Parsing GPS with Arduino – retro-post

I dug up one of my oldest blog posts from about 7 years ago.  In the post, I show how I had connected my Garmin eTrex GPS receiver to an Arduino board and used it to control a camera in a desktop application.

After pumping the data into the Arduino, I parsed the raw GPS data coming from the eTrex and streamed it out to a Python app on the desktop, via a serial port.  I was using the output to position a virtual camera in the OSSIMPlanet platform by formatting XML in Python and sending it to a listener built into the OSSIMPlanet app.  (OSSIMPlanet is a sort of pre-Google Earth, Google Earth on steroids product.)

I haven’t used it for years, but thought some of the methods from this old post may still apply if you have an Arduino + GPS or Arduino -> Python streaming requirement.   Enjoy the flashback – I know it’s inspired me to pick up a new Arduino to continue where I left off.


GPS Controls OSSIMPlanet - With OSSIMPlanet’s nifty camera control and listener functionality, as demonstrated in my last post, you’ve got so many neat opportunities. A couple nights ago I got a basic GPS NMEA parser working. Here’s a pic of the ultra-professional connection method I use to hook it to my arduino board 🙂 Oops, just realised that the picture … Continue reading GPS Controls OSSIMPlanet

Two wires to hook an eTrex data cable up to the Arduino
Two wires to hook an eTrex data cable up to the Arduino

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Kafka Consumer – Simple Python Script and Tips

[UPDATE: Check out the Kafka Web Console that allows you to manage topics and see traffic going through your topics – all in a browser!]


When you’re pushing data into a Kafka topic, it’s always helpful to monitor the traffic using a simple Kafka consumer script.  Here’s a simple script I’ve been using that subscribes to a given topic and outputs the results.  It depends on the kafka-python module and takes a single argument for the topic name.  Modify the script to point to the right server IP.

from kafka import KafkaClient, SimpleConsumer
from sys import argv
kafka = KafkaClient("")
consumer = SimpleConsumer(kafka, "my-group", argv[1])
for message in consumer:
 print("OFFSET: "+str(message[0])+"\t MSG: "+str(message[1][3]))

Max Buffer Size

There are two lines I wanted to focus on in particular.  The first is the “max_buffer_size” setting:


When subscribing to a topic with a high level of messages that have not been received before, the consumer/client can max out and fail.  Setting an infinite buffer size (zero) allows it to take everything that is available.

If you kill and restart the script it will continue where it last left off, at the last offset that was received.  This is pretty cool but in some environments it has some trouble, so I changed the default by adding another line.

Offset Out of Range Error

As I regularly kill the servers running Kafka and the producers feeding it (yes, just for fun), things sometimes go a bit crazy, not entirely sure why but I got the error:

kafka.common.OffsetOutOfRangeError: FetchResponse(topic='my_messages', partition=0, error=1, highwaterMark=-1, messages=)

To fix it I added the “seek” setting:,2)

If you set it to (0,0) it will restart scanning from the first message.  Setting it to (0,2) allows it to start from the most recent offset – so letting you tap back into the stream at the latest moment.

Removing this line forces it back to the context mentioned earlier, where it will pick up from the last message it previously received.  But if/when that gets broke, then you’ll want to have a line like this to save the day.

For more about Kafka on Hadoop – see Hortonworks excellent overview page from which the screenshot above is taken.

Kafka Topic Clearing after Producing Messages

[UPDATE: Check out the Kafka Web Console to more easily administer your Kafka topics]


This week I’ve been working with the Kafka messaging system in a project.

Basic C# Methods for Kafka Producer

To publish to Kafka I built a C# app that uses the Kafka4n libraries – it doesn’t get much simpler than this:

using Kafka.Client;

Connector connector = new Connector(serverAddress, serverPort);
connector.Produce(correlationId, hostName, timeOut, topicName, partitionId, message);

I was reading from various event and performance monitoring logs and pushing them through just fine. Continue reading Kafka Topic Clearing after Producing Messages

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