#SPEEDIFY ON RASPBERRY PI CODE#

(Image credit: Tom's Hardware) Complete Code Listing import networkĪq = urequests.get(' API KEY HERE').Whenever you’re on the move in your RV, you have to rely on any Internet connection you can get. The NeoPixels will show the data via the five colors and the Python shell will show the exact air quality value. Press the button to trigger the Pico W to go online and download the latest air pollution data.

#SPEEDIFY ON RASPBERRY PI PASSWORD#

If not, then check your SSID and password are correct.Ģ4. The NeoPixels should flash green to confirm a Wi-Fi connection. In MicroPython, the main.py file is run each time the Pico boots.Ģ3. Save the code as main.py to the Raspberry Pi Pico W. Finally set the else condition, activated if there is no returned air quality data, to pass, enabling the loop to go back and wait for user input. Set the LEDs to flash red 10 times with a half second delay. Set the LEDs to flash orange 10 times with a half second delay. Set the LEDs to flash purple 10 times with a half second delay. Set the LEDs to flash blue 10 times with a half second delay. Set the LEDs to flash green 10 times with a half second delay. print('The Air Quality index is: ',str(air_quality_index))ġ6. Where 1 = Good, 2 = Fair, 3 = Moderate, 4 = Poor, 5 = Very Poor. Print the air quality index value to the Python shell as a sentence. These are documented in the OpenWeather API reference. This means we can read the exact data using a specific sequence of keys. The returned data is in JSON format, which is almost identical to Python’s dictionary data storage objects. From the returned data, slice out the Air Quality Index and save it to the object, air_quality_index. aq = urequests.get(' API KEY HERE').json()ġ4. This can be found via Google Maps, ours is set to New York City. Also change the lat (latitude) and lon (longitude) to match your location. Copy the API key and replace it in the URL below. Generate a new API key called AirPollution. Note that you will have to sign up for a free account, then click on your username and select My API Keys. Pressing the button triggers the code to download the latest air pollution data from OpenWeather using a free API key. Create an object, aq, and store the latest air quality data. Create an infinite loop, and check the status of the button. If unsuccessful, use a for loop to blink the NeoPixels red 10 times. Using a conditional statement, set the NeoPixels to blink green 10 times to signify that the connection has been successful.

Print the connection status to the Python shell. Add a short pause to allow the connection to be made and stable. Change SSID and PASSWORD to match your AP. Create an object, wlan, and use it to make a connection to your Wi-Fi access point. Note that the pixels are in GRB (Green, Red, Blue) order for our module. Create an object, pixels, which makes a connection between the code and the eight NeoPixels connected to GPIO16. button = Pin(14, Pin.IN, Pin.PULL_DOWN)ħ. Create an object, button, and create a connection to GPIO14, and using the internal resistor for that pin, pull the pin down (to GND). Machine contains “Pin” which is used to get and set the status of a GPIO pin, NeoPixel enables control of a NeoPixel RGB LED strip. Network enables the Pico W to connect to Wi-Fi, time is used to control the timings of the project code, urequests is used to fetch data from the API.

#SPEEDIFY ON RASPBERRY PI SERIES#

Import a series of modules essential to the project. Create a new file for the project code.ĥ. Save the file as neopixel.py to the root of the Raspberry Pi Pico W.Ĥ. Create a new file and paste the contents of this link. This ensures that the Python Shell is open and working correctly.ģ. Open Thonny and click on the Stop button to refresh the connection.

#SPEEDIFY ON RASPBERRY PI INSTALL#

The most important steps are to download and install the UF2 firmware image and to set up Thonny. Follow these steps to download the latest version of MicroPython for the Raspberry Pi Pico W.

Speedify on raspberry pi