2. What is Python?
Python is an interpreted, high-level and general-purpose programming language.
3. Python
Overview
• Python is a high-level, interpreted,
interactive and object oriented-scripting
language.
• Python was designed to be highly readable
which uses English keywords frequently
where as other languages use punctuation
and it has fewer syntactical constructions
than other languages.
4. Python
Overview
• Easy-to-learn: Python has relatively few keywords, simple
structure, and a clearly defined syntax.
• Easy-to-read: Python code is much more clearly defined and
visible to the eyes.
• Easy-to-maintain: Python's success is that its source code is
fairly easy-to-maintain.
• A broad standard library: One of Python's greatest strengths is
the bulk of the library is very portable and cross-platform
compatible on UNIX, Windows, and Macintosh.
• Interactive Mode: Support for an interactive mode in which you
can enter results from a terminal right to the language, allowing
interactive testing and debugging of snippets of code.
6. Apps built
using Python
• Instagram
• YouTube
• DropBox
• Google
• Uber
• Lyft
• Facebook
• Netflix
• Quora , Instagram, Spotify
7. Applications of
Python
• Web Development
• Game Development
• Scientific and Numeric Applications
• Artificial Intelligence and Machine Learning
• Desktop GUI
• Software Development
• Language Development
• Operating Systems
• Web Scraping Applications
• Image Processing and Graphic Design Applications
8. Features of
python
• It is an open-source language
• It is a high-level language
• It is interpreted
• It is both object-oriented and functional
• It is portable
• It is extensible and embeddable
• It comes with a vast collection of libraries
9. Compiling and interpreting
• Many languages require you to compile (translate) your
program into a form that the machine understands.
• Python is instead directly interpreted into machine instructions.
compile execute
output
source code
Hello.java
byte code
Hello.class
interpret
output
source code
Hello.py
10. Python
Environment
• Unix (Solaris, Linux, FreeBSD, AIX, HP/UX, SunOS, IRIX etc.)
• Win 9x/NT/2000
• Macintosh (PPC, 68K)
• OS/2
• DOS (multiple versions)
• PalmOS
• Nokia mobile phones
• Windows CE
• Acorn/RISC OS
• BeOS
• Amiga
• VMS/OpenVMS
• QNX
• VxWorks
• Psion
• Python has also been ported to the Java and .NET virtual machines.
11. Hello World- C
#include <stdio.h>
int main() {
// printf() displays the string inside quotation
printf("Hello, World!");
return 0;
}
12. Hello World- Java
class HelloWorld {
public static void main(String[] args) {
System.out.println("Hello, World!");
}
}
14. Course
Objectives
1. Describe syntax and semantics in Python
2. Illustrate different file handling operations
3. Interpret object-oriented programming in Python
4. Design GUI Applications in Python
5. Express proficiency in the handling Python
libraries for data science
6. Develop machine learning applications using
Python.
15. Syllabus
Introduction to
python
Function and File
handling
Object oriented
Programming
Graphical User
Interface and Image
processing
Numpy, Pandas,
Matplotlib, Seaborn,
Scipy
Python Applications
21. Python Identifiers:
• A Python identifier is a name used to identify a variable, function,
class, module, or other object. An identifier starts with a letter A to Z
or a to z or an underscore (_) followed by zero or more letters,
underscores, and digits (0 to 9).
• Python does not allow punctuation characters such as @, $, and %
within identifiers. Python is a case sensitive programming language.
• Thus, Manpower and manpower are two different identifiers in
Python.
22. Python Identifiers (cont’d)
• Here are following identifier naming convention for Python:
– Class names start with an uppercase letter and all other identifiers
with a lowercase letter.
– Starting an identifier with a single leading underscore indicates by
convention that the identifier is meant to be private.
– Starting an identifier with two leading underscores indicates a
strongly private identifier.
– If the identifier also ends with two trailing underscores, the identifier
is a language-defined special name.
23. Reserved Words:
and exec not
assert finally or
break for pass
class from print
continue global raise
def if return
del import try
elif in while
else is with
except lambda yield
Keywords contain lowercase letters only.
24. Lines and Indentation:
• One of the first caveats programmers encounter when learning Python is the
fact that there are no braces to indicate blocks of code for class and function
definitions or flow control. Blocks of code are denoted by line indentation,
which is rigidly enforced.
• The number of spaces in the indentation is variable, but all statements within
the block must be indented the same amount. Both blocks in this example are
fine:
if True:
print "Answer“;
print "True" ;
else:
print "Answer“;
print "False"
25. Multi-Line Statements:
• Statements in Python typically end with a new line. Python does, however, allow
the use of the line continuation character () to denote that the line should
continue. For example:
total = item_one +
item_two +
item_three
• Statements contained within the [], {}, or () brackets do not need to use the line
continuation character. For example:
days = ['Monday', 'Tuesday', 'Wednesday',
'Thursday', 'Friday']
26. Quotation in Python:
• Python accepts single ('), double (") and triple (''' or """) quotes to
denote string literals, as long as the same type of quote starts and
ends the string.
• The triple quotes can be used to span the string across multiple lines.
For example, all the following are legal:
word = 'word'
sentence = "This is a sentence."
paragraph = """This is a paragraph. It is made up
of multiple lines and sentences."""
27. Comments in Python:
• A hash sign (#) that is not inside a string literal begins a comment. All
characters after the # and up to the physical line end are part of the
comment, and the Python interpreter ignores them.
28. Using Blank Lines:
• A line containing only whitespace, possibly with a comment, is known as
a blank line, and Python totally ignores it.
• In an interactive interpreter session, you must enter an empty physical
line to terminate a multiline statement.
29. Multiple Statements on a Single Line:
• The semicolon ( ; ) allows multiple statements on the single
line given that neither statement starts a new code block.
Here is a sample snip using the semicolon:
import sys; x = 'foo'; sys.stdout.write(x + '
n')
30. Multiple Statement Groups as Suites:
Groups of individual statements making up a single code block are called suites in
Python.
Compound or complex statements, such as if, while, def, and class, are those which
require a header line and a suite.
Header lines begin the statement (with the keyword) and terminate with a colon ( : )
and are followed by one or more lines which make up the suite.
if expression :
suite
elif expression :
suite
else :
suite
31. 3. Python - Variable Types
• Variables are nothing but reserved memory locations to store values.
This means that when you create a variable you reserve some space in
memory.
• Based on the data type of a variable, the interpreter allocates memory
and decides what can be stored in the reserved memory. Therefore, by
assigning different data types to variables, you can store integers,
decimals, or characters in these variables.
32. Assigning Values to Variables:
• Python variables do not have to be explicitly declared to reserve memory
space. The declaration happens automatically when you assign a value to a
variable. The equal sign (=) is used to assign values to variables.
counter = 100 # An integer assignment
miles = 1000.0 # A floating point
name = "John" # A string
print counter
print miles
print name
33. Multiple Assignment:
You can also assign a single value to several variables simultaneously. For
example:
a = b = c = 1
a, b, c = 1, 2, "john"
35. Python Numbers:
• Number data types store numeric values. They are immutable data types,
which means that changing the value of a number data type results in a
newly allocated object.
• Number objects are created when you assign a value to them. For example:
var1 = 1
var2 = 10
Python supports four different numerical types:
• int (signed integers)
• long (long integers [can also be represented in octal and hexadecimal])
• float (floating point real values)
• complex (complex numbers)
37. Python Strings:
• Strings in Python are identified as a contiguous set of characters in between
quotation marks.
• Python allows for either pairs of single or double quotes. Subsets of strings can
be taken using the slice operator ( [ ] and [ : ] ) with indexes starting at 0 in the
beginning of the string and working their way from -1 at the end.
• The plus ( + ) sign is the string concatenation operator, and the asterisk ( * ) is
the repetition operator.
38. Example:
str = 'Hello World!'
print str # Prints complete string
print str[0] # Prints first character of the string
print str[2:5] # Prints characters starting from 3rd to 6th
print str[2:] # Prints string starting from 3rd character
print str * 2 # Prints string two times
print str + "TEST" # Prints concatenated string
Output:
Hello World!
H
llo
llo World!
Hello World!Hello World!
Hello World!TEST
39. Python Lists:
• Lists are the most versatile of Python's compound data types. A list contains
items separated by commas and enclosed within square brackets ([]).
• To some extent, lists are like arrays in C. One difference between them is that
all the items belonging to a list can be of different data type.
• The values stored in a list can be accessed using the slice operator ( [ ] and
[ : ] ) with indexes starting at 0 in the beginning of the list and working their
way to end-1.
• The plus ( + ) sign is the list concatenation operator, and the asterisk ( * ) is
the repetition operator.
40. Python Lists:
list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
tinylist = [123, 'john']
print list # Prints complete list
print list[0] # Prints first element of the list
print list[1:3] # Prints elements starting from 2nd till 3rd
print list[2:] # Prints elements starting from 3rd element
print tinylist * 2 # Prints list two times
print list + tinylist # Prints concatenated lists
Output:
['abcd', 786, 2.23, 'john', 70.2]
abcd
[786, 2.23]
[2.23, 'john', 70.2]
[123, 'john', 123, 'john']
['abcd', 786, 2.23, 'john', 70.2, 123, 'john']
41. Python Tuples:
• A tuple is another sequence data type that is like the list. A tuple
consists of a number of values separated by commas. Unlike lists,
however, tuples are enclosed within parentheses.
• The main differences between lists and tuples are: Lists are enclosed in
brackets ( [ ] ), and their elements and size can be changed, while tuples
are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be
thought of as read-only lists.
42. tuple = ( 'abcd', 786 , 2.23, 'john', 70.2 )
tinytuple = (123, 'john')
print tuple # Prints complete list
print tuple[0] # Prints first element of the list
print tuple[1:3] # Prints elements starting from 2nd till 3rd
print tuple[2:] # Prints elements starting from 3rd element
print tinytuple * 2 # Prints list two times
print tuple + tinytuple # Prints concatenated lists
OUTPUT:
('abcd', 786, 2.23, 'john', 70.2)
abcd
(786, 2.23)
(2.23, 'john', 70.2)
(123, 'john', 123, 'john')
('abcd', 786, 2.23, 'john', 70.2, 123, 'john')
Python Tuples:
43. Python Dictionary:
• Python 's dictionaries are hash table type. They work like associative
arrays or hashes found in Perl and consist of key-value pairs.
• Keys can be almost any Python type but are usually numbers or strings.
Values, on the other hand, can be any arbitrary Python object.
• Dictionaries are enclosed by curly braces ( { } ) and values can be
assigned and accessed using square braces ( [] ).
44. dict = {}
dict['one'] = "This is one"
dict[2] = "This is two“
tinydict = {'name': 'john','code':6734, 'dept': 'sales'}
print dict['one'] # Prints value for 'one' key
print dict[2] # Prints value for 2 key
print tinydict # Prints complete dictionary
print tinydict.keys() # Prints all the keys
print tinydict.values() # Prints all the values
OUTPUT:
This is one
This is two
{'dept': 'sales', 'code': 6734, 'name': 'john'}
['dept', 'code', 'name']
['sales', 6734, 'john']
Python Dictionary:
45. Data Type Conversion:
Function Description
int(x [,base]) Converts x to an integer. base specifies the base if x is a string.
long(x [,base] ) Converts x to a long integer. base specifies the base if x is a
string.
float(x) Converts x to a floating-point number.
complex(real
[,imag])
Creates a complex number.
str(x) Converts object x to a string representation.
repr(x) Converts object x to an expression string.
eval(str) Evaluates a string and returns an object.
tuple(s) Converts s to a tuple.
list(s) Converts s to a list.
set(s) Converts s to a set.
dict(d) Creates a dictionary. d must be a sequence of (key,value) tuples.
frozenset(s) Converts s to a frozen set.
chr(x) Converts an integer to a character.
unichr(x) Converts an integer to a Unicode character.
ord(x) Converts a single character to its integer value.
hex(x) Converts an integer to a hexadecimal string.
oct(x) Converts an integer to an octal string.