Tag: web service

Easy as PI Weather Station – putting it all together

Sorry it has taken me so long to continue with this series. There were little things that got in the way such as C*****19, and going through redundancy but lets put those little things aside and recap. Last time we created a web service using node Express which will be used to capture environmental data from our Raspberry PI Sense Hat.

In this article we are going to hook things up by sending the data collected from the Raspberry PI, to our web service. We will also be updating our endpoints to handle the data correctly. Let’s get started!

First of all open the collector.py file.

We are going to POST the data to our web service endpoint. Find the line where we are checking if we have reached the interval and replace it with the code shown here.

if minute_count == MEASUREMENT_INTERVAL:                                                                                 
    # Create the payload object                                                                                          
    payload = {                                                                                                              
    'date':dt.strftime("%Y/%m/%d %H:%M:%S"),                                                                             
    'temperature':round(temp_c,2),                                                                                       
    'pressure':round(sense.get_pressure(),2),                                                                            
    'humidity':round(sense.get_humidity(),2),                                                                        
    }                                                                                                                     
    data = urllib.urlencode(payload)                                                                                     
    request = urllib2.Request(END_POINT,data)                                                                            
    response = urllib2.urlopen(request).read()                                                                           
    print(payload)                                                                                           
    minute_count = 0;

We are using a couple of Python libraries called urllib and urllib2 to do the heavy lifting of encoding our payload and sending it across to our Node.js server.

All that is left is to add the new endpoint to our Node.js server to process the request and update the list to return an actual list of weather data. Exciting eh! Open up another terminal session and navigate to the server directory. Using your editor of choice open up the index.js file.

Update the endpoints as shown below.

// Provide service meta data
app.get('/api/environment/meta', (req,res) => {
    res.header("Access-Control-Allow-Origin", "*");
    res.send({
        averageTemp:averageTemp,
        count:data.length,
        lastEntry:lastEntry
    } );
} );

// List all entries
app.get('/api/environment/entries', (req,res) => {
    res.header("Access-Control-Allow-Origin", "*");
    res.send(data);
} );

app.post('/api/environment', (req,res) => {
    if (!isValid(req.body)) {
        res.status(400).send('Invalid request, required fields missing.');
        return;
    }
    const count = data.length + 1;
    const entry = {
        id:count,
        date:req.body.date,
        temperature:req.body.temperature,
        pressure:req.body.pressure,
        humidity:req.body.humidity
    }
    lastEntry = entry;
    total += parseFloat(req.body.temperature);
    averageTemp = total / count;
    data.push(entry);
    res.json(entry);
} );

You may recall last time we added a dummy /api/environment/entries endpoint which simply returned an empty array.

Let’s flesh this out. The endpoint is defined as a POST method which means data is sent as part of the body of the request. We validate that we do indeed have a body then update the count metric. We then build a JSON object by pulling out the parts of the request we are interested in. Finally we update the lastEntry variable, work out the average temperature to date before updating our list.

With these changes in place we can run our collector and Node.js server to see the end to end implementation working in all its glory. I would recommend opening two separate terminals and laying them out side-by-side.

In the terminal for the Python collector start the data harvest using the command python collector.py. On your PI you should see regular temperature updates on the matrix display.

Raspberry PI Weather Station
Weather station running in the Raspberry PI

In the second terminal ensure you are in the collector/server directory and start the Node.js server using the command node index.js. If all is well you will see the message Listening on port 3000.

Terminal sessions running the collector and Node.js server
Terminals sessions showing the collector and Node.js server running on the PI

After a while you will see entries printed in the server console indicating that the weather data has collected from the PI and sent it to our server.

Now comes the exciting bit. We can try out our new endpoints. Open a new browser tab and check the new endpoints are functioning correctly.

http://raspberrypi:3000/api/environment/entries

http://raspberrypi:3000/api/environment/meta

The new endpoints shown using the RESTED Chrome extension

All good? Great! What would be good is if we could somehow visualize our data in an attractive way. Well that’s the subject for the next and final instalment where we will be diving into the wonderful world of D3.

Easy as PI Weather Station – create a Node.js web service in 5 minutes

Introduction

In the last article we created a Python script to collect environmental data from a Sense Hat equipped Raspberry PI.

This article will add to that by creating a web service that will display all logged entries. In the next blog post we will add the ability to upload data from PI to the web service.

This web service will be running on the Raspberry PI but of course it could run anywhere as long as it supplies an endpoint to enable consumers to use it.

Building a RESTful API – do’s and do not’s

The web service will use RESTful principles. REST is a set of best practises to use when designing an API. In a nutshell:

  • DO return JSON
  • DO set the Content-Type header correctly i.e. application/json. Note, when using the PATCH method the content type must be application/merge-patch+json
  • DON’T use verbs e.g. use /songs instead of listSongs/
  • DO use plurals e.g. /api/songs/2019
  • DO return error details in the response body
  • DO make use of status codes when returning errors
    • 400-bad request, 403-forbidden, 404-not found, 401-unauthorised, 500 server error
  • For CRUD operation return the following codes
MethodDescriptionURLResponse code
GETretrieve dataapi/customers200
POSTcreate dataapi/customers
{“name”:”jon”, “email”:”a@a.com”}		201
PUTupdate dataapi/customers/1
{“name”:”dave”,”email”:”b@a.com”}		200
DELETEdelete dataapi/customers/1204
PATCHupdate partial dataapi/customers/1
{“op”:”replace”,”path”:”/email”,”value”:”a@a.com”}]		204
REST method, actions and expected response codes.

Defining the endpoints

Our API will have three endpoints. This article is focussed on the first one, to list entries. The other two will be addressed in a later post.

/api/environment/entries – to list all entries

The resulting JSON will be something like this:

[
    {
        "id":1,
        "date":"2020/06/06 15:34:01",
        "temperature":"24.48",
        "pressure":"998.32",
        "humidity":"44.9"
    }
]

/api/environment/ – to create a new entry

/api/environment/meta – to retrieve metadata such as number of entries, average temperature and last entry that was uploaded

Creating the web service using Express

Let’s get started! Connect your PI to the network either wirelessly or using a cable. I use an Ethernet cable directly plugged it into my laptop.

  1. Power up your PI!
  2. SSH into your PI. I used PuTTY
  3. Navigate to the collector directory we created the last blog post.
  4. mkdir server
  5. cd server

We are going to use Node.js to create our server. Node.js is based on the Chrome V8 Javascript engine but has added modules to deal with IO, HTTP and many more. It is basically a Javascript engine wrapped in a C++ exe. It has a single-threaded handler which hands off requests in an asynchronous manner so it is very suitable to quick high-throughput requests.

Out of the box it is very easy to create a simple REST API. We will be using another node module called express which makes managing routing much easier.

So first things first if you haven’t already done so install node and npm on your PI. Here is a noice instructable showing how to do it.
https://www.instructables.com/id/Install-Nodejs-and-Npm-on-Raspberry-Pi/

When you have successfully installed node and npm return to the server directory we created earlier. Now we can install express which is a lightweight framework for creating REST APIs.
npm install express --save

Create a file called index.js using your editor of choice. I used nano.
nano index.js

Paste the following:

 // import the express module and create the express app
const express = require('express');
const app = express();

// install middleware that can encode the payload
app.use(express.urlencoded({extended:false})); 

// create an array to hold the environmental data
const data = []; 

// End points for the web service
//list entries
app.get('/api/environment/entries', (req,res) => {
    res.send(data); //Just send at empty array for now
} );

// create a web server, running on your port of choice or 3000
const port = process.env.PORT || 3000;
app.listen(port,() => {
    console.log(Listening on port ${port});
} );

This server will respond to HTTP GET requests at the /api/environment/entries endpoint listening on port 3000.

Start the node server
node index.js

Open your browser and go to
http://raspberrypi:3000/api/environment/entries

The result will not be very exciting as you will just see an empty array returned in the browser. However, give yourself a pat on the back. You have created your first fledgling web service!