WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
Python is a widely used high-level programming language for general-purpose programming. Python is a simple, powerful and easy to learn the programming language. It is commonly used for Web and Internet development, Scientific and Numeric computing, Business application and Desktop GUI development etc. The basic data structures in python are lists, dictionaries, tuples, strings and sets
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
Python is powerful... and fast; plays well with others; runseverywhere; is friendly & easy to learn;
is Open.These are some of the reasons people who use Python would rather not use anything else.
The Key Difference between a List and a Tuple. The main difference between lists and a tuples is the fact that lists are mutable whereas tuples are immutable. A mutable data type means that a python object of this type can be modified. Let's create a list and assign it to a variable.
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
Python is a widely used high-level programming language for general-purpose programming. Python is a simple, powerful and easy to learn the programming language. It is commonly used for Web and Internet development, Scientific and Numeric computing, Business application and Desktop GUI development etc. The basic data structures in python are lists, dictionaries, tuples, strings and sets
METHODS DESCRIPTION
copy() They copy() method returns a shallow copy of the dictionary.
clear() The clear() method removes all items from the dictionary.
pop() Removes and returns an element from a dictionary having the given key.
popitem() Removes the arbitrary key-value pair from the dictionary and returns it as tuple.
get() It is a conventional method to access a value for a key.
dictionary_name.values() returns a list of all the values available in a given dictionary.
str() Produces a printable string representation of a dictionary.
update() Adds dictionary dict2’s key-values pairs to dict
setdefault() Set dict[key]=default if key is not already in dict
keys() Returns list of dictionary dict’s keys
items() Returns a list of dict’s (key, value) tuple pairs
has_key() Returns true if key in dictionary dict, false otherwise
fromkeys() Create a new dictionary with keys from seq and values set to value.
type() Returns the type of the passed variable.
cmp() Compares elements of both dict.
Python is powerful... and fast; plays well with others; runseverywhere; is friendly & easy to learn;
is Open.These are some of the reasons people who use Python would rather not use anything else.
The Key Difference between a List and a Tuple. The main difference between lists and a tuples is the fact that lists are mutable whereas tuples are immutable. A mutable data type means that a python object of this type can be modified. Let's create a list and assign it to a variable.
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
This is the third presentation in pySIG 2015 @ BMS College of Engineering, Bangalore. The code and assignments can be found at https://github.com/pranavsb
This presentation about Python Interview Questions will help you crack your next Python interview with ease. The video includes interview questions on Numbers, lists, tuples, arrays, functions, regular expressions, strings, and files. We also look into concepts such as multithreading, deep copy, and shallow copy, pickling and unpickling. This video also covers Python libraries such as matplotlib, pandas, numpy,scikit and the programming paradigms followed by Python. It also covers Python library interview questions, libraries such as matplotlib, pandas, numpy and scikit. This video is ideal for both beginners as well as experienced professionals who are appearing for Python programming job interviews. Learn what are the most important Python interview questions and answers and know what will set you apart in the interview process.
Simplilearn’s Python Training Course is an all-inclusive program that will introduce you to the Python development language and expose you to the essentials of object-oriented programming, web development with Django and game development. Python has surpassed Java as the top language used to introduce U.S. students to programming and computer science. This course will give you hands-on development experience and prepare you for a career as a professional Python programmer.
What is this course about?
The All-in-One Python course enables you to become a professional Python programmer. Any aspiring programmer can learn Python from the basics and go on to master web development & game development in Python. Gain hands on experience creating a flappy bird game clone & website functionalities in Python.
What are the course objectives?
By the end of this online Python training course, you will be able to:
1. Internalize the concepts & constructs of Python
2. Learn to create your own Python programs
3. Master Python Django & advanced web development in Python
4. Master PyGame & game development in Python
5. Create a flappy bird game clone
The Python training course is recommended for:
1. Any aspiring programmer can take up this bundle to master Python
2. Any aspiring web developer or game developer can take up this bundle to meet their training needs
Learn more at https://www.simplilearn.com/mobile-and-software-development/python-development-training
Day 1 : Slides for my training course, Well Grounded Python Coding. I'm using PyCharm Pro and Anaconda along the course. Not much to read but it's the main material for my teaching.
Day 1 Slide Handout for my training course, Well Grounded Python Coding. I'm using PyCharm Pro and Anaconda along the course. Not much to read but it's the main material for my teaching.
Functional Python Webinar from October 22nd, 2014Reuven Lerner
Slides from my free functional Python webinar, given on October 22nd, 2014. Discussion included functional programming as a perspective, passing functions as data, and writing programs that take functions as parameters. Includes (at the end) a coupon for my new ebook, Practice Makes Python.
this document consists of the introduction to python, how to install and run it, arithmetic operations, values and types (dictionaries, lists, tuples, strings, numbers, etc.) and the formal language and natural language
Code Like Pythonista
Beautifully made PPT.
Ref. http://python.net/~goodger/projects/pycon/2007/idiomatic/handout.html
Image ref : https://pixabay.com/ko/ and https://morguefile.com/
licensed under a Creative Commons Attribution/Share-Alike (BY-SA) license.
Processing data with Python, using standard library modules you (probably) ne...gjcross
Tutorial #2 from PyCon AU 2012
You have data.
You have Python.
You also have a lot of choices about the best way to work with that data...
Ever wondered when you would use a tuple, list, dictionary, set, ordered dictionary, bucket, queue, counter or named tuple? Phew!
Do you know when to use a loop, iterator or generator to work through a data container?
Why are there so many different "containers" to hold data?
What are the best ways to work with these data containers?
This tutorial will give you all the basics to effectively working with data containers and iterators in Python. Along the way we will cover some very useful modules from the standard library that you may not have used before and will end up wondering how you ever did without them.
This tutorial is aimed at Python beginners. Bring along your laptop so you can interactively work through some of the examples in the tutorial. If you can, install ipython (http://ipython.org/) as we will use it for the demonstrations.
Getting started in Python presentation by Laban KGDSCKYAMBOGO
Python Overview and getting started in Python Language. It includes on how to install, run it and carrying out some simple python codes in different environments(IDLEs)
Top Features to Include in Your Winzo Clone App for Business Growth (4).pptxrickgrimesss22
Discover the essential features to incorporate in your Winzo clone app to boost business growth, enhance user engagement, and drive revenue. Learn how to create a compelling gaming experience that stands out in the competitive market.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Globus Connect Server Deep Dive - GlobusWorld 2024Globus
We explore the Globus Connect Server (GCS) architecture and experiment with advanced configuration options and use cases. This content is targeted at system administrators who are familiar with GCS and currently operate—or are planning to operate—broader deployments at their institution.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Understanding Globus Data Transfers with NetSageGlobus
NetSage is an open privacy-aware network measurement, analysis, and visualization service designed to help end-users visualize and reason about large data transfers. NetSage traditionally has used a combination of passive measurements, including SNMP and flow data, as well as active measurements, mainly perfSONAR, to provide longitudinal network performance data visualization. It has been deployed by dozens of networks world wide, and is supported domestically by the Engagement and Performance Operations Center (EPOC), NSF #2328479. We have recently expanded the NetSage data sources to include logs for Globus data transfers, following the same privacy-preserving approach as for Flow data. Using the logs for the Texas Advanced Computing Center (TACC) as an example, this talk will walk through several different example use cases that NetSage can answer, including: Who is using Globus to share data with my institution, and what kind of performance are they able to achieve? How many transfers has Globus supported for us? Which sites are we sharing the most data with, and how is that changing over time? How is my site using Globus to move data internally, and what kind of performance do we see for those transfers? What percentage of data transfers at my institution used Globus, and how did the overall data transfer performance compare to the Globus users?
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Paketo Buildpacks : la meilleure façon de construire des images OCI? DevopsDa...Anthony Dahanne
Les Buildpacks existent depuis plus de 10 ans ! D’abord, ils étaient utilisés pour détecter et construire une application avant de la déployer sur certains PaaS. Ensuite, nous avons pu créer des images Docker (OCI) avec leur dernière génération, les Cloud Native Buildpacks (CNCF en incubation). Sont-ils une bonne alternative au Dockerfile ? Que sont les buildpacks Paketo ? Quelles communautés les soutiennent et comment ?
Venez le découvrir lors de cette session ignite
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
2. Gimme a definition! → Tuple
• Tuple is one of python data types that categorize
as sequence and it consists of comma-
separated objects like string, number, list and
even another tuple!
• Tuple is immutable, and that’s differ it from list
• Immutable: An object with a fixed value.
Immutable objects include numbers, strings and
tuples. Such an object cannot be altered. A new
object has to be created if a different value has to
be stored. They play an important role in places
where a constant hash value is needed, for
example as a key in a dictionary.(from
docs.python.org)
3. Examples for Tuple
Try it out !
1 >>> x = ("1", 2, [3])
>>> print(x)
????
>>> type(x)
????
2 >>> a = "1"
>>> b = 2
>>> c = [3]
>>> y = a, b, c
>>> print(y)
????
>>> type(y)
????
3 >>> a = "1"
>>> y = (a)
>>> type(y)
????
>>> a = "1"
>>> y = (a,)
>>> type(y)
????
>>> print(y)
????
>>> print(y[1])
????
>>> len(y)
????
4. Tuple: Advantages???
• tuple can assigned faster than list. Can you prove it by yourself? (Try to compare with list creation code!)
• Write protected!
• Use less memory than list. Because, tuple is fixed-size and list is variable-sized.
• Can assign as key at dictionary
5. Tuple: Operations
1. Accessing Values :
• x = (1, 2, 3, 4, 5)
• x[0]
• x[len(x)-1] # or ?
2. Concatenation :
• a = (1, 2, 3)
• b = (4, 5, 6)
• c = a + b
3. Multiply :
• x = ("A",)
• x = x * 2 #??
4. Delete Tuple :
• del x[0] #??
• del x # ??
5. Comparison :
• print((1, 2) == (1, 2))
• print((1, 2) is (1, 2))
The == operator compares the values of both
the operands and checks for value equality.
Whereas is operator checks whether both the
operands refer to the same object or not.
• x = (1, 2)
• y = x
• print(x is y and x == y) #??
6. The ‘in’ operator:
• x = (1, 2)
• print(1 in x)
• print((1 and 2) in x) # print((1 or 4) in x)
7. ‘sorted’ function with ‘reverse’ parameter
6. One question?
>>> x = ("1", 2, [3])
>>> print(x)
>>> y = x[2]
>>> y.append(4)
>>> y.append(5)
>>> y.append(6)
>>> print(x)
7. List = Tuple + something
Additional to tuples:
• sort:
• x=[5,6,2,3,5]
• x.sort()
• reserve:
• x.reverse()
• copy:
• x = [1,3,6]
• y=x
• z=x.copy()
• y[1] = 888
• print(x[1]) #???
• print(z[1]) #???
• List as stack:
• append() and pop()
• del stands for delete
What is lambda?
What is list comprehension?!
8. Dictionary, Are you looking up for something?
• Dictionary consists of two main part:
• Key: What is you will save and retrieve
value with
• Value: What you want to hide with Key
• Why we used hide in above sentences?
• For creating dictionary just use this pattern:
• ‘[key]’:[value] like bellow:
• d = {‘name’:’some thing’,’age’:150}
• How to get ‘some thing’ back??
• d[0] or d[‘name’] or …
• There is no order in saving values for keys
(unlike list)
• Can we say list is a dictionary with ordered
integer as key?
• There is another way to build dictionary
with dict() constructor:
• dict([('sape', 4139), ('guido', 4127), ('jack',
4098)])
9. Dictionary
• Looping through dictionary elements:
• knights = {'gallahad': 'the pure', 'robin':
'the brave'}
• for k, v in knights.items():#(key,value)
• for v in knights.values():
• for k in knights.keys():
• zip:
• For making dictionary out of 2 list with
same size:
• questions = ['name', 'quest', 'favorite
color']
• answers = ['lancelot', 'the holy grail',
'blue']
• for a,b in zip(questions,answers):
• print("%s = %s" % (a,b))
• enumerate: (a way to make list!)
• for i, v in enumerate([‘ali’,’jack’]: