token-here")

4. Query your data of interest:

        ​stoxx.get_historical_prices(ticker="msft", months=2)

## Query Current and Historical Stock Ticker Data:

### Historical Pricing Data:

Input:

        # Get historical daily pricing data
        stoxx.get_historical_prices(ticker="msft", months=2)

Output:

        {
        "changePercent": 0,
        "close": 198.76,
        "date": "2020-03-19",
        "high": 208.75,
        "low": 195.27,
        "open": 201,
        "symbol": "MSFT",
        "updated": 1613017108000,
        "volume": 4796717
        }

### Historical News & Sentiment Data:

Input:

        # Get historical news & sentiment data
        stoxx.get_historical_news(ticker="msft", months=2)

Output:

        {
        "FeedUrl": "url-to-article",
        "Polarity": 0.08882323,
        "PublishDate": "2021-02-17T20:04:00+00:00",
        "Subjectivity": 0.2944154,
        "Title": "News Corp. and Google Settle Long Pay Fight With Global News Pact",
        "VaderAggregate": 0.9933,
        "VaderNegative": 0.045,
        "VaderNeutral": 0.827,
        "VaderPositive": 0.127,
        "id": "4cb8b419-2ec1-32d0-849a-2ac524475c23"
        },

### Company Data and Information:

Input:

        # Get company information
        stoxx.get_company_data("msft")

Output:

        {
                "companyName": "Microsoft Corporation",
                "country": "US",
                "industry": "Data Processing, Hosting, and Related Services",
                "sector": "Information",
                "symbol": "MSFT",
                "tags": [
                "Technology Services",
                "Packaged Software",
                "Information",
                ],
                "website": "https://www.microsoft.com/en-us",
                "zip": "98052-6399"
        }

### Stock Ticker Price Quote:

Input:

        # Get a price quote
        stoxx.get_price_quote("msft")

Output:

        {
                "close": 230.72,
                "exchange": "NASDAQ/NGS (GLOBAL SELECT MARKET)",
                "high": 234.19,
                "high52w": 245.56,
                "lastTime": "March 18, 2021",
                "lastUpdate": 1616097600583,
                "low": 230.33,
                "low52w": 131.19,
                "marketCap": 1740140021762,
                "name": "Microsoft Corporation",
                "pe": 34.38,
                "symbol": "MSFT",
                "volume": 34852251
        }

### List of Publicly Traded Company Tickers:

Input:

        # Get a list of all publicly traded companies
        stoxx.get_public_companies()

Output:

        [
                { "symbol" : "msft" },
                { "symbol" : "amzn" },
                { "symbol" : "amgn" },
                ...
        ]

### Find Company Competition:

Input:

        # Get company competition
        stoxx.get_company_competition("msft")

Output:

        {
        "company": "msft",
        "competition": [
                "ORCL",
                "IBM",
                "GOOGL",
                "AAPL",
                ...
        ]
        }

### Get Current Market Performance by Sector:

Input:

        # Get market performance
        stoxx.get_market_performance()

Output:

        [
                {
                "datetimeUpdated": 1616097600045,
                "performance": -0.00209,
                "sector": "Health Care"
                },
                ...
        ]

### Calculate Sentiment of Stock Market Text:

Input:

        # Calculate Sentiment
        stoxx.calculate_sentiment({"content" : "This is an amazing pypi library!"})

Output:

        {
                "VaderPositive": 0.45,
                "VaderNeutral": 0.55,
                "VaderNegative": 0.0,
                "VaderAggregate": 0.6239,
                "Subjectivity": 0.9,
                "Polarity": 0.750
        }


Disclosures & Disclaimers:

Investing involves substantial risk. Recursiv LLC, the author, nor any of their respective affiliates make any guarantee or other promises as to any result that may be obtained from using the information provided through the Stoxx service or the pyStoxx library. While past performance may be analyzed using the Stoxx service, past performance should not be considered indicative of future performance. Investment decisions should not be made without first consulting a personal financial advisor and careful study of the issuer's prospectus and other public filings. To the maximum extent permitted by law Recursiv LLC, the author, and their respective affiliates, disclaim any and all liability in the event any information, commentary, analysis, opinions, advice and/or recommendations provided by the service prove to be inaccurate, incomplete or unreliable, or result in any investment or other losses. Any and all data provided by the service should be considered commentary and opinion and are subject to change at any time. The information provided in the service is obtained from sources which Recursiv LLC believes to be reliable. However, Recursiv LLC nor the author have not independently verified or otherwise investigated all such information. Neither Recursiv LLC, the author, nor any of their respective affiliates guarantees the accuracy or completeness of any such information. Recursiv LLC, the author, nor any of their respective affiliates are responsible for any errors or omissions in any of the information provided.