These are some of the common questions regarding CircuitPython and CircuitPython microcontrollers.
We are no longer building or supporting the CircuitPython 2.x and 3.x library bundles. We highly encourage you to update CircuitPython to the latest version and use the current version of the libraries. However, if for some reason you cannot update, you can find the last available 2.x build here and the last available 3.x build here.
We are dropping ESP8266 support as of 4.x - For more information please read about it here!
We do not have asyncio support in CircuitPython at this time
The status LED can tell you what's going on with your CircuitPython board. Read more here for what the colors mean!
Memory allocation errors happen when you're trying to store too much on the board. The CircuitPython microcontroller boards have a limited amount of memory available. You can have about 250 lines of code on the M0 Express boards. If you try to
import too many libraries, a combination of large libraries, or run a program with too many lines of code, your code will fail to run and you will receive a
MemoryError in the serial console (REPL).
Try resetting your board. Each time you reset the board, it reallocates the memory. While this is unlikely to resolve your issue, it's a simple step and is worth trying.
Make sure you are using .mpy versions of libraries. All of the CircuitPython libraries are available in the bundle in a .mpy format which takes up less memory than .py format. Be sure that you're using the latest library bundle for your version of CircuitPython.
If that does not resolve your issue, try shortening your code. Shorten comments, remove extraneous or unneeded code, or any other clean up you can do to shorten your code. If you're using a lot of functions, you could try moving those into a separate library, creating a
.mpy of that library, and importing it into your code.
You can turn your entire file into a
import that into
code.py. This means you will be unable to edit your code live on the board, but it can save you space.
import statements affect memory?
It can because the memory gets fragmented differently depending on allocation order and the size of objects. Loading
.mpy files uses less memory so its recommended to do that for files you aren't editing.
You can make your own
.mpy versions of files with
You can download the CircuitPython 2.x version of
mpy-cross for your operating system from the CircuitPython Releases page under the latest 2.x version.
You can build
mpy-cross for CircuitPython 3.x by cloning the CircuitPython GitHub repo, and running
make in the
circuitpython/mpy-cross/ directory. Then run
./mpy-cross path/to/foo.py to create a
foo.mpy in the same directory as the original file.
Will give you the number of bytes available for use.
No. CircuitPython does not currently support interrupts. We do not have an estimated time for when they will be included.