MITx: 6.00.1x Introduction to Computer Science and Programming Using Python

python_notes.py

#
### Week 1: Python Basics
#

#
# 1. Introduction to Python
#

#
# 2. Core Elements of Programs
#

#
### Week 2: Simple Programs
#

#
# 3. Simple Algorithms
#

# Reviewing Strings
s = "abc"
#    012  indexing starts at 0
len(s) # 3
s[0] # a
s[1] # b
s[3] # index out of bounds error!

# Slice string with [start:stop:step]
s = "abcdefgh"
s[::-1] # hgfedcba
s[3:6] # def
s[-1] # h

# Strings are immutable
s = "hello"
s[0] = 'y' # error!
s = 'y' + s[1:len(s)] # is allowed; creates a new object

# Strings and Loops
s = "abcdefgh"
for index in range(len(s)):
    if s[index] == 'i' or s[index] =='u':
        print("There is an i or u")
# Can also be written
for char in s:
    if char == 'i' or char == 'u'

#
# 4. Functions
#

""" Decomposition break problem into different, self-contained, pieces. Abstraction suppresses details of method to compute something
from use of that computation

Create structure with decomposition. Divide code into modules that are self-contained, used to break up code, intended to be
reusable, keep code organized and keep code coherent. Suppress details with abstraction.

Suppress details with abstraction. Think of a piece of code as black box that cannot see details, does not need/want to see details,
and hides details.

Functions have: name, parameters, docstring and body. Returns None if no return statement is given.

Keyword arguments can have default values to use if no value is supplied. """
def printName(firstName, lastName, reverse = False):
    # some code
printName('Eric', 'Grimson') # is a valid call

""" Recursion is a programming technique where a function calls itself. Must have one or more base cases that are easy to solve. """
# Multiplication example
def mult(a, b):
    if b == 1:
        return a
    else:
        return a + mult(a, b-1)

# Factorial example
def factorial(n):
    if n == 1:
        return 1
    else:
        return n* factorial(n-1)