Initial commit

Data/missing.csv

@@ -0,0 +1,29 @@
+name,shares,price
+"AA",15,39.48
+"AXP",10,62.58
+"BA",5,98.31
+"C",,53.08
+"CAT",15,78.29
+"DD",10,50.75
+"DIS",50,N/A
+"GE",,37.23
+"GM",15,31.44
+"HD",20,37.67
+"HPQ",5,45.81
+"IBM",10,102.86
+"INTC",,21.84
+"JNJ",20,62.25
+"JPM",10,50.35
+"KO",5,51.65
+"MCD",,51.11
+"MMM",10,85.60
+"MO",,70.09
+"MRK",5,50.21
+"MSFT",20,30.08
+"PFE",,26.40
+"PG",5,62.79
+"T",10,40.03
+"UTX",8,69.81
+"VZ",,42.92
+"WMT",10,49.78
+"XOM",15,82.50

Data/portfolio.csv

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+name,shares,price
+"AA",100,32.20
+"IBM",50,91.10
+"CAT",150,83.44
+"MSFT",200,51.23
+"GE",95,40.37
+"MSFT",50,65.10
+"IBM",100,70.44

Data/portfolio.dat

@@ -0,0 +1,7 @@
+AA 100 32.20
+IBM 50 91.10
+CAT 150 83.44
+MSFT 200 51.23
+GE 95 40.37
+MSFT 50 65.10
+IBM 100 70.44

Data/portfolio1.dat

@@ -0,0 +1,7 @@
+AA 100 32.20
+IBM 50 91.10
+CAT 150 83.44
+MSFT 200 51.23
+GE 95 40.37
+MSFT 50 65.10
+IBM 100 70.44

Data/portfolio2.csv

@@ -0,0 +1,5 @@
+name,shares,price
+"AA",50,27.10
+"HPQ",250,43.15
+"MSFT",25,50.15
+"GE",125,52.10

Data/portfolio2.dat

@@ -0,0 +1,4 @@
+AA  50 27.10
+HPQ  250 43.15
+MSFT 25 50.15
+GE 125 52.10

Data/portfolio3.csv

@@ -0,0 +1,28 @@
+"AA",15,39.48
+"AXP",10,62.58
+"BA",5,98.31
+"C",-,53.08
+"CAT",15,78.29
+"DD",10,50.75
+"DIS",-,N/A
+"GE",-,37.23
+"GM",15,31.44
+"HD",20,37.67
+"HPQ",5,45.81
+"IBM",10,102.86
+"INTC",-,21.84
+"JNJ",20,62.25
+"JPM",10,50.35
+"KO",5,51.65
+"MCD",-,51.11
+"MMM",10,85.60
+"MO",-,70.09
+"MRK",5,50.21
+"MSFT",20,30.08
+"PFE",-,26.40
+"PG",5,62.79
+"T",10,40.03
+"UTX",8,69.81
+"VZ",-,42.92
+"WMT",10,49.78
+"XOM",15,82.50

Data/portfolio3.dat

@@ -0,0 +1,28 @@
+AA 15 39.48
+AXP 10 62.58
+BA 5 98.31
+C - 53.08
+CAT 15 78.29
+DD 10 50.75
+DIS - N/A
+GE - 37.23
+GM 15 31.44
+HD 20 37.67
+HPQ 5 45.81
+IBM 10 102.86
+INTC - 21.84
+JNJ 20 62.25
+JPM 10 50.35
+KO 5 51.65
+MCD - 51.11
+MMM 10 85.60
+MO - 70.09
+MRK 5 50.21
+MSFT 20 30.08
+PFE - 26.40
+PG 5 62.79
+T 10 40.03
+UTX 8 69.81
+VZ - 42.92
+WMT 10 49.78
+XOM 15 82.50

Data/portfolio_noheader.csv

@@ -0,0 +1,7 @@
+"AA",100,32.20
+"IBM",50,91.10
+"CAT",150,83.44
+"MSFT",200,51.23
+"GE",95,40.37
+"MSFT",50,65.10
+"IBM",100,70.44

Data/prices.csv

@@ -0,0 +1,30 @@
+"AA",9.22
+"AXP",24.85
+"BA",44.85
+"BAC",11.27
+"C",3.72
+"CAT",35.46
+"CVX",66.67
+"DD",28.47
+"DIS",24.22
+"GE",13.48
+"GM",0.75
+"HD",23.16
+"HPQ",34.35
+"IBM",106.28
+"INTC",15.72
+"JNJ",55.16
+"JPM",36.90
+"KFT",26.11
+"KO",49.16
+"MCD",58.99
+"MMM",57.10
+"MRK",27.58
+"MSFT",20.89
+"PFE",15.19
+"PG",51.94
+"T",24.79
+"UTX",52.61
+"VZ",29.26
+"WMT",49.74
+"XOM",69.35

Data/stocksim.py

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+#!/usr/bin/env python
+# stocksim.py
+#
+# Stock market simulator.  This simulator creates stock market
+# data and provides it in several different ways:
+#
+#    1. Makes periodic updates to a log file stocklog.dat
+#
+# The purpose of this module is to provide data to the user
+# in different ways in order to write interesting Python examples
+
+import math
+import time
+import threading
+try:
+    import queue
+except ImportError:
+    import Queue as queue
+
+history_file = "dowstocks.csv"
+
+# Convert a time string such as "4:00pm" to minutes past midnight
+def minutes(tm):
+    am_pm = tm[-2:]
+    fields = tm[:-2].split(":")
+    hour = int(fields[0])
+    minute = int(fields[1])
+    if hour == 12:
+       hour = 0
+    if am_pm == 'pm':
+       hour += 12
+    return hour*60 + minute
+
+# Convert time in minutes to a format string
+def minutes_to_str(m):
+    frac,m = math.modf(m)
+    hours = m//60
+    minutes = m % 60
+    seconds = frac * 60
+    return "%02d:%02d.%02.f" % (hours,minutes,seconds)
+
+# Read the stock history file as a list of lists
+def read_history(filename):
+    result = []
+    for line in open(filename):
+        str_fields = line.strip().split(",")
+        fields = [eval(x) for x in str_fields]
+        fields[3] = minutes(fields[3])
+        result.append(fields)
+    return result
+
+# Format CSV record
+def csv_record(fields):
+    s = '"%s",%0.2f,"%s","%s",%0.2f,%0.2f,%0.2f,%0.2f,%d' % tuple(fields)
+    return s
+
+class StockTrack(object):
+    def __init__(self,name):
+        self.name    = name
+        self.history = []
+        self.price   = 0
+        self.time    = 0
+        self.index   = 0
+        self.open    = 0
+        self.low     = 0
+        self.high    = 0
+        self.volume  = 0
+        self.initial = 0
+        self.change  = 0
+        self.date    = ""
+    def add_data(self,record):
+        self.history.append(record)
+    def reset(self,time):
+        self.time = time
+        # Sort the history by time
+        self.history.sort(key=lambda t:t[3])
+        # Find the first entry who's time is behind the given time
+        self.index = 0
+        while self.index < len(self.history):
+            if self.history[self.index][3] > time:
+                break
+            self.index += 1
+        self.open = self.history[0][5]
+        self.initial = self.history[0][1] - self.history[0][4]
+        self.date = self.history[0][2]
+        self.update()
+        self.low = self.price
+        self.high = self.price
+
+    # Calculate interpolated value of a given field based on
+    # current time
+    def interpolate(self,field):
+        first = self.history[self.index][field]
+        next  = self.history[self.index+1][field]
+        first_t = self.history[self.index][3]
+        next_t = self.history[self.index+1][3]
+        try:
+            slope = (next - first)/(next_t-first_t)
+            return first + slope*(self.time - first_t)
+        except ZeroDivisionError:
+            return first
+
+    # Update all computed values
+    def update(self):
+        self.price = round(self.interpolate(1),2)
+        self.volume = int(self.interpolate(-1))
+        if self.price < self.low:
+            self.low = self.price
+        if self.price >= self.high:
+            self.high = self.price
+        self.change = self.price - self.initial
+
+    # Increment the time by a delta
+    def incr(self,dt):
+        self.time += dt
+        if self.index < (len(self.history) - 2):
+            while self.index < (len(self.history) - 2) and self.time >= self.history[self.index+1][3]:
+                self.index += 1
+        self.update()
+
+    def make_record(self):
+        return [self.name,round(self.price,2),self.date,minutes_to_str(self.time),round(self.change,2),self.open,round(self.high,2),
+                round(self.low,2),self.volume]
+
+class MarketSimulator(object):
+    def __init__(self):
+        self.stocks = { }
+        self.prices = { }
+        self.time = 0
+        self.observers = []
+    def register(self,observer):
+        self.observers.append(observer)
+
+    def publish(self,record):
+        for obj in self.observers:
+            obj.update(record)
+    def add_history(self,filename):
+        hist = read_history(filename)
+        for record in hist:
+            if record[0] not in self.stocks:
+                self.stocks[record[0]] = StockTrack(record[0])
+            self.stocks[record[0]].add_data(record) 
+
+    def reset(self,time):
+        self.time = time
+        for s in list(self.stocks.values()):
+            s.reset(time)
+
+    # Run forever.  Dt is in seconds
+    def run(self,dt):
+        for s in self.stocks:
+            self.prices[s] = self.stocks[s].price
+            self.publish(self.stocks[s].make_record())
+        while self.time < 1000:
+            for s in self.stocks:
+                self.stocks[s].incr(dt/60.0)    # Increment is in minutes
+                if self.stocks[s].price != self.prices[s]:
+                    self.prices[s] = self.stocks[s].price
+                    self.publish(self.stocks[s].make_record())
+            time.sleep(dt)
+            self.time += (dt/60.0)
+
+
+class BasicPrinter(object):
+    def update(self,record):
+        print(csv_record(record))
+
+class LogPrinter(object):
+    def __init__(self,filename):
+        self.f = open(filename,"w")
+    def update(self,record):
+        self.f.write(csv_record(record)+"\n")
+        self.f.flush()
+
+m = MarketSimulator()
+m.add_history(history_file)
+m.reset(minutes("9:30am"))
+m.register(BasicPrinter())
+m.register(LogPrinter("stocklog.csv"))
+m.run(1)
+
+
+

Data/words.txt

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+look into my eyes
+look into my eyes
+the eyes the eyes the eyes
+not around the eyes 
+don't look around the eyes
+look into my eyes you're under

Exercises/README.md

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+# Advanced Python Mastery
+
+Copyright (C) 2007-2023 
+David Beazley ([email protected]) 
+http://www.dabeaz.com
+
+Welcome to the Python Mastery course. This
+directory, `pythonmaster` is where you find support files
+related to the class exercises.  It is also where you will be doing
+your work.
+
+This course requires the use of Python 3.6 or newer.  If you are
+using Python 2, most of the material still applies, but you will
+have to make minor code modifications here and there. 
+
+- link:PythonMastery.pdf[`PythonMastery.pdf`] is a PDF that contains
+all of the presentation slides.
+
+- The link:Exercises/index.html[`Exercises/`] folder is where you
+find all the class exercises.
+
+- The `Data/` folder is where you find data files, scripts, and
+other files used by the exercises.
+
+- The `Solutions/` folder contains complete solution code for
+various exercises.  Each problem has its own directory.  For example,
+the solution to exercise 3.2 can be found in the `Solution/3_2/` directory.
+
+Every attempt has been made to make sure exercises work.  However, it's 
+possible that you will find typos or minor mistakes. If you find any
+errors, please let me know so that I can fix them for future editions
+of the course.
+
+
+
+
+