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    "info": {
        "author": "Quentin Sun",
        "author_email": "qsun.career@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "Intended Audience :: Financial and Insurance Industry",
            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.7",
            "Topic :: Office/Business :: Financial :: Investment",
            "Topic :: Software Development :: Libraries :: Python Modules"
        ],
        "description": "================\nQuant_Experiment\n================\n\n..  image:: https://img.shields.io/pypi/v/quant_experiment.svg\n    :target: https://pypi.python.org/pypi/quant_experiment\n    :alt: PyPI Version\n\n..  image:: https://img.shields.io/pypi/l/quant_experiment.svg\n    :target: https://opensource.org/licenses/Apache-2.0\n    :alt: License\n\n..  image:: https://img.shields.io/pypi/pyversions/quant_experiment.svg\n    :target: https://pypi.python.org/pypi/quant_experiment\n    :alt: Python Version Support\n\nFeatures\n========\n\n- **Realtime stock and option data:** You can easily extract the latest stock and option information\n- **Option characteristics:** Library provides you with option relevant characteristics based on Black-Scholes model\n\nInstallation\n============\n\nInstalling With ``pip``\n-----------------------\n.. code-block:: bash\n\n    $ pip install quant_experiment\n\nQuickstart\n==========\nData is retrieved from Alpha Vantage API free services, make sure initializing a key variable first\n\n.. code:: python\n\n    key = \"YOUR_API_KEY\"\n\n1. Operation on stock data\n\n.. code:: python\n\n    from quant_experiment import finproducts\n        stock_demo = finproducts.Stock('AAPL',key)\n        stock_demo.price #return realtime stock price\n        stock_demo.latestTradingDay #lastest trading day\n        stock_demo.volume #volume\n\n2. Operation on option data\n\n.. code:: python\n\n    from quant_experiment import finproducts\n        option_demo = finproducts.VanillaOption('AAPL', 21, 6, 2019, 180, 'calls')\n        #call option with expiration date 2019-06-21 and strike price 180\n        option_demo.option_info()\n\nGiving us output as:\n\n.. figure:: https://github.com/liveoncecao/quant_experiment/blob/master/images/option_info.png?raw=true\n   :alt: alias of image\n\n3. Return option property based on Black-Scholes\n\n.. code:: python\n\n    from quant_experiment import finproducts\n        option_demo = finproducts.VanillaOption('AAPL', 21, 6, 2019, 180, 'calls')\n        option_demo.BS_Info(key) #return implied volatility by default\n        option_demo.BS_Info(key,'greeks') #return delta, gamma, vega, theta and rho\n\n\nContributing\n============\nAll contributions are welcome.\n\n\n",
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        "keywords": "stocks,market,options,pricing,quant,quotes,tickers,symbol",
        "license": "MIT",
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        "name": "quant-experiment",
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        "summary": "Python module to get stock and option information through Wed Scraping and Alpha Vantage API",
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