TimeTableTool

This tool reads a Google Spreadsheet and returns an overview of each day, sorted by conference using gspread, Pandas and jinja2.

Prequisites

This tool was used (and intended for) DAGM GCPR | VMV | VCBM 2020. However, it can be adapted to bigger and smaller conference events.

You must have one sheet per conference inside the workbook.

Select a rough time raster for the timetable. Set this raster inside of writer.py:

TIME_RASTER = ["08:30", "09:00", "09:30", "10:00", "10:30", "11:00", "11:30", "12:00", "12:30", "13:00", "13:30",
           "14:00", "14:30", "15:00", "15:30", "16:00", "16:30", "17:00", "17:30", "18:00"]

Select the names for the individual conference days (i.e. weekdays).

CONFERENCE_DAYS = ["Monday", "Tuesday", "Wednesday", "Thursday"]

The layout is set up so each conference consists of multiple "tracks" per day, these tracks themselves consist of individual events (i.e. orals, poster sessions etc.)
The conferences can (and probably will) happen in parallel, this is accounted for. However, a single conference should not have multiple tracks running in parallel. (It could still work, but this scenario is untested.)
The tool can also handle joint events, by having a separate sheet calles "JOINT" for events that are shared between the individual conferences.
For more information on the overall conference organization have a look into the guideline document.

Setting the conference names

Open reader.py to change the conference names. Changing the conference names should be pretty self-explanatory:
```
NAME_sheet = workbook.worksheet("NAME OF GOOGLE WORKSHEET GOES HERE")
```
- propagate NAME to the other variables. Hint: The conferences this tool was made for are called GCPR, VMV and VCBM.

Set the names of the conferences inside writer.py as well:

trackids_NAME = all_sheets["CONF_NAME"]["track_id"].unique().tolist()
tracknames_NAME = all_sheets["CONF_NAME"]["track_name"].unique().tolist()
tracks["CONF_NAME"] = list(zip(trackids_NAME, tracknames_NAME))

etc.

Setup of Google sheet

Set up a worksheet for each conference with these columns (in this order!):

conference	day	timeslot	track_id	track_name	track_start	track_end	track_chair	paper_start	paper_end	paper_id	paper_title	author_name	author_mail	oral_spotlight_poster	discord	youtube	paper	abstract
Conference for this Entry	Weekday	Timeslot in Time Raster	ID for conference track, used as anchor	Name for Track as displayed in timetable	Actual start time for track if start time differs from raster	Actual end time for track if end time differs from raster	Name of track chair or contact person per track	Start time of individual event of a track	End time of individual event of a track	ID of an individual event. For internal use.	Title of the entry	Author name(s) for the entry	Author mail address (for internal use)	Type of event. Can be: `oral`, `spotlight`, `poster`, `paper`, `fast-forward`, `social`	Link to discord Channel per track	Link to Youtube (Live/VOD) per Track	Link to PDF	Abstract (hidden per default)

If individual events belong to the same track, be sure to input the track information (track_id, track_name, track_start etc.) into every row for each event.
The columns day and timeslot have to represent the values given in CONFERENCE_DAYS and TIME_RASTER, respectively.

Usage

Install the necessary requirements via pip:
```
pip3 install --user -r requirements.txt
```
Create a Google Docs API key so this application can access your documents. See this URL on how to create said API key.
Save the file credentials.json from the previous step into ~/.config/gspread/credentials.json. Under Windows systems, place the file under %APPDATA%\gspread\credentials.json.

Note: The gspread folder does not exist automatically once gspread is installed, you have to create it manually. (Refer to the gspread documentation for further info.)

Put the URL to the Google spreadsheet in question into main.py:

SPREADSHEET_URL = "https://docs.google.com/spreadsheets/d/SPREADSHEET_ID"

Run the whole thing: python3 main.py

Acknowledgements

gspread is used for reading the Google spreadsheet.
The information inside the spreadsheet is converted into a Pandas dataframe.
Writing the HTML files is done using the jinja2 templating language.

DAGM-GCPR-VMV-VCBM-2020 / ProgramTool