An Affordable REST - Coder Camp Hamilton 2019

AN AFFORDABLE REST
CODING FOR GOOD – A CASE STUDY FOR SUBSIDIZED HOUSING IN TORONTO
SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 1

ABOUT ME
 Quality Assurance Supervisor, Weever Apps
 Former Instructor, Sheridan College & Mohawk College in
Web Design (including WordPress) and Capstone Project
 Co-organizer, WordCamp Hamilton, 2015-18
 “Lead Dudette” defined as: "a young woman or girl who is
very popular or admired by her peers”. Thanks @modmatt!

AN AFFORDABLE REST
 The slides have been posted to http://shanta.ca
 The live project can be found at http://wilt.ninja (wilt = What I Learned Today)
 The API is at http://wilt.ninja/data
 The Github Repository is at https://github.com/TantienHime/An-Affordable-
REST

THE CASE: CITY OF TORONTO – TORONTO COMMUNITY HOUSING
The City of Toronto has a 10-year waiting list for subsidized housing.
In order to determine which development that a seeker can apply to,
they must speak with someone at Toronto Community Housing. All
of the Organizational Unit Managers email addresses and phone
numbers are identical. Can you imagine 82,000+1 households calling
one number and sending to a single email address?
SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 41. Source: https://www.thestar.com/news/gta/2016/05/25/ontarios-affordable-housing-wait-list-grows.html

WHAT’S THE PROBLEM?
When searching for housing, the primary need is the unit size (how many
bedrooms) and special needs (such as wheelchair accessible). The criteria is less
about location, and more about need.
I called the offices of three city councillors to test if what I was going for made
sense. I never got a response. Also, the open data was unusable, given the
above criteria.

WHAT’S THE SOLUTION?
What if seekers had the ability to find out which units in the City are available to
them, based on unit size and speciality? That would shorten the time to serve
these people and reduce the amount of work on an already burdened system.
Note: Since I did the project, they have made some updates to the website, but
it’s still pretty bad.

Snapshot of data
from the Open Data
portal for the City of
Toronto

SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 8https://www1.toronto.ca/wps/portal/contentonly?vgnextoid=e59aa39b8a930410VgnVCM10000
071d60f89RCRD&vgnextchannel=1a66e03bb8d1e310VgnVCM10000071d60f89RCRD

SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 9https://www.torontohousing.ca/about/our-housing/Pages/default.aspx

SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 10https://www.torontohousing.ca/about/our-housing/Pages/Don-Valley-Beaches.aspx

SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 11https://www.torontohousing.ca/about/our-housing/Pages/Don-Valley-Beaches.aspx

MY PROCESS
I wrote the entire app in React and Node and deployed on AWS in a week.
1. Create mock data based on the information that I needed to see, such as unit size and speciality.
2. Scrape the data from the existing site to determine how many org units I need to scrape
3. Feed the previous step into another scrape to grab the names of the buildings, etc., along with the org
unit info.
4. Push the mock data into the scraped data to create a single JSON file and serve it up in an API
5. Serve the data from the API to a front end

1. CREATE THE MOCK DATA
 I used Mockaroo
 This is a sample of a single
building’s data
 I created 1,000 records and just
reused them as needed
{"unitType":
{"bachelor":4,"oneBr":142,
"twoBr":204,"threeBr":10,
"fourBr":90},
"special":
{"seniors":false,
"supportive":false,
"accessible":false,
"aboriginal":false}}

2. DETERMINE NUMBER OF ORG UNITS BY SCRAPING
<li class="static selected"><a class="static selected menu-item
ms-core-listMenu-item ms-displayInline ms-bold ms-core-listMenu-
selected ms-navedit-linkNode" tabindex="0" href="/about/our-
housing/Pages/Don-Valley-Beaches.aspx">Don Valley BeachesCurrently selected</a></li>

2. DETERMINE NUMBER OF ORG UNITS BY SCRAPING (CON’T)
axios.get('https://www.torontohousing.ca/about/our-
housing/Pages/default.aspx')
.then(res => {
const $ = cheerio.load(res.data);
let sidebarData = '#zz4_RootAspMenu'; // This targets the sidebar
menu that contains the organizational names and corresponding
links.
let numOfOrgs = $(sidebarData).children().length; // Should be 11
items.
for(let i=2; i<numOfOrgs; i++){
let orgRow = $(sidebarData).children()[i];
let orgObject = $(orgRow).children()[0];
let orgLinkRaw = $(orgObject)[0];
let orgLink = ('https://www.torontohousing.ca'+
orgLinkRaw.attribs.href);
// urlArray.push(axios.get(req[i].orgLink)); // This one doesn't work
yet
urlArray.push(orgLink); // This will create the array correctly.
}
})
.catch(err => {
console.log(err);
});

2. DETERMINE NUMBER OF ORG UNITS BY SCRAPING (CON’T)
Ideally, I should have been able to
hand off the created array to Axios to
repeat the following steps for as
many items as are in the array.
Unfortunately, one of the items didn’t
work, so I had to manually hand over
the remaining 10 items.
axios.all([axios.get('https://www.toront
ohousing.ca/about/our-
housing/Pages/Wexton-
Rexdale.aspx'),…

3. CAPTURE THE ORG UNIT INFO AND BUILDINGS
Operating Unit Manager: 
 John Perkovic 
Office Location and hours: 
 145 Strathmore Blvd.
 Monday to Friday 8:30am to 4:30pm 
Tel: (416) 981-5500 
Email:
<a href="mailto:info@torontohousing.ca">
info@torontohousing.ca</a>…

3. CAPTURE THE ORG UNIT INFO AND BUILDINGS (CON’T)
Grab the organizational unit
information and put it into an object,
…
1. .then(axios.spread (function (res)…
2. ...const orgData = 'div.ms-rtestate-
field'; let orgManager =
$(orgData).children()[2].prev.data;
…

3. CAPTURE THE ORG UNIT INFO AND BUILDINGS (CON’T)
<table align="left" width="90%" cellpadding="10"
border="1" style="width:100%;" class="table table-
hover"><tbody><tr><td width="8%">
Dev ID</td><td align="left"
width="21%">
Development Name</td><td align="left"
width="71%">
Address(es)</td></tr>
<tr><td>701</td><td>Asquith Park</td><td>40 Asquith
Ave.
 </td></tr>
…then each building.

4. PUSH IN THE MOCK DATA & SERVE IN API
As each building is built,
the mock data is pushed
into the object.
let tempAddress = $(tempRow).children()[2]; //The third
column in the table.
let bldgAddress = $(tempAddress).text();
let bldgData = {
"DEV_ID" : bldgID,
"DEV_NAME" : bldgName,
"BLDG_ADDRESS" : bldgAddress,
"Unit_Type" : mockData[i].unitType,
"Speciality" : mockData[i].special
}SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 20

4. PUSH IN THE MOCK DATA & SERVE IN API (CON’T)
{"orgUnit": "Weston Rexdale",
"orgManager": "Joan White",
"orgAddress": "2765 Islington Ave.",
"orgPhone": "(416) 981-5500",
"orgHours": "Monday to Friday 8:30am to 4:30pm",
"orgEmail": "info@torontohousing.ca",
"orgBuildings": [{
"DEV_ID": "47",
"DEV_NAME": "Albion Shendale",
"BLDG_ADDRESS": "275 Albion Rd.;1 Shendale Dr. ",
"Unit_Type": {
"bachelor": 5,
"oneBr": 172,
"twoBr": 47,
"threeBr": 171,
"fourBr": 5 },
"Speciality": {
"seniors": true,
"supportive": true,
"accessible": true,
"aboriginal": false}},

4. PUSH IN THE MOCK DATA & SERVE IN API (CON’T)
fs.writeFile('./data/webscrapeResults.JSON', JSON.stringify(orgArr, null, 2), ()
=> {
console.log('File written');
})
http://wilt.ninja/data

5. SERVE THE DATA TO THE FRONT END
Now, a seeker can select the most
pertinent information that they can
use to make informed decisions.

5. SERVE THE DATA TO THE FRONT END (CON’T)
Shows the relevant results.

NEXT STEPS
Rebuild the project to bring it up to date:
1. Fix the first webscrape and feed it to the second
2. Connect it to React
3. Build the front end, without Bootstrap
New Features:
1. Produce the details page, that will also use location data to show a map
2. Give users the option to choose the region from the home page so they can select where they might like to
live, broken down by those organizational units
3. Provide a map on the front page that shows the locations of all of the buildings, and make them ”clickable”
4. Take the new data that I’ve found and use real data, rather than mock data and web scrape it.

SHANTA R. NATHWANI - @SHANTADOTCA - HTTP://SHANTA.CA 26https://www.torontohousing.ca/rent/affordable-rent/Pages/Buildings-with-affordable-rent-units.aspx

A BIG THANK YOU TO MY COLLEAGUES THAT HELPED
 James King
 For giving me the idea to give this
talk last month
 Aya Myhr
 For encouraging me when I
thought I was crazy
 Jenifer Champagne
 For helping fix some of the code
on her time off
 Adam Sutch
 For giving such sage advice and
also fixing stuff

THANK YOU!
QUESTIONS?

An Affordable REST - Coder Camp Hamilton 2019

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