IFB104留学生讲解、讲解辅导Python

2019.10.03 - 首页 >> Python编程

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Assignment 2, Part A: News Feed Aggregator

(21%, due 11:59pm Sunday, October 20th, end of Week 12)

Overview

This is the first part of a two-part assignment. This part is worth 21% of your final grade for

IFB104. Part B will be worth a further 4%. Part B is intended as a last-minute extension to

the assignment, thereby testing the maintainability of your solution to Part A and your ability

to work under time pressure. The instructions for completing Part B will not be released until

Week 12. Whether or not you complete Part B you will submit only one solution, and receive

only one mark, for the whole 25% assignment.

This a complex and challenging assignment. If you are unable to solve the whole problem,

submit whichever parts you can get working. You will receive partial marks for incomplete

solutions.

Motivation

The way we consume news has changed dramatically in recent years. The days of morning

and afternoon home newspaper deliveries are long gone. Where readers were once restricted

to a handful of local news sources, we now have a bewildering range of online options from

around the world. Most newspapers, radio and television stations now make their news services

available online, in addition to new purely online news services. Making sense of this

cacophony is a challenge.

One response is news aggregation services. These allow readers to create their own news

channels by mixing their preferred news sources together into a single stream. In this assignment

you will create your own news aggregation application in Python. Your program

will have a Graphical User Interface that allows its user to select how many stories they want

to see from each source and then export an HTML document containing the selected stories.

This document can be examined in a standard web browser or printed as a hardcopy.

This “capstone” assignment is designed to incorporate all of the concepts taught in IFB104.

To complete it you will need to: (a) use Tkinter to create an interactive Graphical User Interface;

(b) download web documents using a Python script and use pattern matching to extract

specific elements from them; and (c) generate an HTML document that integrates the extracted

elements, presenting them in an attractive, easy-to-read format.

Goal

Your aim in this assignment is to develop an interactive “app” which allows its users to select

how many news stories they want to see from several different news sources. There must be

at least four different sources, two of them “live” news feeds and two “archives” of previously-downloaded

news items. Most importantly, the two online web documents from which

you get your “live” news must be ones that are updated on a continuous basis (at least daily

but preferably much more often) so your program needs to be resilient to changes in the

source documents. These two news sources must also come from different web sites (i.e.,

different web servers), to allow for one of the sites being temporarily offline.

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For the purposes of this assignment you have a free choice of which news sources to use,

provided there are always at least ten stories in each one, the stories are updated frequently,

and the information available for each story includes a headline, the date/time of publication,

a photo, and a short textual description. Appendix A below lists many “RSS Feed” web sites

which should be suitable for this assignment, but you are encouraged to find your own of personal

interest.

Using these news sources you are required to build an IT system with the following general

architecture.

Your application will be a Python program with a Graphical User Interface. Under the user’s

control, it allows news feeds to be previewed in the GUI, from both online and archived news

sources. When the user is happy with their selections they can then export the selected stories

as an HTML document. This document will contain full detail of each story and can be

studied by the user in any standard web browser.

This is a large and complex project, so its design allows it to be completed in distinct stages.

You should aim to build the system incrementally, rather than trying to solve the whole problem

at once. A suggested development sequence is:

1. Develop code that allows the static, archived news stories to be previewed in the GUI.

2. Extend your solution so that it allows “live” news stories to be previewed in the GUI.

3. Extend your solution further so that the user’s selected stories can be exported as an

HTML document.

If you can’t complete the whole assignment submit whatever parts you can get working. You

will get partial marks for incomplete solutions (see the marking guide below).

Illustrative example

To demonstrate the idea, below we describe our own news aggregation application, which

uses information extracted from four different news sites. Our demonstration solution allows

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users to select stories from two archived news feeds, The Queensland Times as it appeared on

September 8th 2019 and the Crikey satirical news service from August 29th. It also allows

two “live” news sources to be seen, the Canberra Times and FOX News Entertainment. Both

of these sources are directly accessed by our Python application, so the news displayed is alway

the latest available. The application allows users to select how many stories they wish to

see from each source. The program then accesses all the necessary information from the online

and archived web sites and displays a preview of the top stories from each in the GUI.

The user can then export a personalised news feed which includes stories from all selected

sources as an HTML document which can be viewed in any standard web browser.

The screenshot below shows our example solution’s GUI when first started. We’ve called it

The ‘Smooth Blend’ News Mixer and have included a suitably evocative image of someone

reading news from an RSS feed, but you should choose your own name and GUI design.

The GUI has four ‘spin box’ widgets allowing the user to select how many stories they want

to see from each source, a scrollable text area for displaying previews of the selected stories,

and a push button for exporting the selections. You do not need to copy our example and are

encouraged to design your own GUI with equivalent functionality. For instance, pull-down

menus or text entry boxes could be used for making the selections rather than spin boxes.

Selecting archived stories

When the user chooses a number of stories from the two archived sources, the application

extracts headlines and publication dates for each story from local files, previously down-

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loaded from the web. For instance, in the screenshot below the user has chosen to see two

stories from our archived copy of the Queensland Times and one from the Crikey archive file.

Accordingly, our application extracts the top two stories from the Canberra Times file and

the top story from Crikey. It displays each story’s headline, source and publication date in

the preview pane. (We downloaded a copy of the Crikey site at 8:46am on August 29th but,

as can be seen above, the most recent story on the site at that time was from the previous evening,

with an announcement about Boris Johnson’s latest Brexit move.)

Exporting the selected stories

Happy with their selections, the user then presses the “Export” button. This causes our application

to generate an HTML file called news.html (in the same folder as the Python program).

This document contains copies of the same stories previewed in the GUI, plus additional

detail including a photo and a short story summary.

When opened in a standard web browser this file appears as shown overleaf. It includes a

heading identifying the document and a “splash” image. Following this are the selected stories,

each consisting of a headline, photo, short description, identification of the story’s source,

and the publication date. At the end of the file are four hyperlinks to the original web sites

from which both the “live” and “archived” data is/was sourced.

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The document is well presented and the various elements of each story all match one another.

Importantly, all the images in the exported document, including the “splash” image up the top

and the story photos, are online images, not ones stored on our local computer. To ensure

that the exported web document is portable and can be viewed on any computer, the photos

are all links to online images using appropriate HTML “img” tags and URLs.

You are not required to follow the details of our demonstration GUI or exported HTML

document. You are strongly encouraged to use your own skills and initiative to design your

own solution, provided it has all the functionality and features described herein.

Selecting current stories

Tiring of reading “old news”, our user next selects some “live” stories in the GUI as shown

below, as well as changing the choice of archived stories in the mix.

As can be seen in the preview pane, our program updates the archived stories selected. More

importantly, however, scrolling through the headlines reveals current stories downloaded

“live” from the Internet. To do so our program downloaded copies of the source web pages

and extracted appropriate elements from them. When we ran the program on September 10th

the top three stories in the Canberra Times were as shown below.

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Our user also selected four stories from FOX News Entertainment. Scrolling down in the

preview pane reveals these stories as well.

Notice in the screenshots above that the publication dates for the stories from different sources

are in different formats. This is how the dates were represented in the source web documents.

There is no need to try to normalise or unify the date/time formats; they should simply

be reproduced exactly as they appeared in the original documents.

Exporting the selected stories (again)

At this point our user again presses the “Export” button, causing all ten selected stories to be

written to the news.html file. When opened in a web browser the chosen news feed mix

appears as shown in the following extracts in this case. Here we have a unique mixture of

both old and current news, and Australian and overseas news, but all of the stories are clearly

labelled with their source and publication date, so there is no confusion. As usual, all the images

in the document are links to online files. (And, no, we don’t understand the second Crikey

story either, but that’s what they had on their web site at the time we downloaded their

news feed!)

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Extracting the HTML elements

To produce the news story details for displaying in the GUI and exporting as part of our

HTML document, our application used regular expressions to extract elements from the relevant

source web documents, whether they were stored in the static archive or are downloaded

from the Internet whenever the program runs.

A significant challenge for this assignment is that web servers deliver different HTML/XML

documents to different web browsers or other software clients. This means the web document

you see in a browser may be different from the web page downloaded by your Python

application. For this reason, to create your “archived” files you should download the web

documents using our downloader program (see below), or a similar application. This will

ensure that the “live” and “archived” documents have similar formats, thus making your pattern

matching task easier.

To produce our demonstration solution, we first downloaded copies of the web pages and

then studied their source code to identify text patterns that would help us find the specific

elements we wanted. For instance, the XML source code for the FOX Entertainment news

feed was as follows on September 10th.

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Looking closely at this code we can, for instance, see the various elements of the top story,

concerning the Brady Bunch’s house renovation, including the headline (in <title> tags),

the story summary (in <description> tags), the publication date (in <pubDate> tags),

and the photo (as a JPG image URL, one of several alternatives). This knowledge was enough

to allow us to create regular expressions which extract all the necessary elements for all

strories in the document using Python’s findall function.

Sometimes it’s easier to use other Python features as well as, or instead of, regular expressions

to help extract the data. For instance, we found that our regular expression for extracting

headlines from the FOX Entertainment web site also matched the two “FOX News” titles

at the top of the web page in addition to the headlines we wanted. Rather than complicating

our regular expression, we therefore simply deleted the first two items returned by findall

each time we extracted headlines from this page. (We also found that the URLs for the

photos had inconsistent formats in this site, making them difficult to extract, so we don’t recommend

using this site in your own solution.) Most importantly, you must extract elements

in a general way that will still work when the contents of the source web page are updated.

Obviously working with such complex code is challenging. You should begin with your

static, “archived” documents to get some practice at pattern matching before trying the dynamically

changeable web documents downloaded from online.

Care was also taken to ensure that no HTML/XML tags or other HTML entities appeared in

the extracted text when displayed in either the GUI or the exported HTML document. In

some cases it was necessary to delete or replace such mark-ups in the text after it was extracted

from the original web document. The information seen by the user must not contain

any extraneous tags or unusual characters that would interfere with the appearance of the

news stories either in the GUI or the exported document.

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Exporting the HTML document

Our program creates the exported HTML document by writing code into a text file, integrating

the various elements extracted from the news feeds. Two segments of the HTML code

generated by our Python program are shown below. Although not intended for human consumption,

the HTML code is nonetheless laid out neatly, and with comments indicating the

purpose of each part. Your HTML code must also be well presented to facilitate future

maintenance of your application.

Robustness

Another important aspect of your solutin is that it must be resilient to error. The biggest risk

with this kind of program is problems accessing the source web sites. We have attempted to

make our download function as robust as possible. In particular, if it detects an error while

downloading a web document it returns the special value None instead of a character string,

so your program should allow for this. (We don’t claim that the download function is infallible,

however, because the results it produces are dependent on the behaviour of your specific

Internet connection. For instance, some systems will generate a default web document

when an online site can’t be reached, in which case the download function will be unaware

that a failure has occurred and won’t return None.)

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For instance, in our demonstration solution the GUI alerts the user to a failure to download a

web site as follows.

Therefore, as insurance against the risk of a web site failing completely, your program’s two

“live” web sources must come from different web servers. One way of achieving this is to

ensure that the part of the address at the beginning of each site’sURL is entirely distinct. For

example, our sample solution used two totally different sources for the “live” news feeds, the

Canberra Times and FOX Entertainment. These two sites have the following URLs and

clearly come from different web servers.

(Since they never change, there is no need to use distinct servers for the two “archived”

documents. Nonetheless, we did so in our sample solution to make the program more interesting.)

Specific requirements and marking guide

To complete this part of the assignment you are required to produce an application in Python

3 with features equivalent to those above, using the provided news_aggregator.py

template file as your starting point. In addition you must provide the two (or more) previously-downloaded

web documents that serve as your archive of “old news” and one or more

image files needed to support your GUI. (However, all of the images in the exported HTML

file must be online images and must not be included in your submission.)

Your complete solution must support at least the following features.

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• An intuitive Graphical User Interface (4%). Your application must provide an attractive,

easy-to-use GUI which has all the features needed for the user to choose how

many news stories they want from each of four news feeds (two “archived” and two

“live”), preview the headlines for their selections, and export the complete stories as a

web document. You have a free choice of which Tkinter widgets to use to do the job,

as long as they are effective and clear for the user. This interface must have the following

features:

o An image which acts as a “logo” to identify your application. The image file

should be included in the same folder as your Python application.

o Your GUI must name your application in both the Tkinter window’s title and

as a large heading in the displayed interface. Inside the window the name may

appear as an integrated part of the logo, or as a separate textual label (as in our

demonstration solution).

o One or more widgets that allow the user to select how many stories they want

to see from each of four news feeds (two “archived” and two “live”).

o One or more widgets that allow the user to see details of the stories selected

(headlines, sources and publication dates).

o One or more widgets that allow the user to choose whether or not to export

their story selections as an HTML document.

Note that this criterion concerns the front-end user interface only, not the back-end

functionality. Functionality is assessed in the following criteria.

• Previewing archived news stories in the GUI (4%). Your GUI must be capable of

displaying the top stories, in the quantities selected by the user, from each of two distinct

sources of “archived” news, allowing selection of up to ten stories per source.

For each story the GUI must display

o the headline,

o the news source (usually the name of a newspaper, magazine, TV or radio station),

and

o the publication date/time for the story.

The necessary elements must be extracted from HTML/XML files previously downloaded

and stored along with your Python program. The documents must be stored in

exactly the form they were downloaded from the web server; they cannot be edited or

modified in any way. Pattern matching must be used to extract the relevant elements

from the documents so that the code would still work if the archived documents were

replaced with others in the same format. To keep the size of your solution manageable

only single HTML/XML source files can be stored. No image or style files may

be stored in your “archive”.

• Previewing “live”news stories in the GUI (4%). Your GUI must be capable of displaying

the top stories, in the quantities selected by the user, from each of two distinct

sources of “live” news, allowing selection of up to ten stories per source. For each

story the GUI must display

o the headline,

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o the news source (usually the name of a newspaper, magazine, TV or radio station),

and

o the publication date/time for the story.

The necessary elements must be extracted from HTML/XML files directly downloaded

from the web while your Python program is running. Pattern matching must

be used to extract the relevant elements from the documents so that the code still

works even after the online documents are updated. The chosen source web sites

must be ones that are updated on a regular basis, at least daily and preferably hourly.

The two source web sites must come from different web servers (as insurance against

one of the web sites being offline when your assignment is assessed).

• Exporting selected news stories as an HTML document (5%). Your program must

be able to generate an HTML document containing full details of the top stories from

each of the four news sources, live and/or archived, in the quantities selected by the

user. The resulting “mixed news feed” must be written as an HTML document in the

same folder as your Python program and must be easy to identify through an appropriate

choice of file name, “news.html”. The generated file must contain HTML

markups that make its contents easily readable in any standard web browser, and it

must be self-contained (i.e., not dependent on any other local files), although it may

reference online images and style files. When viewed in a browser, the displayed

document must be neat and well-presented and must contain at least the following

features:

o A heading identifying your application.

o A “splash” image characterising your application, downloaded from online

when the generated HTML document is viewed (i.e., not from a local file on

the host computer).

o Details of each of the news stories selected by the user in the GUI. For each

story at least the following information must be displayed:

 The headline.

 A photograph or image illustrating the story.

 A short story summary or description.

 The identity of the original news feed (typically a newspaper, magazine,

TV or radio station).

 The date/time at which the story was published. (There is no need to

standardise the format of this timestamp. It can appear in exactly the

same format as the source web document. There is also no need to sort

the stories from different sources into chronological order, although

this would be a helpful feature.)

All of this information must be extracted via pattern matching from HTML

documents downloaded from the web. Most importantly, each of these sets of

items must all belong together, e.g., you can’t have the headline of one story

paired with a photo from another story. Each of the elements must be extracted

from the original document(s) separately and used to construct your

own HTML document.

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o Hyperlinks to the original four web sites from which the information was extracted,

both live and archived. (For the live feeds this will help the markers

compare the current web pages with your extracted information).

When viewed in a web browser the exported document must be neatly laid out and

appear well-presented regardless of the browser window’s dimensions. The textual

parts extracted from the original documents must not contain any visible HTML tags

or entities or any other spurious characters. The images must all be links to images

found online, not in local files, must be of a size compatible with the rest of the

document, and their original aspect ratio must be preserved (i.e., they should not be

stretched in just one direction).

• Good Python and HTML code quality and presentation (4%). Both your Python

program code and the generated HTML code must be presented in a professional

manner. See the coding guidelines in the IFB104 Code Presentation Guide (on

Blackboard under Assessment) for suggestions on how to achieve this for Python. In

particular, each significant Python or HTML code segment must be clearly commented

to say what it does, e.g., “Extract the link to the photo”, “Display the story’s

publication date”, etc.

• Extra feature (4%). Part B of this assignment will require you to make a ‘last-minute

extension’ to your solution. The instructions for Part B will not be released until just

before the final deadline for Assignment 2.

You can add other features if you wish, as long as you meet these basic requirements. You

must complete the task using only basic Python 3 features and the modules already imported

into the provided template. You may not use any Python modules that need to be downloaded

and installed separately, such as “Beautiful Soup” or “Pillow”. Only modules

that are part of a standard Python 3 installation may be used.

However, your solution is not required to follow precisely our example shown above. Instead

you are strongly encouraged to be creative in your choices of web sites, the design of your

Graphical User Interface, and the design of your generated HTML document.

Support tools

To get started on this task you need to download various web documents of your choice and

work out how to extract the necessary elements for displaying data in the GUI and generating

the HTML output file. You also need to allow for the fact that the contents of the web documents

from which you get your data will change regularly, so you cannot hardwire the locations

of the elements into your program. Instead you must use Python’s string find method

and/or regular expression findall function to extract the necessary elements, no matter

where they appear in the HTML/XML source code.

To help you develop your solution, we have included two small Python programs with these

instructions.

1. downloader is a Python program containing a function called download that

downloads and saves the source code of a web document as a text file, as well as returning

the document’s contents to the caller as a character string. A copy of this

function also appears in the provided program template. You can use it both to save

copies of your chosen web documents for storage in your “archive”, as well as to

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download “live” web documents in your Python application at run time. Although

recommended, you are not required to use this function in your solution, if you prefer

to write your own “downloading” code to do the job.

2. regex_tester is an interactive program introduced in the lectures and workshops

which makes it easy to experiment with different regular expressions on small text

segments. You can use this together with downloaded text from the web to help perfect

your regular expressions. (There are also many online tools that do the same job

you can use instead.)

Portability

An important aspect of software development is to ensure that your solution will work correctly

on all computing platforms (or at least as many as possible). For this reason you must

complete the assignment using standard Python 3 functions and modules only. You may not

import any additional modules or files into your program other than those already imported

by the given template file. In particular, you may not use any Python modules that need to

be downloaded and installed separately, such as “Beautiful Soup” or “Pillow”. Only

modules that are part of a standard Python 3 installation may be used.

Security warning and plagiarism notice

This is an individual assessment item. All files submitted will be subjected to software plagiarism

analysis using the MoSS system (http://theory.stanford.edu/~aiken/moss/). Serious

violations of the university’s policies regarding plagiarism will be forwarded to the Science

and Engineering Faculty’s Academic Misconduct Committee for formal prosecution.

As per QUT rules, you are not permitted to copy or share solutions to individual assessment

items. In serious plagiarism cases SEF’s Academic Misconduct Committee prosecutes both

the copier and the original author equally. It is your responsibility to keep your solution secure.

In particular, you must not make your solution visible online via cloud-based code

development platforms such as GitHub. Note that free accounts for such platforms are

usually public. If you wish to use such a resource, do so only if you are certain you have a

private repository that cannot be seen by anyone else. For instance, university students can

apply for a free private repository in GitHub to keep their assignments secure

(https://education.github.com/pack). However, we recommend that the best way to avoid being

prosecuted for plagiarism is to keep your work well away from the Internet!

Internet ethics: Responsible scraping

The process of automatically extracting data from web documents is sometimes called

“scraping”. However, in order to protect their intellectual property, and their computational

resources, owners of some web sites may not want their data exploited in this way. They will

therefore deny access to their web documents by anything other than recognised web

browsers such as Firefox, Internet Explorer, etc. Typically in this situation the web server

will return a short “Access Denied” document to your Python script instead of the expected

web document (Appendix B).

In this situation it’s possible to trick the web server into delivering you the desired document

by having your Python script impersonate a standard web browser. To do this you need to

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change the “user agent” identity enclosed in the request sent to the web server. The provided

download function has an option that disguises its true identitity. We leave it to your own

conscience whether or not you wish to activate this feature, but note that this assignment can

be completed successfully without resorting to such subterfuge.

Deliverables

You should develop your solution by completing and submitting the provided Python template

file news_aggregator.py. Submit this in a “zip” archive containing all the files

needed to support your application as follows:

1. Your news_aggregator.py solution. Make sure you have completed the statement

at the beginning of the Python file to confirm that this is your own individual

work by inserting your name and student number in the places indicated. Submissions

without a completed statement will be assumed not to be your own work.

2. One or more small image files needed to support your GUI interface, but no other

image files.

3. The previously-downloaded web documents used as your static “archive” of old news

stories. Only HTML/XML source code files may be included. No image or style

files associated with the web documents may be included. All images or styles

needed to support your exported HTML document must be sourced from online when

it is viewed in a web browser.

Once you have completed your solution and have zipped up these items submit them to

Blackboard as a single file. Submit your solution compressed as a “zip” archive. Do not

use other compression formats such as “rar” or “7z”.

Apart from working correctly your Python and HTML code must be well-presented and easy

to understand, thanks to (sparse) commenting that explains the purpose of significant elements

and helpful choices of variable, parameter and function names. Professional presentation

of your code will be taken into account when marking this assignment.

If you are unable to solve the whole problem, submit whatever parts you can get working.

You will receive partial marks for incomplete solutions.

How to submit your solution

A link is available on Blackboard under Assessment for uploading your solution before the

deadline (11:59pm Sunday, October 20th, end of Week 12). Note that you can submit as

many drafts of your solution as you like. You are strongly encouraged to submit draft solutions

before the deadline as insurance against computer and network failures. If you are unsure

whether or not you have successfully uploaded your file, upload it again!

Students who encounter problems uploading their files to Blackboard should contact the IT

Helpdesk (ithelpdesk@qut.edu.au; 3138 4000) for assistance and advice. Teaching staff will

not answer email queries on the weekend the assignment is due, so ensure that you have successfully

uploaded at least one solution by close-of-business on Friday, October 18th.

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Appendix A: Some RSS feeds that may prove helpful

For this assignment you need to find sources of regularly-updated news or current affairs

stories, containing a headline, a publication date, a link to a photo, and a short summary of

the story. You can choose any web sites that have these features, but to simplify your task

you should seek ones that have a simple source-code format (when downloaded by a Python

script). This appendix suggests some such sites, but you are strongly encouraged to find your

own of personal interest.

The following links point to Rich Site Summary, a.k.a. Really Simple Syndication,

web feed documents. RSS documents are written in XML and

are used for publishing information that is updated frequently in a format

that can be displayed by RSS reader software. Such documents have a

simple standardised format, so we can rely on them always formatting

their contents in the same way, making it relatively easy to extract specific

elements from the document’s source code via pattern matching.

However, a disadvantage of using RSS feeds is that they can be hard to find! Often you can

discover them only by looking for the RSS symbol at the bottom of web pages or by trialand-error

to create the corresponding URL. Because RSS feeds are not intended for human

consumption, they don’t usually feature prominently in the results of web searches using

standard search engines such as Google, DuckDuckGo, Bing, etc. You will need to do some

exploration online to find suitable news feeds for your solution.

Note that you are not limited to using RSS sites for this assignment, but you may find other,

more complex, web documents harder to work with. Most importantly, you are not required

to use any of the sources below for this task. You are strongly encouraged to find online

documents of your own, that contain material of personal interest.

The following web sites are RSS feeds which we found could be viewed in a standard web

browser. We have not confirmed that these are all ideally suited to the assignment. You will

need to work that out for yourself. In particular, we have not checked to see if their servers

deny access to programs other than web browsers, nor have we checked to see what data they

deliver to Python programs.

The following RSS news feeds appear to have headlines, publication dates, story summaries

and links to photos all on the same page. (We used some of these for our demonstration solution.)

o http://www.sbs.com.au/news/rss/Section/Top+Stories — SBS News: Top stories

o https://www.9news.com.au/rss — Channel 9 (Australia) news

o https://www.qt.com.au/feeds/rss/homepage — Queensland Times

o http://www.canberratimes.com.au/rss.xml — Canberra Times: Local news

o https://www.whitsundaytimes.com.au/feeds/rss/homepage — Whitsunday Times

o https://www.crikey.com.au/feed/ — Crikey: Australian news and politics

o http://www.goulburnpost.com.au/rss.xml — Goulburn Post: Local news

o https://www.darkreading.com/rss_simple.asp — Dark Reading: Security news

o https://www.abc.net.au/radionational/feed/2890360/podcast.xml — ABC Radio National Breakfast

news (includes audio links)

o http://www.perthnow.com.au/feed — Perth Now: Breaking news

o https://www.cnet.com/rss/news/ — CNet technology news

o https://www.news-mail.com.au/feeds/rss/homepage — Bundaberg News-Mail

o http://rss.upi.com/news/news.rss — UPI news

IFB104'Building'IT'Systems

Semester'2,'2019

o https://www.coffscoastadvocate.com.au/feeds/rss/homepage — Coffs Coast Advocate

o https://www.dailyexaminer.com.au/feeds/rss/homepage — Grafton Daily Examiner

o https://www.sunshinecoastdaily.com.au/feeds/rss/homepage — Sunshine Coast Daily

o https://www.dailymail.co.uk/articles.rss — Daily Mail (UK): Latest news

o https://www.dailymail.co.uk/auhome/index.rss — Daily Mail: Australian news

o https://www.dailymail.co.uk/tvshowbiz/index.rss — Daily Mail: TV and Showbiz

o https://www.dailymail.co.uk/sciencetech/index.rss — Daily Mail: Science news

o https://www.blogger.com/feeds/2886832199291333748/posts/default — Vivian Violine’s blog: Entertainment

and business news

o http://rss.cnn.com/rss/cnn_topstories.rss — CNN News: Top Stories

o https://www.themorningbulletin.com.au/feeds/rss/homepage — Rockhampton Morning Bulletin

o http://feeds.nbcnews.com/feeds/topstories — NBC News

o https://rss.nytimes.com/services/xml/rss/nyt/HomePage.xml — New York Times: Top Stories

o http://www.nytimes.com/services/xml/rss/nyt/Business.xml — New York Times: Business News

o https://rss.nytimes.com/services/xml/rss/nyt/Technology.xml — New York Times: Tech News

o http://rssfeeds.usatoday.com/usatoday-NewsTopStories — USA Today: Top stories

o http://rssfeeds.usatoday.com/usatoday-LifeTopStories — USA Today: Lifestyle and entertainment

o http://rssfeeds.usatoday.com/usatoday-TechTopStories — USA Today: Tech news (not updated as often

as other USA Today pages)

o https://threatpost.com/feed/ — Threatpost: Security news

o https://www.infoworld.com/index.rss — InfoWorld

o https://www.thechronicle.com.au/feeds/rss/homepage — Toowoomba Chronicle

o https://www.indiatvnews.com/rssnews/topstory.xml — India TV News: Top stories

o https://www.indiatvnews.com/rssnews/topstory-world.xml — India TV News: World news

o https://www.indiatvnews.com/rssnews/topstory-entertainment.xml — India TV News: Entertainment

o http://feeds.foxnews.com/foxnews/world — Fox News: World news

o http://feeds.foxnews.com/foxnews/entertainment — Fox News: Entertainment news

o http://feeds.foxnews.com/foxnews/science — Fox News: Science news

o http://feeds.foxnews.com/foxnews/tech — Fox News: Technology news

o https://nypost.com/feed/ — New York Post: All stories

o https://nypost.com/news/feed/ — New York Post: Breaking news

o https://nypost.com/entertainment/feed/ — New York Post: Entertainment news

o https://www.engadget.com/rss.xml — Technology and gadget news

o https://www.wired.com/feed — Wired magazine: Technology news

o https://abcnews.go.com/abcnews/internationalheadlines — ABC (USA) international news

o http://www.lemonde.fr/rss/une.xml — Le Monde: News from France (in French)

o https://feeds.gizmodo.com.au/gizmodoaustralia — Gizmodo’s Australian feed: News for geeks

o http://syndication.eonline.com/syndication/feeds/rssfeeds/topstories.xml — E! Entertainment news: