This is a Leetcode weekly and biweekly contest rating predictor. The APP is available online at 🔗 lccn.lbao.site
Hopefully, you can get the predicted result within 20-30 minutes after the contest has finished.
- ⚡️ Fast
- The core prediction algorithm is accelerated by a JIT compiler(Numba) which costs around 20 seconds on a two-cores Intel(R) Xeon(R) Platinum 8255C CPU (@ 2.50GHz).
- User's latest rating was cached serval times before predicting which can save a lot of time fetching data.
- 🎯 Accurate
- If there were no massive rejudges(say, everyone's global ranking stays unchanged), the rating difference should be negligible.
- Please note that a normal case is that there would be some misconduct detection, so your global ranking will be slightly higher even if your submissions are not rejudged, which results in a slightly higher rating :)
- 📱 Responsive web page
Tested on phones and tablets.
- 🔗 Chinese introduction on leetcode.cn
- 🔗 refined-leetcode: A Chrome extension for leetcode.cn, created by @XYShaoKang
- APScheduler: background tasks
- Numpy and Numba: core prediction algorithm implementation and acceleration
- FastAPI: restful API
- 🚮
Jinja: HTML templates for server-side rendering
- React: most popular front-end library
- TailwindCSS and DaisyUI: modern CSS framework and its component library
- 🚮
Materialize: responsive front-end framework - Echarts: data visualization
git clone git@github.com:baoliay2008/lccn_predictor.git
cd lccn_predictor
# write your mongodb environment config
cp config.yaml.template config.yaml
vi config.yaml
python3.10 -m virtualenv venv/
source venv/bin/activate
pip3 install -r requirements.txt
python main.py
uvicorn api.entry:app --host 0.0.0.0 --port 55555git clone git@github.com:baoliay2008/lccn_predictor.git
cd lccn_predictor
# write production environment mongodb config
cp config.yaml.template config.yaml
vi config.yaml
# build docker image
docker image build -t lccn_predictor:0.1.1 .
# create docker volume
docker volume create lccn_predictor
# run container
docker run -d -v lccn_predictor:/lccn_predictor -p 55555:55555 --name lp lccn_predictor:0.1.1
docker exec -it lp bash
docker container stop lp
docker container start lp
cd client
# install dependencies
npm install
# change `baseUrl` to your local backend process
vi src/data/constants.js
# if you followed instruction above
# it should be "http://localhost:55555/api/v1"
# local test
npm start
# publish
npm run build
- v0.0.1(2022/11/14)
make this repo public, first release.
- v0.1.1(2023/02/14)
change frontend from server-side rendering(Jinja + Materialize) to client-side rendering(React).
