![]() Feel free to take a look at some of our other tutorials on the Raspberry Pi for inspiration. You should then see the LED on the Pico flashing on and off every second.Īnd viola, you have fully setup P圜harm with the Raspberry Pi Pico, now you can code to your hearts content. Now try Run ‘Flash main.py’ You will see some red text in the console window showing that the code has downloaded to the Pico. If you don’t see Flash Main.py then right click main.py and click on More Run/Debug > Modify Run Configuration then when the window opens, make sure it says Flash Main.py in the Name field and click OK. Right click on main.py and click on Run ‘Flash main.py’ This will make the on board LED Flash on and off every second. Delete the code that P圜harm puts in and write this in: from machine import Pin Here’s something to get you started and make sure everything is setup correctly. Now you can start doing some programming in MicroPython. If you are using Mac or Linux then open a Terminal and type in “ls /dev/tty.usbmodem*” and look for an entry with a load of numbers after it.Įnter COM# or /dev/tty.usbmodem000000000000# in the Device Path and click OK.īack in the main screen you should see a yellow notice that some packages are required, click on the blue link at the end and P圜harm will install the required packages. Select the Device type as “PyBoard” and enter the Device Path, On Windows you can get this by going to Device Manager and under Ports (COM & LPT) you should see USB Serial Device (COM#). Then click the Tick box “Enable MicroPython support”. Under Languages & Frameworks, click on MicroPython. Once you are in the main screen we need to tell P圜harm that we are programming in MicroPython so go to File > Settings. Give it a decent name and leave all the other settings as default. Go back to P圜harm and click on Projects, then click on New Project. Create a new project in P圜harm and configure it for MicroPython Drag the UF2 file you downloaded in to the Pico’s mass storage and it should transfer over and then automatically reboot the Pico.Ĥ. If you’ve got the right cable then it should make a nice bing bong bing sound (on a PC anyway), it should also open folder. Hold down the BOOTSEL button and plug in a Micro USB cable. Download the MicroPython UF2 file for the Pico and install it on to the Pico ( ) Then search for MicroPython in the search bar and click on Install.ģ. Install Jupyter by selecting P圜harm > Preferences > Project Interpreter, then click the + button to add new packages. Once P圜harm opens you will be presented “Welcome to P圜harm” screen, we need to add the MicroPython plugin so click on Plugins. Once it’s downloaded, run the installer, all the default options are fine so click through them all. Visit the P圜harm website and download the community edition of P圜harm for your operating system. The ones we sell are ideal and are braided so they last longer ( ) Now you are ready to play with tensorflow from P圜harm.Micro USB cable that can do power and data (a lot of cheap cables are power only, you’ll know if when you plug it into your PC, it makes the nice bing bong bing noise).In P圜harm, select the previously created Project Interpreter (~/tensorflow_pycharm), and click + button and search for tensorflow, and then double click to install the package.In P圜harm, select the configured Project Interpreter at ~/tensorflow_pycharm Create a Python file In the Project tool window, select the project root (typically, it is the root node in the project tree), right-click it, and select File New.Issue the following command to install TensorFlow and all the packages that TensorFlow requires into the active Virtualenv environment: pip3 install -upgrade tensorflow.Activate the virtualenv environment by issuing one of the following commands: source ~/tensorflow_pycharm/bin/activate.Install tensorflow with one of the following approaches:.For the above case, let's assume the location is ~/tensorflow_pycharm, therefore, run command virtualenv -system-site-packages -p python3 ~/tensorflow_pycharm or python3 -m venv ~/tensorflow_pycharm(changed in version 3.5: the use of venv is now recommended for creating virtual environments). In command line, install tensorflow in the virtualenv location you created in previous step.In Pycharm, Preferences -> Project Interpreter -> Create VirtualEnv ->, and select "inherit global site-packages" option -> OK. Tightly integrated with the Cocoa and Cocoa Touch frameworks, Xcode is an incredibly productive environment for building amazing apps for Mac, iPhone.
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