Here's a brief transcript showing the kind of reporting we expect...

Here's a brief transcript showing the kind of reporting we expect to see in this project (as always user input is in bold):

Enter a list of population files: populationFiles.csv
Enter a start year: 2010
Enter an end year: 2019

State/County            2010         2019       Growth
--------------- ------------ ------------ ------------

--------------- ------------ ------------ ------------
California        37,319,502   39,512,223   +2,192,721  
--------------- ------------ ------------ ------------
   Los Angeles     9,823,246   10,039,107     +215,861
   San Diego       3,103,212    3,338,330     +235,118
   Orange          3,015,171    3,175,692     +160,521
   Riverside       2,201,576    2,470,546     +268,970
   San Bernardi    2,040,848    2,180,085     +139,237
   Santa Clara     1,786,040    1,927,852     +141,812
   Alameda         1,512,986    1,671,329     +158,343
   Sacramento      1,421,383    1,552,058     +130,675
   Contra Costa    1,052,540    1,153,526     +100,986
   Fresno            932,039      999,101      +67,062
   Kern              840,996      900,202      +59,206
   San Francisc      805,505      881,549      +76,044
   Ventura           825,097      846,006      +20,909
   San Mateo         719,699      766,573      +46,874
   San Joaquin       687,127      762,148      +75,021
   Stanislaus        515,145      550,660      +35,515
   Sonoma            484,755      494,336       +9,581
   Tulare            442,969      466,195      +23,226
   Solano            413,967      447,643      +33,676
   Santa Barbar      424,231      446,499      +22,268
   Monterey          416,373      434,061      +17,688
   Placer            350,021      398,329      +48,308
   San Luis Obi      269,802      283,111      +13,309
   Merced            256,721      277,680      +20,959
   Santa Cruz        263,147      273,213      +10,066
   Marin             252,904      258,826       +5,922
   Yolo              201,073      220,500      +19,427
   Butte             219,949      219,186         -763
   El Dorado         181,136      192,843      +11,707
   Imperial          174,716      181,215       +6,499
   Shasta            177,274      180,080       +2,806
   Madera            150,986      157,327       +6,341
   Kings             152,370      152,940         +570
   Napa              136,759      137,744         +985
   Humboldt          135,009      135,558         +549
   Nevada             98,790       99,755         +965
   Sutter             94,751       96,971       +2,220
   Mendocino          87,799       86,749       -1,050
   Yuba               72,348       78,668       +6,320
   Tehama             63,559       65,084       +1,525
   Lake               64,735       64,386         -349
   San Benito         55,516       62,808       +7,292
   Tuolumne           55,190       54,478         -712
   Calaveras          45,468       45,905         +437
   Siskiyou           44,938       43,539       -1,399
   Amador             37,886       39,752       +1,866
   Lassen             34,831       30,573       -4,258
   Glenn              28,127       28,393         +266
   Del Norte          28,566       27,812         -754
   Colusa             21,437       21,547         +110
   Plumas             19,914       18,807       -1,107
   Inyo               18,511       18,039         -472
   Mariposa           18,277       17,203       -1,074
   Mono               14,257       14,444         +187
   Trinity            13,755       12,285       -1,470
   Modoc               9,694        8,841         -853
   Sierra              3,220        3,005         -215
   Alpine              1,161        1,129          -32
--------------- ------------ ------------ ------------
   Average pop.      643,439      681,245
   Median pop.       179,205      187,029

--------------- ------------ ------------ ------------
Indiana            6,490,432    6,732,219     +241,787
--------------- ------------ ------------ ------------
   Marion            904,591      964,582      +59,991
   Lake              495,947      485,493      -10,454
   Allen             355,945      379,299      +23,354
   Hamilton          276,493      338,011      +61,518
   St Joseph         266,797      271,826       +5,029
   Elkhart           197,451      206,341       +8,890
   Tippecanoe        173,104      195,732      +22,628
   Vanderburgh       179,842      181,451       +1,609
   Porter            164,487      170,389       +5,902
   Hendricks         145,954      170,311      +24,357
   Johnson           140,269      158,167      +17,898
   Monroe            138,566      148,431       +9,865
   Madison           131,619      129,569       -2,050
   Clark             110,567      118,302       +7,735
   Delaware          117,665      114,135       -3,530
   LaPorte           111,459      109,888       -1,571
   Vigo              107,888      107,038         -850
   Bartholomew        76,818       83,779       +6,961
   Howard             82,752       82,544         -208
   Kosciusko          77,340       79,456       +2,116
   Floyd              74,709       78,522       +3,813
   Hancock            70,247       78,168       +7,921
   Morgan             69,138       70,489       +1,351
   Boone              56,916       67,843      +10,927
   Wayne              68,889       65,884       -3,005
   Grant              69,903       65,769       -4,134
   Warrick            59,839       62,998       +3,159
   Dearborn           50,083       49,458         -625
   Henry              49,530       47,972       -1,558
   Noble              47,454       47,744         +290
   Marshall           47,000       46,258         -742
   Lawrence           46,102       45,370         -732
   Shelby             44,297       44,729         +432
   Jackson            42,586       44,231       +1,645
   DeKalb             42,336       43,475       +1,139
   Dubois             41,905       42,736         +831
   Harrison           39,330       40,515       +1,185
   LaGrange           37,159       39,614       +2,455
   Montgomery         38,098       38,338         +240
   Cass               38,985       37,689       -1,296
   Putnam             37,909       37,576         -333
   Knox               38,391       36,594       -1,797
   Huntington         37,117       36,520         -597
   Adams              34,444       35,777       +1,333
   Miami              36,810       35,516       -1,294
   Steuben            34,109       34,594         +485
   Whitley            33,353       33,964         +611
   Gibson             33,545       33,659         +114
   Jasper             33,496       33,562          +66
   Daviess            31,720       33,351       +1,631
   Clinton            33,221       32,399         -822
   Jefferson          32,395       32,308          -87
   Greene             33,207       31,922       -1,285
   Wabash             32,848       30,996       -1,852
   Ripley             28,815       28,324         -491
   Wells              27,682       28,296         +614
   Washington         28,292       28,036         -256
   Jennings           28,481       27,735         -746
   Decatur            25,798       26,559         +761
   Clay               26,854       26,225         -629
   Posey              25,861       25,427         -434
   Randolph           26,178       24,665       -1,513
   White              24,683       24,102         -581
   Scott              24,171       23,873         -298
   Fayette            24,325       23,102       -1,223
   Starke             23,345       22,995         -350
   Franklin           23,059       22,758         -301
   Owen               21,566       20,799         -767
   Sullivan           21,390       20,669         -721
   Jay                21,179       20,436         -743
   Spencer            20,915       20,277         -638
   Carroll            20,199       20,257          +58
   Fulton             20,817       19,974         -843
   Orange             19,814       19,646         -168
   Perry              19,409       19,169         -240
   Parke              17,275       16,937         -338
   Rush               17,384       16,581         -803
   Fountain           17,276       16,346         -930
   Vermillion         16,116       15,498         -618
   Tipton             15,878       15,148         -730
   Brown              15,207       15,092         -115
   Newton             14,233       13,984         -249
   Pike               12,720       12,389         -331
   Pulaski            13,323       12,353         -970
   Blackford          12,771       11,758       -1,013
   Switzerland        10,717       10,751          +34
   Crawford           10,708       10,577         -131
   Martin             10,359       10,255         -104
   Benton              8,863        8,748         -115
   Warren              8,521        8,265         -256
   Union               7,537        7,054         -483
   Ohio                6,086        5,875         -211
--------------- ------------ ------------ ------------
   Average pop.       70,548       73,176
   Median pop.        33,827       34,279

--------------- ------------ ------------ ------------
Ohio              11,539,336   11,689,100     +149,764
--------------- ------------ ------------ ------------
   Franklin        1,166,202    1,316,756     +150,554
   Cuyahoga        1,278,088    1,235,072      -43,016
   Hamilton          802,278      817,473      +15,195
   Summit            541,645      541,013         -632
   Montgomery        535,597      531,687       -3,910
   Lucas             441,434      428,348      -13,086
   Butler            369,102      383,134      +14,032
   Stark             375,372      370,606       -4,766
   Lorain            301,478      309,833       +8,355
   Warren            213,429      234,602      +21,173
   Lake              230,014      230,149         +135
   Mahoning          238,381      228,683       -9,698
   Delaware          175,099      209,177      +34,078
   Clermont          197,604      206,428       +8,824
   Trumbull          209,840      197,974      -11,866
   Medina            172,509      179,746       +7,237
   Licking           166,705      176,862      +10,157
   Greene            161,588      168,937       +7,349
   Portage           161,386      162,466       +1,080
   Fairfield         146,417      157,574      +11,157
   Clark             138,274      134,083       -4,191
   Wood              125,950      130,817       +4,867
   Richland          124,162      121,154       -3,008
   Wayne             114,394      115,710       +1,316
   Miami             102,487      106,987       +4,500
   Allen             106,358      102,351       -4,007
   Columbiana        107,890      101,883       -6,007
   Ashtabula         101,403       97,241       -4,162
   Geauga             93,389       93,649         +260
   Tuscarawas         92,543       91,987         -556
   Muskingum          86,214       86,215           +1
   Ross               78,098       76,666       -1,432
   Hancock            74,689       75,783       +1,094
   Scioto             79,664       75,314       -4,350
   Erie               76,978       74,266       -2,712
   Belmont            70,333       67,006       -3,327
   Athens             65,173       65,327         +154
   Jefferson          69,670       65,325       -4,345
   Marion             66,458       65,093       -1,365
   Knox               61,090       62,322       +1,232
   Washington         61,713       59,911       -1,802
   Lawrence           62,424       59,463       -2,961
   Union              52,464       58,988       +6,524
   Sandusky           60,885       58,518       -2,367
   Pickaway           55,740       58,457       +2,717
   Huron              59,560       58,266       -1,294
   Seneca             56,618       55,178       -1,440
   Ashland            53,321       53,484         +163
   Darke              52,963       51,113       -1,850
   Shelby             49,349       48,590         -759
   Logan              45,743       45,672          -71
   Auglaize           45,898       45,656         -242
   Madison            43,434       44,731       +1,297
   Holmes             42,473       43,960       +1,487
   Brown              44,863       43,432       -1,431
   Highland           43,621       43,161         -460
   Fulton             42,629       42,126         -503
   Clinton            41,922       41,968          +46
   Crawford           43,754       41,494       -2,260
   Mercer             40,788       41,172         +384
   Preble             42,170       40,882       -1,288
   Ottawa             41,359       40,525         -834
   Champaign          40,078       38,885       -1,193
   Guernsey           40,155       38,875       -1,280
   Defiance           39,082       38,087         -995
   Williams           37,512       36,692         -820
   Coshocton          36,938       36,600         -338
   Perry              36,037       36,134          +97
   Morrow             34,790       35,328         +538
   Putnam             34,476       33,861         -615
   Jackson            33,248       32,413         -835
   Hardin             32,127       31,365         -762
   Gallia             31,072       29,898       -1,174
   Fayette            29,014       28,525         -489
   Van Wert           28,678       28,275         -403
   Hocking            29,478       28,264       -1,214
   Pike               28,612       27,772         -840
   Adams              28,537       27,698         -839
   Henry              28,171       27,006       -1,165
   Carroll            28,846       26,914       -1,932
   Meigs              23,731       22,907         -824
   Wyandot            22,588       21,772         -816
   Paulding           19,557       18,672         -885
   Harrison           15,825       15,040         -785
   Morgan             15,034       14,508         -526
   Noble              14,660       14,424         -236
   Monroe             14,609       13,654         -955
   Vinton             13,405       13,085         -320
--------------- ------------ ------------ ------------
   Average pop.      131,128      132,830
   Median pop.        58,089       58,487

--------------- ------------ ------------ ------------
Wyoming              564,487      578,759      +14,272
--------------- ------------ ------------ ------------
   Laramie            92,236       99,500       +7,264
   Natrona            75,470       79,858       +4,388
   Campbell           46,245       46,341          +96
   Sweetwater         43,574       42,343       -1,231
   Fremont            40,198       39,261         -937
   Albany             36,469       38,880       +2,411
   Sheridan           29,148       30,485       +1,337
   Park               28,241       29,194         +953
   Teton              21,296       23,464       +2,168
   Uinta              21,089       20,226         -863
   Lincoln            18,099       19,830       +1,731
   Carbon             15,848       14,800       -1,048
   Converse           13,822       13,822           +0
   Goshen             13,422       13,211         -211
   Big Horn           11,666       11,790         +124
   Sublette           10,261        9,831         -430
   Johnson             8,590        8,445         -145
   Platte              8,665        8,393         -272
   Washakie            8,530        7,805         -725
   Crook               7,118        7,584         +466
   Weston              7,198        6,927         -271
   Hot Springs         4,811        4,413         -398
   Niobrara            2,491        2,356         -135
--------------- ------------ ------------ ------------
   Average pop.       24,542       25,163
   Median pop.        15,848       14,800

As you can see, this project has you load a list of states and their associated population files.  For the above transcript the input file looks like this:

California,CaliforniaPopulationData.csv
Indiana,IndianaPopulationData.csv
Ohio,OhioPopulationData.csv
Wyoming,WyomingPopulationData.csv

The file has a state and its associated population data file, one per line, separated by a comma.

Each population data file has the following format - here are the first few lines from the Ohio file:

County,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019
Adams,28537,28459,28293,28089,28066,27926,27807,27753,27694,27698
Allen,106358,105988,105244,105055,104848,104095,103613,103093,102725,102351
Ashland,53321,53252,53239,53153,53161,53310,53520,53662,53706,53484
Ashtabula,101403,101085,100252,99746,99027,98404,98171,97748,97587,97241
Athens,65173,65079,64610,64594,64783,65886,66352,66503,65519,65327
Auglaize,45898,45741,45770,45801,45737,45734,45766,45753,45736,45656
Belmont,70333,70122,69709,69563,69367,68973,68606,68002,67533,67006
Brown,44863,44629,44281,44111,43933,43697,43638,43523,43570,43432
Butler,369102,370123,370550,371395,373750,375998,378354,380607,382000,383134

The first line is a header that indicates what each column holds.  This file says that it holds a county in the first column, and then data for the years 2010-2019 in each column after.  Each county for the state is then listed one per line with the associated population estimate it had each year following it.

To hold this data you will need to create two classes based on the following interfaces - a State interface for state-level data and a County interface for county level data.

The County Interface

In the project folder you will find the County interface file.  This interface is reproduced below:

public interface County {

/**
* Sets the name of the county
* @param name the county name
* @postcond this county name is set to name
*/
void setName(String name);

/**
* Returns the name of the county
* @return the name of this county
*/
String getName();

/**
* Adds a population value for a specific year
* @param year the year to set the population for
* @param pop the population for the county in year
* @postcond the year/pop pair is added to this county
*/
void addPopulation(int year, int pop);

/**
* Returns the population for a given year
* @param year the year to retrieve the population for
* @return the population for this county in the year year
*/
int getPopulation(int year);

}

Each county is defined by a few elements:

• A name
• A collection of year/population pairs for each year in the input file

The methods in the County interface need to be implemented in a concrete class (you can choose how to name this class).  You should also create a toString() method for this class for debugging purposes - the toString() method's output is not defined, so you can choose to implement this as you want.

The State Interface

In the project folder you will also find the State interface file.  This interface is reproduced below:

public interface State {

/**
* Sets the name of the state
* @param name the state name
* @postcond this state name is set to name
*/
void setName(String name);

/**
* Returns the name of the state
* @return the name of this state
*/
String getName();

/**
* Adds a county to this state
* @param county county to add to this state
* @postcond county is added to the state's collection of counties
*/
void addCounty(County county);

/**
* Returns a county based on its name
* @param name name of the county to retrieve
* @precond a county by the name provided is in the state
* @return the county associated with name
*/
County getCounty(String name);

/**
* Returns the total population of the state for a given year
* @param year year to get the population for
* @return total population for the state in the year year
*/
int getPopulation(int year);

/**
* Returns a list of counties in alphabetical order by county name
* @return a list of counties in the state
*/
List<County> getCounties();

/**
* Returns a list of counties in order of descending population
* @param year year to use to order counties by population
* @return list of counties in order of descending population
*/
List<County> getCountiesByPopulation(int year);

}

Each state is defined by:

• A name
• A collection of counties

The methods above return different values - the getPopulation method returns the population for the State in a particular year, which is the sum of all of the given population values for its counties. The getCounties method returns a list of the County objects in the State in order of their names while the getCountiesByPopulation method returns a list of the County objects in the State in descending order of their populations.  In order to construct those two methods you will need to use the Comparator classes described below.

In addition to the above methods, you must implement a toString() method in your Item class for debugging purposes.  Again there is no requirement as to what your toString() method needs to display when called but it should be something that can help you with your program and/or debugging.

The Comparator Classes

In the project folder you will also find two class shells for two Comparator classes.  These classes allow you to make use of the Collections.sort() method or a PriorityQueue with objects that do not have a natural ordering defined (or when you want to use a different order).  For example, the CountyComparatorByPopulation shell looks like this:

public class CountyComparatorByPopulation implements Comparator<County> {

private int year;

public CountyComparatorByPopulation(int year) {
this.year = year;
}

@Override
public int compare(County o1, County o2) {
//TODO: Your code here
}

}

This class has just the compare method for you to implement.  This method must return a -1 if the County object o1 comes before the County object o2, a +1 if the County object o1 comes after o2, and a 0 if the two objects are equal.  For this particular class it should return Counties in descending order by population.  So if o1 has a higher population in the given year set by the constructor then it should return a -1.  If o1 has a lower population than o2 it should return a +1.  And if o1 and o2 have equal populations it should return a 0.

The second Comparator class should do the same thing, but organizing County objects by name rather than by population.

Once you have the Comparator classes written you can use them in one of two ways.  The first is by using them with a PriorityQueue:

CountyComparatorByPopulation cmp = new CountyComparatorByPopulation(year);
PriorityQueue<County> pq = new PriorityQueue<>(numCounties, cmp);

 

The second would be the use them with a list and the Collections.sort() method:

List<County> counties = new ArrayList<>();
// fill the list with County objects
CountyComparatorByPopulation cmp = new CountyComparatorByPopulation(year);
Collections.sort(counties, cmp);

If you do the above, the list of counties is now sorted in descending order by their populations in the year provided to the Comparator constructor.

For more on Comparators, the sort() method, and PriorityQueues, see the Java API for each topic.

The Reporting program

Once you have the individual classes created, write the final Reporting program to tie it all together.  This program will be made of static methods to produce the transcript you see above.  It should work for any pair of years that the user chooses, with an error message if either of the chosen years don't exist in the file.  No matter what bad input the user provides the program should exits gracefully rather than crash (so it should be robust to bad input files as well as to bad dates).  The test cases will only be checking to make sure that your code produces the right output but we will be checking for this in the grading so make sure that you code for bad inputs!  

NOTE:  If you find yourself failing test cases but the output looks good, check to see if you are using any "\n" characters in your output.  If you are, replace them with calls to System.lineSeparator() - this uses the platform independent line separator character(s) and should make it compatible with the test cases.

To use this if your code has something like this:

String myString = str + "\n";

Replace it with something like this:

String myString = str + System.lineSeparator();

package osu.cse2123;

/**

* A Comparator for County objects in ascending order of name

*

* @author YOUR NAME HERE

* @version DATE HERE

*/

import java.util.Comparator;

public class CountyComparatorByName implements Comparator<County> {

@Override

public int compare(County o1, County o2) {

// TODO: Your code here

// TODO: The line below is only to allow this to compile

// TODO: Delete the line below and replace with your own code

return 0;

}

}

package osu.cse2123;

/**

* A Comparator for County objects in descending order of population

*

* @author YOUR NAME HERE

* @version DATE HERE

*/

import java.util.Comparator;

public class CountyComparatorByPopulation implements Comparator<County> {

private int year;

public CountyComparatorByPopulation(int year) {

this.year = year;

}

@Override

public int compare(County o1, County o2) {

// TODO: Your code here

// TODO: The line below is only to allow this to compile

// TODO: Delete the line below and replace with your own code

return 0;

}

}

import java.io.File;

import java.io.IOException;

import java.util.ArrayList;

import java.util.Collections;

import java.util.List;

import java.util.Scanner;

import java.util.Set;

public class Reporting {

public static void main(String[] args) {

// TODO: Your code here

}

}

ReportingTranscriptTest.java

package osu.cse2123;

import static org.junit.jupiter.api.Assertions.*;

import java.io.ByteArrayInputStream;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.FileNotFoundException;
import java.io.InputStream;
import java.io.PrintStream;
import java.util.Scanner;

import org.junit.jupiter.api.Test;

class ReportingTranscriptTest {
private static String runMain(String input) {
 // Set System.in and System.out to our test values
 // Create a stream to hold the output
 ByteArrayOutputStream baos = new ByteArrayOutputStream();
 PrintStream ps = new PrintStream(baos);
 // IMPORTANT: Save the old System.out!
 PrintStream old = System.out;
 // Tell Java to use your special stream
 System.setOut(ps);

 InputStream oldInput = System.in;
 InputStream newInput = new ByteArrayInputStream(input.getBytes());
 System.setIn(newInput);

 // Run the actual project here, output will go into baos, input will
 // come from newInput.
 // This is implemented in the child class inherited from ProjectTest
 // for flexibility.

 Reporting.main(new String[0]);

 // Put System.out and System.in back to what they were.
 // IMPORTANT - make sure to flush System.out so it all gets written
 // to the ByteArray
 System.out.flush();
 System.setOut(old);
 System.setIn(oldInput);

 // Return our output as a String instead of as a ByteArray
 return baos.toString();
}

public static String loadFromFile(String fname) {
 String result ="";
 try {
  Scanner input = new Scanner(new File(fname));
  while (input.hasNext()) {
   result = result+input.nextLine();
   //if (input.hasNextLine()) {
    result += System.lineSeparator();
   //}
  }
  input.close();
 }
 catch(FileNotFoundException e) {
  System.out.println("ERROR - cannot find file "+fname);
 }
 return result;
}

@Test
void testTranscriptOne() {
 String keys = "populationFiles.csv\n2010\n2019\n";
 String testRun = runMain(keys);
 String truth = loadFromFile("output_transcript1.txt");
 assertEquals(truth,testRun,"full program transcript");
}

@Test
void testTranscriptTwo() {
 String keys = "populationFiles.csv\n2018\n2019\n";
 String testRun = runMain(keys);
 String truth = loadFromFile("output_transcript2.txt");
 assertEquals(truth,testRun,"full program transcript");
}

@Test
void testTranscriptThree() {
 String keys = "populationFiles2.csv\n2010\n2011\n";
 String testRun = runMain(keys);
 String truth = loadFromFile("output_transcript3.txt");
 assertEquals(truth,testRun,"full program transcript");
}

}