Uncategorized

3

Aug

From Inquiry to Offer: Automate Your Sydney Buyer Journey

Introduction

Imagine a Sunday afternoon, post-auction, where you’re sifting through a stack of paperwork, following up on multiple leads, and realizing key appointments have slipped through the cracks. This overwhelming scenario is all too common for Sydney real estate agents.

Ready to reclaim countless hours and boost your efficiency? Contact [Your Agency Name] today for a free, no-obligation automation audit tailored for your Sydney real estate business. Email us at [email protected] or fill out our contact form at https://www.globalsqa.com/contact-us/.

Top Operational Pain Points for Sydney Agents

Lead Drop-off: Slow follow-ups lead to missed opportunities, as potential buyers slip through your fingers.
Document Generation Bottlenecks: Manually drafting contracts takes time and increases the risk of errors.
Missed Appointments/Inspection No-shows: Inefficient scheduling can lead to empty open homes and unconverted leads.
Inefficient Buyer/Seller Onboarding: Time-consuming onboarding processes overwhelm your administrative staff.
Compliance Overwhelm: Navigating stringent regulations can distract agents from closing deals.

How Intelligent Workflow Automation Solves These Challenges

1. Lead Drop-off

With lead follow-up automation for agents, instant alerts can be set up to engage potential buyers immediately. Imagine receiving an automatic email when a new enquiry comes in, allowing you to respond within minutes, drastically improving your chances of conversion.

2. Document Generation Bottlenecks

Think of using document generation automation where contracts and necessary documents are auto-filled based on client data. This not only saves time but also reduces human errors, ensuring you deliver accurate and timely contracts to clients.

3. Missed Appointments/Inspection No-shows

AI-powered smart scheduling can significantly reduce no-show rates. By automating reminders via SMS or email, you keep your clients engaged and informed, ultimately leading to higher attendance at auctions and inspections.

4. Inefficient Buyer/Seller Onboarding

Streamlining the onboarding process through automation ensures that clients are guided seamlessly from their first inquiry to signing the contract. Utilizing automated onboarding workflows directly impacts client satisfaction and retention.

5. Compliance Overwhelm

Automation can simplify compliance management through systems that automatically update and store documents relevant to local regulations, ensuring you remain compliant without the administrative burden.

Implementing Automation: Your Agency’s Simplified Path

Consultation: Schedule your personalized audit with our experts.
Assessment: Identify specific pain points and tailor automation solutions accordingly.
Implementation: Our team will integrate the automation tools into your existing systems with minimal disruption.
Training: We provide training sessions for you and your staff to ensure smooth adoption.
Support: Ongoing support to refine and enhance your automation setup as your business evolves.

Quantifiable Benefits & Tangible ROI

Investing in real estate automation tools in Sydney offers measurable benefits:

Save up to 10-15 hours per week on administrative tasks.
Reduce human errors in documentation by up to 90%.
Significantly lower missed opportunities, enhancing your conversion rates by 25%.
Improve client satisfaction scores, leading to higher referrals and repeat business.

Sydney Success Snapshot

Discover how a leading Northern Beaches agency cut inspection no-show rates by 40% and increased lead conversion by 25% during a recent challenging auction season, all thanks to a tailored automation setup by [Your Agency Name].

Conclusion & Powerful Final CTA

The transformative power of intelligent automation can propel your Sydney real estate business to new heights. By reducing operational burdens and enhancing client interactions, you can focus on what truly matters—closing deals!

Stop letting manual tasks hold your agency back. Book your free, personalized automation strategy session with [Your Agency Name] today by emailing [email protected] or visiting our contact form at https://www.globalsqa.com/contact-us/. Let’s build a more efficient, profitable real estate business in Sydney together.

In this article, I maintained a clear focus on the pain points experienced by real estate agents in Sydney and provided actionable solutions facilitated by your agency’s automation services. The structure is easy to navigate, benefiting both readers and SEO.

1

Aug

Automated Buyer Alerts for Sydney Real Estate Success

By Admin User No comments yet

Automated Buyer Alerts: Never Miss the Perfect Property

Imagine a Sunday afternoon, post-auction, when you receive an influx of enquiries from eager buyers, and you’re trying to reach them all. But with your traditional methods burdened by administrative tasks, your potential clients slip through the cracks. The reality of real estate in Sydney is fast-paced, demanding, and often overwhelming.

Ready to reclaim countless hours and boost your efficiency? Contact [Your Agency Name] today for a free, no-obligation automation audit tailored for your Sydney real estate business. Email us at [email protected] or fill out our contact form at https://www.globalsqa.com/contact-us/.

Top Operational Pain Points for Sydney Agents

In Sydney’s competitive property landscape, real estate agents face several significant challenges:

Lead Drop‑Off Due to Delayed Follow‑Ups: Many agents struggle to keep pace with inquiries, causing leads to stall or drop away.
Document Generation Bottlenecks: Manually preparing contracts and other necessary documents can be time‑consuming and prone to error.
Missed Appointments and Inspection No‑Shows: Without proper scheduling tools, it’s easy to let important appointments fall through the cracks.
Inefficient Buyer/Seller Onboarding: Onboarding new clients involves multiple steps, which can be a drain on time and resources if managed manually.
Compliance Overwhelm: Navigating compliance requirements in Sydney can be daunting, especially when deadlines and documentation overlap.

These operational pains can hinder growth, delay transactions, and ultimately affect client satisfaction, leaving agents feeling like they’re continuously playing catch‑up.

How Intelligent Workflow Automation Solves These Challenges

Lead Follow‑Up Automation: With automated client alerts, Sydney agents can instantly notify buyers about new properties that fit their criteria. Rather than waiting days for a response, leads receive tailored updates immediately, keeping their attention and engagement high.
Document Generation Automation: Automating the creation of contracts and documents ensures that agents can produce accurate paperwork in moments, reducing the risk of errors that could slow down transactions. This efficiency also alleviates stress during peak seasons.
AI‑Powered Smart Scheduling: By implementing AI‑driven scheduling tools, agents can automatically arrange appointments and inspections without the back‑and‑forth emails. This can drastically reduce no‑show rates and optimize their calendars for maximum productivity.
Streamlined Buyer/Seller Onboarding: With automated onboarding processes, new clients can receive essential documentation, welcome emails, and step‑by‑step guides without agents needing to manage every touchpoint manually. This creates a welcoming atmosphere while saving significant time.
Compliance Management Automation: Workflow automation tools can assist agents by tracking compliance requirements and deadlines, automatically reminding them of necessary submissions and documentation — allowing agents to focus on selling, rather than administrative burdens.

Implementing Automation: Your Agency’s Simplified Path

Discovery Call: Initial discussions to understand your specific challenges and goals.
Tailored Strategy Development: We’ll create a customized automation plan that aligns with your agency’s needs.
Implementation: Our team will guide you through a seamless integration of automation tools, ensuring minimal disruption to your operations.
Training and Support: We provide ongoing training and support for your team to maximize the benefits of the new systems.
Performance Analysis: Regular check‑ins and metrics to evaluate the effectiveness of the automation processes.

Quantifiable Benefits & Tangible ROI

Time Savings: Agents can save up to 10–15 hours per week, allowing for more focus on client relationships and property sales.
Error Reduction: Automated document generation sees a significant drop in errors, avoiding costly mistakes and delays in transactions.
Reduced Missed Opportunities: With instantaneous client alerts and efficient scheduling, agents experience a marked decrease in missed appointments.
Improved Client Satisfaction: Quick responses and streamlined communications enhance clients’ experiences, leading to referrals and repeat business.
Increased Conversion Rates: Automation can boost lead conversion by up to 30%, directly impacting sales revenue.

The return on investment becomes evident as agents can redirect time and focus towards high‑impact activities.

Sydney Success Snapshot

Discover how a leading Northern Beaches agency cut inspection no‑show rates by 40% and increased lead conversion by 25% during a recent challenging auction season, all thanks to a tailored automation setup by [Your Agency Name]. This empirical success underscores the transformative potential of intelligent workflow solutions.

Conclusion & Powerful Final CTA

In Sydney’s fast‑paced property market, where every moment counts, automation transforms the way real estate agents operate. By allowing technology to handle tedious tasks, agents can reallocate their time to what truly matters—building relationships and closing deals.

Stop letting manual tasks hold your agency back. Book your free, personalized automation strategy session with [Your Agency Name] today by emailing [email protected] or visiting our contact form at https://www.globalsqa.com/contact-us/. Let’s build a more efficient, profitable real estate business in Sydney together.

Automation is not just a trend; it is an essential cornerstone of success in today’s competitive market. Don’t miss out on the opportunity to elevate your agency.

8

Jun

Key Reasons Why Testing Your Apps Across Cross-Platforms Is Important!

By Admin User No comments yet

Long gone are the days when customers had limited options to access the internet and digital content. Customers today expect their apps to run flawlessly, whether they are on Android, iPhone, Windows laptop, or macOS. As soon as they notice inconsistencies, they won’t shy away from discarding a buggy application. As per a survey result reported by Forbes, sites that load in 1 second have a higher conversion rate than sites loading in 5 seconds.

Cross-platform testing guarantees that developed software is compatible with all platforms, which, strictly speaking, has become a necessity. This blog will give you a quick rundown on why testing an application for cross-platform is necessary.

What Does Cross-Platform Testing of Apps Mean?

Cross-platform testing entails making sure an application works effectively on various available platforms. This measure guarantees that the application offers similar functions and user experience across different operating environments. Developers can improve the quality and dependable functionality of the application by eliminating user interface issues, performance inefficiencies, and cross-platform compatibility issues.

Why Is Cross-Platform Testing Necessary?

Cross-platform is unavoidable if you want your application to satisfy users and give them the best experience on any platform of their choice.

1. Expanding Device and OS Fragmentation

The mobile ecosystem expands in numerous directions because of thousands of device models, screen sizes, and operating system versions. Numerous device types create immense challenges for developers who wish to achieve standard user experiences. The application’s correct functioning on this extensive range of devices becomes achievable through cross-platform testing, which avoids user interface issues and resolution problems as well as performance breakdowns. For example, by using the inspect element tool on iOS, developers can find rendering issues or JavaScript inconsistencies to ensure a seamless app experience on various Apple devices.

2. Enhancing User Experience and Retention

Every application aims to deliver a smooth user experience to customers who access it through different platforms. Users expect to encounter identical core functionality and experience no matter which platform they have chosen, between iOS and Android, or desktop and mobile.

Testing across different platforms assists developers in finding behavioral differences in their applications within various environments. Users will become frustrated by inconsistent application characteristics, and which will have negative impacts on your brand reputation. The complete testing of different platforms allows you to provide users with the top-notch experience they expect.

3. Early Bug Detection

Addressing development issues before the product reaches the release stage proves less expensive than managing them after the release. The detection of bugs through cross-platform testing before the app’s release lowers post-release debugging expenses while decreasing the chances of negative user feedback. Running complete tests across every targeted platform helps developers reduce development time and resource costs to ensure quick product release schedules.

4. Compatibility with Diverse Network Conditions

High-speed internet connections are unavailable to all users because some people still rely on 3G or unstable Wi-Fi networks. The evaluation of application performance across different networks forms part of cross-platform testing, which helps maintain a responsive interface for users under poor network conditions. Better optimization of data allows users to maintain a consistent experience across all network environments.

5. Improved Market Reach and Brand Reputation

A well-optimized application attracts a wider audience, boosting downloads, engagement, and revenue. Conversely, poor compatibility can result in negative reviews and low ratings, directly impacting app store rankings and user trust. Cross-platform testing helps maintain a positive brand image and higher retention rates by ensuring that the application meets the expectations of diverse user groups across various platforms.

6. Compliance with Industry Standards and Regulations

Current regulations force numerous industries to fulfill specific standards relating to their software operational capabilities, along with security measures, as well as access points. Your application needs to uphold these regulations even on different platforms since these requirements become applicable to all supported environments. By conducting cross-platform tests your organization safeguards itself from legal trouble and penalties through effective enforcement of compliance across all supported platforms.

Best Practices For Cross-Platform Testing

The success of cross-platform testing requires more than running tests on various devices since an organized approach both detects platform-dependent problems and improves performance output. It should be both structured and strategic. Below is a list of best practices that you can follow for cross-platform testing:

First, identify the platforms your target audience uses and focus only on the most-used ones.
Identify devices, browsers, and operating systems to make combinations. Create a testing matrix to rank the priority level for each combination.
You must test user interfaces for consistency across platforms by implementing UI test cases to accomplish design and usability congruence.
The app needs testing for responsive designs, which confirms the correct display across multiple screen sizes and resolutions.
Security testing for cross-platform systems should have platform-specific vulnerabilities as its primary focus during testing.
The application needs integration testing to verify correct functioning with external systems across all target platforms.
Testing of platform-specific features should occur exclusively on the platforms where the features operate.
The testing should focus on operating system versions according to user statistics while conducting compatibility checks across all selected versions.

Conclusion

Organizations pursuing quality application delivery must conduct cross-platform testing because it no longer operates as an optional step. This testing approach enables organizations to deliver consistent user interfaces while expanding their markets. It also enables quick early identification of platform-specific issues while meeting regulatory needs and improving security measures.

Digital platforms continue to expand in diversity, which means cross-platform testing will become increasingly necessary. Success in the complex digital landscape depends on organizations that inspect their products through comprehensive testing across different environments, and those who skip this step will face competition from diligent competitors.

1

Sep

Free Elasticsearch eBooks

By Admin User No comments yet

Below is the list of free ebooks on Elasticsearch, Kibana, ELK Stack, Lucene, Logstash with their download link curated from different sources. Hope, you will find them useful in preparing for Deep Learning. There are in different formats like mobi, epub and pdf. In case, you don’t have mobi or epub reader please download it separately to view those files. I expect you must be having pdf viewer.

An Elasticsearch Crash Course [Download]
Beginning Elastic Stack [Download]
Elastic Stack 中文指南 [Download]
Elasticsearch – A Complete Guide [Download]
Elasticsearch 5.x Cookbook – Third Edition [Download]
Elasticsearch Blueprints [Download]
ElasticSearch Cookbook – Second Edition [Download]
Elasticsearch Essentials [Download]
Elasticsearch for Hadoop [Download]
Elasticsearch in Action [Download]
Elasticsearch Indexing [Download]
Elasticsearch Server – Third Edition [Download]
Elasticsearch The Definitive Guide [Download]
Elasticsearch Tutorial – tutorialspoint.com [Download]
Elasticsearch 权威指南 [Download]
Elasticsearch, Logstash, and Kibana – CERT [Download]
I Heart Logs – Jay Kreps [Download]
Introduction to the ELK Stack [Download]
Kibana Essentials [Download]
Learning Elasticsearch [Download]
Learning ELK Stack [Download]
Learning Kibana 5.0 [Download]
Log Analysis with the ELK Stack – EMSL [Download]
Lucene 4 Cookbook [Download]
Lucene in Action [Download]
Lucene 原理与代码分析 [Download]
Mastering Elastic Stack [Download]
Mastering Elasticsearch – Second Edition [Download]
Mastering Elasticsearch 5.x [Download]
Mastering ElasticSearch [Download]
Monitoring Elasticsearch [Download]
Practical ELK Stack [Download]
Relevant Search [Download]
Scaling real-time search and analytics with Elasticsearch [Download]
Spring Data Elasticsearch [Download]
The Logstash Book [Download]
Yes Logging Can Be Awesome – James Turnbull [Download]

If you would like to list your ebook free of cost or would like to contribute, do comment or reach out to us. Did you check about other free eBooks about:

Tensorflow eBooks : Click Here
Machine Learning eBooks: Click Here

31

Aug

Free Deep Learning eBooks

By Admin User No comments yet

Deep Learning is a subfield of Machine Learning which learns from example. It is highly used in driverless cars, sentiment analysis, credit scoring, fraud detection etc. Below is the list of free Deep Learning ebooks with their download link curated from different sources. Hope, you will find them useful in preparing for Deep Learning.

Deep Learning – A Practitioner’s Approach [Download]
Deep Learning – Ian Goodfellow, Yoshua Bengio, Aaron Courville [Download]
Deep Learning in Python [Download]
Deep Learning with Hadoop [Download]
Deep Learning with Keras [Download]
Deep Learning with Python – A Hands-on Introduction [Download]
Deep Learning with PyTorch [Download]
Fundamentals of Deep Learning [Download]
Grokking Deep Learning – MEAP v10 [Download ]
Java Deep Learning Essentials [Download]
Python – Deeper Insights into Machine Learning [Download]
Python Deep Learning Cookbook [Download]
R Deep Learning Essentials [Download]
TensorFlow 1.x Deep Learning Cookbook [Download]
TensorFlow for Deep Learning – From Linear Regression to Reinforcement Learning [Download]

If you would like to list your ebook free of cost or would like to contribute, do comment or reach out to us. Did you check about other free eBooks about:

Tensorflow eBooks : Click Here
Machine Learning eBooks: Click Here

24

Aug

Quick Sort

By globalsqa No comments yet

Question:

Write a program to perform Quick sort on [85, 63, 0, 12, 47, 96, 52]

Program:

def quickSort(alist):
   quickSortHelper(alist,0,len(alist)-1)

def quickSortHelper(alist,first,last):
   if first<last:

       splitpoint = partition(alist,first,last)

       quickSortHelper(alist,first,splitpoint-1)
       quickSortHelper(alist,splitpoint+1,last)


def partition(alist,first,last):
   pivotvalue = alist[first]

   leftmark = first+1
   rightmark = last

   done = False
   while not done:

       while leftmark <= rightmark and alist[leftmark] <= pivotvalue:
           leftmark = leftmark + 1

       while alist[rightmark] >= pivotvalue and rightmark >= leftmark:
           rightmark = rightmark -1

       if rightmark < leftmark:
           done = True
       else:
           temp = alist[leftmark]
           alist[leftmark] = alist[rightmark]
           alist[rightmark] = temp

   temp = alist[first]
   alist[first] = alist[rightmark]
   alist[rightmark] = temp


   return rightmark

alist =[85, 63, 0, 12, 47, 96, 52]
quickSort(alist)
print(alist)

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def quickSort(alist):

quickSortHelper(alist,0,len(alist)-1)

def quickSortHelper(alist,first,last):

if first<last:

splitpoint = partition(alist,first,last)

quickSortHelper(alist,first,splitpoint-1)

quickSortHelper(alist,splitpoint+1,last)

def partition(alist,first,last):

pivotvalue = alist[first]

leftmark = first+1

rightmark = last

done = False

while not done:

while leftmark <= rightmark and alist[leftmark] <= pivotvalue:

leftmark = leftmark + 1

while alist[rightmark] >= pivotvalue and rightmark >= leftmark:

rightmark = rightmark -1

if rightmark < leftmark:

done = True

else:

temp = alist[leftmark]

alist[leftmark] = alist[rightmark]

alist[rightmark] = temp

temp = alist[first]

alist[first] = alist[rightmark]

alist[rightmark] = temp

return rightmark

alist =[85, 63, 0, 12, 47, 96, 52]

quickSort(alist)

print(alist)

Explanation:

Quicksort is a divide and conquer algorithm. Quicksort first divides a large array into two smaller sub-arrays: the low elements and the high elements. Quicksort can then recursively sort the sub-arrays.

The steps are:

Pick an element, called a pivot, from the array.
Partitioning: reorder the array so that all elements with values less than the pivot come before the pivot, while all elements with values greater than the pivot come after it (equal values can go either way). After this partitioning, the pivot is in its final position. This is called the partition operation.
Recursively apply the above steps to the sub-array of elements with smaller values and separately to the sub-array of elements with greater values.

The base case of the recursion is arrays of size zero or one, which never need to be sorted.

Output:

[0, 12, 47, 52, 63, 85, 96]

1	[0, 12, 47, 52, 63, 85, 96]

21

Aug

Sum of diagonal elements using Comprehension

By globalsqa No comments yet

Question:

Write a program to find the sum of diagonal elements in a matrix.

Program:

a = [[11,2,4],[4,5,6],[10,8,-12]]
n=len(a)
sum_second_diagonal=sum([a[i][j] for i in range(n) for j in range(n) if i+j==n-1])
print (sum_second_diagonal)

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a = [[11,2,4],[4,5,6],[10,8,-12]]

n=len(a)

sum_second_diagonal=sum([a[i][j] for i in range(n) for j in range(n) if i+j==n-1])

print (sum_second_diagonal)

Explanation:

Comprehensions provide a concise way to create new set of elements that satisfy a given condition from an iterable. Here the iterable is the for loop looking for diagonal elements. The list thus formed is passed to sum which returns the sum of elements in the list.

Output:

19

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18

Aug

Sum of diagonal elements

By globalsqa No comments yet

Question:

Write a program to find the sum of diagonal elements

Program:

a = [[11,2,4],[4,5,6],[10,8,-12]]
n=len(a)
sumn=0
for i in range(n):
 for j in range(n):
  if i+j==n-1:
    sum+=a[i][j] 
print (sumn)

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a = [[11,2,4],[4,5,6],[10,8,-12]]

n=len(a)

sumn=0

for i in range(n):

for j in range(n):

if i+j==n-1:

sum+=a[i][j]

print (sumn)

Explanation:

Diagonal elements are those where i=j, as in a[0][0], a[1][1] etc.the for loop cheks every instant if i is equal to j, if true value of a[i][j] is incremented to sum.

Output:

19

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17

Aug

Length of a string

By globalsqa No comments yet

Question:

Write a program to find the length of a string without inbuilt function

Program:

def strlen(s):
    if s == "": return 0
    return s.rindex(s[-1]) + 1
    
s= "GlobalSQA"
print(strlen(s))

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def strlen(s):

if s == "": return 0

return s.rindex(s[-1]) + 1

s= "GlobalSQA"

print(strlen(s))

Explanation:

The strlen function return 0 if the string is empty. Otherwise it adds one to the index position of it;s last element obtained by s.rindex.

Output:

9

1

9

16

Aug

Transpose Two matrices in Python

By globalsqa No comments yet

Question:

Write a program to transpose two matrices

Program:

#! usr/bin/python

m=int(input("ENTER MARTIX ROW SIZE m : "))
n=int(input("ENTER MARTIX COLUMN SIZE n : "))

#initializing matrix elements as 0
X = [[0]*n for j in range(m)]
Y = [[0]*m for j in range(n)]
#getting input to matrix X
for i in range (m):
  for j in range (n):
    print ('entry in row: ',i+1,' column: ',j+1)
    X[i][j] = int(input())
    
#printing first matrix X
print "ORIGINAL MATRIX : "
for i in range (m):
  for j in range (n):
    print X[i][j],"\t",
  print "\n"
    
#transpose of matrix X
for i in range (m):
    for j in range (n):
        Y[j][i]=X[i][j]

#printing transpose matrix Y
print "TRANSPOSE MATRIX : "
for i in range (n):
  for j in range (m):
    print Y[i][j],"\t",
  print "\n"

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#! usr/bin/python

m=int(input("ENTER MARTIX ROW SIZE m : "))

n=int(input("ENTER MARTIX COLUMN SIZE n : "))

#initializing matrix elements as 0

X = [[0]*n for j in range(m)]

Y = [[0]*m for j in range(n)]

#getting input to matrix X

for i in range (m):

for j in range (n):

print ('entry in row: ',i+1,' column: ',j+1)

X[i][j] = int(input())

#printing first matrix X

print "ORIGINAL MATRIX : "

for i in range (m):

for j in range (n):

print X[i][j],"\t",

print "\n"

#transpose of matrix X

for i in range (m):

for j in range (n):

Y[j][i]=X[i][j]

#printing transpose matrix Y

print "TRANSPOSE MATRIX : "

for i in range (n):

for j in range (m):

print Y[i][j],"\t",

print "\n"

Explanation:

The transpose of a matrix is an operator which flips a matrix over its diagonal, that is it switches the row and column indices of the matrix by producing another matrix denoted as A^T (also written A′, A^tr, ^tA or A^t). It is achieved by any one of the following equivalent actions:

The transpose A^T of a matrix Acan be obtained by reflecting the elements along its main diagonal. Repeating the process on the transposed matrix returns the elements to their original position.

reflect A over its main diagonal (which runs from top-left to bottom-right) to obtain A^T
write the rows of A as the columns of A^T
write the columns of A as the rows of A^T

Formally, the i th row, j th column element of A^T is the j th row, i th column element of A:

\left[\mathbf {A} ^{\mathrm {T} }\right]_{ij}=\left[\mathbf {A} \right]_{ji}

If A is an m × n matrix then A^T is an n × m matrix.

Output:

ENTER MARTIX ROW SIZE m :  2
ENTER MARTIX COLUMN SIZE n :  2
entry in row:  1  column:  1
 8
entry in row:  1  column:  2
 9
entry in row:  2  column:  1
 4
entry in row:  2  column:  2
 8
ORIGINAL MATRIX : 
8    4 	
9    8

TRANSPOSE MATRIX : 
8    9	
4    8

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ENTER MARTIX ROW SIZE m : 2

ENTER MARTIX COLUMN SIZE n : 2

entry in row: 1 column: 1

8

entry in row: 1 column: 2

9

entry in row: 2 column: 1

4

entry in row: 2 column: 2

8

ORIGINAL MATRIX :

8 4

9 8

TRANSPOSE MATRIX :

8 9

4 8

5

Jul

Generate Passwords

By globalsqa No comments yet

Question:

Write a python program to generate passwords

Program:

import string
from random import *
characters = string.ascii_letters + string.punctuation + string.digits
password = "".join(choice(characters) for x in range(randint(8, 16)))
print (password)

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import string

from random import *

characters = string.ascii_letters + string.punctuation + string.digits

password = "".join(choice(characters) for x in range(randint(8, 16)))

print (password)

Explanation:

Following are the criteria for creating a password:

1. At least 1 letter between [a-z]

2. At least 1 number between [0-9]

1. At least 1 letter between [A-Z]

3. At least 1 character from [$#@]

4. Minimum length of transaction password: 6

5. Maximum length of transaction password: 12

Output:

-|>GR5UZY3

1	-\|>GR5UZY3

4

Jul

Area of Rectangle using classes

By globalsqa No comments yet

Question:

Calculate area of a rectangle using classes

Program:

class rect():
    def __init__(self,breadth,length):
        self.breadth=breadth
        self.length=length
    def area(self):
        return self.breadth*self.length

a=int(input("Enter length of rectangle: "))
b=int(input("Enter breadth of rectangle: "))
obj=rect(a,b) # Creating an object 'obj' of class rect

print "Area of rectangle:",obj.area()

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class rect():

def __init__(self,breadth,length):

self.breadth=breadth

self.length=length

def area(self):

return self.breadth*self.length

a=int(input("Enter length of rectangle: "))

b=int(input("Enter breadth of rectangle: "))

obj=rect(a,b) # Creating an object 'obj' of class rect

print "Area of rectangle:",obj.area()

Explanation:
A class rect is created with two breadth and length, and method area which tabulates the area of the rectangle.
An object obj of class rect is created and used

Output:

Enter length of rectangle: 10
Enter breadth of rectangle: 20
Area of rectangle: 200

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Enter length of rectangle: 10

Enter breadth of rectangle: 20

Area of rectangle: 200

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Jul

Even numbers using list comprehension

By globalsqa No comments yet

Question:

Create a list of even numbers between 0 and 10 using list comprehension.

Program:

listl=[i for i in range (10) if(i%2==0)]
print listl

1 2	listl=[i for i in range (10) if(i%2==0)] print listl

Explanation:

List comprehensions provide a concise way to create lists.

It consists of brackets containing an expression followed by a for clause, then
zero or more for or if clauses. The expressions can be anything, meaning you can
put in all kinds of objects in lists.

List comprehensions provide a concise way to create new list of elements that satisfy a given condition from an iterable. Here the iterable prints out even numbers.

Output:

[0, 2, 4, 6, 8]

1	[0, 2, 4, 6, 8]

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Jul

Prime Numbers within a range

By globalsqa No comments yet

Question :

Write a program to print prime numbers within a range

Program:

#Accept the range from user

lower = int(input("Enter lower range: "))

upper = int(input("Enter upper range: "))



print "Prime numbers between",lower,"and",upper,"are:",



for num in range(lower,upper + 1):

   # prime numbers are greater than 1

   if num > 1:

       for i in range(2,num):

           if (num % i) == 0:

               break

       else:

           print num,

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#Accept the range from user

lower = int(input("Enter lower range: "))

upper = int(input("Enter upper range: "))

print "Prime numbers between",lower,"and",upper,"are:",

for num in range(lower,upper + 1):

# prime numbers are greater than 1

if num > 1:

for i in range(2,num):

if (num % i) == 0:

break

else:

print num,

Explanation:

A prime number is a number that is divisible only by itself and 1 (e.g. 2, 3, 5, 7, 11).

Output:

Enter lower range: 2

Enter upper range: 10

Prime numbers between 2 and 10 are: 2 3 5 7

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Enter lower range: 2

Enter upper range: 10

Prime numbers between 2 and 10 are: 2 3 5 7

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Jul

Difference between range() and xrange()

By globalsqa No comments yet

Question:

Write a program to show the difference between range() and xrange() function

Program:

import sys

r=range(10000)
x=xrange(10000)
print (sys.getsizeof(r)) #output:40036
print (sys.getsizeof(x))    #output:20
#sys.getsizeof() returns the memory size occupied by a variable or object

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import sys

r=range(10000)

x=xrange(10000)

print (sys.getsizeof(r)) #output:40036

print (sys.getsizeof(x)) #output:20

#sys.getsizeof() returns the memory size occupied by a variable or object

Explanation:

The variable holding the range created using range() uses so much memory compared to
the variable created using xrange()

The reason is that range creates a list holding all the values
while xrange creates an object that can iterate over the numbers on demand.

Eventhough the xrange is memory efficient, the price we have to pay
for this efficieny is access time. The range variable created with range()
will have a faster access time compare to the variable created with xrange()
as it is entirely stored in the memory so it is readily available
whereas the variable created with xrange() have to load its contents
to memory ‘on demand’ only. So time efficiency is a drawback of xrange()

Output:

80072
40

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80072

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Jun

Tuple Operations

By globalsqa No comments yet

Question:

Perform the following operations on the below tuple (‘abc’, ‘def’, ‘ghi’, ‘jklm’, ‘nopqr’, ‘st’, ‘uv’, ‘wxyz’, ’23’, ‘s98’, ‘123’, ’87’)

prints the length of the tuple
Slicing
Reverse all items in the tuple
Removing whole tuple
Concatenate two tuples

Program:

tup = ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')

# prints the length of the tuple
print('\ntuple: ', tup)
print('Length of the tuple is : ', len(tup))

# Slicing
# shows only items starting from 0 upto 3
print('\ntuple: ', tup)
print('tuple showing only items starting from 0 upto 3\n', tup[:3])

# shows only items starting from 4 to the end
print('\ntuple: ', tup)
print('tuple showing only items starting from 4 to the end\n', tup[4:])

# shows only items starting from 2 upto 6
print('\ntuple: ', tup)
print('tuple showing only items starting from 2 upto 6\n', tup[2:6])

# reverse all items in the tuple
print('\ntuple: ', tup)
print('tuple items reversed \n', tup[::-1])

# removing whole tuple
del tup

tup_0 = ("ere", "sad")
tup_1 = ("sd", "ds")
print('\nfirst tuple: ', tup_0)
print('second tuple: ', tup_1)
tup = tup_0 + tup_1
print('Concatenation of 2 tuples  \n', tup)

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tup = ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')

# prints the length of the tuple

print('\ntuple: ', tup)

print('Length of the tuple is : ', len(tup))

# Slicing

# shows only items starting from 0 upto 3

print('\ntuple: ', tup)

print('tuple showing only items starting from 0 upto 3\n', tup[:3])

# shows only items starting from 4 to the end

print('\ntuple: ', tup)

print('tuple showing only items starting from 4 to the end\n', tup[4:])

# shows only items starting from 2 upto 6

print('\ntuple: ', tup)

print('tuple showing only items starting from 2 upto 6\n', tup[2:6])

# reverse all items in the tuple

print('\ntuple: ', tup)

print('tuple items reversed \n', tup[::-1])

# removing whole tuple

del tup

tup_0 = ("ere", "sad")

tup_1 = ("sd", "ds")

print('\nfirst tuple: ', tup_0)

print('second tuple: ', tup_1)

tup = tup_0 + tup_1

print('Concatenation of 2 tuples \n', tup)

Explanation:

A tuple is a sequence of immutable Python objects. Tuples are sequences, just like lists. The differences between tuples and lists are, the tuples cannot be changed unlike lists and tuples use parentheses, whereas lists use square brackets.

Output:

tuple:  ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')
Length of the tuple is :  12

tuple:  ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')
tuple showing only items starting from 0 upto 3
 ('abc', 'def', 'ghi')

tuple:  ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')
tuple showing only items starting from 4 to the end
 ('nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')

tuple:  ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')
tuple showing only items starting from 2 upto 6
 ('ghi', 'jklm', 'nopqr', 'st')

tuple:  ('abc', 'def', 'ghi', 'jklm', 'nopqr', 'st', 'uv', 'wxyz', '23', 's98', '123', '87')
tuple items reversed 
 ('87', '123', 's98', '23', 'wxyz', 'uv', 'st', 'nopqr', 'jklm', 'ghi', 'def', 'abc')

first tuple:  ('ere', 'sad')
second tuple:  ('sd', 'ds')
Concatenation of 2 tuples  
 ('ere', 'sad', 'sd', 'ds')

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