Fundamentals of Python Programming

Fundamentals of Python
Programming

Introduction to python programming
• High level, interpreted language
• Object-oriented
• General purpose
• Web development (like: Django and Bottle),
• Scientific and mathematical computing (Orange, SciPy, NumPy)
• Desktop graphical user Interfaces (Pygame, Panda3D).

• Other features of python includes the following:
• Simple language which is easier to learn
• Free and open source
• Portability
• Extensible and embeddable
• Standard large library

• Created by Guido van Rossum in 1991
• Why the name Python?
• Not after a dangerous snake.
• Rossum was fan of a comedy series from late seventies.
• The name "Python" was adopted from the same series "Monty Python's
Flying Circus".

Reasons to Choose Python as First Language
• Simple Elegant Syntax
• Not overly strict
• Expressiveness of the language
• Great Community and Support

Installation of Python in Windows
• Go to Download Python page on the official site
(https://www.python.org/downloads/) and click Download Python
3.6.5 (You may see different version name)
• When the download is completed, double-click the file and follow the
instructions to install it.
• When Python is installed, a program called IDLE is also installed along
with it. It provides graphical user interface to work with Python.

• Open IDLE, Write the following code below and press enter.
print("Hello, World!")
• To create a file in IDLE, go to File > New Window (Shortcut: Ctrl+N).
• Write Python code and save (Shortcut: Ctrl+S) with .py file extension
like: hello.py or your-first-program.py
print("Hello, World!")
• Go to Run > Run module (Shortcut: F5) and you can see the output.

Fundamentals of Python Programming

Few Important Things to Remember
• To represent a statement in Python, newline (enter) is used.
• Use of semicolon at the end of the statement is optional (unlike
languages like C/C++)
• In fact, it's recommended to omit semicolon at the end of the
statement in Python
• Instead of curly braces { }, indentations are used to represent a block

Python Keywords
• Keywords are the reserved words(can not be used as a identifier) in
Python
• Are case sensitive

Python Identifiers
• Name given to entities like class, functions, variables etc. in Python
• Rules for writing identifiers
• Can be a combination of letters in lowercase (a to z) or uppercase (A to Z) or
digits (0 to 9) or an underscore (_)
• myClass, var_1 and print_this_to_screen, all are valid examples
• Cannot start with a digit
• 1variable is invalid, but variable1 is perfectly fine
• Keywords cannot be used as identifiers
• Cannot use special symbols like !, @, #, $, % etc. in our identifier
• Can be of any length.

Things to care about
• Python is a case-sensitive language.
• Variable and variable are not the same.
• Multiple words can be separated using an underscore,
this_is_a_long_variable
• Can also use camel-case style of writing, i.e., capitalize every first
letter of the word except the initial word without any spaces
• camelCaseExample

Python Statement
• Instructions that a Python interpreter can execute are called
statements.
• Two types
• Single line statement:
• For example, a = 1 is an assignment statement
• Multiline statement:
• In Python, end of a statement is marked by a newline character.
• So, how to make multiline statement?

• Technique1:
• make a statement extend over multiple lines with the line continuation
character ().
• For example:
a = 1 + 2 + 3 +
4 + 5 + 6 +
7 + 8 + 9

• Technique2:
• make a statement extend over multiple lines with the parentheses ( )
• For example:
a = (1 + 2 + 3 +
4 + 5 + 6 +
7 + 8 + 9)

• Technique3:
• make a statement extend over multiple lines with the brackets [ ] and braces {
}.
• For example:
colors = ['red',
'blue',
'green']

• We could also put multiple statements in a single line using
semicolons, as follows
a = 1; b = 2; c = 3

Python Indentation
• Most of the programming languages like C, C++, Java use braces { } to
define a block of code
• Python uses indentation
• A code block (body of a function, loop etc.) starts with indentation
and ends with the first un-indented line

Error due to incorrect indentation

Python Comments
• To make the code much more readable.
• Python Interpreter ignores comment.
• Two types of comment is possible in python:
• Single line comment and
• Multi-line comment

Single line comment
• In Python, we use the hash (#) symbol to start writing a comment.
• It extends up to the newline character

Multi-line comments
• Two way:
• By using # sign at the beginning of each line
#This is a long comment
#and it extends
#to multiple lines
• By using either ‘ ‘ ‘ or “ “ “ (most common)
"""This is also a
perfect example of
multi-line comments"""

Python Variable
• a variable is a named location used to store data in the memory.
• Alternatively, variables are container that hold data which can be
changed later throughout programming

Declaring Variables
• In Python, variables do not need declaration to reserve memory
space.
• The "variable declaration" or "variable initialization" happens
automatically when we assign a value to a variable.
• We use the assignment operator = to assign the value to a variable.

Assigning same value to the multiple variable

Assigning multiple values to multiple variables

Constants
• Value that cannot be altered by the program during normal
execution.
• In Python, constants are usually declared and assigned on a module
• And then imported to the file

Rules and Naming convention for variables
and constants
• Create a name that makes sense. Suppose, vowel makes more sense
than v.
• Use camelCase notation to declare a variable
• For example: myName, myAge, myAddress
• Use capital letters where possible to declare a constant
• For example: PI,G,MASS etc.

• Never use special symbols like !, @, #, $, %, etc.
• Don't start name with a digit.
• Constants are put into Python modules
• Constant and variable names should have combination of letters in
lowercase (a to z) or uppercase (A to Z) or digits (0 to 9) or an
underscore (_).
• For example: snake_case, MACRO_CASE, camelCase, CapWords

Literals
• Literal is a raw data given in a variable or constant. In Python, there
are various types of literals they are as follows:
• Numeric literals
• String literals
• Boolean literals
• Special literals

Data Types
• In python data types are classes and variables are instance (object) of
these classes
• Different types of data types in python are:
• Python numbers
• Python lists
• Python tuples
• Python strings
• Python sets
• Python dictionary

Python List
• Ordered sequence of items
• Can contain heterogeneous data
• Syntax:
• Items separated by commas are enclosed within brackets [ ]
• Example: a= [1,2.2,'python']

Extracting elements from the list

• Note: Lists are mutable, meaning, value of elements of a list can be
altered.

Python Tuple
• Same as list but immutable.
• Used to write-protect the data
• Syntax:
• Items separated by commas are enclosed within brackets ( )
• Example:
• t = (5,'program', 1+3j)

Python Strings
• use single quotes or double quotes to represent strings.
• Multi-line strings can be denoted using triple quotes, ''' or """.
• Example:
s = "This is a string"
s = '''a multiline
string’’’
• Strings are also immutable.

Python Set
• Unordered collection of unique items
• defined by values separated by comma inside braces { }

• Set have unique values. They eliminate duplicates.
• Example:

• Since, set are unordered collection, indexing has no meaning.
• Hence the slicing operator [] does not work.
• Example:

Python Dictionary
• An unordered collection of key-value pairs.
• Must know the key to retrieve the value.
• Are defined within braces {} with each item being a pair in the form
key: value
• Key and value can be of any type

Conversion between data types
• Conversion can be done by using different types of type conversion
functions like:
• int(),
• float(),
• str() etc.

convert one sequence to another

• To convert to dictionary, each element must be a pair:

Python Type Conversion and Type Casting
• The process of converting the value of one data type (integer, string,
float, etc.) to another data type is type conversion
• Python has two types of type conversion.
• Implicit Type Conversion
• Explicit Type Conversion

• Type Conversion is the conversion of object from one data type to
another data type
• Implicit Type Conversion is automatically performed by the Python
interpreter
• Python avoids the loss of data in Implicit Type Conversion
• Explicit Type Conversion is also called Type Casting, the data types of
object are converted using predefined function by user
• In Type Casting loss of data may occur as we enforce the object to
specific data type

Implicit Type Conversion
• Automatically converts one data type to another data type
• Always converts smaller data type to larger data type to avoid the loss
of data

Problem in implicit type conversion

Explicit Type Conversion
• Users convert the data type of an object to required data type.
• Predefined functions like int(), float(), str(), etc. are to perform explicit
type conversion
• Is also called typecasting because the user casts (change) the data
type of the objects.
• Syntax :
• (required_datatype)(expression)
• Int(b)

Python Input, Output and Import
• Widely used functions for standard input and output operations are:
• print() and
• input()

Python Output Using print() function

Output formatting
• Can be done by using the str.format() method
• Is visible to any string object
• Here the curly braces {} are used as placeholders. We can specify the
order in which it is printed by using numbers (tuple index).

• We can even use keyword arguments to format the string

• We can even format strings like the old printf() style used in C
• We use the % operator to accomplish this

Input() function
• input() function to take the input from the user.
• The syntax for input() is :
• input([prompt])
• where prompt is the string we wish to display on the screen.
• It is optional

• Entered value 10 is a string, not a number.
• To convert this into a number we can use int() or float() functions
• This same operation can be performed using the eval(). It can
evaluate expressions, provided the input is a string.

Python Import
• When our program grows bigger, it is a good idea to break it into
different modules.
• A module is a file containing Python definitions and statements.
• Python modules have a filename and end with the extension .py
• Definitions inside a module can be imported to another module or
the interactive interpreter in Python
• We use the import keyword to do this

• import some specific attributes and functions only, using the from
keyword.

Python Operators
• Operators are special symbols in Python that carry out arithmetic or
logical computation.
• The value that the operator operates on is called the operand.
• For example:
>>> 2+3
5
• Here, + is the operator that performs addition.
• 2 and 3 are the operands and 5 is the output of the operation.

Bitwise operators
• Bitwise operators act on operands as if they were string of binary
digits. It operates bit by bit, hence the name.
• For example, 2 is 10 in binary and 7 is 111.
• In the table below: Let x = 10 (0000 1010 in binary) and y = 4 (0000
0100 in binary)

Assignment operators
• Assignment operators are used in Python to assign values to
variables.
• a = 5 is a simple assignment operator that assigns the value 5 on the
right to the variable a on the left.
• There are various compound operators in Python like a += 5 that adds
to the variable and later assigns the same.
• It is equivalent to a = a + 5.

Special operators
• identity operator
• membership operator

Identity operators
• is and is not are the identity operators in Python.
• They are used to check if two values (or variables) are located on the
same part of the memory.
• Two variables that are equal does not imply that they are identical.

Membership operators
• in and not in are the membership operators in Python
• They are used to test whether a value or variable is found in a
sequence (string, list, tuple, set and dictionary).
• In a dictionary we can only test for presence of key, not the value

Python Namespace and Scope
• Name (also called identifier) is simply a name given to objects.
• Everything in Python is an object
• Name is a way to access the underlying object.
• For example:
• when we do the assignment a = 2, here 2 is an object stored in memory and a
is the name we associate it with
• We can get the address (in RAM) of some object through the built-in function,
id()

A name could refer to any type of object

Functions are objects too, so a name can
refer to them as well

What is a Namespace in Python?
• namespace is a collection of names.
• Help to eliminate naming collision/naming conflict

• A namespace containing all the built-in names is created when we
start the Python interpreter and exists as long we don't exit
• Each module creates its own global namespace
• Modules can have various user defined functions and classes.
• A local namespace is created when a function is called, which has all
the names defined in it.
• Similar, is the case with class

Python Variable Scope
• All namespaces may not be accessible from every part of the program
• Scope is the portion of the program from where a namespace can be
accessed directly without any prefix

• At any given moment, there are at least three nested scopes.
• Scope of the current function which has local names
• Scope of the module which has global names
• Outermost scope which has built-in names
• When a reference is made inside a function, the name is searched in
the local namespace, then in the global namespace and finally in the
built-in namespace.
• If there is a function inside another function, a new scope is nested
inside the local scope.

Fundamentals of Python Programming

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