%doctest_mode? output from IPython probably needs to be wrapped in a fenced
code block?:
```python
>>> help(help)
>>> help(dir)
>>> dir(dir)
>>> help(__import__('IPython.display.display'))
```
On Wed, Feb 3, 2021, 15:41 Wes Turner <wes.tur...@gmail.com> wrote:
> You can export notebook inputs to (hopefully mostly hyperkitty-compatible)
> Markdown with jupytext:
>
> ```bash
> conda install -c jupytext jupyterlab
> jupyter-lab
> # Pair with Markdown, light, percent, hydrogen
> # Click refresh in the file pane to see the jupytext-linked copy
> ```
>
> Pandoc can convert the html version of a notebook (with output; i.e. from
> nbconvert) to e.g. 'gfm' GitHub-flavored Markdown
>
> On Wed, Feb 3, 2021, 12:34 kirby urner <kirby.ur...@gmail.com> wrote:
>
>>
>>
>> On Tue, Feb 2, 2021 at 11:28 AM André Roberge <andre.robe...@gmail.com>
>> wrote:
>>
>>>
>>>
>>> On Tue, Feb 2, 2021 at 2:37 PM kirby urner <kirby.ur...@gmail.com>
>>> wrote:
>>>
>>>> On Tue, Feb 2, 2021 at 5:48 AM André Roberge <andre.robe...@gmail.com>
>>>> wrote:
>>>>
>>>>> Hello everyone,
>>>>>
>>>>> For about 20 months now, I have been working on a Python package
>>>>> intended to help beginners figure out what went wrong when their program
>>>>> generates a traceback. This package is called Friendly-traceback; you can
>>>>> find the fairly extensive documentation at
>>>>> https://aroberge.github.io/friendly-traceback-docs/docs/html/
>>>>>
>>>>>
>>>> Hi André --
>>>>
>>>> I'm reading your docs now.
>>>>
>>>> When I start into Python with beginners, I'll typically start with:
>>>>
>>>> >>> dir( ) # how will HyperKitty mangle this?
>>>>
>>>
>> Hah hah, look what HyperKitty did:
>>
>>
>> https://mail.python.org/archives/list/edu-sig@python.org/message/C6CF53KBJNLM7CF6QT35VBCCTWBTDNBU/
>>
>> I'd say HyperKitty is not very friendly to the indigenous Python we used
>> to share here.
>>
>>
>>>>
>>>
>>>> showing what's in the namespace, the names Python
>>>> knows when "in" the namespace.
>>>>
>>>> But then the question right away arises: where are
>>>> print, hex, str, dict... all these names Python knows?
>>>>
>>>> Answer (as we all know): __builtins__
>>>>
>>>> So then I do a dir(__builtins__)
>>>>
>>>
>>> I think you mean simply __builtins__, without the dir(). I use
>>> "pretty" from Rich (
>>> https://rich.readthedocs.io/en/latest/introduction.html?highlight=pretty#python-in-the-repl)
>>> so that dicts are nicely formatted.
>>>
>>>
>> Like in this screenshot:
>>
>>
>> https://www.flickr.com/photos/kirbyurner/50905387656/in/album-72157660337424600/
>>
>> You have to feed __builtins__ (not quoted) to dir( ) to dump its contents
>> as
>> a list of strings. That solves the mystery of where quit, range, map,
>> complex,
>> abs and so on and on are coming from. Python knows these names and yet
>> dir( ) -- with no argument -- does not reveal them to be present in the
>> top-level
>> namespace (__main__). I describe __builtins__ as like a "utility belt" of
>> tools
>> around your waist, so close at hand that it's unnecessary to import them.
>>
>> We're expanding out in concentric shells, taking in more and more of
>> what constitutes "Python". I introduce my Five Dimensions (or Layers):
>>
>> 0. Core syntax: keywords and punctuation (including indentation)
>> 1. __builtins__
>> 2. __ribs__ i.e. special names, magic methods, the scaffolding
>> 3. Standard Library (batteries included)
>> 4. 3rd Party ecosystem (from small like friendly-traceback, and rich
>> all the way to giant frameworks like SQLAlchemy and Twisted -- to
>> name some of the early big projects And of course your own RUR-PLE).
>>
>> I tell students the optimum learning curve is not about mastering all
>> of level 0, then moving to level 1 and so on (plodding, methodical,
>> unproductive). No, it's about spiraling, and going a little deeper
>> into each level as we progress. So in the very first lesson I'm likely
>> to:
>>
>> (a) talk about the five levels and
>> (b) dump the contents of __builtins__
>> (c) remark on the "funny look" of __rib__-syntax.
>>
>> I'm giving them a sense of the big picture, and how much there is to
>> know about (e.g. "Python includes about fifty special names but you
>> will use far fewer than that on a regular basis").
>>
>> In dumping the contents of builtins, I'm getting my segue to Exceptions
>> (so much of what's in there are "flags" that might get raised).
>>
>> I speak very metaphorically e.g. how when you're new to an environment
>> you're always bumping up against limits, like a baby. Or you're new to a
>> certain sport and don't really know the rules yet. What's a foul? Can I
>> pick up the ball and just run with it? That depends on the namespace,
>> and the rules. Exceptions are about doing something other than crashing
>> when a rule is broken.
>>
>> The environment pushes back, telling you what went wrong. Python
>> creates such an environment for us the moment we enter the REPL.
>> We're free to play in it, to explore, and understanding the Exceptions
>> are there for our convenience and instruction makes them not scary.
>> Noobs are conscientiously afraid of "breaking things" and a teacher's
>> role includes showing safe ways to explore and gain fluency.
>>
>> From Exceptions, it's but a short step to try except syntax (level 0) and
>> Tracebacks (debugger, diagnostics, IDE features, your enhancements
>> -- level 4).
>>
>> Kirby
>>
>> _______________________________________________
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>> https://mail.python.org/mailman3/lists/edu-sig.python.org/
>> Member address: wes.tur...@gmail.com
>>
>
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