We're considering using Python (IronPython, but I don't think that's relevant) to provide a sort of 'macro' support for another application, which controls a piece of equipment.
We'd like to write fairly simple functions in Python, which take a few arguments - these would be things like times and temperatures and positions. Different functions would take different arguments, and the main application would contain user interface (something like a property grid) which allows the users to provide values for the Python function arguments.
So, for example function1 might take a time and a temperature, and function2 might take a position and a couple of times.
We'd like to be able to dynamically build the user interface from the Python code. Things which are easy to do are to find a list of functions in a module, and (using inspect.getargspec) to get a list of arguments to each function.
However, just a list of argument names is not really enough - ideally we'd like to be able to include some more information about each argument - for instance, it's 'type' (high-level type - time, temperature, etc, not language-level type), and perhaps a 'friendly name' or description.
So, the question is, what are good 'pythonic' ways of adding this sort of information to a function.
The two possibilities I have thought of are:
Use a strict naming convention for arguments, and then infer stuff about them from their names (fetched using getargspec)
Invent our own docstring meta-language (could be little more than CSV) and use the docstring for our metadata.
Because Python seems pretty popular for building scripting into large apps, I imagine this is a solved problem with some common conventions, but I haven't been able to find them.
metadata, is a Python module for accessing and managing an item's metadata. You can explore information describing your maps and data and automate your workflows, particularly for managing standards-compliant geospatial metadata.
A decorator is a design pattern in Python that allows a user to add new functionality to an existing object without modifying its structure. Decorators are usually called before the definition of a function you want to decorate.
Use the keyword def to declare the function and follow this up with the function name. Add parameters to the function: they should be within the parentheses of the function. End your line with a colon. Add statements that the functions should execute.
Decorators are a good way to add metadata to functions. Add one that takes a list of types to append to a .params property or something:
def takes(*args):
def _takes(fcn):
fcn.params = args
return fcn
return _takes
@takes("time", "temp", "time")
def do_stuff(start_time, average_temp, stop_time):
pass
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