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https://github.com/kfl/staffeli_nt

Staffeli NT Technology
https://github.com/kfl/staffeli_nt

canvas-lms-api hacktoberfest python

Last synced: 5 months ago
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Staffeli NT Technology

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README 

        
# staffeli_nt



Staffeli NT Technology



Getting Started

===============



With Staffeli, we work with local course clones. We aim to keep these

clones compatible with git.



We recommend that you create a local directory ``canvas``,

``absalon``, or similar, for all of you Canvas-related local course

clones.



Obtain your personal Canvas token

---------------------------------

Staffeli needs some initial help to be able to login with your

credentials. You need to [generate a

token](https://guides.instructure.com/m/4214/l/40399-how-do-i-obtain-an-api-access-token-for-an-account)

for Staffeli to use, and save it in your home directory in a file with

the name `.canvas.token`.



**NB!** This is your personal token so **do not** share it with others,

else they can easily impersonate you using a tool like Staffeli.

Unfortunately, to the best of our knowledge, Canvas has no means to

segregate or specialize tokens, so this is really "all or nothing".



Install required libraries

--------------------------



    $ pip3 install -r requirements.txt



Or you can install in a [virtual

environment](https://packaging.python.org/guides/installing-using-pip-and-virtual-environments/#creating-a-virtual-environment):



 1. Create a virtual environment called `env`.



    On macOS and Linux:



        $ python3 -m venv env



    On Windows:



        $ py -m venv env



 2. Activate `env`



    On macOS and Linux:



        $ source env/bin/activate



    On Windows:



        $ .\env\Scripts\activate



 3. Now install the requirements for `staffeli_nt` in `env`



        $ pip3 install -r requirements.txt



Fetch Submissions for an Assignment

-----------------------------------

There are multiple options for fetching submissions.



The general command is `python  download    [flags]`, where

- `` is the path to the directory where `staffeli_nt` is located, i.e. where the files `download.py` and `upload.py` etc. can be found.

- `` is the canvas `course_id` for the course.

- `` is the template file to use when generating the `grade.yml` file for each submission

- `` is a *non-existing* directory, that staffeli will create and store the submissions in.



**Windows**:  

Since `staffeli_nt` is written in `python3`, you will need to invoke it via your `python3` interpreter. 

Example: `python  download    [flags]`



**Fetching all submissions**:  

To fetch **all** submissions from the course with id `12345`, using the template-file `ass1-template.yml` and create a new directory "ass1dir" to store the submissions in:



    $ python  download 12345 ass1-template.yml ass1dir



This will present you with a list of assignments for the course, where you will interactively choose which assignment to fetch.

For each submission, a directory will be created in ``, in which the handed-in files of the submission will be stored, alongside a file `grade.yml` generated form the `` for a TA to fill out during grading of the assignment.

Submission comments, if any, will be downloaded as well, and stored alongside `grade.yml` and the files of the hand-in.



*In case the student hands in a file called `grade.yml` it will be overwritten by staffeli. If the student hands in a file called `submission_comments.txt` and has written submission comments on the submission, the downloaded submission comments will be renamed.*



### Flags

#### Fetching all submissions for a section

What we call "Hold", canvas/absalon calls sections.

To fetch all submissions for an assignment, where the student belongs to a given section, and the `` is `12345`:



    $ python  download 12345 ass1-template.yml ass1dir --select-section



This will present you with a list of assignments for the course, where you will interactively choose which assignment to fetch, followed by a list of sections for you to choose from.



#### Fetching specific submissions (based on kuid)

It is possible to fetch specific submissions based on a list of kuids.

To do this, create a YAML-file with the following format:



``` yaml

TA1:

- kuid1

- kuid2

- kuid3

TA2:

- kuid4

- kuid5

```



To then fetch all submissions for an assignment for a given TA:



    $ python  download  ass1-template.yml ass1dir --select-ta ta_list.yml



where `ta_list.yml` is a YAML-file following the above format.



This will present you with a list of assignments for the course, where you will interactively choose which assignment to fetch, followed by the list of TA's from your `ta_list.yml` file.

Selecting a TA, will fetch submissions from each `kuid` in the file, associated with the chosen TA, i.e. selecting `TA1` will fetch submission from `kuid1`, `kuid2` and `kuid3`.



### Automatically running onlineTA for each submission

In the `template.yml`-file you can add a field:



`onlineTA: https://address.of.onlineTA.dk/grade/assignmentName`



This will (attempt to) run onlineTA for each downloaded submission.



#### Fetching only ungraded submissions (resubs)

It is possile to only fetch submissions that are either ungraded or have a score < 1.0.

Currently this is implemented specifically for the PoP-course and might not be available in the current form in later releases. 

This can be achieved by appending the `--resub` flag to any use of the `download` subcommand.



Upload Feedback and grades

--------------------------



Use `python  upload   [--live] [--step]`.

The default to do a *dry run*, that is **not** to upload anything

unless the `--live` flag is given.



For instance, to review all feedback for submissions in the directory

`ass1` before uploading:



    $ python  upload ass1-template.yml ass1 --step



To upload all feedback for submissions in the directory

`ass1`:



    $ python  upload ass1-template.yml ass1 --live



To upload feedback for a single submission:



    $ python  upload-single     [--live]



To generate `feedback.txt` locally for submissions in the directory `ass1`:



    $ python  upload ass1-template.yml ass1 --write-local



Template format

---------------



A (minimal) template could look like:



```yaml

name: Mini assignment



tasks:

  - overall:

      title: Overall

      points: 6

      rubric: |

        Some default feedback.



        Your code and report are unreadable.



        Wow, that's really clever.

```



### Optional fields



The template files support a few optional fields.



- `passing-points: N`:

Adding this field will have the effect, that the grade posted is `1` if the total sum of points is

greater than or equal to `passing-points`, and `0` otherwise.

- `show-points: BOOL`

Setting show-points to `false` will exclude the `points/grade` from the generated `feedback.txt` files.

Use this, if you do not want the students to see the points-per-task, but only receive an overall grade.



- `onlineTA: ADDR`

Include this field to (attempt to) run onlineTA at address `ADDR` for each submission, when downloading submissions.



### Fully fledged example template

```yaml

name: Mega assignment

passing-points: 42

show-points: false

onlineTA: https://yeah-this-is-not-a-real-address.dk/grade/megaassignment



tasks:

  - megaAssignmentGeneral:

      title: Mega assignment - General comments and adherence to hand-in format requirements

      points: 100

      rubric: |

        [*] You should spell check your assignments before handing them in

        [-] You are using the charset iso-8859-1. Please move to the modern age.

        [-] Your zip-file contains a lot of junk. Please be aware of what you hand in.



  - megaAssignmentTask1:

      title: Task 1

      points: 2

      rubric: |

        [+] Your implementation follows the API

        [-] Your implementation does not follow the API

        [+] Your tests are brilliant

        [-] Your tests are not tests, just print-statements.

            This is equivalent to an exam without an examinator, where you shout

            in a room for half an hour and give yourself the grade 12.



  - megaAssignmentTask2:

      title: Task 2

      points: 2

      rubric: |

        [+] Very good points.

        [+] Very good points. However, I disagree with ...

        [-] I fail to comprehend you answer to this task.



  - megaAssignmentBonusTask:

      title: Bonus tasks that do not give points, or another option for general comments

      rubric: |

        [*] You did extra work! It won't help you though.

```