![]() Keeping student environments (where students might try out sample code before submitting it) and test environments in sync could also be a real issue. I also haven’t figured out how to properly inspect the test environment:Ĭo-opting a question preview as an error displaying terminal seems really ineffective? ( There has to be a better way, surely?)ĭeveloping sample answers / tests in my own environment means I need to make sure my environment is exactly the same as the one used by CodeRunner and then copying exact match expected answers is fraught with danger? so it looks like we could hack a way round package requirements by tweaking settings… but are things like time limits defined globally? Or at least, at a level above the question type level? (What if I have a question for which I know any legitimate answer will take a longish time to execute?) So I guess if I upload a Python package zip file there I might be able to install from it? It looks like there is an opportunity to provide files that are available at run time… I’ve not got far enough into yet to know if I can call on arbitrary packages that need installing on top of the base environment (I suspect I can’t?). I’m guessing this is used as an exact match string, so, erm, I really need it to be right? That cell really should be automatically populated by running the test case against a correct answer? Human hands should have nothing to do with it… The test definitions also look like they don’t let me interactively test them? It’s also not clear where I’m expected to pick up the Expected output from. (Also, I’m not sure about the semantics of ‘Validate on save’? Does that mean it runs the code against the defined tests?) I can save the code and have it validated automatically, but that’s not really interactive. (The jupytergraffiti Jupyter notebook extension has some interesting ideas about inline terminals and workflows around a similar sort of use case, in which the contents of a code cell are saved into a Python file that is then executed from a terminal.) (I guess that means we could also hack a way to running code against an arbitrary Jupyter kernel?)Ī slot is provided for a valid example answer, but it doesn’t look like there’s a way I can interactively edit and test that code (a simple terminal onto the underlying execution environment would be really handy. The R support looks like it’s not offered natively, but seems to be hacked together via a system call from the Python environment: a Python 3 environment with particular packages preinstalled): The question set up includes an execution environment selection, but I’m not sure how easy it is to define bespoke ones (e.g. Debugging code in any language has never been so quick and easy.Of interest to me on the courses I’m involved with are support for Python3, SQL (or at least, the dialect supported by SQLite), and R, which looks like it has hacky support via a command line call to R from a Python3 question type… How to download new fonts microsoft word. Explore the call stack, view and edit variables and interact with the debugger. Simply click the text margin to set a breakpoint and start debugging. With CodeRunner, you can set breakpoints and step through your code in more than a dozen languages instantly. Add a language is as easy as entering your command terminal.ĬodeRunner projects can also run multiple files without manual configuration.Ī good debugging workflow is key to producing quality code. CodeRunner can run code in 25 languages from the outset, and can be easily extended to support other languages. That’s why CodeRunner offers a powerful IDE code for most languages, including fuzzy search, selectable markers position tabulators and fragments of documentation.ĬodeRunner was built on the principle that you need to run your code instantly in any language. Any programmer knows the importance of good code completion.
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