# flotpython exos: pure Python

this repo contains exercises and TPs that [complement the Python MOOC](https://www.fun-mooc.fr/en/cours/python-3-des-fondamentaux-aux-concepts-avances-du-langage/)

excluded are the auto-corrected exercises mentioned in the MOOC
[these are bundled with the main course repo](https://github.com/flotpython/course)

in the present repo we try to gather all the other, generally more informal,
material for **practising pure Python** (for numpy etc. see the other repo
<https://github.com/flotpython/exos-ds>)

## there is no runtime tool here !

also note that, as opposed to the auto-corrected exercises mentioned above,
there is a **deliberate choice to not provide a notebooks infrastructure**  
this is because we want our students to become autonomous, so it means they are
supposed to solve all these problems **on their own laptop**, where they are
expected to have acquired the skills for installing and managing a decent
software stack (typically bash + vscode + python + ipython + jupyter)  
the fact that most of the material is written as a notebook is mostly a
convenience, both for authoring (outputs are up-to-date), and of course in cases
where the starting material is a notebook itself  
if you can really not install anything on your laptop, you can in last resort
use [the emergency resources at the bottom of this page](label-lite-tools)

## contents

the material is organized along these rather vague categories:

* `exos`: short, simple one-shot assignments
* `tps`: more elaborate assignments, with several steps, that let students
  achieve something
* `howtos`: more for reading than for practising, that can be recipes to achieve
  some common tasks

as well as, less interesting probably, some low-order categories like `samples`, `reading`, `quizzes`, etc.

**historical note**: in an older version, this repo contained material about both pure Python and the Data Science tools; it has been split in two to ease its maintenance - github slugs are now `flotpython/exos-python` and `flotpython/exos-ds` respectively

## formats & jupytext

as noted above, most of the contents is written as notebooks; all notebooks are
jupytext-encoded using either `py:percent` or `md:myst` formats  
you will **need to `pip install jupytext`** to be able to read those as notebooks  
also all notebooks have their filename prefix ending in `-nb` to help the
distinction between notebooks and pure Python or pure markdown

(label-autoreload)=
## note on autoreload in ipython or notebooks

if you use IPython or Jupyter on your laptop, make sure to read  
<https://ue12-p24-intro.readthedocs.io/en/main/1-01-installations-nb.html#configuration-de-l-autoreload>

it's in French, but gives you the recipe to get IPython and the notebooks to play along if you're doing module development (otherwise you'll be bitten by the caching of modules)

(label-lite-tools)=
## last resort computing resources

if you really cannot install anything on your laptop, you can use this instead  
this is a best effort, not everything works exactly like on a laptop  

you should first check whether you can effectively save your work; in
particular, keep in mind that the only place where your work is likely to be
saved is .. in the brower itself; so for example using another browser, or *a
fortiori* another computer, will likely make you lose your work

### a browser-based JupyterLab

`````{admonition} browser-hosted Jupyter Lab
:class: seealso dropdown

````{div}
```{jupyterlite}
:kernel: python
:theme: JupyterLab Light
:width: 100%
:height: 90vh
:prompt: click to start a JuptyerLab
:prompt_color: pink

# please be patient ...
print("welcome to Python in the browser")

```
````
`````

### a browser-based REPL

`````{admonition} browser-hosted IPython console
:class: seealso dropdown

````{div}
```{replite}
:kernel: python
:theme: JupyterLab Light
:width: 100%
:height: 90vh
:prompt: click to start a console
:prompt_color: yellow

# please be patient ...
print("welcome to Python in the browser")

```
````
`````