Metadata-Version: 2.1
Name: pricefetch
Version: 0.1.1
Summary: Tool for fetching realtime options and stock data
Home-page: UNKNOWN
Author: Devesh Todarwal, Rutuvi Narang
Author-email: todarwal.devesh@gmail.com, rutuvinarang@gmail.com
License: MIT
Description: # Price-Fetch: Real time Stock and Option tools
        
        Price-Fetch is a Python 3 library for monitoring and analyzing real time Stock and
        Option data. Quotes are provided from the Yahoo Finance API and Google Finance API.
        Price-Fetch requires minimal input from the user, it uses available online data to
        calculate option greeks and even scrapes the US Treasury website to get the current risk free rate.
        
        ## Authors
        ---
        
        Rutuvi Narang   - <rutuvinarang@gmail.com>
        
        Devesh Todarwal - <todarwal.devesh@gmail.com>
        
        ## Usage
        -----
        
        **Stocks:**
        
        ```python
          from pricefetch import Stock, Call, Put
        
          >>> s = Stock('MSFT')
          >>> s.price
          326.48
          >>> s.change
          -0.35
          >>> s.last_trade
          '20 Oct 2021 13:32:12'
        ```
        **Options:**
        
        ```python
        
          >>> a = Call('AAPL', d=10, m=10, y=2021, strike=700)
          >>> a.price
          19.60
          >>> a.implied_volatility()
          0.49222968442691889
          >>> a.delta()
          0.56522039722040063
          >>> a.vega()
          0.685034827159825
          >>> a.underlying.price
          149.59
        ```
        ### Alternative construction:
        
        ```python
        
          >>> g = Call('GOOG', d=20, m=10, y=2021)
          >>> g
          Call(ticker=GOOG, expiration='12-20-2021')
          >>> g.strikes
          (580, 610, 620, 630, 640, 650, 660, 670, 680, 690, 697.5, 700, 702.5, 707.5, 710, 712.5, 715, 720, ...)
          >>> g.set_strike(712.5)
          >>> g
          Call(ticker=GOOG, expiration='12-20-2021', strike=712.5)
        ```
        
        ### Download historical data (requires pandas)
        
        ```python
            s = Stock('BTC-USD')
            >>> df = s.historical(days_back=30, frequency='d')
            >>> df
                     Date          Open          High           Low         Close     Adj Close      Volume
            0  2019-07-10  12567.019531  13183.730469  11569.940430  12099.120117  12099.120117  1554955347
            1  2019-07-11  12099.120117  12099.910156  11002.389648  11343.120117  11343.120117  1185222449
            2  2019-07-12  11343.120117  11931.910156  11096.610352  11797.370117  11797.370117   647690095
            3  2019-07-13  11797.370117  11835.870117  10827.530273  11363.969727  11363.969727   668325183
            4  2019-07-14  11363.969727  11447.919922  10118.849609  10204.410156  10204.410156   814667763
            5  2019-07-15  10204.410156  11070.179688   9877.019531  10850.259766  10850.259766   965178341
            6  2019-07-16  10850.259766  11025.759766   9366.820313   9423.440430   9423.440430  1140137759
            7  2019-07-17   9423.440430   9982.240234   9086.509766   9696.150391   9696.150391   965256823
            8  2019-07-18   9696.150391  10776.540039   9292.610352  10638.349609  10638.349609  1033842556
            9  2019-07-19  10638.349609  10757.410156  10135.160156  10532.940430  10532.940430   658190962
            10 2019-07-20  10532.940430  11094.320313  10379.190430  10759.419922  10759.419922   608954333
            11 2019-07-21  10759.419922  10833.990234  10329.889648  10586.709961  10586.709961   405339891
            12 2019-07-22  10586.709961  10676.599609  10072.070313  10325.870117  10325.870117   524442852
            13 2019-07-23  10325.870117  10328.440430   9820.610352   9854.150391   9854.150391   529438124
            14 2019-07-24   9854.150391   9920.540039   9535.780273   9772.139648   9772.139648   531611909
            15 2019-07-25   9772.139648  10184.429688   9744.700195   9882.429688   9882.429688   403576364
            16 2019-07-26   9882.429688   9890.049805   9668.519531   9847.450195   9847.450195   312717110
            17 2019-07-27   9847.450195  10202.950195   9310.469727   9478.320313   9478.320313   512612117
            18 2019-07-28   9478.320313   9591.519531   9135.639648   9531.769531   9531.769531   267243770
            19 2019-07-29   9531.769531   9717.690430   9386.900391   9506.929688   9506.929688   299936368
            20 2019-07-30   9506.929688   9749.530273   9391.780273   9595.519531   9595.519531   276402322
            21 2019-07-31   9595.519531  10123.940430   9581.599609  10089.250000  10089.250000   416343142
            22 2019-08-01  10089.250000  10488.809570   9890.490234  10409.790039  10409.790039   442037342
            23 2019-08-02  10409.790039  10666.639648  10340.820313  10528.990234  10528.990234   463688251
            24 2019-08-03  10528.990234  10915.000000  10509.349609  10820.410156  10820.410156   367536516
            25 2019-08-04  10820.410156  11074.950195  10572.240234  10978.910156  10978.910156   431699306
            26 2019-08-05  10978.910156  11945.379883  10978.889648  11807.959961  11807.959961   870917186
            27 2019-08-06  11807.959961  12316.849609  11224.099609  11467.099609  11467.099609   949534020
            28 2019-08-07  11467.099609  12138.549805  11393.980469  11974.280273  11974.280273   834719365
            29 2019-08-08  11974.280273  12042.870117  11498.040039  11982.799805  11982.799805   588463519
            30 2019-08-09  11983.620117  12027.570313  11674.059570  11810.679688  11810.679688   366160288
        ```
        ---
        ## Installation
        ------------
        
        ```bash
        
            $ pip install pricefetch
        ```
        
        
        ## API Attributes
        ----------------
        Stock Attributes
        ----------------
        
        - ticker
        - price
        - id
        - exchange
        - last_trade
        - change   (change in currency)
        - cp   (percentage change)
        
        
        Option Attributes and Methods
        -----------------------------
        
        - strike
        - expiration
        - underlying  (underlying stock object)
        - ticker
        - bid
        - ask
        - price (option price)
        - id
        - exchange
        - change  (in currency)
        - cp  (percentage change)
        - volume
        - open_interest
        - code
        - expirations (list of possible expiration dates for option chain)
        - strikes (list of possible strike prices)
        
        - set_strike()
        - implied_volatility()
        - delta()
        - gamma()
        - vega()
        - theta()
        - rho()
        
Keywords: stocks options finance market shares greeks implied volatility real-time googlefinance yahoofinance
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Education
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Description-Content-Type: text/markdown
