Detection Of Learning Obstacles via Risk-aware Interaction Signals
Project description
Doloris
中山大学 2025 年《模式识别》大作业。
组员：许睿林、傅小桐。
Doloris：Detection Of Learning Obstacles via Risk-aware Interaction Signals.
环境配置
可直接运行下方命令安装 Doloris。
pip install doloris
对于项目的开发者而言，请执行下方的指令，便于本地进行开发与调试。
pip install .
安装成功后，执行下列指令，可以得到 Doloris 版本号的输出。
doloris version
使用方式
运行下列命令，启动 Doloris，其中 指明了运行时缓存的存储路径，默认存放在 ~/.doloris/
doloris panel --cache-path <cache path>
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
doloris-0.2.0.tar.gz
(5.4 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file doloris-0.2.0.tar.gz.
File metadata
- Download URL: doloris-0.2.0.tar.gz
- Upload date:
- Size: 5.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.7.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
bd3e1e057bef6876fbb54539c9af7f2fc6a409b29f57680d1ff72178577266e9
|
|
| MD5 |
cdbbfca8b7d6a1fc26ed99876a96a85a
|
|
| BLAKE2b-256 |
4fe76e75909594f6b6ba69480c08c2f203bae69f5403b619ef9eb25b654628dc
|
File details
Details for the file doloris-0.2.0-py3-none-any.whl.
File metadata
- Download URL: doloris-0.2.0-py3-none-any.whl
- Upload date:
- Size: 6.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.7.18
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c599b9658050f167ca757b055f9f70dbe5cef50043ad21ca67f3dfd284ad07b1
|
|
| MD5 |
b4ca82c7825d65d730195ba73fcd34b4
|
|
| BLAKE2b-256 |
ab86140f2145baad6511ce7a466b0d3d23229254b911394cea05ed8e1d35808d
|
