I'm prepping for class tomorrow, as a Python instructor for employed adults eligible for California State funded professional development electives, not for college credit but career-relevant nonetheless.
My approach is to use collections.namedtuple to show the tuple (a sequence type, like a list) having its "slots" accessed via dot notation, not just through indexing, then swapping in an equivalent class that does the same thing (down to having __getitem__ in some examples). Seeing how a class duplicates features we've already introduced, makes a nice bridge to "defining your own types" (vs using the __builtins__ or standard library types). Once with have dicts and lists introduced, near the start, we're ready to talk about JSON already, which brings in early previews of web services, APIs, inter-operability with JavaScript (ES) and of course MongoDB. I just use json module to store .json files, as soon as we get to the function open( ), i.e. here's a first example of Talking about Python in the context of getting between a browser and a database or persistent storage, gets the juices flowing about "an ecosystem". These two source code files show off the web API angle, using an open API to get IMDB information (movie database): https://github.com/4dsolutions/Python5/blob/master/get_movie.py https://github.com/4dsolutions/Python5/blob/master/get_movie_v2.py Here's another example, going from namedtuple Element (for Periodic Table atoms), to class-based Element: namedtuple: https://github.com/4dsolutions/Python5/blob/master/elements_02.py class based: https://github.com/4dsolutions/Python5/blob/master/elements_04.py Actually running these would require the *.json files, both included in the repo: elements_v1.json elements_v2.json Next stop: SQLite and try / except syntax. Kirby PS: I'm pushing Pyret pretty seriously even though it's very much the moving target. Follow the action on Twitter @4DsolutionsPDX python-cuba working group also going well. Py2017 shaping up.
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