Python: Week 1

Getting Started: Installing Python 

Programming Languages

Programs are found in many places such as on your computer, your cell phone, or on the internet. A program is a set of instructions that are run or executed. There are many programming languages and, for this course, we will use the Python programming language.

Python 

This course uses Python 3. The main Python website contains links to downloads and documentation. Here are some brief instructions:

1. Download and install the latest version of Python 3: http://www.python.org/download. (Please do not install Python 2: you need Python 3.)
   • Linux users: use your package manager to install Python 3.
   • Windows users: choose the "Python 3.3.2 Windows x86 MSI Installer" from the downloads page.
   • Mac users: choose the "Python 3.3.2 Mac OS X 64-bit/32-bit x86-64/i386 Installer" from the downloads page, unless you have OS X version 10.5 or earlier.
2. OS X users only: install ActiveTCL 8.5.14.

The Python Standard Library contains descriptions of many Python features. It contains much more information than we will be able to cover in this course, and may seem overwhelming at first, but if you continue to program in Python after this course you'll find it useful.
The programming environment we use is IDLE, the software we use to write Python programs. IDLE comes with Python.

The Python Visualizer

We provide software that helps you visualize program execution. We introduce this in our week 2 video lectures.

• The Python Visualizer, written by Philip Guo.

Textbook: Practical Programming

This course is intended to be self-contained. However, should you want more reading material with additional examples and exercises, our textbook follows the syllabus quite closely. You can choose to purchase an electronic version (PDF, ePub, mobi) instead of a paper book. The price for the electronic version is $25 USD.

• Practical Programming (2nd edition): An Introduction to Computer Science Using Python

 

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Python as a Calculator

Arithmetic Operators

Operator	Operation	Expression	English description	Result
+	addition	11 + 56	11 plus 56	67
-	subtraction	23 - 52	23 minus 52	-29
*	multiplication	4 * 5	4 multiplied by 5	20
**	exponentiation	2 ** 5	2 to the power of 5	32
/	division	9 / 2	9 divided by 2	4.5
//	integer division	9 // 2	9 divided by 2	4
%	modulo (remainder)	9 % 2	9 mod 2	1

Types int and float

A type is a set of values and operations that can be performed on those values.
Two of Python's numeric types:

• int: integer
  For example: 3, 4, 894, 0, -3, -18
  
• float: floating point number (an approximation to a real number)
  For example: 5.6, 7.342, 53452.0, 0.0, -89.34, -9.5
  

Arithmetic Operator Precedence

When multiple operators are combined in a single expression, the operations are evaluated in order of precedence.

Operator	Precedence
**	highest
- (negation)
*, /, /, %
+ (addition), - (subtraction)	lowest

Syntax and Semantics

Syntax: the rules that describe valid combinations of Python symbols
Semantics: the meaning of a combination of Python symbols is the meaning of an instruction — what a particular combination of symbols does when you execute it.

Errors

A syntax error occurs when we an instruction with invalid syntax is executed. For example:

>>> 3) + 2 * 4
SyntaxError: invalid syntax

A semantic error occurs when an instruction with invalid semantics is executed. For example:

>>> 89.4 / 0
Traceback (most recent call last):
  File "", line 1, in
    89.4 / 0
ZeroDivisionError: float division by zero 

  
  

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Python and Computer Memory

Computer Memory

For the purpose of this course, you may think of computer memory as a long list of storage locations where each location is identified with a unique number and each location houses a value. This unique number is called a memory address. Typically, we will write memory addresses as a number with an "id" as a prefix to distinguish them from other numbers (for example, id201 is memory address 201).
Variables are a way to keep track of values stored in computer memory. A variable is a named location in computer memory. Python keeps variables in a separate list from values. A variable will contain a memory address, and that memory address contains the value. The variable then refers to the value. Python will pick the memory addresses for you.

Terminology

A value has a memory address.
A variable contains a memory address.
A variable refers to a value.
A variable points to a value.

Example: Value 8.5 has memory address id34.
Variable shoe_size contains memory address id34.
The value of shoe_size is 8.5.
shoe_size refers to value 8.5.
shoe_size points to value 8.5.

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Variables

Assignment statements

The general form of an assignment statement:

variable = expression

Example assignment statements:

>>> base = 20
>>> height = 12
>>> area = base * height / 2
>>> area
120.0

The rules for executing an assignment statement:

1. Evaluate the expression. This produces a memory address.
2. Store the memory address in the variable.

Variable names

The rules for legal Python names:

1. Names must start with a letter or _.
2. Names must contain only letters, digits, and _.

For Python, in most situations, the convention is to use pothole_case.

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Built-in Functions

Function Call

The general form of a function call:

function_name(arguments)

The rules for executing a function call:

1. Evaluate the arguments.
2. Call the function, passing in the argument values.

Terminology:

• Argument: a value given to a function
• Pass: to provide to a function
• Call: ask Python to evaluate a function
• Return: pass back a value

Example function calls:
>>> abs(-23) 23 >>> abs(56.24) 56.24

Function dir

Python has a set of built-in functions. To see the list of built-in functions, run dir(__builtins__):
>>> dir(__builtins__)< br/> ['ArithmeticError', 'AssertionError', 'AttributeError', 'BaseException', 'BufferError', 'BytesWarning', 'DeprecationWarning', 'EOFError', 'Ellipsis', 'EnvironmentError', 'Exception', 'False', 'FloatingPointError', 'FutureWarning', 'GeneratorExit', 'IOError', 'ImportError', 'ImportWarning', 'IndentationError', 'IndexError', 'KeyError', 'KeyboardInterrupt', 'LookupError', 'MemoryError', 'NameError', 'None', 'NotImplemented', 'NotImplementedError', 'OSError', 'OverflowError', 'PendingDeprecationWarning', 'ReferenceError', 'ResourceWarning', 'RuntimeError', 'RuntimeWarning', 'StopIteration', 'SyntaxError', 'SyntaxWarning', 'SystemError', 'SystemExit', 'TabError', 'True', 'TypeError', 'UnboundLocalError', 'UnicodeDecodeError', 'UnicodeEncodeError', 'UnicodeError', 'UnicodeTranslateError', 'UnicodeWarning', 'UserWarning', 'ValueError', 'Warning', 'ZeroDivisionError', '_', '__build_class__', '__debug__', '__doc__', '__import__', '__name__', '__package__', 'abs', 'all', 'any', 'ascii', 'bin', 'bool', 'bytearray', 'bytes', 'callable', 'chr', 'classmethod', 'compile', 'complex', 'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod', 'enumerate', 'eval', 'exec', 'exit', 'filter', 'float', 'format', 'frozenset', 'getattr', 'globals', 'hasattr', 'hash', 'help', 'hex', 'id', 'input', 'int', 'isinstance', 'issubclass', 'iter', 'len', 'license', 'list', 'locals', 'map', 'max', 'memoryview', 'min', 'next', 'object', 'oct', 'open', 'ord', 'pow', 'print', 'property', 'quit', 'range', 'repr', 'reversed', 'round', 'set', 'setattr', 'slice', 'sorted', 'staticmethod', 'str', 'sum', 'super', 'tuple', 'type', 'vars', 'zip']

Function help

To get information about a particular function, call help and pass the function as the argument. For example:
>>> help(abs) Help on built-in function abs in module builtins: abs(...) abs(number) -> number Return the absolute value of the argument.

Optional arguments

In the description of function pow below, the square brackets around [, z] indicate that the third argument is optional:
>>> help(pow) Help on built-in function pow in module builtins: pow(...) pow(x, y[, z]) -> number With two arguments, equivalent to x**y. With three arguments, equivalent to (x**y) % z, but may be more efficient (e.g. for longs). Function pow can be called with either two or three arguments:
>>> pow(2, 5) 32 >>> pow(2, 5, 3) 2

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Defining Functions

Function Definitions

The general form of a function definition:

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def function_name(parameters): body

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• def: a keyword indicating a function definition
• function_name: the function name
• parameters:
  • the parameter(s) of the function, 0 or more and are separated by a comma
  • a parameter is a variable whose value will be supplied when the function is called
• body:
  • 1 or more statements, often ending with a return statement

Example of a function definition:
def f(x): return x ** 2

return statement

The general form of a return statement:

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return expression

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The rules for executing a return statement:

1. Evaluate the expression. This produces a memory address.
2. Pass back that memory address to the caller. Exit the function.

Function Calls

Function calls are expressions and the result can be stored in a variable.
The general form of a function call:

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function_name(arguments)

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The rules for executing a function call:

1. Evaluate the arguments to produce memory addresses.
2. Store those memory addresses in the corresponding parameters.
3. Execute the body of the function.

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Example of a function definition and function calls: >>> def area(base, height): return base * height / 2 >>> area(3, 4) 6.0 >>> result = area(10, 7.45) >>> result 37.25

Saving your programs to ".py" files

We usually save our Python programs in ".py" files. A file can contain multiple function definitions and other statements. Before calling a function from a ".py" file in the shell in IDLE, you need to first execute Run -> Run Module, or else the shell will not recognize the function call.

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