https://github.com/emptyflash/allergeez
Get alerts and see trends for Houston's tree pollen, weed pollen, and mold spores.
https://github.com/emptyflash/allergeez
allergies houston pollen
Last synced: 5 months ago
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Get alerts and see trends for Houston's tree pollen, weed pollen, and mold spores.
- Host: GitHub
- URL: https://github.com/emptyflash/allergeez
- Owner: emptyflash
- Created: 2018-05-19T19:26:59.000Z (almost 8 years ago)
- Default Branch: master
- Last Pushed: 2018-06-15T15:09:24.000Z (almost 8 years ago)
- Last Synced: 2025-03-22T05:13:53.424Z (12 months ago)
- Topics: allergies, houston, pollen
- Language: Python
- Homepage: https://allergeez.me
- Size: 378 KB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 1
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Metadata Files:
- Readme: README.md
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README
# [allergeez](https://allergeez.me)
Created for the Houston Hackathon 2018. Check out our [devpost submission](https://devpost.com/software/allergeez).
This application scrapes the Houston Heatlh Department [Pollen and Mold Page](http://www.houstontx.gov/health/Pollen-Mold/index.html)
and saves it in a database. Whenever the database is updated, notifications will be sent if any allergens are above a user's
configured threshold.
The dashboard displays the most current pollen levels and graphs the last 5 days of data. Users
can choose which allergens they want to see, subscribe to notifications for them, and provide
feedback on how they're feeling.
## Development
### Overview
* Frontend built in Typescript with Angular (lives in `src/`)
* Notifications using [Service Workers and Push Notifications](https://blog.angular-university.io/angular-push-notifications/)
* Scraper written in Python 3 with `BeautifulSoup` and `requests`
* Data is store in a MySQL database and accessed in Python with `PyMySQL`
* API serves data and stores user data with `Flask`
### Getting started
* Install and start MySQL
* The easiest way to do this with local dev is run `./backend/start_mysql_docker.sh` (requires docker)
* Install python dependencies with `pip3 install -r requirements.txt`
* Create the database tables with `python3 backend/db.py`
* Fill the database with the last five days of data with `python backend/scraper_populate.py`
* Install npm dependencies with `npm install`
* Build the frontend with `npm run build`
* Start the backend server in dev mode with `npm run backend`
* For automatic reload of the frontend and backend, run `npm run dev`
* The server will be online at `http://localhost:5000`