Dev Env Setup

->Need Python 3 installed w/ pip and virtualenv for dev env and mysql
Install Python 3 w/ pip
MacOS: brew install mysql
pip install virtualenv

->Clone this repo
gh repo clone DePaul-CCR/dsqscreen

->CD into repo

->Create an environment for packages
python3 -m venv ./env

->Activate the environment and install packages source ./env/bin/activate
pip install -r requirements.txt

->Add environment to path if needed
export PYTHONPATH=$PYTHONPATH:~/Github/Depaul_CCR/Screener/env/lib/python3.11/site-packages

-> Run database migrations if exist

-> To start dev server
python3 main.py dev

Dev pipeline:

featurebranch -> PR main -> PR production -> Create release on Github -> autodeploys to render.com

Production:

-> To start production server
gunicorn main:app prod

N.B. For Data Export and DSQ Question Changes:

-If you change the routes please update the route-order "page_flow" tuple in 'utils/back_function.py' so the back button works correctly

• the docs/dsqitems_and_routes_map.txt file, which shows the DSQ item var names mapped to routes, should be updated also.
• dsq_columns in utils/export_columns_util.py are order-specific so will also be misaligned if the order of questions changes. (TODO: make the data export order-agnostic)

-If you change which items / questions are used, you also need to update the dsq_columns in utils/export_columns_util.py +Also, you will need to update the columns in the export sheet if in use: depaulccrdev@gmail.com's "DSQScreen Output" +Manually, you can compare the data frame which holds the responses to the header row in the Google sheet via:

#Debug breakpoint on ~line 22 in utils/export_columns_util.py
import nump as np
gs_arr = np.array(#paste gsheet column headers in here formatted as a list ['x', 'y', 'z'...]
)
np.array(df.columns.to_list()) == gs_arr

-To make changes to question pages there is one partial for all the F/S questions and then the single-question items are less templated so need to be modified directly (dsq/viral.html and short_form/reduction.html)

-The api key for our Google Sheet is accessed at /etc/secrets/<name of json file> in our Render.com environment

-To enable data retention to Google Sheets you must ensure the api key is in place and uncomment these lines in screener_utils.py, short_form_utils.py, and dsq_utils.py:

# df = build_dataframe_for_export(session)
# dump_collected_data_to_sheet(df)