Generate time series data using Python

This tutorial will show you how to generate mock time series data about the International Space Station (ISS) using Python.

Table of contents


CrateDB must be installed and running.

Make sure you’re running an up-to-date version of Python (we recommend 3.7 or higher).

Then, use pip to install the requests and CrateDB Python Client libraries:

sh$ pip install requests crate

The rest of this tutorial is designed for Python’s interactive mode so that you can experiment with the commands as you see fit. The standard Python interpreter works fine for this, but we recommend IPython for a more user-friendly experience.

You can install IPython with Pip:

sh$ pip install ipython

Once installed, you can start an interactive IPython session like this:

sh$ ipython

Get the current position of the ISS

Open Notify is a third-party service that provides an API to consume data about the current position, or ground point, of the ISS.

The endpoint for this API is

Start an interactive Python session (as above).

Next, import the requests library:

>>> import requests

Then, read the current position of the ISS with an HTTP GET request to the Open Notify API endpoint, like this:

>>> response = requests.get("")
>>> response.json()
{'message': 'success',
 'timestamp': 1582730500,
 'iss_position': {'latitude': '33.3581', 'longitude': '-57.3929'}}

As shown, the endpoint returns a JSON payload, which contains an iss_position object with latitude and longitude data.

You can encapsulate this operation with a function that returns longitude and latitude as a WKT string:

>>> def position():
...     response = requests.get("")
...     position = response.json()["iss_position"]
...     return f'POINT ({position["longitude"]} {position["latitude"]})'

When you run this function, it should return your point string:

>>> position()
'POINT (-30.9188 42.8036)'

Set up CrateDB

First, import the CrateDB Python Client client:

>>> from crate import client

Then, Connect to CrateDB:

>>> connection = client.connect("localhost:4200")


You can omit the function argument if CrateDB is running on localhost:4200. We have included it here for the sake of clarity. Modify the argument if you wish to connect to a CrateDB node on a different host or port number.

Get a cursor:

>>>  cursor = connection.cursor()

Finally, create a table suitable for writing ISS position coordinates.

>>> cursor.execute(
...     """CREATE TABLE iss (
...            position GEO_POINT)"""
... )

In the The CrateDB Admin UI, you should see the new table when you navigate to the Tables screen using the left-hand navigation menu:


Record the ISS position

With the table in place, you can start recording the position of the ISS.

The following command calls your position function and will insert the result into the iss table:

>>> cursor.execute("INSERT INTO iss (position) VALUES (?)", [position()])

Press the up arrow on your keyboard and hit Enter to run the same command a few more times.

When you’re done, you can select that data back out of CrateDB.

>>> cursor.execute('SELECT * FROM iss ORDER BY timestamp DESC')

Then, fetch all the result rows at once:

>>> cursor.fetchall()
[[1582295967721, [-8.0689, 25.8967]],
 [1582295966383, [-8.1371, 25.967]],
 [1582295926523, [-9.9662, 27.8032]]]

Here you have recorded three sets of ISS position coordinates.

Automate the process

Now you have key components, you can automate the data collection.

Create a new file called, like this:

import time

import requests
from crate import client

def position():
    response = requests.get("")
    position = response.json()["iss_position"]
    return f'POINT ({position["longitude"]} {position["latitude"]})'

def insert():
    # New connection each time
        connection = client.connect("localhost:4200")
        print("CONNECT OK")
    except Exception as err:
        print("CONNECT ERROR: %s" % err)
    cursor = connection.cursor()
            "INSERT INTO iss (position) VALUES (?)", [position()],
        print("INSERT OK")
    except Exception as err:
        print("INSERT ERROR: %s" % err)

# Loop indefinitely
while True:
    print("Sleeping for 10 seconds...")

Here, the script sleeps for 10 seconds after each sample. Accordingly, the time series data will have a resolution of 10 seconds. You may want to configure your script differently.

Run the script from the command line, like so:

sh$ python
Sleeping for 10 seconds...
Sleeping for 10 seconds...
Sleeping for 10 seconds...

As the script runs, you should see the table filling up in the CrateDB Admin UI:


Lots of freshly generated time series data, ready for use.

And, for bonus points, if you select the arrow next to the location data, it will open up a map view showing the current position of the ISS:



The ISS passes over large bodies of water. If the map looks empty, try zooming out.


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