Python Web services, JSON, and ISS Oh My!


In this post I will talk about how to handle JSON data from an external API utilizing python. Making calls to web services is made simple with python, with just a few lines of code you can track the International Space Station’s (ISS) position and time, realtime with a sleek graphical user interface. The following is a link to the project files download,

The Turtle module is an object oriented graphics tool that draws to a canvas or screen. Turtle’s methods derived include forward(), backwards(), left() and right() like telling a turtle in what direction to draw. Turtle will draw over a NASA curated 2D map of Earth, so you should place the ‘map.jpg’ file in your project directory.

So one of the first things we need to do is instantiate a turtle screen with the following command.

# turtle provides a simple graphical interface to display data
# we need a screen to plot our space station position
import turtle
screen= turtle.Screen()

The image size is 720w by 360h so our turtle screen size should fit the image size.

# the image size is 720w x 360h
# set coordinates to map longitude and latitude
# set background picture to NASA world map, centered at 0



To represent the ISS on the 2D map let’s choose an image, it doesn’t have to be the following icon but it’s a nice icon so Houston we have liftoff!

# adds turtle object with name iss to list of objects
iss= turtle.Turtle()


Our location object will tell turtle to write the ISS png file to the screen at a specific position given the latitude and longitude of the ISS. Instantiate a Turtle() to create an object with the following code.


# location object for turtle to plot
location= turtle.Turtle()

# used later to write text

Now, before we can tell our turtle to draw the ISS overhead-time we need the actual latitude and longitude coordinates of the passing ISS. A quick google search gives us the coordinates to store in a dictionary.

# Cape Canaveral ---> 28.392218, -80.607713
# Central Park, NYC ---> 40.782865, -73.965355
# create python dictionary to iterate and plot time of overhead location
coords['nasa_fl']=(28.523397, -80.681874)
coords['centralp']=(40.782865, -73.965355)

To call the api we first need the url, ‘,’ this will tell the api to give us the data we need to extrapolate the ISS data.

import urllib.request
import json

Then to make the call to the url use urllib.request to access the url, querying for each given location. The data is then stored as a result,  loaded in json format. Json stands for JavaScript Object Notation and is used to conveniently organize data.

Screenshot (76)

The lines above are the contents of the json data, data is accessed similar to a python dictionary utilizing keys and indices.

import time

# setup loop to iterate and plot when the iss will be at the plotted location.
for k,v in coords.items():
 pass_url= ''
 pass_url= pass_url+'?lat='+str(v[0])+'&lon='+str(v[1])
 pass_response= urllib.request.urlopen(pass_url)
 pass_result= json.loads(
# write turtle at new location coords
 location.write(time.ctime(over), font=style)

The above code block makes a call to the api, loads the json data, parses the overhead pass time (when the iss will be over the specified position) and then plots the time at the given location.

Screenshot (77)

# init current loc off iss coord
# make call to api
loc_url= ''
# the coords are pcked into jso, iss_position key
location= loc_result['iss_position']
lat= float(location['latitude'])
lon= float(location['longitude'])
<pre># set up while loop to plot moving iss
# iss loc updates approx 3 sec

# update call to webservice to get new coords
 loc_url= ''
 location= loc_result['iss_position']
 lat= float(location['latitude'])
 lon= float(location['longitude'])
# write turtle at new location coords


The above code block makes a call to the api, loads the json data, parses the overhead position at the current geographic coordinates and plots the iss icon. The while loop is infinite to constantly track the iss.

Screenshot (75)

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