Added Work directory

Notes/00_Setup.md

@@ -1,6 +1,13 @@
 # Course Setup and Overview
 
-Welcome to Practical Python Programming!
+Welcome to Practical Python Programming!   This page has some important information
+about course setup and logistics.
+
+## Course Duration and Time Requirements
+
+This course was originally given as an instructor-led in-person
+training that spanned 3 to 4 days.  To complete the course in its
+entirety, you should plan on committing 25-35 hours of work. 
 
 ## Setup and Python Installation
 
@@ -54,18 +61,30 @@ bash %
 With this option, you just won't be able to commit code changes except
 to the local copy on your machine.
 
-## File Layout
+## Coursework Layout
 
-Do all of your coding work in the `Work/` directory.   Within that directory, 
-there is a `Data/` directory.  The `Data/` directory contains a variety of
-datafiles and other scripts used during the course. You will frequently have
-to access files in `Data/`.  Course exercises are written with the assumption
-that you are creating programs in the `Work/` directory.
+Do all of your coding work in the `Work/` directory.  Within that
+directory, there is a `Data/` directory.  The `Data/` directory
+contains a variety of datafiles and other scripts used during the
+course. You will frequently have to access files located in `Data/`.
+Course exercises are written with the assumption that you are creating
+programs in the `Work/` directory.
 
-## Solutions
+## Course Order
+
+Course material should be completed in section order, starting with
+section 1.  Course exercises in later sections build upon code written in
+earlier sections.  
+
+## Solution Code
 
 The `Solutions/` directory contains full solution code to selected exercises.
-Feel free to look at this if you need a hint.
+Feel free to look at this if you need a hint.   To get the most out of the
+course, you should try to create your own solutions first.
+
+[Contents](Contents)
+
+
 
 
 

Work/Data/missing.csv

@@ -0,0 +1,8 @@
+name,shares,price
+"AA",100,32.20
+"IBM",50,91.10
+"CAT",150,83.44
+"MSFT",,51.23
+"GE",95,40.37
+"MSFT",50,65.10
+"IBM",,70.44

Work/Data/portfolio.csv

@@ -0,0 +1,8 @@
+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

Work/Data/portfolio.dat

@@ -0,0 +1,8 @@
+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

Work/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

Work/Data/portfolioblank.csv

@@ -0,0 +1,16 @@
+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
+

Work/Data/portfoliodate.csv

@@ -0,0 +1,8 @@
+name,date,time,shares,price
+"AA","6/11/2007","9:50am",100,32.20
+"IBM","5/13/2007","4:20pm",50,91.10
+"CAT","9/23/2006","1:30pm",150,83.44
+"MSFT","5/17/2007","10:30am",200,51.23
+"GE","2/1/2006","10:45am",95,40.37
+"MSFT","10/31/2006","12:05pm",50,65.10
+"IBM","7/9/2006","3:15pm",100,70.44

Work/Data/prices.csv

@@ -0,0 +1,31 @@
+"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
+

Work/Data/stocksim.py

@@ -0,0 +1,183 @@
+#!/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
+#    2. Provides stock data through an embedded HTTP server.
+#
+# 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
+
+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 = []
+    f = open(filename)
+    next(f)
+    for line in f:
+        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 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)
+
+
+   

Work/README.md

@@ -0,0 +1,8 @@
+# Work Area
+
+Do all of your coding work here, in the `Work/` directory.  A number of starting
+files have been given (`bounce.py`, `mortgage.py`, `pcost.py`, etc.) along with
+their corresponding exercise number.
+
+Many of the programs you write reference files found in the `Data/` directory.
+That is also located here.

Work/bounce.py

@@ -0,0 +1,3 @@
+# bounce.py
+#
+# Exercise 1.5

Work/fileparse.py

@@ -0,0 +1,3 @@
+# fileparse.py
+#
+# Exercise 3.3

Work/mortgage.py

@@ -0,0 +1,3 @@
+# mortgage.py
+#
+# Exercise 1.7

Work/pcost.py

@@ -0,0 +1,3 @@
+# pcost.py
+#
+# Exercise 1.27

Work/report.py

@@ -0,0 +1,3 @@
+# report.py
+#
+# Exercise 2.4