**Blackboard Gradebook Organiser** is a tool for organising a downloaded gradebook with assignment submissions from [Blackboard Learn](https://en.wikipedia.org/wiki/Blackboard_Learn).
The submission files are organised per student, by extracting the student number from the submission file names and creating a directory per student. Any compressed files (.zip, .rar, .7z) are extracted into the student's directory, with any remaining files submitted individually also moved into the student's directory. Student comments from submissions are also extracted into a single text file for convenient access and review.
Additionally, after organising submissions, you can inspect all submitted files to detect duplicated files from different submissions/students by generating and comparing SHA256 hashes. See section [Inspect submissions](#inspect-submissions-mag) for details.
- While running, the script displays on the terminal information and stats about the gradebook submissions and files
### Post-run
- All submission files can be found - organised in directories per student number - in directory *BB_submissions* under the sub-directory named after the gradebook name provided when running the script
- e.g. `python organise_gradebook.py GRADEBOOK_DIR_NAME` creates the directory *GRADEBOOK_DIR_NAME* inside *BB_submissions*
- Each student directory contains the student's extracted and individually submitted files, and the text file generated by Blackboard with the submission (which also contains any comments left by the student)
- All comments found in the gradebook are extracted in a text file in *BB_submissions*, with the gradebook name as prefix
- e.g. *AssignmentX_comments.txt* will be created for gradebook *AssignmentX*
- Compressed files are deleted after successfully extracting and organising the contents
- Compares the generated hashes and finds any duplicate hashes - ignores duplicates if they are by the same student/submission
- Finds all files with a duplicated hash and outputs them to CSV file with the following information: Student ID, file path, file name (without path), SHA256 hash
- Further inspection and filtering needs to be done manually, depending on the submission files
### Usage
- For this feature you also need to install the pandas package
- e.g. for AssignmentX: create *AssignmentX_excluded.csv*, with a column named "exclude_filename" and list the file names
- Note: the directory *csv* is automatically created when you run inspect_submissions.py - you need to create it manually if you want to exclude files before the first run
