Collection of open source (BSD Licence) code examples useful for connecting to the IoT cloud service Byteport.

Read all about it here

https://www.byteport.se/home and

Sign up for an account to get started.

It is free for small volume users, such as hobbyists, academics and start-ups.

If you would like to build a web-application built upon this API using only HTML and Javascript, you should check out one of our other open git-repositorys: https://github.com/iGW/byteport-application-skeletons for some fully working project skeletons that should get you started in no time.

You can find the API v1 specification here: https://github.com/iGW/byteport-api/blob/master/APIv1.adoc

Byteport accepts:

• Numbers
• Text
• Objects

When you store Objects, you may specify what kind of object you are storing by assigning a media type (formerly termed MIME-type) that will be supplied when fetching the data again.

While storing data usign HTTP GET calls might seem a bit backwards. But it is sometimes a nice feature for quick and dirty scenarios. The only caveat is the data size limitation of 2 Kb.

To store data blocks larger than 2K you must use other methods available. For HTTP you can use the POST call instead. The reference implementations below all contain methods for storing objects. Binary data needs to be base64 encoded before storing. And before doing that, you might as well apply some compression to save some bandwidth and Byteport storage space.

Independent of client technology, do the following steps to ensure you can store data using the HTTP API

1. Create a new namespace in Byteport: http://www.byteport.se/manager/namespaces/
2. Open up the namespace and click the Security tab.
3. In the box API settings change HTTP Write method to allow storage using the HTTP GET and POST methods.
4. Use API Write key when trying out the client examples below. You can set a new one, or use the generated. Leave blank to generate a new.

The reference implementation is made in Python. But the HTTP API can of course be accessed using any language. Python is clear and simple enough to be used as a

Pytz is so good it should be in the standard library. It is not yet, so we have to pip it. Asuming you have PIP on your system:

 $ git clone https://github.com/iGW/byteport-api/
 $ cd byteport-api/python
 $ pip install -r requirements.txt
 $ python ./setup.py install

A common use-case is to send some data at regular intervals

from byteport.clients import ByteportHttpClient
import time

# Will send a single empty heart beat packet.
client = ByteportHttpClient('myownspace', 'f00b4s3cretk3y', 'barDev1')

while True:
    # Store a string and the current UNIX Epoch time on a regular interval
    client.store({'info': 'All systems nominal', 'current_time': time.time()})
    time.sleep(60)

A file is read and the content of the file is stored as value to the field called temperature.

from byteport.clients import ByteportHttpClient

client = ByteportHttpClient('myownspace', 'f00b4s3cretk3y', 'barDev1')

client.store_file('temperature', './current_temperature')

This example make use of a convenience function that will continously poll a directory (default every 5 seconds, can be changed py parameter as below) for any change of the files. If a file is added, its content will be added to the next call. If a file is changed the new file content will be used. This makes integration with Byteport very simple - as whatever programming language you use, you can just dump data to a file in a directory and use the directory as the point of integration.

from byteport.clients import ByteportHttpClient

client = ByteportHttpClient('myownspace', 'f00b4s3cretk3y', 'barDev1')

# NOTE: This will block the current thread!
client.poll_directory_and_store_upon_content_change('/home/iot_user/measured_values/', 'barDev1', poll_interval=10)

In this case a single file is read, compressed, encoded and sent to byteport with a few lines of code.

from byteport.clients import ByteportHttpClient

client = ByteportHttpClient('myownspace', 'f00b4s3cretk3y', 'barDev1')

path_to_interesting_file = '/tmp/status_data'

client.base64_encode_and_store_store_file('staus_files', path_to_interesting_file, compression='bzip2')

For event more examples, have a look at the integration test suite.