PMARINA Email Aggregator

What does it do

Given CSV and/or ZIP files, it extracts all CSVs and all unique, valid email addresses from them.

Probably not: I wrote this to work on a small scale (<1000 emails) from a few google forms. Here are some of the main issues with doing so:
- Efficiency: I didn't try to make this a parallelized operation, so that's a big drop in speed.
- Memory: I load all of the files into memory before trying to process them, rather than one at a time. Why? Because otherwise I either need to find the total number of lines in all the files combined, or tqdm doesn't look as nice (the purpose of this was to figure out tqdm/logger).
- Robustness? - I wrote this to parse out a few forms for a university club. The regex provided by email.utils probably wasn't designed to be used the way I'm using it, and there's a good chance my way of doing this will break if your form accepts info/generates CSVs in a different way. You should definitely look through the output to make sure it works as expected before acting on it.

People doing email aggregation on small scales, but who can carefully look through the output to make sure nothing strange appears.

Get Python 3+
pip install --upgrade tqdm loguru dnspython google-api-python-client google-auth-oauthlib
- Do I really need these?
  - Yes, for email-sending & drive file access, Google APIs are important. TQDM & Loguru are necessary for clean outputs. dnspython helps with email validation.
Put all important events in a new file input.txt inside the top level of this repository.
- The format is as follows: (note that # is used as the comment character, but only if it is the first (non-whitespace) character in the line)
  1. Title Line
  2. Description Line
  3. Event Sign-up link (heavily recommend dynamic URLs)
  4. Date & Time: (yyyy.mm.dd hhmm) eg "2021.12.31 2359"
Run the applicable file (python main_weekly.py or python main_reminder.py)