Merge branch 'release/1.3.1'

README.md

@@ -6,7 +6,7 @@
 [![Average time to resolve an issue](http://isitmaintained.com/badge/resolution/RomelTorres/alpha_vantage.svg)](http://isitmaintained.com/project/RomelTorres/alpha_vantage "Average time to resolve an issue")
 [![Percentage of issues still open](http://isitmaintained.com/badge/open/RomelTorres/alpha_vantage.svg)](http://isitmaintained.com/project/RomelTorres/alpha_vantage "Percentage of issues still open")
 
-*Python module to get stock data from the Alpha Vantage API*
+*Python module to get stock data/cryptocurrencies from the Alpha Vantage API*
 
 Alpha Vantage delivers a free API for real time financial data and most used finance indicators in a simple json or pandas format. This module implements a python interface to the free API provided by Alpha
 Vantage (http://www.alphavantage.co/). It requires a free API, that can be requested on http://www.alphavantage.co/support/#api-key. You can have a look at all the api calls available in their documentation http://www.alphavantage.co/documentation
@@ -87,9 +87,29 @@ plt.tight_layout()
 plt.grid()
 plt.show()
 ```
+
 Giving us as output:
 ![alt text](images/docs_sp_rt_example.png?raw=True "Real Time Sector Performance")
 
+Finally, we can also plot crypto currencies prices like BTC:
+
+```python
+from alpha_vantage.cryptocurrencies import CryptoCurrencies
+import matplotlib.pyplot as plt
+
+cc = CryptoCurrencies(key='YOUR_API_KEY', output_format='pandas')
+data, meta_data = cc.get_digital_currency_intraday(symbol='BTC', market='CNY')
+data['. price (USD)'].plot()
+plt.tight_layout()
+plt.title('Intraday value for bitcoin (BTC)')
+plt.grid()
+plt.show()
+```
+
+Giving us as output:
+![alt text](images/docs_cripto_btc.png?raw=True "Crypto Currenci daily (BTC)")
+
+
 ## Tests
 
 In order to run the tests you have to first export your API key so that the test can use it to run.

alpha_vantage/alphavantage.py

@@ -5,7 +5,7 @@
     # Python 2.* import
     from urllib2 import urlopen
 
-from simplejson import loads
+from json import loads
 from functools import wraps
 import inspect
 import pandas
@@ -19,30 +19,7 @@ class AlphaVantage:
     _ALPHA_VANTAGE_API_URL = "http://www.alphavantage.co/query?"
     _ALPHA_VANTAGE_MATH_MAP = ['SMA', 'EMA', 'WMA', 'DEMA', 'TEMA', 'TRIMA', 'T3',
                                'KAMA', 'MAMA']
-    _EXCHANGE_SUPPORTED = { 'ASX': 'Australian Securities Exchange',
-                            'BOM': 'Bombay Stock Exchange',
-                            'BIT': 'Borsa Italiana Milan Stock Exchange',
-                            'TSE': 'Canadian/Toronto Securities Exchange',
-                            'FRA': 'Deutsche Boerse Frankfurt Stock Exchange',
-                            'ETR': 'Deutsche Boerse Frankfurt Stock Exchange',
-                            'AMS': 'Euronext Amsterdam',
-                            'EBR': 'Euronext Brussels',
-                            'ELI': 'Euronext Lisbon',
-                            'EPA': 'Euronext Paris',
-                            'LON': 'London Stock Exchange',
-                            'MCX': 'Moscow Exchange',
-                            'NASDAQ': 'NASDAQ Exchange',
-                            'CPH': 'NASDAQ OMX Copenhagen',
-                            'HEL': 'NASDAQ OMX Helsinki',
-                            'ICE': 'NASDAQ OMX Iceland',
-                            'STO': 'NASDAQ OMX Stockholm',
-                            'NSE': 'National Stock Exchange of India',
-                            'NYSE': 'New York Stock Exchange',
-                            'SGX': 'Singapore Exchange',
-                            'SHA': 'Shanghai Stock Exchange',
-                            'SHE': 'Shenzhen Stock Exchange',
-                            'TPE': 'Taiwan Stock Exchange',
-                            'TYO': 'Tokyo Stock Exchange'}
+    _ALPHA_VANTAGE_DIGITAL_CURRENCY_LIST = "https://www.alphavantage.co/digital_currency_list/"
 
     def __init__(self, key=None, retries=5, output_format='json', treat_info_as_error=True):
         """ Initialize the class
@@ -54,7 +31,8 @@ def __init__(self, key=None, retries=5, output_format='json', treat_info_as_erro
             output_format:  Either 'json' or 'pandas'
         """
         if key is None:
-            raise ValueError('Get a free key from the alphavantage website: https://www.alphavantage.co/support/#api-key')
+            raise ValueError(
+                'Get a free key from the alphavantage website: https://www.alphavantage.co/support/#api-key')
         self.key = key
         self.retries = retries
         self.output_format = output_format
@@ -94,7 +72,8 @@ def _call_api_on_func(cls, func):
             # Asumme most of the cases have a mixed between args and named
             # args
             positional_count = len(argspec.args) - len(argspec.defaults)
-            defaults = dict(zip(argspec.args[positional_count:], argspec.defaults))
+            defaults = dict(
+                zip(argspec.args[positional_count:], argspec.defaults))
         except TypeError:
             if argspec.args:
                 # No defaults
@@ -119,7 +98,8 @@ def _call_wrapper(self, *args, **kwargs):
             # Form the base url, the original function called must return
             # the function name defined in the alpha vantage api and the data
             # key for it and for its meta data.
-            function_name, data_key, meta_data_key = func(self, *args, **kwargs)
+            function_name, data_key, meta_data_key = func(
+                self, *args, **kwargs)
             url = "{}function={}".format(AlphaVantage._ALPHA_VANTAGE_API_URL,
                                          function_name)
             for idx, arg_name in enumerate(argspec.args[1:]):
@@ -151,7 +131,8 @@ def _output_format(cls, func, override=None):
         """
         @wraps(func)
         def _format_wrapper(self, *args, **kwargs):
-            json_response, data_key, meta_data_key = func(self, *args, **kwargs)
+            json_response, data_key, meta_data_key = func(
+                self, *args, **kwargs)
             data = json_response[data_key]
             if meta_data_key is not None:
                 meta_data = json_response[meta_data_key]
@@ -221,26 +202,13 @@ def _handle_api_call(self, url):
         response = urlopen(url)
         url_response = response.read()
         json_response = loads(url_response)
-        
+
         if not json_response:
-            raise ValueError('Error getting data from the api, no return was given.')
+            raise ValueError(
+                'Error getting data from the api, no return was given.')
         elif "Error Message" in json_response:
             raise ValueError(json_response["Error Message"])
         elif "Information" in json_response and self.treat_info_as_error:
             raise ValueError(json_response["Information"])
-
-        return json_response
-
-    def is_exchange_supported(self, exchange_name):
-        """
-            Get if a specific global exchange type is supported by this library
 
-            Keyword Arguments:
-                exchange_name: The exchange type to check for
-            Returns:
-                The description of the given key or None
-        """
-        try:
-            return AlphaVantage._EXCHANGE_SUPPORTED[exchange_name]
-        except KeyError:
-            return None
+        return json_response

alpha_vantage/cryptocurrencies.py

@@ -0,0 +1,95 @@
+from .alphavantage import AlphaVantage as av
+
+
+class CryptoCurrencies(av):
+    """This class implements all the crypto currencies api calls
+    """
+
+    @av._output_format
+    @av._call_api_on_func
+    def get_currency_exchange_rate(self, from_currency, to_currency):
+        """ Returns the realtime exchange rate for any pair of digital
+        currency (e.g., Bitcoin) or physical currency (e.g., USD).
+
+        Keyword Arguments:
+            from_currency: The currency you would like to get the exchange rate
+            for. It can either be a physical currency or digital/crypto currency.
+            For example: from_currency=USD or from_currency=BTC.
+            to_currency: The destination currency for the exchange rate.
+            It can either be a physical currency or digital/crypto currency.
+            For example: to_currency=USD or to_currency=BTC.
+        """
+        _FUNCTION_KEY = 'CURRENCY_EXCHANGE_RATE'
+        return _FUNCTION_KEY, 'Realtime Currency Exchange Rate', None
+
+    @av._output_format
+    @av._call_api_on_func
+    def get_digital_currency_intraday(self, symbol, market):
+        """ Returns the intraday (with 5-minute intervals) time series for a
+        digital currency (e.g., BTC) traded on a specific market
+        (e.g., CNY/Chinese Yuan), updated realtime. Prices and volumes are
+        quoted in both the market-specific currency and USD.
+
+        Keyword Arguments:
+            symbol: The digital/crypto currency of your choice. It can be any
+            of the currencies in the digital currency list. For example:
+            symbol=BTC.
+            market: The exchange market of your choice. It can be any of the
+            market in the market list. For example: market=CNY.
+        """
+        _FUNCTION_KEY = 'DIGITAL_CURRENCY_INTRADAY'
+        return _FUNCTION_KEY, 'Time Series (Digital Currency Intraday)', 'Meta Data'
+
+    @av._output_format
+    @av._call_api_on_func
+    def get_digital_currency_daily(self, symbol, market):
+        """ Returns  the daily historical time series for a digital currency
+        (e.g., BTC) traded on a specific market (e.g., CNY/Chinese Yuan),
+        refreshed daily at midnight (UTC). Prices and volumes are quoted in
+        both the market-specific currency and USD..
+
+        Keyword Arguments:
+            symbol: The digital/crypto currency of your choice. It can be any
+            of the currencies in the digital currency list. For example:
+            symbol=BTC.
+            market: The exchange market of your choice. It can be any of the
+            market in the market list. For example: market=CNY.
+        """
+        _FUNCTION_KEY = 'DIGITAL_CURRENCY_DAILY'
+        return _FUNCTION_KEY, 'Time Series (Digital Currency Daily)', 'Meta Data'
+
+    @av._output_format
+    @av._call_api_on_func
+    def get_digital_currency_weekly(self, symbol, market):
+        """ Returns  the weekly historical time series for a digital currency
+        (e.g., BTC) traded on a specific market (e.g., CNY/Chinese Yuan),
+        refreshed daily at midnight (UTC). Prices and volumes are quoted in
+        both the market-specific currency and USD..
+
+        Keyword Arguments:
+            symbol: The digital/crypto currency of your choice. It can be any
+            of the currencies in the digital currency list. For example:
+            symbol=BTC.
+            market: The exchange market of your choice. It can be any of the
+            market in the market list. For example: market=CNY.
+        """
+        _FUNCTION_KEY = 'DIGITAL_CURRENCY_WEEKLY'
+        return _FUNCTION_KEY, 'Time Series (Digital Currency Weekly)', 'Meta Data'
+
+    @av._output_format
+    @av._call_api_on_func
+    def get_digital_currency_monthly(self, symbol, market):
+        """ Returns  the monthly historical time series for a digital currency
+        (e.g., BTC) traded on a specific market (e.g., CNY/Chinese Yuan),
+        refreshed daily at midnight (UTC). Prices and volumes are quoted in
+        both the market-specific currency and USD..
+
+        Keyword Arguments:
+            symbol: The digital/crypto currency of your choice. It can be any
+            of the currencies in the digital currency list. For example:
+            symbol=BTC.
+            market: The exchange market of your choice. It can be any of the
+            market in the market list. For example: market=CNY.
+        """
+        _FUNCTION_KEY = 'DIGITAL_CURRENCY_MONTHLY'
+        return _FUNCTION_KEY, 'Time Series (Digital Currency Monthly)', 'Meta Data'

alpha_vantage/sectorperformance.py

@@ -4,6 +4,7 @@
 import pandas
 import re
 
+
 class SectorPerformances(av):
     """This class implements all the sector performance api calls
     """
@@ -14,8 +15,7 @@ def percentage_to_float(self, val):
         Keyword Arguments:
             val: The string to convert
         """
-        return float(val.strip('%'))/100
-
+        return float(val.strip('%')) / 100
 
     def _output_format_sector(func, override=None):
         """ Decorator in charge of giving the output its right format, either
@@ -29,14 +29,15 @@ def _output_format_sector(func, override=None):
         """
         @wraps(func)
         def _format_wrapper(self, *args, **kwargs):
-            json_response, data_key, meta_data_key = func(self, *args, **kwargs)
+            json_response, data_key, meta_data_key = func(
+                self, *args, **kwargs)
             if isinstance(data_key, list):
                 # Replace the strings into percentage
-                data = {key: {k:self.percentage_to_float(v)
-                for k,v in json_response[key].items()} for key in data_key}
+                data = {key: {k: self.percentage_to_float(v)
+                              for k, v in json_response[key].items()} for key in data_key}
             else:
                 data = json_response[data_key]
-            #TODO: Fix orientation in a better way
+            # TODO: Fix orientation in a better way
             meta_data = json_response[meta_data_key]
             # Allow to override the output parameter in the call
             if override is None:
@@ -59,8 +60,6 @@ def _format_wrapper(self, *args, **kwargs):
                     self.output_format))
         return _format_wrapper
 
-
-
     @_output_format_sector
     @av._call_api_on_func
     def get_sector(self):
@@ -73,13 +72,13 @@ def get_sector(self):
         _FUNCTION_KEY = "SECTOR"
         # The keys for the json output
         _DATA_KEYS = ["Rank A: Real-Time Performance",
-        "Rank B: 1 Day Performance",
-        "Rank C: 5 Day Performance",
-        "Rank D: 1 Month Performance",
-        "Rank E: 3 Month Performance",
-        "Rank F: Year-to-Date (YTD) Performance",
-        "Rank G: 1 Year Performance",
-        "Rank H: 3 Year Performance",
-        "Rank I: 5 Year Performance",
-        "Rank J: 10 Year Performance"]
+                      "Rank B: 1 Day Performance",
+                      "Rank C: 5 Day Performance",
+                      "Rank D: 1 Month Performance",
+                      "Rank E: 3 Month Performance",
+                      "Rank F: Year-to-Date (YTD) Performance",
+                      "Rank G: 1 Year Performance",
+                      "Rank H: 3 Year Performance",
+                      "Rank I: 5 Year Performance",
+                      "Rank J: 10 Year Performance"]
         return _FUNCTION_KEY, _DATA_KEYS, 'Meta Data'

helpers/pipy_rst_convert.py

@@ -9,6 +9,6 @@
     parent = path.abspath(path.dirname(path.dirname(__file__)))
     readmemd_path = path.join(parent, 'README.md')
     readmerst_path = path.join(parent, 'README.rst')
-    output = pypandoc.convert_file(readmemd_path,'rst')
+    output = pypandoc.convert_file(readmemd_path, 'rst')
     with codecs.open(readmerst_path, 'w+', encoding='utf8') as f:
         f.write(output)

setup.py

@@ -11,7 +11,7 @@
 
 setup(
     name='alpha_vantage',
-    version='1.2.1',
+    version='1.3.1',
     author='Romel J. Torres',
     author_email='[email protected]',
     license='MIT',
@@ -35,7 +35,8 @@
     ],
     keywords=['stocks', 'market', 'finance', 'alpha_vantage', 'quotes',
               'shares'],
-    packages=find_packages(exclude=['helpers', 'test_alpha_vantage', 'images']),
+    packages=find_packages(
+        exclude=['helpers', 'test_alpha_vantage', 'images']),
     package_data={
         'alpha_vantage': [],
     }