Reading data from an atmospheric sensor

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Overview

  • In this lesson we are going to write code that will allow us to download data from an atmospheric sensor.
  • The sensor will give us data on temperature, atmospheric pressure, battery voltage and signal strength.
  • We will use the python language to get this data.
  • Once we have data we can do other amazing things such as save the data and even graph the data.
  • Environmental data is very important because it allows us to monitor the environment we live in more closely.

Learning Objectives

  • Learn how to use the requests library in python to get data from a URL
  • Learn how to interpret data presented in the JSON format
  • Learn how to process data in python so that it can be saved in variables

Requesting new data from a sensor URL in Python

  • Sensors are now commonly connected to the internet.
  • This has given rise to the term – The Internet of Things.
  • If a sensor is connected to the internet then it will often have a URL (Universal Resource Locator) to allow us to interact with the sensor.
  • One common interaction is to be able to see or download data collected by the sensor.
  • To get data from a sensor we need to import the requests library in python.
  • In this lesson we will download some data from an atmospheric sensor.
  • The sensor data includes temperature, air pressure, sensor battery voltage and signal strength.
  • In this example we write a python3 program to download sensor data using the requests library.
  • The data will be presented in the python Shell.

Create a new file in python named atm_sensor_get.py

  • From the Raspberry Pi main menu drop down select Programming > Python3 (IDLE).
  • This will open up the Python Shell.
  • From the File drop down menu select New File.
  • This will open up a new file Editor Window.
  • We are going to name the file atm_sensor_get.py

Adding Comments within files

  • We can add notes within our program called Comments.
  • Comments always start with a # (hash symbol) at the start of the line.
  • Computers ignore comments because comments are only read by humans.
  • To signal that the text has been commented out, the text colour will change to red.
  • In this example the comment is the file name.

  • To save the new file, select File > Save As

  • Navigate to your working directory and then save the file as atm_sensor_get.py
  • In Linux we never use names that include spaces.
  • Replace spaces with either the _ (underline) symbol or the – (hyphen) symbol.

Request data from sensor using python

  • The key items in the code are described:
    • import requests – this statement imports a python library so that the python program can get data from the internet.
    • r = requests.get(URL) – this statement gets the data from a specified URL and stores the result in the variable object named r. URL is short for Uniform Resource Location, also known as a web address.
    • print(r) – this statement prints a code that determines if the request was successful or not.
  • Save and the Run the program.

  • The response in the Python Shell should be [200].
  • A value of [200] means that the request was successful.
  • Other numbers or errors will indicate that there is a problem either with the Python code or with communication with the sensor.

View sensor data in JSON format

  • We can now add some more code so that we can look at the actual data.
  • Add the statement print(r.json()) and run the code.
  • The method json() means that the data will be presented in JSON format.
  • JSON stands for JavaScript Object Notation.
  • It is an open standard to help format data for data exchange between computers and it uses human-readable text.
  • The data is stored in attribute-value pairs' similar to the format of a dictionary.

  • You can see the data output in the python Shell Window.

  • Unfortunately, presenting the data this way is not very readable.
  • In the next section of this lesson we will learn how to view and interpret data stored in the JSON format.

Interpreting data in json format

  • As previously mentioned, JSON is an open standard that allows data to be exchanged more easily between computers.
  • JSON data is stored as text, and this makes it human-readable however you need a special application to see this data more clearly.
  • In this lesson we will use the web browser Firefox to visualise the data so we can see the arrangement of attribute-value pairs.

Copying, editing and saving JSON formatted data

  • One way to see the data more easily is to view it in the web browser Firefox.
  • To do this we need to Copy the JSON data output from the Raspberry Pi and Paste it in a file on your PC.
  • We also need to replace all ‘ characters with “ otherwise Firefox wont show the JSON data correctly.
  • Copy the data above from the Python Shell.
  • To copy, right-mouse button click and select Copy.
  • Paste it into a text editor on your PC.
  • To paste, right-mouse button click and select Paste.
  • Replace all ‘ characters with “ using the in-build Find/Replace function in your Text Editor.
  • Then Save the data as a file with the file extension .json on your PC.
  • In this example the file name is atm_data.json

Download and install Firefox web browser

Visualising JSON formatted data in Firefox

  • In the Firefox Browser Open the new file you created named atm_data.json
  • You can do this by selecting File > Open File... from the top Drop Down Menu.
  • You should see something like the following displayed. See image below.
  • Some key points:
    • Sensor data is divided into four sections labelled [0, 1, 2, 3]
    • Each section is for different data set:
      • Temperature
      • Air Pressure
      • Battery Voltage
      • Signal Strength (RSSI)
  • The attribute-value pair we are interested in (for each data set) is the attribute named “val_calibrated”.
  • For each data set [0, 1, 2, 3] the “val-calibrated” attribute will match with either [temperature, pressure, battery voltage, signal strength]
  • For example, for data set [0], the “val_calibrated” value is 9.04 – which is the Temperature.

Learning how to extract Temperature data from JSON formatted data

  • To extract the relevant data from our JSON data we enter the following code print(r.json[0][“val_calibrated”])
    • [0] – represents the first data set (containing Temperature data)
    • [“val_calibrated”] – is the attribute in the attribute-value pair that pairs with the temperature value
    • print() – will print out the temperature data to the Python Shell

  • The result can be seen on the last line of the Python Shell.
  • In this case the temperature is 5.61 (degrees Centigrade).

Assigning temperature data into a variable

  • Now that we know how to find and extract temperature data we can also pass on this value to a variable.
  • Putting the temperature data in a variable allows us to save or manipulate the data more easily, just like in algebra.
  • Add the following code:
    • temp = r.json()[0][“val_calibrated”] – assign temperature data to variable named temp
    • print(temp) – display the value held in temp in the Python Shell
  • Save and then Run this program.

  • The output of the program is shown below in the Python Shell window.
  • The very last line of output (5.61) shows the output of the print(temp) statement.

  • The output of the program has a lot of information we no longer need.
  • To reduce the clutter from the output we can comment out some of the statements in our program using the # (hash) symbol.
  • Note that when we comment out statement the text will change to a red colour.
  • If we comment out statements the computer will no longer execute (run) them.
  • Follow the example below and comment out three of the print() statements.
  • Save and Run the program.

  • You can see that the output of the program has been simplified.
  • We can always uncomment these print() statements in the future.

Collecting more data from the atmospheric sensor

  • The atmospheric sensor collects other data in addition to temperature.
  • The key data we are interested in is:
    • temperature – measured in degrees Celsius
    • air pressure – measured in kilopascals. 101kPa normal. 105kPa high pressure (fine weather).
    • battery voltage – charge level of battery powering the sensor. Max voltage 4.20V. Min voltage 3.60V
    • signal strength (RSSI) – a record of how powerful this signal is at the receiving station (LoRa Gateway)
  • In this next example, we will capture data on the air pressure and the battery voltage.

Extracting Air Pressure from JSON formatted data

  • If we refer to the data presented in the Firefox web browser, we can see the data is divided into sections.
  • Temperature data was in a section prefaced by [0].
  • Air Pressure data is a section prefaced by [1].
  • Using this information, we can extract the Air Pressure data using the following code.
    • print(r.json()[1][“val_calibrated”])
  • Add this additional statement, then Save and Run the program.

  • This is the output in the python Shell Window.
  • Both Temperature (18.78) and Air Pressure (101.05) data are now displayed.

  • As for the temperature data, we can store the Air Pressure data in a variable.
  • For Air Pressure we have created a new variable named pres
  • Enter the following code, and also comment out the preceding print() statement.
    • pres = r.json()[1][“val_calibrated”]
    • print(pres)

Extracting Battery Voltage from JSON formatted data

  • In this last example we will also request Battery Voltage.
  • Add the following code to extract the Battery Voltage data:
    • print(r.json()[2][“val_calibrated”]
  • Save and Run the program.

  • The output in the python Shell Window will now show all three data values including Battery Voltage.
  • If the battery voltage drops below 3.70 Volts, then the battery will need to be recharged.

  • As a final step we will store the Battery Voltage data in a variable named voltage.
  • Enter the following code and remember to comment out the preceding print() statement.
    • voltage = r.json()[2][“val_calibrated”]
    • print(voltage)
  • Save and Run the program.

  • Congratulations on completing this lesson.
  • In the next lesson we will learn to save all this data in a file and also add a date/time stamp so that we have a record of when the data was collected.
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