Question

I will like to compare automobile producers. This assignment suppose to read data like div tags a etc. And count occurrence of them.

Reading from a URL while working with an API (using Mediawiki API as an example)

Input: Will be obtained from a URL using Mediawiki API -- starter code below

Output: Up to you... sort of.

What to submit: Upload a report (.pdf preferred) containing screenshots of code, output, and discussion/conclusions to d2l dropbox. Please also submit your code (yourlastname_lab3_p2.py)

Assignment Description: Compare how Wikipedia articles describe various items in the same category. The choice of items and category is up to you. Briefly describe the category, items, and your hypothesis in your report. Example categories/items/questions:

1) Automotive Brands; Toyota vs. Honda vs. Ford vs. Chevy; Do Wikipedia articles use significantly different terms when describing these brands? Are brands associated with certain countries described differently?

2) College football teams; similar questions as in (1)

3) Universities; similar questions as in (1)

4) Historical eras or significant events; Classical/bronze age history topics vs. Medieval vs. Modern; Does the terminology historians use change significantly (not the content being described -- obviously that will be different, but the historians' language itself)?

Detailed information about the API can be found here:

https://www.mediawiki.org/w/api.php?action=help&modules=query

https://www.mediawiki.org/wiki/Extension:TextExtracts

Starter code to help you get started using the Mediawiki API (NOTE: Use ps11. "requests" is a Python 2.7 module):

___________________________________________________

import requests

response = requests.get(
    'https://en.wikipedia.org/w/api.php',
    params={
            'action': 'query',
            'format': 'json',
            'titles': 'University',
            'prop': 'extracts',
            'exintro': True,
            'explaintext': True,
           }
    ).json()
page = next(iter(response['query']['pages'].values()))
print(page['extract'])

__________________________________________________

Action, format, and title are standard API parameters.

prop: extracts -- uses TextExtract extension

exintro: True -- Return only content before the first section

explaintext: Return extracts as plain text instead of HTML

(see "detailed information" section's link for more info)

You may choose to work with extracts or full articles -- this is up to you.

Note: You may use one of the many "third-party" Python Wikipedia parsers available online if you choose. Please cite it properly if you do. I'm not 100% sure about this, but I think it may actually make the lab more difficult though... We could say this: "If you'd like to make Part II of the lab more challenging, learn how to use a third-party parser to extract text from Wikipedia articles".

Answer 1

#include <iostream>
using namespace std;

int main()
{
    string str = "C++ Programming is awesome";
    char checkCharacter = 'a';
    int count = 0;

    for (int i = 0; i < str.size(); i++)
    {
        if (str[i] ==  checkCharacter)
        {
            ++ count;
        }
    }

    cout << "Number of " << checkCharacter << " = " << count;

    return 0;
}

#include<iostream.h>
#include<conio.h>
#include<stdlib.h>
void main()
{
        clrscr();
        int i, count=0;
        char str[1000], ch;
        cout<<"Enter the String : ";
        gets(str);
        cout<<"Enter a character to find frequency : ";
        cin>>ch;
        for(i=0; str[i]!='\0'; i++)
        {
                if(ch==str[i])
                {
                        count++;
                }
        }
        cout<<"Frequency of the character "<<ch<<" = "<<count;
        getch();
}