PySJTU - The Python iSJTU client for Humans.
>>> import pysjtu
>>> c = pysjtu.create_client(username="FeiLin", password="WHISPERS")
>>> chemistry = c.schedule(year=2019, term=0).filter("大学化学")
>>> chemistry[0].teacher_name
['麦亦勇']
>>> calculus_exam = c.exam(year=2019, term=0).filter(course_id="MA248")
>>> calculus_exam[0].date
datetime.date(2019, 11, 6)
And, to persist your session...
>>> import pysjtu
>>> session = pysjtu.Session()
>>> session.login("FeiLin", "WHISPERS")
>>> session.dump("lin_fei.session")
>>> session = pysjtu.Session()
>>> session.load("lin_fei.session")
>>> pysjtu.Client(session).student_id
519027910001
PySJTU allows you to manipulate iSJTU APIs easily.
You don't need to construct queries on your own, or guessing the meaning of poorly named variables (to name a few, kch_id
, rwzxs
) any more.
Now course.name
course.hour_total
is enough!
Main features of PySJTU:
- A friendly API with understandable attribute names.
- Easy session persistence.
- Robust captcha recognition using ResNet.
- 80% iSJTU APIs covered. (Course selection APIs included.)
- Fully type annotated.
- 99% test coverage.
Install with pip:
$ pip install pysjtu[ocr]
You may omit 'ocr' extra dependencies if you don't need the builtin captcha recognizers.
Python 3.9 still doesn't have a prebuilt ONNXRuntime release, so 'ocr' features won't work on it.
(You may still use the JCSSRecognizer which depends on a remote service called JCSS.)
PySJTU requires Python 3.7+.
- HTTPX - A next generation HTTP client for Python.
- marshmallow - An ORM/ODM/framework-agnostic library for converting complex datatypes, such as objects, to and from native Python datatypes.
- ONNX Runtime - A performance-focused complete scoring engine for Open Neural Network Exchange (ONNX) models.
- NumPy - The fundamental package for scientific computing with Python.
- Pillow - The friendly PIL fork.
This project is licensed under GNU General Public License v3.0 - see the LICENSE file for details.
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