The document discusses various Python datatypes. It explains that Python supports built-in and user-defined datatypes. The main built-in datatypes are None, numeric, sequence, set and mapping types. Numeric types include int, float and complex. Common sequence types are str, bytes, list, tuple and range. Sets can be created using set and frozenset datatypes. Mapping types represent a group of key-value pairs like dictionaries.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
In this PPT you will learn how to use looping in python.
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Learn more about Python by clicking on given below link
Python Introduction- https://www.slideshare.net/RaginiJain21/final-presentation-on-python
Basic concept of Python -https://www.slideshare.net/RaginiJain21/python-second-ppt
Python Datatypes - https://www.slideshare.net/RaginiJain21/data-types-in-python-248466302
Python Library & Module - https://www.slideshare.net/RaginiJain21/python-libraries-and-modules
Basic Python Programs- https://www.slideshare.net/RaginiJain21/basic-python-programs
Python Media Libarary - https://www.slideshare.net/RaginiJain21/python-media-library
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
In this PPT you will learn how to use looping in python.
For more presentation in any subject please contact us on
raginijain0208@gmail.com.
You get a new presentation every Sunday at 10 AM.
Learn more about Python by clicking on given below link
Python Introduction- https://www.slideshare.net/RaginiJain21/final-presentation-on-python
Basic concept of Python -https://www.slideshare.net/RaginiJain21/python-second-ppt
Python Datatypes - https://www.slideshare.net/RaginiJain21/data-types-in-python-248466302
Python Library & Module - https://www.slideshare.net/RaginiJain21/python-libraries-and-modules
Basic Python Programs- https://www.slideshare.net/RaginiJain21/basic-python-programs
Python Media Libarary - https://www.slideshare.net/RaginiJain21/python-media-library
A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
Variables & Data Types In Python | EdurekaEdureka!
YouTube Link: https://youtu.be/6yrsX752CWk
(** Python Certification Training: https://www.edureka.co/python **)
This Edureka PPT on 'Variables and Data Types in Python' will help you establish a foothold on Python by helping you learn basic concepts like variables and data types. Below are the topics covered in this PPT:
Introduction To Python
Applications Of Python
Variable Declaration
Variable Data Types
Type Conversion
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A class is a code template for creating objects. Objects have member variables and have behaviour associated with them. In python a class is created by the keyword class.
An object is created using the constructor of the class. This object will then be called the instance of the class.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
Variables & Data Types In Python | EdurekaEdureka!
YouTube Link: https://youtu.be/6yrsX752CWk
(** Python Certification Training: https://www.edureka.co/python **)
This Edureka PPT on 'Variables and Data Types in Python' will help you establish a foothold on Python by helping you learn basic concepts like variables and data types. Below are the topics covered in this PPT:
Introduction To Python
Applications Of Python
Variable Declaration
Variable Data Types
Type Conversion
Python Tutorial Playlist: https://goo.gl/WsBpKe
Blog Series: http://bit.ly/2sqmP4s
Follow us to never miss an update in the future.
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Python Session - 3
Escape Sequence
Data Types
Conversion between data types
Operators
Python Numbers
Python List
Python Tuple
Python Strings
Python Set
Python Dictionary
Python is an interpreted, object-oriented programming language similar to PERL, that has gained popularity because of its clear syntax and readability.
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics.
Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together.
Python is an interpreted, object-oriented programming language similar to PERL, that has gained popularity because of its clear syntax and readability.
Python is an interpreted, object-oriented, high-level programming language with dynamic semantics.
Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together.
INTRODUCTION TO PYTHON
Python is an interpreted, object-oriented, high-level programming language
Python's simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance.
A standard distribution includes many modules
Dynamic typed Source can be compiled or run just-in-time Similar to perl, tcl, ruby
Why Python
Python works on different platforms (Windows, Mac, Linux, Raspberry Pi, etc).
Python has a simple syntax similar to the English language.
Python has syntax that allows developers to write programs with fewer lines than some other programming languages.
Python runs on an interpreter system, meaning that code can be executed as soon as it is written. This means that prototyping can be very quick.
Python can be treated in a procedural way, an object-oriented way or a functional way
Python Interfaces
IDLE : a cross-platform Python development
Python Win: a Windows only interface to Python
Python Shell running 'python' from the Command Line opens this interactive shell
IDLE — Development Environment
IDLE helps you program in Python by
color-coding your program code
debugging ' auto-indent ‘
interactive shell Python Shell
Auto indent
Example python
Print (“Hello World”)
output:
Hello World
Python Indentation
Indentation refers to the spaces at the beginning of a code line.
Where in other programming languages the indentation in code is for readability only, the indentation in Python is very important.
Python uses indentation to indicate a block of code.
Example:
if 5 > 2: print("Five is greater than two!")
Python Comments
Comments can be used to explain Python code.
Comments can be used to make the code more readable.
Comments can be used to prevent execution when testing code
Example
#This is a commentprint("Hello, World!")
Python Variables
Variables are containers for storing data values
Python has no command for declaring a variable.
A variable is created the moment you first assign a value to it
Example
x = 5y = "John"print(x)print(y)
Python - Variable Names
A variable can have a short name (like x and y) or a more descriptive name (age, carname, total_volume). Rules for Python variables:
A variable name must start with a letter or the underscore character
A variable name cannot start with a number
A variable name can only contain alpha-numeric characters and underscores (A-z, 0-9, and _ )
Variable names are case-sensitive (age, Age and AGE are three different variables)
Example
Legal variable names:
myvar = "John"my_var = "John"_my_var = "John"myVar = "John"MYVAR = "John"myvar2 = "John
Python Variables - Assign Multiple Values
Python allows you to assign values to multiple variables in one line:
Example
x, y, z = "Orange", "Banana", "Cherry"print(x)print(y)print(z)
Python - Output Variables
Python output variable function are print()
Example
x = "Python is awesome"print(x)
Python - Global Variables
Variables that are created outside of a function (as in all
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
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JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
2. Comments in Python
• Single Line Comments
• Comments are non-executable statements.
• Python compiler nor PVM will execute them.
#To find the sum of two numbers
a = 10 # store 10 into variable a
3. Comments in Python
• When we want to mark several lines as comment, then we can write the previous
block of code inside ””” (triple double quotes) or ’’’ (triple single quotes) in the
beginning and ending of the block as.
”””
Write a program to find the total marks scored by a
student in the subjects
”””
’’’
Write a program to find the total marks scored by a
student in the subjects
’’’
4. Comments in Python
• Python supports only single line comments.
• Multiline comments are not available in Python.
• Triple double quotes or triple single quotes
are actually not multiline comments but they are regular
strings with the exception that they can span
multiple lines.
• Use of ’’’ or ””” are not recommended for comments as
they internally occupy memory.
5. Variables
• In many languages, the concept of variable is
connected to memory location.
• In python, a variable is seen as a tag that is tied to
some value.
• Variable names in Python can be any length.
• It can consist of uppercase and lowercase letters (A-Z,
a-z), digits (0-9), and the underscore character (_).
• A restriction is that, a variable name can contain digits,
the first character of a variable name cannot be a
digit.
6. Datatypes in Python
• A datatype represents the type of data stored
into a variable or memory.
• The datatypes which are already avaiable in
Python language are called Built-in datatypes.
• The datatypes which are created by the
programmers are called User-Defined
datatypes.
8. None Type
• ‘None’ datatype represents an object that does not contain
any value.
• In Java, it is called ‘Null’ Object’, but in Python it is called
‘None’ object.
• In Python program, maximum of only one ‘None’ object is
provided.
• ‘None’ type is used inside a function as a default value of the
arguments.
• When calling the function, if no value is passed, then the
default value will be taken as ‘None’.
• In Boolean expressions, ‘None’ datatype is represents ‘False’
10. int Datatype
• The int datatype represents an integer number.
• An integer number is a number without any
decimal point or fraction part.
•
int datatype supports both negative and positive
integer numbers.
• It can store very large integer numbers
conveniently.
a = 10
b = -15
11. Float datatype
• The float datatype represents floating point numbers.
• A floating point number is a number that contains a decimal
point.
#For example : 0.5, -3.4567, 290.08,0.001
num = 123.45
x = 22.55e3
#here the float value is 22.55 x 103
12. bool Datatype
• The bool datatype in Python represents
boolean values.
• There are only two boolean values True or
False that can be represented by this
datatype.
• Python internally represents True as 1 and
False as 0.
15. Print Statement
>>> print "Hello,","I","am",“Python"
Hello, I am Python
>>> print “Python","is",27,"years","old"
Python is 27 years old
>>> print 1,2,3,4,5,6,7,8,9,0
1 2 3 4 5 6 7 8 9 0
16. Print Statement
>>> print "Hello Python, " + "How are you?"
Hello Python, How are you?
>>> print "I am 20 Years old " + "and" + " My friend is 21 years old.“
I am 20 Years old and My friend is 21 years old.
17. Sequences in Python
• A sequence represents a group of elements or items.
• There are six types of sequences in Python
– str
– bytes
– bytearray
– list
– tuple
– range
18. str datatype
• A string is represented by a group of characters. Strings are
enclosed in single quotes or double quotes.
• We can also write string inside “““ (triple double quotes) or ‘‘‘
(single double quotes)
str = “Welcome to TMES”
str = ‘Welcome to TMES’
str1 = “““ This is book on python which discusses all the topics of Core python
in a very lucid manner.”””
str1 = ‘‘‘This is book on python which discusses all the topics of Core python in
a very lucid manner.’’’
19. str datatype
str1 = “““ This is ‘Core Python’ book.”””
print(str1) # This is ‘Core Python’ book.
str1 = ‘‘‘This is ‘Core Python’ book.’’’
print(str1) # This is ‘Core Python’ book.
s = ‘Welcome to Core Python’
print(s[0]) #display 0th character from s
W
print(s[3:7]) #display from 3rd to 6th character
come
print(s[11:]) #display from 11th characters onwards till end.
Core Python
print(s[-1]) #display first character from the end
n
20. str datatype
• The repetition operator is denoted by ‘*’ symbol and useful to
repeat the string for several times. For example s * n repeats
the string for n times.
print(s*2)
Welcome to Core PythonWelcome to Core Python
21. bytes Datatype
• A byte number is any positive integer from 0 to
255.
• Bytes array can store numbers in the range from
0 to 255 and it cannot even storage.
• We can modify or edit any element in the bytes
type array.
elements = [10, 20, 0, 40, 15] #this is a list of byte numbers
x = bytes(elements) #convert the list into byte array
print(x[10]) #display 0th element, i.e 10
22. list Datatype
• Lists in Python are similar to arrays in C or Java.
• The main difference between a list an array is that a list can
store different types of elements, but array can store only one
type of elements.
• List can grow dynamically in memory.
• But the size of arrays is fixed and they cannot grow at
runtime.
list = [10, -20, 15.5, ‘vijay’, “Marry”]
23. list Datatype
• The slicing operation like [0:3] represents elements from 0th to
2nd positions. i.e 10,20,15.5
>>>list = [10, -20, 15.5, ‘vijay’, “Marry”]
>>>print(list)
10, -20, 15.5, ‘vijay’, “Marry”
>>> print(list[0])
10
>>>print(list[1:3])
[-20,15.5]
>>>print(list[-2])
vijay
>>>print(list*2)
[ 10, -20, 15.5, ‘vijay’, “Marry” 10, -20, 15.5, ‘vijay’, “Marry”]
24. tuple datatype
• A tuple contains a group of elements which
can be of different types.
• The elements in the tuple are separated by
commas and enclosed in parentheses().
• It is not possible to modify the tuple elements.
tpl = (10, -20, 15.5, ‘Vijay’ , “Marry”)
26. range Datatype
• The range datatype represents a sequence of
numbers.
• The numbers is the range are not modifiable.
• Range is used for repeating a for loop for a
specific number of times.
28. range Datatype
>>> r = range(30,40,2)
>>> for i in r:print(i)
30
32
34
36
38
>>> lst = list(range(10))
>>>
>>> print(lst)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
29. Sets
• A set is an unordered collection of elements muck like
a set in Mathematics.
• The order of elements is not maintained in the sets.
• It means the elements may not appear in the same
order as they are entered into the set.
• A set does not accept duplicate elements.
• There are two sub types in sets
– Set datatype
– Frozenset datatype
30. Sets
• To create a set, we should enter the elements separated by
commas inside curly braces {}.
s = {10, 20, 30, 20, 50}
>>> print(s)
{10, 20, 50, 30}
ch = set("Python")
>>> print(ch)
{'n', 'h', 't', 'o', 'P', 'y'}
>>> lst = [1,2,4,3,5]
>>> s = set(lst)
>>> print(s)
{1, 2, 3, 4, 5}
31. Sets
• To create a set, we should enter the elements separated by
commas inside curly braces {}.
s = {10, 20, 30, 20, 50}
>>> print(s)
{10, 20, 50, 30}
ch = set("Python")
>>> print(ch)
{'n', 'h', 't', 'o', 'P', 'y'}
>>> lst = [1,2,4,3,5]
>>> s = set(lst)
>>> print(s)
{1, 2, 3, 4, 5}
32. Sets
>>> print(s[0])
Traceback (most recent call last):
File "<pyshell#7>", line 1, in <module>
print(s[0])
TypeError: 'set' object does not support indexing
>>> s.update([110,200])
>>> print(s)
{1, 2, 3, 4, 5, 200, 110}
>>> s.remove(4)
>>> print(s)
{1, 2, 3, 5, 200, 110}
33. frozenset Datatype
• The frozenset datatype is same as the set datatype.
• The main difference is that the elements in the set datatype
can be modified.
• The elements of the frozenset cannot be modified.
>>> s = {20,40,60,10,30,50}
>>> print(s)
{40, 10, 50, 20, 60, 30}
>>> fs = frozenset(s)
>>> print(s)
{40, 10, 50, 20, 60, 30}
34. frozenset Datatype
• The frozenset datatype is same as the set datatype.
• The main difference is that the elements in the set datatype can be
modified.
• The elements of the frozenset cannot be modified.
>>> s = {20,40,60,10,30,50}
>>> print(s)
{40, 10, 50, 20, 60, 30}
>>> fs = frozenset(s)
>>> print(s)
{40, 10, 50, 20, 60, 30}
>>> fs = frozenset("Python")
>>> print(fs)
frozenset({'n', 'h', 't', 'o', 'P', 'y'})
35. What is ?
• Mapping Types
• Literals
• type function