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-Google-API-Database-and-Visualizing-Data-on-Google-Map

Using the Google Places API with a Database and Visualizing Data on Google Map

Files in order of execution

  1. geoload.py
  2. geodump.py
  3. where.html

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

Note: Windows has difficulty in displaying UTF-8 characters in the console so for each command window we open, we may need to type the following command before running this code:

chcp 65001

http://stackoverflow.com/questions/388490/unicode-characters-in-windows-command-line-how

we 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 a fixed number of requests per day. So if we have a lot of data we 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 retrieve 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.

we 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.

As of December 2016, the Google Geocoding APIs changed dramatically. They moved some functionality that we use from the Geocoding API into the Places API. Also all the Google Geo-related APIs require an API key. To complete this assignment without a Google account, without an API key, or from a country that blocks access to Google, we can use a subset of that data which is available at:

http://py4e-data.dr-chuck.net/json

To use this, simply leave the api_key set to False in geoload.py.

This URL only has a subset of the data but it has no rate limit so it is good for testing.

If we want to try this with the API key, follow the instructions at:

https://developers.google.com/maps/documentation/geocoding/intro

and put the API key in the code.

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

Mac: python3 geoload.py Win: geoload.py

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

Once we have some data loaded into geodata.sqlite, we 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: python3 geodump.py Win: geodump.py

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:

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 us.

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