Index of /code/geodata

Icon  Name                    Last modified      Size  Description
[PARENTDIR] Parent Directory - [TXT] geodump.py 2015-12-04 14:05 1.0K [TXT] geoload.py 2016-01-10 16:23 1.7K [   ] where.data 2015-12-04 14:05 6.4K [TXT] where.html 2016-01-10 16:23 1.8K [   ] where.js 2015-12-04 14:05 19K
Using the Google Geocoding API with a Database and 
Visualizing data on Google Map

In this project, we are using the Google geocoding API
to clean up some user-entered geographic locations of 
university names and then placing the data on a Google
Map.

You should install the SQLite browser to view and modify 
the databases from:

http://sqlitebrowser.org/

The first problem to solve is that the Google geocoding
API is rate limited to 2500 requests per day.  So if you have
a lot of data you might need to stop and restart the lookup
process several times.  So we break the problem into two
phases.  

In the first phase we take our input data in the file
(where.data) and read it one line at a time, and retreive the
geocoded response and store it in a database (geodata.sqlite).
Before we use the geocoding API, we simply check to see if
we already have the data for that particular line of input.

You can re-start the process at any time by removing the file
geodata.sqlite

Run the geoload.py program.   This program will read the input
lines in where.data and for each line check to see if it is already
in the database and if we don't have the data for the location,
call the geocoding API to retrieve the data and store it in 
the database.

Here is a sample run after there is already some data in the 
database:

Mac: python geoload.py
Win: geoload.py

Found in database  Northeastern University

Found in database  University of Hong Kong, Illinois Institute of Technology, Bradley University

Found in database  Technion

Found in database  Viswakarma Institute, Pune, India

Found in database  UMD

Found in database  Tufts University

Resolving Monash University
Retrieving http://maps.googleapis.com/maps/api/geocode/json?sensor=false&address=Monash+University
Retrieved 2063 characters {    "results" : [  
{u'status': u'OK', u'results': ... }

Resolving Kokshetau Institute of Economics and Management
Retrieving http://maps.googleapis.com/maps/api/geocode/json?sensor=false&address=Kokshetau+Institute+of+Economics+and+Management
Retrieved 1749 characters {    "results" : [  
{u'status': u'OK', u'results': ... }

The first five locations are already in the database and so they 
are skipped.  The program scans to the point where it finds un-retrieved
locations and starts retrieving them.

The geoload.py can be stopped at any time, and there is a counter 
that you can use to limit the number of calls to the geocoding
API for each run.

Once you have some data loaded into geodata.sqlite, you can 
visualize the data using the (geodump.py) program.  This
program reads the database and writes tile file (where.js)
with the location, latitude, and longitude in the form of
executable JavaScript code.   

A run of the geodump.py program is as follows:

Mac: python geodump.py
Win: geodump.py

Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA 42.3396998 -71.08975
Bradley University, 1501 West Bradley Avenue, Peoria, IL 61625, USA 40.6963857 -89.6160811
...
Technion, Viazman 87, Kesalsaba, 32000, Israel 32.7775 35.0216667
Monash University Clayton Campus, Wellington Road, Clayton VIC 3800, Australia -37.9152113 145.134682
Kokshetau, Kazakhstan 53.2833333 69.3833333
...
12 records written to where.js
Open where.html to view the data in a browser

The file (where.html) consists of HTML and JavaScript to visualize 
a Google Map.  It reads the most recent data in where.js to get 
the data to be visualized.  Here is the format of the where.js file:

myData = [
[42.3396998,-71.08975, 'Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA'],
[40.6963857,-89.6160811, 'Bradley University, 1501 West Bradley Avenue, Peoria, IL 61625, USA'],
[32.7775,35.0216667, 'Technion, Viazman 87, Kesalsaba, 32000, Israel'],
   ...
];

This is a JavaScript list of lists.  The syntax for JavaScript 
list constants is very similar to Python so the syntax should 
be familiar to you.

Simply open where.html in a browser to see the locations.  You 
can hover over each map pin to find the location that the 
gecoding API returned for the user-entered input.  If you 
cannot see any data when you open the where.html file, you might 
want to check the JavaScript or developer console for your browser.