# make sure to install the python deps first. Virtual env are recommended here.
# virtualenv -p python3 venv3; source venv3/bin/activate; pip install -r requirements.txt
# Remove "--max_num_files 100" to process the whole dataset (few hours and 50GB of free disk space are required.)
./process_and_train.sh <BreachCompilation path>

INPUT:   BreachCompilation/
         BreachCompilation is organized as:

         - a/          - folder of emails starting with a
         - a/a         - file of emails starting with aa
         - a/b
         - a/d
         - ...
         - z/
         - ...
         - z/y
         - z/z

OUTPUT: - BreachCompilationAnalysis/edit-distance/1.csv
        - BreachCompilationAnalysis/edit-distance/2.csv
        - BreachCompilationAnalysis/edit-distance/3.csv
        [...]
        > cat 1.csv
            1 ||| samsung94 ||| samsung94@
            1 ||| 040384alexej ||| 040384alexey
            1 ||| HoiHalloDoeii14 ||| hoiHalloDoeii14
            1 ||| hoiHalloDoeii14 ||| hoiHalloDoeii13
            1 ||| hoiHalloDoeii13 ||| HoiHalloDoeii13
            1 ||| 8znachnuu ||| 7znachnuu
        EXPLANATION: edit-distance/ contains the passwords pairs sorted by edit distances.
        1.csv contains all pairs with edit distance = 1 (exactly one addition, substitution or deletion).
        2.csv => edit distance = 2, and so on.

        - BreachCompilationAnalysis/reduce-passwords-on-similar-emails/99_per_user.json
        - BreachCompilationAnalysis/reduce-passwords-on-similar-emails/9j_per_user.json
        - BreachCompilationAnalysis/reduce-passwords-on-similar-emails/9a_per_user.json
        [...]
        > cat 96_per_user.json
        {
            "1.0": [
            {
                "edit_distance": [
                    0,
                    1
                ],
                "email": "[email protected]",
                "password": [
                    "090698d",
                    "090698D"
                ]
            },
        {
                "edit_distance": [
                    0,
                    1
                ],
                "email": "[email protected]",
                "password": [
                    "5555555555q",
                    "5555555555Q"
                ]
         }
        EXPLANATION: reduce-passwords-on-similar-emails/ contains files sorted by the first 2 letters of
        the email address. For example [email protected] will be located in 96_per_user.json
        Each file lists all the passwords grouped by user and by edit distance.
        For example, [email protected] had 2 passwords: 090698d and 090698D. The edit distance between them is 1.
        The edit_distance and the password arrays are of the same length, hence, a first 0 in the edit distance array.
        Those files are useful to model how users change passwords over time.
        We can't recover which one was the first password, but a shortest hamiltonian path algorithm is run
        to detect the most probably password ordering for a user. For example:
        hello => hello1 => hell@1 => hell@11 is the shortest path.
        We assume that users are lazy by nature and that they prefer to change their password by the lowest number
        of characters.

python3 run_data_processing.py --breach_compilation_folder <BreachCompilation path> --output_folder ~/BreachCompilationAnalysis