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Quercus & Canvas Course Downloader

Download University of Toronto Quercus and Canvas LMS courses, then browse them locally with a Canvas-style interface.

This is an unofficial personal backup tool. It is not affiliated with Instructure, Canvas, Quercus, or the University of Toronto.

Features

  • Sync active and completed courses available to your account
  • Archive Modules, Pages, Announcements, Assignments, Grades, Quizzes, Discussions, and course navigation
  • Download PDFs, presentations, documents, ZIP files, source code, images, and other attachments
  • Discover Canvas files embedded in pages, announcements, assignments, quizzes, and discussions
  • Skip completed downloads and retry missing files
  • Browse downloaded courses through a local Quercus / Canvas-style web interface
  • Preserve links to external tools and video platforms

Quick Start

Requires Python 3.10 or newer.

git clone https://github.com/james123wang5/QuercusCanvasDownloader.git
cd QuercusCanvasDownloader
python3 save_token.py
python3 sync_quercus.py
python3 backend.py

The command above syncs course navigation, pages, assignments, announcements, grades, and other metadata. It does not download every course file, but it is still not a fast "list courses only" command: it visits each accessible course and fetches course details.

To also download files, run:

python3 sync_quercus.py --download-files --workers 1

Open:

http://127.0.0.1:8765

save_token.py stores the token locally in config/local.json. This directory is ignored by Git.

Commands

Sync course navigation, pages, assignments, announcements, grades, and other metadata without downloading every file:

python3 sync_quercus.py

This is metadata-only, not file-download mode. It can still take time because it checks each accessible course.

Quick test with only the first few courses:

python3 sync_quercus.py --limit 3

Sync only one course when you already know the Canvas course ID:

python3 sync_quercus.py --course-id 123456

Use more course workers if the Canvas server and your network are stable:

python3 sync_quercus.py --workers 4

Download files for all accessible courses:

python3 sync_quercus.py --download-files --workers 1

Download one course:

python3 sync_quercus.py --course-id 123456 --download-files

Save a download log:

mkdir -p logs
PYTHONUNBUFFERED=1 python3 sync_quercus.py \
  --download-files \
  --workers 1 \
  2>&1 | tee "logs/download-$(date +%Y%m%d-%H%M%S).log"

Use more workers when the network and Canvas instance are stable:

python3 sync_quercus.py --download-files --workers 4

Check which known files are still missing locally:

python3 tools/missing_downloads.py

Show a compact per-course summary:

python3 tools/course_download_report.py

Show each missing file grouped under its course:

python3 tools/course_download_report.py --details

Show every missing row:

python3 tools/missing_downloads.py --limit 999

Export the missing-file report as a TSV file:

python3 tools/missing_downloads.py --tsv --limit 999 > /tmp/missing-downloads.tsv
open /tmp/missing-downloads.tsv

Only show files that are worth retrying:

python3 tools/missing_downloads.py --category retryable-network --limit 999

The report categories mean:

  • retryable-network: network, DNS, SSL, timeout, reset, or incomplete-transfer failure. Re-running downloads may fix it.
  • permission-or-private: Canvas returned 401 or 403. The token cannot access the file.
  • missing-or-deleted: Canvas or the external site returned 404. The file is probably deleted, expired, or the link is stale.
  • bad-or-nonfile-link: the page looked like a file link but the endpoint is not a downloadable file.
  • not-attempted: the archive knows about the file but no download warning was recorded yet.

Local Data

Downloaded content is stored under:

archive/courses/<course-id-course-name>/

The following local data is excluded from Git:

archive/
config/
logs/
.env

The public repository contains program code only. It does not include personal tokens, downloaded courses, grades, or local logs.

Supported Content

The downloader can store:

  • Course navigation, Modules, and course structure
  • Pages, syllabi, and front pages
  • Announcement and discussion topic content
  • Assignment descriptions, rubrics, and grade information
  • Quiz metadata and descriptions
  • Canvas files and attachments discovered in course content

Some content can only be preserved as links or partial metadata:

  • Piazza, MarkUs, Crowdmark, Gradescope, and other third-party tools
  • YouTube, Zoom, U of T Play, Panopto, SharePoint, and other video services
  • Quiz attempts and complete interactive quiz pages
  • Complete discussion reply threads
  • Deleted, expired, or permission-restricted content

The tool does not bypass Canvas permissions. It can only download content available to the configured token.

Project Structure

sync_quercus.py   Course sync and file discovery
canvas_client.py  Canvas API client and file downloader
save_token.py     Local token configuration
backend.py        Local web server
web/              Local course browser

Privacy and Usage

  • Never publish your Canvas token.
  • Do not commit archive/, config/, logs/, or .env.
  • Course materials may be protected by copyright or course policies. Use this tool for personal backups.
  • Review git status before publishing changes.

中文说明

Quercus / Canvas 课程下载器

把 Canvas LMS / U of T Quercus 课程下载到本地，并通过接近原课程网站的网页界面离线浏览。

非官方个人备份工具，与 Instructure、Canvas、Quercus 或 University of Toronto 无隶属关系。

功能

  • 同步当前账号可访问的 active 和 completed 课程
  • 保存 Modules、Pages、Announcements、Assignments、Grades、Quizzes、Discussions 和课程导航
  • 下载 PDF、PPTX、DOCX、ZIP、代码、图片等课程文件
  • 自动发现页面、公告和作业正文中的 Canvas 文件链接
  • 已下载文件自动跳过，失败文件可以重新运行补下
  • 本地 Quercus / Canvas 风格网页界面
  • 记录外部工具和视频平台入口

快速开始

要求 Python 3.10 或更高版本。

git clone https://github.com/james123wang5/QuercusCanvasDownloader.git
cd QuercusCanvasDownloader
python3 save_token.py
python3 sync_quercus.py
python3 backend.py

上面的命令会同步课程导航、页面、作业、公告、成绩和其他元数据，不会下载所有课程文件。但它不是“只快速列出课程”的命令：它仍然会逐门访问你账号可见的课程并抓取课程详情，所以课程多时会比较慢。

如果要同时下载课程文件，再运行：

python3 sync_quercus.py --download-files --workers 1

浏览器打开：

http://127.0.0.1:8765

save_token.py 会把 token 保存在本机的 config/local.json。该目录已被 Git 忽略。

常用命令

同步课程导航、页面、作业、公告、成绩和其他元数据，不下载所有文件：

python3 sync_quercus.py

这是 metadata-only 模式，不是文件下载模式。但它仍然会检查每门可访问课程，所以不是快速列表模式。

只测试前几门课程：

python3 sync_quercus.py --limit 3

已知 Canvas course ID 时，只同步一门课：

python3 sync_quercus.py --course-id 123456

网络和 Canvas 服务器稳定时，可以增加课程并发：

python3 sync_quercus.py --workers 4

下载所有可访问课程的文件：

python3 sync_quercus.py --download-files --workers 1

只下载一门课程：

python3 sync_quercus.py --course-id 123456 --download-files

保存运行日志：

mkdir -p logs
PYTHONUNBUFFERED=1 python3 sync_quercus.py \
  --download-files \
  --workers 1 \
  2>&1 | tee "logs/download-$(date +%Y%m%d-%H%M%S).log"

网络稳定时可以提高并发数：

python3 sync_quercus.py --download-files --workers 4

查看哪些已识别文件还没有下载到本地：

python3 tools/missing_downloads.py

按课程显示简洁汇总：

python3 tools/course_download_report.py

按课程列出每个缺失文件：

python3 tools/course_download_report.py --details

显示全部缺失记录：

python3 tools/missing_downloads.py --limit 999

导出成 TSV 表格：

python3 tools/missing_downloads.py --tsv --limit 999 > /tmp/missing-downloads.tsv
open /tmp/missing-downloads.tsv

只看值得重试的网络类失败：

python3 tools/missing_downloads.py --category retryable-network --limit 999

分类含义：

  • retryable-network：网络、DNS、SSL、超时、连接重置或下载不完整，重新运行下载可能成功。
  • permission-or-private：Canvas 返回 401 或 403，当前 token 没权限。
  • missing-or-deleted：Canvas 或外部网站返回 404，通常是文件已删除、过期或链接失效。
  • bad-or-nonfile-link：页面里像文件链接，但实际端点不是可下载文件。
  • not-attempted：本地已识别该文件，但还没有记录下载失败原因。

本地数据

下载内容保存在：

archive/courses/<course-id-course-name>/

以下本地数据不会提交到 GitHub：

archive/
config/
logs/
.env

公开仓库只包含程序代码，不包含个人 token、课程文件、成绩或日志。

支持的内容

可以保存：

  • 课程导航、Modules 和课程结构
  • Pages、Syllabus 和 Front Page
  • Announcements 和 Discussion 主题正文
  • Assignments 描述、rubric 和成绩信息
  • Quiz 基本信息和描述
  • Canvas 文件及课程正文中的附件

只能保留链接或部分信息：

  • Piazza、MarkUs、Crowdmark、Gradescope 等第三方工具
  • YouTube、Zoom、U of T Play、Panopto、SharePoint 等视频
  • Quiz 作答记录和完整交互页面
  • Discussion 完整回复线程
  • 已删除、已过期或当前账号无权访问的内容

工具不会绕过 Canvas 权限，只能下载当前 token 可以访问的内容。

项目结构

sync_quercus.py   课程同步与文件发现
canvas_client.py  Canvas API 和文件下载
save_token.py     本地 token 配置
backend.py        本地网页服务器
web/              本地课程浏览界面

隐私与使用

  • 不要公开分享 Canvas token。
  • 不要提交 archive/、config/、logs/ 或 .env。
  • 课程资料可能受版权或课程政策限制，仅用于个人备份。
  • 公开修改前请检查 git status。

About

Download and browse University of Toronto Quercus and Canvas LMS courses offline.

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archivecanvas-downloadercanvas-lmscourse-downloadereducationofflinepythonquercus

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