Featured Post

Best Practices for Handling Duplicate Elements in Python Lists

-
Image
Here are three awesome ways that you can use to remove duplicates in a list. These are helpful in resolving your data analytics solutions.  01. Using a Set Convert the list into a set , which automatically removes duplicates due to its unique element nature, and then convert the set back to a list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = list(set(original_list)) 02. Using a Loop Iterate through the original list and append elements to a new list only if they haven't been added before. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] for item in original_list:     if item not in unique_list:         unique_list.append(item) 03. Using List Comprehension Create a new list using a list comprehension that includes only the elements not already present in the new list. Solution: original_list = [2, 4, 6, 2, 8, 6, 10] unique_list = [] [unique_list.append(item) for item in original_list if item not in unique_list] All three methods will result in uni
Post a Comment

Case Study On Cloud Computing

-
The concept of cloud computing is in use for many years, but in recent years has it become a highlighted and come in picture. In the year 1990s, cloud computing was developed by major IT providers such as Sun, Microsoft, Google, and Amazon.

Cloud computing
Cloud computing
Different products came into use for different levels of users. The most popular services for end users include web-based email systems (SaaS), e.g. AOL, Gmail, Hotmail, and Yahoo! Mail, and office applications such as Google Docs, Microsoft MS Office Online, Cloud-canvas.com, and Write.fm, etc.

 Developers can run their programs on the cloud (PaaS) like Google AppEngine, Windows Azure, and Force.com. Companies or organizations store or backup their large data on remote servers (IaaS), for example, Rackspace, Microsoft Azure, Animoto, Jungle Disk and Amazon's EC2 or S3 servers.

In 2011, the Primary Research Group (PRG) published a report of its recently conducted survey on library use of cloud computing (Primary Research Group, 2011). Participants included 70 libraries worldwide with the majority from the United States. The survey report reveals that 61.97 percent of libraries in the sample used free SaaS while 22.54 percent of libraries sampled used paid subscription SaaS; less than 3 percent of libraries surveyed used PaaS, and 4.23 percent used IaaS.

Most libraries using PaaS or IaaS had annual budgets over $5,000,000. Smaller libraries usually used the servers of their parent organizations, while libraries with multi-million dollar budgets tended to use their own servers.

  • Few case studies also show the exploration and adoption of other models of cloud computing in libraries. For example, California State University libraries have migrated their key library systems to vendors' cloud-based servers (i.e. a public cloud) and to campus IT's internally virtualized environment (i.e. a private cloud) (Wang, 2012). 
  • The Burritt Library at Central Connecticut State University used Amazon's S3 to back up their high-resolution digital objects (Iglesias, 2011). Murray State University library experimented with Dropbox for library services (Bagley, 2011). University of Arizona Libraries have migrated their ILS, Digital Libraries website, Interlibrary Loan system and repository software to cloud-based services (Han, 2010). 
  • The Z. Smith Reynolds Library in Winston Salem, NC, started to use Amazon's EC2 for hosting its website, discovery services, and digital library services in 2009 (Mitchell, 2010b).

The service model represent server administration and maintenance responsibilities are moved from local personnel to the hosting vendor, while the management of the application remains in the traditional way, i.e. librarians are still able to access the backend of the system for local customizations as if they were managing the system locally.

Comments

Post a Comment

Thanks for your message. We will get back you.

Popular posts from this blog

Explained Ideal Structure of Python Class

-
Image
When you are designing a class, you need to ensure that the classification of its critical parts is outlined at the beginning. The clearer the initial design, the more performant and scalable the class is. Some of the components in the order in which they should be defined in the class are mentioned as follows. Ideal structure of a class Class variables Constants or default variables are usually defined at the top of the class. For someone who is reading the code, it comes as an easy-to-view consolidated list, and for the interpreter it ensures that all such variables are processed before diving into the main logic of the class, including any other Instance method or constructor. The __init__ method The __init__ method provides information about inputs needed and how to instantiate the class. It is also the constructor of the class, which the very first method called while initializing the class . Special Python methods These methods change the functionality of the class or provide add
Read more

6 Python file Methods Real Usage

-
Image
Files always have data in them. For different purposes, you need methods to deal with them. These six file methods of use in this case. Related:  5 top file modes in python. Python file methods Below are the top six file methods in python: Tell() Seek() Flush() Fileno() truncate() isatty() 1. tell() The usage of tell method is it  returns the cursor-position of the file-pointer from the beginning of the file. It tells the current cursor position. The position starts from zero, which is same as of an index. Syntax:  fileobject.tell() 2. seek() The usage of seek  method is cursor position, from one position to the specified position from the beginning of the file, it moves. Here, the cursor will be sought to a particular location. Syntax:  fileobject.seek(position) 3. flush() The usage of flush  method is clean out the internal buffer. Before writing the text in the file, it is best practice to clear out that the internal buffer can be cleared. Syntax:  fileobject.flush() 4. fileno() The
Read more

How to Decode TLV Quickly

-
Image
TLV format contains three parts Tag, Length, and value. In a credit card or financial transactions, the TLV protocol supports this format. Below, you will find the ideas to decode TLV data quickly.  According to IBM , the tag tells what type of data it is. The length field denotes the length of the value. The value-field denotes the actual value. Structure of TLV. TLV comprises three field values. Tag Length Value How to Decode TLV The EMV labs developed tags which in turn part of EMV protocol. Each tag has an unique meaning. And the Tag and Length together takes 1 to 4 bytes of memory. 1. The Best example for TLV. Below is the way to decode the EMV tag. The first part of the TLV format is TAG. The second part is LENGTH, and finally the VALUE. Syntax of EMV tag: [Tag][Value Length][Value] (ex. " 9F40 05 F000F0A001 ") where,  Tag Name =  9F40 Value Length (in bytes) =  05  Value (Hex representation of bytes. Example, "F0" – 1-byte) =  F000F0A001 Finally, what is 9F40
Read more