The data in this repository comes from my other repository--ctenopharyngodon-idella, which uses the Fast API to build custom APIs for anyone to use anywhere. Support for GET and POST requests. I personally use Data Ease, which is open source by Feizhi Cloud, for graphical analysis.
This repository contains:
number | item name | details |
---|---|---|
1 | province | Each province contains a university |
2 | dual_class | Each province contains the number of double first-class |
3 | type | School category statistics |
4 | spacial_name | All majors statistics |
5 | score_province | Admissions Statistics |
6 | big_data | Statistics of different big data majors |
7 | big_data_province | Statistics of provincial universities including Big data majors |
8 | big_data_type | Statistics of universities in provinces with big data majors |
9 | big_data_level2 | Big data secondary category statistics |
10 | big_data_level3 | Big data primary category statistics |
11 | big_data_in_dual | Proportion of Big Data in 211/985 |
12 | big_data_in_null | The proportion of big data in ordinary colleges and universities |
13 | artificial_intelligence_in_dual | The proportion of artificial intelligence in 211/985 |
14 | artificial_intelligence_in_null | The proportion of artificial intelligence in ordinary universities |
This project uses python git. Go check them out if you don't have them locally installed.
git clone https://github.com/weiensong/opsariichthys-bidens.git
Creating the virtual environment and activating it.
python -m venv venv && source ./venv/bin/activate
Installing dependencies.
pip install -r requriements.txt
Running in local machine:
python run.py
If you want to run it in docker
python docker_run.py
If you want to build image by yourself.
sudo docker build -t opsariichthys_bidens:lastest .
docker run -d -v "$(pwd):/app" -p 2518:2518 --name opsariichthys_bidens opsariichthys_bidens:lastest
If you want to use curl to access:
curl -X POST -H "Content-Type: application/json" -d '{"key": "item"}' http://127.0.0.1:2518/api
- fastapi — FastAPI framework, high performance, easy to learn, fast to code, ready for production
- dataease — 人人可用的开源数据可视化分析工具
- ctenopharyngodon-idella — Hadoop, MapReduce distributed crawling of all Chinese university data for the handheld college entrance examination. (Hadoop,mapreduce分布式爬取掌上高考的所有中国大学数据)
Feel free to dive in! Open an issue or submit PRs.
Standard Python follows the Python PEP-8 Code of Conduct.
This project exists thanks to all the people who contribute.
GNU General Public License v3.0 © weiensong