stock_info added

--HG--
branch : aspn

.hgignore

@@ -0,0 +1,2 @@
+syntax: glob
+.settings

.pydevproject

@@ -3,7 +3,7 @@
 
 <pydev_project>
 <pydev_property name="org.python.pydev.PYTHON_PROJECT_INTERPRETER">Default</pydev_property>
-<pydev_property name="org.python.pydev.PYTHON_PROJECT_VERSION">python 2.6</pydev_property>
+<pydev_property name="org.python.pydev.PYTHON_PROJECT_VERSION">python 2.7</pydev_property>
 <pydev_pathproperty name="org.python.pydev.PROJECT_SOURCE_PATH">
 <path>/aspn/src</path>
 <path>/aspn/tktable</path>

src/game_of_life.py

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+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+
+import numpy as np
+
+"""
+This program is an extensible Conway's game of life. It allows to define
+different type of grid (for example 2D or 3D) and more complex rules. 
+Each grid inherits an Abstract grid that implement the method (next()) 
+to pass for the next configuration. 
+Furthermore, each element can be whatever type. In this
+example I designed Grid2DBool that represent the simple Conway's game of life,
+but could be possible to develop and easily implement more complex grids and
+rules.
+
+Note:
+The demo save also the animation in a file .mp4 and plot it through pyplot.
+The demo could take long time because of storing all the configurations before
+showing the animation. Therefore, the visualization can be improved using other
+libraries (as wxpython) that paint the configuration of the grid once it's
+created.
+With a more complex view it's convenient to apply MVC pattern declaring the
+model AbstractGrid as the Observable class.
+
+@author Filippo Squillace
+@date 02/12/2011
+@version 0.0.5
+"""
+
+class AbstractGrid():
+    """
+    This class represents the abstract grid that implement 
+    the template method to generate the next configuration. The rules are
+    definied in the abstract method next_state() and it's not
+    implemented in this class because depends on the structure of the matrix
+    and the type of elements in the grid.
+    """
+    def __init__(self):
+        self.matrix = np.array([], dtype=bool)
+    
+    def __str__(self):
+        return self.matrix.__str__()
+
+    ####### Abstract methods ########
+    def next_state(self, coords, el):
+        raise NotImplementedError()
+    def is_done(self):
+        raise NotImplementedError()
+    ################################
+
+    def add_element(self, coords, el):
+        self.matrix[coords] = el
+
+    def next(self):
+        # copy the matrix
+        old_matrix = self.matrix.copy()
+        itr = self.matrix.flat
+        coords = itr.coords
+        for el in itr:
+            old_matrix[coords] = self.next_state(coords, el)
+            coords = itr.coords
+
+        # copy all the modifications
+        self.matrix = old_matrix
+
+
+class Grid2D(AbstractGrid):
+
+    def __init__(self, n, m, typ=bool):
+        AbstractGrid.__init__(self)
+        self.n = n
+        self.m = m
+        self.matrix = np.array([None for x in range(n*m)], dtype=typ).reshape(n,m)
+
+class Grid2DBool(Grid2D):
+    """
+    Represents the classical Conway's game of life with 2D grid 
+    and each element can be either True (alive) or Fase (death)
+    Params:
+    n - number of rows
+    m - number of columns
+    """
+    def __init__(self, n, m):
+        Grid2D.__init__(self, n, m, bool)
+
+    def add_element(self, x, y):
+        t = (x, y)
+        Grid2D.add_element(self, t, True)
+
+    def next_state(self, coords, el):
+        # Gets all information from the neighbors
+        (x, y) = coords
+        neighbors = 0
+        if x==0:
+            x1=0
+        else:
+            x1=x-1
+        if x==self.n-1:
+            x2=self.n-1
+        else:
+            x2=x+1
+
+        if y==0:
+            y1=0
+        else:
+            y1=y-1
+        if y==self.m-1:
+            y2=self.m-1
+        else:
+            y2=y+1
+
+        for n in self.matrix[x1:x2+1, y1:y2+1].flat:
+            if n:
+                neighbors = neighbors + 1
+
+        # Excludes the main element
+        if el:
+            neighbors = neighbors - 1
+        
+        if el: # el alives
+            if neighbors==2 or neighbors==3:
+                return True
+            if neighbors<2 or neighbors>3:
+                return False
+        else: # el death
+            if neighbors==3:
+                return True
+    
+    def is_done(self):
+        return not self.matrix.max() # there is no True
+
+
+def light_spaceship(g, x, y, invert=False):
+    """
+    Puts the lightweight spaceship right in the grid starting from icoords
+    """
+    if not invert:
+        g.add_element(x,y)
+        g.add_element(x+2,y)
+        g.add_element(x+3,y+1)
+        g.add_element(x+3,y+2)
+        g.add_element(x+3,y+3)
+        g.add_element(x+3,y+4)
+        g.add_element(x+2,y+4)
+        g.add_element(x+1,y+4)
+        g.add_element(x,y+3)
+    else:
+        g.add_element(x,y)
+        g.add_element(x+2,y)
+        g.add_element(x+3,y-1)
+        g.add_element(x+3,y-2)
+        g.add_element(x+3,y-3)
+        g.add_element(x+3,y-4)
+        g.add_element(x+2,y-4)
+        g.add_element(x+1,y-4)
+        g.add_element(x,y-3)
+
+
+if __name__ == '__main__':
+
+    import matplotlib.pyplot as plt
+    import matplotlib.animation as animation
+
+    n = 50
+    
+    g = Grid2DBool(n, n)
+
+    light_spaceship(g, 5,2)
+    light_spaceship(g, 25,2)
+    light_spaceship(g, 45,2)
+    light_spaceship(g, 5,40, True)
+    light_spaceship(g, 25,40, True)
+    light_spaceship(g, 45,40, True)
+
+
+
+    x = np.arange(0, n+1)
+    y = np.arange(0, n+1)
+    X,Y = np.meshgrid(x,y)
+    ims = []
+    ims.append((plt.pcolor(X, Y, g.matrix),))
+    
+    counter = 0
+    while(not g.is_done() and counter < 100):
+        g.next()
+        ims.append((plt.pcolor(X, Y, g.matrix),))
+        counter = counter + 1
+    
+    fig = plt.figure(1)
+    im_ani = animation.ArtistAnimation(fig, ims, interval=2,\
+            repeat_delay=3000,\
+            blit=True)
+
+    im_ani.save('im.mp4')
+    plt.axis([0, n, n, 0])
+    plt.axis('off')
+    plt.show()
+	

src/stock_info.py

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+#!/usr/bin/env python
+#
+#  Copyright (c) 2007-2008, Corey Goldberg (corey@goldb.org)
+#
+#  license: GNU LGPL
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 2.1 of the License, or (at your option) any later version.
+#
+# Made into class by Alexander Wallar on December 17, 2011
+
+import urllib
+
+class StockInfo:
+    """
+    Constructor
+    """
+    def __init__(self, __symbol):
+        self.symbol = __symbol
+        
+    def __request(self, stat):
+        url = 'http://finance.yahoo.com/d/quotes.csv?s=%s&f=%s' % (self.symbol, stat)
+        return urllib.urlopen(url).read().strip().strip('"')
+    
+    def get_all(self):
+        """
+        Get all available quote data for the given ticker symbol.
+        Returns a dictionary.
+        """
+        values = self.__request(self.symbol, 'l1c1va2xj1b4j4dyekjm3m4rr5p5p6s7').split(',')
+        data = {}
+        data['price'] = values[0]
+        data['change'] = values[1]
+        data['volume'] = values[2]
+        data['avg_daily_volume'] = values[3]
+        data['stock_exchange'] = values[4]
+        data['market_cap'] = values[5]
+        data['book_value'] = values[6]
+        data['ebitda'] = values[7]
+        data['dividend_per_share'] = values[8]
+        data['dividend_yield'] = values[9]
+        data['earnings_per_share'] = values[10]
+        data['52_week_high'] = values[11]
+        data['52_week_low'] = values[12]
+        data['50day_moving_avg'] = values[13]
+        data['200day_moving_avg'] = values[14]
+        data['price_earnings_ratio'] = values[15]
+        data['price_earnings_growth_ratio'] = values[16]
+        data['price_sales_ratio'] = values[17]
+        data['price_book_ratio'] = values[18]
+        data['short_ratio'] = values[19]
+        return data
+
+    get_price = lambda self: float(self.__request('l1'))    
+    get_change = lambda self: float(self.__request('c1'))
+    get_volume = lambda self: float(self.__request('v'))
+    get_avg_daily_volume = lambda self: float(self.__request('a2'))
+    get_stock_exchange = lambda self: float(self.__request('x'))    
+    get_market_cap = lambda self: float(self.__request('j1')) 
+    get_book_value = lambda self: float(self.__request('b4'))
+    get_ebitda = lambda self: float(self.__request('j4'))
+    get_dividend_per_share = lambda self: float(self.__request('d'))
+    get_dividend_yield = lambda self: float(self.__request('y'))
+    get_earnings_per_share = lambda self: float(self.__request('e'))
+    get_52_week_high = lambda self: float(self.__request('k'))
+    get_52_week_low = lambda self: float(self.__request('j'))
+    get_50day_moving_avg = lambda self: float(self.__request('m3'))
+    get_200day_moving_avg = lambda self: float(self.__request('m4'))
+    get_price_earnings_ratio = lambda self: float(self.__request('r'))
+    get_price_earnings_growth_ratio = lambda self: float(self.__request('r5'))
+    get_price_sales_ratio = lambda self: float(self.__request('p5'))
+    get_price_book_ratio = lambda self: float(self.__request('p6'))
+    get_short_ratio = lambda self: float(self.__request('s7'))
+        
+    def get_historical_prices(self, start_date, end_date):
+        """
+        Get historical prices for the given ticker symbol.
+        Date format is 'YYYYMMDD'
+    
+        Returns a nested list.
+        """
+        url = 'http://ichart.yahoo.com/table.csv?s=%s&' % self.symbol + \
+              'd=%s&' % str(int(end_date[4:6]) - 1) + \
+              'e=%s&' % str(int(end_date[6:8])) + \
+              'f=%s&' % str(int(end_date[0:4])) + \
+              'g=d&' + \
+              'a=%s&' % str(int(start_date[4:6]) - 1) + \
+              'b=%s&' % str(int(start_date[6:8])) + \
+              'c=%s&' % str(int(start_date[0:4])) + \
+              'ignore=.csv'
+        days = urllib.urlopen(url).readlines()
+        data = [day[:-2].split(',') for day in days]
+        return data